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i
DETERMINING THE KEY SUCCESS FACTORS OF
TOURISM SMALL AND MEDIUM-SIZED ENTERPRISES (TSMEs)
IN MALAYSIA
By
KALSITINOOR SET
MBA (Mas), BBA (Hons.) (Mas)
Thesis submitted for the degree of Doctor of Philosophy
Newcastle Business School, University of Newcastle, Australia
December, 2013
ii
STATEMENT OF ORIGINALITY
The thesis contains no material which has been accepted for the award of any other degree
or diploma in any university or other tertiary institution and, to the best of my knowledge
and belief, contains no material previously published or written by another person, except
where due references has been made in the text. I give consent to this copy of my thesis,
when deposited in the University Library Auchmuty, being made available for loan and
photocopying subject to the provisions of the Copyright Act 1968.
**Unless an Embargo has been approved for a determined period.
Kalsitinoor Set
iii
ABSTRACT
This thesis investigates the underlying success factors of tourism small- and medium-sized
enterprises (TSMEs) in Malaysia. Tourism has emerged as one of the world’s major
industries with significant changes in the structure and operation of the tourism industry
worldwide. The global transition to tourism-focused economies, the emergence of new
destinations, and increasing demands for differentiated tourism products and services have
engendered the need for TSMEs to develop strategies to become competitive in the
changing global economy. Despite the efforts, TSMEs continue to face challenges that
impede successful tourism development in destination countries, thus slowing gains that
can emerge from TSMEs activities.
As one of the most popular destinations in the world, the Malaysian government has taken
a strategic approach to developing the performance of its tourism industry. Currently,
tourism has become the second largest contributor to gross domestic product and a major
contributor to foreign exchange earnings in the country. Given this, the Malaysian
government has made concerted efforts to spur the tourism industry through empowering
and supporting TSMEs. Understanding the key success factors of TSMEs is therefore
pertinent.
To achieve this objective, this study examines the operations and identifies key success
factors of TSMEs in Malaysia based on Resource-Based View (RBV) theoretic framework.
A structured questionnaire was administered to 346 Malaysian tourism entrepreneurs to
iv
elicit information on their managerial characteristics and performance. The descriptive and
inferential analyses were conducted using the SPSS 18 and AMOS 18 statistical packages.
The empirical findings from this research are summarised. First, the motivation of tourism
entrepreneurs to enter the industry in Malaysia is driven by certain socio-economic and
demographic characteristics. Empirical results indicate that there exists a positive
association between age and entrepreneurial motivation. Second, tourism entrepreneurs in
Malaysia perceive management practices of business planning, business alliances,
motivation and government support as key factors for sustaining TSME business
performance. Third, there is strong empirical evidence to indicate that a causal relationship
exists between management practices and TSME performance in Malaysia. That, the key
success factors of business planning, tourism entrepreneurial motivation and government
assistance programmes have had a strong positive effect on the performance of TSMEs in
Malaysia.
This study provides strong empirical evidence to indicate that to improve the performance
of TSMEs there is the need to enhance the socio-economic and demographic characteristics
of managers as well as continue to maintain government assistance programmes to TSMEs.
This could be achieved through developing effective government policies and creating
greater awareness of assistance programmes offered by the government, improve efficacy
of public and private institutions that support TSMEs, and encouraging further training and
exposure of managers to advances in entrepreneurial skill development in Malaysia.
v
For my beloved husband and children
Ismadi Ismail
Julia Ismadi
Jasmine Ismadi
Johan Ismadi
With Love and Respect
My Late Parents - Kalsom Dohat and Set Sani
Parents in Law –Norliah Hussin and Ismail Jejaka
vi
ACKNOWLEDGEMENTS
Al-hamdu lillaahi Rabbil-‘Aalamin – ‘All praise unto Allah, the sustenance of the universe,
the most gracious’. Because of Him I managed to complete this study and He sent some
wonderful people to help me complete this challenging journey.
I sincerely thank and am deeply grateful to my supervisors, Professor Amir Mahmood and
Dr. Frank Agbola, for their direction, guidance and endless support. Their wide-reaching
knowledge, patience and invaluable advice helped considerably over the course of my PhD
journey. I am extremely grateful to have both of you as my supervisors.
I am particularly indebted to University Malaysia Terengganu (UMT) and the Ministry of
Higher Education (MOHE) for giving me the opportunity and supporting me financially to
do my PhD at the University of Newcastle. I would also like to thank all the members of
staff at the University of Newcastle for the resource support and administrative assistance.
Last but definitely not the least, I am grateful to my beloved husband and best friend,
Ismadi Ismail, for the unrelenting support he has afforded me, and for being there for me
through thick and thin. Thanks also to my gorgeous daughters, Julia and Jasmine, for the
laughter. To my family-in-law, thank you and much appreciation for your help and your
good care looking after Julia and Jasmine while I was doing my thesis. Also to my
supportive family members: thanks for the prayers and unconditional love and to my late
parents for the inspiration. Thanks are also given to my friends for their moral support and
encouragement throughout my studies. It is only Allah that can repay all your kindness.
THANK YOU.
vii
TABLE OF CONTENTS
TITLE PAGE ..........................................................................................................................i
STATEMENT OF ORIGINALITY ....................................................................................... ii
ABSTRACT .......................................................................................................................... iii
ACKNOWLEDGEMENTS .................................................................................................. vi
TABLE OF CONTENTS ..................................................................................................... vii
LIST OF FIGURES .............................................................................................................. xv
LIST OF TABLES ............................................................................................................. xvii
LIST OF ABBREVIATIONS ............................................................................................... xx
CHAPTER ONE: INTRODUCTION ................................................................................. 1
1.1 Background of the Study .................................................................................................. 1
1.2 Problem Statement ............................................................................................................ 5
1.3 Research Questions ........................................................................................................... 7
1.4 Objectives of the thesis ..................................................................................................... 8
1.5 Methodology ..................................................................................................................... 8
1.6 Organisation of the Thesis .............................................................................................. 10
CHAPTER TWO: THE POLITICAL ECONOMY OF MALAYSIA AND TSMEs ... 12
2.1 Introduction ..................................................................................................................... 12
2.2 Geography, Population and Culture of Malaysia ............................................................ 12
2.2.1 Malaysian Regions .................................................................................................. 17
2.2.1.1 Northern Region ........................................................................................................... 17
2.2.1.2 Central Region .............................................................................................................. 18
2.2.1.3 Southern Region ........................................................................................................... 19
2.2.1.4 East Coast Region ......................................................................................................... 20
2.2.1.5 Sabah, Sarawak and Labuan (East Malaysia) ............................................................... 21
2.3 Stages of Economic Development in Malaysia .............................................................. 22
2.3.1 Malaysia’s Economic Status, 1957-1959 ................................................................ 22
viii
2.3.2 Malaysia’s Economic Status, 1960s to 1980s ......................................................... 23
2.3.3 Malaysia’s Economic Status, 1990s ....................................................................... 26
2.3.4 Malaysia’s Current Economic Status, 2000s .......................................................... 27
2.4 Tourism Organisation in Malaysia .................................................................................. 30
2.4.1 The National Tourism Organisation ....................................................................... 30
2.4.2 State Tourism Organisations ................................................................................... 35
2.4.3 Local Tourism Organisation ................................................................................... 37
2.5 Tourism Policy Planning in Malaysia ............................................................................. 38
2.5.1 The First Malaysia Plan (1966–1970) ..................................................................... 38
2.5.2 The Second Malaysia Plan (1971-1975) ................................................................. 39
2.5.3 The Third Malaysia Plan (1976-1980) .................................................................... 41
2.5.4 The Fourth Malaysia Plan (1981-1985) .................................................................. 43
2.5.5 The Fifth Malaysia Plan (1986-1990) ..................................................................... 44
2.5.6 The Sixth Malaysia Plan (1991-1995) .................................................................... 45
2.5.7 The Seventh Malaysia Plan (1996-2000) ................................................................ 47
2.5.8 The Eighth Malaysia Plan (2001-2005) .................................................................. 49
2.5.9 The Ninth Malaysia Plan (2006-2010) ................................................................... 51
2.5.10 The Tenth Malaysia Plan (2011-2015) ................................................................. 53
2.6 Tourism Industry Performance in Malaysia ................................................................... 56
2.7 TSMEs in Malaysia ......................................................................................................... 59
2.8 Concluding Remarks ....................................................................................................... 65
CHAPTER THREE: LITERATURE REVIEW .............................................................. 67
3.1 Introduction ..................................................................................................................... 67
3.2 Definition of SMEs ......................................................................................................... 68
3.3 Contributions of TSMEs ................................................................................................. 71
3.3.1 Employment Creation ............................................................................................. 71
3.3.2 Economic Growth and Development to Tourism Country ..................................... 71
3.3.3 Diversification on Tourism Products ...................................................................... 72
3.4 TSMEs Challenges .......................................................................................................... 73
ix
3.4.1 High Labour Turnover ............................................................................................ 73
3.4.2 Shortage of Financial Resources ............................................................................. 74
3.4.3 Business Failure Rate .............................................................................................. 74
3.4.4 Limited Business Skills ........................................................................................... 75
3.4.5 Lifestyle Entrepreneur............................................................................................. 76
3.4.6 Supply Dominated by Family Business .................................................................. 76
3.5 Theoretical Foundations .................................................................................................. 78
3.5.1 Resource-based Theory ........................................................................................... 78
3.5.2 Theories on Entrepreneurship ................................................................................. 82
3.5.2.1 Entrepreneurship from an Economic Perspective ......................................................... 82
3.5.2.2 Entrepreneurship from the Psychological Perspective .................................................. 85
3.5.2.3 Entrepreneurship from the Sociological Perspective .................................................... 87
35.2.4 Entrepreneurship from the Tourism Perspective ........................................................... 89
3.6 Factors Affecting the Performance of TSMEs ................................................................ 92
3.6.1 Internal Factors ....................................................................................................... 92
3.6.1.1 Socio-economic Characteristics .................................................................................... 92
3.6.1.2 Business Skills .............................................................................................................. 98
3.6.1.3 Business Planning ......................................................................................................... 99
3.6.1.4 An Adoption of Internet .............................................................................................. 100
3.6.1.5 Business Alliance ........................................................................................................ 103
3.6.2 External Factors .................................................................................................... 104
3.6.2.1 Government Assistance Programmes ......................................................................... 104
3.6.2.2 Technology ................................................................................................................. 106
3.6.2.3 Global Event ............................................................................................................... 107
3.6.2.4 Consumer Behaviour .................................................................................................. 107
3.7 The Conceptual Framework of the Factors to Influence the Success of TSMEs ......... 109
3.8 Limitation of Previous Studies ...................................................................................... 111
3.9 Concluding Remarks ..................................................................................................... 112
CHAPTER FOUR: STUDY METHODOLOGY ........................................................... 115
4.1 Introduction ................................................................................................................... 115
x
4.2 Internal Resource Factors and TSME Success – the Critical Linkages ........................ 115
4.3 Operationalisation of Variables and Research Hypotheses .......................................... 118
4.3.1 Socio-economic Characteristics ............................................................................ 118
4.3.1.1 Age of the Owner-Manager ........................................................................................ 119
4.3.1.2 Gender ......................................................................................................................... 120
4.3.1.3 Education Level .......................................................................................................... 121
4.3.1.4 Ethnic group ................................................................................................................ 122
4.3.1.5 Family Business Background ..................................................................................... 124
4.3.1.6 Working Experience ................................................................................................... 125
4.3.2 Tourism Entrepreneur Motivation ........................................................................ 126
4.3.3 Business Planning ................................................................................................. 128
4.3.4 Business Alliance .................................................................................................. 130
4.3.5 Adoption on Internet ............................................................................................. 131
4.3.6 Government Assistance Programmes ................................................................... 133
4.3.7 TSMEs Performance ............................................................................................. 135
4.4 Data Sources and Description ....................................................................................... 139
4.4.1 Survey Area .......................................................................................................... 140
4.4.2 Population and Sampling Frame ........................................................................... 141
4.4.3 Sampling Method and Sample Size ...................................................................... 143
4.4.4.1 Personally-Administered Questionnaire Approach .................................................... 145
4.4.4.2 Data Collection Procedure .......................................................................................... 145
4.5 Statistical Techniques and Data Analysis ..................................................................... 146
4.5.1 Validity and Reliability of a Construct ................................................................. 147
4.5.1.1 Content Validity .......................................................................................................... 147
4.5.1.2 Constructs Validity ..................................................................................................... 147
4.5.1.3 Convergent Validity .................................................................................................... 148
4.5.1.4 Discriminant Validity ................................................................................................. 148
4.5.1.5 Constructs Reliability ................................................................................................. 149
4.5.2 Descriptive and Inferential Analyses .................................................................... 149
4.5.3 Multivariate Analysis ............................................................................................ 150
4.5.4 Data Analysis Procedure for SEM ........................................................................ 151
xi
4.5.4.1 Measurement Model Procedures ................................................................................. 151
4.5.4.2 Structural Model Procedures ....................................................................................... 157
4.6 Concluding Remarks ..................................................................................................... 158
CHAPTER FIVE: AN EMPIRICAL INVESTIGATION ON THE
CHARACTERISTICS OF TSMEs AND MANAGEMENT PRACTICES OF
TOURISM ENTREPRENEURS IN MALAYSIA ................................................... 159
5.1 Introduction ................................................................................................................... 159
5.2 Structure of TSMEs in Malaysia ................................................................................... 160
5.2.1 Type of TSMEs’ Businesses ................................................................................. 160
5.2.2 TSMEs Firm Size Structure .................................................................................. 164
5.2.3 TSMEs Ownership Structure ................................................................................ 165
5.2.4 TSMEs Firm Age Structure .................................................................................. 168
5.3 Tourism Entrepreneur Characteristics in Malaysia ....................................................... 171
5.3.1 Age of Tourism Entrepreneur ............................................................................... 171
5.3.2 Gender ................................................................................................................... 175
5.3.3 Level of Education ................................................................................................ 178
5.3.4 Ethnic Group ......................................................................................................... 181
5.3.5 Family Business Background ............................................................................... 184
5.3.6 Working Experience ............................................................................................. 186
5.3.7 Motivation to Start a Business .............................................................................. 189
5.4 Management Practices of TSMEs in Malaysia ............................................................. 191
5.4.1 Business Planning ................................................................................................. 191
5.4.2 Business Alliance .................................................................................................. 192
5.4.3 Adoption of Internet .............................................................................................. 194
5.4.4 Awarenes and Use of Government Assistance Programmes ............................... 196
5.5 Concluding Remarks ..................................................................................................... 198
xii
CHAPTER SIX: EMPIRICAL ANALYSIS OF CAUSAL RELATIONSHIPS:
TSMEs MANAGEMENT PRACTICES AND PERFORMANCE ........................ 200
6.1 Introduction ................................................................................................................... 200
6.2 Confirmatory Factor Analysis of Tourism Entrepreneur’s Motivation and TSMEs’
Management Practices .................................................................................................. 201
6.2.1 Tourism Entrepreneurs’Motivation ...................................................................... 201
6.2.2 Business Planning ................................................................................................. 203
6.2.3 Business Alliance .................................................................................................. 205
6.2.4 Adoption of Internet .............................................................................................. 208
6.2.5 Government Assistance Programmes ................................................................... 210
6.2.6 Business Performance ........................................................................................... 211
6.3 Full Measurement Model .............................................................................................. 213
6.4 Validity and Reliability of Constructs .......................................................................... 217
6.4.1 Construct Validity ................................................................................................. 217
6.4.1.1 Convergent Validity .................................................................................................... 217
6.4.1.2 Discriminant Validity ................................................................................................. 218
6.4.2 Reliability .............................................................................................................. 218
6.5 Structural Model and Hypotheses’ Testing ................................................................... 219
6.6 Discussion of the Empirical Results ............................................................................. 224
6.6.1 Relationship between Socio-economic Factors towards Tourism Entrepreneur’s
Motivation ........................................................................................................... 225
6.6.2 Relationship between Tourism Entrepreneurs’ Motivation and Business Planning
............................................................................................................................. 229
6.6.3 Relationship between Tourism Entrepreneurs’ Motivation and Business Alliances
............................................................................................................................. 230
6.6.4 Relationship between Tourism Entrepreneurs’ Motivation and TSMEs’
Performance ........................................................................................................ 231
6.6.5 Relationship between Tourism Entrepreneurs’ Motivation and Internet Adoption
............................................................................................................................. 232
xiii
6.6.6 Relationship between Tourism Entrepreneurs’ Motivation and Government
Assistance Programmes ...................................................................................... 233
6.6.7 Relationship between Business Planning and TSMEs Performance .................... 234
6.6.8 Relationship between Business Alliance and TSMEs’ Performance ................... 234
6.6.9 Relationship between Internet Adoption and TSMEs’ Performance .................... 235
6.6.10 Relationship between Government Assistance Programmes and TSMEs’
Performance ........................................................................................................ 236
6.7 Concluding Remarks ..................................................................................................... 237
CHAPTER SEVEN: SUMMARY, CONCLUSSIONS AND IMPLICATIONS OF
THE FINDINGS .......................................................................................................... 238
7.1 Summary ....................................................................................................................... 238
7.2 Conclusions ................................................................................................................... 241
7.2.1 An Evaluation on the Impact of Government Policy on TSMEs in Malaysia ...... 241
7.2.2 An Appraisal of the Relationship Between Socio-Economic Characteristics and
Tourism Entrepreneurs’ Motivation ................................................................... 242
7.2.3 An Evaluation on the Tourism Entrepreneurs’ Perception on the Importance of
Management Practices on TSMEs’ Performance ............................................... 243
7.2.4 An Assessment on the Causal Relationships between TSMEs’ Management
Practices and Firm Performance in Malaysia ..................................................... 244
7.2.5 The Key Success Factors of TSMEs in Malaysia ................................................. 246
7.3 Policy Implications ....................................................................................................... 247
7.3.1 Managerial Implications ....................................................................................... 247
7.3.2 Implications for Policy Makers ............................................................................. 250
7.4 Suggestions for Future Research .................................................................................. 252
REFERENCES ................................................................................................................... 255
APPENDIX 2.1 ................................................................................................................... 293
APPENDIX 4.1 ................................................................................................................... 295
APPENDIX 4.2 ................................................................................................................... 297
xiv
APPENDIX 5.1 ................................................................................................................... 305
APPENDIX 5.2 ................................................................................................................... 306
APPENDIX 5.3 ................................................................................................................... 307
APPENDIX 5.4 ................................................................................................................... 308
APPENDIX 5.5 ................................................................................................................... 310
APPENDIX 5.6 ................................................................................................................... 311
APPENDIX 5.7 ................................................................................................................... 312
APPENDIX 5.8 ................................................................................................................... 313
APPENDIX 5.9 ................................................................................................................... 314
APPENDIX 5.10 ................................................................................................................. 315
APPENDIX 5.11 ................................................................................................................. 316
APPENDIX 5.12 ................................................................................................................. 317
APPENDIX 5.13 ................................................................................................................. 319
APPENDIX 5.14 ................................................................................................................. 320
APPENDIX 5.15 ................................................................................................................. 321
APPENDIX 5.16 ................................................................................................................. 322
APPENDIX 5.17 ................................................................................................................. 323
APPENDIX 5.18 ................................................................................................................. 324
APPENDIX 5.19 ................................................................................................................. 326
APPENDIX 5.20 ................................................................................................................. 327
APPENDIX 5.21 ................................................................................................................. 329
APPENDIX 5.22 ................................................................................................................. 330
xv
LIST OF FIGURES
Figure 1.1: Thesis Outline .................................................................................................... 11
Figure 2.1: Map of Malaysia ................................................................................................ 13
Figure 2.2: The Development of MOTOUR ........................................................................ 32
Figure 2.3: Government Departments in Malaysia's Tourism Industry Development ........ 33
Figure 3.1: Factors Affecting SMEs' Success .................................................................... 111
Figure 4.1: The Proposed Conceptual Framework ............................................................ 117
Figure 5.1a: TSMEs by Type of Family Business and Type of Ownership ...................... 165
Figure 5.1b: TSMEs by Type of Non-Family Business and Types of Ownership ............ 166
Figure 5.2a: TSMEs by Travel Agency, Tour Operator and Tourism Guide Services and
Business Year of Establishments ..................................................................... 169
Figure 5.2b: TSMEs by Accommodation Services and Business Year of Establishments 169
Figure 5.3: Tourism Entrepreneurs by Location and Family Business Background..........182
Figure 6.1: Standardised Parameters Estimated in One-Factor Congeneric Model for
Tourism Entrepreneurs’ Motivation Items ....................................................... 203
Figure 6.2: Standardised Parameters Estimated in One-Factor Congeneric of Business
Planning’s Items ............................................................................................... 205
Figure 6.3: Standardised Parameters Estimated in One-Factor Congeneric Model for
Business Alliance’s Items ................................................................................ 207
Figure 6.4: Standardised Parameters Estimated in One-Factor Congeneric Models for the
Adoption on Internet’s Items ........................................................................... 209
Figure 6.5: Standardised Parameters Estimated in One-Factor Congeneric Model for
Government Assistance Programmes’ Items ................................................... 211
xvi
Figure 6.6: Standardised Parameters estimated in One-Factor Congeneric Model for
TSMEs’Performance ........................................................................................ 212
Figure 6.7: Full Measurement Model for Determining Key Success Factors Affecting
TSMEs’ Performance in Malaysia ................................................................... 216
Figure 6.8: AMOS Model Specification for Determining Key Success Factors of TSMEs in
Malaysia ........................................................................................................... 221
Figure 6.9: Results of Path Analysis of Determining Key Success Factors of TSMEs in
Malaysia ........................................................................................................... 222
xvii
LIST OF TABLES
Table 2.1: Key Natural Resources Attractions in Malaysia ................................................. 21
Table 2.2: Key Economic Indicators of Malaysian Economy, 2009-2011 .......................... 29
Table 2.3: Collaboration with Other Ministry on Tourism Programmes ............................. 34
Table 2.4: Courses Programme Provided by MOTOUR ..................................................... 35
Table 2.5: List of Some Key City Excitement Attractions in Malaysia .............................. 36
Table 2.6: Festivals and Events in Malaysia ........................................................................ 37
Table 2.7: Malaysia's Tourism Specific Economic Planning and Initiatives, 1965-2015 ... 55
Table 2.8: International Tourist Arrivals to Southeast Asia, 1967 and 2011....................... 57
Table 2.9: Tourist Arrivals into Malaysia by Country of Origin, 1980 - 2011 .................... 59
Table 2.10: Key Indicators of SMEs in Malaysia, 2010 ...................................................... 60
Table 2.11: Distribution of SMEs by Sectors, 2005 and 2010 ............................................ 61
Table 2.12: Distribution of TSMEs, 2010 ........................................................................... 63
Table 2.13: Key Performance Indicators of TSMEs, 2010 .................................................. 64
Table 2.14: Distribution of TSMEs by Size, 2003 and 2010 ............................................... 65
Table 3.1: Factors Influencing Growth in SMEs ............................................................... 110
Table 4.1: Measurement Items for Tourism Entrepreneur’s Motivation ........................... 128
Table 4.2: Operational Variables for Importance of Business Planning............................ 129
Table 4.3: Operational Variables for Importance of Business Alliances ........................... 131
Table 4.4: Operational Variables for an Adoption on Internet .......................................... 133
Table 4.5: Operational Variables of Government Assistance Programmes ....................... 135
Table 4.6: Operational Variables of TSMEs Performance ................................................ 138
xviii
Table 4.7: Summary of Research Questions, Research Objectives and Hypotheses of the
Study ................................................................................................................ 138
Table 4.8: Number of Tourist Arrival, 2009 ...................................................................... 140
Table 4.9: Index Category and the Level of Acceptance ................................................... 153
Table 5.1: Distribution of TSMEs by Location and Type of Business .............................. 161
Table 5.2: Distribution of Firm Size by Location .............................................................. 164
Table 5.3: Distribution of TSMEs by Age of Tourism Entrepreneur by Location ............ 172
Table 5.4: ANOVA Results of Hypothesis H1a Relating Tourism Entrepreneur’s Age and
Motivation ........................................................................................................ 175
Table 5.5: Distribution of Tourism Entrepreneurs by Location and Gender ..................... 176
Table 5.6: T-test Results of Hypothesis H1b Relating Gender and Tourism .................... 178
Table 5.7: Distribution of TSMEs by Education Background and Location ..................... 179
Table 5.8: ANOVA Results of Hypothesis H1c Relating Education Level and Tourism
Entrepreneur’s Motivation ............................................................................... 181
Table 5.9: Tourism Entrepreneurs by Location and Ethnic Group .................................... 181
Table 5.10: ANOVA Results on Hypothesis H1d Relating Ethnic Group and Tourism
Entrepreneur’s Motivation ............................................................................... 183
Table 5.11: T-test Results of Hypothesis H1e Relating Family Business Background and
Tourism Entrepreneur’s Motivation ................................................................ 186
Table 5.12: Tourism Entrepreneurs by Location and Working Experience ...................... 187
Table 5.13: Tourism Entrepreneurs by Location and Working Experience ...................... 188
Table 5.14: T-test Results of Hypothesis H1f Relating Working Experience and Tourism
Entrepreneur’s Motivation ............................................................................... 189
xix
Table 5.15: Tourism Entrepreneurs' Motivation to Start a Business ................................. 190
Table 5.16: TSMEs and Business Planning ....................................................................... 191
Table 5.17: Business Alliance Activity of TSMEs in Malaysia ........................................ 193
Table 5.18: Distribution of TSMEs Based on Period of Starting to Use the Internet ........ 194
Table 5.19: The Internet Adoption Among TSMEs in Malaysia ....................................... 196
Table 5.20: Level of Awareness and Use on the Government Assistance Programmes ... 197
Table 6.1: Mean and Standard Deviation Values of Entrepreneur's Motivation’s Items .. 202
Table 6.2: Mean and Standard Deviation Values of Business Planning’s Items ............... 204
Table 6.3: Mean and Standard Deviation Values of Business Alliance’s Items................ 206
Table 6.4: Mean and Standard Deviation Values of an Adoption of Internet’s Items ....... 208
Table 6.5: Mean and Standard Deviation Values of Government Assistance Programmes’
Items ................................................................................................................. 210
Table 6.6: Mean and Standard Deviation Values of Business Performance’s Items ......... 212
Table 6.7: Confirmatory Factor Analysis of Full Measurement Model ............................ 213
Table 6.8: Discriminant Validity Test ............................................................................... 218
Table 6.9: Reliability Analyses .......................................................................................... 219
Table 6.10: Results of Hypotheses Testing ........................................................................ 223
Table 6.11: Summary of Research Questions and Key Findings ...................................... 224
xx
LIST OF ABBREVIATIONS
ATV All Terrain Vehicle
AVE Average Variance Extracted
BNM Bank Negara Malaysia
CFA Confirmatory Factor Analysis
CFI Comparative Fit Index
DOS Department of Statistics, Malaysia
EFA Exploratory Factor Analysis
GDP Gross Domestics Product
GFI Goodness-of-fit index
HRM Human Resource Management
ICT Information and Communication Technology
KLIA Kuala Lumpur International Airport
KMO Kaiser-Meyer-Oklin
KSF Key Success Factors
LCCT Low Cost Carrier Terminal
MAS Malaysia Airlines System
MECD Ministry of Entrepreneur and Cooperative Development
MICE Meeting, Incentives Convention and Exhibition
MITI Ministry of Trade and Industry
MLVK National Vocational Training Council
MOCAT Ministry of Arts, Culture and Tourism
MOTOUR Ministry of Tourism Malaysia
MPTB Malaysian Tourism Promotion Board
MRS Manufacturing Related Services
NERP National Economic Recovery Plan
NFI Normed Fit Index
xxi
NOSS National Occupational Skill Standards
NSDC National SME Development Council
NTHRDC National Tourism Human Resource Development Counsil
OECD Organisation of Economic co-Operation and Development
PAF Principal Axis Factoring
PWTC Putra World Trade Centre
RBV Resource Based View
RM Ringgit Malaysia
RMSEA Root Mean Square Error of Approximation
SARS Severe Acute Respiratory Syndrome
SEM Structural Equation Modelling
SFL Satisfactory Factor Loading
SMEs Small and Medium Sized of Enterprises
SRMR Standardised Root Mean Square Residual
STACD State Tourism Action Council Department
TDC Tourist Development Corporation
TLI Tucker Lewis Index
TSA Tourism Satellite Account
TSMEs Tourism Small and Medium Sized of Enterprises
UK United Kingdom
UNWTO World Tourism Organisation
VMY Visit Malaysia Year
1
CHAPTER ONE
INTRODUCTION
1.1 Background of the Study
Tourism is one of the fastest growing sectors of the world economy, an international
and global phenomenon that is continuously changing. Globally, travel and tourism
industries employ nearly 240 million people and create 10 per cent of the world’s gross
domestic product (GDP) (World Tourism Organisation, 2013). Recent years have seen
rapid growth in travel and tourism. Since the beginning of the new millennium, the
industry has witnessed the growth of the leisure society and people have continued to
value vacations, holidays and travel for cultural experience. In light of global changes,
particularly global warming, there is an emerging trend in the tourism industry for
tourists to demand environmentally friendly holidays (Dodds & Butler, 2010; Jovicic,
2011; Krippendorf, 1987). Further, with the rising number of low-cost air carriers
around the world, the number of younger tourists and travellers has also increased
(Abdullah, Ahmad & Alam, 2007; Musa & Ndawayo, 2011). In the context of this shift
and the corresponding demand for differentiated products, the tourism industry is
becoming increasingly globally competitive.
Globalisation and information technology have allowed cheaper and easier access to
information about places to travel and created greater opportunities and choices for
tourists. At the same time, the importance of TSMEs has been widely recognised in
light of the significant changes in global tourist consumption, and the increase of
differentiated and niche tourism products (Ateljevic, 2009; Buhalis, 1998; Getz &
Carlsen, 2005; Page, Forer & Lawton, 1999).. The implication of these changes
2
increases the range of tourism products and TSMEs’ business opportunities, which
depend on the creative and innovative capacity of individual entrepreneurs to identify
and take advantage of the changing landscape (Ateljevic & Doorne, 2000; Strobl &
Peters, 2013).
However, a major challenge for many tourism-focused countries is their exposure to
computerised information and reservation systems, which have made firms operating in
such countries increasingly fragile to global competition. Terrorism is another challenge
faced by TSMEs. The attack on the United States (more commonly known as
September 11), and the more recent bombings in countries such as Indonesia and India
that purposely target Western tourists have made such travel destinations great deal less
attractive to tourists.
These incidents have exacerbated the lingering challenges of the tourism industry and
its firms. Rigid security measures for air transportation and border crossing, as well as
the introduction of new security policies in the airline industry, have been introduced
due to terrorist attacks and threats. Governments around the world have also tightened
their security on the domestic front thus making travelling a lot less attractive to the
general public. Travel warnings to certain targeted destinations on a country’s websites
have also discouraged potential tourists from travelling to such destinations.
Further, the tourism industry is inextricably bound to nature and the environment.
Unexpected natural disasters can lead to devastating tragedies. For example, the Boxing
Day Tsunami on 26 December, 2004 in South and South East Asia, the earthquake in
New Zealand on 21 February, 2011 and most recently, the worst earthquake and
3
tsunami on record that hit Japan on 11 March, 2011 led to substantial damages to the
infrastructure of these countries, and subsequently had a severely damaging effect on
tourism activities. For example, the recent tsunami caused Japan to lose 50 per cent of
its international arrivals and 24 per cent of its demand for hotel rooms (World Travel
and Tourism Council, 2011).
In Malaysia, the Asian financial crisis of 1997, the Iraq War and the outbreak of Severe
Acute Respiratory Syndrome (SARS) have adversely affected the performance of its
tourism industry. Malaysia faced an 80 per cent drop in tourist arrivals from SARS
affected countries - China, Hong Kong, Singapore, Thailand, Japan, Taiwan and
Vietnam (Nathan, 2003).
These challenges have created more intense competition among firms operating in the
tourism industry in countries around the world. The management and operations of
tourism firms, which are primarily SMEs, has changed quite dramatically to ensure
survival in the tourism industry (Morrison, Carlsen & Weber, 2010; Morrison &
Teixeira, 2004; Thomas et al., 2011; Wanhill, 2000). Further, the performance of
TSMEs is critical, especially during the start-up phase (Hall, 1995) where the survival
rate for new SMEs, regardless of the industry, is very low (Chaston, 1992; William &
Nadin, 2013).
This study focuses on Malaysian TSMEs because the Malaysian government sees the
potential of the tourism industry through its contribution to economic growth and social
development. The Malaysian government has encouraged the active participation of
both the public and private sectors through vigorous promotion and marketing,
4
diversifying target markets, as well as improving the competitiveness of tourism
products and services in an effort to sustain tourists’ interest in Malaysia. The
Malaysian government has a series of five-year economic development plans that have
been implemented since the country’s independence in 1957. Prior to the Visit Malaysia
Year (VMY) campaign in 1990, the country’s tourism revenue from 1981 to 1988 was
in the range of RM 1000 million to RM 2000 million. In 1989, tourist receipts rose by
39 per cent to RM 2.8 billion and by 61 per cent during Visit Malaysia Year 1990 to
RM 4.5 billion. By 1998, the country’s tourism revenue had increased significantly to
RM 8.6 billion with 5.5 million tourists, boosted by the Visit Malaysia Year II
campaign. In 2011, the tourism industry in Malaysia increased by up to RM 58.3 billion
tourist receipts from 24.7 million tourist arrivals in the country (Tourism Malaysia,
2013b). The industry has become the second major contributor to the nation’s GDP and
is now one of the fastest growing sectors in the Malaysian economy.
TSMEs performance and survival in the industry are particularly important to Malaysia
because apart from their key role in delivering tourism products to the tourist, they also
play an active role in advancing the local community. It is essential to observe TSME
performance to ensure the TSMEs will reach their full potential. To ensure TSMEs in
Malaysia continue to support the national tourism industry and remain a source of
employment to the community, this study focuses on determining the key success
factors of Malaysian TSMEs’ performance with a focus on tourism entrepreneurs’
motivation and management. The results of this study will identify resources and their
capabilities for increasing the survival rate of TSMEs in Malaysia.
5
1.2 Problem Statement
It is evident that the tourism industry is an economic reality that can assist Malaysia to
achieve sustained economic growth and contribute to social development. As such, the
Malaysian government has made continuous efforts to stimulate the Malaysian tourism
industry through various channels. Given that TSMEs play a crucial role in the tourism
industry by delivering tourism products and services to the tourist (Ateljevic, 2009;
Buhalis, 1998; Getz & Carlsen, 2005; Page, Forer & Lawton, 1999), vigorous efforts
have been made by the Malaysian government to utilise the advantages that TSMEs can
offer. There are various TSME programmes and policies implemented by the
government to promote the Malaysian tourism industry through TSMEs. The funding
on development allocation for TSMEs has been increasing over the years. In 2011, the
government spent RM 4,677.1 million in the form of 183 training and financial
programmes (Small and Medium Enterprise Corporation Malaysia, 2012). This
indicates that the government has placed high expectations on TSMEs to play their role
as a vital component in increasing the country’s foreign exchange earnings.
However, most tourism entrepreneurs begin TSMEs due to the low entry barrier in the
industry (Brouder & Eriksson, 2013; Morrison & Thomas, 1999, 2004; Skokic &
Morrison, 2011), which gives them an opportunity to be part of the industry (Jaafar,
Maideen & Sukarno, 2010). Previous studies have highlighted the profound challenges
faced by SMEs in other industries that affect the survival of their businesses during the
start-up phase (Hall, 1995). The common challenge impeding their performance is a
lack of management practices in the entrepreneurs such as not regarding the creation of
a business plan as a worthwhile activity (Brinckmann, Grichnik & Kapsa, 2010), not
engaging in business networking (Bosworth & Farrek, 2011); and a poor rate on internet
6
adoption (Alam, Ahmad, Abdullah & Ishak, 2007; Junaidah, 2007; Tan, Chong &
Uchenna, 2009). Further, the owner–manager’s socio-economic characteristics such as
age, gender and education level also form a part of the obstacles that have a
considerable effect on entrepreneurial intention and business performance (Mazzarol,
Volery, Doss & Thein, 1999; Skokic & Morrison, 2011).
In the context of tourism studies, a great deal of research has been conducted on
different segments, including the constrained growth of the tourism industry (Rasul &
Manandhar, 2009), the environmental goals of rural family-owned/family-operated
tourism (Carlsen, Getz & Knight, 2001), financial performance (Sharma & Upneja,
2005) and family business (Getz & Calrsen, 2005). An intensive literature review
reveals that there have been very few studies on tourism entrepreneurship and small
businesses in the tourism industry. One of the significant results from research by
Dewhrust and Horobin (1998) highlighted the ‘lifestyle’ motivations of tourism
entrepreneurs. They are motivated by multiple factors such as providing employment
for family members, companionship with guests and fulfilling their interest or hobbies
(Schroeder, 2003; Skokic Morrison, 2011). These findings characterise tourism
entrepreneurs with a low degree of entrepreneurial motivation, as their managerial
decisions are largely based on personalised criteria (Dewhurst & Horobin, 1998;
Lashley & Rowson, 2010). Further evidence demonstrates that tourism entrepreneurs
are primarily motivated to maintain their business at what they feel is a level that allows
them to maintain the ‘lifestyle’ of a tourism entrepreneur (Carlsen, Morrison & Weber,
2008; Shaw & Williams, 1990, 1998; Tomas et al., 2011).
7
Thus, the scenario of TSMEs presents a challenge for Malaysian governments that aim
to achieve economic growth in the tourism industry, because TSMEs are the backbone
of the industry. The traditional approaches to achieving efficiency through encouraging
entrepreneurs may not work in the case of Malaysia because tourism entrepreneurs are
likely to behave differently. Further, the majority of studies on entrepreneurship and
SMEs have been conducted in different sectors; however, such study in TSMEs in
Malaysia is negligible.
The findings of this research are expected to provide a deeper understanding of tourism
entrepreneurs and TSME characteristics, particularly in Malaysia’s tourism industry.
This research will make several of contributions to the theory and practice of tourism
entrepreneurship and TSME performance. It will validate the RBV theory and reveal
some differences that may exist between TSMEs in developed and developing countries
using a cross-sectional research design. It will also formulate a new approach to
TSMEs’ perceived performance by adopting socio-economic factors in determining the
key success factors of TSMEs in Malaysia.
1.3 Research Questions
The research question for this study is to investigate the underlying success factors for
TSMEs in Malaysia. Specifically, this study aims to address the following research
questions:
1. What is the effect of government assistance programmes on the performance of
Malaysian TSMEs?
2. What is the effect of socio-economic characteristics on Malaysian tourism
entrepreneurs’ motivation?
8
3. How does Malaysian tourism entrepreneurs’ motivation affect the management
practices of Malaysian TSMEs?
4. What is the effect of management practices on Malaysian TSME performance?
1.4 Objectives of the thesis
The objectives of this thesis are:
1. To review government policy on TSMEs in Malaysia.
2. To empirically investigate the characteristics of TSMEs and management practices of
tourism entrepreneurs in Malaysia.
3. To empirically analyse the causal relationships between TSMEs management
practices and TSMEs performance in Malaysia.
4. To identify the key success factors of TSMEs in Malaysia.
1.5 Methodology
Based on the aims of this study, a questionnaire was administered to elicit information
on tourism entrepreneur characteristics, management practices, and government policy
pertaining to TSMEs in Malaysia. The questionnaire contains a series of questions that
were compiled following a review of previous empirical studies on SME and TSME
performance. The structured questionnaire was pre-tested for clarity, difficulty and ease
of response before the execution of the survey. A pilot study was administered to 10
owner-managers of TSMEs based in Kuala Lumpur and Pahang. The questionnaire was
revised following the pilot survey. In order to achieve higher respondent rate and to
save time, data were acquired through personally administered questionnaires at their
business premises. The survey resulted in 346 useable questionnaires, a response that is
9
considered satisfactory for subsequent empirical analysis (Hair, Black, Babin, &
Anderson, 2010)
Due to the incomplete data of TSMEs in Malaysia, the study only focuses on TSMEs
engaged in: a) accommodation services; b) tour operations; c) travel agency services;
and d) tourism guide services. These TSMEs are located in Pahang, Pulau Pinang,
Kedah, Kuala Lumpur and Sabah. The geographical selection of these locations is based
on their significant role and contribution to the Malaysian tourism industry in terms of
number of tourist arrivals. The analysis is narrowed to only TSMEs, due to their role as
the backbone of the Malaysian tourism industry and the increasing share of TSMEs in
recent years.
The empirical investigation in this study consists of two phases. The first phase is a
descriptive analysis of the TSMEs and the characteristics of tourism entrepreneurs. It
consists of correlation analyses, independent sample t-tests and non-parametric test to
test for significant differences of TSME characteristics across locations. The second
phase involves confirmatory factor analysis of the measurement model and full
measurement model.
The confirmatory analysis is performed to examine the measurement model and the full
measurement model based on several fit indices. In determining the fit of measurement
model and full measurement model, at least one absolute fit index, one incremental fit
index and the normed chi-square is utilised (Hair, et al., 2010). If the results indicate a
poor fit model, the measurement model and full measurement model is re-examined and
re-specified by removing items that had factor loadings below 0.50 (Byrne, 2010),
10
squared multiple correlation or R² less than 0.40 (Awang, 2012) or value of
modification indices is above 15 (Awang, 2012). The deletion of items is made one item
at a time and it is repeated until all values satisfy the criteria. Subsequently, the analysis
is expanded to analyse the structural equation model (SEM) to determine the factors
that have significant effects on TSME performance in Malaysia. In order to determine
the fit indices of SEM, it applied the same fit indices of at least one absolute fit index,
one incremental fit index and the normed chi-square utilised on examining
measurement and full measurement model.
1.6 Organisation of the Thesis
This thesis consists of seven chapters. Chapter 2 provides an overview of the Malaysian
economy, the Malaysian government’s policies towards the tourism industry and the
tourism industry’s contribution to the national economy. Chapter 3 focuses on the
literature pertaining to theoretical studies on entrepreneurship and SME performance.
Chapter 4 outlines and discusses the methodological framework to identify key internal
and external factors that explain TSME performance. This chapter also discusses the
sources of data and methods used to compile the data, and explain hypotheses
development and testing. Chapter 5 reports and discusses the results arising from
descriptive statistical analysis. Chapter 6 analyses and discusses the outcomes of
correlation analyses and inferential analyses. This chapter also reports and discuss the
results of the SEM and provides a detailed discussion on hypotheses testing and
findings. Chapter 7 summarises the findings of this thesis, draws some conclusions,
discusses the policy implications of the findings for managerial decision-making and
policy makers, and makes suggestions for future research.
11
Figure 1.1: Thesis Outline
Chapter One Introduction
Chapter Two The Political Economy of Malaysia
and TSMEs
Chapter Three Literature Review
Chapter Four Methodological Framework
Chapter Seven Summary, Conclussions and Implications of the Findings
Chapter Five An Empirical
Investigation on the Characteristics of TSMEs and Management Practices of Tourism Entrepreneurs
in Malaysia
Chapter Six Empirical Analysis of Causal Relationship: TSMEs Management
Practices and Performance
12
CHAPTER TWO
THE POLITICAL ECONOMY OF MALAYSIA AND TSMEs
2.1 Introduction
Chapter 2 provides an overview of Malaysia from a political–economic perspective.
The principal purpose of this chapter is to introduce and explore the manner in which
the political institutions, the geographical landscape and the economy of Malaysia
influence its tourism industry and the development of its TSMEs. It will also explicitly
discuss government efforts to promote the development of TSMEs in Malaysia.
To advance the stated purpose, this chapter is organised as follows: Section 2.2 provides
an overview of the geography, population and culture of Malaysia; Section 2.3 analyses
economic developments in Malaysia; Section 2.4 discusses the tourism industry in
Malaysia; Section 2.5 discusses the organisation of tourism in Malaysia; Section 2.6
discusses tourism policy planning in Malaysia; Section 2.7 examines the effect of
tourism policies on TSME development in Malaysia; and Section 2.8 summarises the
key points of the chapter.
2.2 Geography, Population and Culture of Malaysia
Tourism industry in Malaysia is derived from the great combination of its geographical,
population and the unique cultures of Malaysian. Malaysia is a tropical country situated
in Southeast Asia and has an area of 329,758 square kilometres. The country is
strategically located along the Strait of Malacca, which is a major sea-route connecting
the Far East and Asia, Europe, and the Middle East. The country is divided into 2 parts
– the Peninsular Malaysia and East Malaysia. Peninsular Malaysia consists of 11 states:
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14
dozens of small islands along the coast. Such geographic features allow a wide variety
of activities, from nature-based, eco-friendly adventures to activities such as beach
holidays and scuba diving in locations such as Batu Feringgi Beach located in Pulau
Pinang and Sipadan Island in Sabah.
The country’s mountainous landscape and tropical forests offer a range of outdoor
activities such as caving, hiking, jungle trekking, white-water rafting, rock climbing,
bird watching and river cruising, not only to domestic tourists but also to international
tourists located in Pahang National Park, Gunung Mulu National Park in Sarawak
among other locations. Malaysia’s landscape is varied and each of the regions in
Malaysia has its own local attractions, which are promoted as Malaysian tourism
products.
In terms of population, Malaysia recorded a population of 27,730,000 in 2011
(Department of Statistics, 2012a). The country has three major ethnic groups: the
Malays, the Chinese and the Indians. They make up the majority of Malaysia’s
population. The country also has numerous ethnic and indigenous groups such as Iban,
Bidayuh, Orang Ulu, Kadazan, Bajau and Murut.
The Malays are the largest ethnic group in Malaysia and make up 54 per cent of
Malaysia’s population (Economic Planning Unit, 2012). The Malays are predominantly
Muslims; thus, Islamic values and beliefs are deeply embedded in the Malay culture.
The Malays emphasise values such as courtesy, moderation, tolerance, harmony and
cordial relations among family members, neighbours and community. The Malays also
have their own literature, music, dances and decorative arts. In terms of population
15
distribution across Malaysia, most Malays is highly populated in Terengganu, Kelantan,
Perlis and Kedah (Department of Statistics, 2012c).
The Chinese are the second largest ethnic group and forms about 25 per cent of the
population in Malaysia (Economic Planning Unit, 2012). The majority of Chinese are in
Penang, Perlis, Perak, Kuala Lumpur and Johor. The Chinese arrived in Malaysia
during the 19th century for business and trade. They are originated from the southern
provinces of Kwangtung, Fukien and Kwangsi in China. They are well known for their
entrepreneurial aptitude and hard work. Their natural flair for business activities has
made them successful and advance in economic status. The Malaysian Chinese still
retain their ancestral culture. Their culture is derived from the Chinese civilisation and
is represented by literature, drama, music, painting and architecture. The Chinese are
predominantly Buddhists, though some embrace other religions such as Christianity and
Islam. Buddhist temples are places of worship but also display interesting architectural
elements such as a curved roof ridge, cut-and-paste Chien Nien decoration, and gable
design. All of these elements are derived from ancient Chinese architecture.
The Indians make up the smallest of the three main ethnic groups, and represent 8 per
cent of the population (Department of Statistics, 2012c). They are mainly in the states of
Melaka, Negeri Sembilan, Penang, Perak, Selangor and Kuala Lumpur (Economic
Planning Unit, 2012). The Indians were brought in Malaysia by the British to work on
the rubber plantations. Most Malaysian Indians are Hindus, but some embrace other
religions such as Christianity and Islam. The Indians have a colourful culture and
tradition such as ornate temples, delicious spicy cuisines and exquisitely bright sarees.
They celebrate Deepavali, which is also known as the festival of lights, and Thaipusam,
16
which is a Tamil Nadu celebration and displayed by breaking the coconuts. Thaipusam
is celebrated on a large scale in Penang, Selangor and Perak.
In Sarawak, the Ibans, Bidayuhs and Orang Ulus are the major ethnic groups (Economic
Planning Unit, 2012). They live in longhouses and traditional community homes that
house 20 to 100 families. Most of them are originally animists, but many have now
converted to Christianity. The Ibans are skilled boatsmen and are the upriver tribe from
the heart of Kalimantan. The Bidayuhs are farmers and hunters, who make homes in
Sarawak’s mountainous regions. The Orang Ulus are also known as upriver tribes of
Sarawak, and are artistic people. Their large longhouses are ornately decorated with
murals and superb woodcarvings.
The largest indigenous ethnic groups in Sabah are the Kadazans, the Dusuns, the Bajaus
and the Muruts (Economic Planning Unit, 2012). The Kadazans and the Dusuns both
share the same language and culture but the Kadazans are mainly inhabitants of flat
valley deltas, which are conducive to paddy field farming, while the Dusuns
traditionally live in the hilly and mountainous regions of interior Sabah. The second
largest ethnic group in Sabah are the Bajaus, who are nomadic sea-faring people, and
sometimes referred to as the Sea Gypsies. Those who choose to leave their sea-faring
ways become farmers and cattle-breeders. These land Bajaus are nicknamed 'Cowboys
of the East' as a tribute to their impressive equestrian skills. The third largest ethnic
group in Sabah is the Muruts. Traditionally inhabiting the northern inland regions of
Borneo, they were the last of Sabah's ethnic groups to renounce headhunting. Now, they
mostly practice shifting cultivation of hill paddies and tapioca, and supplementing their
17
diet with blowpipe hunting and fishing. Like most indigenous tribes in Sabah, their
traditional clothing is decorated with distinctive beadwork.
In addition to its natural resources, Malaysia’s multiracial and multicultural society
creates a unique blend of cultures, values, faiths and beliefs, and a contemporary and
diverse Malaysian heritage. Malaysia has a wide variety of music, dance, literature,
cuisine, architecture, decorative arts and festivals stemming from the blend of diverse
ethnic groups and religions, all of which are key city attractions that are also promoted
to international tourists by MOTOUR and the State Tourism Action Department
(STAD) located in each region in Malaysia (see explanation in Section 2.5.2).
2.2.1 Malaysian Regions
Based on Malaysia’s geographical landscape, the 11 states and three federal territories
are divided based on regions. Malaysia has five regions and each region has differences
in its geographical landscape, economic activities, ethnicities and lifestyle. Thus,
utilising these unique features, MOTOUR has promoted each region based on its
specific tourism attractions. The following sections explain the five regions: the
northern region, central region, southern region, east coast region, as well as Sabah,
Sarawak and Labuan with more detail related to their key tourism attractions.
2.2.1.1 Northern Region
The northern region is made up of the states of Perlis, Kedah, Pulau Pinang and Perak.
The population of the northern region represent of 20.5 per cent of the national
population (Department of Statistics, 2012a). The geographical landscape of the
northern region is made up of islands, beaches, landscape and rainforest. Kedah and
18
Pulau Pinang are famous their idyllic islands while Perlis and Perak are formed of rocky
limestone and famous for their ancient historical sites.
In terms of urbanisation level, the most outstanding state in this region is Pulau Pinang
with level of urbanisation of 90.8 percent while the other states are in general above 50
per cent (Department of Statistics, 2012c). This may reflect the economic activity of
Pulau Pinang which is a highly industrialised sector while Kedah and Perlis dominate
the agriculture sector in Malaysia on paddy growing and Perak handles small and
medium based manufacturing. In terms of ethnicity, Perlis, Kedah and Perak are
dominated by Malays while Pulau Pinang has a predominantly Chinese and Indian
population, with Malays in the minority.
2.2.1.2 Central Region
The central region constitutes of Selangor and Negeri Sembilan and Kuala Lumpur
Federal Territory and Putrajaya Federal Territory. The area of Selangor surrounds the
Federal Territory of Kuala Lumpur, which is the capital of Malaysia. Kuala Lumpur is a
bustling cosmopolitan city with modernity, high-tech buildings and major shopping
centres while Putrajaya is the hub of the federal government offices. This region is the
most populous region with 29.3 per cent of Malaysians living in this region. Selangor’s
population is the largest in Malaysia (19.4 per cent of total population) and also the
highest urbanised in Malaysia with the level of 91.4 per cent (Department of Statistics,
2012c). Selangor’s geographical position in the centre of Peninsular Malaysia
contributed to the rapid development as Malaysia’s transportation and industrial hub.
19
Selangor and Negeri Sembilan are dominated by Malays, followed by Chinese, Indian
and other ethnic groups. Selangor’s economies are commerce, industry and services. It
has several industrial sites producing electronic goods, chemicals, and automotive
vehicles such as Proton and Perodua cars and assembling imported cars in the state.
Negeri Sembilan is an agricultural state mainly focusing on rubber, oil palm plantations
and livestock. It is famous for its rural landscape and for the local traditions of the
Minangkabau.
2.2.1.3 Southern Region
The southern region consists of Melaka and Johor (the state that forms part of the long
eastern coastline facing the South China Sea). The beaches and particularly the coral
islands are the main attractions in Johor. Melaka is famous for its historical attractions
related to the Dutch invasion and also the lifestyle of the Baba-Nyonya, or Straits
Chinese. Chinese migrants intermarried with the locals and settled in Malaysia during
the early 1400s. They have strong Malay influence in their clothing and food but also
retained their Chinese heritage, especially the religion, name and ethnic identity.
The population in this region makes up only 14.8 per cent of the total population in
Malaysia. Melaka is the least populated state with only 2.9 per cent; Johor ,on the other
hand, is the second most populated state in Malaysia with 11.9 per cent of the nation’s
population living here (Department of Statistics, 2012c). Both states have majority
Malay and Chinese populations. Indian and other ethnic groups are the minority in
Southern region. In spite of low population, the urbanisation level on Melaka is
relatively high at 86.9 per cent, and Johor at above 71.9 per cent compared to states in
20
other regions (Department of Statistics, 2012a). Aside from the manufacturing industry,
both Melaka and Johor are among the major tourist attractions in Peninsular Malaysia.
2.2.1.4 East Coast Region
Facing the South China Sea is the East Coast region, made up of Pahang, Terengganu
and Kelantan. It covers 51 per cent of the land area of Peninsular Malaysia and
represents 14 per cent of the national population (Department of Statistics, 2012c). The
region remains the least urbanised at 41.3 per cent compared to other regions in
Peninsular Malaysia (Department of Statistics, 2012a). As the region is highly
populated with Malay compared to other parts of Malaysia, this region is known for its
strong Malay culture, especially Kelantan and Terengganu. Both states have strong
influence with Thai elements. Thus, the Malay culture of these two states differs
somewhat from Malay culture in the rest of the peninsula. This is reflected in the
cuisine, arts and even the peculiarity of the East Coast Malay dialect.
The geographical landscape of the East Coast Region, which made up of rainforest and
coastline, influences its economic activities. Kelantan and Terengganu are involved in
the fishing industry, as well as cottage industries which employ traditional skills in
handicraft productions such as batik, wood carving and songket weaving. On the other
hand, besides fishery products, Pahang’s other industries include forestry,
petrochemical processing and shipping, and port industry. This physical geography in
Pahang (the highlands, the rainforest and the coastal area) has contributed to its tourism
industry. Thus, most of the tourism attractions in Pahang are ecotourism activities.
21
2.2.1.5 Sabah, Sarawak and Labuan (East Malaysia)
In these regions, Sabah, Sarawak and Labuan have a mostly indigenous population and
represent 20.7 percent of Malaysia’s total population. As one of the Federal Territories,
Labuan is home to only 0.4 per cent of Malaysia’s population, which makes it the least
populated (Department of Statistics, 2012c). The multi-ethnic nature of this region also
differs from other regions in Peninsular Malaysia in terms of culture, arts, cuisine and
dialect. In term of the level of urbanisation, Sabah and Sarawak have some of the lowest
levels of urbanisation in Malaysia, with less than 54 per cent in Sabah and 55.8 per cent
in Sarawak (Department of Statistics, 2012a). In terms its economic activity, East
Malaysia is focused mainly on oil and gas reserves and natural resources. The landscape
of East Malaysia is mostly lowland rain forest (with some areas of mountain rainforest)
as well as aquatic bio-diversity. These features have become its key tourism attraction
to the world. Table 2.1 lists some of the key natural resource attractions of each region
in Malaysia.
Table 2.1: Key Natural Resources Attractions in Malaysia
Peninsular Malaysia Region States Tourism products Attractions
Northern Region
Perlis Nature and adventure Kuala Perlis,,KelamCave, Wang Burma Cave,Ayer Forest Reserve,Wang Mu Forest Reserve
Kedah Islands and beaches
Langkawi Island,Payar Island Marine Park,Dayang Bunting Lake,Beras Basah Island
Nature and adventure Ulu Legong Hot Spring, Bukit Batu Pahat, Kota Kuala Muda, Muara Sungai Muda, Langkawi Mangroves
Pulau Pinang
Islands and beaches Batu Feringghi Beach Nature and adventure Pulau Pinang National Park, Tropical
Spice Garden, Pulau Pinang Botanic Garden
Perak Island and beaches Pangkor Island Nature and adventure Sungai Klah Hot Spring Park, Belum
Forest Reserve, Bukit Larut (Maxwell Hill), Tempurung Cave
Central Region
Negeri Sembilan
Island and beaches Port Dickson Beach
22
Southern Region
Johor Island and beaches Sibu Island, Desaru Beach, Aur Island, Kukup Island, Johor National Park
Nature and adventure Kota Tinggi Waterfall, Tanjung Piai National Park, Sungai Lebam Wetlands, Gunung Ledang
East Coast Region
Kelantan Island and beaches Bisikan Bayu Beach Nature and adventure Gunung Stong State Park
Terengganu Island and beaches Redang Island, Perhentian Island, Lang Tengah Island, Kapas Island
Nature and adventure Kenyir Lake Pahang Island and beaches Tioman Island
Nature and adventure Genting Highland ,Taman Negara, Cameron Highlands, Fraser’s Hill
East Malaysia
Sarawak, Sabah and
Labuan
Sarawak Nature and adventure Gunung Mulu National Park, Bako National Park, Gunung Gading National Park
Sabah Island and beaches Sipadan Island, Tuanku Abdul Rahman Marine Park,Layang-layang Island, Mabul Island
Nature and adventure Danum Valley,Mount Kinabalu, Rainforest Discovery Center, Sepilok Orang Utan Sanctuary
Source: MOTOUR (2013)
2.3 Stages of Economic Development in Malaysia
2.3.1 Malaysia’s Economic Status, 1957-1959
When Malaysia attained its independence in 1957, the tourism industry was of
secondary importance due to the reconfiguration of the social structure and the focus on
setting up the basic infrastructure for the country (Economic Planning Unit, 1966). The
main economy was primarily commodity-based, with heavy dependence on rubber and
tin. The agriculture and mining sectors were major contributors to the country’s
employment and GDP. Both sectors generated 45.7 per cent of GDP and 61.3 per cent
of total employment. The secondary sector, consisting of manufacturing, building and
construction, was a relatively small contributor to GDP and employment. It contributed
11.1 per cent to GDP and 9.6 per cent of total employment. Trade sub-sectors such as
financial and banking services contributed 15.2 per cent to the nation’s GDP during this
23
period. The services sector (consisting of private and public services such as health and
education) was next in importance, contributing 11.1 per cent to GDP (Shari, 2000).
During this period, the population grew at 3.4 per cent, one of the highest recorded rates
of natural population increase in the world. The unemployment rate increased from 2
per cent in 1957 to 7 per cent in 1967 and 8 per cent in 1970 (Shari, 2000). Due to the
uneven distribution of income between the rural and urban populations and between the
various ethnic groups in Malaysia, the government set up the Rural and Industrial
Development Authority (RIDA) in 1950 as a programme to increase the number of
Malays in business and commerce. This initiative became a major part of the
government’s economic development plan (Gomez & Jomo, 1999; Siddiqui, 2012).
A final feature of the economy at this period was the low level of human resource
development, which resulted in a shortage of many skills required for the nation’s
economic development (Siddiqui, 2012). In summary, the Malaysian economy in its
early years of independence was characterised by exports of primary products of tin and
rubber, resource-based industries, a high degree of inequality, high unemployment and
population growth.
2.3.2 Malaysia’s Economic Status, 1960s to 1980s
The period from the 1960s through the 1980s witnessed the transition from primary
products (like tin and rubber) and resource-based industries to an economy heavily
dependent on manufacturing. This was a result of two fundamental strategies: the
import substitution strategy, which was actively pursued in the First Malaysia Plan
(1966–1970) and the export oriented strategy, which was implemented in the Second
24
Malaysia Plan (1971–1975) (Economic Planning Unit, 1966, 1971, 1976). These two
strategies and the economic policy, which are outlined in the next section, have shaped
the main features of Malaysia’s economic status during these three decades.
In the early 1960s, the Malaysian economy was still heavily dependent on the
agriculture sector, which was the main foreign exchange earner and source of
employment. The reliance on agriculture brought an influx of international visitors for
dealing with the supply of raw materials such as rubber and spices into Malaysia (Jomo,
1990). Since tourism industry was not a primary element at this stage, international
visitors were not counted as part of tourism industry performance. Despite high
productivity in the agriculture sector, most of the population was either unemployed or
engaged in low-income employment. Furthermore, the agriculture sector did not
provide enough growth impetus for the overall economy (Gomez & Jomo, 1999).
This led to the economic shift from the agriculture to the manufacturing sector. The
implementation of the import substitution and export oriented strategies led to the early
structural change to industrialisation, which began in the 1970s and continues today. As
a result, the country gained a better balance between agriculture, manufacturing and
services sectors (Kamaruddin & Masron, 2010). The range of economic activities and
products, as well as sources of growth, became more diversified and enlarged. This
included tourism industry activities under the services sectors. The Malaysia
government has invested RM17.2 million for tourism industry development, which was
spenton basic tourism infrastructure such as airports and tourist sites (Economic
Planning Unit, 1971).
25
The 1980s saw major structural transformations of the economy. During this decade, the
manufacturing sector surpassed the agricultural sector. The tourism industry was
considered as one of the solutions to improve the socio-economic status of Malaysians
through employment, regional development and diversification of the economic base of
the country (Khalifah & Tahir, 1997). The focus on tourism industry has significantly
increased the foreign-exchange earnings to the country. In 1980, the tourism industry
endowed RM619 millions of total receipts to the country (Tourism Malaysia, 2013b).
This move towards industrialisation was based on the premise that the nation needed to
reduce its dependence on imports of capital and intermediate goods in order to sustain
growth and generate rapid development through heavy industries. During this era, the
government imposed deregulation and reforms on several administration and
institutional agendas. Efforts were also focused on upgrading the efficiency of the
public sector and adopting a private sector-led growth strategy to promote private sector
participation (Kuruvilla, 1995). This created an environment conducive for private
sectors to flourish and contribute to economic development. The manufacturing sector
was the largest contributor to employment creation in the economy during this era. Four
industries (wood products, textiles and clothing; rubber products; and electronics
components and assembly) were prominent contributors of growth in manufactured
exports (Wan Abdullah, 1994). Tourism has also significantly provided jobs to the local
community, particularly to the rural population. Focusing on tourism activities in rural
areas—East Coast Region and Sabah and Sarawak (Economic Planning Unit, 1976)—
has led to the improvement on the wealth of communities in these least developed
regions in Malaysia. Since the industries were relatively labour intensive and
established at a time when Malaysia urgently required greater job opportunities for
26
expanding labour force, they have changed the composition of Malaysian exports from
resource-based to non-resource commodities.
2.3.3 Malaysia’s Economic Status, 1990s
The manufacturing sector and the focus on cluster-based (cluster is an agglomeration of
interlinked or related activities comprising of industries, suppliers, critical business
services, requisite infrastructure and institutions) development provided the guiding
principles for Malaysia’s industrial development in the 1990s. During this era, the
government also focused on the promotion of greater intra-industry and inter-industry
trade and foreign direct investment-driven growth policies under the National
Development Policy (NDP) (Leong, 1992). The performance of tourism industry during
this stage was the breakthrough to the national economic contribution. The industry has
contributed RM4.5 billion of total tourist receipt to the country during the 1990. This
thrive performance of tourism industry was a result from the Visit Malaysia Year
campaign in 1990 (Economic Planning Unit, 1986).
However, in mid-1997, the Asian financial crisis interrupted this momentum. The effect
of the financial crisis was evident in all sectors of the economy and led to massive
unemployment and reduction in national income. Malaysia’s GDP in 1998 registered a
reduction in growth to 6.8 per cent, resulting in the decline of per capita income by 1.8
per cent. Tourism industry performance was severely affected and posted losses of
RM30 million in tourist receipts, a decline of 4.8 per cent (de Sausmarez, 2004;
Economic Planning Unit, 1986). The loss of tourists in rest of Asia, which was facing
the same financial crisis, has caused a drop in tourism industry performance. The
agriculture sector also declined by 4 per cent in 1998 as a result of lower production on
27
all major commodities. The manufacturing sector, particularly the production of
electrical machinery, apparatus, appliances and supplies has declined by 7.7 per cent.
The main reasons for the decline were caused by the weak demand from the Asia-
Pacific region and the depressed global market for semiconductors (Economic Planning
Unit, 2008). In contrast, output in the mining sector rose marginally by 0.8 per cent due
entirely to the higher output of crude petroleum and gas.
The government came out with the National Economic Recovery Plan (NERP) to
address the worsening economic situation and to revitalise the economy. Through
NERP, the Malaysian government adopted the policy to focus on reducing risks during
the financial crisis to ensure macroeconomic stability, restore confidence and promote a
stronger financial system in all sectors (Economic Planning Unit, 2013a).
2.3.4 Malaysia’s Current Economic Status, 2000s
In the early 21st century, Malaysia and the rest of the world were affected by Severe
Acute Respiratory Syndrome (SARS), the war in Iraq and an increase in world oil
prices. The Malaysian government introduced the Package of New Strategies in 2003 to
stimulate economic growth. The package was aimed at promoting private sector
investment, strengthening the nation’s competitiveness in manufacturing industry,
developing new sources of growth in tourism industry and enhancing the effectiveness
of the delivery system. This strategy resulted in robust external demand and increased
private sector activity in the domestic economy. The economic performance of 5.2 per
cent growth in 2003 was better than expected (Economic Planning Unit, 2013b).
28
Malaysia’s momentum continued and the economy grew by 6.3 per cent in 2007, above
the 5.8 per cent average recorded between 2000 and 2006. This was attributed to the
diversified economic structure, strong public and private sector expenditures, enhanced
delivery systems and an impressive trade performance (Economic Planning Unit,
2013c). From 2005 to 2007, Malaysia’s GDP grew at an average rate of 4 per cent per
annum. The agriculture sector registered a notable growth of 6.4 per cent in 2007,
reflecting higher production of natural rubber, crude palm oil and cocoa. Manufacturing
outputs had expanded by 7.0 per cent. The services sector continued to grow by about
6.5 per cent, supported by the growth in finance, insurance, real estates and tourism
industry (Ministry of International Trade and Industry, 2009). The tourism industry
indicated a positive contribution to the national’s GDP’s by7.4 per cent in 2007.These
results reflected the effectiveness of the new strategy, which focused on new
international markets such as Australia, Europe, USA and Middle East to boost tourist
arrivals into the country. At the same time, it improved the foreign exchange earning of
the industry instead of merely depending on targeting international tourist arrivals from
Asian region (Economic Planning Unit, 2013a).
Table 2.2 indicates Malaysian key economic performance from 2009 to 2011. In 2011,
the Malaysia economic faced a decrease of GDP to 5.1 per cent, from 7.2 percent in
2010. This resulted from the slowing export following the United States’ economic
performance, the deepening euro debt crisis, global supply chain disruptions resulting
from the earthquake and tsunami in Japan, as well as rising global inflation. In terms of
the sector contribution to Malaysian GDP during 2011, the manufacturing sector
showed slow growth by 4.7 per cent, due mainly to weak export-oriented industries.
The agriculture sector grew at a more moderate pace by 3 per cent following the
29
deceleration in the production of palm oil amidst the onset of a yield down cycle.
Growth in the mining sector was sluggish at -0.3 per cent as a result of a lower natural
gas output (Ministry of Finance Malaysia, 2013). The services sector continued to
expand despite this challenging economic environment with sustained expansion and an
increase of 7.0 per cent. Tourism remained resilient, generating tourist receipts of RM
56.6 billion from 24.6 million tourist arrivals (Tourism Malaysia, 2013b) and in terms
of its GDP contribution, tourism industry showed growth of 6.9 per cent (Economic
Planning Unit, 2012).
Table 2.2: Key Economic Indicators of Malaysian Economy, 2009-2011
2009 2010 2011 Real GDP growth rate (% p.a) 6.0 7.2 5.1
Sector contribution to GDP RM
billion %
growth RM
billion %
growth RM
billion %
growth Agriculture, forestry & fishing 50.1 0.1 51.3 2.4 54.3 5.9
Mining and quarrying 66.4 -6.5 66.1 -0.4 62.3 -5.7 Manufacturing 152.2 -9.0 170.3 11.9 178.3 4.7 Construction 19.3 6.2 20.4 6.0 21.4 4.6 Services 335.0 2.9 359.2 7.2 384.3 7.0 -Tourism industry* 103.4 2.1 111.8 8.0 119.5 6.9
% of labour force Labour force (million) 11.3 12.1 12.6 Unemployment rate 3.7 3.3 3.1 Notes: * Accommodation and restaurant only Source: Economic Planning Unit (2012)
As a highly open economy with strong financial and real economic linkages with the
rest of the world, the Malaysian economy was affected by the global financial
environment. The significant slowdown in global growth is expected to affect the export
sector. However, Malaysia’s better resilience lies in the established strong fundamentals
that have been built up over several years. The continued significant current account
surplus, low external debt, large international reserves and well-capitalised banking
30
system will place the economy in a stronger position to weather future challenging
periods. To mitigate the impact of the weak global growth on the domestic economy,
the Malaysian Government announced the Economic Transformation Programme (ETP)
consisting of initiatives and continuous investment focus on National Key Economic
Areas (NKEAs) that focus on technology-related, services and resource-based industries
(Economic Planning Unit, 2011; PEMANDU, 2013)
2.4 Tourism Organisation in Malaysia
In structuring the tourism development in Malaysia, there are three tiers of government
involvement; Federal government, State government and Local Authorities. The
following section will look into the role of this three-tier organisation in developing
Malaysia’s tourism industry.
2.4.1 The National Tourism Organisation
The development of Malaysia’s tourism industry began in 1972 with the establishment
of the Tourist Development Corporation (TDC) under the Ministry of Trade and
Industry (MITI). In 1987, TDC was shifted under the new ministry: the Ministry of
Culture, Arts and Tourism (MOCAT). The establishment of MOCAT resulted from the
significant contribution of the tourism industry to the national income. Then, in 2004,
MOCAT was split into two ministries: the Ministry of Culture, Arts and Heritage, and
the Ministry of Tourism. The Ministry of Tourism, known as MOTOUR, is under the
federal government, and is responsible for monitoring the development and growth of
the industry as a whole. Figure 2.2 shows the development of MOTOUR in Malaysia.
31
Under MOTOUR, the TDC changed to a new name: the Malaysian Tourism Promotion
Board (MPTB), simply known as Tourism Malaysia. The main role of Tourism
Malaysia is to market and promote the country as a premier tourist destination to the
world. The efforts are geared to increase the number of foreign tourists and to extend
the average length of stay for both local and foreign tourists, through extensive
promotional strategies locally as well as internationally. Tourism Malaysia has offices
in all states and federal territories in Malaysia, 12 Tourist Information Centres in key
tourist attractions in Malaysia, 40 international offices, and eight marketing
representatives in prospective international target markets (see Appendix 2.1) in order
to extensively promote Malaysia as holiday destinations to the world (Tourism
Malaysia, 2013a)
32
Figure 2.2: The Development of MOTOUR Source: Developed by the candidate
Although MOTOUR controls the tourism administration, other related ministries are
also involved directly in tourism development. Figure 2.3 shows the important
ministries and departments engaged with planning, maintaining and controlling tourism
activities in Malaysia.
Ministry of Trade and Industry Tourist Development Corporation (TDC)
1970’s Agency
1980’s
Ministry of Culture, Arts and Tourism (MOCAT)
Tourist Development Corporation (TDC)
Agency
Establishment of new ministry
1990’s
Malaysia Tourism Promotion Board or Tourism Malaysia
TDC changed to a new name
2000’s MOCAT split into two ministries with more specific functions
Ministry of Culture, Arts and Heritage (MOCAT)
Ministry of Tourism
(MOTOUR) Tourism Malaysia
TDC shifted MOCAT in 1987
33
Figure 2.3: Government Departments in Malaysia's Tourism Industry
Development
Source: Modified from Marzuki (2010)
MOTOUR also works closely with other Ministries, namely: the Ministry of Transports;
the Ministry of Entrepreneur and Cooperative Development (MECD); HERITAGE; the
Ministry of Education; the Ministry of Higher Education; the Ministry of Agriculture
and Agro-based Industry; the Ministry of Natural Resource and Environment; and the
Ministry of Youth and Sports. The collaboration with these ministries is intended to
implement national tourism programmes such as the homestay programme, the
Malaysia My Second Home programme, Student Tourism Programme, Education
Tourism, Agro Tourism and Sport Tourism. Table 2.3 lists some tourism programmes
by MOTOUR in collaboration with other related ministries.
Ministry of Tourism -Tourism Malaysia; Policy & Legislation Infrastructure, Promotion
Ministry of Housing & Local Government -Town & Country Planning Department: Prepare local Plan & Structure Plan
Ministry of Science, Tech. & Environment -Wildlife & National Park Department; Wildlife management -Ecotourism Division; Advise government, Identify & Plan programs
Ministry of Primary Industry -Forestry Department; Forest Management
Ministry of Transport -Marine Department; Marine Management
Ministry of Agriculture -Agriculture Department-Fisheries Department
Ministry of Health - Corporate Policy and Health Industry Division; Policy on Medical tourism and related health care products including traditional medicine
Ministry of Higher Education - Educational tourism policy
Tourism in
Malaysia
34
Table 2.3: Collaboration with Other Ministry on Tourism Programmes
Federal Government Tourism Programme Ministry of Higher Education • Student Tourism Programme
• Education Tourism Ministry of Agriculture and Agro-Based Industry • Agro-Tourism Ministry of Youth and Sport • Sport-Tourism Ministry of Health Malaysia • Medical-Tourism Ministry of Health Ministry of Energy, Green Technology and Water
• 1Malaysia Green and 1Malaysia Clean
Source: MOTOUR (2013b)
As the tourism industry in Malaysia is one of the largest industries and employers in
Malaysia, MOTOUR is also responsible for developing the tourism industry in a
sustainable manner and for maximising its potential as a primary and new growth
industry, which in turn generates substantial employment for Malaysians. Thus, besides
planning and developing national tourism products, MOTOUR also provides tourism-
related courses for tourism workers, publics and especially to tourism operators to
increase their competency and competitiveness and to expand the opportunities for
long-term careers in tourism.
Table 2.4 lists the courses provided by MOTOUR in order to provide and support the
human capital with appropriate skills. In 2012, there are 58 MOTOUR registered
tourism training institutes that offer and conduct such courses all over Malaysia
(Ministry of Tourism Malaysia, 2013a). MOTOUR also offered extensive training
supervised by the National Tourism Human Resource Development Council
(NTHRDC) and the National Vocational Training Council (MLVK) to improve the
quality of tourism services. MLVK has developed 77 National Occupational Skills
Standards (NOSS) covering hotel, tourism and travel segments, theme parks and
recreational activities to provide semi-skilled employees to meet the labour force
demand of Malaysia’s tourism industry. According to the 7th Malaysia Plan review, in
35
2005 there are more than 2,500 tourism-related training programmes offered in 113
training places throughout Malaysia (Economic Planning Unit, 2006).
Table 2.4: Courses Programme Provided by MOTOUR
Courses under the Malaysia Welcomes the World Programme 1. Mesra Malaysia 11. Halal Product 2. Think and Act Tourism 12. Marketing 3. Tourism English 13. Train the Trainer 4. Basic Tourist Guide Course 14. Eco-Host Malaysia 5. Local Nature Tourist Guide Course 15. Product Development 6. Homestay 16.Foreign Language 7. Ethics/Communication/Appearance 17. Hygiene Awareness 8. Crisis Management 18. Excellent Customer Service 9. Tourism Awareness 19. Tourist Boat Operating Course
and Courteous Taxi Driver Course 10. Hotel and Services Management
(i.e.. Budget Hotel Efficiency Improvement Course)
Source: Ibrahim (2009)
2.4.2 State Tourism Organisations
Prior to 2002, the tourism industry in Malaysia was largely monitored and controlled by
the federal government. In 2002, state governments requested greater representation in
tourism matters via the State Tourism Action Council (STAC) in each state under
MOTOUR. In 2009, the State Tourism Action Department (STAD) replaced the STAC.
The roles of the STAD include coordinating and monitoring the growth and
development of national tourism products, and making local tourism products and
programmes of each state to become a main sector that is sustainable, viable and
valuable for national tourism products.
MOTOUR and STAD work closely together to generate tourist attractions and attract
both international and domestic tourists to visit Malaysia. They actively promote
Malaysia as a multicultural society and country through the variety of foods, ethnic
36
cultures, and festivals. They also introduced local city excitements as an extension to
Malaysia’s tourism products to develop Malaysia as a key destination in the global
tourism industry. Table 2.5 lists some of the Malaysia’s city excitements promoted and
highlighted by STAD. Each state’s STAD develops its own city attractions that are
supported by MOTOUR to increase tourist arrivals in the state and in Malaysia as a
whole.
Table 2.5: List of Some Key City Excitement Attractions in Malaysia
States Attractions Perlis Padang Besar, Kota Kayang Museum, Snake and
Reptile Farm Kedah Langkawi Cable Car, Klim River Cruise, Langkawi,
Mahathir’s Birthplace, The Paddy Museum Pulau Pinang Cheong Fatt Tze Mansion, Fort Cornwalls, Gurney
Drive,Pulau Pinang, War Museum Perak Kellie’s Castle, Taiping Lake Gardens, Lenggong
Archaeological Museum, Pasir Salah Historical Complex
Selangor Batu Caves, Sunway Lagoon Theme Park, i-City, Kidzania
Kuala Lumpur (Federal Territories)
Petronas Twin Towers, Central Market, KL Tower, Aquaria KLCC, Islamic Arts Museum
Negeri Sembilan Seri Menanti Royal Museum, Rembau Crystal Army Museum
Melaka St. John’s Fort, A’ Famosa, Jonker Walk, Portuguese Square, Baba Nyonya Heritage Museum
Johor Legoland, Endau Rompin National Park, Johor Zoo, Direct Factory Outlet
Kelantan Siti Khadijah Market, Handicraft Village and Craft Museum
Terengganu Tengku Tengah Zaharah Mosque, Terengganu State Museum, Pasar Payang
Pahang Genting Highland, Cameron Highlands Kuala Gandah Elephant Orphanage Sanctuary
Sarawak Sarawak Cultural Village, Longhouse Tours Jalan Satok Sunday Market, Matang Wildlife Center
Sabah Sepilok Orang Utan Sanctuary ,Monkey Tops Safari Labuan (Federal Territories)
Water Village, Tanjung Kubong Tunnel and Chimney, Peace Park
Source: MOTOUR (2013)
.
37
Also, STAD has developed festivals and event celebrations to highlight the diversity in
their local tourist attractions. Each festival events is organised and created based on the
local attractions. For example, the festival in Pulau Pinang is synonymous with the
Chinese culture‘s Hungry Ghost Festival and Dragon Boat Race Festival. Besides that,
the Pulau Pinang Bridge Marathon (promoting Pulau Pinang Bridge, a national
landmark) is an annually held event that successfully attracts both local and
international participants. Other STAD have practiced the same approach, and Table 2.6
lists the festival celebrations held in Malaysia.
Table 2.6: Festivals and Events in Malaysia
States Festival Throughout Malaysia
Visit Malaysia, Merdeka Parade, Malaysia Mega Sales, Malaysia Fest, Eid-Mubarak Celebration, Chinese New Year, Deepavali Celebration
Pulau Pinang Pulau Pinang World Music Festival, Pulau Pinang Hungry Ghost Festival, Pulau Pinang Bridge International Marathon, Dragon Boat Race Festival
Negeri Sembilan Ethnic Arts Festival, ASEAN Regatta Melaka Festival Songket and Batik Melaka, Melaka International Kite
Festival, Anniversary of UNESCO World Heritage City Celebration
Johor Johor Bahru Lantern Festival Terengganu Monsoon Cup Kelantan Cultural Carnival,International Kite Festival Sabah Tamu Besar Festival, Regatta Lepa, Pesta Kalimunan Sarawak Sarawak Regatta, Gawai Sowa Festival, Harvest Festival,
Belaga Regatta and Gawai Dayak, Rainforest Music Festival Labuan (Federal Territory)
Labuan International Sea Challenge
Source: MOTOUR (2013b)
2.4.3 Local Tourism Organisation
Local authorities are established under the Ministry of Housing and Local Government
with the objective to provide and maintain public facilities such as recreational areas,
landscaping areas and garbage disposal services. The local authorities’ tourism-related
projects in each state and the Federal Territories are mainly to improve and beautify the
38
streets such as the Bintang Walk in Kuala Lumpur, the Star Walk in Alor Setar, Kedah,
and the Batu Pahat Walk in Batu Pahat, Johor. These are carried out to create a vibrant
focal point and tourist attraction within cities or towns in each state or Federal Territory
in Malaysia.
2.5 Tourism Policy Planning in Malaysia
The Malaysian government has a three-tier government structure: federal government,
state government and local authorities. These organisations are responsible for
developing tourism strategies as a partial driver for Malaysia’s overall economic
development. This is implemented by preparing the tourism industry’s economic plan,
and strategies and guidelines for the five-year economic plan. Since 1966, the
Malaysian government’s five-year economic plans (better known as the Malaysia Plans)
has been established to implement Malaysia’s overall economic development strategies.
The following sub-sections discuss all ten Malaysia Plans, with particular emphasis on
the strategies and planning pertaining to the tourism industry.
2.5.1 The First Malaysia Plan (1966–1970)
The development of tourism industry was not particularly a concern during the First
Malaysia Plan (1966–1970) (Economic Planning Unit, 1966). During this plan, the
government strategy was to promote the integration of the people of Malaysia and
improve the living conditions in rural areas, particularly among low-income groups. As
the economy was fundamentally primarily commodity-based with heavy dependence on
rubber and tin, the government diversified and modernised its agricultural production.
This stimulated new lines of economic activities in the agricultural and industrial
39
sectors. At this stage, the government’s priority was more on the formation of the basic
facilities.
2.5.2 The Second Malaysia Plan (1971-1975)
After the implementation of the First Malaysia Plan, Malaysia’s economy gained
strength but the deficit in the balance of payments of the country’s foreign exchange
was high (Mohamed, 1995). At the same time the prevalence of poverty and income
disparities between the various ethnic groups exacerbated tensions within the society
(Economic Planning Unit, 1971). As a result, tourism was considered one of the
solutions for decreasing the deficit in the balance of payment, encouraging economic
diversification and eradicating poverty among all ethnic groups, as well as eliminating
the existing racial and spatial imbalance in the Malaysian economy by promoting
greater understanding of the various cultures and lifestyles of the multiethnic
population.
To facilitate the tourism policies designed to meet the Malaysian government’s
objectives on the Malaysian tourism industry’s performance and development, the
Tourist Development Corporation (TDC) was established in 1972 as an agency under
the Ministry of Trade and Industry (MITI). TDC was formed with the following
objectives:
1. To coordinate activities pertaining to the tourism industry conducted by
government and non-governmental bodies,
2. To make recommendations to the government on measures and policies to
be adopted to facilitate the growth of tourism and to implement and assist in
the implementation of approved measures and policies, and
40
3. To generally promote national and international tourism of Malaysia, as well
as to participate in the physical development of the tourism industry in
Malaysia.
To achieve these objectives, TDC set the following targets:
1. To promote Malaysia as a tourist destination at the international and regional
levels,
2. To encourage the growth of domestic tourism,
3. To maintain representational functions and duties on the international as well as
regional levels on matters relating to tourism,
4. To project Malaysia as a convention centre in the region,
5. To monitor and determine present and future requirements of foreign and
domestic tourists as well as recommend desirable land usage strategies for the
purpose of tourism within the development areas,
6. To gather, interpret and disseminate tourism data and information to users of
tourism statistics,
7. To regulate, control and guide the growth of the industry for the best interest of
the country, and
8. To ensure Malaysia’s tourism industry develops in accordance with the
government’s New Economic Policy.
Under the Second Malaysia Plan, the government allocated RM17.2 million for tourism
industry development. The funds were invested in basic tourism infrastructure, such as
highways, airports and tourist sites in all states (Economic Planning Unit, 1971; Musa,
2000). Tourism activities were aimed to increase employment, which would
41
subsequently increase income levels, foster regional development and diversify the
economic base of the country (Khalifah & Tahir, 1997). The TDC developed an
integrated approach to tourism promotion, which reflected the rise of tourist arrivals
into Malaysia and subsequently proved tourism activities as a solution to address NEP’s
objectives.
Besides TDC’s vigorous tourism promotions through its overseas offices and
participation in international tourism conventions, the Corporation also actively
emphasised domestic or local tourism. However, the government paid little attention to
the issues surrounding the negative socio-cultural aspects of tourism. The development
of the tourism industry in Malaysia at this time was not properly organised. Most
tourism economic activities concentrated on the urban centres, particularly Kuala
Lumpur and Pulau Pinang. Traditional destinations or rural areas, primarily those on the
East Coast of Malaysia, Sabah and Sarawak, were given little attention by the
government and no efforts were put into upgrading tourism facilities and accessibility in
these areas. During this period, tourism activities were not fully explored with regard to
the rich cultural and natural attractions.
2.5.3 The Third Malaysia Plan (1976-1980)
Continuing the NEP’s objectives, the Third Malaysia plan emphasised assistance to
enable indigenous groups to participate in the tourism sector. For a start, the
predominantly indigenous populated areas located in the east coast region of Peninsular
Malaysia and Sabah and Sarawak were provided with better facilities for and access to
tourists. This was to raise the incomes of the indigenous and rural population and fully
utilise the rich cultural and natural attractions of the areas. This approach was similar to
42
those embraced by other tourism-oriented countries that have adopted tourism as
economic and social tools to improve national wealth. Thailand, for instance, presented
its ‘colourful’ cultures and tribal lifestyles of ethnic groups from Burma, China and
Laos as its tourism attraction (Andriotis, 2003) in addition to its predominantly
agricultural income.
Under the Third Malaysia Plan, the government introduced a special provision relating
to the hotel industry in the Investment Incentive Act of1968. The Investment Incentive
Act included the granting of pioneer status, location incentives and abatement of
income tax for the establishment of new hotels and expansion and modernisation of
existing hotels (Economic Planning Unit, 1976). The government targeted 1.9 million
tourist arrivals into Peninsular Malaysia with an increase of 5per cent per annum, and
103,000 and 114,000 visitors into Sabah and Sarawak, respectively, by 1980. Besides
increasing promotional activities to achieve the target, a sum of RM 20 million was
provided to TDC to implement a project to establish a company providing management
and consultancy services in the tourism industry, a duty free shop in Pulau Pinang and
the construction of hotels in Kelantan, Johor and Terengganu.
Another promotional effort by TDC during the Third Malaysia Plan was the cooperation
between TDC and the Singapore Tourist Promotion Board, and the National Hotels,
Restaurants and Travel Agents Associations to integrate tourism promotion to increase
tourist arrivals into Malaysia. These aspirations and efforts to improve Malaysia’s
tourism industry for the country’s economic development and racial unity have shifted
Malaysia’s tourism image from the least attractive destination to one of the more
attractive destinations in the region. On May 20, 1987, the Ministry of Arts, Culture and
43
Tourism (MOCAT) was formed, and TDC was transferred from the Ministry of Trade
and Industry to this new ministry. This action was to streamline the roles and
responsibilities of tourism development on a national level.
2.5.4 The Fourth Malaysia Plan (1981-1985)
During this Malaysia Plan, following the success of TDC’s promotion activities in the
Third Malaysia Plan, the Malaysian Government was convinced that the tourism
industry was a significant income-generating sector for the country. This prompted the
government to develop tourist facilities in rural areas, such as the Tanjong Jara and
Rantau Abang projects (tourist destinations for viewing giant leatherback turtles
between May and August) in Terengganu (Economic Planning Unit, 1981)on the east
coast of Malaysia, as well as other projects in rural areas primarily populated by
indigenous people. Approximately RM40 million was allocated for the development of
a tourist complex at Tanjung Rhu in Pulau Langkawi, Kedah and the expansion of
Rantau Abang Visitor Centre in Terengganu (Economic Planning Unit, 1981).
Following the advice of foreign tourism consultants, TDC concentrated marketing
efforts on selected major markets (namely Japan, Australia, Hong Kong, New Zealand,
Germany and the United Kingdom) and explored new potential markets such as West
Asian countries, France and the U.S.A. This targeted marketing is a common practice
among tourism countries to raise revenue. Singapore, for instance, made provisions for
the Japanese market and addressed Japanese tourists’ preference such as room
requirements, food preferences and language difficulties (Din, 1982). These efforts
succeeded in increasing tourism revenues from the selected markets.
44
Within this period, the Malaysian government liaised with air transportation authorities.
TDC and the Malaysian Airline System (MAS) undertook joint promotional efforts to
promote Malaysia abroad. Their joint venture was a huge success. The growth in the
number of tourist arrivals and receipts were substantial. To promote a safe environment
for tourists, the Tourist Police Unit was established under the Royal Malaysian Police
during the Fourth Malaysia Plan. This effort was put forward to ensure tourists’ welfare,
safety and security.
2.5.5 The Fifth Malaysia Plan (1986-1990)
During the Fifth Malaysia Plan, Malaysian tourism policies focused on domestic
tourism to reduce foreign exchange outflows. The government noted a lack of tourism
promotion in the domestic market, and this led to an increasing number of Malaysians
travelling outside the country. Foreign exchange outflows increased from RM807
million in 1980 to RM1,525 million in 1984 (Andriotis, 2003). As a result, besides
actively promoting Malaysia to the international market, the Malaysian government also
put more promotional efforts on the domestic market.
Tourism promotion strategies during this period were based on four themes:
conventions, vacations, sightseeing and special interests. The completion of the Putra
World Trade Centre during this plan intensified Kuala Lumpur as the principal
convention centre and destination. Meanwhile, other destinations were promoted as
secondary destinations for smaller forums and exhibitions. The sightseeing theme
focused on the major cities of Kuala Lumpur, Georgetown in Pulau Pinang and Melaka.
The special interest campaign was promoted toward the national parks, caves and hills,
particularly the National Park in Peninsular Malaysia, the Kinabalu National Park in
45
Sabah and the Niah National Park in Sarawak. Concise and informative state and city
maps and guidebooks were produced and introduced by TDC during this period.
In terms of encouraging the private sector to participate in the tourism industry, tax
incentives under the Hotel Incentives section of the Investment Incentives Act (1968)
was further extended to both accommodation and non-accommodation projects. The
non-accommodation projects included investments in safari parks, zoos, recreation
centres and children’s playgrounds. Under the accommodation project, a new set of
incentives was created for two additional types of economy-priced accommodations:
lodging houses and rest houses (Economic Planning Unit, 1986).
Despite the short- to medium-term effects of the world economic slowdown and post
Gulf War scenario, the Malaysian government continued its emphasis on tourism
promotion and its resilient economy augured well for the long-term growth of its
tourism industry. The Malaysian government set up the Malaysian Tourism Promotion
Board (MTPB), also known as Tourism Malaysia to undertake the roles and
responsibilities previously carried out by TDC. The primary objective of MTPB is to
stimulate and increase the number of tourist arrivals into the country. In pursuit of this
objective, Tourism Malaysia continues to serve the needs of the tourism industry and to
spearhead marketing and promotional activities to place Malaysia on the tourism map.
2.5.6 The Sixth Malaysia Plan (1991-1995)
In the Sixth Malaysia Plan, the Malaysian government increased tourism allocation to
RM533.9 million, which was later revised to RM719.1 million during mid-term review
(Economic Planning Unit, 1991). The additional allocation was mainly to improve and
46
expand tourism facilities and infrastructure. During this period, tourism and distributive
trade grew at a double-digit rate (surpassing the original target), and contributed
significantly to greater output, investment and employment. Within the overall strategy
of improving the balance of payments accounts, tourism became an important foreign
exchange earner. This was largely attributed to the development of new and improved
tourism products, and an increase in accessibility to tourist destinations as well as
enhanced promotion and marketing efforts. The distributive trade sector continued to
provide a wide range of products at competitive prices to consumers in line with the
Government’s policy of maintaining stable prices for essential goods and services. This
was further facilitated by increased modernisation, which led to a more efficient
distributive system.
Besides granting various incentives to promote tourism investment, such as pioneer
status, investment tax allowance and income tax exemption for tour operators, the
Government established the Special Fund for Tourism, which was a revolving fund
amounting to RM200 million. Small and medium sized tourism related projects such as
motel and hotel renovations were eligible for soft financing under the Fund. By the end
of 1995, about RM206.1 million was used to finance 182 tourism-related ventures
(Economic Planning Unit, 1991).
In 1992, the Government established the first National Tourism Policy (NTP),
consisting of broad policies for the planning, development and marketing of tourism.
The policy objectives in NTP were used as the guiding principles to generate foreign
policies, encourage equitable economic and social development, promote rural
enterprises, generate employment, accelerate urban/rural integration and cultural
47
exchange, encourage participation in the tourism sector by all ethnic communities, and
ultimately forge national unity and create an improved image of Malaysia
internationally. The policy also emphasised the “sea, sand and sun” market segment of
Malaysia’s tourism industry. The focus was on tourism product development, including
fly-drive holidays, riverine tourism, eco-tourism, agro-tourism, cultural and heritage-
based tourism, Meeting, Incentive, Convention and Exhibition (MICE) and special
interest tourism. In general, the policy aimed on exploring on the country’s diverse
nature- and culture-based attractions. Besides, NTP also recommended promoting
Malaysia as a shopping destination. This was exemplified by the heavy investments in
promoting Malaysia as a shopping haven through nationwide Mega Sale carnivals.
During the same year, Malaysia increased its cooperation with ASEAN’s national
tourism authorities to promote multi-destination travel to the region. The inauguration
of “Visit ASEAN Year 1992” was an example of cooperative marketing by tourism
agencies of the six-member ASEAN countries (Malaysia, Thailand, Indonesia, Brunei,
the Philippines and Singapore). To continue promoting Malaysia, 1994 was designated
“Visit Malaysia Year” to follow the same campaign success in 1990.
2.5.7 The Seventh Malaysia Plan (1996-2000)
For the Seventh Malaysia Plan, tourism development focused on expanding the range of
activities, products and markets, thereby contributing further to foreign exchange
earnings and savings. Distributive trade continued to be modernised and rationalised in
line with changing consumer preferences and this took into account increasing foreign
investment in this sector. During the Seventh Plan, the tourism sector focused on
improving existing strategies as well as introducing new ones which would enhance the
48
image of Malaysia as a highly diversified and competitive tourist destination (Small and
Medium Enterprise Corporation Malaysia, 2011). The strategies included:
1. Diversifying into new products and services to cater for the varying demands
and interests of international and domestic tourists,
2. Ensuring more effective promotion and marketing for both the foreign and local
markets,
3. Encouraging private sector investment and participation in innovative tourism
products as well as special projects and events,
4. Increasing the involvement of the local population, especially small
entrepreneurs, in the development of distinct and localised tourism products and
services,
5. Improving and facilitating access into and within the country,
6. Providing the requisite infrastructure and amenities at designated tourist sites,
and
7. Focussing on formal as well as on-the-job skills training in order to meet the
rising manpower demand.
However, between 1997 and 1998, Malaysia’s tourism industry was substantially
affected by a series of uncontrollable factors. In 1997, tourist arrivals from Singapore
(Malaysia’s biggest market) dropped due to the dispute of an agreement of railway
services and tourism promotion between Malaysia and Singapore. Soon after that, the
dengue outbreak, the Coxsackie B virus and the cholera epidemic all descended on
Malaysia. Indonesia’s mass forest burning also adversely affected Malaysia. As a result,
Malaysia suffered 30 to 40 per cent holiday cancellations. The incidents and
49
subsequently the economic downturn not only affected Malaysia, but the Asian region
as a whole.
In 1998, the National Economic Recovery Plan was established to stimulate Malaysia’s
economy. The tourism industry faced many issues such as increasing competition from
developing countries like Vietnam, Cambodia, China and India. At the same time,
Thailand, Singapore and Hong Kong launched aggressive promotion efforts to attract
tourists, while Malaysia slashed its tourism promotional activities for economic reasons.
The Government reduced the tourism budget from RM 79 million in 1997 to RM 63
million in 1998. Furthermore, currency depreciation also hit Malaysia’s main tourism
markets such as Japan, Thailand and Indonesia, and caused tourist arrivals from these
regions to decline.
2.5.8 The Eighth Malaysia Plan (2001-2005)
Following the economic slowdown and the success of the National Recovery Plan,
Malaysia’s tourism industry recovered. With limited financial resources, Malaysia
devised strategic plans and effective promotions through the use of electronic media.
Marketing and promotional efforts were focused on countries that were not heavily
affected by the regional economic downturn. Australia, Hong Kong, Taiwan, India,
China, Europe, the USA and West Asia all helped to boost tourist arrivals into the
country.
During the Eighth Malaysia Plan, the Government’s tourism development allocation
reached RM 1 billion. According to Malaysia’s Prime Minister’s Department (2008),
the allocation focussed on a combination of programmes that projected maximum
50
returns to the industry and economy. The major programmes that were implemented
included the preservation and conservation of national historical sites, beautification
and environment protection, tourism product development as well as the provision of
medium budget accommodation and tourism-related infrastructure facilities.
During this period, the Government identified specialised products and services for the
tourism industry. Eco-tourism, agro-tourism, homestay programmes, cultural heritage
tourism, thematic events, MICE (for conventions), sports and recreation, educational
tourism, and Malaysia My Second Home programme were intensified to increase tourist
arrivals, expand tourists’ lengths of stay and boost tourists’ spending. The Eighth
Malaysia Plan saw the development of a more robust tourism industry, contributing to
greater foreign exchange earnings as well as generating new businesses and
employment opportunities.
In 2001, the Rural Tourism Master Plan was established by MOCAT. Its objective was
to target increased visitor spending in rural areas through long stay/high spending to
create a new brand of tourist experience. This was to be achieved by building the two
main strengths of Malaysia: its beautiful countryside and friendly people. The Master
Plan featured attractive scenery of a lush tropical landscape, offered activities and
amenities for tourists to utilise and enjoy safely, provided new and improved
accommodations and nurtured a smiling, friendly customer care approach. A few
priority districts (one in each state) were carefully selected as pilot model areas with
recommended improvement in rural tourism infrastructure (MOCAT, 2001). This plan
would cost RM 75 million for Rural Tourism Product Development and RM 5 million
51
for Human Resource Development over a five-year period, but its implementation was
delayed due to financial constraints (Hamzah, 2004; MOCAT, 2001) .
Later in 2003, the Second National Tourism Policy (2003-2010) was designed to
emphasise Malaysia’s unique multiculturalism as its major selling point. Its main output
is to provide the mechanism to transform Malaysia’s low-yield tourism to that of high
yield. Intra-region cooperation was seen as a major course of action in increasing
tourism receipts (Hamzah, 2004).
2.5.9 The Ninth Malaysia Plan (2006-2010)
For the Ninth Malaysia Plan, the government strengthened Malaysia’s position as the
preferred global tourist destination to ensure that the tourism industry continued to be
an important source of foreign exchange earnings, entrepreneurship development and
employment generation. A more integrated approach to tourism planning and
implementation was implemented. Emphasis was placed on preserving and enhancing
existing natural and cultural assets that are susceptible to environmental damage. As
such, to implement the strategies under this plan, the government formulated
sustainable tourism development, enhancing the development of innovative tourism
products and services, encouraging and facilitating domestic tourism, intensifying
marketing and promotion activities, enhancing human resource development, and
ensuring the comfort, safety and wellbeing of tourists.
Besides specialised tourism products and services (i.e., eco-tourism, agro-tourism
etc.),which were intensified in the previous Malaysia Plan, the Government also
initiated efforts to promote Malaysia as a preferred location for feature films, television
52
commercials and documentaries. The Government’s objective with this new tourism
product, the Film and Media Location was the additional avenue for international
publicity and exposure for many of Malaysia’s holiday destinations and tourist
attractions (Economic Planning Unit, 2006).
The Government’s development allocation for the tourism industry under the Ninth
Malaysia Plan increased to RM 1.8 billion. The Government focused on the provision
of adequate infrastructure, largely upgrading and maintaining tourism-related facilities
and amenities. Attention was also given on improving location accessibility through
improved air and surface transport, including hassle-free travel with online visa
applications and multiple entry permits. Flight frequencies and capacities between
Malaysia and specific markets were increased to facilitate inbound travellers. The
liberalisation of air services in the ASEAN region in 2008 allowed greater access to
ASEAN capitals, thus increasing regional travels, which showed significant increase of
tourist arrivals from ASEAN countries. The Government also expanded the Kota
Kinabalu Airport in Sabah as the nation’s second Low Cost Carrier (LCC) terminal
after KLIA.
Under the Ninth Malaysia Plan, the Government also realised the importance of having
the Tourism Satellite Account (TSA) to quantify the contribution of the tourism
industry to economic growth, income and investments. TSA also supported subsequent
policy making and readjustment of strategies and programmes for the tourism industry.
Thus, the government developed TSA mechanism to ensure an integrated approach in
project planning and implementation (Economic Planning Unit, 2006).
53
2.5.10 The Tenth Malaysia Plan (2011-2015)
The Tenth Malaysia Plan is the current recent Malaysia Plan. It recognises the
importance of the tourism sector as a driver of economic activity that will contribute
towards the growth and distribution of wealth to the economy. The Tenth Malaysia
Plan’s target is to improve Malaysia’s position to be in the top 10 in terms of global
receipts, and to increase the sector contribution by 2.1 times, contributing RM115
billion in receipts by 2015 (Economic Planning Unit, 2011). Key strategies include:
catering to the various market segments, whilst leveraging existing tourism products
such as the Pulau Pinang and Kinabalu Park, Sabah (which has been classified as a
UNESCO Heritage site).
In addition, the tourism sector focuses on eco-tourism (as the country has a comparative
advantage arising from Malaysia’s natural resource endowment), while ensuring the
quality and sustainability of the tourism products. Arising from this, Malaysia hopes to
be able to establish and capture a greater share of the global tourism market, especially
in eco-tourism. This would be accomplished via domestic and regional partnerships as
start up and running costs can be low compared to many other forms of industry
development.
The Performance Management and Delivery Unit (PEMANDU) identified tourism
amongst the 12 National Key Result Areas (NKRAs). These are national priority areas
of focus identified under the Government Transformation Programme (GTP). The goal
of the Tourism NKRA is to formulate initiatives to transform the nation into a high-
income economy though it’s Economic Transformation Programme (ETP).
54
PEMANDU has identified twelve big Entry Point Projects (EPPs) on tourism industry
that could possibly generate RM28 billion in GNI and create another 200,000 new jobs
by 2020. The EPPs are based on five travel themes, i.e. nature adventure and culture
diversity, family, luxury, events and business related which comprises of meetings,
incentives, conventions and exhibitions (MICE). The success of the EPPs includes
support from both the private and public sector in funding and supportive policies from
the federal and state government. Such funding would include the corporate sponsorship
from the private sector in maintaining the heritage sites and involved in marketing to
target growth markets especially Russia, India, China and the Middle East.
The above discussion has look through the economic development strategies
implemented in all ten Malaysia Plans. During these Malaysia Plans, Malaysian
government has developed three specific policies focused on tourism development
which bring great impact to the industry – National Tourism Policy (1992), Rural
Tourism Master Plan (2001) and Second National Tourism Policy (2003-2010). Table
2.7 below provides a summary of the Malaysian government’s tourism-specific
initiatives undertaken during each plan.
55
Table 2.7: Malaysia's Tourism Specific Economic Planning and Initiatives, 1965-
2015
Malaysia Plan Tourism-Specific Initiatives
Budget Allocation
(RM Billions)
Impact on tourism industry
Tourist Arrivals (Billions)
Tourist Receipts
(RM Billions)
1st Malaysia Plan (1965-1970)
No initiatives on tourism No allocation
N/A N/A
2nd Malaysia Plan (1971-1975)
• Provision of basic tourism infrastructure • Establishment of Tourist Development
Corporation (TDC)
0.0085 1.4 0.02
3rd Malaysia Plan (1976-1980)
• Establishment of management and consultancy services for tourism
• Special provision for hotel industry, location incentives and abetment of income tax for new hotels and expansion of existing hotels
0.02 2 0.06
4th Malaysia Plan (1981-1985)
• Improvement of facilities located at all key tourism destinations
• TDC liaisons with Malaysia Airlines (MAS) undertook joint-promotional strategy
0.04 3.1 0.10
5th Malaysia Plan (1986-1990)
• Intensification of domestic tourism campaign • Focused on four-themed campaign;
conventions, vacations, sightseeing and special interest.
0.14 7.4 0.90
6th Malaysia Plan (1991-1995)
• Establishment of a special fund for tourism; small and medium-sized related projects
• National Tourism Policy (1992)
0.53 7.4 0.90
7th Malaysia Plan (1996-2000)
• Expansion of a range of tourism activities, products and markets
0.60 10.2 17.3
• Focus on innovative tourism products and services
8th Malaysia Plan (2001-2005)
• Transition from low yield to high yield- to increase the expenditure yields of tourist while in Malaysia
• Rural Tourism Master Plan (2001) • Second National Tourism Policy (2003-2010)
1.09 16.4 32.0
9th Malaysia Plan (2006-2010)
• Increase of flight frequencies and liberalization of air services in ASEAN region
1.8 24.6 56.5
10th Malaysia Plan (2011-2015)
• Intensification on 5 travel themes ; nature adventure and culture diversity, family, luxury, events and business related which comprises of MICE
9.7 N/A N/A
Source: Economic Planing Unit (1966, 1971, 1976, 1981, 1986, 1991, 1996, 2006, 2008,
2011), Tourism Malaysia (2013b), Marzuki (2010)
56
2.6 Tourism Industry Performance in Malaysia
The tourism policies developed and implemented by the Malaysian government through
Malaysia’s five-year strategic plans since the Second Malaysia Plan (1971–1975) have
resulted in positive achievements in Malaysia’s tourism industry. The combination of
the unique features of Malaysia’s geographical structures, its natural resources and its
multiracial and multicultural society has become the competitive advantage for the
Malaysian tourism industry. It has successfully outperformed other destinations,
particularly the Southeast Asian countries in receiving international tourists and this has
contributed to its national foreign exchange earnings.
In comparison with other Southeast Asian countries, Malaysia is a latecomer to the
industry. Other Southeast Asian countries have been actively promoting their tourism
industry since the 1950s. For example, the Philippines formed its Board of Travel and
Tours Industry in 1956, while both Thailand and Singapore established their tourism
boards in 1960 and 1964 respectively. Conversely, Malaysia established its TDC in
1972 to promote Malaysian tourist destinations.
From the Second Malaysia Plan (1971–1975) to the most recent Tenth Malaysian Plan
(2011–2015), the Malaysian government has concentrated a great deal on the
development of the tourism industry in Malaysia. The provision of basic tourism
infrastructure and the establishment of TDC during the Second Malaysia Plan (1971–
1975) resulted in significant growth in the Malaysian tourism industry. It grew from
attracting fewer than 500,000 tourists in the beginning of 1970, to receiving an increase
of more than 305 per cent to 1,529,915 tourists, with total receipts of RM 619 million in
1980. According to the TDC, the Asian region continues to be the major contributor of
57
visitors to Peninsular Malaysia, accounting for 57.4 per cent of the overall tourists to
Peninsular Malaysia.
Another significant effect of Malaysia’s tourism polices is on arrivals from international
tourists. Resulting from improvements on facilities and joint promotional strategies with
Malaysia Airlines Systems (MAS) targeting the international market during the Fourth
Malaysia Plan (1981–1985), total international tourist arrivals to the country increased
from fewer than 2 million in 1980 to more than 2.9 million over between 1981 to 1985
period. Tourist receipts also increased from RM 618.9 million in 1980 to RM 1,412.3
million in 1985 (Tourism Malaysia, 2013b). Table 2.8 depicts the number of
international tourist visits to Indonesia, Malaysia, Philippines, Singapore and Thailand
during 1967 and 2011. Malaysia recorded the lowest number of international tourist
arrivals in 1967, lagging behind Thailand, Singapore, Philippines and Indonesia.
However, in 2011, Malaysia received the highest influx of international tourists.
Table 2.8: International Tourist Arrivals to Southeast Asia, 1967 and 2011
Destination 1967 (Millions)
2011 (Millions)
Indonesia 0.032 7 Malaysia 0.025 24.7 Philippines 0.120 3.5 Singapore 0.150 11.6 Thailand 0.261 19.1
Source: Din (1982), Singapore Tourism Board (2013), Ministry of Tourism and Creative Economy of The Republic of Indonesia (2013), Department of Tourism, Philippines (2012), Office of Tourism Development, Thailand (2012) Tourism Malaysia (2013c)
Table 2.9 demonstrates that the industry has performed favourably throughout the years,
as reflected by the growth of tourist arrivals and expenditures based on the proportion of
the international target market. ASEAN countries constitute the largest source of
tourists and account for more than 70 per cent of total tourist arrivals into Malaysia
58
particularly from Singapore, Indonesia, Thailand and the Philippines. This resulted from
extensive promotion to international markets. Further, the prosperity and high economic
growth rates of Asian countries encouraged regional travel (Chon, Singh & Mikula,
1993).
Throughout the 1990s, the volume of tourist arrivals into Malaysia grew by 53.6 per
cent to 7,445,908, and total tourist receipts reached RM 4.5 billion. This was principally
attributed to the Visit Malaysia Year 1990 campaign during the Fifth Malaysia Plan
(1986–1990). The Visit Malaysia Year 1990 campaign generated substantial awareness
and recognition of Malaysia as a leading tourist attraction and foreign investment
destination among foreign holidaymakers and business tourists. In 1995, there were
arrivals in Malaysia of tourists from West Asia. This resulted from the Islamic tourism
promotion implemented by MOTOUR to encourage the Muslim community to visit
Malaysia (Tourism Malaysia, 2013c).
The Malaysian tourism industry was affected during the economic turmoil from 1997
until 1999. However, actions were taken and recovery was made because of successful
strategies implemented by the Malaysian government through the National Economic
Recovery Plan. The Malaysian government re-focused its international market to the
countries less affected by the regional economic downturn such as Australia, India,
China, countries in Europe, the United States and countries in West Asia. This approach
has successfully increased the number of visitors from such countries. Other strategy
was to increase international tourist’s expenditure while in Malaysia. Then, during the
Eighth Malaysia Plan (2001–2005), the focus was to increase the expenditure yields of
tourism in Malaysia (Economic Planning Unit, 2001). Thus, the expansion of tourism
59
activities, products and services shows an increment from RM 0.05 billion in 1980 to
RM 72.6 billion of tourist expenditure in 2011, as indicated in Table 2.9.
Table 2.9: Tourist Arrivals into Malaysia by Country of Origin, 1980 - 2011
Indicator 1980 1985 1990 1995 2000 2005 2011 Number of Tourist Arrivals (million)
2.25 3.22 7.4 7.5 10.2 16.4 24.7
Tourist Expenditure (RM,billion)
0.05 0.1 0.7 2.4 23.6 41.1 72.6
By Country of Origin (per cent)
ASEAN 70.2 76.7 73.8 72.9 70.4 76.8 76.6 China - - - - 4.2 3.8 4.6 Japan 3.8 3.9 6.8 5.8 4.5 1.9 1.7 Australia 3.7 2.7 2.0 2.0 2.3 1.5 2.4 United Kingdom 2.5 2.5 2.6 2.3 2.3 1.5 1.7 Taiwan 0.9 0.4 0.8 1.6 2.1 1.3 0.8 India 1.7 1.8 n/a n/a 1.3 1.2 2.8 West Asia - - - 11.5 0.5 1.0 0.9 Others 16.8 11.9 14.8 17.0 12.4 11.0 8.5
Source: Economic Planning Unit (1986, 1996), Tourism Malaysia (2013c)
The industry not only creates considerably high multiplier effects and linkages in the
Malaysian economy, but it also fosters national integration and unity (GOM, 1991).
Presently, with continuous efforts to stimulate tourism industry performance, the
tourism industry in Malaysia has become the second highest foreign exchange earner to
the national economy and is experiencing tremendous growth from year to year. The
revenue earned from international tourism plays a pivotal role in directing the
Malaysian economy to higher growth (Sadi & Bartels, 1997).
2.7 TSMEs in Malaysia
The continuous efforts to stimulate the tourism industry by the Malaysian government
has created a positive effect on the business activities of TSMEs. With the increase in
international tourist arrivals, the tourism industry has created business potential and
60
diversification of tourism products and services, particularly by TSMEs in MalaysiaIn
Malaysia, SMEs contributed only 28.5 per cent to the country’s Gross Domestic
Product (GDP) in 2010 compared to the same firms in Singapore and Canada, which
contributed over 50 per cent of their countries’ GDP (Industry Canada, 2013; Spring
Singapore, 2013). Nevertheless, SMEs in Malaysia form the bulk of the businesses in
three major sectors in Malaysia: manufacturing, services and agriculture. Based on the
recent Economic Census Survey 2011, with the reference year 2010 conducted by the
Malaysian Department of Statistics (2011), there are 645,136 SMEs, representing 97.3
per cent of total businesses in 2010 and providing employment to 52.7 per cent of the
total workforce. Table 2.10 lists the key indicators of SMEs in the country for 2010.
Table 2.10: Key Indicators of SMEs in Malaysia, 2010
Indicators Total Large SMEs Number of establishments 662,939 17,803 645,136Gross output (RM million) 1,777,317 1,270,228 507,089Value added (RM million) 707,489 493,568 213,921Employment (persons) 6,963,973 3,294,714 3,669,259
Percentage (%) Number of establishments 100.0 2.7 97.3Gross output 100.0 71.5 28.5Value added 100.0 69.8 30.2Employment 100.0 47.3 52.7
Source: Department of Statistics. Census 2011(2012b)
Table 2.11 presents the distribution of SMEs in Malaysia according to sector. Many of
the SMEs in Malaysia are in the services sector, with more than a third of the firms
involved in the tourism industry in 2010. SMEs in the manufacturing and agricultural
sectors make up more than 86.6 per cent of overall SMEs in 2005, and increased to 90
per cent in 2010 (Department of Statistics, 2012b).
61
SMEs in the services sector, particularly in the tourism industry increased from 100,637
firms (or 21.1 per cent of overall SMEs) in 2005, to 239,110 firms (41.1 per cent of
growth) in 2010. Thus, TSMEs make a significant portion of SMEs in Malaysia, and
play a big role as the backbone in Malaysia tourism industry.
Table 2.11: Distribution of SMEs by Sectors, 2005 and 2010
Sector 2005 % 2010 % Manufacturing 39,373 7.2 57,144 8.9 Agriculture 34,188 6.2 7,007 1.1 Services: -Other services 374,069 68.2 341,875 52.9 -Tourism services 100,637 18.4 239,110 37.1
Total 548,267 100.0 645,136 100.0 Source: Malaysian Department of Statistics, Census 2005, 2011 (2012b; 2006)
Generally, the investment by the government during the Malaysian Plans particularly
the Sixth, Seventh and Eighth Malaysia Plans has played an important role in the
growth of TSMEs because Malaysian government aggressively invested in hotels and
relevant tourism and recreation projects. Government investment increased to RM 8.8
billion in the Sixth Malaysian Plan (1991–1995), and to RM 18.2 billion during the
Seventh Malaysian Plan (1996–2000) (Economic Planning Unit, 1991, 1996). During
the Seventh Malaysian Plan (1996–2000), the government implementation of the
expansion of a range of tourism activities, products and marketing by spending RM
484.2 million increased the number of middle-cost hotels operated by TSMEs
(Economic Planning Unit, 1996). This was the result of the need to support the
increasing demand from both and foreign domestic tourists because of the aggressive
actions taken by the government to increase the number of tourists in Malaysia. The
number of small-sized and medium-sized hotels increased from 1,220 in 1996 to 1,492
in 2000, the average hotel occupancy also increased by 55 per cent in 2000 because of
this aggressive action (Economic Planning Unit, 2006
62
In line with the country’s vision to become a developed country by 2020 (Economic
Planning Unit, 1991), the Government realises the importance of developing a group of
diverse and competitive SMEs as a fundamental part of the national economy including
in tourism industry. The Government is committed to develop competitive and resilient
SMEs across all sectors, and an SME development framework has been developed and
implemented during the Second Industrial Master Plan (IMP2) (1996–2005) in 1996
(MITI, 1996). Following on this commitment, under the Eighth Malaysia Plan (2000-
2005), the Government provided a wide range of assistance programmes for TSMEs
(Economic Planning Unit, 2008). Under the 15-year blueprint of the Third Industrial
Master Plan (IMP3) (2006-2015), the Government outlined five strategies particularly
focused to support the development of diverse and competitiveness of SMEs in all
sectors (MITI, 2006; Small and Medium Enterprise Corporation Malaysia, 2011) .
These national development agendas are geared to SMEs in all sectors in the country’s
stride towards broadening the sources of growth and sustaining the growth momentum.
These SME policies have contributed to significant growth on TSMEs from 2005 to
2010, as indicated in Table 2.13. TSMEs in Malaysia are engaged in tourism-related
businesses. They offer tourism products and services, and have unique characteristics
compared to tangible manufactured products. Following the guidelines introduced by
international organisations such as the United Nations World Tourism Organization
(UNWTO), Eurostat, and the Organization of Economic Co-Operation and
Development (OECD), the Malaysian Government applies the Tourism Satellite
Accounts (TSA) to characterise tourism-specific products from suppliers’ perspectives.
The categorisation of tourism products are as follows:
• accommodation services,
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• food and beverage serving services,
• passenger transport services,
• travel agency, tour operator and tourism guide services,
• cultural services, recreation and other entertainment services, and
• miscellaneous tourism services (i.e., Personal care and salus Per Aqua (SPA),
camping sites, Zoo, museum and theme parks).
Table 2.12 presents TSMEs activities in 2010. TSMEs are the backbone of the
country’s tourism industry with 239,110 active establishments. There are 142,721 firms
(59.7 per cent) offering food and beverage services, 40,025 firms (16.7 per cent)
offering transportation services and other miscellaneous tourism services. Meanwhile
,accommodation services; arts, entertainment and recreation services; and travel agency,
tour operator and tourism guide services are offered by 19,643 TSMEs (8.2 per cent of
total TSMEs).
Table 2.12: Distribution of TSMEs, 2010
TSMEs % Accommodation services 2,817 1.2 Transportation services 40,025 16.7 Art, entertainment and recreation services 6,217 2.6 Food and beverage service 142,721 59.7 Miscellaneous tourism services 36,721 15.4 Travel agency, tour operator and tourism guide services 10,609 4.4
TOTAL 239,110 100.0 Source: Malaysian Department of Statistics, Census 2011(2012b)
Table 2.13 compares TSME performance indicators with those of other SMEs in the
services sector in Malaysia in 2010. TSME gross output was relatively low at RM
70,846 (24.7 per cent of total output) compared to that of other SMEs in the services
sector (RM215,794 million or 75 per cent of total output). TSMEs contributed
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RM31,043 (18.7 per cent of total value added). In 2010, of the 2.6 million workers in
SMEs in the services sector, TSMEs employed about 991,419 workers (38.1 per cent of
total employment in SMEs in the services sector). The tourism industry employs more
than a third of employees in the services sector, is the second highest earner in foreign
exchange and national income (MOTOUR, 2011). TSMEs thus play a big part in
contributing income to the industry and the nation.
Table 2.13: Key Performance Indicators of TSMEs, 2010
Source: Malaysian Department of Statistics, Census 2011(2009, 2012b)
Table 2.14 shows the number of TSMEs based on size in 2003 and 2010. The number
of TSMEs establishments showed an apparent increase from 2003 to 2010. One of the
factors that contribute to this increase are the Government’s incentives such as the
special fund for tourism on SMEs-sized related projects during the 6th Malaysia Plan
(1991 – 1995) and the range of tourism activities, products and markets during the 7th
Malaysia Plan (1996 – 2000). The tourism industry saw an increase of more than 80 per
cent of establishments of various sizes. The dominance of micro-sized firms in the
tourism industry in 2003 continued in 2010, with 66.1 per cent and 83.8 per cent of
micro firms respectively. In terms of the proportion of small and medium-sized
enterprises, in 2010 the percentage is getting smaller compared to 2003.
Indicators
Total SMEs in the Services
Sector TSMEs Other SMEs
services
Total % Total % Total % Number of establishments 580,985 100.0 239,110 41.1 341,875 58.9 Gross output (RM million) 286,640 100.0 70,846 24.7 215,794 75.3 Value added (RM million) 165,284 100.0 31,043 18.7 134,241 81.3 Employment (persons) (million) 2,600,000 100.0 991,419 38.1 1,608,518 61.9
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Table 2.14: Distribution of TSMEs by Size, 2003 and 2010
Source: Malaysian Department of Statistics, Census 2011(2012b)
2.8 Concluding Remarks
This section has discussed the multiethnic population, culture, and natural attractions of
Malaysia that have served as Malaysia’s competitive advantage in positioning Malaysia
as the best worldwide holiday tourism destination. To develop and sustain the tourism
industry’s performance in Malaysia, the Malaysian government has played the vital role
in planning, gearing and developing the industry. The government has implemented
various and continuous tourism-specific initiatives through its five-year economic plans
since the Second Malaysia Plan (1971–1975) until the recent Tenth Malaysia Plan
(2011–2015).
The Sixth Malaysia Plan (1991–1995) played a particularly prominent role in
developing the tourism industry in Malaysia because of the establishment of the first
National Tourism Policy (NTP), which served as the guiding principle for planning,
developing and marketing the tourism industry in Malaysia. The National Eco-tourism
Plan (1996) was established during the Seventh Malaysia Plan (1996–2000); the Rural
Tourism Master Plan (2001) was established during the Eighth Malaysia Plan (2001–
2005); and the second NTP (2003–2010). Each of these tourism-specific policies was
established to focus on the needs to increase tourism industry performance based on
tourism products and services.
Size 2003 2010 Total % Total %
Micro 7,233 66.1 200,402 83.8 Small 3,033 27.8 35,098 14.6 Medium 674 6.1 3,610 1.6 Total TSMEs 10,940 100.0 239,110 100.0
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Besides focusing on tourism products and services, the Malaysian government has
acknowledged the importance of TSMEs in the tourism industry’s performance. Lists of
financial and non-financial programmes have been established to equip TSMEs’
performance. This action was taken to further prosper Malaysian TSMEs’ performance
and to increase business longevity to realise the government’s plan for the tourism
industry in Malaysia.
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CHAPTER THREE
LITERATURE REVIEW
3.1 Introduction
The tourism industry’s business environment is continuously changing due to global
phenomena such as the transformation of information technology, terrorism, global
warming and natural disasters. These factors have increased the demand for
environmentally friendly holidays, and differentiated and niche tourism products for
travellers. These significant changes in the tourism industry have contributed to
increased competition among tourism firms, particularly TSMEs. The management and
operation of TSMEs has changed quite dramatically. The implication of these changes
has created a demand for TSMEs to seek manners in which to increase their competitive
advantage to survive in the tourism industry’s business environment.
Despite the low survival rate among TSMEs, based on the empirical studies, TSMEs
have been acknowledged for the role they play in economic contribution and social
development. Thus, government intervention is crucial to support TSMEs’ performance.
As discussed in Chapter 2, the Malaysian government has implemented extensive
tourism economic development plans to support TSMEs’ performance to realise the
country’s tourism industry growth. There is a range of factors, both internal and
external, that influence the performance and development of TSMEs. Therefore,
determining which factors are influential is crucial for TSMEs’ survival and
performance.
The aim of this chapter is to provide a theoretical platform for the analysis of factors
affecting the performance of TSMEs. First, the chapter begins by providing definitions
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to classify SMEs in Section 3.2. Next, this chapter discusses on the contribution of
TSMEs to the community development and national income in Section 3.3. It then
discusses the TSMEs challenges in Section 3.4. The theoretical platforms of TSME
performance are discussed in Section 3.5. Next, the chapter provides an overview of
empirical studies in both internal and external factors affecting the performance of
TSMEs in Section 3.6. After describing the theoretical platforms and empirical studies
in the factors affecting TSMEs, Section 3.7 reviews the established theory on the
success-factor models. Next, the chapter discusses the limitation of previous studies that
are relevant to the TSMEs development. Finally, Section 3.8 concludes the key point of
this chapter.
3.2 Definition of SMEs
There is no common international definition for SMEs. The definition of an SME
depends on a country’s physical and economic size, cultural situation, government
policy, and data collection measures to produce SME statistics (Chittithaworn, Islam,
Keawchana & Yusuf, 2011; Mohammad, 2012).
Table 3.1: Definitions of SMEs in Selected Countries
Country Definition of SMEs Sector Number of employees Assets
Australia Between 5 and 199 employees - New Zealand
Less than 20 full-time employees
-
Hong Kong Manufacturing Less than 100 employees - Others Less than 50 employees Japan Manufacturing Less than 300 employees Wholesaling Less than 100 employees - Retailing Less than 50 employees China Between 500 and 2000
employees Between Yuan$30 million and Yuan$300 million of annual sales
Singapore Less than 200 employees Less than $100 million of annual sales turnover
Philippines Less than 200 employees Less than P$60million on fixed assets
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Indonesia Less than 100 employees² Less than Rp$ 5 billion of fixed assests³
Malaysia Agriculture Between 5 and 50 employees Between RM$200,000 and less than RM$1 million of annual sales turnover
Manufacturing Between 5 and 150 employees Between RM$250,000 and less than RM$25 million of annual sales turnover
Services Between 5 and 50 employees Between RM$200,000 and less than RM$5 million of annual sales turnover
Thailand Manufacturing Less than 200 employees Less than THB$200 million of fixed assets
Services Less than 200 employees Less than THB$200 million of fixed assets
Wholesaling Less than 50 employees Less than THB$100 million of fixed assets
Retailing Less than 30 employees Less than THB$60 million of fixed assets
Sources: Schaper et al (2011); SPRING (2011), SMIDEC (2011), Hall (2011)
Table 3.1 compiles the definitions of SMEs used in selected countries. Some countries,
like Japan, Hong Kong, Malaysia and Thailand, define SMEs in various sectors to
differentiate the SMEs’ business activities such as manufacturing, wholesaling,
retailing, agriculture and services. This is because different sectors have different
characteristics, particularly in terms of the number of employees. Other countries such
as Australia, New Zealand, China, Singapore, the Philippines and Indonesia define
SMEs by the number of employees and assets value.
Most countries use the number of employees to categorise firms into small and medium
sizes. However, the number of employees what makes up small and medium-sized firms
differs across the countries. China, for instance, considers firms with employees
between 500 to 2000 employees to be small and medium-sized, while other countries
such as Australia, Singapore and Philippines consider firms with 5 to 200 employees to
be small and medium-sized. Countries such as China, Singapore, the Philippines,
Indonesia, Malaysia and Thailand have an additional measure of SMEs, which is assets
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value, but differ in terms of the range of assets value in differentiating the size of the
firms.
In Malaysia, SMEs are defined based on the number of full-time employees or the total
sales or revenue. Table 3.2 summarises the definitions of SMEs in Malaysia and these
definitions apply to the tourism industry, under the services category. SMEs are further
categorised into micro, small and medium enterprises.
Table 3.2: Definition of SMEs in Malaysia
Category Micro-enterprise Small enterprise Medium enterprise Manufacturing, Manufacturing-Related Services and Agro-based industries
Sales turnover of less than RM250,000 or fewer than five full-time employees.
Sales turnover between RM250,000 and RM10 million or between five and 50 full-time employees.
Sales turnover between RM10 million and RM25 million or between 51 and 150 full-time employees.
Services, Primary Agriculture and Information & Communication Technology (ICT)
Sales turnover of less than RM200,000 or fewer than five full-time employees.
Sales turnover between RM200,000 and RM1 million or between five and 19 full-time employees.
Sales turnover between RM1 million and RM5 million or between 20 and 50 full-time employees
Source: SMIDEC (2011)
The definitions are obtained from the National SME Development Council (NSDC), a
government agency primarily responsible for SME development in the country.
Malaysia follows countries such as Hong Kong, Japan and Thailand that define SMEs
according to sector. This study adopts the definition of SMEs by the NSDC to define
TSMEs.
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3.3 Contributions of TSMEs
3.3.1 Employment Creation
Operations of TSMEs, which include offering accommodation services, food and
beverages, guide services, recreational activities and other entertainment services
among others, are labour-intensive. Thus, the establishment of TSMEs at a particular
tourist destination creates job opportunities for the local community (Narayan & Prasad,
2010; Scheyvens & Russell, 2012). For instance, Wanhill’s (2000) study covering 216
projects over the period 1990-1995 in Wales, reveal that job creation in the principle
sectors of serviced accommodation, caravan and camping, restaurants, activity
attractions, and general attractions on the whole exceeded the employment targets
during UK’s economic recession. Overall, the European tourism industry depended on
TSMEs with over 99 per cent of firms employing fewer than 250 individuals.
3.3.2 Economic Growth and Development to Tourism Country
In terms of economic contribution, TSMEs play a crucial role in foreign exchange
earnings activities. This is why tourism countries such as European United (EU), China
and Australia focused on TSME performance (World Tourism Organisation, 2013).
This is because tourism worldwide is dominated by small businesses (Ateljevic, 2009;
Gartner & Lime, 2000; Peters & Buhalis, 2005). For instance, in EU countries there are
almost 99 per cent or 18 million companies in the tourism industry are classified as
SMEs (Cavlek, 2002) and 91 per cent in Australia (Australian Tourism Export Council,
2007). Thus, the dominancy of TSMEs in tourism will lead to higher tourist expenditure
in the industry. Furthermore, the predominance of TSMEs also will create prospects of
investment, notably in rural areas (Causevic & Lynch, 2013; Thomas, 2004; 2000).
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TSMEs have numerous economic and social benefits, as illustrated in Wanhill’s (2000)
study from Bali’s hotel industry. Three scales of tourism enterprises exist in Bali’s hotel
industry: large industrial, small industrial, and craft tourism. Various economic effects
in terms of increased earnings, foreign exchange, investment, job opportunities,
entrepreneurship, infrastructure, as well as the minimization of adverse social and
cultural effects were best met through small hotels (Wanhill, 2000). They are more
likely to market their services directly to guests rather than the tourism trade. Due to the
low entry barriers in the tourism industry, there is more local ownership of small hotels
and these hotels have better local supply connections.
Furthermore, a study conducted in Fiji on the impact of small-scale tourism enterprises
towards poverty alleviation in the country shows that small scale tourism enterprises
make positive contributions to revenue generation, job creation and community
development (Scheyvens & Russell, 2012). This indicates that tourism industry is
targeted as a development option because it is labour-intensive and shows a creditable
performance which gives weight to the importance of TSMEs in job creation and the
partnership approach (Ladkin, 2011; Scheyvens & Russell, 2012).
3.3.3 Diversification on Tourism Products
Compared to large companies, TSMEs are in a good position to cater to consumers’
increasing demand for more personalised services. Standardised tourism products are no
longer appealing to consumers, and tourists expect providers to tailor products and
services to their specific needs and tastes. TSMEs have greater flexibility to adapt their
services and products to tourists’ changing requirements and preferences compared to
larger companies (Akbaba, 2012; Sampaio, Thomas, & Font, 2012). TSMEs can play a
73
key role to be a part of the output experience for tourists through their ability to initiate
introductions to their neighbours, advise visitors about itineraries, provide narratives on
local history, culture, folklore and landscape, and play an active role in the advancement
of the community (Thomas, et al., 2011; Wanhill, 2002). Rafting activities in remote
areas and ATV tracks in deep jungle territory have made destinations more attractive
and appealing. These new attractions have enticed potential tourists (who are searching
for adventure activity) into visiting the destinations.
3.4 TSMEs Challenges
Even though TSMEs contribute to the growth of the tourism industry growth and the
national economy, they are bounded by significant limitations and barriers. The
following section details the challenges faced by TSMEs.
3.4.1 High Labour Turnover
High labour turnover is one of the main challenges faced by tourism enterprises within
the industry, where the relationship between employees and customers is critical
(Iverson & Deery, 1997; Kim, 2012). A high rate of turnover is also a significant factor
in decreased customer satisfaction, resulting in the loss of regular customers and the
good reputation of a business (Chen & Wallace, 2011; Choudhury & McIntosh, 2013).
Thus, labour turnover is often accepted as an inevitable part of the industry. It is
considered as a hindrance to achieving high levels of productivity and efficiency in
business operations (Alverén, Andersson, Eriksson, Sandoff, & Wikhamn, 2012; López-
Fernández, Serrano-Bedia, & Gómez-López, 2011). Furthermore, according to Cho,
Woods, Jang and Erdem (2006), employee turnover in the tourism industry is
consistently higher than in other industries, and is therefore the most problematic
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managerial topic. This is because people who leave represent a lost source and labour
turnover increase administrative costs for tourism businesses, creating severe
operational difficulties and reducing profitability (Marchante & Ortega, 2012). This
then reflects a symptom of poorly-managed organizations, affects organizational
morale, creates poor images in the labour market and makes it harder to recruit good
performers in the future (Bresciani, Thrassou, & Vrontis, 2012; Subramaniam,
Shamsudin, & Ibrahim, 2011; Yang, Wan, & Fu, 2012) .
3.4.2 Shortage of Financial Resources
According to Wanhill (2002), finance becomes an issue because TSMEs do not
engender confidence in lenders. In addition, they are susceptible to slumps in property
values because in many cases, TSMEs owners’ houses or business premises are put up
as collateral on their bank overdraft or loan. Commercial banks finance business
expansion with the intention of bringing the business to market flotation rather than ‘a
way of life’, which leaves TSMEs with high cost of finance from the retail banking
sector(G. Jennings, 2010). This also has relevance to public funding mechanisms, as
they tend to stress financial performance, which may demand a level of commitment
that owner-managers with lifestyle goals are unwilling to provide (Medina, 2005;
Olawale & Garwe, 2010).
3.4.3 Business Failure Rate
Wanhill (2000) warns of the controversial evidence about TSMEs and their high failure
rates. According to the Best Practice Forum, one in eight UK hospitality businesses fails
every year, suggesting hospitality is an extremely vulnerable business sector (Deakin,
2004). In its 1996 publication Tourism – Competing with the Best, the United
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Kingdom’s Department of National Heritage (1996) stated that TSMEs are more
vulnerable than larger firms to market pressure and so are less likely to invest in long-
term human resource strategies, which may cause short-term financial difficulties. This
is illustrated by Shaw and Williams (1990, cited in Wanhill, 2000), who identified many
family enterprises with little market stability, low levels of capital investment, weak
management skills and are resistant to change, all of which are barriers to successful
tourism development.
3.4.4 Limited Business Skills
TSMEs often have severe limitations with regards to marketing, delivering quality,
price policy, cost control and re-adjustment ability. For TSMEs, marketing may simply
consist of one or two advertisements in tourist brochures whose effectiveness is
unknown. Often, there is a profusion of literature, which does no more than ‘clutter’ the
marketplace so that its impact is dissipated through internal competition. The high exit
or marginal survival levels in the tourism sector is an indication of the magnitude of the
problem. TSMEs are often ‘price takers’ in the manner of the perfectly competitive
economic model because they are unaware of market trends.
It appears that transactions and information costs are taken as major barriers for TSMEs
in obtaining knowledge of their demand curves. This forces them to behave in a cost-
oriented manner in what is a market-oriented industry (Kotas & Wanhill, 1981). Their
ability to track market is limited to their weekly booking patterns and year-on-year
sales. When demand falls, they do not have a pro-active stance, unlike larger operators
who are able to get back into the marketplace with improved product offers. TSMEs
resort to cost-cutting, particularly staff hours, with owners and family labour putting in
more time to make up the differences. They may often have little empathy in managing
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staff or dealing with customers, and much of management time is spent ‘fire fighting’,
rather than developing the business.
3.4.5 Lifestyle Entrepreneur
Tourism entrepreneurs are labelled lifestyle entrepreneurs as they reject economic and
business growth. Self-employment and control are more important motives for these
entrepreneurs and disparities occur among TSMEs in relation to the aims and objectives
of the individual business, which are not always consistent with economic profit
objectives (Beaver, Lashley, & Steward, 1998; Strobl & Peters, 2013). Morrison and
Teixeira (2004) and Skokic and Morrison (2011) assert that the motivations among
tourism entrepreneurs are associated with family lifecycles, rejection of the corporate
way of life, and the general pursuit of a work/life balance, all of which contribute to the
majority of the TSMEs set up mainly to satisfy personal and family goals.
3.4.6 Supply Dominated by Family Business
A family-run business often consists of relatives as employees. Similarly in the tourism
industry, most TSMEs employ their own relatives as employees. This approach is
preferable as it is one way of offering jobs to relatives and at the same time a solution to
the difficulties in hiring casual and permanent staff. Getz and Carlsen’s study (2000)
focused on examining goals pertaining to enterprise start-ups by family and owner-
operated TSMEs, and they identified lifestyle and family related-goals as predominant.
However, there is also recognition that the business should be profitable. From the
survey, most respondents were uncertain about the ultimate disposition of their
businesses; only about one-third had definite succession plans to involve children or
other family members. Furthermore, half of the respondents did not have formal
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business goals and this fact supports high rates of failure among small business in
general. Many respondents did appear to be under-performing in the context of their
own performance targets. Their economic objectives seem to be being able to make
enough earnings to support the family. One major point of contention within the family
business relates to the benefit of being together on the job but this finding entails risk of
disharmony and often results in less free time to spend together on desired leisure
pursuits.
To date, research on TSME performance and operations is done extensively in
developed Western countries, particularly in the UK. Empirical studies from these
countries have highlighted and distinguished the outstanding characteristics of TSMEs.
The significance of social and non-economic factors in tourism entrepreneurship within
developed countries is a significant finding that is raised by tourism scholars. Several
managerial characteristics have been identified as distinguishing the operations of
TSMEs from larger enterprises. Among the most important of these features is TSMEs’
limited knowledge of the business environment.
Even though tourism industries in many tourism-focused countries are dominated by
TSMEs, and the growth of business establishments among lifestyle entrepreneurs is
increasing, they still face major barriers in handling the businesses. The challenges and
limitations faced by TSMEs as discussed above affect their growth and performance,
and should be addressed.
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3.5 Theoretical Foundations
3.5.1 Resource-based Theory
Resource-based theory has been applied by strategic management scholars as the
foundation for studying small business performance. According to the resource-based
theory, venture resources in the form of capabilities, assets, and skills provide
competitive advantage and underpin firm’s performance (Barney, 1991; Grant, 1991;
Peteraf, 1993). In other words, resource-based theory hinges on the resources and
capabilities of the firm as an underlying factor of performance. Findings from Chandler
and Hank’s study (1994) on small manufacturing businesses demonstrate the link
between the availability of resource-based capabilities and venture performance. An
abundance of capabilities in the firm ensures survival, rapid growth and profitability
(Chandler and Hanks, 1994). The centrality of the business owner in the operation of
the firm cannot be overemphasised (Lerner and Haber, 2000). To the extent that the
business owner makes all the important decisions, his/her skills become a critical asset
on which the success of the firm depends. Implicitly, when the skill set is stronger, the
performance of the business will be higher (Lerner and Almor, 2002).
The resource-based perspective argues that sustained competitive advantage is
generated by the unique bundle of resources at the core of the firm (Barney, 1991;
Conner and Prahalad, 1996). In other words, the resource-based view describes how
business owners build their businesses from the resources and capabilities that they
currently possess or can acquire (Dollinger, 1999). The term “resources” is broadly
conceptualised as “anything that can be thought of as a strength or a weakness” of the
firm (Wernerfelt, 1984, p. 172). The theory addresses the central issue of how superior
performance can be attained relative to other firms in the same market and posits that
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superior performance results from acquiring and exploiting unique resources of the
firm.
Implicit in the resource-based perspective is the centrality of the venture’s capabilities
in explaining a firm’s performance. Resources have been found to be important
antecedents to products and ultimately to performance (Wernerfelt, 1984). According to
resource-based theorists, firms can achieve sustainable competitive advantage from
such resources as strategic planning (Michalisin et al 1997; Powell 1992), management
skills (Castanis and Helft 1991), tacit knowledge (Polanyi, 1962, 1966), capital, and
employment of skilled personnel (Wernerfelt, 1984) among others. Resource-based
theorists (e.g. Barney 1991; Grant 1991; Peteraf 1993) contend that the assets and
resources owned by companies may explain differences in performance. Resources may
be tangible or intangible and are harnessed into strengths and weaknesses by
companies, which in turn lead to competitive advantage. The resource-based theory
continues to be refined and empirically tested (Bharadwaj, 2000; Hadjimanolis, 2000;
Medcof, 2000). Given that the resource-based view addresses the resources and
capabilities of the firm as an underlying factor of performance, it is found to be a
suitable theory to use in this study.
Because TSMEs belong to the service-based industry, they require tangible and
intangible resources to produce varied services and activities, such as accommodation,
transportation, shopping and recreation activities (McIntosh, Goeldner, & Ritchie,
1995). Considering tourism activities are highly related to physical and spatial factors
such as view, infrastructures and superstructures (Mill and Morrison, 1992), the type
and location of the venture are interrelated. Tangible resources such as venture location,
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attractiveness, and facilities are vital resources in tourism (Lundberg et al., 1995).
Furthermore, the capabilities of the tourism entrepreneurs in managing TSMEs and
exploiting these bundles of resources by creating niche markets within the tourism
industry are seen as creating the firm’s competitive advantage (Leonidou, Leonidou,
Fotiadis, & Zeriti, 2013). This activity is founded to be explicable with the RBV theory.
As such, many tourism researchers use the RBV theory to explain the importance of
these resources and the capabilities of TSMEs.
Researchers such as Saffu, Apori, Elijah-Mensah and Ahumatah (2008) use the RBV
theory in order to assess TSMEs’ resources and performance. Grounded in the human
capital theory and resource-based view, they examined the effect of entrepreneurs’
human capital and the venture’s resources on the performance of TSMEs in Ghana.
Results show that weak relationship between business resources and TSME
performance in Ghana. Owner-managers’ managerial skills have no influence on TSME
performance in Ghana because tourism entrepreneurs are more concerned on surviving
and maintaining sufficient income to ensure that firms produce satisfactory income.
However, their findings may be due to the fact that in Ghana, small tourism ventures
(especially those in rural areas) are micro-enterprises owned by families whose
decision-making processes are flexible, informal and unstructured. In such an
environment, more emphasis is on personal—and by implication, informal—approach,
and less emphasis is put on a formal, managerial approach. This study asserts that
higher education and previous entrepreneurial experience guarantee success for TSMEs,
and profitability in the tourism industry is contingent on innovation, customer service,
financial resources and cost control (Saffu, et al., 2008).
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Urbano and Yordanova (2008) proposed a conceptual model to explore the factors of
HRM practices in TSMEs in Spain. The conceptual model is based on the RBV of the
firm, and presents several characteristics of the firm and the person responsible for
HRM within the firm as determinants of the adoption of HRM practices in TSMEs.
According to RBV, resources that are valuable, rare, imperfectly imitable and not
substitutable by other resources can be sources of sustained competitive advantage.
They also argue that the adoption of HRM practices may lead to establishing sustained
competitive advantage by facilitating the development and utilisation of organisational
competence that are presumed to yield over competitors. The findings explain that in
the presence of an HR department, cooperation with other firms and possession of
previous experience in similar positions by the person responsible for HRM are
associated with greater adoption of HRM practices. Furthermore, in SMEs, the person
responsible for HRM is the owner/manager of the company and is also more likely to
adopt HRM practices. Their findings have added knowledge about the factors
influencing the adoption of HRM practices in TSMEs.
Das and Teng (2000) examined the role of firm resources in strategic alliances and put
forward a general resource-based theory of strategic alliances, synthesising the various
findings in the literature on alliances from the RBV theory. They used the
organisational learning model, which explains that most firms engage in strategic
alliances either to acquire the other’s organisational know-how, or to maintain one’s
own know-how while benefiting from others’ resources. The nature of the firm’s
resource characteristics - imperfect imitability, and imperfect substitutability - makes
strategic alliances an important involvement for firms. RBV suggests that the rationale
for alliances is the value-creation potential of firm resources that are pooled together.
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Thus, according to Das and Teng’s findings, partner resource alignment directly affects
collective strengths, and ultimately contributed to alliance performance.
Bharadwaj (2000) has provided arguments on how the resource-based view of the firm
attributes superior financial performance and organisational resources and capabilities.
The study developed the concept of IT as an organisational capability and empirically
examined the association between IT capability and firm performance. Firm specific IT
resources are classified as IT infrastructure, human IT resources, and IT-enabled
intangibles. Results indicate that firms with high IT capability tend to outperform a
controlled sample of firms on a variety of profit and cost-based performance measures.
3.5.2 Theories on Entrepreneurship
The achievement of SMEs brings great interest among researchers from different
perspectives to understand the role and nature of the entrepreneur. This has led to a
research on entrepreneurship since the early 1960s from economic, psychological and
sociological perspectives. The following sub-sections highlight entrepreneurship studies
from the economic, psychological, sociological, and tourism perspectives.
3.5.2.1 Entrepreneurship from an Economic Perspective
Profit maximisation is the primary goal of any firm. From the economic perspective, the
objective of an entrepreneur embarking on an economic activity is to achieve the most
profit possible from its production and sale of goods or services. As such, profit
maximization requires decision from entrepreneurs to anticipate based on their best
judgment and requires some degree of expertise to make choices that maximise the sum
of current and future profits.
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Entrepreneurs are also characterised as risk-takers and innovators. They create new
things in the act of pursuing the businesses. They are always in the act of endowing
resources with a new capacity to create wealth. Those who are motivated by financial
gain and profit maximisation may be stimulated to take risks as the essence of
commitment of present resources to future expectations and that means to uncertainty
and risk (Drucker, 1994). Entrepreneurship from the economics perspective has sought
to define qualities that characterise entrepreneurial acts as being different from those of
the small business owner/manager. Carland et al. (1984) distinguished entrepreneurs
from small business owner/managers. They note that there is considerable overlap
between small business and entrepreneurship although they are not entirely the same.
Not all new ventures are entrepreneurial in nature, while entrepreneurial firms may
begin at any size and are keen on business growth over time. Small firms
owned/managed by ‘small business owners’ may grow on the one hand, but many will
remain small throughout their organisational lifetime. This distinguishes entrepreneurs
from non-entrepreneurs, whereby an entrepreneur is characterised by a preference for
creating activities, manifested by some innovative combination of resources for profit.
Scholars have examined the impact of entrepreneurial motivational aspects on an
economy. Cantillion, Say and Schumpeter are the pioneer economists who explained
the motivation of entrepreneurs in the early stage of an entrepreneurship evolution in
Western countries (seeCarland, et al., 1984; Chell, Haworth, & Brearley, 1991;
Drucker, 1994). Economists view enterprises as important for the health and growth of
an economy. Many jobs have been created by SMEs and many of these SMEs are new
businesses that did not exist before (Drucker, 1994, p. 19). A few economists try to
differentiate between an entrepreneur and a small business owner or founder, arguing
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that not all business owners are entrepreneurs. Carland, et al. (1984) proposes that a
small business owner establishes and manages a business for the purpose of personal
goals and as a source of income and as such the business is bounded by family needs.
An entrepreneur establishes and manages a business for the purpose of profit and
growth and is characterised by innovative motivations (see Carland et al., 1984).
According to Drucker (1994), to be entrepreneurial, an enterprise has to have special
characteristics over and above being new and small. Furthermore, entrepreneurs are a
minority among new businesses. They create something new and/or different, and they
change or transmute values (p. 20).
Despite the growing interest in entrepreneurship studies, there is no generally accepted
definition or model on what an entrepreneur is or does. Models of entrepreneurship are
almost as numerous as the authors who write about entrepreneurs (Cunningham &
Lischeron, 1991). “Entrepreneur” typically refers to a person who is creative,
innovative, passionate and a risk taker to lead the way to a greater economic
development (Kuratko & Hodgetts, 2004) as commonly understood in the modern day
business context. In this new era, successful entrepreneurship requires more than merely
luck and money. Entrepreneurship is a cohesive process of creativity, risk taking and
planning. Entrepreneurship has become synonymous or at least closely linked to free
enterprise and capitalism. Many people now regard entrepreneurship as a pioneer ship
on the frontier of business.
Reviewing the development of economists’ work, it is clear that there is an increasing
tendency to separate the entrepreneur from the small business owner. The entrepreneur
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is increasingly recognised as an agent of change, having the willingness to take risks
and the ability to make confident and judgemental decisions (Casson, 2003).
3.5.2.2 Entrepreneurship from the Psychological Perspective
The majority of entrepreneurship studies from the psychological perspective focus on
the personality traits of entrepreneurs. Like economists, who argue that not all small
business owners are entrepreneurs, entrepreneurship from this stream highlights the
differences between the traits of entrepreneurs and those of small business owners.
The trait approach seems to be the most promising approach, and the significance of
psychological attributes for entrepreneurial activity and economic growth are
considered to be important and vital for a person’s possibility and interest in acting in
an entrepreneurial way. Consequently, based on the psychological perspective, an
entrepreneur is someone who demonstrates a marked use of enterprising attributes such
as initiative, persuasive powers, moderate risk-taking, flexibility, creativity,
independence, problem solving, need for achievement, imagination, leadership, hard
work and internal locus control (Gibb, 1987).
The literature provides a list of an entrepreneur’s personality traits that show the
connection between an entrepreneur and small business owner. At the same time, there
are critics of the attempt to identify personality traits as characteristics of entrepreneurs.
Some studies have not succeeded in demonstrating the differences in the locus of
control between entrepreneurs and small business owners (Brockhaus, 1980). The
discrepancies are due to methodological difficulties inherent in the identification of
personality characteristics and the conflicting findings of different studies. To some
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extent, it is suggested that the trait approach in entrepreneurship studies should be
abandoned (Stanworth & Gray, 1991). The most common traits identified from the
literature are the need for achievement (McClelland, 1965), risk-taking propensity
(Caird, 1990), locus of control (Caird, 1990), independence (Collins & Moore, 1970),
and innovation or creativity (Kanter, 1992).
McClelland (1965) in his study discussed the influential factors of an individual’s need
for achievement to the growth of the firm. The achievement motive will push the
individual to come out with a strategy and business plan for growth. This has suggested
that an entrepreneur can be trained, as the achievement motive is based on the
expectation of doing something better. The achievement motive will occur when an
individual organises it and puts it into strategic planning and strives for excellence.
However, the relation between the need for achievement and other attributes is
complicated to measure due to methodological difficulties (Stanworth & Gray, 1991).
The risk-taking trait of an entrepreneur was noted as early as 1755 by Cantillon (in
Caird, 1990). There are three levels of risk preferences: low, intermediate or moderate,
and high. These levels of risk affect an individual’s decision to start a business venture.
The relationship between motivation and risk taking reveals that moderate risk taking is
a function of the strength of the motive to achieve or avoid failure. However, the
significance of risk taking as a primary entrepreneurial trait is modified with suggestion
that the entrepreneur is a risk avoider and not a risk taker. Research examining the
relative risk-taking propensities of entrepreneurs and managers has produced conflicting
findings and posed an impediment to the development of entrepreneurship theory.
However, according to Brockhaus (1980), the general risk-taking propensities of
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entrepreneurs and small business owners can be compared empirically to determine
whether this component of risk distinguishes entrepreneurs from small business owners.
Internal locus of control appears to be an important psychological concept that
differentiates entrepreneurs from small business owners. It is called the internal locus of
control because the individual has direct control or influence on its outcome. The
internal locus of control theory states that human motivation is not only a function of
reinforcement, but also depends on people’s conception of the locus of control of
reinforcement. People will attribute the reason why something happens either to
themselves or to the external environment. Those who appear to have control over
occurrences have an internal locus of control and will be referred to as internal. People
who seem to think the control over what happens is situated with external forces have
an external locus of control and will be referred to as external (Caird, 1992).
3.5.2.3 Entrepreneurship from the Sociological Perspective
Entrepreneurship from the sociological perspective focuses on the differences between
types of business owners by creating different name and categories. This typology
approach has reduced the number of profiles and contributed to more sophisticated
descriptions of entrepreneurs and their motivations. Chell et al. (1991) cited Smith’s
(1967) work who has grouped business owners into three groups, labelled as craftsman
entrepreneurs, opportunistic entrepreneurs and business hierarchy. Craftsman
entrepreneurs come from blue-collar backgrounds, have relatively narrow education,
possess a good record as successful workers and identify in the past with plant
operations rather than top management. Opportunistic entrepreneurs come from a
middle-class background, possess broader education and a variety of work experience,
and have a past identification with management. Firms founded by opportunistic
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entrepreneurs experience higher growth rates compared to those by craftsmen
entrepreneurs.
Dukelbenrg and Cooper (1982) produced a classification of three types of business
owners. Type 1 business owners are primarily oriented towards growth and see their
businesses changing rapidly. Type 2 owners are oriented towards independence and
they are strongly driven to avoid working for others. Type 3 owners possess a craftsman
orientation. They are strongly oriented to doing the work they want to do and are most
comfortable selling or handling technical problems rather than working on management
issues.
Stevenson et al. (1985) rejected both the idea of entrepreneurship as an economic
function and the identification of the personal characteristics of entrepreneurs. They
argue that ‘entrepreneurship was an approach to management’ which they define as the
pursuit of opportunity without regard to currently controlled resources. They conceive a
spectrum of business behaviours ranging from entrepreneurial at one extreme and
personified in the form of the ‘promoter’ and administrative at the other extreme. The
‘promoter’ is the person who is confident of his or her ability to seize opportunity
regardless of the resources under current control, whereas the trustee emphasizes the
efficient use of existing resources.
Based on the research that attempts to group or categorize business owners, three types
of small business owner can be identified. This includes ‘craft’ owners, who pursue
personal satisfaction and are therefore motivated to do the work when they want. The
second type comprises ‘promoters’ who seek personal wealth and/or financial return
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and the third type is made up of ‘professional managers’ who seek to build a successful
firm which they can manage (Hornaday, 1990).
3.5.2.4 Entrepreneurship from the Tourism Perspective
Entrepreneurship specifically from the tourism perspective has not been looked into. In
fact, in terms of economic contribution, the tourism industry has flourished through the
entrepreneurial activities and the establishments of TSMEs. However, very limited
empirical studies on entrepreneurship provide little information on the influence of
tourism entrepreneurship on economic development. Thus, little is known about the
economic behavioural characteristics of entrepreneurs and its impact on economic
development (Shaw & Williams, 1990).
Tourism and hospitality firms have also received scant attention within the general area
of small firms research. Other economic sectors, such as manufacturing, have attracted
a lot of attention due to its huge impact on economic development. Only recently, a few
studies have focused on owners of TSMEs. Research done by Dewhurst and Horibin
((1998) and Carlsen, Morrison and Weber (2008) have provided valuable insights in
identifying business motivations among TSME owner-managers. The work on small
firm owners by Stallinbrass (1980) and Brown (1987) identified that many small firm
owners have non-economic motives for entering the business. This finding is also
confirmed by Shaw and Williams (1990). Non-economic reasons for owner-managers
to venture into tourism businesses include semi-retirement and to stay at the place
where the business was established. For some business owners, tourism
entrepreneurship can be seen as a form of consumption rather than production (Rodhi
Thomas, et al., 1997)
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For many small business owner-managers, the pursuit of growth and business expansion
is not a priority (Smallbone, Leigh, & North, 1995). The evidence from tourism and
hospitality industries appears to indicate that a significant percentage of entrepreneurs
are driven by social as well as by non-economic motives (Shaw & Williams, 1998).
According to Ateljevic and Doorne (2000), a growing number of studies on
entrepreneurs have found that the often conscious rejection of economic and business
growth opportunities by entrepreneurs in the tourism industry is an expression of their
socio-political ideology.
TSME owner-managers often have no working experience or formal qualification in
tourism industry (Page, et al., 1999). They also have a major portion of their wealth
invested in the firm, but lack financial, managerial, and marketing skills to run such
businesses (Getz & Carlsen, 2005). In the context of the significant change in tourist
consumption as mentioned earlier, the importance of TSMEs has been widely
recognised (Buhalis, 1998; Page, et al., 1999). As emphasised by Ateljevic and Doorne
(2000), the ability of businesses to position products in a highly segmented marketplace
is dependent on the creative and innovative capacity of individual entrepreneurs to
identify and take advantage of the changing landscape. In a review of tourism
entrepreneurs, Williams (1998) argues that the small business culture, limited capital,
lack of skills, lifestyle motivations and the acceptance of suboptimal profits constrain
regional economies and create problems for firms’ survival.
Ateljevic and Doorne (2000) and Dewhurst and Horobin (1998) in a study of
entrepreneurial activity within tourism, conclude that the traditional economic definition
of entrepreneur cannot be used to describe entrepreneurs in the tourism industry. There
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is a growing recognition, although not well established, that the entrepreneurial
behaviour within the tourism industry is characterised by the lack of motivation to
pursue the goal of maximising economic gain with managerial decisions based on
highly personalised criteria.
The above findings have led Shaw and Williams (1990) to conclude that the theoretical
or conceptual qualities of entrepreneurship, including innovation, responding to
uncertainty and adjusting to disequilibrium, are precisely the qualities that appear to be
poorly developed among small tourism firms. However, with reference to arguments
advanced earlier, such characteristics are acknowledged to be limited to the place where
the research has been undertaken. Thus, there is an emphasis on a move from a purely
economic definition to developing a definition of entrepreneurship in a wider context.
There are a number of perspectives that can be used to understand the characteristics of
small firm owner-managers. The above discussions are derived from three perspectives:
economics, psychology, sociology and tourism. Concepts and findings on small firm
owner-managers from these perspectives are not directly applicable in the context of
TSMEs. The tourism perspective has offered an understanding of the characteristics of
ownership from new tourism and hospitality specific insights (Dewhurst & Horobin,
1998). Based on the above discussions, there is a need for a broad body of works on the
nature and characteristics of small firm owner-managers within the tourism context.
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3.6 Factors Affecting the Performance of TSMEs
Next, factors that affect the operations and performance of small enterprises particularly
within the tourism context are presented. These factors include both internal and
external factors that influence the success or failure of the enterprises.
3.6.1 Internal Factors
Internal factors are controllable elements of the business environment (Hunger and
Wheelen, 2003) and the predominant causes of business failures. The following internal
factors have been shown to a strong impact on business performance.
3.6.1.1 Socio-economic Characteristics
A various of studies have identified ways in which cultural factors shape values,
attitudes and behaviours of people (Alves et al 2006; Hofstede 1991, 2001,2003,2006)
and that different cultures influence views and expectations with respect to the ways
things ‘ought to be done’. Such influences affect organisational behaviours. The
following discuss certain socio-economic characteristics, which were identified by
previous researchers to influence entrepreneurial behaviour in business operations.
3.6.1.1.1 Ethnicity of Tourism Entrepreneur
According to Petersen (1980), ‘ethnic’ is an adjective that refers to differences between
categories of people. Ethnicity has historically played an important role in
entrepreneurship. There is substantial information about the extent to which various
ethnic groups or new immigrants engage in entrepreneurial behaviour in the Asia-
Pacific region. According to Schaper et al. (2007), the main explanation of ethnic
entrepreneurship is based on its motivation factor. Entrepreneurship triggered by ethnic
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discrimination in the host society, lack of recognition of qualifications, poor use of local
language and limited opportunities are the push factors. The presence of role models in
the family, the perception of good entrepreneurial opportunities in the family, the
presence and belongingness to and availability of resources in ethnic networks are all
pull factors to entrepreneurship.
3.6.1.1.2 Owner-Manager’s Age
Entrepreneur age has been studied as a factor of entrepreneurial activity. Reynolds et al.
(2000) found that individuals aged 25 to 44 years are the most entrepreneurially active.
Findings from another study in India by Sinha (1996) disclosed that successful
entrepreneurs are relatively younger in age. Kristiansen, Furuholt and Wahid (2003)
found a significant correlation between age of entrepreneurs and business success, with
older (more than 25 years old) entrepreneurs being the more successful ones. Another
study conducted by Valdez (2009) found that most tourism entrepreneurs in Vigan City
are in the middle-age bracket. Because of their age, they are more experienced in going
into the tourism business.
3.6.1.1.3 Working Experience
Kolvereid (1996)) found that individuals with prior entrepreneurial experience possess
significantly higher entrepreneurial intentions that those without such experience.
Conversely, Mazzarol et al. (1999) found that respondents with previous government
employment experience are less likely to be successful founders of small businesses.
Due to the ease of entry into the industry, many owner-managers are reported to have
various types of occupation and experience prior to their venture into this sector
(Ateljevic et al., 1999; Szivas 2001). In New Zealand, however, previous job experience
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in tourism and hospitality is not particularly represented, but the most common
experiences possessed by tourism entrepreneurs are related to farming, teaching,
marketing and construction (Altejevic et al., 1999). In the UK, about one-third of
owner-managers have working experience in the tourism and hospitality industry, while
others hail from agriculture, retail, education, and various other sectors (Szivas, 2001).
It is emphasised that individual experience is paramount in generating knowledge
(Huber 1996) and can itself engender and encourage innovation (Hayness, 2003). Grant
and Romanelli (2001) argue that the prior experience of the founder of a firm is the
source of knowledge assets critical for the creation of new routines and capabilities to
innovate new products. It also equips managers with the skills and knowledge of
combining or organising and exploiting resources for innovation (Alvarez and Busenits,
2001). Furthermore, according to Brockhaus (1980), Goedhuys and Sleuwaegan (2000)
and Jones-Evans (1996) previous business experience often equips decision makers
with a positive attitude towards business risks and entrepreneurship. For example, in the
case of international business, prior exposure to or involvement in an international
environment removes some of the fears and uncertainties inherently associated with the
‘uncertain’ international market (Ibeh and Young, 2001). Decision makers thus focus
less on risks and more on the exploitation of opportunities. An added bonus of previous
experience is a much-improved personal network that reduces the risk of engaging in
entrepreneurial activities (Basu and Gosmawi, 1999; Ibeh, 2004).
3.6.1.1.4 Education Level
The empirical evidence of the Global Entrepreneurship Monitor project shows that the
relationship between education and entrepreneurial activities is not unclear (Bosma and
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Harding, 2007). However, in theory, prior knowledge is a crucial antecedent of different
dimensions of entrepreneurial orientation, including innovation (Carneiro, 2000; Dove,
1999;Nonaka and Takeuchi, 1995), proactiveness (Clercq and Arenius, 2006) and risk
taking (Knight et al., 2003; Xia et al., 2001). More specifically, acquisition and
exploitation of knowledge, knowledge dissemination and responsiveness to knowledge
have been identified as the components that have the most impact on a firm’s ability to
innovate, act proactively and take risks (Day, 1994; Fahey and Prusak, 1998; Grant,
1996; Teece, 1998). Following this line of argument, the educational background of the
entrepreneur plays an important role in this endeavour.
In his study of Greek-owned businesses in Sydney, Walker (1988) found that the
businesses underwent expansion when university-educated sons joined the firms.
Similarly, Peters (2002) discovered that the Greek Kailis brothers attributed their
success as exporters of lobster and other seafood to their educational attainments. Their
qualifications equipped them with the skills and mindsets to remain flexible and open to
market forces and opportunities.
3.6.1.1.5 Gender
Gender differences between males and females have been widely researched to compare
the differences in performance of female- and male-owned business firms, especially in
western countries (Shim & Eastlink, 1998). Furthermore, gender factor also influential
in shaping an entrepreneurial perceptions and intention (Hofstede, 1998). It is generally
accepted that men have stronger entrepreneurial intentions than women (de Bruin,
Brush, & Welter, 2007; Diaz-Garcia & Jimenes-Moreno, 2010).Yet, based on the
research conducted by Shinnar, Giacom and Janssen (2012), it is suggested that cultural
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values can also act to shape societal gender roles and stereotypes in terms of the
occupations considered appropriate for men and women. This has led to each gender
being prone to select the ‘appropriate’ occupations or career based on the femininity
and masculinity of the working environment.
This is explained by the research of Wagener (2007) and Langowitz and Minniti
(2007)on the gender factor. The fact that women entrepreneurs are less self-assured in
their perception of their own abilities than men depends on the hostility of business
environment which may constrain the entrepreneurial spirit among women. This
indicates that gender can shape entrepreneurial attitudes, intentions and motivation to be
an entrepreneur and create a new business (Mitchell et al., 2002).
3.6.1.1.6 Family Business Background
A family business background also influences the entrepreneurial behaviour of
individuals (Basu & Goswami, 1999; Duchesneau & Gartner, 1990; Gurel, Altinay, &
Daniele, 2010). People who have a parent or close family member who is self-employed
are more likely to follow an entrepreneurial career (Matthews and Moser, 1996,
Drennan et al, 2005). A family business background leads perhaps to lower barriers to
entrepreneurial entry, since those having it may capitalize on their social ties and social
capital (Greve and Saleff, 2003). Family capital refers to the totality of resources of the
owning family members and has three components: human, social, and financial (Danes
et al, 2009). Research has shown that family social capital (described as non-financial
resources and support offered by family members to the entrepreneur) positively affects
the start-up decision (Chang et al, 2009).
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The family embeddedness perspective describes the impact and the importance of
parents on the entrepreneurial career of their offspring (Aldrich and Cliff, 2003). Both
the breadth and quality of family business experience matter (Krueger, 1993).
Experiences during early childhood and socialization at home and in school probably
shape the attitudes of young people towards entrepreneurship (Basu and Virick, 2008).
Parents act as initial role models, and parents active in a family business influence the
future entrepreneurial intentions through changing attitudes and beliefs, e.g. self-
efficacy (Shapero and Sokol, 1982, Krueger et al, 2000).
3.6.1.1.7 Motivation
The expression of being either ‘pulled’ or ‘pushed’ into starting a business has been
used extensively in the literature regarding owner-managers’ motivation to start a
business (Brodie and Stanworth, 1998; Burtner and Moore, 1997; Gray, 1994;
Hamilton, 1987). The ‘pull’ motivation factor is associated with the individual’s strong
positive internal desire to start a business venture. The opposite ‘push’ motivation factor
is associated with a possible equally strong desire to start a business venture, but based
on external negative reasons. Personal freedom, independence gained from being one’s
own boss, personal satisfaction, a less rigid and more flexible lifestyle and greater job
satisfaction are pull motivation factors identified in the literature (Birley and Westhead,
1994; Brush 1992; LeCornu et al., 1996; Loscocco, 1997).
A study by Fielden et al. (2000) indicated that a large proportion of their sample (88 per
cent) listed making money as a motivator for their business ventures. However, 71 per
cent mentioned that job satisfaction, greater independence, creating opportunities,
encountering new challenges and pursuing one’s own interests are also important
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factors that led them to open their own business. According to Glancey and Pettigrew
(1997), motivations for founding a business fall into two broad groups, which are (1)
those that reflect the ‘push’ factors, such as redundancy and job insecurity, and the need
for supplementary income, and (2) those that reflect the ‘pull’ factors, such as the desire
to be his/her own boss, high levels of profit, and spotting a business opportunity, or
retirement.
In Australia, Bransgrove and King (1996) reported that the top goals of owners of small
tourism business in both urban and rural settings are challenge or stimulus, business
opportunity, lifestyle and long-term financial gain. According to Getz and Carlsen
(2000), 34 per cent of their respondents suggest that an appealing lifestyle is the major
reason for venturing into business, and this is followed by business opportunities and
investments. Glancey and Pettigrew (1997) found that the behaviour of the majority
(65%) of their respondents adhered to the pull factors, and this provided evidence for
categorising them as opportunistic entrepreneurs. Rural entrepreneurs, as reported by
Schroeder (2003), are motivated by multiple pull factors such as providing employment
for family members, generating additional income, meeting the need of the market,
companionship with guests, fulfilling their interest or hobby, and providing employment
to communities.
3.6.1.2 Business Skills
Business skills are the management skills and knowledge of the owner-managers.
According to Mckercher and Robbins (1998), lack of skills is a major impediment for
tourism entrepreneurs. They found that new tourism entrepreneurs have no formal
business skills, no management background and no prior industry experience. Other
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related research also shows that entrepreneurs’ management skills contribute to venture
performance and growth (Lerner and Almor, 2002; Bird, 1995; Cooper and Gimeno-
Gascon, 1994). The propensity of entrepreneurs to employ and apply a variety of skills
is recognised (Hunger and Wheelen, 1996). According to Hood and Young (1993),
some of the important skills of successful entrepreneurs include accounting, marketing,
sales and financial management. Comparing male and female entrepreneurs, Brush
(1993) demonstrated that women business owners often rate themselves lower than men
in terms of financial skills. Also, Hisrich and Brush (1984) found that American women
entrepreneurs scored themselves high on generating ideas, product innovation and
dealing with people, average on marketing and operations, and weak on financial skills.
3.6.1.3 Business Planning
Research has shown an association between planning in small businesses and
performance. The literature suggests that planning is a good management practice, and
may be beneficial to business (Gibson et al., 2002; Schwenk and Shrader, 1993).
According to Berman, Gordon and Sussman (1997:14) “firms that plan produce better
financial results than firms that do not plan.”Bracker et al. (1986, 1988) found that firms
that undertook strategic planning performed better financially. Lerner and Almor (2002)
contend that planning lays the groundwork for developing the strategic capabilities
needed for high performance.
Various scholars have studied strategic planning (Mintzberg, 1973, 1994; Brush and
Bird, 1996; Bracker and Pearson, 1986; Braker, Keats and Pearson, 1988). Previous
research shows a positive relationship between strategic planning and firm performance.
According to Miles and Snow (1978), successful, proactive firms have the propensity to
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invest time in strategic planning. On the contrary, unsuccessful, reactive firms fight
fires instead of investing time in strategic planning.
Li (1998) investigated SMEs providing travel agent services in Taiwan. Taiwan’s
TSMEs have contributed significantly to the country’s economic growth and this study
explored the factors that underpin their relative success. The study was grounded in a
framework that focused on structure, technology and people, and examined the major
management practices of successful TSMEs and the roles of successful TSME owner-
managers. Based on 43 TSMEs in Taiwan, results show that in a global economic
environment, TSMEs face increased competition from multinational companies both at
home and abroad. Successful TSMEs should emphasize structure and technology, such
as rearranging its internal systems or managerial hierarchy rather than people issues
such as changing the behaviour of employees by focusing attention on their skills,
attitudes, perceptions and expectations. These findings reveal the unique coping
strategies of TSMEs in Taiwan. Management skills and management concepts of
TSMEs owner-managers are more important than their technical skills and their concern
about production. Employees’ skills are of crucial concern and these successful TSMEs
have thrived under keen competition in an environment of meagre resources.
3.6.1.4 An Adoption of Internet
Karanasios and Burgess (2006) explored the use of the Internet by TSMEs. The
objectives of the study were to improve knowledge on how STEs use and to overcome
typical hurdles to adopt Internet use. The study sought to identify how TSMEs exploit
the information, communication, and transactions spaces created by the Internet. The
study sampled 14 semi-rural and urban TSMEs in Malaysian Borneo, and used semi-
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structured questionnaires. The results suggest that TSMEs in the region adopt the norm
of using the Internet in their businesses. Most TSMEs have a web site and have been
using email for more than three years. The study indicates that entrepreneurs’ awareness
and adoption of the Internet as business tools has significant benefits to TSMEs and
those that are not online are placing themselves at a disadvantage.
Nodder et al. (2003) analysed the use of Information Communication Technology (ICT)
in highly competitive tourism industry in Auckland, New Zealand. The study focused
on the degree to which national and local governments are providing a policy
framework to support the uptake and use of ICT among TSMEs in the Auckland region.
Using qualitative research design and in depth interviews with local governments and
small business owner/managers of TSMEs, findings revealed that local governments are
beginning to embrace ICT in the tourism industry. Policies regarding the adoption of
ICT among tourism businesses can affect relationships, drive visionary business
strategy development, establish and build networks, and add new dimensions to the
capabilities of network organizations. Nodder et al. (2003) stated that connectivity
optimised the exchange of knowledge and sharing of resources for those whose aim is
to foster a more effective way of doing business to achieve regional economic growth.
General marketing activities and communication with customers are major reasons for
using e-commerce. However, as recommended by the APEC Tourism Working Group
(2002), TSMEs should utilize e-commerce for various other functions such as business
to business (B2B) transactions, market research, after-sales service, and competitor
analysis. The extent to which e-commerce is integrated throughout the business value
chain is crucial to determine the benefits that can be gained. Making a more proactive
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and comprehensive utilization of e-commerce is far more beneficial than adopting e-
commerce for specific functions such as receiving orders or ordering goods and services
(Frías, Rodríguez, Alberto Castañeda, Sabiote, & Buhalis, 2012). From the survey, the
APEC Tourism Working Group identified that TSMEs can use more advanced solutions
that are applied to B2B and business to consumer (B2C) transactions with reasonable
prices by using the Internet. The results were gathered through research undertaken by
the APEC Tourism Working Group of TSMEs within APEC member economies. The
survey was held in 2002 and was based on data and information provided by more than
50 experts from several APEC member economies.
Matlay (2004) focused on issues related to the emergence of e-businesses and Internet
trading in e-Europe and the effect that these developments could have on small tourism
firms operating in Western, Central and Eastern Europe. According to Matlay (2004),
tourism represents the largest economic activity in Europe with potentials for further
and sustainable growth. This is partly due to the inherent socio-economic and cultural
diversity of the continent, which incorporates a wide variety of national and regional
identities. In addition, local business, demographic and geographic variations can
impact significantly upon tourism related demand and supply. Importantly, however,
although the main developments in the tourism industry tend to be dominated by large
firms, the vast proportion of related business activities involve SMEs operating in local
and regional markets (Mistilis & Buhalis, 2012; Nodder, et al., 2003).
The recent ICT-related developments in the tourism industry have ensured that more
individuals and firms become connected electronically, resulting in a dramatic change
in competitive drive, from traditional business towards e-business. Entrepreneurship has
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been identified as the main factor that determines whether a firm, industry or region will
succeed in exploiting the opportunities inherent in e-business (Law, Qi, & Buhalis,
2010; Mistilis & Buhalis, 2012). Hence, official support for e-business is evident not
only at the firm level, but is increasingly promoted at local, regional and national levels
(Neuhofer, et al., 2012). Thus, tourism industry in Europe is positioned to take
advantage of the on-going advances in ICT where strategic change is closely related to
the drive for sustainable competitive advantage (Matlay, 2004).
3.6.1.5 Business Alliance
Braun (2002) discussed how the fostering of a culture of connectivity, networking,
learning, and trust between regional Australian TSMEs may offer potential solutions to
the possible loss of competitive advantage in the new economy. She justifies that
networking and cooperative relationships are considered prime determinants of
commercial success. As such, Australian TSMEs have the opportunity to both
collaborate and compete by joining a regional marketing portal founded on cooperative
principles such as sharing resources and exchanging industry knowledge.
One consistent pattern in the new economic business process is the complex networks
of interaction, whereby emphasis on collaboration between firms is placed as the key
for new models of innovation. Research indicates that network building is not only a
major new source of competitive advantage for any company, but a crucial asset to
business survival and an essential global and, indeed, regional management
requirement.
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Australian SMEs, on their involvement in business networks, noted a significant level
of interest in networking or formulating networks in the future, indicating that
networking is likely to become important in the business future of Australian SMEs
(Dean, Holmes, & Smith, 1997). Two types of business networks were identified:
formal and informal. The formal networks constituted formal arrangements between
companies to consolidate resources and informal networks were seen as loose
arrangements facilitating information exchange. Service companies were notably more
likely to be involved in formal and informal networking than manufacturing companies.
3.6.2 External Factors
External factors are made up in the societal environment, and generally affect the long
run decision of an organisation. They include political/legal forces, economic forces,
socio-cultural forces and technological changes. External factors are not controllable by
small firms compared to larger organisations. Nevertheless, it is critical for small firms
to be attuned to these forces as they also affect performance of small firms.
3.6.2.1 Government Assistance Programmes
Wanhill (2004) examined the theory and practice of government intervention in the
tourism industry to understand market failure. The study focused on issues of
investment strategy, and principal instruments for implementation, namely investment
incentives. Results show that small businesses, which dominate the sector, face
numerous problems to guarantee success. These difficulties relate to: (1) structuring
small business finance, (2) upgrading standards, (3) improving communications
channels, and (4) a lack of market intelligence. The rationale for government
intervention lies in the complex nature of tourist products, which makes it unlikely for
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the private sector to assist in implementing the country’s tourism policy objectives by
producing conditions and facilities that meet the needs of visitors, benefit the host
community and are compatible with the wishes of the same community. According to
Wanhill (2004), therefore, market mechanism and governance should not be seen as
mutually exclusive activities, but rather complementary actions. Besides that, Wanhill
(2004) also added that an action program is needed to create the right business
environment for SMEs in order to improve their quality, diversity, competitiveness and
profitability.
Sharma and Sneed (2008) investigated performance efficiency of small hotels in three
major cities in Tanzania. Spatial performance analysis and comparison of small hotel in
Tanzania’s key tourism location were used to seek out the factors that affect small
hotels. To look at the performance efficiency of the hotels, Sharma and Sneed evaluated
factors such as the scale, location effects and employee skills and their effect on hotels’
performance. Results show that the biggest challenge facing small hotels in Tanzania is
increasing capacity to capitalize on cost-saving associated with larger operations. This
requires the government to provide education and training for the industry. The above
measures may also improve critical infrastructure in certain parts of the key tourism
locations to allow the industry to increase tourist and visitor traffic. Thus, marketing
and promotion effort of hospitality and tourism require the industry to partner with the
government.
Wanhill (2002) discussed the weaknesses of TSMEs that can prevent successful tourism
development. Among of the recognized weaknesses of TSMEs are family businesses,
lack of entrepreneurial drive, limited business skills, shortage of finance and tendency
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to free ride. To provide continuous support for tourism development, evidence suggests
that only government intervention can sustain the tourism industry because of the high
degree of fragmentation in the industry and asymmetric information flows. Hence, a
practical approach to development should involve legislative control and the provision
of public money and technical support to channel the energies of the private sector in
directions that are both sustainable and profitable. Thus, tourism authorities must
evaluate the viability of firms targeted for government assistance. A general action
programme for SMEs is needed to improve the competitiveness of tourism economy
such as improving communication channels, raising the level of market intelligence,
upgrading standards and structuring small business finance. Therefore, given the
fragmented nature of the industry, a pro-active role from public bodies in the form of a
coordinated tourism strategy is required to give a sense of direction and engender
confidence through local community involvement. Based on the survey results, Wanhill
(2002) concluded that an action programme is needed to target SMEs to improve their
quality, diversity, competitiveness and profitability, within the context of sustainable
development to account for the cultural and environmental aspects of tourism.
3.6.2.2 Technology
In tourism, the Internet as a channel of distribution has become one of the most
successful channels used by consumers to research travel options, compare prices and
make reservations for airline tickets, hotel rooms and car rental services. The Internet
also has a profound effect on the internal and external operating procedures within the
hospitality industry (Cheng and Piccoli, 2002).
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Despite all of the benefits to be achieved, the Internet and new technologies have failed
to make a major impact on the majority of TSMEs in the hospitality industry. TSMEs
have been slow to adopt and to realise the actual benefits of applying ICT to their
business (Standing et al., 1999, Buhalis, 2003; Morrison et al., 1999). However,
according to Anckar and Walden (2001), there is evidence that a small minority of
TSMEs are taking full advantage of the electronic marketplace and benefiting from the
many opportunities that it provides.
3.6.2.3 Global Event
Terrorism acts have had a major effect on the global tourism industry. The impacts of
terrorism on tourism destinations from an economic perspective have been studied and
documented in numerous studies. For instance, the September 11, 2001, terrorism act in
the United States has had an enormous negative effect on tourism demand worldwide
and a devastating impact on the tourism industry of the United States. Airlines, tour
operators, theme parks and attractions, and car rental and hotel companies, to name just
a few, have all reported drastic cancellations of existing reservations and extensive
declines in future bookings (Pizam and Fleischer, 2002). It is found that these impacts
of terrorism on tourism can occur up to three months after the event took place and last
for a relatively long time - six to nine months after the event (Sonmez 1994; Enders,
Sandler, & Parise 1992). To TSMEs, these impacts bring great damages on their
business performance and also survival.
3.6.2.4 Consumer Behaviour
Consumer behaviour in tourism consumption is changing extensively, developing a
more segmented, specialised and sophisticated market mainly aiming at unique
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activities available at the destinations (Nylander & Hall, 2005; Robinson & Novelli,
2005). Consumer behaviour is also influence by the image of tourism destinations. For
instance, terrorism acts at a certain destination bring negative consequences on the local
tourism industry. Thus, tourists can easily choose other safer destinations. In an era
when tourism is dominated by requests for tailored experiences, TSMEs play a key role
in providing adequate products and services to tourists by responding to their most
specific interests and needs.
Both internal and external factors among tourism business environment have an
influence on the performance of TSMEs. The tourism industry is highly vulnerable to
natural (i.e., hurricanes, volcanic eruptions, torrential rains) and human caused disasters,
both social and political (i.e., riots, insurgency, terrorism, crime, political upheaval, war,
regional tensions). Regardless of their nature, disasters create difficult, often tragic
situations for the afflicted area and its residents. However, these external factors are
beyond the control of the owner-managers of TSMEs. But, according to Lee and
Peterson (2000) and Coetzee et al. (1993), owner-managers must develop closer
relations with these external environments because their opportunities and resources
emanate from this environment.
Based on the above discussion, internal factors are more likely controllable by owner-
managers of TSMEs, and are more likely related to the central role of an entrepreneur in
the small firms. Furthermore, the internal perspectives can be used as the approach for
measuring firm performance.
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3.7 The Conceptual Framework of the Factors to Influence the Success of TSMEs
The earlier sections have discussed on a wide range of factors affecting the performance
of SMEs in the context of the tourism industry. This section concerns the development
of a model that attempts to conceptualise the relationship between the underlying
factors that influence SME performance in the tourism industry. However, the factors
influencing TSMEs are expected to differ from SMEs in other industries.
Merely, earlier studies on factors affecting the performance of SMEs have focused on
looking into a limited set of variables, and others look into more holistic profiles of
successful SMEs in manufacturing industry. For instance, Gosh and Kwan (1996) made
a cross national inter sectoral study in Singapore and Australia of the key success
factors of SMEs in the manufacturing industry. Gadenne (1998) focused on the effect of
management practices of SMEs by studying 369 businesses in the retail, service and
manufacturing industries in Australia. Wijewardena and Coray (1996) investigated the
success factors of SMEs in Japan’s manufacturing industry. Kauranne (1996) also
focused on SMEs in manufacturing in Finland, and also carried out a follow up study by
looking at firm success in the short and long terms.
Pelham (2000) focused on SMEs in manufacturing to explore the relationship between
market orientation and SME performance in eight industry sectors. Based on the above
research, the findings of the factors affecting SMEs business success were based on the
direct relationship of internal and external factors. In Storey’s (1994) work, the factors
are group into three components: the characteristics of entrepreneurs, the characteristics
of the SMEs, and the type of strategy associated with growth. Table 3.1 lists these three
components, which are important factors in analysing the growth of SMEs.
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Table 3.1: Factors Influencing Growth in SMEs
The entrepreneur/resources The firm Strategy
1. Motivation 1. Age of the firm 1. Workforce training 2. Unemployment 2. Sector 2. Management training 3. Education 3. Legal form 3. External equity 4. Management experience 4. Location 4. Technological sophistication 5. Number of founders 5. Size 5. Market positioning 6. Prior self-employment 6. Ownership 6. Market adjustments 7. Family history 7. Planning 8. Social marginality 8. New products 9. Functional skills 9. Management recruitment 10. Training 10. State support 11. Age of the entrepreneur 11. Customer concentration 12. Prior business failure 12. Competition 13. Prior sector experience 13. Information and advice 14. Prior firm size
experience 14. Exporting
15. Gender Source: Storey (1994)
Based on Storey’s (1994) framework, Indarti and Langerberg (2004) have examined the
factors affecting Indonesian SMEs based on the modified framework from Storey’s
(1994) research. In their study, Indarti and Langerberg classified the factors affecting
the SMEs performance into three dimensions: entrepreneur characteristics, SME
characteristics and contextual variables of SMEs that were hypothesised to have a direct
bearing on SMEs’ success. They recommend that based on the results of the study,
education and source of capital were related significantly to business success, while
capital access, marketing and technology are not influential to the performance of SMEs
in Indonesia. Figure 3.1 shows the direct relationship of three components as the factors
affecting the performance of SMEs.
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Figure 3.1: Factors Affecting SMEs' Success
Source: Indarti and Langenberg (2004)
3.8 Limitation of Previous Studies
Research on factors affecting SMEs’ success is highly discussed in manufacturing
industry, but not in the tourism industry, which may have differences in terms of factors
affecting TSME performance. Furthermore, previous research has only looked into the
direct relationship between factors affecting SMEs and the performance of SMEs. Less
research has investigated the antecedents’ factors, which might also influence the
performance of SMEs.
The existing research on entrepreneurship in tourism and on the operations of tourism
firms originates from the developed economies, particularly Western European
countries. In Malaysia, despite the fact that SMEs have been playing an important role
Characteristics of entrepreneur -Age -Gender -Work experience -Education
Characteristics of SMEs -Origin of enterprise -Length time in operation -Size of enterprise -Capital source
Contextual variables -Marketing -Technology -Information access -Entrepreneurial readiness -Social network -Legality -Capital access -Government support -Business plan
Business success
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in the development process of the national economy (Bank Negara Malaysia, 2005),
research involving SMEs particularly in the context of service sector seems to be
neglected. Many researchers have concentrated on SMEs in the manufacturing sector
while limited research has focused on SMEs in the tourism industry.
Since the Malaysian tourism industry is a key driver of its social, economic, and
regional development, there is an urgency to examine the entities that play significant
roles in tourism growth and success performance. Given the significance of Malaysia’s
tourism industry and the fact that TSMEs dominate this industry, the importance of
research on issues that underpin the development of TSMEs in Malaysia cannot be
underestimated.
Reviewing other studies related to TSME performance and tourism entrepreneurs, most
of the sample come from the accommodation and hotel sectors (Morrison, 1996;
Morrison, Rimmington, & Williams, 1999; Nuntsu, Tassiopoulos, & Haydam, 2004;
Poutziouris, Wang, & Chan, 2002; Shane, Locke, & Collins, 2003). Focusing solely on
such data does not represent the true colours of TSMEs. Aside from the accommodation
and hotel sectors, tourism businesses encompass other services such as facilitation,
transportation, food and beverage and travel related retails businesses (Koh &Hayyen,
2002).
3.9 Concluding Remarks
The review of the literature conducted in this chapter has demonstrated that TSMEs
play a significant role in tourists’ perceptions of their experience in their destinations.
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The theoretical basis for this research, RBV, focuses on a firm’s unique resources and
capabilities to underpin its performance, while theories on entrepreneurship highlight
the differences that exist in the economic, psychological, sociological and tourism
perspectives regarding the entrepreneur. Each of the perspectives discussed attempted to
provide justifications to understand the characteristics of small firm owner–managers.
However, the reasons for these characteristics of entrepreneurs within the tourism
context still require a broad body of work.
Besides the importance of the entrepreneur in business performance, the internal and
external factors of the business environment have been extensively discussed in
previous research as the predominant causes of small business success or failure. Of the
internal factors, socio-economic characteristics such as ethnicity, owner–manager’s age,
employment experience, education level, gender, family business background,
motivation, business skills, business planning, adoption of the internet and business
alliances are regarded as controllable elements of the small business environments. The
external factors, which consist of the societal environment, generally affect the long-
term decisions of small business. Besides technology, global events and consumer
behaviour, government assistance programmes are crucial in influencing the
performance of TSMEs.
The final section of this chapter has reviewed a number of conceptual frameworks
explaining the factors affecting the performance of firms, particularly their effects on
SMEs. Despite the differences among the models about the determinants of success
factors for SMEs, it can be concluded that different sets of the internal and external
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factors influence the performance of SMEs and these factors are expected to assist in
the improvement of TSMEs’ performance in Malaysia.
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CHAPTER FOUR
STUDY METHODOLOGY
4.1 Introduction
Chapters 2 and 3 presented the literature review, incorporating various theories and factors
that are relevant in this study. It has highlighted a number of justifications to support the need
to examine success factors of TSME in Malaysia. Previous studies could significantly vary
from nation to nation and from one business environment to the other due to economical,
geographical and cultural disparities and variations. This chapter will provide the underlying
framework constructed for this study.
This chapter is organised as follows. Section 4.2 describes the critical linkage between the
proposed of three dimensions which are considered as the key factors and TSMEs
performance. Section 4.3 looks in the operationalisation of variables and research hypothesis
of the study. Section 4.4 presents the data sources and description. Section 4.5 focuses on the
statistical techniques for data analysis. The chapter draws its conclusion in Section 4.6.
4.2 Internal Resource Factors and TSME Success – the Critical Linkages
Based on the review of related literature discussed in Chapter 3, there is a common set of
underlying success factors towards the performance of SMEs. However, the effectiveness of
this set of factors varies, depending on the cultural context in which the business operates.
Furthermore, most previous studies in this regard were conducted in different countries all
over the world and the majority focused on SMEs in the manufacturing industry (see Feindt,
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Jeffcoate, & Chappell, 2002; Ghosh, Liang, Meng, & Chan, 2001; Hashim, 2000; Henry
Pribadi & Kazuyori Kanai, 2011; Lin, 1998; Sebora, Lee, & Sukasame, 2009), very few of
which were conducted in developing countries and focused on TSMEs. Hence, the essence of
this study is to contribute to the literature of small business success of TSMEs by identifying
key success factors on business operations in Malaysia.
In this study, three key resource factors have been chosen to investigate as key success
factors to TSMEs in Malaysia. These are: socio-economic characteristics, tourism
entrepreneurs’ motivation, and management practices. This study identifies how socio-
economic characteristics influence tourism entrepreneurs’ motivation. The study will also
examine the outcomes of management practices, focusing on business planning, business
alliances, adoption of Internet, and utilisation on government assistance programmes on the
performance of TSMEs. Furthermore, since the RBV addresses these resources and
capabilities of the firms as an underlying factor of performance, it is therefore a suitable
theory to use within the framework of this study. The purpose of this section is to justify why
these internal and external resources in particular were chosen to assess small business
performance and to explain the framework of the relationship between these resources
towards TSME success.
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Figure 4.1: The Proposed Conceptual Framework
The proposed conceptual framework for this study, as depicted in Figure 4.1, shows all the
predictors belonging to the internal environment of TSMEs resources: socio-economic
characteristics factors, tourism entrepreneur’s motivation, business planning, business
alliances, adoption on Internet and government assistance programmes utilisation. The
correlation between each specific internal factor will determine the firm success performance
of TSMEs. Using the framework from Indarti and Lagenberg (2004), based on the suitability
with the Malaysian context, some new variables were included; ethnicity, family business
background, tourism entrepreneurial behaviour and utilisation of government assistance as
components in the adopted framework. With the new variables, the framework is modified
Socio-economic
characteristics
Tourism entrepreneur’s
motivation
Business planning
Business alliances
Adoption on Internet
Government assistance
programmes
TSMEs performance
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and improved on the older technique used by using structural equation approaches to solve
the correlations and relationships between each variable of the model.
4.3 Operationalisation of Variables and Research Hypotheses
This study examines the theoretical constructs known as latent variables (Byrne, 2010). As
latent variables are not observed directly, these variables cannot be measured directly.
Therefore, ‘the researcher must operationally define the latent variable of interest in terms of
behaviour believed to represent it’ (Byrne, 2010, p. 4). The approach employed is to generate
scale items derived from previous work conducted by other researchers. These items are
widely used in this research area and have been tested for scale validity in these studies.
However, a number of items have been modified for this study and some items were
generated based on variable definitions. This section describes the manner in which the
constructs that emerged from the literature were operationalised.
4.3.1 Socio-economic Characteristics
The entrepreneur is recognised by many researchers due to their role in starting the business
enterprise, managing the business and being responsible for its success or failure. This
undoubtedly explains the sustainability of SMEs being dependent on entrepreneur
motivation. Several previous studies have identified socio-economic characteristics that are
triggering factors of entrepreneurial motivation. Age, gender, education level, work
experience, ethnicity, family business background are found to be important drivers of
entrepreneurial behaviour and motivation (Arenius & Minniti, 2005; Curiel-Piña, González-
Pernía, Jung, López-Trujillo, & Peña-Legazkue, 2013; Galloway, Brown, & Arenius, 2002)
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and help to explain firms’ strategic behaviour as they a manifestation of managerial
psychological dimensions (Wiersema & Bantel, 1992). The emphasis on demographic
characteristics was also justified by Mazzarol (2005; 1999) and Kolvereid (1996). The
following sections will discuss the significance of each of the selected demographic
characteristics made operational in this study.
4.3.1.1 Age of the Owner-Manager
In an attempt to explain the motivation of tourism entrepreneurs, age has been seen as one
determinant factor of the socio-economic characteristics to influence the motivations of an
entrepreneur. For example, findings from Kristian, Furoholt and Wahid (2003) found a
significant relationship between age of an entrepreneur and business success. They indicated
that older entrepreneurs were more successful compared to younger entrepreneur. Other
findings from Reynolds et al. (2000) found that individuals aged 25-44 years are the most
entrepreneurially active. However, findings from another study in India by Sinha (1996)
disclosed that successful entrepreneurs are in a relatively younger age group . This is
supported by Reijonen and Komppula (2007) in their study on TSMEs’ barriers to growth.
They found a negative link between age of tourism entrepreneur and business growth.
Entrepreneurs whose age is above 41 years old are less motivated to grow their business
compared to younger entrepreneurs. Based on the arguments above, it is hypothesised that:
H1a: Age contributes to tourism entrepreneur’s motivation.
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The tourism entrepreneur’s age is made operational based on Reijonen and Komppula’s
(2007) findings from gathering data from respondents in the following age groups: younger
than 30 years of age, between 31 and 40 years age, between 41 and 50 years of age, and older
than 50 years age. Respondents’ ages were required to evaluate the age factor on tourism
entrepreneurs’ motivation. These items required respondents to classify their age according
to the age groups provided.
4.3.1.2 Gender
Generally, small firms are owned and managed by men (Morrison, Breen, & Ali, 2003).
According to Ahmad (2005), 81.1 per cent male owner/managers dominate the small
business. Furthermore, in Kristian, Furoholt and Wahid’s (2003) study, it was indicated that
women entrepreneurs were less ambitious to grow and were also less optimistic. Likewise,
according to Kolvereid (1996) and Tominc and Rebernik (2012) male entrepreneurs also
have significantly higher entrepreneurial intentions compared to females. However, many
studies on tourism entrepreneurship identified that the prominence of lifestyle motives is the
foremost reason to get involved in the tourism industry. The research also characterised such
entrepreneurs as having a lack of growth orientation, possessing non-economic motives and
not wanting to grow the business (Dewhurst & Horobin, 1998; Getz & Carlsen, 2000). Getz
and Carlsen (2000) found that there was no significant difference between genders among
tourism entrepreneurs in Bornholm, Canada. This somehow reflects the influence of the
lifestyle motives among tourism entrepreneurs; hence male and female tourism entrepreneurs
likely show no difference. Nevertheless, female entrepreneurs often possess unique
circumstances and characteristics compared to males in terms of motivations for start-up
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business and for business growth. At the same time, female entrepreneurs maintain
traditional domestic roles alongside their professional ones (Galloway, et al., 2002). Thus, it
would be reasonable to hypothesise that:
H1b: Gender contributes to tourism entrepreneur’s motivation.
The respondents on this variable are transformed through dummy variable coding 0 for male
and 1 for female in order to enable statistical techniques to be carried out to the test direction
and magnitude of dependent/independent variable relationships.
4.3.1.3 Education Level
The finding of the formal educational level on the owner/managers is inconsistent. In
Australia and Tanzania, respondents with university education form only the minority of the
total sample of the study conducted by Getz and Carlsen (2000) and Sharma and Upneja
(2008). However, Glancey and Pettigrew (1997) find that there is an equal balance between
respondents with secondary education and those with university-level education in Scotland.
In the UK and Turkey, the percentage of respondents with tertiary education is higher, that is
70per cent (Szivas, 2001) and more than 50 per cent (Avcikurt, 2003). In terms of expanding
a business, recent research found a positive effect of individual educational level on the
likelihood to perceive entrepreneurial opportunities (Clercq and Arenius, 2006). A higher
level of education develops both the analytical ability and the computational skill of the
entrepreneur as well as communication skills. Those who attain a higher level of education
are better equipped to communicate with customers, gather market intelligence and develop
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proactive strategies which then lead to higher growth (Casson, 2003). Education could also
enhance an individual’s capacities for creativity, flexibility, self-direction and the ability to
respond to widely different situations and thus contribute to innovative behaviour within a
firm (Rauchand Frese, 2000; Collinson and Quinn, 2002; Shook et al., 2003; Llewellyn and
Wilson,2003; Walton, 2003).Therefore, this study hypothesises that:
H1c: Education level contributes to tourism entrepreneur’s motivation.
The tourism entrepreneur’s educational level is made operational based on Passannen (2003)
by the inclusion of a variable that collects educational level in four options: primary,
secondary, tertiary and other.
4.3.1.4 Ethnic group
The role of ethnicity as an antecedent of entrepreneurial motivation could be explained
through self-efficacy differences or differences in family and household characteristics,
including human and financial capital across ethnic groups (Krueger, Reilly, & Carsrund,
2000; Rodriguez, Tuggle, & Hacket, 2009). This is due to the closeness of the entrepreneur
and specific society traits which influence the entrepreneurs’ mindset and behaviour (Gamini
de Alwis & Senathiraja, 2003). The positive link between Asian ethnicity and the work
setting and culture is highlighted by Henry, Durganard and Wilpert (1999).Furthermore, the
differences of culture on each ethnicity are pervasive and entrenched in all societies. These
differences also play a role in personal values and decision-making ((Chu & Katsioloudes,
2001; Kennedy & Drennan, 2002; Lee & Peterson, 2000).
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In the Malaysian context, the Malays are very hierarchical and lack individual decision-
making. The idea of entrepreneurship is not favoured in Malay society due to the uncertain
nature of entrepreneurship (Mueller & Thomas, 2001). This also implies the same to Indian
and other minority ethnic groups in Malaysia. In terms of business ownership across
industries in Malaysia, data from the SME (Small and Medium Enterprise Corporation
Malaysia, 2011) demonstrates that there is a low number from Indian and other minority
group in Malaysia compared to Malays and Chinese, which indicates that they have low
interest in entrepreneurial activity. Furthermore, as Malays are Muslim, their definition of
success is not associated with only wealth (Al-Omar &Abedl-Haq, 1996). Likewise, studies
conducted by Turan and Kara (2007), Muslims are more likely to be pulled into business than
non-Muslim. In contrast on a global scale, Chinese are known for their business tradition.
They have positive association with power and wealth and place high value on materialism
(Chong, Syed and Roselina, 2003). Profit is their business goal and monetary reward is a
great motivator for Chinese to enter into a business (Chong, 2012).
Malaysia is multi-ethnic, with Malays comprising the dominant ethnic group. However,
Malaysian Chinese and Indians (as well as other minority ethnic groups) have differences in
various aspects (such as cultural values and religious background) which may influence their
entrepreneurial motivation. Thus, this study hypothesises that:
H1d: Ethnic group contributes to tourism entrepreneur’s motivation.
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The tourism entrepreneur’s ethnicity is based on the Malaysia’s classification of ethnic
groups according to Department of Statistics, Malaysia (2009) census, by inclusion of a
variable that collects the majority of Malaysia ethnic groups: Malay; Chinese; Indian and
others.
4.3.1.5 Family Business Background
The importance of family business background as the influential factor on entrepreneurial
motivation of individuals has been highlighted by previous studies (Altinay, Madanoglu,
Daniele, & Lashley, 2012; Basu, 2004). According to Getz and Carlsen (2005), as most of
TSMEs is dominated by family businesses, thus children’s intention to continue with an
existing business or to start a new business have strong influence from their parents.
Furthermore, Asian communities have stronger family ties and family involvement in
business in comparison with Western communities (Basu, 2004). Likewise, Mueller and
Thomas (2001) point out that family backgrounds of individuals acts as stimulator and/or
motivator of their entrepreneurial behaviours where the family business tradition helps an
individual to acquire business knowledge and skills. According to Altinay and Altinay (2006)
those acquired business knowledge and skills if harnessed with their personality traits can
stimulate entrepreneurial activity. Therefore, the following hypothesis is:
H1e: Family business background contributes to tourism entrepreneur’s motivation.
The respondents on this variable are transformed through dummy variable coding 0 for no
family business background and 1 for with family business experience in order to enable
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statistical techniques to be carried out to the test direction and magnitude of
dependent/independent variable relationships.
4.3.1.6 Working Experience
Previous working experience is one of the key factors that influences level of
entrepreneurship (Hayton et al., 2002; Morrison 2000). The entrepreneur’s previous work
experience prior to opening a new venture is an important factor that influences how the
entrepreneur handles the start-up and the growth of the business (Hatch and Dyer, 2004). It
creates a ‘cognitive framework’ that facilitates pattern recognition and contributes to the
management of risks associated with entrepreneurial motivation. Furthermore, according to
Basu (2004) and Westhead et al, (2001) the working experience can assist in building up the
entrepreneur’s knowledge base, developing access to market information and business
networks, improving managerial capability and thus diversifying products and services. In
addition, in circumstances where the context of the new business is similar to the one where
the entrepreneurs gained earlier, it will help the operations of the business (Haber & Reichel,
2007). Based on these findings, this study proposed the following hypothesis:
H1f: Working experience contributes to tourism entrepreneur’s motivation.
The operation of previous working experience is based on Pasanen’s (2003) study; the
respondents have to indicate their previous working experience from four options:
No experience
Experience mainly as an employee
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Experience mainly as a manager
Much experience as an employee and as a manager
The respondents on this variable are transformed through dummy variable coding 0 for no or
without experience and 1 for yes or with experience in order to enable statistical techniques
to be carried out to the test direction and magnitude of dependent/independent variable
relationships.
4.3.2 Tourism Entrepreneur Motivation
According to Delmar (1996), entrepreneur behaviour is defined as actions taken by the
entrepreneur to reach desired goals, and can be measured and determined by the
entrepreneur’s motivation to enter the business. In the context of RBV, the actions taken by
the entrepreneurs are defined as the intangible resources of the firms. According to McGrath
(1996) the intangible resources are embedded in the venture in the form of entrepreneurial
capital conceptualised as the present value of an infinite series of shadow options. Thus, a
tourism entrepreneur has full authority to make a decision on how to manage the firm. The
entrepreneur also utilises the firm’s internal and external resources to ensure the performance
of the business.
Nevertheless, even though previous studies have signified that most tourism entrepreneurs’
motivation is oriented on ‘push’ motives, providing employment for family members,
generating additional income, meeting market need, companionship with guests and
appealing lifestyle (Getz &Carlsen, 2000; Schroeder, 2003) has led to lack of motivation to
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achieve profit in business and less entrepreneurial activity (Smallbone, Leigh & North, 1995;
Shaw & Williams, 1990; Dewhurst &Horibin 1988). Such motives havealso led to constraint
of regional economies and create problems for firms’ survival (Williams, 1988). This is
argued by Ateljevic and Doorne (2000) where the lifestyle motivations of tourism
entrepreneurs have created the ability to position their business in a highly segmented
marketplace or niche market with this unique behaviour of tourism entrepreneurs in their
business goal. Thus, this study hypothesises that utilising business planning, business
alliances, internet adoption and government support will determine the performance of
TSMEs:
H2: Tourism entrepreneur’s motivation will have a positive impact on business planning
H3: Tourism entrepreneur’s motivation will have a positive impact on business alliances
H4: Tourism entrepreneur’s motivation will have a positive impact to TSMEs performance
H5: Tourism entrepreneur’s motivation will have a positive impact to Internet adoption
H6: Tourism entrepreneur’s motivation will have a positive impact to utilisation on
government assistance programmes
This construct was measured using seven items. All items were developed based on Walker
and Brown’s (2004) study (see Table 4.1), which emphasised ‘lifestyle motivation’. The
operation of tourism entrepreneurs’ motivation uses a five-point Likert scale from ‘Strongly
agree’ (1), ‘Disagree’ (2), ‘In between’ (3), ‘Agree’ (4) and ‘Strongly agree’ (5). The
respondents were required to specify the extent to which they agree with the five statements.
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To shed light on the significance of possible differences in perceptions of motivation based
on socio-economic factors, chi-square, independent sample t-test and Analysis of Variance
(ANOVA) will be utilised. The reason for using these tests is that they allow for the analysis
of rank data used in measuring this variable.
Table 4.1: Measurement Items for Tourism Entrepreneur’s Motivation
Entrepreneur motivation’s items
Personal satisfaction is more important than making lots of money Having a flexible lifestyle is more important than making lots of money As a small business I have responsibility to the wider community When I first started the business I was more money oriented than today I think of my business as something that my children can be involved in I would rather keep the business modest and under control than have it grows too big I feel I am running a successful business
Source: Walker and Brown (2004)
4.3.3 Business Planning
Research in small businesses has shown an association between planning and performance.
The literature suggests that planning is a good management practice, and may be beneficial
to business (Gibson et al 2002; Schwenk and Shrader, 1993). According to Berman, Gordon
and Sussman (1997:14) ‘firms that plan produce better financial results than firms that do not
plan. ’Bracker et al. (1986, 1988) also found that firms that undertook strategic planning
perform better financially. Lerner and Almor (2002) contended that planning lays the
groundwork for developing the strategic capabilities needed for high performance. Strategic
planning has been studied by various scholars, including Mintzberg (1973, 1994), Brush and
Bird (1996), Bracker and Pearson (1986), and Bracker, Keats and Pearson (1988). Findings
from these studies agree that there is a positive relationship between strategic planning and
firm performance.
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According to Miles and Snow (1978), successful, proactive firms have the propensity to
invest time in strategic planning. On the contrary, unsuccessful, reactive firms do not invest
time in strategic planning; rather, they ‘fight fires’. Rue and Ibrahim’s study involving 253
small firms in the United States (US) found a positive link between planning sophistication
and growth in sales. A recent study of 168 manufacturing SMEs in Sri Lanka found that
planning and control sophistication led to increased sales (Wijewardena et al., 2004). Their
study concluded that greater sophistication in planning contributed to greater sales.
Therefore, this study hypothesises that:
H7: Business planning will have a positive impact on performance of TSMEs.
Five items were utilised to measure the construct of the importance of business planning and
this is based on Chung’s (2006) study (see Table 4.2). The importance of business planning
on firm performance was measured by evaluating the level of business planning’s importance
on a five-point Likert scale from ‘Not important (1), ‘Least important’ (2), ‘In between’ (3),
‘Important’ (4) and ‘Very important’ (5). The respondents were required to specify the extent
to which they agree with the five statements.
Table 4.2: Operational Variables for Importance of Business Planning
Business planning’s items
Business plan is an effective way of setting business goal and targets Business plan is a useful business strategy to track the business development Business plan improves business performance in term of sales revenue and/or profits Business plan is an effective way to organise the business operations Business plan simplify your role as a manager
Source: Chung (2006)
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4.3.4 Business Alliance
In the small business context, business alliance activity is relevant due to the firms’ limited
resources including goods, information, technology and products as well as limited market
presence (Barnir and Smith, 2002). Building business alliances is a strategic move by SMEs
to overcome limited resources. Having business alliances allows SMEs to acquire financial
resources, technological know-how, market position, reputation, or unique managerial or
human resources.
Alliances reflect the collective use resources and cross-organisational information flows to
assist alliance partners in achieving a future desired strategic position. From the RBV
perspective, this describes how business owners build their businesses from the resources and
capabilities that they currently possess or can acquire (Dollinger, 1999).This activity
provides SMEs with plenty of opportunities to partner in and establish cooperative
arrangements. Research indicates that network building is not only a major new source of
competitive advantage for any company, but a crucial asset to business survival and an
essential global tool. According to Jarrat (1998), alliances enhance the capability of
businesses to perform various activities along the value chain, and deliver superior customer
value through developing and integrating business processes. On the other hand, business
alliance activity that develops due to the limited resources of an organisation will then turn
into an opportunity to expand business performance. It is therefore hypothesised that:
H8: Business alliances will have a positive impact on performance of TSMEs.
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This construct was newly developed for this study based on studies of business alliance (e.g.
Braun, 2002; Lee, 2007; Pansiri, 2009). This item assesses the influence of business alliance
on firm performance. Content validity is conducted in order to ensure the internal consistency
and reliability of these newly developed items. Respondents were asked to rate these items
based on a five-point Likert scale from ‘Not important (1), ‘Least important’ (2), ‘In
between’ (3), ‘Important’ (4) and ‘Very important’ (5). The respondents were required to
specify the extent to which they agree with the five statements. Table 4.3 displays the
importance of the business alliances variables used in this study
Table 4.3: Operational Variables for Importance of Business Alliances
Business alliance’s items
An organisation can actually experience competitive advantage through business alliance Business alliance activity simplifies roles as manager Business alliance activity improves the organizational relationship with customers and/or suppliers Business alliances among businesses is an economic way of delivering services Business alliances is an effective way to gather market- and competitor-related information Business alliances improve business performance in terms of sales revenue and/or profits
Source: Developed by the candidate
4.3.5 Adoption on Internet
ICT is believed to be the most cost-efficient tool to help companies gain bigger markets and
the ability to compete with larger organisations in attracting customers to their products,
services and information (Tan et al, 2009). In the tourism industry, ICT (particularly the
application of the Internet) has proven its consolidating effect on the performance of TSMEs.
Findings by Atlejevic, (2009) showed that tourism operators in Wairarapa, New Zealand are
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taking advantage of ICT and have developed their own in-house ‘research-centre’,
incorporating marketing activities, extensive customer information and analysis.
The initiative has opened up a direct relationship between TSME operators and tourists.
Tourists can make their own travel arrangements on their own computers. Hence, tourism
entrepreneurs must provide value-added services, in utilizing information technology
particularly from the use of the Internet, which enable them to provide value for money for
tourists and increase competency with other industry players. The use of the Internet has
been identified as the main factor that determines whether a firm, industry or region will
succeed in exploiting the opportunities inherent in e-business (Matlay, 2004). In his study,
Matlay concludes that official support for encouraging the use of the Internet among tourism
SMEs is evident, as it will increase the performance of tourism SMEs and create
competitiveness among them. Nodder (2003) found that the adoption of the Internet among
tourism SMEs will boost industry yield, manage information, improve decision-making and
enhance planning processes for the business. From the foregoing arguments, it is
hypothesised that:
H9: The adoption of the internet will have a positive impact on performance of TSMEs.
Five items were utilised to measure this construct. These items examine the advantages of
adopting the internet in business operations. The items were developed based on Chung’s
(2006) study. Respondents were required to rate these items based on a five-point Likert
scale from ‘Strongly disagree’ (1), ‘Disagree’ (2), ‘In between’ (3), ‘Agree’ (4) and ‘Strongly
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agree’ (5). The respondents were required to specify the extent to which they agreed with the
five statements (see Table 4.4).
Table 4.4: Operational Variables for an Adoption on Internet
Internet’s items
The Internet is an efficient way of communicating with customers and/or suppliers An organization can actually experience competitive advantage through Internet technologies The Internet simplify your role as a manager The Internet improves the organizational relationship with customers and/or suppliers The Internet is an economic way of answering customer and/ or suppliers queries
Source: Chung (2006)
4.3.6 Government Assistance Programmes
Based on a review of previous empirical studies, government involvement also factors as one
of the important resources for SMEs’ success (Park & Kim, 2010) and is regarded as an
external resource toward factors affecting SME success (Chittithaworn, et al., 2011). Some
studies have identified the ineffectiveness of government support toward SMEs performance.
According to Storey (2008), government influence on SMEs can exert either a positive or a
negative influence. According to Kozan, Oksoy and Ozsoy (Kozan, et al., 2006)2006),
Turkish SMEs suffer from a lack of financial support, a high burden of taxes and regulations,
and too few government programs.
A study conducted by the Korea Institute for Industrial Economics and Trade (2008) it was
found out that the Korean government supporting policy on R&D has limited effect on SME
performance and it was performed neither effectively nor efficiently. In Iran, the failure rate
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of SMEs is alarming due to the inability of the Iranian government to successfully offer the
necessary support for SMEs (Sorooshian, et al., 2011). In spite of that, in general,
government support has a positive impact on the performance of SMEs because government
support has been shown to be important for small firm success (Yusuf, 1995). Likewise, the
effect of government policy is needed for SME success (Porter, 1980). It was also supported
by other studies that there is a positive association of external supports by the government
toward the success business growth among SMEs (Johnson, Conway, & Kattuman, 1999;
Storey, 1994; Trau, 1996). Despite the ambiguous relationship between government support
and the positive performance of SMEs in general, in the context of this study and the
rigorous commitment and continuous support of the Malaysian government towards TSMEs’
performance through its TSME and tourism policies, this study hypothesises that:
H10: Government assistance programmes will have a positive impact on performance of
TSMEs.
This construct was measured using items that were developed based on Wanhill’s (2004)
study and assess the influence of government assistance programmes on TSMEs’
performance. Respondents were required to rate these items based on a five-point Likert
scale from ‘Strongly disagree (1), ‘Disagree’ (2), ‘In between’(3), ‘Agree’(4) and ‘Strongly
agree’ (5). The respondents were required to specify the extent to which they agree with the
five statements (see Table 4.5).
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Table 4.5: Operational Variables of Government Assistance Programmes
Government’s assistance programmes items
The programmes designed by the government have improved the performance of TSMEs and its competitiveness There is adequate financial assistance in Malaysia to enable those interested in venturing into tourism business activities There is adequate non-financial assistance in Malaysia to enable those interested in venturing into tourism business activities The government has put in place adequate tourism incentives to support the growth and development of TSMEs
Source: Developed by the candidate
In measuring the level of awareness and use of government assistance programmes, this
study adopted a list of assistance programmes from SME (2011) (see Table 5.20). This
allows for the analysis of rank data in measuring this variable.
4.3.7 TSMEs Performance
In investigating the performance of SMEs, issues relating to the type of measurement have
been discussed extensively. Traditionally, financial performance measurement such as profit
margin, turnover, return on investment, return on equity, market share, debt to equity,
earning per share, sales growth and asset growth are some of the key financial ratios that are
particularly used as criteria for measuring organizational performance (David, 1999, p. 287).
This approach has been applied in investigating the performance of big companies and SMEs
in manufacturing. This traditional measure of business success has been based on either
employee numbers or financial performance such as profit, turnover or return on investment.
Economic measures of performance have generally been popular due to the ease with which
they can be administered and applied since they are very much ‘hard’ measures (Barkham et
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al., 1996; Gibb and Davies, 1992; Ibrahim and Goodwin, 1986). Furthermore, as Marlow and
Strange (1994:180) state, ‘all businesses must be financially viable on some level in order to
continue to exist’. However, recent studies have identified that this approach is only
applicable for measuring businesses that aim for profit maximisation (Akbaba, 2012).
Implicit in these measures is an assumption of growth that presupposes all small business
owners want or need to ‘grow’ their businesses.
Nevertheless, not all small business owners want to grow and prefer to keep their size small.
Despite this, their businesses are successful. Thus, non-financial measurement is another tool
in the performance measurement of an organization, particularly in a small-business context.
Since small business owners are motivated to start a business on the basis of lifestyle or
personal factors - and this applies particularly in the tourism industry - non-financial
performance is used to reflect a combination of the personal characteristics and attributes of
owners-managers together with their reasons for starting the business (Walker & Brown,
2004)
As the majority of small-business owners work on a full-time basis within their businesses,
then logically most business decisions are taken by the owners, either individually or with a
partner. Therefore, implying financial criteria alone is not viable to measure success among
businesses that are not keen to maximize profit. Therefore, non-financial criteria are used to
measure businesses that are motivated for lifestyle or personal factors. In order to measure
lifestyle business performance, the intrinsic measures are referred to as ‘psychic rewards’ by
Owen et al., (1992) or psychic income by Wheelock and Baines (1998) and are helpful in
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explaining personal objectives and goals of small business owners. They are often used by
people who have not necessarily been as financially successful, yet are still happy with other
types of rewards such as personal satisfaction. These affective measurements are not
necessarily substitutes for, but are complementary to financial goals.
The firm performance is resultant from the implementation and execution of its strategy
contributing to the bottom-line improvement of the firm. In any business, regardless of the
size of the firm, performance is measured to determine how effective and efficient the firm
actually is. The results then will allow for critical comparisons to compare the firm’s
performance over different time periods, over competitors and compared to industry averages
(David, 1999). In measuring the performance of a firm, financial criteria are usually the most
appropriate measure of business success. However, as discussed previously, many small
enterprise owners and entrepreneurs, specifically in the tourism industry, are motivated to
venture into tourism businesses on the basis of lifestyle or personal factors.
Thus, non-financial performance measurement is also needed to measure the performance of
small enterprise. Furthermore, recent studies that have investigated performance in a small
business context have included both financial and non-financial measurement. For that, this
study will apply both financial and non-financial factors as the performance indicators in
measuring success in TSME performance through number of employees and
owner/managers’ business satisfaction using tested items from research undertaken by
Walker and Brown (2004) and Pasanen (2003). Table 4.6 shows the financial and non-
financial performance measurement of TSMEs.
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Table 4.6: Operational Variables of TSMEs Performance
TSME Performance items
Please estimate the number of full-time employee in 2008 Please estimate the number of full-time employee in 2009 I consider my business succeeded compare to my competitor I am satisfied with my business success Source: Walker and Brown (2004) and Pasanen (2003)
There are four items measuring TSMEs’ performance. The operation of TSME performance
utilises a five-point Likert scale. Items 1 and 2 are based on the number of full-time
employees from ‘1–10’ (1), ’11–20’ (2), ’21–30’ (3), ’31–40’ (4) and ’41–50’ (5). Items 3
and 4 are ranked from ‘Strongly disagree’ (1), ‘Disagree’ (2), ‘In between’ (3), ‘Agree’ (4)
and ‘Strongly agree’ (5). The respondents were required to specify the extent to which they
agree with the statements. These four items were developed for this study based on studies by
Walker and Brown (2004) and Pasanen (2003).
The summary of research questions, research objectives and hypotheses of the study are
presented in Table 4.7.
Table 4.7: Summary of Research Questions, Research Objectives and Hypotheses of the
Study
Subsidiary research questions Hypotheses
1. What is the impact of socio-economic characteristics to tourism entrepreneur’s motivation?
H1a Age contributes to tourism entrepreneur’s motivation.
H1b Gender contributes to tourism entrepreneur’s motivation.
H1c Education contributes to tourism entrepreneur’s motivation.
H1d Ethnicity contributes to tourism entrepreneur’s motivation.
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H1e Family business background contributes to tourism entrepreneur’s motivation.
H1f Working experience contribute to tourism entrepreneur’s motivation.
2. How does tourism entrepreneur’s motivation affect the management practices of Malaysian TSMEs?
H2 Tourism entrepreneur’s motivation will have a positive effect on business planning.
H3 Tourism entrepreneur’s motivation will have a positive effect on business alliances.
H4 Tourism entrepreneur’s motivation will have a positive effect to TSME performance.
H5 Tourism entrepreneur’s motivation will have a positive effect to Internet adoption.
H6 Tourism entrepreneur’s motivation will have a positive effect to utilisation on government assistance programmes.
3. What is the impact of management practices to Malaysian TSMEs performance?
H7 Business planning will have a positive effect on performance of TSMEs.
H8 Business alliances will have a positive effect on performance of TSMEs.
H9 The adoption of the internet will have a positive effect on performance of TSMEs.
4. What is the impact of government assistance programmes on the performance of Malaysian TSMEs?
H10 Government assistance programmes will have a positive effect on performance of TSMEs.
4.4 Data Sources and Description
The secondary data used in this study was obtained sourcing extensively from the Ministry of
Tourism (MOTOUR), Tourism Malaysia, DOS and SME Corp located in Putrajaya and
Kuala Lumpur, Malaysia. These sources are reliable as they are the key provider of related
statistic data and information associated with tourism and TSMEs in Malaysia. However,
besides the above authorities, in order to gather information and compile data on TSMEs
establishments in Malaysia, this study also obtained secondary data from Malaysian
Association of Hotels (MAH) and Malaysian Association of Tour and Travel Agents
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(MATTA) in order to assemble the number of TSMEs in Malaysia, which is not listed on the
official sites.
In terms of primary sources of data, this study was obtained from the owner-managers of
TSMEs to provide related information on socio-economic characteristics, management
practices and TSMEs’ business performance through the administered questionnaires
distributed during the survey. Further discussion on primary data of this study is discussed in
Section 4.4.4.
4.4.1 Survey Area
The study focused on five localities in Malaysia, namely: Kuala Lumpur, Kedah, Pahang,
Pulau Pinang and Sabah. These locations are considered to be representative due to their
higher number of tourist arrivals than other locations in Malaysia. As shown in Table 4.8,
this was confirmed through the statistical data derived from Tourism Malaysia.
Table 4.8: Number of Tourist Arrival, 2009
Location Tourist Arrival
(million) Kuala Lumpur 15.7 Pahang 9.6 Pulau Pinang 5.9 Sabah 5.6 Kedah 4.7 Sarawak 3.9 Melaka 3.7 Johor 3.5 Selangor 2.8 Perak 2.5 Negeri Sembilan 1.6
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Terengganu 1.2 Kelantan 0.8 Labuan 0.2 Perlis 0.1 Putrajaya 0.1
Source: Tourism Malaysia (Tourism Malaysia, 2013c)
The five selected locations of Kuala Lumpur, Pahang, Pulau Pinang, Sabah and Kedah are
considered to be representative due to each of the locations representing each region in
Malaysia except for Southern Region (due to the low of tourist arrivals compared to other
locations in Malaysia). Northern Region is represented by Pulau Pinang and Kedah; Central
Region is represented by Kuala Lumpur; East Coast Region is represented by Pahang; and
Sabah, Sarawak and Labuan (collectively known as East Malaysia) is represented by Sabah.
4.4.2 Population and Sampling Frame
The sample population in this study comprises small- and medium-sized firms providing
products and services of tourism activities (TSMEs). TSMEs are the focus in this study
because they play a role in boosting the tourism industry which generates considerable
income for the country (Ateljevic, 2007; Morrison & Thomas, 1999). TSMEs have a huge
impact in delivering the products and services directly to tourists and it is through this
channel that tourists receive their memorable experience in Malaysia.
In this study, certain tourism characteristic activities of TSMEs will be selected to assure
international comparability of the data. The tourism characteristics for this study are based on
Tourism Satellite Accounts (TSA) established by international organizations: the United
Nations (UN), the World Tourism Organization (WTO), Eurostat and the Organization for
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Economic Co-operation and Development (OECD). However, due to the fragmented nature
of the activities of TSMEs in Malaysia and the nature of available data, the sample will be
limited to TSMEs that provide the following characteristics:
1. Accommodation services
2. Travel agency services, tour operator and tourism guide services.
The sampling frame is developed from MOTOUR, Tourism Malaysia and DOS in order to
achieve the most comprehensive list possible. However, due to the nature of available data on
TSMEs in Malaysia and this study, the characteristics and the total number of TSMEs in each
state and federal territories in Malaysia have not been categorically identified. Furthermore,
some of the TSMEs in Malaysia have not registered with MOTOUR thus creating a
deficiency in compiling the total population of this study. In addition, there are differences
in terms of TSMEs’ statistical data gathered from MOTOUR, MATTA and MAH on the total
number of tourism enterprises providing accommodation services and travel agency services,
tour operator and tourism guide services in all sizes.
In ensuring the sample shares the same attributes, the following criteria are used to select
tourism enterprises into the final sampling frames:
1. Tourism enterprises must have between at least one to 50 employees. This is meeting
the SME definition in Malaysia which is defined and practiced by National SMEs
Development Council (2005). All other sizes above this number will be considered
as larger enterprises.
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2. TSMEs must have operated for more than two years. Longevity is one of the
determinants for being a successful operator in a small business context (Rogerson,
2000; Walker & Brown, 2004) and is perceived as one of the key indicators of small
business success and overall performance (Cuba, Decenzo, & Anish, 1983; A. B.
Ibrahim & Goodwin, 1987).
3. Key informants for this study are primarily the owner–managers of the businesses. In
small business, owner–managers or entrepreneurs have a great deal of influence on
enterprise growth (Tharenou, Donohue & Cooper, 2007). The questionnaire was
designed to be completed by the owner–managers (or entrepreneurs). This is in line
with Campbell’s (1995) suggestion that the key informant should not be chosen for
statistical representativeness but for the knowledge they have that is relevant to the
study.
4.4.3 Sampling Method and Sample Size
In order to select TSMEs from the lists in the five major tourist destinations, the study used
the stratified sampling technique. This technique was adopted for this study because the
stratification process will provide greater effectiveness in controlling extraneous sampling
variation and all-important sub-populations are represented in the sample. It is a two-step
process in which the population is partitioned into sub-populations or strata. The strata
should be mutually exclusive and collectively exhaustive in that every population element
should be assigned to one and only one stratum and no population elements should be
omitted (Maholtra, 2010).
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It is important to avoid extraneous sampling variation because if the characteristics of the
sample are not met, the research objective will not be achieved since the sample is
heterogeneous. For this study, the stratification is based on the selected major tourist
destinations in Malaysia and the subpopulation in this study is the selected tourism
enterprises that provide accommodation services, travel agency services, tour operator
services or tourism guide services.
As the tourism enterprises currently registered in the five locations are of all sizes, the study
was stratified into micro, small and medium size businesses, and then finally into a smaller
sample, a simple random sample of TSMEs was taken on each of the five locations. Each
TSME was assigned with numbers and then selected completely at random. Therefore, each
TSME in this study was equally likely to be chosen. According to Tharenou, Donohue and
Cooper (2007), random sampling the selection of any given participant has no effect on
inclusion or exclusion from the sample, as the choice of participants is independent.
As the study encountered a deficiency on the statistics of TSMEs’ population in the chosen
five locations (Kuala Lumpur, Pahang, Pulau Pinang, Kedah and Sabah), this study used the
Raosoft Sample Size Calculator in order to determine the sample size. The Raosoft calculator
is based on the normal distribution statistical method given by:
x = Z(c/100)2r(100-r)
n = N x/((N-1)E2 + x)
E = Sqrt[(N - n)x/n(N-1)]
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Where n is the sample size, E is the margin of error, N is the population size, r is the fraction
of responses of interest, and Z(c/100) is the critical value for the confidence level c.
Raosoft recommended to use 20,000 as the population, since the sample size difference does
not change for a population larger than 20,000 (Raosoft Inc, 2004). Based on the calculation,
Raosoft provided a sample size of 377 to show a statistical significance at a 5 per cent margin
of error, 95 per cent confidence level and a response distribution of 50 per cent.
4.4.4 Data Collection Methods
4.4.4.1 Personally-Administered Questionnaire Approach
A self-administered questionnaire was design to collect data for this study. This type of
questionnaire was chosen because of its ease of use and it provides the most plausible
alternative for measuring unobservable constructs such as attitudes, values and personalities
(Walker & Brown, 2004). However, as self-administered questionnaires have a low response
rate, the completed questionnaire was collected at the respondent’s premises to increase
participation among the participants. At the same time, the respondents were also provided
with the consideration to return the completed questionnaire via post to increase the freedom
of participants’ decision to participate in this research.
4.4.4.2 Data Collection Procedure
The questionnaire, which was designed, based on the information needed to test the
hypothesis. The choice of answer used in this study is Dichotomous ‘yes’ or ‘no’ and
multiple-choice answers. Besides that, Likert-scale approach is used extensively in this study.
The five-point Likert-scale with anchors such as ‘strongly disagree’ (1) and ‘strongly agree’
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(5) is used to indicate the strength of agreement of their TSMEs performance. The standard
set and rules for item generation is used according to guidelines by Oppenheim (1993).
Then, with the approval from the University’s Human Research Ethics Committee (see
Appendix 4.1), a pilot survey was conducted on a small sample of 12 respondents who were
not part of this study in order to identify and eliminate potential errors. According to Polit
and Hungler (1997), a pre-test is a trial to determine whether an instrument solicits the type
of information envisioned by the researcher. As a result of the pilot test, a number of minor
changes were made to the wording of questions to improve clarity and the instruments
construct reliability. Finally with the finalised questionnaire (see Appendix 4.2), potential
respondents among owner-managers of TSMEs located in Kuala Lumpur, Kedah, Pahang,
Pulau Pinang and Sabah were then contacted and invited to participate in this study through
telephone.
4.5 Statistical Techniques and Data Analysis
The statistical methods employed to analyse the survey data of this study are comprised of
descriptive, inferential and multivariate techniques. Statistical Package for Social Science
(PASW) 18.0 (Coakes, Steed, & Ong, 2009) is used in this study to analyse on descriptive
and inferential analysis while Analysis of Moment Structure 18.0 (AMOS)(Arbuckle, 2006)
is used to run the multivariate techniques for Structural Equations Modelling (SEM) in this
study. This programme is an addition to the statistical package PASW 17.0. Each of these
methods is discussed in the following sections and the results of the analysis presented in
Chapter 5; descriptive and inferential analysis and Chapter 6; multivariate techniques for
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SEM. The following discussion outlines the data processing and data analysis procedures
utilised in this study.
4.5.1 Validity and Reliability of a Construct
In order to ensure the internal consistency of items in constructs and to form the basis of
reliability estimates of the factor analysis, the scales used in this study were tested before
using them in the analysis. The following section discusses the validity and reliability
measurement used in this study.
4.5.1.1 Content Validity
One of the measures was through content validity. A scale has content validity to the extent
that its items represent a chosen subset of the universe of appropriate items (DeVellies,
1991). It is attained by defining precisely what must be measured via literature reviews,
expert panels and pre-testing, to ensure that all possible attributes are included in the scale
(Mcdaniel & Gates, 1999). In accordance with this process, a review of literature was used to
generate potential scale items. The subsequent survey draft was then submitted to a panel of
academics from the Newcastle Business School, University of Newcastle through the
University's Human Research Ethics Committee (HREC) and then to a pre-test sample. The
results of this process indicated that each of the constructs possessed content validity.
4.5.1.2 Constructs Validity
The second measure is construct validity, which refers to the confirmation of a relationship
by independent measurement procedures from a statistical perspective. For construct validity
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to occur, methods measuring the same constructs should all have a high level of correlation
(Churchill, 1999; Hair, et al., 2010). Construct validity is established through the
determination of both convergent validity and discriminant validity.
4.5.1.3 Convergent Validity
Convergent validity refers to the confirmation of a relationship by independent measurement
procedures. Convergent validity of constructs in this study was tested by conducting the full
measurement Confirmatory Factor Analysis (CFA). This is done by examining the t-values
and the satisfactory factor loadings (SFL) where these values should exceed 1.96 and 0.50
respectively (Dunn, Seaker, & Waller, 1994). The results of convergent validity for all items
in this study is further discussed in Section 6.4.1.1
4.5.1.4 Discriminant Validity
Discriminant validty refers to the degree to which measures of conceptually distinct
constructs differ from other constructs (Hair, et al., 2010). It looks at the degree of difference
between constructs tested in a model. Evaluating discriminant validity is vital to ensure that
constructs are not interrelated. Values greater than 0.80 indicate large correlations between
constructs, and this implies a lack of discriminant validity (Campbell & Fiske, 1959). Fornell
and Larckner’s (1981) approach was also utilized to test the discriminant validty. According
to this test, the square root of the AVE for a given construct should exceed the absolute value
of the standardized correlation of the given construct with any other construct in the analysis.
Section 6.4.2.2 has further discussion on the square root AVE results for all construct in this
study.
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4.5.1.5 Constructs Reliability
Reliability measures the extent to which a group of different items are consistent with one
another and whether every measure is free from measurement error (Leech, Barrett, &
Morgan, 2005). It is assumed that each item comprised a true score measuring an underlying
construct. Based on the recommendation from Garver and Mentzer (1999), this study
calculated three estimates of reliability for each constructs: Cronbach’s alpha, composite
reliability and average variance extracted (AVE). The preferred value was equal to or higher
than 0.50, although values exceeding 0.30 are usually adopted as standard (Cunningham,
2007). Composite reliability, also known as construct reliability, measures the internal
reliability of a set of items (Bollen, 1989). Meanwhile, AVE reveals the overall amount of
inconsistency in the indicators of the latent construct. The accepted value for composite
reliability and AVE should be equal to or greater than 0.70 and 0.50 respectively (Hair,
Anderson, Tatham, & Black, 2003).
4.5.2 Descriptive and Inferential Analyses
Using SPSS, the descriptive and inferential analysis is used to identify patterns and general
trends in the dataset of this study. Descriptive analyses such as those for distribution
(variable frequency counts, percentages and cumulative percentages), the central tendency
(mean, median, mode), the dispersion (standard deviation) and the chi-square test (Uma
Sekaran & Bougie, 2009) are employed in this study to describe the TSMEs’ descriptive
statistics and relationship that could explain TSMEs distribution (type of TSMEs businesses,
TSMEs firm size structure, TSMEs ownership structure, TSMEs firm age structure) and
tourism entrepreneurs’ characteristics (demographic factors such as age, gender, level of
education, ethnic group and employment and entrepreneurial experience) in Malaysia.
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Inferential analysis was used to test the relationship among the variables in the data set
(Andereck, 2011). Some of the inferential analyses employed in this study were t-tests and
ANOVA. These analyses were used to investigate the first research question of this study,
investigating the effect of socio-economic characteristics on tourism entrepreneurs’
motivation. The results from these analyses will determine whether the means of socio-
economic characteristics (age, gender, education, ethnic groups, family and employment
experience) differ in the observation groups.
4.5.3 Multivariate Analysis
According to Hair, Black, Babin and Anderson (2010), multivariate analysis refers to all
statistical techniques that simultaneously analyse multiple measurements on individuals or
objects under investigation. It is used to measure, explain and predict the degree of
relationship among variates. Thus, in this study, SEM was utilised to investigate the second
and third research question of this study, the effect of tourism entrepreneurs’ motivation on
management practices (creation of a business plan, business alliance, internet adoption and
government assistance) of Malaysian TSMEs and the effect of management practices on
TSME performance. SEM will examine the causal relationships of Malaysian tourism
entrepreneurs’ perceptions of management practices and the relationship between TSMEs’
management practices and TSMEs’ performance based on statistical fit (for further
discussion see Section 4.5.4.1). Further, SEM was used because of its rigorous approach in
conducting multivariate analysis (Kline, 2005).
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4.5.4 Data Analysis Procedure for SEM
SEM comprises two categories of model: the measurement model and the structural model
(Schumacker & Lomax, 2004). The purpose of the measurement model is to measure the
relationship between observed variables and latent variables in order to determine whether
the theoretical model is consistent with the observed data. The structural model, on the other
hand, is to test the hypothesised relationships between the constructs. The measurement
model is examined using confirmatory factor analysis (CFA) to determine the adequacy of
model fit and then proceeds to the structural model. In determining the adequacy of fit for
both the measurement model and the structural model, several fit indices were applied. The
following discussion outlines the data processing of measurement model using CFA
throughout the analysis of this survey.
4.5.4.1 Measurement Model Procedures
The measurement model was first analysed using CFA. The CFA’s objective is to finalise the
variables listed in the constructs of the framework with the adequate statistical fit and to
ensure the variables make theoretical or substantive sense. The finalised variables with
smaller constructs will represent better variables for the study. First, a full model is specified
based on current theory and practice. Secondly, before testing this full measurement model, a
series of one-factor congeneric models for each construct (which consists of four or more
indicator items) are tested and evaluated separately before being tested in combination with
other constructs. Constructs with two or three indicators should be tested in pairs (Jöreskorg,
1993), as a construct with fewer than four items will lead the degrees of freedom (df) to be
zero. This will generate a zero chi-square value, which is meaningless. If the chi-square
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statistic is unsatisfactory, testing and changes of the models are done one step at a time,
provided that the changes make substantive sense. Once constructs have been examined
singly, in pairs, or both, a full measurement model comprising all the constructs of interests
is then evaluated.
CFA analysis using AMOS is performed by the maximum likelihood (ML). ML assumes
multivariate normality and continuity of the data being analysed. Another estimation method
that makes no distributional assumptions is also available when the data violates the
assumption (i.e. weighted least squares (WLS) or asymptotically distribution-free (ADF);
(Browne 1984). However, this method of distribution-assumption-free estimation requires
very large sample sizes and is usually not achievable in social science research (Muthén
1993). Therefore, to account for this non-normality, the Bollen-Stine bootstrap p (Bollen&
Stine 1992) may be applied as a post-hoc adjustment in producing the correct p value for the
assessment of model fit. The Bollen-Stine p-value is a bootstrap modification of the normal
theory χ2, and is based on generating an adjusted chi-square distribution that takes into
account the extent to which the data depart from normality. Therefore, ML estimation
together with the Bollen-Stine bootstrap p will be utilised in assessing model fit in this
research. This is most useful when the data indicate departures from normality, and
particularly departures from multivariate normality.
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Table 4.9: Index Category and the Level of Acceptance
Fitness category
Index Level of acceptance
Explanation
Absolute fit
Discrepancy Chi Square (Chisq)
P > 0.05 Sensitive to sample size > 200. If the sample obtained for the study is greater than 200, the minimum value of Chisq could be ignored (Hair, Anderson, Tatham, & Black, 1995; Joreskorg & Sorbom, 1984)
Root Mean Square of Error Approximation (RMSEA)
RMSEA < 0.08 Range 0.05 to 1.00 acceptable (Browne & Cudeck, 1993)
Goodness of Fit Index (GFI)
GFI > 0.90 GFI = 0.95 is a good fit (Byrne, 2010)
Incremental fit
Adjusted Goodness of Fit (AGFI)
AGFI > 0.90 AGFI = 0.95 is a good fit (Byrne, 2010)
Comparative Fit Index (CFI)
CFI > 0.90 CFI = 0.95 is a good fit (Byrne, 2010)
Tucker-Lewis Index (TLI)
TLI > 0.90 TLI = 0.95 is a good fit (Byrne, 2010)
Normed Fit Index (NFI)
NFI> 0.90 NFI = 0.95 is a good fit (Byrne, 2010)
Parsimonious fit
Chi Square/Degrees of Freedom (Chisq/df)
Chi Square/df < 5.0 The value should be less than 5.0 (Marsh & Hocevar, 1985)
Source: Modified from Awang (2012)
In determining the adequacy of fit for the measurement model, several fit indices were
applied. Hair et al (1995, 2010) and Holmes-Smith (2006) recommended the use of at least
three fit indices by including at least one index from each category of model fit. The three
categories are absolute fit, incremental fit and parsimonious fit. Table 4.9 presents the level
of acceptance and an explanation for each of the fitness categories.
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In this study, Chisq, RMSEA, CFI, TLI and Chisq/df are selected for the purpose of
measuring the model fit indices that represent the three-fitness category. Following is a
discussion on the mentioned fit indices.
• Chisq
The significance value of χ² test of p-value should be more than 0.05 to indicate the model
fits well (Kline, 2005). The χ2 statistic is a test of whether the matrix of implied variances
and covariances is significantly different from the matrix of empirical sample variances and
covariances. When the probability is more than .05, it indicates that there is no discrepancy
between the matrix of implied variances and covariances and the matrix of empirical sample
variance and covariances. This implies that the data fit the model well, as the parameter
estimates raised by this model yield such a small value for the discrepancy function.
• RMSEA
Root-mean-square-error of approximation (RMSEA), with values of 0.08 or less is
considered to indicate a good fit between data and the hypothesised model (Hu & Bentler,
1998).The RMSEA was originally proposed by Steiger and Lind (1980) and was developed
by Browne and Cudeck (1993) as an absolute index that does not require a baseline
comparison. RMSEA assumes that there will be no perfect model to fit any population.
Therefore, it takes into account the closest approximation to reality (Browne & Cudeck
1993). The χ2 statistic, degrees of freedom, and sample size for the target model are required
to calculate this index (Rigdon 1996). When the value of RMSEA is close to zero, this
indicates perfect fit, and as the value increases, the model fit deteriorates. A nice
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characteristic of the RMSEA is the confidence interval associated with this fit index (Browne
& Cudeck 1993). Within a hypothesis-testing framework, a ‘test of close fit’ is examined by
testing the null hypothesis (i.e. RMSEA ≤ .05) and an alternative hypothesis (i.e. RMSEA ≥
.05). For confidence interval with the value of more than .05, the null hypothesis is rejected,
indicating that the data are not a close fit to the model. A close fit is still acceptable if the
confidence interval does not exceed .05 (Hancock & Freeman 2001). If the RMSEA value is
more than .05 but still equal to or below .08, then the data indicate a reasonable fit to the
model (Browne & Cudeck, 1993). Researchers are compelled to utilise the RMSEA fit index
because of the available confidence interval that gives essential information about the
accuracy of the estimate of fit, which is not available for most other fit indices (MacCallum&
Austin 2000). Hence, this study utilizes RMSEA with a value of .08 or less to indicate model
fit.
• CFI
The CFI incremental fit index was proposed by Bentler (1990) based on the χ2 statistic. CFI
measures the improvement in the change from target model to independence model (i.e. a
model in which all variables are assumed to be uncorrelated and only error variances are
estimated). Similar to NFI, the value of CFI ranges from 0 to 1. A CFI value that is closer to
1 indicates a satisfactory fit of the data. CFI is one of the most popular fit indices reported in
SEM analysis, as it is relatively independent of sample size (Bentler 1990).
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• TLI
TLI also known as non-normed fit index (NNFI) was originally proposed by Tucker and
Lewis (1973) and was further developed by Bentler and Bonett (1980). TLI compares the
lack of fit between target model and independence model that is calculated by the χ2 statistic
(Hu & Bentler 1998). TLI examines the relative improvement for each degree of freedom of
the target model over the independence model, which is scaled to an estimate range of 0-1. A
TLI value of .95 is favoured to indicate a good-fitting model. Nevertheless, a TLI value of
more than 1 specifies an over-fitting model. TLI has been consistently shown to be unrelated
to sample size (Anderson & Gerbing 1984; Marsh, Balla & McDonald 1988). Consequently,
TLI is more sensitive to the occurrence of model misspecification than the comparative fit
index (Hutchinson & Olmos 1998). This will be discussed further in the next section.
• Chisq/df
Chisq/df, also known as Normed chi-square (Schumacker & Lomax, 2004) is a simple ratio
of chi-sq to the degrees of freedom for a model. Generally, Chisq/df associated with better-
fitting models, except in circumstances with larger samples (greater than 750). Chisq/df is
widely used because if it is not provided directly by the software program, it is easily
calculated from the model results (Hair, et al., 2010).
Following the CFA procedure, besides meeting the statistical fit of measurement model, the
following condition is also fulfilled throughout this study.
1. The standardised factor loadings (SFL) on every item should be more than 0.5. For
any items with factor loadings below 0.5, the deletion of items is done one item at a
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time. This procedure is repeated until all the factor loadings for each item exceeded
0.5 (Byrne, 2010).
2. The squared multiple correlation (or R2) for every item should be more than 0.4. Any
items that had R2 less than 0.4 should be deleted, and the deletion of items is done
one time at a time. This procedure is repeated until all R2 for each item are more than
0.4 (Awang, 2012).
3. The modification indices (MI) with value above 15 indicate the correlated error
between items. The deletion of items with the lower factor loading or set identified
pair of correlated error as ‘free parameter estimate’ is done one item at a time. This is
repeated until the model meets the statistical fit of model fitness (Awang, 2012)
Finally, the CFA results indicate that the measurement model possesses good fit, thereby
demonstrating that analysis can proceed to the structural model.
4.5.4.2 Structural Model Procedures
After conducting CFA analysis to the both measurement and full measurement model, the
finalised constructs were then used to proceed to the structural model to examine and analyse
the hypothesised between constructs in this study. In determining the adequacy of fit for the
structural model, similar fit indices were applied as measurement and full measurement
models: Chi-square, RMSEA, CFI, TLI, and Chisq/df.
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4.6 Concluding Remarks
This chapter outlined and discussed the research methodology to be applied in the study. The
operationalisation of each variable utilised in this study to generate the research instrument
was also discussed. This chapter indicated the procedures in soliciting the target population
and the ways in which potential respondents were contacted and invited to participate in this
research. Furthermore, the analysis procedures utilised in this research were explained.
Finally this chapter highlighted the methodology of SEM and the ways that the model fit
indices were used to indicate whether the proposed model fits with the empirical data. The
next chapter presents the descriptive analysis and results of this study.
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CHAPTER FIVE
AN EMPIRICAL INVESTIGATION ON THE CHARACTERISTICS OF TSMEs AND MANAGEMENT PRACTICES OF TOURISM ENTREPRENEURS IN
MALAYSIA
5.1 Introduction
Tourism represents an increasingly important industry in the Malaysian economy. TSMEs
now play a greater role in Malaysian tourism industry and contribute to its overall
performance. Various policies and strategies have been implemented to enhance TSMEs’
business performance. Therefore, a review of TSME characteristics and management
practices will help to provide better insight on TSME development in Malaysia. This chapter
reports and discusses the findings of the characteristics of TSMEs and the management
practices of tourism entrepreneurs in Malaysia. This chapter will also investigate the
differences and similarities that exist in organisational and managerial styles among TSMEs
in Malaysia.
The organisation of this chapter is as follows: Section 5.2 discusses the structures of TSMEs
based on the responding firms. Section 5.3 examines the TSMEs’ entrepreneurial
characteristics. Section 5.4 explores on the characteristics of TSMEs management practices.
Section 5.5 summarizes the findings in this chapter.
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5.2 Structure of TSMEs in Malaysia
This section reports the characteristics of TSMEs in Malaysia to better understand their
distinctiveness between each location. The discussion looks at the following TSME
characteristics: type of business, size, ownership and year of establishment to examine and to
provide some insight on TSMEs’ organisational characteristics in Malaysia.
5.2.1 Type of TSMEs’ Businesses
There were 750 questionnaires distributed to a random sample of TSMEs.370 were returned,
yielding a 49.3 per cent response rate. Only 346 (or 46.1 per cent) were found useable for this
study. The findings of this study are based on a sample of 346 TSMEs in Malaysia.
Table 5.1 depicts the type of TSMEs surveyed in this study. TSMEs offering accommodation
services make up 51 per cent (or 176 TSMEs), while the other 49 per cent (or 170 TSMEs)
are travel agents, tour operators and other tourism guide services providers. Respondent
TSMEs are evenly distributed in terms of the types of tourism services they offer.
Location plays a role in terms of the type of tourism businesses at tourist attractions planned
by the State Tourism Actions Department (STAD) in each state. As discussed in Chapter 2,
the natural resources are one of the factors in promoting local tourist attractions. In addition
to the natural resources, each state also extends its local attractions by offering man-made
attractions such as museums, shopping complexes, historical places and festival celebrations.
Diversifying the attractions creates attention from tourists (Weaver & Lawton, 2001) and
these man-made (created) and socio-cultural (cultural events and festivals) attractions show
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positive impact to tourist arrivals and the overall tourism industry (Jafari & Ritchie, 1981).
Two states, Pahang and Penang, show dominance on certain types of tourism businesses:
Pahang on nature and adventure, and Pulau Pinang on City Excitements.
Table 5.1: Distribution of TSMEs by Location and Type of Business
Location Total TSMEs
Type of business Travel agency services, tour operator, and tourism guide
services
Accommodation services
Freq. %a Freq. %a Freq. %a Pahang 70 20.3 40 11.5 30 8.7 Pulau Pinang 69 19.9 28 8.1 41 11.8 Kedah 71 20.5 36 10.4 35 10.2 Kuala Lumpur 72 20.8 34 9.8 38 11.0 Sabah 64 18.5 32 9.2 32 9.3
Total 346 100.0 170 49.0 176 51.0 Note: a% refers the number of type of businesses express as a percentage of the total
number of TSME
Source: Data derived from survey
Pahang shows the highest number of TSMEs involved in travel agency services, tourist
operations and tourism guide services. This is reflected in Pahang’s location, which is in the
East Coast Region of Malaysia. It has a variety of eco-tourism attractions compared to other
states in Malaysia. It is surrounded by the highlands, rainforest which covers 66 per cent of
the state’s area, and lakes full of various flora and fauna. Pahang has been extensively
promoted as the key tourism attractions by MOTOUR and Pahang STAD. These natural
resources of Pahang have led to the wide promotion of eco-tourism activities by the STAD of
Pahang, which focuses primarily on its niche tourism products. This may imply the higher
162
number of registered travel agency services, tour operator and tourism guide services in
Pahang compared to other locations in Malaysia.
Meanwhile, Pulau Pinang has the highest establishment of accommodation services in this
study, with 41 TSMEs or 60 per cent of TSMEs. Only 40 per cent were travel agency
services, tour operator and tourism guide services. This again may reflect its key tourism
attractions and promotions carried out by Pulau Pinang STAD on its highly focused tourism
products: City Excitements, and Islands and Beaches. Thus, many resorts are primarily
located along the Pulau Pinang, including famous beaches such as Tanjung Bungah, Batu
Feringhi and Teluk Bahang. The state also continuously refurbishes its city attractions,
particularly at Gurney Drive, a famous place offering a variety of Penangite delicious local
foods.
The other locations of Kedah, Kuala Lumpur and Sabah do not focus on niche tourism
products but concentrate on both natural-resource attractions and city excitements attractions.
This justifies the equal distribution of the type of TSME businesses: travel agency services,
tour operators and tourism guide services and accommodation services established in these
locations.
In order to find out whether the location of TSMEs and type of TSME business had a
relationship that could be used to explain the distribution above, the Pearson Chi-Square (χ²)
test for independence was carried out. Prior to performing the test throughout the chapter, the
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underlying assumptions of the test were investigated. A contingency table generated by SPSS
fulfilled the following conditions (Coakes, et al., 2009):
1. Observations should be randomly sampled from the population of all possible
observations.
2. Each observation should be generated by a different subject, and no subject is counted
twice.
3. When the number of cells is less than ten and particularly when the total sample size is
small, the lowest expected frequency required for a chi-square test is five. However, the
observed frequencies can be any value, including zero.
Following the test for independence and given the calculated value of χ² (DF = 4, N = 346) =
4.01 and a p-value of 0.40 which is more than the critical value of 0.05, the study accepts the
null hypothesis and concludes that there is no significant relationship between location and
type of business at the 5 per cent significance level (see Appendix 5.1). The statistical result
indicated that there is no difference in terms of the TSMEs’ location and its type of business.
This indicates that regardless of the fact that certain locations such as Pahang and Pulau
Pinang have advantages on its natural resources which contribute to their tourism attractions
compared to other locations in Malaysia, it has no influence on the preferences on type of
tourism businesses established in the location. This implies that travel agents, tour operators
and other tourism guide services providers and accommodation services are the main services
providers in tourism industry (Hills & Cairncross, 2011).
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5.2.2 TSMEs Firm Size Structure
Firm size in this study is measured by the total number of full-time employees. Respondent
TSMEs in this study are primarily small-sized TSMEs with 62 per cent, while medium-sized
TSMEs make up the remaining 38 per cent. Table 5.2 depicts the respective frequency
distribution of the TSMEs by location and size.
According to Table 5.2, 213 firms (or 62 per cent of the total sample)are of small size; that is,
they have 5 to 19 full-time employees.133 firms (or 38 per cent) are of medium size and have
20 to 50 full time employees. Reviewing the data in terms of TSME size distribution across
locations, Pahang has the highest number of small-sized enterprises with 67 firms or 19.5 per
cent; followed by Pulau Pinang with 45 firms or 13.0 per cent; and Kuala Lumpur with 44
firms or 12.8 per cent. Kedah dominates the medium-size enterprises with 44 firms or 12.6
per cent; followed by Sabah with 34 firms or 9.6 per cent of medium-size enterprises from
the total of TSMEs in this study.
Table 5.2: Distribution of Firm Size by Location
Location Total TSMEs
TSMEs firms size (Full Time Employee)
Small (5-19)
Medium (20-50)
Freq. %a Freq. %a Freq. %a Pahang 70 20.3 67 19.5 3 0.8 Pulau Pinang 69 19.9 45 13.0 24 7.0 Kedah 71 20.5 27 7.9 44 12.6 Kuala Lumpur 72 20.8 44 12.8 28 8.0 Sabah 64 18.5 30 8.8 34 9.6
Total 346 100.0 213 62.0 133 38.0 Note: a% refers the number of firm size express as a percentage of the total number of TSME
Source: Data derived from survey
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Further analysis was carried out to explain the distribution above. The results from the test
for independence showed the calculated value of χ² ( DF = 4, N = 346) = 57.35 and a p-value
of 0.00, which is less than the critical value of 0.05 (see Appendix 5.2). The study therefore
rejects the null hypothesis and concludes that there is a significant relationship between
TSMEs’ locations and firm size, at the 5 per cent significance level. This can be related to the
preference to keep the business small in order to avoid the complexities in handling bigger
tasks in business operation (Jaafar, Abdul-Aziz, Maideen, & Mohd, 2011).
5.2.3 TSMEs Ownership Structure
TSMEs ownership structure is important because previous research conducted on SMEs in
other industries indicates that small family firms are positively associated to SME
performance (Davis, Dchoorman, & Donaldson, 1997; Wenyi, 2009).
Figure 5.1a and Figure 5.1b illustrate the ownership type by location in the sample firms.
Ownership type in this study is categorized into family and non-family business, and each
category is further differentiated in terms of sole proprietorship, partnership or private
limited firms. Figure 5.1a indicates that the majority of TSMEs in this study are family
owned with 231 firms or 67 per cent. Out of this 67 per cent, 82 firms or 39 per cent are
registered as private limited firms. The findings of the higher number of family-owned
TSMEs is in line with the structure of SME ownership surveyed by Rachagan and
Satkunasingam (2009) and Rahman (2006) who also found a dominance of family owned
SMEs in Malaysia. Findings in this study also indicate that the majority of TSMEs’
respondents with 208 firms or 59 per cent operate as sole proprietorships and partnerships.
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Figure 5.1a: TSMEs by Type of Family Business and Type of Ownership
Note: Percentage is refers the types of ownership express as a percentage of the total number
of TSME
Source: Data derived from survey
The family TSMEs in Pahang, Kuala Lumpur and Sabah prefer to register their firms as
private limited companies. This is quite interesting because only the non-family TSMEs from
the northern region (Pulau Pinang and Kedah) prefer to register their firms as sole
proprietorships and partnerships. Based on the Pearson Chi-Square analysis, there is no
significant relationship between type of family business and type of ownership. χ² (DF = 2, N
= 346) = 3.0, and p-value = 0.22, which is more than the critical value of 0.05 (see Appendix
5.3).
3%
7% 7%
3%4%4%
11%
9%
5%
7%
11%
5%6%
11%
7%
0%
2%
4%
6%
8%
10%
12%
Pahang Pulau Pinang Kedah Kuala Lumpur Sabah
Sole Propriertorship Partnership Private Limited Company
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Figure 5.1b: TSMEs by Type of Non-Family Business and Types of Ownership
Note: Percentage isrefers the types of ownership express as a percentage of the total number
of TSME
Source: Data derived from survey
However, in terms of the location and type of ownership, the study rejects the null hypothesis
and concludes that there is a significant relationship at the 5 per cent significance level. The
calculated value of χ² (DF = 8, N = 346) = 26.92, and p-value =0.00, which is less than the
critical value of 0.05 (see Appendix 5.4). The simplicity in establishing and terminating sole
proprietorships and partnerships compared to private limited companies, has made these two
types of business ownership the most common ownership among Malaysian SMEs (Small
and Medium Enterprise Corporation Malaysia, 2011).Similar empirical studies by Wibowo
(2007) and Pidani (2011) found out a similar pattern of SMEs ownership structure in
Indonesia.
4%
6%
1%
3%2%
9%
4%
11%
9% 9%
11%
8%
6%
9%10%
0%
2%
4%
6%
8%
10%
12%
Pahang Pulau Pinang Kedah Kuala Lumpur Sabah
Sole Propriertorship Partnership Private Limited Company
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5.2.4 TSMEs Firm Age Structure
TSMEs in this study are also reported in terms of the years they are established. The number
of years in operation can explain the extent of accumulated knowledge, experience and
capabilities in managing the business operation (Graner & Isaksson, 2002). Thus in the
context of firm performance, older firms relatively will show higher capabilities from
experience than younger firms which are still new and emerging in the industry (Camison-
Zomoza, Lapierda-Alcami, Segarra-Cipres, & Boronat-Navarro, 2004).
Figures 5.2a and 5.2b show the majority of TSMEs in Malaysia are considered experienced
firms. More than 197 firms or 57.0 per cent have been in operation for more than 30 years.
About 120 firms or 34.6 per cent were established in between 1992– 2002. 59 firms or 17.0
per cent and 18 firms or 5.2 per cent of the sampled TSMEs in Malaysia are the longest
running in the business, established before 1980. There are 149 firms or 43 per cent that were
established in between 2003 – 2009. Pulau Pinang and Kuala Lumpur contains
predominantly older firms, as many have been in the industry longer compared to other
TSMEs in Malaysia. This can be attributed to the early tourism programs and promotions
carried out in these two states by the Malaysian Government since the Second Malaysian
Plan (1971-1975) (Economic Planning Unit, 1971).
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Figure 5.2a: Proportion of TSMEs Travel Agency, Tour Operator and Tourism Guide
Service by Year of Establishments
Note: Percentage is travel agency, tour operator and tourism guide services express as a
percentage of the total number of TSME
Source: Data derived from survey
Figure 5.2b: Proportion of TSMEs Accommodation by Year of Establishments
Note: Percentage is accommodation services express as a percentage of the total number of
TSME
Source: Data derived from survey
0.3%
0.9%
0.0%0.9%
0.0%
2.0%
0.3%
2.3%1.7% 1.7%
3.2%
4.0%3.5% 3.5%
4.9%
6.1%
2.9%
4.6%3.8%
2.6%
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
6.0%
7.0%
Pahang Pulau Pinang Kedah Kuala Lumpur Sabah
Before 1980 1981-1991 1992-2002 2003-2009
0.0%
1.7%
0.6%0.9%
0.0%
1.7%1.2%
0.3%1.7%
4.0%
2.0%
3.2%
4.0%
3.2% 2.9%
4.9%
5.8%5.2% 5.2%
2.0%
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
6.0%
7.0%
Pahang Pulau Pinang Kedah Kuala Lumpur Sabah
Before 1980 1981-1991 1992-2002 2003-2009
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Further analysis was conducted to test for independence to find out whether TSMEs ‘location
and year of the business established had a relationship to explain the distribution above. The
results from the Pearson Chi-Square test showed the calculated value of χ² (DF = 12, N =
346) = 39.93 and a p-value of 0.00 which is less than the critical value of 0.05 (see Appendix
5.5). The study therefore rejects the null hypothesis and concludes that there is a significant
relationship between the location and year of establishment at the 5 per cent significance
level.
Based on the data, the number of newly established TSMEs in 1992 onwards increased for
both types of TSMEs businesses: travel agency and tour operator and tourism guide services
and accommodation services. The periods between 1992 – 2002 and 2003 – 2009 saw more
than 100 being established in the tourism industry: 120 firms or 34.6 per cent in between
1992 – 2002, and 149 firms or 43 per cent in 2003 – 2009. Compare the figures to only 77
firms or 22.2 per cent of TSMEs established before 1991. The government’s tourism-specific
programs and policies (especially during the Sixth, Seventh and Eighth Malaysia Plans)
contribute to the high number of TSMEs. During these periods, Malaysia government
emphasized a highly integrated approach and implementation on tourism planning which
increased the number of TSME establishments. For example, during the Sixth Malaysia Plan
(1991-1995), the government has set up a special fund for tourism of RM 200 million,
focusing on small and medium-sized projects. The government also introduced a new clause
of the Investment Incentive Act of 1968,which provided an income tax exemption for tour
operators (Economic Planning Unit, 1991).
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During the Seventh Malaysia Plan (1996 – 2000), the government focused on expanding the
country’s tourism activities, products and market (Economic Planning Unit, 1996). In the
Eighth Malaysia Plan, the government focused on specialised tourism products and services
such as eco-tourism, agro-tourism, homestay programmes, cultural heritage tourism, thematic
events, MICE, sports and recreation, education tourism and the Malaysia My Second Home
programme (Economic Planning Unit, 2008). In the Ninth Malaysia Plan, the government
promoted the country as a preferred location for feature films, television commercials and
documentaries in addition to the specialised tourism products and services (Economic
Planning Unit, 2006). These Malaysia Plans have expanded tourism business opportunities
among Malaysians and boosted the establishments of TSMEs during these periods.
5.3 Tourism Entrepreneur Characteristics in Malaysia
In order to better understand tourism entrepreneur behaviour and to find out the similarities
or differences that exist among Malaysian tourism entrepreneurs, this study looked into
certain tourism entrepreneurs’ characteristics. This includes the following demographic
factors: age, gender, level of education, ethnic group, and their work and entrepreneurial
experience. The following sections will discuss each of the characteristics surveyed in this
study.
5.3.1 Age of Tourism Entrepreneur
Age has some influence on the behaviour of an entrepreneur. Many empirical studies have
found that certain age groups have an influence entrepreneurial activity. In Malaysia, the
working population is between 15 to 64 years old and it comprises 67 per cent of Malaysia’s
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total population (Department of Statistics, 2012c). Table 5.3 presents tourism entrepreneurs
sampled in this study in terms of age and location. The majority of tourism entrepreneurs are
in a relatively mature age group. About 180 of respondents or 85.2 per cent are at least 41
years old, with 42.2 per cent aged between 41 and 50 years. Approximately 14.8 per cent of
the tourism entrepreneurs belong to the younger age group (21 to 30 years old). This finding
is similar with other studies where themajority of adults above 30 years of age were more
active in entrepreneurship than any other age group (eg Chittithaworn, et al., 2011;
Kristiansen, et al., 2003; Reynolds, et al., 2000; Roland, Noorseha, Leilanie, & Mohar, 2010)
Table 5.3: Distribution of TSMEs by Age of Tourism Entrepreneur by Location
Note: a % refers age of tourism entrepreneur express as a percentage of the total number of
TSME
Source: Derived from survey
Location Total TSMEs
Age group 21- 30 %a 31-40 %a 41-50 %a Above
51 %a
Freq. %a Freq. %a Freq. %a Freq. %a Freq. %a Pahang 70 20.3 7 2.0 22 6.4 34 9.8 7 2.0 Pulau Pinang
69 19.9 5 1.4 31 9.0 29 8.4 4 1.2
Kedah 71 20.5 10 2.8 24 7.0 32 9.2 5 1.4 Kuala Lumpur
72 20.8 18 5.3 21 6.2 26 7.4 7 2.0
Sabah 64 18.5 11 3.3 16 4.6 26 7.4 11 3.2 Total 346 100.0 51 14.8 115 33.2 146 42.2 34 9.8
Younger age group (30 years
below)
Mature age group (31 years above)
Total 346 100.0 51 14.8 295 85.2
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The Pearson Chi-Square (χ²) test for independence was carried out to find out whether
location of TSMEs and age of tourism entrepreneurs had a relationship to explain the
distribution above. The results from the test for independence showed a calculated value of χ²
(DF = 12, N = 346) = 20.53 and a p-value of 0.05 which is more than the critical value of
0.05 (see Appendix 5.6). The study therefore accepts the null hypothesis and concludes that
there is no significant relationship between the locations and age of tourism entrepreneurs at
the 5 per cent significance level.
The findings reflect that the younger population in Malaysia is not heavily involved in the
country’s tourism industry. This can be due to the trend of the younger population (18-30
years old) in Malaysia preferring to stay in a college or university or to work in the private
sector, rather than owning a business after their secondary education. Data from the Ministry
of Higher Education indicated that in 2007, there were approximately 748,793 of Malaysians
aged between 18 to 30 years old in public and private education institutions (Ministry of
Higher Education of Malaysia, 2010) which were 13 percent of the Malaysian population
(Department of Statistics, 2012c). Those who are aged 31 or above are more financially
stable have work experience and have the interest to start a business. Thus, the majority of
tourism entrepreneurs belong to this group.
In order to address the first research question of investigating the impact of socio-economic
characteristics (age factor has an impact on tourism entrepreneur’s motivation), a one-way
analysis of variance (ANOVA) was carried out in an attempt to determine whether the means
of a variable differ from one group of observations to another. Prior to performing the
174
ANOVA test throughout the chapter, the following underlying assumptions of the test were
carried out (Coakes, et al., 2009):
1. The dependent variable data should be at the interval or ratio level of measurement.
2. The populations from which the samples have drawn should be normal.
3. The scores in each group should have homogeneous variances. Levene’s test determined
whether the variances are equal or unequal.
4. The post-hoc comparison (Tukey HSD) value with the asterisks (*) identify which group
are significantly different from one another.
Table 5.4 depicts the results on Hypothesis H1a – Age contributes to tourism entrepreneur’s
motivation. The Levene’s test results (F-value = 0.88 , p-value = 0.44, p>0.05) were not
significant and the assumption of homogeneity of variances was not violated. Then, based on
the ANOVA’s test, the overall F is statistically significant (F-value = 1.22, p-value = 0.03,
p<0.05). This indicates there are some differences between the age of groups on tourism
entrepreneur’s motivation. Hence, post-hoc test or known as Tukey HSD, will provide
information on the differences in means among the groups by the asterisks (*) next to the
value of the group that identify which group are significantly higher than the other. Based on
the Tukey HSD results, it shows there are differences in means among the group of age.
Entrepreneurs aged between 31 – 40 years old (M = 3.15, SD = 0.88, F-value = 1.22, p-value
= 0.03) where p is less than the critical value of 0.05 is significantly different from any other
age group. The study therefore reject the null hypothesis and concludes that there is a
significant relationship between age and motivation where at certain ages there is a
considerable impact on entrepreneurs’ motivation to enter tourism businesses. In order to
175
investigate the correlation significant relationship, since one of the data is on ordinal scales,
the Spearman’s rank-order correlation (rs) was used throughout the chapter. Based on the
correlation analysis results, a significant positive correlation was found between motivation
and age, rs = 0.20, p-value = 0.00, which is less than critical value of 0.05 (see Appendix
5.7). Further discussion on these results is provided in Section 6.6.
Table 5.4: ANOVA Results of Hypothesis H1a Relating Tourism Entrepreneur’s Age
and Motivation
Characteristics Mean sd
Levene’s Test for Equality of
VariancesANOVA’s Test
Results H1a
F Sig. F Sig.
Motivation Under 30 3.02 0.89
0.88 0.44 1.22 0.03 Supported Between 31-40 3.15* 0.88 Between 41-50 2.85 0.76 Above 50 2.59 0.70
Source: Data derived from survey
5.3.2 Gender
The gender of an entrepreneur is important, as some studies have found that gender
influences business operations and to a certain extent causes low business performance.
Furthermore, it is generally accepted that males have stronger entrepreneurial intentions than
females. However, based on Zhao, Seibert and Hills (2005) the business environment can be
a barrier to female entrepreneurs whereby it limits their ability to access necessary resources
or receive necessary support to become successful entrepreneurs. In the context of tourism
business environments in Malaysia, the gender factor may have different implications.
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Table 5.5 presents the findings in terms of gender of tourism entrepreneurs. Respondents in
this study from all tourism destinations are predominantly male entrepreneurs, (251 male
respondents, or 73 per cent of total respondents) while the rest are female with only 95 (27
per cent). A possible explanation for the higher number of male tourism entrepreneurs can be
attributed to the influence of Malaysia’s traditional culture, where males normally act as the
head of the family and the primary decision maker, and enjoying more privileges than
females. There are more male tourism entrepreneurs in all locations compared to females
except in Kedah.
Table 5.5: Distribution of Tourism Entrepreneurs by Location and Gender
Locations Total TSMEs
Gender Male Female
Freq. %a Freq. %a Freq. %a Pahang 70 20.3 58 16.7 12 3.5 Pulau Pinang 69 19.9 47 13.5 22 6.5 Kedah 71 20.5 40 11.5 31 8.9 Kuala Lumpur 72 20.8 56 16.2 16 4.6 Sabah 64 18.5 50 14.5 14 4.0
TOTAL 346 100.0 251 72.5 95 27.5 Note: a% refers gender of tourism entrepreneurs express as a percentage of the total
number of TSME Source: Data derived from survey
According to Jaafar et al (2011), the involvement of women in this industry is indirect and
many of them do not hold positions in the company. Furthermore, Jimenez (2012) reported
that the relationship between gender and entrepreneurship is linked to culture and people’s
habits. In developed countries, the people enjoy greater equality between men and women. In
other countries, it is unusual for women to work or develop their own projects. In general, the
ratio between male and female entrepreneurs in this study is in line with other similar
empirical studies (eg Carlsen, et al., 2008; Gartner, 2004; Morrison, et al., 1999)
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Further analysis was conducted to test the relationship and to explain the distribution above.
The results from the Chi-Square test showed a calculated value of χ² (DF = 4, N = 346) =
15.77 and a p-value of 0.003 which is less than the critical value of 0.05 (see Appendix 5.8).
The study therefore rejects the null hypothesis and concludes that there is a significant
relationship between the location and gender of tourism entrepreneurs in Malaysia, at the 5
per cent significance level.
Independent t-tests were carried out in an attempt to address and determine the impact of the
following socio-economic characteristics: gender factor toward the motivation of tourism
entrepreneur. Prior to performing independent t-tests throughout the chapter, the following
assumptions of the test were carried out (Coakes, et al., 2009):
1. The independent variable should be at the dichotomous nominal data and dependent
variable should be at interval or ratio level of measurement.
2. The dependent variable should be randomly sampled from the population of interest.
3. The dependent variable should be normally distributed in the population.
4. The homogeneity of variance should be equal between groups. This can be done by using
the Levene test for equality of variances.
In order to investigate the first research question (i.e. the socio-economic characteristics on
tourism entrepreneur’s motivation), independence sample t-test analyses were carried out to
investigate hypothesis H1b – Gender contributes to tourism entrepreneur’s motivation, given
the assumption of homogeneity of variances was judged to have been violated (F-value =
7.91, p-value = 0.00) with p is less than the critical value of 0.05. Hence, the results indicate
178
there is no significance difference between male and female tourism entrepreneur on their
motivation to enter tourism. Based on the t-test results (t-value = 0.74, p-value = 0.46), with
p is more than the critical value of 0.05, it indicate the t statistics is not significant. Therefore,
the study accepts the null hypothesis and concludes gender has no impact on tourism
entrepreneur’s motivation. Based on the correlation analysis results, a significant positive
correlation was found between motivation and gender, rs = 0.32, p-value = 0.00, which is less
than critical value of 0.05 (see Appendix 5.9). Further discussion on this result is provided in
section 6.6.
Table 5.6: T-test Results of Hypothesis H1b Relating Gender and Tourism
Entrepreneur’s Motivation
Characteristics Mean sd
Levene’s Test for Equality of Variances
t-test for Equality of Means Results
H1b F Sig. t Sig.
(2-tailed) Motivation Male 3.97 0.51
7.91 0.00 0.74 0.46 Not
supported Female 3.92 0.70 Source:Data derived from survey
5.3.3 Level of Education
The level of education is an important factor in the behaviour of tourism entrepreneurs, as it
equips the entrepreneur with the skills and mindset to remain flexible and open to market
forces and opportunities. Entrepreneurs with low education may negatively affect the
business capability as they lack critical thinking and reasoning skills required in business
decision-making.
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The level of education among Malaysian tourism entrepreneurs in this study is presented in
Table 5.7. The findings show that 40 per cent of the entrepreneurs had obtained primary
education level, and 60 per cent have tertiary education. The majority of tourism
entrepreneurs in Malaysia are Diploma holders (153 respondents, 44 per cent) and followed
by Secondary School graduates with 130 respondents or 36 per cent. 49 tourism
entrepreneurs or 16 per cent have university and postgraduate degrees.
Table 5.7: Distribution of TSMEs by Education Background and Location
Location
Education backgroundPrimary school
Secondary school Diploma Degree Masters Phd
Freq %a Freq %a Freq %a Freq %a Freq %a Freq %a
Pahang 3 0.8 15 4.3 41 11.8 8 2.3 2 0.6 1 0.3 Pulau Pinang
4 1.2 29 8.4 30 8.6 4 1.1 2 0.6 0 0.0
Kedah 6 1.8 34 9.8 22 6.3 8 2.3 0 0.0 0 0.0 Kuala Lumpur
0 0 32 9.3 28 8.1 6 1.7 3 0.8 3 0.8
Sabah 0 0 20 5.7 32 9.2 8 2.4 3 0.8 1 0.3 TOTAL 13 4.6 130 36.0 153 44.0 34 9.8 10 2.8 5 1.4
Note: a % refers the education backgrounds express as a percentage of the total number of TSME
Source: Derived from survey data
In terms of locations distributions, all tourism entrepreneurs in Sabah have completed
secondary school, while entrepreneurs in other locations completed at least their primary
education except for one tourism entrepreneur in Kedah, who had only completed primary
school. Further analysis reveals that those with tertiary educations have undertaken tourism
education prior to setting up tourism business, with 68 per cent doing so. This indicates that
tourism entrepreneurs with higher levels of education are more prepared to be in the business
180
by equipping themselves with tourism knowledge compared to those with lower levels of
education.
Independence tests were conducted to find out whether location and education level of
tourism entrepreneurs had a relationship to explain the distribution above. The results from
the Person Chi-Square test showed the calculated value of χ² (DF = 8, N = 346) = 24.10 and a
p-value of 0.002 which is less than the critical value of 0.05 (see Appendix 5.10). The study
therefore rejects the null hypothesis and concludes that there is a significant relationship
between location and level of educations had by Malaysian tourism entrepreneurs at the 5 per
cent significance level.
In order to investigate the impact of socio-economic characteristics (education level factor on
tourism entrepreneur’s motivation), ANOVA test were carried out to test hypothesis H1c –
Education level contributes to tourism entrepreneur’s motivation. Based on the Levene’s
test, the homogeneity assumption has been violated which indicated the population variances
of education level for each group are approximately unequal (F-value = 3.67, p-value = 0.02)
which indicates there is no differences across the level of education background had by
tourism entrepreneurs. Further tests on ANOVA and Tukey HSD indicates H1c is
statistically not significant (F-value = 0.71, p-value = 0.49, which is more than the critical
value of 0.05) and Tukey HSD’s results show no differences in means exist among the
education level. Thus, it is concluded that the study accept the null hypothesis and concludes
that educational level of tourism entrepreneurs had no influence on their motivation to enter
tourism businesses. Based on the correlation analysis results, a negative correlation was
found between motivation and education level, rs = 0.74, p-value = 0.17, which is more than
181
critical value of 0.05 (see Appendix 5.11). Further discussion of these results is provided in
Section 6.6.
Table 5.8: ANOVA Results of Hypothesis H1c Relating Education Level and Tourism
Entrepreneur’s Motivation
Characteristics Education Level Mean sd
Levene’s Test for Equality of Variances
ANOVA’s Test Results H1c
F Sig. F Sig. Motivation Primary 3.87 0.74
3.67 0.02 0.71 0.49 Not supported
Secondary 4.00 0.48 Tertiary 3.96 0.60 Source: Data derived from survey
5.3.4 Ethnic Group
Ethnic group is an important role to understand the motivation of an entrepreneur. as ethnic
groups are defined by different underlying value systems specific to a group or society and
motivate individuals to behave in certain ways (Hofstede & McCraem, 2004). Thus, this may
influence and contribute to tourism entrepreneurial behaviour toward management practices.
Table 5.9: Tourism Entrepreneurs by Location and Ethnic Group
Location Total TSMEs Ethnic group
Malay Chinese Indian Others Freq. %a Freq. %a Freq. %a Freq. %a Freq. %a
Pahang 70 20.3 54 15.7 9 2.6 5 1.5 2 1.1 Pulau Pinang
69 19.9 27 7.9 27 7.8 14 4.0 1 0.2
Kedah 71 20.5 20 5.7 35 10.1 15 4.4 1 0.2 Kuala Lumpur
72 20.8 32 9.3 33 9.5 7 2.0 0 0.0
Sabah 64 18.5 21 6.0 29 8.4 10 2.8 4 1.1 TOTAL 346 100.0 154 44.5 133 38.4 51 14.7 8 2.3
Note: a % refers the ethnic group express as a percentage of the total number of TSME
Source:Data derived from survey
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In Table 5.9, the majority of TSMEs’ owner-managers are Malay (154 respondents, 45 per
cent) followed by Chinese (133 respondents, 38 per cent). There is low involvement from
both Indians (51 respondents, 15 per cent) and other ethnic groups, which consist of Kadazan
- Dusun, Siamese and Burmese (8 respondents, 2 per cent). The majority of Malays in the
tourism business can be related to the objective of the Malaysia Plans to reduce economic
disparity among ethnic groups and encourage and provide incentives to Bumiputeras to
participate in business in any industry, including tourism.
Meanwhile, half of Chinese owner-managers are located in Kedah and Kuala Lumpur.
Historically, the Chinese are dominant in trade and business and they form the majority of
the entrepreneurs in Kedah, a state is highly populated with Malays and Indians(Department
of Statistics, 2012c). Meanwhile, findings for Kuala Lumpur are as predicted as the Chinese
form the second largest community. Despite being the only Chinese majority state in
Malaysia, Pulau Pinang shows a low number of tourism entrepreneurs. This can be explained
by the fact that the majority of Chinese in the state prefer to venture into manufacturing
activities rather than tourism businesses. 78 per cent of SMEs in Pulau Pinang are in the
manufacturing industry, while only 12 per cent belong to the tourism industry (Small and
Medium Enterprise Corporation Malaysia, 2011).
Based on the Pearson Chi-Square test, the calculated value of χ² (DF = 12, N = 346) = 53.26
and the p-value = 0.000 which is less than the critical value of 0.05 (see Appendix 5.12).
Thus, statistically it is proven that there is a significant relationship between location and
183
ethnicity of tourism entrepreneurs in Malaysia. Therefore, the study rejects the null
hypothesis at the 5 per cent significance level.
In order to investigate the impact of ethnic group on tourism entrepreneur’s motivation,
ANOVA were carried out to test the relationship. Table 5.10 depicts the ANOVA results on
hypothesis H1d –Ethnic group contributes to tourism entrepreneur’s motivation. Based on
the Levene’s test, the homogeneity assumption has been violated which indicated the
population variances of ethnic group are approximately unequal (F-value = 3.36, p-value =
0.01, which is less than the critical value of 0.05). Further tests on ANOVA and Tukey’s
HSD shows the results are not significant (F-value = 0.24, p-value = 0.86, which is above the
critical value of 0.05) and there is no significance differences across the ethnic group. It is
concluded that this study accept the null hypothesis of H1d , indicating that the ethnic group
of tourism entrepreneurs has no influence on their motivation to enter tourism businesses.
Based on the correlation analysis results, a significant positive correlation was found between
motivation and ethnic group, rs = 0.12, p-value = 0.01, which is less than critical value of
0.05 (see Appendix 5.13). Further discussion of these results is provided in Section 6.6.
Table 5.10: ANOVA Results on Hypothesis H1d Relating Ethnic Group and Tourism
Entrepreneur’s Motivation
Characteristics Ethnic Group Mean sd
Levene’s Test for Equality of
Variances ANOVA’s Test Results
H1d F Sig. F Sig.
Motivation Malay 3.94 0.53
3.36 0.01 0.24 0.86 Not supported
Chinese 3.99 0.52 Indian 3.92 0.77 Others 3.93 0.52
Source: Data derived from survey
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5.3.5 Family Business Background
Family business background is important in shaping the entrepreneurial behaviour as it acts
as the stimulator of motivations and helps an individual to acquire business knowledge and
skills from their families. These all help increase the entrepreneurial activity of an individual.
Figure 5.3 depicts the findings of tourism entrepreneurs in Malaysia in terms of family
business background. Most tourism entrepreneurs (257 respondents, 74.3 per cent) in this
survey indicated that they have not been raised in a family business environment and only a
quarter (89 respondents, 25.7 per cent) has a family business background. Despite the strong
family-run business culture of the ethnic Chinese, only 25 tourism entrepreneurs (29 per
cent) were born in a business family compared to 44 respondents (51 per cent) of Malay
tourism entrepreneurs who have family business background.
Figure 5.3: Tourism Entreprenuers by Location and Family Business Background
Note: % refers the family business background express as a percentage of the total number
of TSME
Source:Data derived from survey
7.5%
12.7%
4.6%
15.3%
1.4%
19.1%
6.6%
14.2%
5.5%
13.0%
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
With family business background Without family business background
Pahang Pulau Pinang Kedah Kuala Lumpur Sabah
185
From the respondents with non-family business background, 176 respondents (68 per cent)
are the founders of the firms indicating that most tourism entrepreneurs in Malaysia are risk
takers and they do not rely on their family to start a business. Another 76 respondents (29.5
per cent) have purchased all or part of the TSMEs, while 5 respondents (1.95 per cent) are
leasing the business. With regard to location, Kedah has the highest number of self-
developed entrepreneurs with no family business background while Pahang has the most
tourism entrepreneurs who have been exposed to business environment in their family.
Based on the Pearson Chi-Square test, it showed there was no relationship between location
and family business background of tourism entrepreneurs. The calculated value of χ² (DF =
4, N = 5346) = 5.66 and a p-value = 0.224 which is more than the critical value of 0.05 (see
Appendix 5.14).
In order to address the first research question, the impact of socio-economic characteristics
and tourism entrepreneur’s motivation, independence sample t-tests were carried out in
determining the relationship and testing hypothesis H1e –Family business background
contributes to tourism entrepreneur’s motivation, the Levene’s test has been not been
violated. This indicates the population variances of family business background’s group are
approximately equal (F-value = 3.00, p-value = 0.08) with p value is more than the critical
value of 0.05. Table 5.11 indicates the mean for tourism entrepreneurs with family business
background (M = 3.89, SD = 0.68) is significantly higher from that who do not have family
business background (M = 3.98, SD = 0.52). The t-test results however indicated that
Hypothesis H1e is not supported, t–value = 1.24, p-value = 0.21 with p-value is above the
critical value of 0.0. Hence, the study accepts the null hypothesis and concludes family
186
business background does not motivate entrepreneurs. Based on the correlation analysis
results, a significant positive correlation was found between motivation and family business
background, rs = 0.10, p-value = 0.04, which is less than critical value of 0.05 (see Appendix
5.15). Further discussion of the results is provided in Section 6.6.
Table 5.11: T-test Results of Hypothesis H1e Relating Family Business Background and
Tourism Entrepreneur’s Motivation
Characteristics Family Business
Background Mean sd
Levene’s Test for Equality of Variances
t-test for Equality of Means Results
H1e F Sig. t Sig.
(2-tailed) Motivation Yes 3.89 0.68
3.00 0.08 1.24 0.21 Not
supported No 3.98 0.52 Source: Data derived from survey
5.3.6 Working Experience
Previous working experience is one of the important factors to influence the behaviour of an
entrepreneur. Having previous work experience can influence the way an entrepreneur
handles the business operation particularly during start-ups. Prior working experience brings
in a business knowledge base, market information and business networks.
In this study, respondents were asked if they had any previous working experience prior to
setting up the business, and if yes, the duration of their working experience. Table 5.12
presents the findings. The majority (302 respondents, 87.3 per cent) have worked elsewhere
prior to setting up their tourism businesses, while the rest (44 respondents, 12.7 per cent)
have no prior working experience.
187
Table 5.12: Tourism Entrepreneurs by Location and Working Experience
Location Total TSMEs Without Experience With Experience
Freq. %a Freq. %a Freq. %a
Pahang 70 20.3 0 0.0 70 100.0 Pulau Pinang 69 19.9 6 1.7 63 91.3 Kedah 71 20.5 6 1.7 65 91.5 Kuala Lumpur 72 20.8 9 2.6 63 87.5 Sabah 64 18.5 23 6.6 41 64.0
Total 346 100.0 44 12.7 302 87.3 Note: a% refers the working experience express as a percentage of the
total number of TSME Source: Data derived from survey
In further analysis, Table 5.13 shows that out of the 302 respondents who have prior working
experience, close to half (49.7 per cent) obtained them in the tourism industry. Most of the
tourism entrepreneurs have working experience in Sales and Marketing (96 respondents, 32.6
per cent), followed by Banking (90 respondents, 29 per cent), General management (85
respondents, 28.1 per cent), Planning (30 respondents, 10 per cent) and Accounting with only
1 respondent (0.3 per cent).
In terms of location, more tourism entrepreneurs from Pahang have working experience (70
respondents, 20.2 per cent) compared to those in other locations, while Sabah shows the
lowest number of entrepreneurs with working experience prior to setting up their tourism
business. Further analysis was conducted to test for independence to find out whether there
was a relationship between TSME location and working experience had by tourism
entrepreneurs.
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Table 5.13: Tourism Entrepreneurs by Location and Working Experience
Location With
Experience Planning Sales
& Marketing
General Manage-
ment
Banking &
Financing
Accounting &
Auditing Freq. %a Freq %a Freq %a Freq %a Freq %a Freq %a
Pahang 70 20.3 5 1.7 14 4.6 17 5.6 34 11.3 0 0.0 Pulau Pinang 63 19.9 4 1.3 34 11.4 16 5.3 9 2.9 0 0.0
Kedah 65 20.5 4 1.3 24 7.9 23 7.6 14 4.6 0 0.0
Kuala Lumpur 63 20.8 6 1.9 12 3.9 22 7.3 23 7.6 0 0.0
Sabah 41 18.5 5 1.7 12 3.9 7 2.3 16 5.3 1 0.3 Total 302 100.0 24 7.9 96 31.7 85 28.1 96 31.7 1 0.3 Note: a % refers the working experience by department express as a percentage of the total
number of TSME Source:Data derived from survey
The results from the Chi-Square test showed the calculated value of χ² (DF = 4, N = 346) =
43.46 and a p-value of 0.000 which is less than the critical value of 0.05 (see Appendix 5.16).
The study therefore rejects the null hypothesis and concludes that there is a significant
relationship between the locations and previous working experience of tourism entrepreneurs
in Malaysia.
Additional questions were also asked to respondents. The largest group of them obtained
their working experience in the private sector (119 respondents, 39.4 per cent), followed by
self-employment (108 respondents, 35.8 per cent), and the public sector (75 respondents,
24.9 per cent). Many of the tourism entrepreneurs had various types of occupations and
experience prior to setting up tourism businesses due to the ease of entry to this industry
(Ateljevic & Doorne, 2000; Szivas, 2001).
189
In determining whether working experience contributed to tourism entrepreneur’s
motivation, a independence sample t-test were carried out to test Hypothesis H1f –Working
experience contribute to tourism entrepreneur’s motivation. Table 5.14 indicates t-test
findings and found that no significant correlation between entrepreneurs’ previous working
experience (t-value = 1.16, p-value = 0.24, which is above than the critical value of 0.05)
with the tourism entrepreneur’s motivation. Table 5.14 shows the t-test results and revealed
Hypothesis H1f is not supported. Hence, this study accepts the null hypothesis and concludes
that working experience does not motivate entrepreneurs. Based on the correlation analysis
results, a significant positive correlation was found between motivation and working
experience, rs = 0.11, p-value = 0.04, which is less than critical value of 0.05 (see Appendix
5.17). Further discussion of these results is provided in Section 6.6.
Table 5.14: T-test Results of Hypothesis H1f Relating Working Experience and
Tourism Entrepreneur’s Motivation
Characteristics Working Experience Mean sd
Levene’s Test for Equality of Variances
t-test for Equality of Means Results
H1f F Sig. t df Sig.
(2-tailed) Motivation Yes 3.86 0.61
1.07 0.30 1.16 344 0.24 Not
supported No 3.97 0.56 Source: Data derived from survey
5.3.7 Motivation to Start a Business
Motivation to start a business can be based either on ‘pull’ or ‘push’ factors. Table 5.15 ranks
tourism entrepreneurs’ motivation to start a business according to mean. Tourism
entrepreneurs’ personal need for growth is the top motivation for setting up the business
(Mean = 4.14), while the lowest motivation for setting up the business is because they either
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could not find work or they lost their jobs (Mean = 3.25). The findings reinforce previous
empirical findings suggesting that most entrepreneurs were motivated primarily by pull
factors rather than push factors (Kirkwood, 2009; Shane, et al., 2003; Wang, Walker, &
Redmond, 2006)
Table 5.15: Tourism Entrepreneurs' Motivation to Start a Business
Motivational Factors Mean rank s.d Rank
1. To provide personal needs for growth 4.14 0.784 1 2. Opportunity to use own knowledge and experience 4.01 0.779 2 3. To utilise business opportunity in tourism industry 3.90 0.821 3 4. To keep my family together 3.86 0.910 4 5. To utilise the Government support availability 3.70 0.891 5 6. Influenced by family and/or friends 3.61 1.029 6 7. To gain prestige by operating a business 3.53 0.997 7 8. Could not find work/loss a job 3.25 1.221 8
Source: Data derived from survey
A one-way analysis of variance (ANOVA) was conducted between location and tourism
entrepreneur’s motivation to start a tourism business. Levene’s test showed the calculated
value of F (DF = 4, N = 341) = 2.24, and a p-value of 0.064 which is more than the critical
value of 0.05, and so the assumption of homogeneity of variances was judged to have not
been violated. A significant effect was found for location of TSMEs, F (DF = 4, N = 345) =
5.83, and a p-value of 0.000 which is less than the critical value of 0.05. Thus, the study
rejects the null hypothesis. The post-hoc comparison (Tukey HSD) results was found to
display Kedah, Pahang, Pulau Pinang and Kuala Lumpur have significantly different mean of
motivation to start a tourism business compared to tourism entrepreneurs in Sabah (see
Appendix 5.18).
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5.4 Management Practices of TSMEs in Malaysia
Previous studies have investigated the effect of various management practices on small
performance. For this study, in order to fit suitability with the Malaysian context, four
management practices (use of business plan, business alliances, the Internet, and government
assistance) were examined and described in this section.
5.4.1 Business Planning
As found in Table 5.16, the majority of tourism entrepreneurs in this study do plan their
business strategy. About 72.3 per cent of respondents do exercise formal business planning,
while only 27.3 per cent do not organise their business operations. Of those with a plan,
about half were formal (written) and half were informal (i.e unwritten/’in my head’).
Additional questions were also asked on their business plan.
Table 5.16: TSMEs and Business Planning
Location Total TSMEs Business Planning Formal Informal
Freq. %a Freq. %a Freq. %a
Pahang 70 20.3 52 15.0 18 5.2 Pulau Pinang 69 19.9 58 16.8 11 3.2 Kedah 71 20.5 56 16.2 15 4.3 Kuala Lumpur 72 20.8 49 14.2 23 6.6 Sabah 64 18.5 35 10.1 29 8.4 Total 346 100.0 250 72.3 96 27.7
Note: a% refers the number of business planning express as a percentage of the total number of TSME
Source: Data derived from survey
About 44.5 per cent stated that their plan is on an annual-term plan, 31.8 per cent had a
quarterly-term plan, and another 22.5 per cent operated on a monthly basis. Of those with
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plans, 90 per cent reviewed their plans half-yearly while another 10 per cent did not. These
findings provide similar empirical research findings by Wang et. al (2006) where most SMEs
in Western Australia exercise informal business plans.
In terms of TSME business planning distributions across locations, generally all TSMEs in
Malaysia organised their business operations. Pulau Pinang indicated the highest meanwhile
Sabah ranked the highest TSMEs not practising formal planning in business operations.
Further analysis was conducted to test for independence to find out whether TSMEs location
and types of business planning had a relationship to explain the distribution above. The
results from the Pearson Chi-Square test showed the calculated value of χ² (DF = 4, N = 346)
= 16.76 and a p-value of 0.002 which was less than the critical value of 0.05 (see Appendix
5.19). The study therefore rejects the null hypothesis and concludes that there is a significant
relationship between location and type of business planning practiced by tourism
entrepreneurs at the 5 per cent significance level.
5.4.2 Business Alliance
A little over half (53.5 per cent) of the surveyed TSMEs have informal business alliances,
while the rest (46.5 per cent) do not have any business alliances. Pahang records the highest
proportion of TSMEs that have business alliances (13 per cent) while Sabah hosts TSMEs
(11.3 per cent) that have no business alliance activity compared to other locations in
Malaysia.
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Table 5.17: Business Alliance Activity of TSMEs in Malaysia
Source:Data derived from survey
Table 5.17 ranks the means and standard deviations in terms of the motives for engaging in
business alliances. TSMEs are mostly forming business alliances for information sharing
(Mean = 3.72) and knowledge sharing (Mean = 3.70). This type of alliance formation is
categorised as organisational learning and the main concern for the alliance formation is to
improve individual and collective organisational actions via improved knowledge and
understanding (Peter & Gunasekaran, 1999). TSMEs indicated that the least motivational
factor to form business alliances are subcontracting, human resource support (Mean=3.43)
and equipment sharing (Mean = 3.40). According to Zakarija (2003), in Croatia, the lack of
reliability and trust towards other firms are a hindrance to business alliances formation and
can also explain why human resource support and equipment sharing are the least-alliance
activity for TSMEs in the Malaysian context. Because the assumption of homogeneity has
been violated, F-value = 4.92, and a p-value of 0.00. Further tests on ANOVA and Tukey’s
HSD shows the results are significant (F-value = 8.34, p-value = 0.00, which is less than the
critical value of 0.05) and there is a significance difference across the location of TSMEs (see
Appendix 5.20).
Alliance activity Mean s.d Rank 1. Information sharing 3.72 1.05 1 2. Knowledge sharing 3.70 1.07 2 3. Economies of scale 3.66 1.09 3 4. Entering new market 3.63 1.04 4 5. Subcontracting 3.50 1.17 5 6. Human resource support 3.43 1.13 6 7. Equipment sharing 3.40 1.07 7
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5.4.3 Adoption of Internet
In tourism industry, the Internet is regarded as an important tool for better management and
business operations and also provides many opportunities and advantages through the
electronic marketplace to attract customers. Some empirical studies have found that the use
of the Internet among SMEs increases the business and industry performance (Karanasios &
Burgess, 2006; Kristiansen, et al., 2003; Salman & Hasim, 2011; Tan, et al., 2009) .
Table 5.18: Distribution of TSMEs Based on Period of Starting to Use the Internet
Note: a% refers the number of use the internet express as a percentage of the total number of TSME
Source: Data derived from survey
Table 5.18 depicts the period in which TSMEs first adopted and used the Internet. The
majority adopted use of the Internet between 2001-2005 (162 firms, 47 per cent). This was
during the 8th Malaysia Plan (2001-2005) when the main agenda of the plan was to
encourage SMEs in all industries to create online presence and emphasize ICT competencies.
The Government allocated RM1 billion to increase SMEs’ business capacity through e-
commerce activity (Economic Planning Unit, 2008) as the Internet provides TSMEs the
avenues to offer virtual tourism products and build relationships with potential customers.
Nevertheless, a few forward-looking TSMEs started using the Internet as early as 1996 to
Locations Total
TSMEs Year
1996-2000 2001-2005 After 2006 Freq. %a Freq. %a Freq. %a Freq. %a
Pahang 70 20.3 12 3.5 30 8.7 36 10.4 Pulau Pinang 69 19.9 14 4.0 34 9.8 21 6.1 Kedah 71 20.5 6 1.7 42 12.1 23 6.6 Kuala Lumpur
72 20.8 13 3.8 32 9.2 27 7.8
Sabah 64 18.5 5 1.4 24 6.9 28 8.1 Total 346 100.0 49 14.1 162 46.8 135 39.0
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2000 (49 firms, 16 per cent). Many of the owners of these TSMEs are Diploma holders (27
respondents or 55 percent) and know the advantages of using the Internet in the business.
The results from the Pearson Chi-Square test showed the calculated value of χ² (DF = 8, N =
346) = 18.51 and a p-value of 0.0018 which less than the critical value of 0.05 (see Appendix
5.21). The study therefore rejects the null hypothesis and concludes that there is a significant
relationship between the location and year of Internet adoption by TSMEs at the 5 per cent
significance level. This can be attributed to the uneven distribution of ICT use between
TSMEs in Peninsular Malaysia and those in Sabah before 2005. TSMEs in Pahang, Pulau
Pinang, Kedah and Kuala Lumpur have higher Internet adoption than those in Sabah. Sabah’s
geographical condition and its isolated and mainly rural population may explain this trend.
The development of ICT infrastructure in Sabah has been challenging and in turn caused
delayed Internet adoption in the state. Nevertheless, from 1996 to 2006, TSMEs from Sabah
gradually adopted the Internet. This followed the continued and expanded efforts of the Ninth
Malaysia Plan (2006-2010) where various funds were made available for ICT development in
SMEs (Economic Planning Unit, 2006).
Table 5.19 presents the use of the Internet by TSMEs in this study. The three most common
uses of the Internet by the TSMEs are: to convey information to customers (Mean=3.78), use
emails (Mean=3.70), and search for information (Mean=3.61). Other uses of the Internet
include receiving orders from customers (Mean=3.57), obtain information from suppliers
(Mean=3.48) and to a lesser extent as an advertisement to place for job vacancies
(Mean=3.01). According to Moodley and Morries (2004), Palmer (2000) and Lal (2005),
those are the most common e-commerce practices adopted by businesses in both developed
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and developing countries. In the tourism industry, the Internet is regarded as an important
means and the most cost-efficient tool to communicate with customers, particularly with
international tourists (Buhalis & Law, 2008; Salwani, et al., 2009a; Sebora, et al., 2009). The
assumption of homogeneity has been violated with F-value = 4.92, and p-value = 0.00 is less
than critical value of 0.05. Further tests on ANOVA and Tukey’s HSD shows the results are
not significant (F-value = 2.14, p-value = 0.75, which is above the critical value of 0.05) and
the results indicates there is no significance differences across the ethnic group (see
Appendix 5.22).
Table 5.19: The Internet Adoption Among TSMEs in Malaysia
The uses of Internet Mean Rank s.d Rank
Information to customer 3.7791 1.08422 1 Email 3.7093 1.17671 2 Looking for information 3.6163 1.10834 3 Receiving orders from customer 3.5727 1.12510 4 Information from supplier 3.4855 1.11957 5 Internal communication 3.4390 1.09959 6 Sending purchase order 3.4012 1.17882 7 Service and market research 3.3924 1.21940 8 Offering online payment options 3.3779 1.23938 9 Contact with governmental agencies 3.3430 1.12941 10 Placing job vacancies 3.0174 1.31364 11
Source:Data derived from survey
5.4.4 Awarenes and Use of Government Assistance Programmes
Government assistance is regarded as one of SMEs’ important external resources. Both
financial and non-financial assistance from the government can have some influence on
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SMEs’ performance, particularly during the start-up stage. Furthermore, some studies have
identified that lack of government support is one of the major reasons for SMEs’ failure.
Table 5.20: Level of Awareness and Use on the Government Assistance Programmes
Assistance provided Mean s.d RankFrequency %
Yes No Financial assistance: Tourism Special Fund 3.04 1.19 1 122(35..3) 224(64.7) MARA Business Financing Scheme 3.01 1.20 2 118(34.1) 228(65.9) Tourism Infrastructure Fund 2.93 1.18 3 109(31.5) 237(68.5) Graduate Entrepreneur Fund 2.87 1.18 4 106(30.6) 240(69.4) TEKUN Financing Scheme 2.84 1.24 5 111(32.1) 235(67.9) Bumiputera Entrepreneur Project Fund
2.82 1.18 6
108(31.2) 238(68.8)
Soft Loan for SMEs 2.81 1.19 7 112(32.4) 234(67.6) Fund for Small and Medium Industries 2
2.80 1.18 8
99(28.6) 247(71.4)
Special Fund for Tourism 2 2.79 1.14 9 105(30.3) 241(69.7) Initiative Financing Scheme 2.77 1.17 10 101(29.2) 245(70.8) New Entrepreneur Fund 2 2.76 1.18 11 103(29.8) 243(70.2) Rural Economy Financing Scheme 2.73 1.18 12 102(29.5) 244(70.5) Soft Loan for ICT Adoption 2.72 1.19 13 105(30.3) 241(69.7) Special assistance scheme for women entrepreneurs
2.69 1.18 14
100(28.9) 246(71.1)
Youth Business Scheme 2.68 1.17 15 104(30.1) 242(69.9) Tanmiah Scheme 2.65 1.17 16 108(31.2) 238(68.8) Non-financial assistance: Tourist Guide Course 3.09 1.22 1 139(40.2) 207(59.8) Marketing and promotion 2.99 1.20 2 152(43.9) 194(56.1) Strengthening skills of workforce 2.97 1.17 3 143(41.3) 203(58.7) Entrepreneurial development programmes
2.91 1.16 4
135(39) 210(60.7)
Budget Hotel Efficiency Improvement Course
2.87 1.25 5
133(38.4) 213(61.6)
Advisory Services 2.87 1.21 6 138(39.9) 208(60.1) Tourist Boat Operating Course 2.80 1.24 7 121(35) 225(65) Think Tourism 2.75 1.19 8 131(37.9) 215(62.1) Mesra Malaysia Course 2.74 1.21 9 126(36.4) 220(63.6)
Source: Data derived from survey
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Table 5.20 lists the financial and non-financial assistance provided by the Malaysian
Government to the TSMEs in the country. Most of the respondent SMEs have a low level of
awareness of both financial and non-financial assistance programmes, where most of the
programmes means ranged between 2.74 and 3.04. In term of the level of use of financial
assistance and the non-financial courses and training, the majority of TSMEs do not use both
assistance types provided by the government.
Further analysis shows that nearly half (157 respondent, 47 per cent) of the TSMEs in this
study are not members of any tourism associations in Malaysia, while a little over half (174
respondents, 53 per cent) are registered with a tourism association. This indicates that many
TSME owner–managers have a lack of information related to the government’s available
financial and non-financial programmes. A similar study by Salleh and Ndubisi (2006) has
identified that one of the challenges of Malaysian SMEs is poor access to financial assistance
due to differing criteria for eligibility for receiving funds and the bureaucracy that exists
within the government agencies.
5.5 Concluding Remarks
This chapter has described Malaysian TSMEs’ and tourism entrepreneurs’ characteristics. A
number of interesting findings are reported on the similarities and differences of TSMEs
across the five selected locations for this study. With regard to the characteristics of tourism
entrepreneurs, the entrepreneurs in Pahang are dominant in terms of education level, gender,
working experience and family business background compared to other TSMEs’ locations in
this study. Findings show a few differences across the TSMEs in Peninsular Malaysia
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(Pahang, Pulau Pinang, Kedah and Kuala Lumpur) and East Malaysia (Sabah) in terms of
their management practices. The majority of TSMEs in Malaysia practiced formal business
planning in their business operations. Regarding Internet adoption, TSMEs in Pulau Pinang,
Kedah and Kuala Lumpur started to adopt in between 2001 – 2005 while Pahang and Sabah
adopted Internet use after 2006. This provides new insights on Malaysian TSMEs’ profiles.
Besides that, this chapter has tested Hypothesis 1 which investigates the impact of socio-
economic characteristics on tourism entrepreneurs’ motivation. The F-test from ANOVA
analysis indicates that only age group has different impact on tourism entrepreneurs’
motivation while Spearman’s rank-order correlation analysis confirms a positive association
between socio-economic characteristics and motivation, except for education level. In
Chapter 6, a more detailed discussion of the hypotheses’ results is presented in Section 6.6.
Chapter 6 also focuses on testing the relationship between the variables in which all variables
were analysed simultaneously in the Structural Equation Modelling (SEM) using the AMOS
program. This step will finalize the framework model of the study based on statistical fit and
also whether the framework makes theoretical or substantive sense. These steps will be
covered in Chapter 6 and 7.
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CHAPTER SIX
AN EMPIRICAL ANALYSIS OF CAUSAL RELATIONSHIPS: TSMEs’ MANAGEMENT PRACTICES AND PERFORMANCE
6.1 Introduction
The results of Chapter 5 discussed the characteristics of TSMEs, socio-economic
characteristics of tourism entrepreneurs, and management practices of tourism entrepreneurs
in Malaysia. A review of the literature in Chapter 2 revealed that from the First Malaysian
Plan (1966-1970) until the Tenth Malaysia Plan (2011-2015), there has always been a five-
year economic plan implemented for tourism. This includes TSME policies aimed at
improving the Malaysian tourism industry, at the same time minimising or reducing obstacles
that TSMEs face. An understanding of the interrelationships between TSMEs’ management
practices and firm performance in Malaysia is important in informing the formulation and
implementation of policies that will promote TSME performance and the tourism industry in
Malaysia. In order to empirically analyse these causal relationships, this chapter has two
parts. The first part investigates Malaysian tourism entrepreneur’s perceptions toward
management practices (business planning, business alliances, use of Internet, government
assistance). The second part investigates the relationship between TSMEs’ management
practices and performance.
This chapter is organised as follows: Section 6.2 explains the confirmatory factor analysis of
the variables in this study. Section 6.3 explores the measurement model of the framework.
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Section 6.4 discusses the structural model and hypotheses testing. Section 6.5 concludes the
chapter.
6.2 Confirmatory Factor Analysis of Tourism Entrepreneur’s Motivation and TSMEs’
Management Practices
CFA is the first step before proceeding to the model measurement model analysis and
structural equation modelling (SEM). The next section looks into the CFA results on each of
the constructs listed in the framework of this study.
6.2.1 Tourism Entrepreneurs’Motivation
Table 6.1 presents the findings of TSMEs entrepreneurs’ motivation. In general, they
perceive non-financial goals to be more important to starting a business than financial goals.
Respondents scored highly on statements that described the non-financial goals of starting a
business (such as personal satisfaction and flexible lifestyle). Although the results in this
study were restricted to TSMEs offering accommodation services and travel agency services,
tour operators, and tourism guide services, they show that business owners who are
financially motivated are in the minority and that most TSME business owners in Malaysia
are content to stay small. Tourism entrepreneurs’ preferences for non-financial goals include
lifestyle factors, particularly the flexibility of self-employment, the freedom to arrange
professional and personal activities, the involvement of their children in the business and the
opportunities to connect with the local community. These lifestyle choices are the owner-
managers’ perceived advantages that are not available in larger organizations (Walker &
Brown, 2004)
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Table 6.1: Mean and Standard Deviation Values of Entrepreneur's Motivation’s Items
Item Entrepreneurial Motivation’s Items Mean s.d
Mot1 Personal satisfaction is more important than making lots of money 4.03 0.62
Mot2 Having a flexible lifestyle is more important than making lots of money 3.51 0.94
Mot3 As a small business I have responsibility to the wider community 3.79 0.94
Mot4 When I first started the business I was more money oriented than today 3.86 0.75
Mot5 I think of my business as something that my children can be involved in 3.84 0.87
Mot6 I would rather keep the business modest and under control than have it grows too big 3.98 0.74
Mot7 I feel I am running a successful business 3.66 0.99 Source:Data derived from survey
CFA was carried out to determine whether all 7 constructs of entrepreneur motivation (see
Table 6.1) meet the statistical fit or could be grouped into smaller constructs. The item Mot7
(I feel I am running a successful business)has standardised loading less than 0.5 and hence
has been dropped from the analysis. The model is re-specified and the MI table produced by
SEM indicated that items Mot6 and Mot4 are highly correlated, with MI value of 16.85,
above the threshold value of 15. Based on these findings, two correlated errors were made to
be ‘free parameter estimate’ and the measurement model for tourism entrepreneurs’
behaviour were re-specified. Using the bootstrapping procedure, the data fit the measurement
model well with χ²( DF = 8, N = 346) = 24.65, Bollen-Stine p = 0.17, ChiSq/df = 3.08, TLI =
0.96, CFI = 0.98, RMSEA = 0.07 (see Figure 6.1).
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Figure 6.1: Standardised Parameters Estimated in One-Factor Congeneric Model for
Tourism Entrepreneurs’ Motivation Items
Source: Data derived from survey
6.2.2 Business Planning
Table 6.2 illustrates tourism entrepreneurs’ perception of the importance of business planning
on business performance. Tourism entrepreneurs in Malaysia perceive that business planning
is important for business performance. Five items measure the constructs for business
planning. Almost all of the items in the business planning construct show mean values near
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to 4.0 with the lowest mean of 3.82 (Plan2). Business planning conducted either formally or
informally by tourism entrepreneurs, is generally perceived to have a positive influence on
TSMEs’ performance. Business planning has always been associated with an objective to
expand the business (Ackelsberg & Arlow, 1985; Baker, Addams, & Davis, 1993; Delmar &
Shane, 2003). In the context of the lifestyle of tourism entrepreneurs, the objectives of
planning their business are related to achievement and a substitute source of income
(Matthews, Schenkel, & Hechavarria, 2009). Factors such as passing the business on to their
children, providing employment to the local community and protecting nature are among the
reasons for business planning among lifestyle entrepreneurs in this study.
Table 6.2: Mean and Standard Deviation Values of Business Planning’s Items
Item Business Planning’s Items Mean s.d
Plan1 Business plan is an effective way of setting business
goal and targets 4.04 0.71
Plan2 Business plan is a useful business strategy to track the
business development 3.82 0.90
Plan3 Business plan improves business performance in term
of sales revenue and/or profits 3.94 0.86
Plan4 Business plan is an effective way to organise the
business operations 4.03 0.76
Plan5 Business plan simplifies your role as a manager 3.92 0.82
Source: Data derived from survey
Figure 6.2 shows the statistical fit following CFA. The MI value for the covariance between
items Plan4 and Plan5 is 72.33, more than the acceptance level of 15. This indicates that the
two items are redundant. Based on this, both items were set to be ‘free parameter estimate’
and the model was re-specified. The findings show that the five measures of business
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planning did not fit the model well, with χ²(df = 4, n = 346) = 10.57, p = 0.03. A post-hoc test
was conducted showing an adjusted chi-square as a Bollen-Stine p value of 0.49. Other fit
indices are ChiSq/df = 2.64, TLI = 0.98, CFI = 0.98, RMSEA = 0.06 (see Figure 6.2).
Figure 6.2: Standardised Parameters Estimated in One-Factor Congeneric of Business
Planning’s Items
Source:Data derived from survey
6.2.3 Business Alliance
The business alliance construct was measured by six items. From the findings illustrated in
Table 6.3, all six items for business alliance show mean values greater than 3.73, indicating
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that respondents are generally satisfied and agree with items representing the business
alliance construct. This indicates that TSMEs in Malaysia perceive business alliances to
bring positive performance. This implies an integrated, collaborative nature of the tourism
industry (Bullock, 1998). Business alliance scan be in the form of a joint venture or
franchising (Contractor & Kundu, 1998), marketing alliances (Glisson, Gunningham, Harris,
& Di Lorenzo-Aiss, 1996) or shared facilities (Bennett, 1997) to deliver and provide the
quality of service demanded by tourists (Peattie & Moutinho, 2000).
Table 6.3: Mean and Standard Deviation Values of Business Alliance’s Items
Item Business Alliance’sItems Mean s.d
Allia1 An organisation can actually experience competitive
advantage through business alliance 3.90 0.86
Allia2 Business alliance activity simplifies roles as manager 3.73 0.82
Allia3
Business alliance activity improves the
organisational relationship with customers and/or
suppliers
3.98 0.78
Allia4 Business alliances among businesses is an economic
way of delivering services 3.90 0.76
Allia5 Business alliances is an effective way to gather
market- and competitor-related information 3.80 0.84
Allia6 Business alliances improve business performance in
terms of sales revenue and/or profits 4.00 0.81
Source: Data derived from survey
Based on the CFA results presented in Figure 6.3, one item, allia5 (Business alliances is an
effective way to gather market- and competitor-related information) has standardised factor
loading less than 0.5 and hence has been dropped from the analysis (Byrne, 2010). CFA was
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conducted on five items (Allia1, Allia2, Allia3, Allia4, Allia6) and findings indicate that the
model did not fit the data well, χ²(df = 9, n = 346) = 34.23, p = 0.000. A bootstrapping
procedure was performed with the adjusted chi-square as Bollen-Stine p = 0.69, indicating a
good fit. The fit indices also support the model: ChiSq/df = 1.76, TLI = 0.98, CFI = 0.99,
RMSEA = 0.04.
Figure 6.3: Standardised Parameters Estimated in One-Factor Congeneric Model for
Business Alliance’s Items
Source: Data derived from survey
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6.2.4 Adoption of Internet
Table 6.4 illustrates the means and standard deviations of five items to measure tourism
entrepreneurs’ use of the Internet. All five items show mean values above the ‘in between’
score of 3.55. This signifies that tourism entrepreneurs are aware of the importance and the
ability of the Internet to support the needs and boost performance of their businesses. This
positive perception of Internet use among Malaysian tourism entrepreneurs reflects the
continuous approaches of the Malaysian government to increase the level of Internet
penetration among SMEs in Malaysia (Junaidah, 2007; Karkoviata, 2001). SMEs have
increased their use of the Internet since the 8th Malaysia Plan (2001-2005), when the
Government allocated funding for computer systems upgrades, training programmes,
technology acquisition, consultancy fees and electronic commerce activities for SMEs. These
continuous efforts by the Government contribute to the high Internet penetration among
TSMEs in Malaysia.
Table 6.4: Mean and Standard Deviation Values of an Adoption of Internet’s Items
Item Adoption on Internet’s Items Mean s.d
Inter1 The Internet is an efficient way of communicating
with customers and/or suppliers 3.66 0.91
Inter2 An organisation can actually experience competitive
advantage through Internet technologies 3.55 0.98
Inter3 The Internet simplifies your role as a manager 3.55 0.99
Inter4 The Internet improves the organisational
relationship with customers and/or suppliers 3.64 0.92
Inter5 The Internet is an economical way of answering
customer and/ or suppliers’ queries 3.55 0.99
Source: Data derived from survey
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CFA indicates that the data did not fit the model well, with values of Chisq/df and RMSEA
above the acceptance level. Examination done on MI shows that the MI value between items
Inter4 and Inter5 of 30.51, more than the threshold value of 15. As shown in Figure 6.4, the
decision to solve the problem by setting them to be ‘free parameter estimate’ and re-specify
the model was made. Using the bootstrapping procedure, the data show a good model fit χ²
(df = 4, n = 346) = 15.52, Bollen-Stine p = 0.20. Other fit indices also support the model:
ChiSq/df = 3.88, TLI = 0.96, CFI = 0.98, RMSEA = 0.09.
Figure 6.4: Standardised Parameters Estimated in One-Factor Congeneric Models for
the Adoption on Internet’s Items
Source: Data derived from survey
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6.2.5 Government Assistance Programmes
Table 6.5 presents the mean and standard deviation values of the four items for the
government assistance construct. Most tourism entrepreneurs in the study do not perceive
Government support highly, as the mean values of all four items (Govt1, Govt2, Govt 3, and
Govt 4) are at most 3.47, lower than the ‘in between’ score. This indicates that tourism
entrepreneurs the Government’s financial and non-financial assistance have not been
supporting the needs and assistance of the TSMEs. The findings correspond to the descriptive
findings of the low level of awareness and use of financial and non-financial programmes
provided by the Malaysian government (see Section 5.4.4). The results has triggered
frustration of tourism entrepreneurs in Malaysia, as government support is crucial for the
success of small businesses (Rose, Kumar, & Yen, 2006).
Table 6.5: Mean and Standard Deviation Values of Government Assistance
Programmes’ Items
Item Government Assistance Programmes’ Items Mean s.d
Govt1
The programmes designed by the government have
improved the performance of TSMEs and its
competitiveness
3.47 0.95
Govt2 There is adequate financial assistance in Malaysia to enable
those interested in venturing into tourism business activities 3.28 1.10
Govt3
There is adequate non-financial assistance in Malaysia to
enable those interested in venturing into tourism business
activities
3.34 1.11
Govt4
The government has put in place adequate tourism
incentives to support the growth and development of
TSMEs
3.35 1.01
Source:Data derived from survey
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CFA analysis in Figure 6.5 was examined on the four measures of government assistance
programmes and found that the model fit the data well, with χ²(df = 2, n = 346) = 0.149, p =
0.928. Other fit indices were: ChiSq/df = 0.07, TLI = 1.0, CFI = 1.00, RMSEA = 0.00.
Figure 6.5: Standardised Parameters Estimated in One-Factor Congeneric Model for
Government Assistance Programmes’ Items
Source:Data derived from survey
6.2.6 Business Performance
Table 6.6 illustrates the mean and standard deviation values for the items for TSMEs’
performance. Based on the items in the business performance construct, most of the TSMEs
had 21 to 30 employees in 2008 and 2009. With regard to their perception toward their
business performance, most regard their business as stable, feel that their business is in a
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good position compared to other competitors, and are somewhat satisfied with their business
performance.
Table 6.6: Mean and Standard Deviation Values of Business Performance’s Items
Item TSMEs’ Performances’ Items Mean s.d
Per1 Please estimate the number of full-time employees in 2008 3.66 0.98 Per2 Please estimate the number of full-time employees in 2009 3.64 0.85 Per3 I consider my business succeeded compared to competitor 3.76 0.86 Per4 I am satisfied with my business success 3.65 0.97
Source:Data derived from survey
Figure 6.6 depicts the CFA results of business performance constructs and shows that the
data fit the model well with χ² (df =2, n =346) = 0.66, p = 0.71. Other fit indices
were:ChiSq/df = 0.33, TLI = 1.0, CFI = 1.00, RMSEA = 0.00
Figure 6.6: Standardised Parameters estimated in One-Factor Congeneric Model for
TSMEs’Performance
Source: Data derived from survey
213
6.3 Full Measurement Model
This section shows the full measurement model of tourism entrepreneurial behaviour and
TSMEs’ management practices and performance. The items in each construct that were not
omitted were subjected to a comprehensive confirmatory factor analysis. Following the
earlier procedure adopted on the measurement model, the same fit indices used to assess
model fit were used in the full measurement model. In this stage, all six constructs (tourism
entrepreneur’s motivation, business planning, business alliance, use of the Internet,
government assistance and business performance) were simultaneously subjected to
confirmatory factor analysis.
Table 6.7: Confirmatory Factor Analysis of Full Measurement Model
Factor and item FL t- value
CronbachAlpha
Entrepreneur motivation Mot1 Personal satisfaction is more important than making
lots of money 0.81 13.90 0.84
Mot2 Having a flexible lifestyle is more important than making lots of money
0.76 14.81
Mot3 As a small business I have responsibility to the wider community
0.72 15.87
Mot4 When I first started the business I was more money oriented than today
0.79 a
Mot5 I think of my business as something that my children can be involved in
0.74 14.21
Mot6 I would rather keep the business modest and under control than have it grow too big
0.55 11.41
Business planning Plan1 Business plan is an effective way of setting business
goals and targets 0.89 12.21 0.80
Plan2 Business plan is a useful business strategy to track the business development 0.91 12.39
Plan3 Business plan improves business performance in terms of sales revenue and/or profits 0.79 11.36
Plan4 Business plan is an effective way to organise the business operations 0.60 a
Plan5 Business plan simplifies your role as a manager 0.60 12.78
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Business alliance Allia1 An organisation can actually experience competitive
advantage through business alliance 0.81 12.59 0.81
Allia2 Business alliance activity simplifies roles as manager 0.64 10.40
Allia3 Business alliance activity improves the organisational relationship with customers and/or suppliers
0.69 a
Allia4 Business alliances among businesses is an economic way of delivering services 0.61 10.06
Allia6 Business alliances improve business performance in terms of sales revenue and/or profits 0.57 9.44
Adoption on Internet Inter1 The Internet is an efficient way of communicating
with customers and/or suppliers 0.84 12.39 0.83
Inter2 An organisation can actually experience competitive advantage through Internet technologies 0.90 12.77
Inter3 The Internet simplifies your role as a manager 0.78 11.70 Inter4 The Internet improves the organisational
relationship with customers and/or suppliers 0.59 11.41
Inter5 The Internet is an economical way of answering customer and/ or suppliers’ queries 0.63 a
Government assistance programmes Govt1 The programmes designed by the government have
improved the performance of TSMEs and its competitiveness
0.67 12.26 0.84
Govt2 There is adequate financial assistance in Malaysia to enable those interested in venturing into tourism business activities
0.81 a
Govt3 There is adequate non-financial assistance in Malaysia to enable those interested in venturing into tourism business activities
0.80 14.62
Govt4 The government has put in place adequate tourism incentives to support the growth and development of TSMEs
0.73 13.53
Business performance Per1 Please estimate the number of full-time employees
in 2008 0.81 12.99 0.83
Per2 Please estimate the number of full-time employees in 2009
0.80 12.88
Per3 I consider my business succeeded compared to competitor
0.70 11.55
Per4 I am satisfied with my business success 0.71 a
Note: N = 346; a = loadings are fixed to unity to scale the latent variable, FL = Factor loading
Source: Data derived from survey
215
Results of the analysis reveal that the data did not fit the model well with χ²(df =359, n
=346) = 653.84, p = 0.00. Therefore, a bootstrapping procedure was performed, resulting in
an adjusted chi-square p value or Bollen-Stine p of 0.08, indicating the data fit the model
well. Other fit indices were: ChiSq/df = 1.82, TLI = 0.93, CFI = 0.94, RMSEA = 0.49.The
confirmatory factor analysis for the comprehensive model is shown in Table 6.7. Figure 6.7
depicts the full measurement models with the fit indices’ result.
216
Figure 6.7: Full Measurement Model for Identifying Key Success Factors Affecting
TSMEs’ Performance in Malaysia
Source: Data derived from survey
217
6.4 Validity and Reliability of Constructs
This section discusses the results of validity and reliability analyses of the measurement
model. This is to ensure the constructs of the study measure the intended concept and that the
scale is free from any statistical or non-random error (Hair, et al., 2010; Sekaran, 2003). The
content validity has been discussed in Chapter 4 where the proposed scale items used in this
study (questionnaires) have been reviewed by a panel of academics from the Newcastle
Business School, University of Newcastle through the University's Human Research Ethics
Committee (HREC), and later pre-tested on a sample.
6.4.1 Construct Validity
Construct validity is established through the determination of both convergent validity and
discriminant validity. The following section discusses the results of both types of construct
validity in this study.
6.4.1.1 Convergent Validity
The analysis presented in Table 6.7 show that the items to measure the latent variables are
observed to be statistically convergent. This is done by examining the t-values and the
satisfactory factor loadings (SFL). Both values should exceed 1.96 and 0.50, respectively
(Dun, Seaker & Waller, 1994). Subsequent analysis using these measures revealed:
1. Satisfactory factor loadings, with each item’s factor loading ranging between 0.53
and 0.80 (see Table 6.7), exceeding the 0.50 benchmark, and
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2. Satisfactory t-values, with each item’s t-values ranging between 8.79 and 14.49
(see Table 6.7), exceeding the 1.96 benchmark.
6.4.1.2 Discriminant Validity
Table 6.8 indicates that the square root AVE value for all constructs—entrepreneur’s
behaviour, business planning, business alliance, use of the Internet, government assistance
and TSME performance—are higher than the standardised correlation values, signifying
discriminant validity of the constructs.
Table 6.8: Discriminant Validity Test
Construct Mot Plan Allia Inter Govt Per Entrepreneur’s motivation (Mot) 0.72
Business planning (Plan) 0.60 0.76
Business alliance (Allia) 0.53 0.60 0.66
Adoption onInternet (Inter) 0.14 0.17 0.42 0.75
Government assistance programmes
(Govt) 0.05 0.49 0.17 0.02 0.74
Business performance (Per) 0.37 0.39 0.43 0.18 0.18 0.75
Note: The bold numbers in diagonal row are the square root of AVE
Source:Data derived from survey
6.4.2 Reliability
Reliability test measures the extent to which a group of different items are consistent with
one another and whether each measure is free from measurement error (Leech, Barrett&
Morgan, 2005). It is assumed that each item comprises a true score measuring an underlying
construct. Based on the recommendation from Garver and Mentzer (1999), this study
219
calculated three estimates of reliability for each construct – the Cronbach’s alpha, the
composite reliability and the average variance extracted (AVE). Subsequent analysis using
these measures reveal that:
1. Satisfactory Cornbach’s alphas, with all constructs’ alphas exceeding 0.70 (see
Table 6.9);
2. Satisfactory composite reliability with all values exceeding the 0.70 benchmark
(see Table 6.9); and
3. Satisfactory AVE values, with all values exceeding the 0.5 benchmark (see Table
6.9).
Table 6.9: Reliability Analyses
Constructs Cronbach’s Alpha
Composite Reliability
Average Variance Extracted (AVE)
Entrepreneur’s motivation 0.84 0.87 0.53
Business planning 0.80 0.87 0.59
Business alliance 0.81 0.80 0.44
Adoption on Internet 0.83 0.86 0.57
Government assistance programmes 0.84 0.84 0.56
Business performance 0.83 0.84 0.57
Source:Data derived from survey
6.5 Structural Model and Hypotheses’ Testing
The CFA and full measurement have tested the validity of the constructs for TSMEs’
management practices (business planning, business alliance, use of the Internet, government
assistance). The findings have highlighted the differences between the observed factor
structure and the overall structure suggested by the literature. As a result of the statistical
considerations, the model has changed in order to achieve the model fit. In this section,
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structural equation modelling (SEM) analysis was used to examine the causal relationship
between tourism entrepreneurs’ motivation and key success factors (business planning,
business alliance, Internet adoption, and government assistance) with TSME business
performance. The advantages of using SEM include the ability to incorporate latent and
measured constructs into the analysis, the assessment of multiple relationships, and its
primary use to study consumer behaviour, psychology and management (Cunningham, 2008;
Hair, et al., 2003).
Figure 6.8 presents the structural model for Malaysian TSMEs’ key success factors and
business performance. The first saturated model did not fit the model well with χ² (df =365, n
= 346) =746.18, p = 0.00. None of the standardised residuals exceed a magnitude of 2;
hence, there is no indication of serious misfit between the data and the model. Therefore, a
bootstrapping procedure was performed, and the data fit the model well, with Bollen-Stine p
= .24. Other fit indices were: ChiSq/df = 2.04, TLI = 0.91, CFI = 0.92, RMSEA = 0.55.
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Figure 6.8: AMOS Model Specification for Identifying Key Success Factors of TSMEs in Malaysia
Source: Data derived from survey
222
Figure 6.9: Results of Path Analysis of Identifying Key Success Factors of TSMEs in
Malaysia
Source: Derived by candidate from empirical hypothesis results
The hypotheses for this study were tested by determining the statistical significance of the
path coefficients. To estimate the causal relation, the actual size of each parameter was
assessed in terms of the standardised ß coefficients and ρ-values. In summary, the findings
provide support for the structural model. Hypotheses H6, H8 and H9 are not supported,
while hypotheses H2, H3, H4, H5, H7and H10 are supported. These relationships are
H1 H2
H3
H4
H5
H7
H8
H9
H10
Entrepreneur’s motivation
Adoption on Internet
Business alliance
Business planning
Government assistance
programmes
TSMEs performance
Socio-economic
characteristics
H6
Notes: Significants
paths Non-significants paths
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illustrated in Figure 6.9 and summarised in Table 6.10. Further discussion of these results is
found in section 6.6.
Table 6.10: Results of Hypotheses Testing
Predictor
variables
Criterion
variables ß
t-
value
p-
value
Hypo-
theses Results
Entrepreneur’s
motivation Business planning 0.05 11.05 *** H2 Supported
Entrepreneur’s
motivation Business alliance 0.05 8.45 *** H3 Supported
Entrepreneur’s
motivation
TSMEs’
performance 0.09 2.55 0.01 H4 Supported
Entrepreneur’s
motivation
Adoption on
Internet 0.05 2.95 0.00 H5 Supported
Entrepreneur’s
motivation
Government
assistance
programmes
0.07 0.92 0.35 H6 Not
Supported
Business
planning
TSMEs’
performance 0.07 2.70 0.00 H7 Supported
Business alliance TSMEs’
performance 0.08 1.29 0.19 H8
Not
Supported
Adoption on
Internet
TSMEs’
performance 0.06 1.03 0.30 H9
Not
Supported
Government
assistance
programmes
TSMEs’
performance 0.04 2.69 0.00 H10 Supported
Notes: * p<.05; ** p<.01, *** p<.001
Source:Data derived from survey
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6.6 Discussion of the Empirical Results
This section discusses the results based on the hypotheses tested and the analyses
conducted in this study. Table 6.11 summarises the research questions and key findings of
this research.
Table 6.11: Summary of Research Questions and Key Findings
Research questions Hypotheses Results 1. What is the impact of
socio-economic characteristics affects tourism entrepreneur’s motivation?
H1a Age contributes to tourism entrepreneur’s motivation.
Supported
H1b Gender contributes to tourism entrepreneur’s motivation.
Not supported
H1c Education level contributes to tourism entrepreneur’s behaviour.
Not supported
H1d Ethnic group contributes to tourism entrepreneur’s motivation.
Not supported
H1e Family business background contributes to tourism entrepreneur’s motivation.
Not supported
H1f Working experience contributes to tourism entrepreneur’s motivation.
Not supported
2. How does tourism entrepreneur’s motivation affect the management practices of Malaysian TSMEs?
H2 Tourism entrepreneur’s motivation will have a positive effect on business planning
Supported
H3 Tourism entrepreneur’s motivation will have a positive effect on business alliances
Supported
H4 Tourism entrepreneur’s motivation will have a positive effect to TSME performance
Supported
H5 Tourism entrepreneur’s motivation will have a positive effect to Internet adoption
Supported
H6 Tourism entrepreneur’s motivation will have a positive effect to utilisation on government assistance programmes
Not Supported
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3. What is the impact of management practices to Malaysian TSMEs performance?
H7 Business planning will have a positive effect on performance of TSMEs. Supported
H8 Business alliances will have a positive effect on performance of TSMEs.
Not supported
H9 The adoption of the internet will have a positive effect on performance of TSMEs.
Not Supported
4. What is the impact of government assistance programmes on Malaysian TSMEs performance?
H10 Government assistance programmes will have a positive effect on performance of TSMEs. Supported
Source: Data derived from survey
6.6.1 Relationship between Socio-economic Factors towards Tourism Entrepreneur’s
Motivation
H1a: Age contributes to tourism entrepreneur’s motivation.
A positive relationship between the age of tourism entrepreneurs and their motivation is
suggested as H1a. Results reveal that entrepreneurs who are in the middle age bracket (age
31 and above) have positive attitudes to manage the tourism business and are generally
more capable of starting and running a business. Furthermore, entrepreneurs in this age
group are financially stable and have an interest to start their own business. The findings
therefore support this hypothesis and other studies that link mature entrepreneurs and
positive entrepreneur motivation (Popa & Marghitas, 2011; Levesque & Minniti, 2003,
Valdez, 2009). This suggested that, in order to encourage entrepreneurial behaviour when
potential business owners reach the age of 31 or above, exposure to the business
environment could be done during secondary education and tertiary education. This is
when they are still younger than 30 years old.
H1b: Gender contributes to tourism entrepreneur’s motivation.
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A positive association between gender and tourism entrepreneur’s motivation is suggested
as H1b. The findings did not support the hypothesis and other studies where males are more
likely to have a higher level of motivation than females (Matthews & Moser, 1996; Delmar
& Davidson, 2000; Jaafar et al; 2011). This is likely due to the tourism business
environment which is not too complex for women entrepreneur to handle the business
operations compare to other industry which requires extensive business skills in managing
the business operation. This findings also can be supported based on the pull factor motives
by tourism entrepreneurs in Malaysia which indicates both gender have no differences on
their motivation to start tourism business-for personal needs for growth, use own
knowledge and experience and to utilise business opportunity in tourism industry (see
Section 5.3.7)
H1c: Educationl evel contributes to tourism entrepreneur’s motivation.
A positive relationship between education level and tourism entrepreneur motivation is
suggested as H1c where by a higher education level will have an impact on tourism
entrepreneur motivation. The findings did not support this hypothesis and previous related
studies stating that a higher level of education develops analytical ability and the
computational skills of the entrepreneur as well as communication skills (Rauch & Frese,
2000; Collinson & Quinn, 2002; Clercq & Arenius, 2006). However, according to Lerner
and Haber (2001) and Valdez (2009), having higher education is unimportant because it
does not contribute to business success in the tourism industry.
H1d: Ethnic group contributes to tourism entrepreneurs’ motivation.
227
A positive association between ethnic group and tourism entrepreneur motivation is
suggested by H1d, whereby differences in family and household characteristics (including
human and financial capital across ethnic groups) will have an impact on tourism
entrepreneur motivation. However, the findings did not support this hypothesis or related
studies that signify the role of ethnicity on entrepreneurial motivation in the tourism
industry (Basu, 2004; Hitchcock, 2000).
Regardless of the differences in cultural values, religions and attitudes between Malays,
Chinese, Indians and other minority groups, Malaysian tourism entrepreneurs have similar
entrepreneurial motivation. This is reflected in the motivation factors to enter the tourism
industry, mainly to satisfy personal and family goals.
H1e: Family business background contributes to tourism entrepreneur’s motivation.
A positive association between family business background and tourism entrepreneur’s
motivation is suggested as H1e whereby entrepreneurs who have family business
background are more likely to exhibit positive tourism entrepreneur motivation. The results
did not support the hypothesis and suggest that early exposure to a family business have no
influences on the entrepreneur motivation. This findings did not support other studies that
signify the influence of family entrepreneurial background on entrepreneurial motivation of
an individual (Altinay, et al., 2012; Basu, 2004).
Furthermore, as tourism industry has a relatively low entry barriers, only required few
skills in business operations compare to other industry and few restrictions or regulations
imposed in setting up the business (Quinn, Larmour and McQuillan, 1992) has reflects on
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the low number of tourism entrepreneurs who have family business background in this
study. This may justifies that family business background is not a strong indicator of
tourism entrepreneur’s motivation to enter tourism businesses instead due to less risk
involved and less complexity in business operation compare to other industry which
requires early exposure on the business environment and operational tasks.
H1f: Working experience contributes to tourism entrepreneur’s motivation.
A positive relationship between previous working experience and tourism entrepreneur
motivation is hypothesised as H1f. However, the finding is inconsistent with other studies
on the importance of prior working experience in shaping the motivation of lifestyle
tourism entrepreneurs. This can be justified by the ‘pull’ motivation factors of tourism
entrepreneurs’ involvement in the tourism industry in this study, as reported in Chapter 5.
Previous related studies found that tourism entrepreneurs often have strong desires to start a
tourism business to provide employment to family members, to fulfil their interests or
hobby, and (because of the flexible lifestyle) personal satisfaction, and companionship with
guests (Getz & Carlsen, 2000; Kirkwood, 2009; C. Wang, et al., 2006). These pull factors
confirm that previous working experience has no influence on the motivation of tourism
entrepreneurs. Also, previous working experience does not contribute to tourism
entrepreneur motivation because the industry has low barriers to entry, few restrictions and
regulations, and requires few skills to start a tourism business.
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6.6.2 Relationship between Tourism Entrepreneurs’ Motivation and Business
Planning
H2: Tourism entrepreneurs’ motivation will have a positive effect on business planning.
In testing this hypothesis, we investigate the extent to which tourism entrepreneurs’
motivation influences business planning. The null hypothesis is that tourism entrepreneur
motivation has no impact on business planning against the alternative that it has a positive
impact on business planning. The result reported in Table 6.10 shows a t-value of 11.05 and
a p-value of less than 1%. Hence, we reject the null hypothesis in favour of the alternative
and conclude that tourism entrepreneur motivation has a positive impact on business
planning in Malaysia. In this study, based on the statistical results reported in Section 5.3.7
in Chapter 5, it was found that most Malaysian tourism entrepreneurs were motivated
primarily by pull factors rather than push factors. The expression of a strong positive
internal desire to start a business venture (such as ‘to keep personal needs for growth’,
‘opportunity to use own knowledge and experience’, ‘to utilise business opportunity in
tourism industry’) received higher mean rankings compared to push-factor motivations.
Push-factor motivations such as ‘could not find work/loss a job’ ranked with the lowest
means by Malaysian tourism entrepreneurs in this study. This explains why the regression
weight of tourism entrepreneur motivation was found to be significant on the perception of
the importance of business planning. Thus, hypothesis H2 has a direct effect on tourism
entrepreneurs’ motivation for business planning at the 5 per cent significance level. The
results establish that the relationship is supported, and suggest that positive internal desire
(which motivates entrepreneurs to venture into the tourism business) has influenced their
230
perception on the importance of exercising a business plan in their operations, either by
formal or informal business planning.
6.6.3 Relationship between Tourism Entrepreneurs’ Motivation and Business
Alliances
H3: Tourism entrepreneurs’ motivation will have a positive effect on business alliances.
A positive relationship between tourism entrepreneur motivation and business alliances is
hypothesised as H3 and the null hypothesis is that tourism entrepreneur motivation has no
impact on forming business alliances. The result reported in Table 6.10 shows a t-value of
8.45 and a p-value of less than 1 per cent. Hence, we reject the null hypothesis and
conclude that tourism entrepreneur motivation has a positive impact on business alliance in
Malaysia. The regression weight of tourism entrepreneur motivation was found to be
significant on the perception of the importance of business alliances. Thus, hypothesis H3
has a direct effect on tourism entrepreneur motivation to form business alliances at the 5
per cent significance level. Results indicate that most Malaysian tourism entrepreneurs
agree that business alliances are essential in operating tourism businesses. The opportunity
to utilise their past experience and knowledge, as well as other related pull motivation
factors have influenced Malaysia tourism entrepreneurs to become involved in business
alliance activity, due to the complexity of the tourism industry. It comprises more than a
few actors such as tourism operators, tourism support infrastructure, and public and private
organisations and associations (Russell & Faulkner, 2004), all for the purpose of providing
good tourism services to tourists. Thus, Malaysian tourism entrepreneurs perceive
231
networking within the industry in order to deliver quality tourism products and services as
essential to the tourism industry.
6.6.4 Relationship between Tourism Entrepreneurs’ Motivation and TSMEs’
Performance
H4: Tourism entrepreneurs’ motivation will have a positive effect on TSMEs’ performance.
A positive relationship between tourism entrepreneur motivation and TSME performance is
suggested as H4. The findings in the structural model indicated a significant relationship
between motivation of tourism entrepreneurs and TSME performance, and reject the null
hypothesis that tourism entrepreneur motivation has no impact on TSME performance.
Table 6.10 shows the results of hypothesis H4 indicates that the probability of getting a t-
value of 2.55 and a p-value of less than 1 per cent. This finding is consistent with other
studies which demonstrate that pull motivation factors lead to successful business
performance (Bellu & Sherman, 1995; Jennings & Beaver, 1997; Kolvereid & Bullvag,
1996; Miner, Smith, & Bracker, 1994).
The psychological perspective better explains why people take a broader view of
motivation than an economic one does. Bandura (1997) pointed that ‘people’s level of
motivation, affective status and actions are based more on what they believe than on what
he or she will act and how the available knowledge and skills will be utilised’ (p.14).
Consequently, people behave according to beliefs about their capabilities, rather than on
real facts based on their competence and capabilities. This perspective appears highly
232
appropriate in the TSMEs’ context, because this study provides evidence that tourism
entrepreneurs are motivated by factors other than simply the promise of financial reward.
6.6.5 Relationship between Tourism Entrepreneurs’ Motivation and Internet
Adoption
H5: Tourism entrepreneurs’ motivation will have a positive effect on Internet adoption.
H5 hypothesised a positive relationship between tourism entrepreneurs’ ‘push’ motivation
and use of the Internet. Table 6.10 shows the results of hypothesis H5, with a t-value of
2.95 and a p-value of less than 1 per cent. Hence, the regression weight of tourism
entrepreneurs’ motivation was found to be significant on the perception of the importance
of the Internet. Thus, the null hypothesis that tourism entrepreneur motivation has no
impact on Internet adoption is rejected, and it can be concluded that tourism entrepreneur
motivation has a positive impact on Internet adoption in Malaysia.
This indicates that Malaysian tourism entrepreneurs aware on the importance and
advantages of the Internet to business performance. This finding is supported by a study
conducted in Malaysia where most SMEs in Malaysia realize that ICT is critical to the
productivity and performance of their companies (Lim, 2006). In the context of the tourism
industry, the Internet is very influential in providing information and promoting tourism
products to potential tourists around the world.
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6.6.6 Relationship between Tourism Entrepreneurs’ Motivation and Government
Assistance Programmes
H6: Tourism entrepreneurs’ motivation will have a positive effect on the importance of
government assistance programmes.
In testing this hypothesis, this study investigated the extent to which tourism entrepreneur
motivation influenced the importance of government assistance programmes. The null
hypothesis was that tourism entrepreneur motivation had no impact on government
assistance programmes, against the alternative hypothesis that it had a positive impact on
the importance of government assistance programmes in assisting TSMEs. Table 6.10
shows the results of hypothesis H6, with a t-value of 0.92 and a p-value of less than 1 per
cent. Hence, the study accepted the null hypothesis and concluded that tourism
entrepreneurs’ motivation had no direct effect on government assistance programmes.
This indicates that tourism entrepreneurs have a low perception of the available support
programmes provided by the Malaysian government. This can be supported by the
corresponding results on the tourism entrepreneurs’ low level of awareness on the financial
and non-financial tourism assistance programmes, with more than 47 percent of tourism
entrepreneurs being unaware of such assistance. Likewise, this also reflects Malaysian
entrepreneurs’ frustration of the Government’s support and assistance, and they are also
sceptical about obtaining funds and participating in the programs provided by the
Malaysian government (Rose, et al., 2006).
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6.6.7 Relationship between Business Planning and TSMEs Performance
H7: Business planning will have a positive effect on TSMEs’ performance.
H7 hypothesised a positive relationship between business planning and TSME
performance, and the null hypothesis is that business planning has no impact on TSMEs
performance. Findings from the structural model confirm those of other studies, which
indicated that business planning guaranteed business success and reduced the risk of failure
(Baker, et al., 1993; Delmar & Shane, 2003; Peel & Bridge, 1998; Vasudevan &
Venkatraman, 1987). Table 6.10 shows the results of hypothesis H7, indicating a t-value of
2.70 and a p-value of less than 1 per cent. Hence, the null hypothesis is rejected and it can
be concluded that business planning was found to be significant on TSMEs’ business
performance.
This indicates that whether or not business planning is documented, it is crucial for
business growth, as it can assist entrepreneurs to analyse information, evaluate required
tasks, identify risks, formulate a strategy, and project financial developments. This activity
will help owner-managers to make better decisions more quickly, and to manage resource
supply and demand in ways that minimise time-consuming bottlenecks. This will more
efficiently turn abstract goals into concrete operational activities (Delmar & Shane, 2003).
6.6.8 Relationship between Business Alliance and TSMEs’ Performance
H8: Business alliances will have a positive effect on TSMEs’ performance.
In testing this hypothesis, this study investigated the extent to which business alliances
influence TSMEs performance. The null hypothesis is that business alliances have no
235
impact on TSMEs performance against the alternative that it has a positive relationship on
TSMEs performance. Table 6.10 shows the results of hypothesis H8, indicating a t-value of
1.29 and p-value of less than 1 per cent. Hence, we accept the null hypothesis and reject
H8, concluding that business alliance activity has no impact on TSMEs’ performance. The
findings in this study did not support this hypothesis or other studies that showed business
alliance activity would lead to positive outcomes on SME performance (Curran, Jarvis,
Blackburn, & Black, 1993; Hoffmann & Schlosser, 2001; Mehdi & Edward, 2011; Miles,
Preece, & Baetz, 1999; Pansiri, 2008).
6.6.9 Relationship between Internet Adoption and TSMEs’ Performance
H9: The adoption of the internet will have a positive effect on TSMEs’ performance.
Internet technology can bring great advantages to business performance; thus, this study
investigated the extent to which Internet adoption influences TSMEs performance. The null
hypothesis is that Internet adoption has no impact on TSMEs performance.H9 hypothesised
a positive relationship between Internet use and TSME performance. Findings indicate that
the Internet is not a crucial factor for TSMEs’ performance in Malaysia. The results are
contradictory with empirical studies indicating that the use of the Internet contributes
positively to SMEs’ performance (Feindt, et al., 2002; Karanasios & Burgess, 2006). Table
6.10 shows the results of hypothesis H9 indicates a t-value of 1.03 and a p-value of less
than 1 per cent. Hence, the null hypothesis is accepted, concluding that Internet adoption
was found not to be significant on TSMEs’ business performance.
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However, these results are best explained due to the low level of technological adoption
and information and communications technology penetration by the Malaysian SME
industry (Salleh & Ndubisi, 2006). Furthermore, The Federation of Malaysian
Manufacturers (FMM) identified that one of the deemed factors for Malaysian IT use issue
is the lack of awareness among SMEs of the importance of IT. Even though Internet
services have been present in Malaysia since 1995, there was only a 21 percent application
of the Internet among TSMEs in the 2000s (Salwani, Marthandan, Norzaidi, & Chong,
2009b). Only 30 percent of Malaysian SMEs have their own websites, although these sites
are not regularly updated (Ramayah, Osman , Azizah, & Malliga, 2009).
6.6.10 Relationship between Government Assistance Programmes and TSMEs’
Performance
H10: The government assistance programmes will have a positive effect on TSMEs’
performance.
H10 posited a positive relationship between the Malaysian Government’s assistance and
TSMEs’ performance, and the null hypothesis is that government assistance programmes
have no impact on TSMEs performance. Results are congruent with other studies, which
suggest government’s crucial role in developing small businesses’ performance (Jenkins &
Henry, 1982; Ron Chuen Yeh, et al., 2008). Table 6.10 shows the results of hypothesis H10
indicates the t-value is 2.69 and the p-value is less than 1 per cent. Hence, the study rejects
the null hypothesis and concludes that government assistance programmes were found to be
significant on TSMEs’ business performance.
237
Governments can affect the nature and pace of SMEs. Macroeconomic policies, legislation,
regulations, direct support policies and programmes that are designed to assist TSMEs
bring great impact to their performance. This suggests that many TSMEs are set up, survive
and grow with the government’s involvement.
6.7 Concluding Remarks
To summarize, this chapter evaluated the hypothesised relationship between dependent
variables and independent variables in one structural model. The SEM techniques were
used to evaluate the goodness-of-fit of the association of the socio-economic characteristics
factors affecting the motivation of tourism entrepreneurs in Malaysia. Key factors affecting
Malaysian TSMEs’ performance (and on which this study has focused) include: tourism
entrepreneurs’ motivation, business planning, business alliance, Internet adoption and
government assistance programmes. The model fit indices suggested a general fit to the
model.
The results also indicate key factors that have a positive relationship on Malaysian TSMEs’
performance. Tourism entrepreneur’s age and gender positively influenced tourism
entrepreneur’s motivation. Business planning and government assistance programmes are
also key management practices for TSMEs in Malaysia. The next chapter of this thesis,
Chapter 7, will look into the implication of these findings to the government tourism
policy. Chapter 7 will provide some policy recommendations to improve TSMEs
performance in Malaysia.
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CHAPTER SEVEN
SUMMARY, CONCLUSIONS AND IMPLICATIONS OF THE FINDINGS
7.1 Summary
The Malaysian government has acknowledged the development of tourism industry since
the establishment of the Tourist Development Corporation in the 1970s. Then, it was taken
more seriously with the establishment of Ministry of Culture, Arts and Tourism (MOCAT)
in the 1980s. By the 2000s, tourism now had its own ministry to monitor its development.
The establishment of the Ministry of Tourism has a core objective of stimulating and
sustaining growth in the Malaysian tourism industry. A series of five-year development
plans (known as Malaysia Plans) were intended to establish development priorities and set
specific growth targets. The Malaysia Plans have explicitly espoused government
commitment toward TSMEs; however, in spite of the rigorous policies and programs
undertaken by the government, the tourism industry still faces challenges in sustaining the
life span and business growth of TSMEs, especially among tourism entrepreneurs who hold
non-economic motives in business. The purpose of this research is to undertake an
empirical study to investigate the key factors that will contribute to the longevity and
performance of TSMEs in Malaysia.
The specific objectives of the study were:
1. To critically evaluate the impact of government policy on TSMEs in Malaysia.
2. To empirically investigate the characteristics of TSMEs and management practices of
tourism entrepreneurs in Malaysia.
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3. To empirically analyse the causal relationships between TSMEs management practices
and firm performance in Malaysia.
4. To identify the key success factors of TSMEs in Malaysia.
5. To provide policy recommendations for improving TSMEs performance in Malaysia.
The present study has synthesized and integrated aspects from each of the existing
determinants of controllable internal factors of TSME performance. These include the
social and cultural orientation of tourism entrepreneurs, management practices, and
available programs provided by the Malaysian government into the conceptual framework.
The study then employed a quantitative approach using multivariate data analysis.
The study was based on personally administered questionnaires on 346 TSME owner-
managers. It identified that controllable internal factors, social-cultural factors, business
alliances, tourism, motivation, business planning, and government assistance can all be
significantly exploited as a bundle of unique resources to ensure success performance of
TSMEs in Malaysia. These findings contribute to a better understanding of tourism
entrepreneurs’ motivation and management practices in a developing country context.
TSME performance in Malaysia has been the focus of the Malaysian government due to
key roles in facilitating tourism industry performance. Beginning with the 2nd Malaysia
Plan (1971-1975) until the current 10th Malaysia Plan (2011-2015), the Malaysian
government has been pursuing a policy and implementation framework for TSMEs. Since
then, the establishment of TSMEs across Malaysia has increased to support the growth and
development of the tourism industry. This has been attributed to the low entry barriers in
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the tourism industry and the exhibition of a low degree of entrepreneurial behaviour. As a
result, TSMEs do not reach their full potential and fail to grow during the start-up phase or
the first three years of business (Hall., 1995).
Identifying key success factors of TSMEs can assist to avoid pitfalls during start-up, and
ensure survival in the industry. Several factors (both internal to the firm, and the external
environment) influence SME performance in all industries, including tourism. The
literature has proven that the individual entrepreneur cannot control the external
environment (Hunger & Wheelen, 2003). Thus, entrepreneurs must be aware of and take
actions via the internal factors, which include utilising available resources for small-sized
businesses and operation management to positively impact their businesses.
The remaining discussion in this chapter is organized around five objectives stated earlier.
The emphasis will be on drawing conclusions and outlining managerial and public policy
implications. The study’s contribution to the tourism entrepreneur literature and TSME
business management, its limitations, and its suggestions for future research are scrutinized
in the last two sections.
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7.2 Conclusions
7.2.1 An Evaluation on the Impact of Government Policy on TSMEs in Malaysia
Within the context of this study, Malaysian government tourism policy has adopted both
short-term and long-term strategic planning on the performance of tourism industry. The
Malaysian government has developed such policies on its five-year economic plans, known
as Malaysia Plans, and has developed tourism-specific policies as guiding principles for the
planning, developing and marketing of tourism.
Essentially, the tourism policy planning on each of the five-year economic plans covered
tourism development in relation to the other economic sectors, manufacturing and
agriculture and services. On each of the five-year economic plans starting with the 1st
Malaysian Plan (1966-1970) until the 10th Malaysian Plan (2011-2015), Malaysia
government has organised its policy planning to increase tourist arrivals and receipts. It can
be seen that the policy planning of tourism development in Malaysia is comprehensive and
top-down in nature. As tourism is a federal matter, MOTOUR has provided the overall
framework and direction for tourism product development in Malaysia. However, since the
implementation of the tourism policy also involved three tiers of government organisation
(federal government, state government and local authorities), this has led to complexity,
redundancy in job implementation, and conflict in terms of which government organisation
is responsible for organising tourism activities at the state and national levels.
The tourism-specific policies—the National Tourism Policy (1992), the National Eco-
tourism Plan (1996), the Rural Tourism Master Plan (2001) and the Second National
242
Tourism Policy (2003-2010)—served as the guiding principles for the planning,
development and marketing of tourism. From then on, the major Unique Selling
Propositions (USPs) identified in the First National Tourism Policy were built—namely,
nature and culture. The National Eco-tourism Plan (1996) provided a blueprint for the
development of nature based on the principles of sustainability, with a strong emphasis on
local participation. The strategies and policies contained in the Rural Tourism Master Plan
(2001) call for the commoditisation of rural resources—notably, rural ambience and the
warm rural host. Finally, the Second National Tourism Policy (2003-2010) emphasised
Malaysia’s unique multiculturalism as its major selling point.
7.2.2 An Appraisal of the Relationship Between Socio-Economic Characteristics and
Tourism Entrepreneurs’ Motivation
The main part of the objective of this study is to understand the motivation of tourism
entrepreneurs in Malaysia and to bridge the knowledge gap in the Malaysian context by
undertaking a critical assessment of tourism entrepreneurs’ motivation. While numerous
studies on entrepreneurial intentions have examined only the impact age, gender,
educational background, and work experience to examine antecedent socio-economic
factors toward tourism entrepreneurial motivation, this study has also included the
importance of ethnicity and family business background due to its suitability with the
Malaysian context, comprised of multiracial community and the tourism industry.
Subsequent analysis revealed that the construct of age proved to be significantly and
positively associated with tourism entrepreneur motivation. The interesting finding of this
243
study is that no significant relationship was found out between gender, education level,
ethnicity, family background and tourism entrepreneurs’ motivation. Even though each
ethnic group may have unique differences in family, household characteristics such as
human and financial capital have a greater impact on tourism entrepreneurial motivation
(Basu, 2004; Basu & Goswami, 1999). It was also found that educational level and work
experience have no significant impact on shaping tourism entrepreneurial motivation. This
result implies that the involvement of tourism entrepreneurs in Malaysia is due to the low
entry barrier in the tourism industry, the strong presence of the Malaysian government in
encouraging Malaysians to participate in tourism with continuous government assistance
programs and incentives to support TSMEs. By contrast, other industries may require more
knowledge of the industry, extensive work experience and a higher education background.
7.2.3 An Evaluation on the Tourism Entrepreneurs’ Perception on the Importance of
Management Practices on TSMEs’ Performance
It is important to note that management practices are essential for business success,
particularly the SMEs (Munikrishnan & Veerakumaran, 2011). In the context of this study,
the focus of management practices has been on business planning, business alliances,
Internet adoption and government assistance programmes. It is important to examine the
tourism entrepreneurs’ perception of these management practices and their impact on the
business performance. In the context of the tourism industry, the entrepreneurs’ perception
of the importance of business planning, business alliances, adoption of the Internet and
government assistance programmes will help them identify the ability to position their
business in a highly segmented marketplace or niche market.
244
Based on the results, Malaysian tourism entrepreneurs perceived that business planning,
business alliances, motivations, and Internet adoption are crucial for determining the
performance of TSMEs. This provides some startling insights, since tourism
entrepreneurship is characterized as a “non-serious” business due to the lack of motivation
to achieve profit and growth in business. However, based on the results of the SEM
analysis, it appears that the typical tourism entrepreneur does believe that management
practices are important to be executed in business operations.
However, assistance programmes provided by the Malaysia government are perceived as
not important by Malaysian tourism entrepreneurs. Based on the results, the low awareness
of the related government assistance tourism programmes has implications for level of use
or application of the tourism assistance programmes. This interesting finding needs to be
further investigated in order to identify the reasons for this pessimistic perception among
tourism entrepreneurs on the available assistance programmes provided by the Malaysian
government.
7.2.4 An Assessment on the Causal Relationships between TSMEs’ Management
Practices and Firm Performance in Malaysia
The findings of this research are expected to provide a deeper understanding of the value
positions underlying small and medium enterprise entrepreneurial activity, particularly in
the tourism industry. The study also aims to provide important information for the
Malaysian government to formulate and implement effective policies aimed at sustaining
TSME growth within the tourism industry.
245
From this research, it is eminently clear that business planning and government assistance
programmes have a positive relationship on TSMEs’ performance. Since most TSMEs in
Malaysia practice informal business planning, the Malaysian Government should develop
awareness and educate tourism entrepreneurs on the importance of having a more
structured and proper business plan. This will enhance the capacity and capability of the
existing TSMEs in Malaysia by improving on their business planning practice.
In the context of government assistance programmes, in regard to the pessimistic
perception by tourism entrepreneurs on the importance of government assistance
programmes towards firms performance, the results shows that government assistance
programmes are an influential factor in contributing to the positive performance of TSMEs.
Thus, tourism entrepreneurs of TSMEs should utilise the available assistance programmes,
which are designed to promote TSME performance of Malaysia.
Thus, if TSMEs pay attention to these resources during the start-up phase of tourism
business operation, it will increase the chances of success and survival in their business
longevity. However, Internet adoption has to be emphasised by the Malaysian government
among TSMEs for use and penetration of the technology into the business. Globally, most
countries have used the Internet to their advantage in their respective tourism industries.
Malaysian TSMEs also should take this chance, and the government must play a big role to
encourage and ensure that Internet adoption is practised among TSMEs in Malaysia.
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7.2.5 The Key Success Factors of TSMEs in Malaysia
In determining the key success factors for survival among TSMEs in Malaysia, this study
focused on internal resources of TSMEs: socio-economic characteristics and management
practices, which have a strong influence on small-business performance. This study
signified that certain characteristics of tourism entrepreneurs’ demographics and basic
management practices need to be encouraged by tourism entrepreneurs. Both factors are
statistically proven to contribute to TSMEs’ business performance during the start-up
phase.
Based on the statistical results, it is indicated that age has an impact on tourism
entrepreneurship. This study found out that tourism entrepreneurs who are 31 years or older
are highly motivated to enter the tourism business. This shows that in this age group,
tourism entrepreneurs are more likely to accept demands and obligations associated with
owner-manager responsibilities, and they see the potential to utilise the business
opportunity in tourism industry. Furthermore, this mature group is often well established in
terms of financial capability and the business environment.
Business planning, either formal or informal, shows positive results for the performance of
TSMEs. Thus, it indicates that business planning is very significant as one of the key
success factors for TSMEs. Well-planned activities and the arrangement of tourism
products or services will determine the satisfaction level among tourists. This also has a
great impact on the tourist experience in Malaysia, and it will influence Malaysia’s impact
on the global tourism industry. Therefore, business planning needs to be practiced by
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TSMEs at the early stages of business operation, in the start-up phase, business operation
must be well organised, as TSMEs deal directly with the tourist visiting Malaysia.
Government assistance is regarded as an important resource for SMEs’ success.
Conversely, lack of government support will limit the performance of SMEs. In this study,
assistance programmes provided by the Malaysian Government through various agencies
are an effective influence on the success performance of TSMEs. The various programmes
offered to the TSMEs have helped tourism entrepreneurs to further improve their business
performance. The programmes also provide support in minimizing or reducing the barriers
that TSMEs face.
7.3 Policy Implications
This section presents the implication of the findings, and in so doing, addresses the study’s
final objective of providing policy recommendations for improving TSME performance in
Malaysia. Several managerial and policy-making implications are discussed in this section.
7.3.1 Managerial Implications
In the context of managerial implications, this study provides entrepreneurs of TSMEs with
the information on the importance of management practices affecting the performance of
their business. Based on the empirical results of this study, it was found out that most
tourism entrepreneurs lack the necessary training and experience. The majority of tourism
entrepreneurs in this study have no background in the tourism industry, either in terms of
previous work experience or education background. This indicates that most tourism
248
entrepreneurs enter the industry without early preparation to understand and gain
experience prior to setting up their tourism business operations. The tourism industry is
very complex, comprised of residential activities (hotels, apartments, camp sites),
transportation (by air, sea and overland), services in the place of origin (tour operators,
travel agencies, information services), and services at the place of destination
(accommodation, foodservice, sports, leisure, culture, banking, insurance, security)
(Argandona, 2010). All of these activities overlap and influence one another. Tourism
entrepreneurs who lack preparation will face big challenges in handling the tourism
business, particularly during the early stages of operation. Furthermore, in the tourism
business, meeting tourist demand is crucial as it brings a direct impact on business
performance. This limitation needs to be addressed by tourism entrepreneurs by attending
and utilising workshops, seminars and training programmes held by MOTOUR and/or
agencies. The workshops will equip the entrepreneurs with knowledge, and exposure to
tourism industry environment and specifically the tourism business environment. This will
facilitate business operations and provide a better understanding on the complexity of the
tourism industry.
In the context of forming business alliances, there is a low level of business alliance
activity among TSMEs in Malaysia. Most tourism entrepreneurs had a positive perception
on the importance of business alliance on performance; however, the level of networking
activity is still low among TSMEs in Malaysia. The low involvement in corporate
relationships will reduce the opportunity to share resources and exchange industry
knowledge (Braun, 2012). Collaboration with other TSMEs or organisations will improve
249
networking and provide new sources of competitive advantage for companies while also
ensuring business survival. This can be done via formal or informal networking.
The low level of Internet adoption among TSMEs has a big impact on the performance of
TSMEs. Internet in the tourism industry is now absolutely crucial, due to today’s society
lifestyle. Tourists now prefer to make their own travel arrangements, search information by
browsing the webpage, and contact TSMEs operators via email to get relevant information
for making a holiday decision. The inability to utilise the advantage of the Internet will
reduce a business’s potential to attract and receive potential customers while promoting the
business to a broader global market.
Low level of awareness and use of government assistance programmes will impede
business performance, particularly during the start-up phase of business. This study found
out that most TSMEs in Malaysia did not participate in tourism programmes provided by
the government. It was indicated that most tourism entrepreneurs had no awareness of the
relevant tourism programmes provided by the government to support and nurture TSMEs’
business performance in all areas of business operations. This includes financial support
and non-financial support such as advisory services, marketing and promotion courses and
entrepreneurial development programmes. Thus, tourism entrepreneurs need to be
proactive in seeking information and support from the related ministry and agency about
the available assistance provided by the Malaysian Government.
250
7.3.2 Implications for Policy Makers
Within the context of this study, the Malaysian government needs to realise that the well-
intentioned policies originally designed to encourage mass participation of Malaysians in
business also created unintended drawbacks. The 'lifestyle' aspirations, combined with low
entry barriers to business in the tourism industry, have led to declines in successful
performance among tourism entrepreneurs. Thus, it is important for the government,
through public and private educational institutions, to provide entrepreneurial programmes.
This could take the form of mentoring or incubator support programmes, where prospective
tourism entrepreneurs could understudy or serve an apprenticeship under a successful
tourism entrepreneur. It behoves prospective tourism entrepreneurs to take steps to acquire
experience before starting a TSME. By addressing the education and entrepreneurial
experience of tourism entrepreneurs as prerequisites for successfully running TSMEs, it
will play a greater role in poverty alleviation and employment creation at the national,
regional and district levels of government.
Regardless of the education background of the tourism entrepreneurs, it was found out that
most tourism entrepreneurs in Malaysia did not have a prior educational background in
tourism before entering the tourism industry. Thus, it is recommended that MOTOUR and
the Ministry of Higher Education collaborate to develop a tourism training policy that will
build a pool of resources for the tourism sector and continue to support training
accreditation programmes in the tourism industry.
251
This study also highlighted the ineffectiveness of disseminating information to Malaysian
TSMEs about the availability of financial and non-financial programs provided by the
governments. Most tourism entrepreneurs are unaware of the existing supports to which
they are entitled. This also explains why the majority of tourism entrepreneurs have not
applied for the available funds or attended the programme provided by MOTOUR and its
agency. Thus, MOTOUR together with SME Corp must take actions to ensure that
information is delivered to tourism entrepreneurs about financial and non-financial
programmes for TSMEs.
It was highlighted that there is insufficient data on TSMEs in Malaysia. This is because
TSMEs in tourism are classified as SMEs in the services sector. Since TSMEs are
recognised as the backbone of the tourism industry, and based on a review of empirical
studies of TSMEs in other tourism countries, it is suggested that MOTOUR, DOS and SME
Corp have to take the initiative to collaborate in providing sufficient data on Malaysian
TSME businesses based on business size, type of business and location. The lack of the
TSME data will limit the real potential of Malaysian TSMEs due to the difficulties faced by
researchers to gather extensive information to explore TSMEs’ economic contribution to
the Malaysian tourism industry and also to the national level.
The Malaysian government should encourage the involvement of younger age groups,
particularly the unemployed student graduated from higher education. The educational
attainment they acquired regardless of study major will help in terms of providing
diversification of TSME business products in Malaysia.
252
It is also suggested that government agencies should develop market intelligence systems to
understand the opportunities and demand challenges for TSMEs’ type of business, and put
them into a suitable market segment based on their niche market or location. Improvement
in the quality and accessibility of information gathered through market intelligence will in
turn solve the problem of determining the business products or services that TSMEs should
best provide.
The government also needs to increase TSME involvement in utilising the Internet to
market their business globally. It should also emphasise to TSMEs the distinct advantage of
using the Internet as a key marketing tool. For instance, this could be done by assisting
TSMEs to develop their business websites. The government could also help monitor
website development progress by checking that the business website is continuously
updated and by offering online payments.
Since most tourism entrepreneurs in Malaysia prefer to keep the business small and only a
minority of them are interested in expanding business, the Malaysian government should
consider focusing on how to utilise these lifestyle TSMEs in order to ensure that they can
still contribute to tourism industry performance.
7.4 Suggestions for Future Research
In conducting this study, some limitations have been recognised and create suggestions for
future research. This study has provided a range of insights into controllable success
factors; however, the quantitative method employed using a structured questionnaire
253
limited the potential to determine other possible controllable success factors of Malaysian
TSMEs. Thus, a qualitative approach is suggested for future research, based on in-depth
interviews with TSME owner–managers to confirm their views on all factors affecting
TSMEs’ performance identified in this study. By expanding the study to a longitudinal and
qualitative research design, insight into dynamic processes could also be gained. Multiple
case study methodology would be appropriate to investigate and chart the effects of internal
factors on decision making in TSMEs in Malaysia.
The sampling frame of this study is focused on small-sized and medium-sized firms dealing
in tourism businesses in two sub-sectors only: accommodation services and travel-agent
services. Thus, it is suggested that future research expand the type of tourism business
services involved in the research to better understand and identify tourism entrepreneurs’
motivation and the management practices that are influential in the performance of TSMEs.
Consequently, this research has made several of contributions of theory and practice of
tourism entrepreneurship and TSME performance. These are summarised below.
First, this study validates the resource-based theory that has previously been applied in
developed countries, within the context of a developing country, Malaysia. The finding
reveals some differences that exist between TSMEs in developed and developing countries
using a cross-sectional research design.
Secondly, this study formulates a new approach to TSMEs’ perceived performance by
adopting socio-economic factors in identifying the motivation of tourism entrepreneurs.
Extending the methodology proposed by Indarti and Langenberg (2004), this study defined
254
and validated that ethnicity factors have no impact on tourism entrepreneurial behaviour in
Malaysia.
Thirdly, the adoption of data analysis using the AMOS 18 platform provided a means for
simultaneously examining two subjects. The first subject was using a single model to
investigate the relationship between various internal factors (entrepreneur characteristics,
organisation characteristics and various management practices). The second subject was the
quantification of said relationships. This also provided a means for testing hypotheses using
multivariate and univariate data analysis techniques.
255
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APPENDIX 2.1
Tourism Malaysia Offices
Local Offices Overseas Offices 1. Alor Setar, Kedah 1. Australia – Perth and Sydney 2. Ipoh, Perak 2. Brunei 3. Johor Bahru, Johor 3. Canada 4. Kangar, Perlis 4. China – Beijing and Shanghai 5. Kota Bharu, Kelantan 5. France 6. Kota Kinabalu, Sabah 6. Germany 7. Kuantan, Pahang 7. Hong Kong 8. Kuching, Sarawak 8. India – New Delhi, Chennai and
Mumbai 9. Melaka 9. Indonesia – Medan and Jakarta 10. Pulau Pinang, Pulau Pinang 10. Italy 11. Shah Alam, Selangor 11. Japan – Tokyo and Osaka 12. Seremban, Negeri Sembilan 12. Kingdom of Saudi Arabia 13. Netherlands
14. New Zealand 15. Philipines 16. Republic of Korea 17. Russia 18. Singapore 19. South Africa 20. Sweeden 21. Taiwan 22. Thailand – Bangkok and Phuket 23. Turkey 24. United Arab Emirates 25. United Kingdom
Marketing Representatives
Offices 1. Bangladesh 2. Cambodia 3. China – Chengdu 4. Dublin 5. Iran 6. Laos 7. Pakistan 8. Vietnam
294
Tourist Information Centre
States/Federal Territories Locations 1. Kedah • Bukit Kayu Hitam,
• Langkawi International Airport, • Kuah, • Jetty Point
2. Johor • Tanjung Belungkor, • Tanjung Pengelih, • Johor Bahru Sentral, • Johor Bahru
3. Terengganu • Kemaman, • Kuala Besut
4. Kuala Lumpur • Kuala Lumpur Sentral 5. Sarawak • Kuching International Airport 6. Labuan • Labuan 7. Perak • Lumut 8. Melaka • Menara Taming Sari 9. Negeri Sembilan • Mambau 10. Pulau Pinang • Georgetown, Pulau Pinang International
Airport 11. Sabah • Kota Kinabalu International Airport 12. Selangor • Low Cost Carrier Terminanl Sepang
295
APPENDIX 4.1
Approval from University of Newcastle’s Human Research Ethics Committee
296
297
APPENDIX 4.2
Questionnaires
298
299
300
301
302
303
304
305
APPENDIX 5.1
Location * Type of business Crosstabulation
Type of business
Total Travel agent Accommodation
Location Pahang Count 40 30 70
% within Location 57.1% 42.9% 100.0%
% of Total 11.6% 8.7% 20.2%
Pulau Pinang Count 28 41 69
% within Location 40.6% 59.4% 100.0%
% of Total 8.1% 11.8% 19.9%
Kedah Count 36 35 71
% within Location 50.7% 49.3% 100.0%
% of Total 10.4% 10.1% 20.5%
Kuala Lumpur Count 34 38 72
% within Location 47.2% 52.8% 100.0%
% of Total 9.8% 11.0% 20.8%
Sabah Count 32 32 64
% within Location 50.0% 50.0% 100.0%
% of Total 9.2% 9.2% 18.5%
Total Count 170 176 346
% within Location 49.1% 50.9% 100.0%
% of Total 49.1% 50.9% 100.0%
Chi-Square Tests
Value df
Asymp. Sig. (2-
sided)
Pearson Chi-Square 4.011a 4 .404
Likelihood Ratio 4.030 4 .402
Linear-by-Linear Association .183 1 .668
N of Valid Cases 346
a. 0 cells (.0%) have expected count less than 5. The minimum expected
count is 31.45.
306
APPENDIX 5.2
Location * FirmSize Crosstabulation
FirmSize
Total small Medium
Location Pahang Count 67 3 70
% within Location 95.7% 4.3% 100.0%
% of Total 19.4% .9% 20.2%
Pulau Pinang Count 45 24 69
% within Location 65.2% 34.8% 100.0%
% of Total 13.0% 6.9% 19.9%
Kedah Count 27 44 71
% within Location 38.0% 62.0% 100.0%
% of Total 7.8% 12.7% 20.5%
Kuala Lumpur Count 44 28 72
% within Location 61.1% 38.9% 100.0%
% of Total 12.7% 8.1% 20.8%
Sabah Count 30 34 64
% within Location 46.9% 53.1% 100.0%
% of Total 8.7% 9.8% 18.5%
Total Count 213 133 346
% within Location 61.6% 38.4% 100.0%
% of Total 61.6% 38.4% 100.0%
Chi-Square Tests
Value df
Asymp. Sig. (2-
sided)
Pearson Chi-Square 57.350a 4 .000
Likelihood Ratio 68.046 4 .000
Linear-by-Linear Association 30.039 1 .000
N of Valid Cases 346
a. 0 cells (.0%) have expected count less than 5. The minimum expected
count is 24.60.
307
APPENDIX 5.3
A family business * Type of ownership Crosstabulation
Type of ownership
Total
Sole
proprietorship Partnership
Private limited
company
A family
business
Yes Count 40 54 58 152
% within A
family
business
26.3% 35.5% 38.2% 100.0%
% of Total 11.6% 15.6% 16.8% 43.9%
No Count 36 77 81 194
% within A
family
business
18.6% 39.7% 41.8% 100.0%
% of Total 10.4% 22.3% 23.4% 56.1%
Total Count 76 131 139 346
% within A
family
business
22.0% 37.9% 40.2% 100.0%
% of Total 22.0% 37.9% 40.2% 100.0%
Chi-Square Tests
Value df
Asymp. Sig. (2-
sided)
Pearson Chi-Square 3.000a 2 .223
Likelihood Ratio 2.982 2 .225
Linear-by-Linear Association 1.862 1 .172
N of Valid Cases 346
a. 0 cells (.0%) have expected count less than 5. The minimum expected
count is 33.39.
308
APPENDIX 5.4
Location * Type of ownership Crosstabulation
Type of ownership
Total
Sole
proprietorship Partnership
Private limited
company
Location Pahang Count 12 19 39 70
% within
Location
17.1% 27.1% 55.7% 100.0%
% of Total 3.5% 5.5% 11.3% 20.2%
Pulau
Pinang
Count 23 31 15 69
% within
Location
33.3% 44.9% 21.7% 100.0%
% of Total 6.6% 9.0% 4.3% 19.9%
Kedah Count 18 33 20 71
% within
Location
25.4% 46.5% 28.2% 100.0%
% of Total 5.2% 9.5% 5.8% 20.5%
Kuala
Lumpur
Count 12 23 37 72
% within
Location
16.7% 31.9% 51.4% 100.0%
% of Total 3.5% 6.6% 10.7% 20.8%
Sabah Count 11 25 28 64
% within
Location
17.2% 39.1% 43.8% 100.0%
% of Total 3.2% 7.2% 8.1% 18.5%
Total Count 76 131 139 346
% within
Location
22.0% 37.9% 40.2% 100.0%
% of Total 22.0% 37.9% 40.2% 100.0%
309
Chi-Square Tests
Value df
Asymp. Sig. (2-
sided)
Pearson Chi-Square 26.924a 8 .001
Likelihood Ratio 27.502 8 .001
Linear-by-Linear Association .537 1 .464
N of Valid Cases 346
a. 0 cells (.0%) have expected count less than 5. The minimum expected
count is 14.06.
310
APPENDIX 5.5
Location * Business Founded Crosstabulation
Business Founded
Total >1980 1981-1991 1992-2002 2003-2009
Location Pahang Count 1 13 18 38 70
% within Location 1.4% 18.6% 25.7% 54.3% 100.0%
% of Total .3% 3.8% 5.2% 11.0% 20.2%
Pulau
Pinang
Count 0 5 30 34 69
% within Location .0% 7.2% 43.5% 49.3% 100.0%
% of Total .0% 1.4% 8.7% 9.8% 19.9%
Kedah Count 2 9 26 34 71
% within Location 2.8% 12.7% 36.6% 47.9% 100.0%
% of Total .6% 2.6% 7.5% 9.8% 20.5%
Kuala
Lumpur
Count 6 12 23 31 72
% within Location 8.3% 16.7% 31.9% 43.1% 100.0%
% of Total 1.7% 3.5% 6.6% 9.0% 20.8%
Sabah Count 9 18 23 14 64
% within Location 14.1% 28.1% 35.9% 21.9% 100.0%
% of Total 2.6% 5.2% 6.6% 4.0% 18.5%
Total Count 18 57 120 151 346
% within Location 5.2% 16.5% 34.7% 43.6% 100.0%
% of Total 5.2% 16.5% 34.7% 43.6% 100.0%
Chi-Square Tests
Value df
Asymp. Sig. (2-
sided)
Pearson Chi-Square 39.937a 12 .000
Likelihood Ratio 42.686 12 .000
Linear-by-Linear Association 23.026 1 .000
N of Valid Cases 346
a. 5 cells (25.0%) have expected count less than 5. The minimum
expected count is 3.33.
311
APPENDIX 5.6
Location * Age4grup Crosstabulation
Age4grup
Total below 30 31-40 41-50 51 above
Location Pahang Count 7 22 34 7 70
% within Location 10.0% 31.4% 48.6% 10.0% 100.0%
% of Total 2.0% 6.4% 9.8% 2.0% 20.2%
Pulau
Pinang
Count 5 31 29 4 69
% within Location 7.2% 44.9% 42.0% 5.8% 100.0%
% of Total 1.4% 9.0% 8.4% 1.2% 19.9%
Kedah Count 10 24 32 5 71
% within Location 14.1% 33.8% 45.1% 7.0% 100.0%
% of Total 2.9% 6.9% 9.2% 1.4% 20.5%
Kuala
Lumpur
Count 18 22 25 7 72
% within Location 25.0% 30.6% 34.7% 9.7% 100.0%
% of Total 5.2% 6.4% 7.2% 2.0% 20.8%
Sabah Count 11 16 26 11 64
% within Location 17.2% 25.0% 40.6% 17.2% 100.0%
% of Total 3.2% 4.6% 7.5% 3.2% 18.5%
Total Count 51 115 146 34 346
% within Location 14.7% 33.2% 42.2% 9.8% 100.0%
% of Total 14.7% 33.2% 42.2% 9.8% 100.0%
Chi-Square Tests
Value df
Asymp. Sig. (2-
sided)
Pearson Chi-Square 20.530a 12 .058
Likelihood Ratio 19.852 12 .070
Linear-by-Linear Association .433 1 .510
N of Valid Cases 346
a. 0 cells (.0%) have expected count less than 5. The minimum expected
count is 6.29.
312
APPENDIX 5.7
Correlations
Motivation Age4grup
Spearman's rho Motivation Correlation Coefficient 1.000 .202**
Sig. (2-tailed) . .000
N 346 346
Age4grup Correlation Coefficient .202** 1.000
Sig. (2-tailed) .000 .
N 346 346
**. Correlation is significant at the 0.01 level (2-tailed).
313
APPENDIX 5.8
Location * Gender Crosstabulation
Gender
Total Male Female
Location Pahang Count 58 12 70
% within Location 82.9% 17.1% 100.0%
% of Total 16.8% 3.5% 20.2%
Pulau Pinang Count 47 22 69
% within Location 68.1% 31.9% 100.0%
% of Total 13.6% 6.4% 19.9%
Kedah Count 40 31 71
% within Location 56.3% 43.7% 100.0%
% of Total 11.6% 9.0% 20.5%
Kuala Lumpur Count 56 16 72
% within Location 77.8% 22.2% 100.0%
% of Total 16.2% 4.6% 20.8%
Sabah Count 50 14 64
% within Location 78.1% 21.9% 100.0%
% of Total 14.5% 4.0% 18.5%
Total Count 251 95 346
% within Location 72.5% 27.5% 100.0%
% of Total 72.5% 27.5% 100.0%
Chi-Square Tests
Value df
Asymp. Sig. (2-
sided)
Pearson Chi-Square 15.770a 4 .003
Likelihood Ratio 15.393 4 .004
Linear-by-Linear Association .002 1 .968
N of Valid Cases 346
a. 0 cells (.0%) have expected count less than 5. The minimum expected
count is 17.57.
314
APPENDIX 5.9
Correlations
Motivation Gender
Spearman's rho Motivation Correlation Coefficient 1.000 .326**
Sig. (2-tailed) . .000
N 346 346
Gender Correlation Coefficient .326** 1.000
Sig. (2-tailed) .000 .
N 346 346
**. Correlation is significant at the 0.01 level (2-tailed).
315
APPENDIX 5.10
Location * Edu Crosstabulation
Edu
Total Primary Secondary Tertiatry
Location Pahang Count 0 15 55 70
% within Location .0% 21.4% 78.6% 100.0%
% of Total .0% 4.3% 15.9% 20.2%
Pulau Pinang Count 0 32 37 69
% within Location .0% 46.4% 53.6% 100.0%
% of Total .0% 9.2% 10.7% 19.9%
Kedah Count 1 38 32 71
% within Location 1.4% 53.5% 45.1% 100.0%
% of Total .3% 11.0% 9.2% 20.5%
Kuala Lumpur Count 0 33 39 72
% within Location .0% 45.8% 54.2% 100.0%
% of Total .0% 9.5% 11.3% 20.8%
Sabah Count 0 20 44 64
% within Location .0% 31.3% 68.8% 100.0%
% of Total .0% 5.8% 12.7% 18.5%
Total Count 1 138 207 346
% within Location .3% 39.9% 59.8% 100.0%
% of Total .3% 39.9% 59.8% 100.0%
Chi-Square Tests
Value df
Asymp. Sig. (2-
sided)
Pearson Chi-Square 24.103a 8 .002
Likelihood Ratio 24.187 8 .002
Linear-by-Linear Association 1.280 1 .258
N of Valid Cases 346
a. 5 cells (33.3%) have expected count less than 5. The minimum
expected count is .18.
316
APPENDIX 5.11
Correlations
Motivation Edu
Spearman's rho Motivation Correlation Coefficient 1.000 .074
Sig. (2-tailed) . .172
N 346 346
Edu Correlation Coefficient .074 1.000
Sig. (2-tailed) .172 .
N 346 346
317
APPENDIX 5.12
Location * Ethnicity Crosstabulation
Ethnicity
Total Malay Chinese Indian Others
Location Pahang Count 54 9 5 2 70
% within Location 77.1% 12.9% 7.1% 2.9% 100.0%
% of Total 15.6% 2.6% 1.4% .6% 20.2%
Pulau
Pinang
Count 27 27 14 1 69
% within Location 39.1% 39.1% 20.3% 1.4% 100.0%
% of Total 7.8% 7.8% 4.0% .3% 19.9%
Kedah Count 20 35 15 1 71
% within Location 28.2% 49.3% 21.1% 1.4% 100.0%
% of Total 5.8% 10.1% 4.3% .3% 20.5%
Kuala
Lumpur
Count 32 33 7 0 72
% within Location 44.4% 45.8% 9.7% .0% 100.0%
% of Total 9.2% 9.5% 2.0% .0% 20.8%
Sabah Count 21 29 10 4 64
% within Location 32.8% 45.3% 15.6% 6.3% 100.0%
% of Total 6.1% 8.4% 2.9% 1.2% 18.5%
Total Count 154 133 51 8 346
% within
Location
44.5% 38.4% 14.7% 2.3% 100.0%
% of Total 44.5% 38.4% 14.7% 2.3% 100.0%
Chi-Square Tests
Value df
Asymp. Sig. (2-
sided)
Pearson Chi-Square 53.269a 12 .000
Likelihood Ratio 55.781 12 .000
Linear-by-Linear Association 10.873 1 .001
N of Valid Cases 346
318
Location * Ethnicity Crosstabulation
Ethnicity
Total Malay Chinese Indian Others
Location Pahang Count 54 9 5 2 70
% within Location 77.1% 12.9% 7.1% 2.9% 100.0%
% of Total 15.6% 2.6% 1.4% .6% 20.2%
Pulau
Pinang
Count 27 27 14 1 69
% within Location 39.1% 39.1% 20.3% 1.4% 100.0%
% of Total 7.8% 7.8% 4.0% .3% 19.9%
Kedah Count 20 35 15 1 71
% within Location 28.2% 49.3% 21.1% 1.4% 100.0%
% of Total 5.8% 10.1% 4.3% .3% 20.5%
Kuala
Lumpur
Count 32 33 7 0 72
% within Location 44.4% 45.8% 9.7% .0% 100.0%
% of Total 9.2% 9.5% 2.0% .0% 20.8%
Sabah Count 21 29 10 4 64
% within Location 32.8% 45.3% 15.6% 6.3% 100.0%
% of Total 6.1% 8.4% 2.9% 1.2% 18.5%
Total Count 154 133 51 8 346
% within
Location
44.5% 38.4% 14.7% 2.3% 100.0%
a. 5 cells (25.0%) have expected count less than 5. The minimum
expected count is 1.48.
319
APPENDIX 5.13
Correlations
Motivation Ethnic
Spearman's rho Motivation Correlation Coefficient 1.000 .126*
Sig. (2-tailed) . .019
N 346 346
Ethnic Correlation Coefficient .126* 1.000
Sig. (2-tailed) .019 .
N 346 346
*. Correlation is significant at the 0.05 level (2-tailed).
320
APPENDIX 5.14
Location * A family business Crosstabulation
A family business
Total Yes No
Location Pahang Count 24 46 70
% within Location 34.3% 65.7% 100.0%
% of Total 6.9% 13.3% 20.2%
Pulau Pinang Count 34 35 69
% within Location 49.3% 50.7% 100.0%
% of Total 9.8% 10.1% 19.9%
Kedah Count 37 34 71
% within Location 52.1% 47.9% 100.0%
% of Total 10.7% 9.8% 20.5%
Kuala Lumpur Count 31 41 72
% within Location 43.1% 56.9% 100.0%
% of Total 9.0% 11.8% 20.8%
Sabah Count 26 38 64
% within Location 40.6% 59.4% 100.0%
% of Total 7.5% 11.0% 18.5%
Total Count 152 194 346
% within Location 43.9% 56.1% 100.0%
% of Total 43.9% 56.1% 100.0%
Chi-Square Tests
Value df
Asymp. Sig. (2-
sided)
Pearson Chi-Square 5.680a 4 .224
Likelihood Ratio 5.720 4 .221
Linear-by-Linear Association .147 1 .702
N of Valid Cases 346
a. 0 cells (.0%) have expected count less than 5. The minimum expected
count is 28.12.
321
APPENDIX 5.15
Correlations
Motivation
FamilyBusBack
ground
Spearman's rho Motivation Correlation Coefficient 1.000 .108*
Sig. (2-tailed) . .045
N 346 346
FamilyBusBackground Correlation Coefficient .108* 1.000
Sig. (2-tailed) .045 .
N 346 346
*. Correlation is significant at the 0.05 level (2-tailed).
322
APPENDIX 5.16
Location * WorkExp Crosstabulation
WorkExp
Total Yes No
Location Pahang Count 0 70 70
% within Location .0% 100.0% 100.0%
% of Total .0% 20.2% 20.2%
Pulau Pinang Count 6 63 69
% within Location 8.7% 91.3% 100.0%
% of Total 1.7% 18.2% 19.9%
Kedah Count 6 65 71
% within Location 8.5% 91.5% 100.0%
% of Total 1.7% 18.8% 20.5%
Kuala Lumpur Count 9 63 72
% within Location 12.5% 87.5% 100.0%
% of Total 2.6% 18.2% 20.8%
Sabah Count 23 41 64
% within Location 35.9% 64.1% 100.0%
% of Total 6.6% 11.8% 18.5%
Total Count 44 302 346
% within Location 12.7% 87.3% 100.0%
% of Total 12.7% 87.3% 100.0%
Chi-Square Tests
Value df
Asymp. Sig. (2-
sided)
Pearson Chi-Square 43.461a 4 .000
Likelihood Ratio 43.883 4 .000
Linear-by-Linear Association 33.377 1 .000
N of Valid Cases 346
a. 0 cells (.0%) have expected count less than 5. The minimum expected
count is 8.14.
323
APPENDIX 5.17
Correlations
Motivation WorkExp
Spearman's rho Motivation Correlation Coefficient 1.000 .110*
Sig. (2-tailed) . .041
N 346 346
WorkExp Correlation Coefficient .110* 1.000
Sig. (2-tailed) .041 .
N 346 346
*. Correlation is significant at the 0.05 level (2-tailed).
324
APPENDIX 5.18
Descriptives
Motivation
N Mean
Std.
Deviation Std. Error
95% Confidence Interval for
Mean
Minimum Maximum Lower Bound Upper Bound
Pahang 70 3.8518 .64349 .07691 3.6984 4.0052 1.75 5.00
Pulau Pinang 69 3.8152 .50576 .06089 3.6937 3.9367 2.25 5.00
Kedah 71 4.1972 .45003 .05341 4.0907 4.3037 2.88 5.00
Kuala Lumpur 72 3.8872 .66182 .07800 3.7316 4.0427 2.13 5.00
Sabah 64 4.0508 .46490 .05811 3.9347 4.1669 3.13 5.00
Total 346 3.9595 .56984 .03063 3.8993 4.0198 1.75 5.00
Test of Homogeneity of Variances
Motivation
Levene Statistic df1 df2 Sig.
2.244 4 341 .064
ANOVA
Motivation
Sum of Squares df Mean Square F Sig.
Between Groups 7.170 4 1.792 5.829 .000
Within Groups 104.858 341 .308
Total 112.027 345
325
Post Hoc Tests
Multiple Comparisons
Motivation
Tukey HSD
(I) Location (J) Location
Mean Difference
(I-J) Std. Error Sig.
95% Confidence Interval
Lower
Bound Upper Bound
Pahang Pulau Pinang .03657 .09407 .995 -.2214 .2946
Kedah -.34540* .09340 .002 -.6015 -.0893
Kuala Lumpur -.03537 .09308 .996 -.2906 .2199
Sabah -.19900 .09590 .233 -.4620 .0640
Pulau Pinang Pahang -.03657 .09407 .995 -.2946 .2214
Kedah -.38197* .09374 .001 -.6390 -.1249
Kuala Lumpur -.07194 .09342 .939 -.3281 .1843
Sabah -.23556 .09624 .105 -.4995 .0284
Kedah Pahang .34540* .09340 .002 .0893 .6015
Pulau Pinang .38197* .09374 .001 .1249 .6390
Kuala Lumpur .31003* .09275 .008 .0557 .5644
Sabah .14640 .09558 .543 -.1157 .4085
Kuala
Lumpur
Pahang .03537 .09308 .996 -.2199 .2906
Pulau Pinang .07194 .09342 .939 -.1843 .3281
Kedah -.31003* .09275 .008 -.5644 -.0557
Sabah -.16363 .09527 .424 -.4249 .0976
Sabah Pahang .19900 .09590 .233 -.0640 .4620
Pulau Pinang .23556 .09624 .105 -.0284 .4995
Kedah -.14640 .09558 .543 -.4085 .1157
Kuala Lumpur .16363 .09527 .424 -.0976 .4249
*. The mean difference is significant at the 0.05 level.
326
APPENDIX 5.19
Location * Business strategy Crosstabulation
Business strategy
Total Formal informal
Location Pahang Count 52 18 70
% within Location 74.3% 25.7% 100.0%
% of Total 15.0% 5.2% 20.2%
Pulau Pinang Count 58 11 69
% within Location 84.1% 15.9% 100.0%
% of Total 16.8% 3.2% 19.9%
Kedah Count 56 15 71
% within Location 78.9% 21.1% 100.0%
% of Total 16.2% 4.3% 20.5%
Kuala Lumpur Count 49 23 72
% within Location 68.1% 31.9% 100.0%
% of Total 14.2% 6.6% 20.8%
Sabah Count 35 29 64
% within Location 54.7% 45.3% 100.0%
% of Total 10.1% 8.4% 18.5%
Total Count 250 96 346
% within Location 72.3% 27.7% 100.0%
% of Total 72.3% 27.7% 100.0%
Chi-Square Tests
Value df
Asymp. Sig. (2-
sided)
Pearson Chi-Square 16.976a 4 .002
Likelihood Ratio 16.714 4 .002
Linear-by-Linear Association 9.790 1 .002
N of Valid Cases 346
a. 0 cells (.0%) have expected count less than 5. The minimum expected
count is 17.76.
327
APPENDIX 5.20
Test of Homogeneity of Variances
BusinessAllianceActi
Levene Statistic df1 df2 Sig.
4.917 4 341 .001
ANOVA
BusinessAllianceActi
Sum of Squares df Mean Square F Sig.
Between Groups 22.302 4 5.575 8.344 .000
Within Groups 227.868 341 .668
Total 250.170 345
Descriptives
BusinessAllianceActi
N Mean
Std.
Deviation Std. Error
95% Confidence Interval
for Mean
Minimum Maximum
Lower
Bound Upper Bound
Pahang 70 3.7490 .59099 .07064 3.6081 3.8899 2.00 5.00
Pulau Pinang 69 3.7660 .82247 .09901 3.5685 3.9636 1.00 4.86
Kedah 71 3.3883 .90001 .10681 3.1753 3.6014 1.00 4.57
Kuala Lumpur 72 3.1944 .97579 .11500 2.9651 3.4237 1.00 5.00
Sabah 64 3.8482 .72882 .09110 3.6662 4.0303 1.00 5.00
Total 346 3.5813 .85155 .04578 3.4913 3.6714 1.00 5.00
328
Post Hoc Tests Multiple Comparisons
BusinessAllianceActi
Tukey HSD
(I) Location
(J)
Location
Mean
Difference
(I-J) Std. Error Sig.
95% Confidence Interval
Lower Bound Upper Bound
Pahang Pulau Pinang -.01707 .13868 1.000 -.3974 .3632
Kedah .36065 .13769 .069 -.0170 .7382
Kuala Lumpur .55454* .13721 .001 .1782 .9308
Sabah -.09923 .14138 .956 -.4870 .2885
Pulau
Pinang
Pahang .01707 .13868 1.000 -.3632 .3974
Kedah .37772 .13819 .051 -.0013 .7567
Kuala Lumpur .57160* .13772 .000 .1939 .9493
Sabah -.08217 .14187 .978 -.4712 .3069
Kedah Pahang -.36065 .13769 .069 -.7382 .0170
Pulau Pinang -.37772 .13819 .051 -.7567 .0013
Kuala Lumpur .19389 .13672 .616 -.1811 .5688
Sabah -.45988* .14090 .011 -.8463 -.0735
Kuala
Lumpur
Pahang -.55454* .13721 .001 -.9308 -.1782
Pulau Pinang -.57160* .13772 .000 -.9493 -.1939
Kedah -.19389 .13672 .616 -.5688 .1811
Sabah -.65377* .14044 .000 -1.0389 -.2686
Sabah Pahang .09923 .14138 .956 -.2885 .4870
Pulau Pinang .08217 .14187 .978 -.3069 .4712
Kedah .45988* .14090 .011 .0735 .8463
Kuala Lumpur .65377* .14044 .000 .2686 1.0389
*. The mean difference is significant at the 0.05 level.
329
APPENDIX 5.21
Location * Year of business first started use IT Crosstabulation
Year of business first started use IT
Total 1996-2000 2001-2005 >2006
Location Pahang Count 4 30 36 70
% within Location 5.7% 42.9% 51.4% 100.0%
% of Total 1.2% 8.7% 10.4% 20.2%
Pulau Pinang Count 14 35 20 69
% within Location 20.3% 50.7% 29.0% 100.0%
% of Total 4.0% 10.1% 5.8% 19.9%
Kedah Count 6 42 23 71
% within Location 8.5% 59.2% 32.4% 100.0%
% of Total 1.7% 12.1% 6.6% 20.5%
Kuala Lumpur Count 13 32 27 72
% within Location 18.1% 44.4% 37.5% 100.0%
% of Total 3.8% 9.2% 7.8% 20.8%
Sabah Count 12 24 28 64
% within Location 18.8% 37.5% 43.8% 100.0%
% of Total 3.5% 6.9% 8.1% 18.5%
Total Count 49 163 134 346
% within Location 14.2% 47.1% 38.7% 100.0%
% of Total 14.2% 47.1% 38.7% 100.0%
Chi-Square Tests
Value df
Asymp. Sig. (2-
sided)
Pearson Chi-Square 18.511a 8 .018
Likelihood Ratio 19.310 8 .013
Linear-by-Linear Association 1.493 1 .222
N of Valid Cases 346
a. 0 cells (.0%) have expected count less than 5. The minimum expected
count is 9.06.
330
APPENDIX 5.22
Descriptives
InternetApplication
N Mean
Std.
Deviation Std. Error
95% Confidence Interval
for Mean
Minimum Maximum
Lower
Bound Upper Bound
Pahang 70 3.7026 .61149 .07309 3.5568 3.8484 2.27 4.91
Pulau Pinang 69 3.3347 .78350 .09432 3.1464 3.5229 1.64 4.82
Kedah 71 3.5621 .75394 .08948 3.3836 3.7406 1.73 4.91
Kuala
Lumpur
72 3.5581 .87228 .10280 3.3531 3.7631 1.64 5.00
Sabah 64 3.6591 .97307 .12163 3.4160 3.9022 1.27 5.00
Total 346 3.5623 .81037 .04357 3.4766 3.6480 1.27 5.00
Test of Homogeneity of Variances
InternetApplication
Levene Statistic df1 df2 Sig.
3.544 4 341 .008
ANOVA
InternetApplication
Sum of Squares df Mean Square F Sig.
Between Groups 5.555 4 1.389 2.143 .075
Within Groups 221.009 341 .648
Total 226.563 345
331
Post Hoc Tests Multiple Comparisons
InternetApplication
Tukey HSD
(I) Location (J) Location
Mean
Difference (I-J) Std. Error Sig.
95% Confidence
Interval
Lower
Bound
Upper
Bound
Pahang Pulau Pinang .36795 .13657 .057 -.0066 .7425
Kedah .14050 .13560 .838 -.2314 .5124
Kuala Lumpur .14452 .13513 .822 -.2261 .5151
Sabah .04351 .13923 .998 -.3383 .4253
Pulau
Pinang
Pahang -.36795 .13657 .057 -.7425 .0066
Kedah -.22745 .13609 .453 -.6007 .1458
Kuala Lumpur -.22343 .13563 .468 -.5954 .1485
Sabah -.32444 .13971 .140 -.7076 .0587
Kedah Pahang -.14050 .13560 .838 -.5124 .2314
Pulau Pinang .22745 .13609 .453 -.1458 .6007
Kuala Lumpur .00402 .13465 1.000 -.3652 .3733
Sabah -.09699 .13876 .957 -.4775 .2836
Kuala
Lumpur
Pahang -.14452 .13513 .822 -.5151 .2261
Pulau Pinang .22343 .13563 .468 -.1485 .5954
Kedah -.00402 .13465 1.000 -.3733 .3652
Sabah -.10101 .13831 .949 -.4803 .2783
Sabah Pahang -.04351 .13923 .998 -.4253 .3383
Pulau Pinang .32444 .13971 .140 -.0587 .7076
Kedah .09699 .13876 .957 -.2836 .4775
Kuala Lumpur .10101 .13831 .949 -.2783 .4803