STAKEHOLDERS’ ANALYSIS ON KARAIKUDI ASshodhganga.inflibnet.ac.in/bitstream/10603/32546/1/... · · 2015-01-072.2.3.2 Doxey's Irridex Model (1975) 54 2.3 Theoretical background

STAKEHOLDERS’ ANALYSIS ON KARAIKUDI AS

A RURAL TOURISM DESTINATION

A THESIS

Submitted by

YAVANA RANI.S.

Register No: 200902212

In partial fulfillment for the award of the degree

of

DOCTOR OF PHILOSOPHY

DEPARTMENT OF BUSINESS ADMINISTRATIONKALASALINGAM UNIVERSITY

ANAND NAGARKRISHNANKOIL – 626 126

AUGUST 2013

ii

KALASALINGAM UNIVERSITY

KRISHNANKOIL 626 126

BONAFIDE CERTIFICATE

Certified that this Thesis title “STAKEHOLDERS’ ANALYSIS ON

KARAIKUDI AS A RURAL TOURISM DESTINATION” is the bonafide

work of Ms. YAVANA RANI.S., who carried out the research under my

supervision. Certified further, that to the best of my knowledge the work reported

herein does not form part of any other thesis or dissertation on the basis of which

a degree or award was conferred on an earlier occasion on this or any other

scholar.

Signature of the supervisor

Dr.M.Jeyakumaran

SUPERVISOR

Professor

Department of Business Administration

Kalasalingam University

Krishnankoil

iii

ABSTRACT

Identification of stakeholders’ involvement in destination tourism planning and

development, as well as the factors that might influence their level of

involvement, is not only important for tourism destination planners, but also the

host community’s support for destination tourism development and competitive

strategies. This study tests the structural equation model between stakeholders’

perceptions and opinions about the impacts of tourism development, community

participation and further to determine their willingness to support the competitive

development strategies. The implications of social exchange theory and

stakeholders’ theory provide the theoretical underpinning for this study. The

study is descriptive in nature, and is based on both quantitative and qualitative

methodologies to investigate the relationships between different constructs. This

study also examined how demographic characteristics affect community

participation and support for rural tourism in the destination. The study area is a

rural tourism spot Karaikudi, Sivaganga District in Tamilnadu, India.

Convenience and quota sampling methods were adapted to collect quantitative

data from different tourism stakeholders. Convenience sampling was used

because difficulty in approaching households for interviews due to the

conventional nature of the society. Quota sampling was used to ensure different

subgroups of the population have been included. The sample size is 320. The

data was analyzed using Structural Equation Modeling (SEM) with the statistical

iv

package Analysis of Moment Structures (AMOS).The research shows some

statistical significance between tourism development impacts people may

experience and their desire for more participation in the decision-making

process. The results will help the rural tourism planners, governments and

support organizations in other areas to better evaluate and understand the

stakeholders’ attitude and perceptions before implementing the project.

Keywords: Rural Tourism, Stakeholders’ Attitude, Community Satisfaction,

Tourism Support, Tourism Development Impacts.

v

ACKNOWLEDGEMENT

My sincere thanks to our Chairman Kalvivallal Mr.T.KALASALINGAM,

Illayavallal Mr.K.SRIDHARAN Chancellor, Dr. S. SARAVANA SHANKAR,

Vice-Chancellor Kalasalingam University, for providing opportunity to carry out

the research work in our University.

DR. M.JEYAKUMARAN, Professor, Department of Business

Administration, Kalasalingam University, my mentor and supervisor have

extended his valuable guidance and motivation throughout this research. His

approach and kindness has motivated me to execute this research lively. It was

possible to maintain quality throughout the research only because of his freedom

and trust.

I extend my thanks to Dr.S.SAKTHIVEL RANI, Associate Professor,

Head, Department of Business Administration, Kalasalingam University, who

gave all moral support behind the screen.

I dedicate all my work to my Father R.SUBRAMANIAN and mother,

husband, in-laws and my children. I express my gratitude to the effort and pain

they have taken in this regard.

I extend my thanks to the Dean, Research and Development and faculty

members of MBA department for their moral support and encouragement. I

thank my friends Mr. Kamal Dhayalan, Advocate and Mr. V.Ramesh, IBM for

extending their valuable support for my research

I express my pleasure in thanking the students, friends, and my colleagues

for the support and valuable suggestions for the improvement of this research.

There are many others, who have helped me directly and indirectly to complete

this research. I thank them whole-heartedly.

YAVANA RANI.S

vi

TABLE OF CONTENTS

Chapter

No

Title Page

No

ABSTRACT iii

LIST OF TABLES xiii

LIST OF FIGURES xvi

LIST OF SYMBOLS and ABBREVIATIONS xvii

1 INTRODUCTION 1

1.0 Introduction 1

1.1 Research Background 4

1.2 Research Problem 7

1.3 Conceptual framework 10

1.4 Research objectives and hypotheses 11

1.4.1 Primary objectives of the study 11

1.4.2 Primary Hypotheses 11

1.4.3 Secondary objectives of this study 12

1.4.4 Sub hypotheses 12

1.5 Theoretical background 14

1.6 Research methodology 15

1.7 Key findings and contributions of the research 15

1.8 Functional definitions 17

1.9 Tourism in India 18

1.9.1 Introduction 18

vii

1.9.2 India tourism statistics at a glance 2010 19

1.9.3 Rural tourism in India 23

1.9.4 Tourism in Tamilnadu 24

1.9.5 Rural tourism in Tamilnadu 28

1.9.6 Karaikudi’s destination competitiveness 30

1.10 Structure of the Thesis 32

2 LITERATURE REVIEW 34

2.1 Introduction 34

2.2 Tourism background literature 34

2.2.1 Perspectives on rural tourism 34

2.2.1.1 Rural tourism –A multi-faceted activity 37

2.2.1.2 Tourism as a tool for local development 42

2.2.2 Tourism and its systematic approaches 47

2.2.3 Tourism planning and development concepts 49

2.2.3.1 Tourism destination development life cycle 51

2.2.3.2 Doxey's Irridex Model (1975) 54

2.3 Theoretical background of tourism theories 57

2.3.1 Social exchange theory 59

2.3.2 The Social exchange theory and tourism 61

2.3.3 Stakeholder theory 64

2.3.4 Stakeholder theory and tourism 66

2.4 Conceptual framework and hypotheses 67

2.4.1 Tourism development impacts 68

viii

2.4.2 Tourism support 75

2.4.3 Community participation 76

3 RESEARCH METHODOLOGY 81

3.1 Introduction 81

3.2 Research framework 81

3.3 Research hypotheses 84

3.4 Research methods used in tourism research 86

3.5 Research Design 87

3.5.1 Qualitative Data 88

3.5.1.1 Sampling Method 88

3.5.1.2 Sample Size 89

3.5.1.3 Data Analysis 89

3.5.2 Quantitative Data 90

3.5.2.1 Study Population 90

3.5.2.2 Sample size determination 90

3.5.2.3 Sampling Technique 91

3.5.2.4 Sample Size 93

3.5.2.5 Data Collection 93

3.6 Measurement Scales and Instruments 94

3.6.1 Exogenous Constructs: (Independent variables) 97

3.6.1.1Measurement of Tourism Development Impacts 97

3.6.1.2 Measurement of community participation 98

3.6.2 Endogenous Construct: (The dependent variable) 99

ix

3.6.2.1 Measurement of Tourism Support 99

3.6.2.2 Overall community Satisfaction 99

3.6.3 Data analysis 99

3.7 Statistical method for the hypotheses test –StructuralEquation Modeling(SEM)

100

3.7.1 Measurement model or Confirmatory Factor Analysis 101

3.7.2 Structural Model 102

3.7.3 Structural Equation Modeling 103

3.7.4 Reliability and Validity of the MeasurementScales

104

3.8 Other statistical tools 106

3.9 Software Used 106

4 ANALYSIS AND INTERPRETATION OF DATA 107

4.1 Introduction 107

4.2 Data Collection and Response Rate 107

4.3 Profile of Respondents 108

4.3.1 Demographic Characteristics of TourismStakeholders

108

4.4 Descriptive Analysis of Measurement Scales 112

4.4.1 Results of Tourism Development Impacts 112

4.4.2 Results of Community Participation 116

4.4.3 Results of Tourism Support Strategies 117

4.5 Reliability and Validity of Measurement Scales 119

4.5.1 Reliability of Measurement Scales 119

4.5.2 Validity of Measurement Scales 121

x

4.6 Exploratory factor analysis for tourism developmentimpacts

124

4.7 Demographic Profile Analysis 127

4.7.1 Students t-test 128

4.7.2 Analysis of Variance (ANOVA) 132

4.7.3 Chi-Square test 146

4.7.4 Correlation Analysis 147

4.7.5 Regression Analysis 150

4.7.6 Discriminant Analysis 153

4.8 Measurement Model 157

4.8.1 First order Confirmatory factor analysis (CFA) 157

4.8.2 Second order Confirmatory factor analysis (CFA) 166

4.9 Structural model of tourism support 169

4.10 Outcomes of Hypotheses Testing 178

4.11 Reliability and Validity of the measurement instrument 179

4.12 The summary of the hypotheses testing 180

4.13 The summary of sub hypotheses testing 181

4.14 Data analysis of Focus Group Interview 183

4.14.1 Stakeholders views on the community participationimplementation

183

4.14.2 Comparing the residents and stakeholders views 185

5 CONCLUSION AND DISCUSSION 187

5.1 Introduction 187

5.2 Discussion of the Research Findings 188

5.2.1 General Findings and Discussion 188

xi

5.2.2 Demographic characteristics of the respondents 189

5.2.3 Dimensions of tourism development impacts of ruraltourism.

191

5.2.4 Impact of demographic characteristics on communityparticipation

193

5.2.5 Impact of demographic characteristics on overallcommunity satisfaction

194

5.2.6 Impact of demographic characteristics on tourismsupport

195

5.3 Findings of structural equation modeling 198

5.4 Contributions and Implications of the research findings 200

5.4.1 Theoretical contribution 200

5.4.2 Utilization of SEM for key construct relationshiptesting

200

5.4.3 Development of measures and scales. 201

5.4.4 Managerial contributions 201

5.5 Suggestions and recommendations 202

5.5.1 General suggestions 202

5.5.2 Suggestion from findings 203

5.5.3 Recommendations 205

5.6 Limitations and directions for future research 206

5.7 Concluding Comments 208

APPENDICES 210

Appendix 1 - Questionnaire 210

Appendix 2 – List of rural tourism sites in India 215

Appendix 3 – Snap Shots of rural tourism site-Karaikudi 220

xii

REFERENCES 225

LIST OF PUBLICATIONS 240

CURRICULUM VITAE 241

xiii

LIST OF TABLES

TABLE

NO

TITLE PAGE

NO

1.1 Foreign Tourist Arrivals (FTAs) in India, from 1997 to2011

22

1.2 Tourist visit to Tamilnadu 27

2.1 A list of contrasting features between urban tourism andrural tourism

41

2.2 A framework for analyzing the social impacts of tourism 51

2.3 Doxey’s index of irritation (irridex’) 56

3.1 The proportionate numbers of samples 93

3.2 Measurement of variables 95

4.1 Demographic profile of respondents 110

4.2 Descriptive analysis of tourism development impact 114

4.3 Descriptive analysis of community participation 117

4.4 Descriptive analysis of tourism support strategies 118

4.5 Summary of the measurement reliability (cronbach’salpha)

120

4.6 Rotated factor matrix for tourism development impacts 125

4.7 Student t-test- Gender with community participation intourism development

128

4.8 Student t-test- Gender with community satisfaction 129

4.9 Student t-test- Gender with tourism support 129

4.10 Student t-test- Nature of business and tourism support 130

4.11 Student t-test- Closer to the destination or far away andtourism support

131

4.12 Student t- test - consolidated result 132

4.13 ANOVA - Age with community participation in tourismdevelopment

132

4.13.1 Overall mean agreeability score 133

4.14 ANOVA - Occupation with community participation 134


xiv

4.15 ANOVA - Marital status with community participation 135


4.16 ANOVA - length of residency with community participation 137


4.17 ANOVA - Age with overall community satisfaction 138


4.18 ANOVA - Length of residency with community satisfaction 139


4.19 ANOVA - Age with tourism support strategies 140


4.20 ANOVA - Occupation with tourism support strategies 141


4.21 ANOVA- Education with tourism support strategies 143


4.22 ANOVA - length of residency with tourism supportstrategies

144


4.23 ANOVA - consolidated result 145

4.24 Chi-square test for association between years of residencyand support for tourism

146

4.25 Inter-correlation matrix of economic impact variables 147

4.26 Inter-correlation matrix of socio-cultural impact variables 148

4.27 Inter-correlation matrix of environmental impact variables 149

4.28 Inter-correlation matrix of community participationvariables

149

4.29 Inter-correlation matrix of tourism support strategies 150

4.30 Variables in the multiple regression analysis 152

4.31 F tests of equality of group means 154

4.32 Canonical discriminant function unstandardized coefficients 155

4.33 Discriminant analysis classification results 156

xv

4.34 Model Fit Indices- First order CFA 162

4.35 I order - Standardized Regression Weight Factor Loadings 163

4.36 Model Fit Indices – Second order CFA 166

4.37 II order CFA - Standardised Regression Weight FactorLoadings

168

4.38 Model Fit indices – Structural model 170

4.39 Structural model - standardized regression weight factorloadings

177

4.40 Summary of hypotheses testing 178

4.41 Reliability and validity of the measurement instrument 179

4.42 The summary of the Structural Model Hypotheses Findings 180

4.43 The summary of the Sub Hypotheses Finding –Demographic Profile

181

xvi

LIST OF FIGURES

FIGURE

NO

TITLE PAGE NO

1.1 The initial conceptual framework for rural tourismsupport

10

1.2 Percentage share of top 10 states in foreign tourist visitsto states in 2011

21

1.3 Percentage share of top 10 States in domestic touristvisits in 2011

21

1.4 Census 2011 Highlights for Tamilnadu 25

1.5 Karaikudi, Sivaganga District, Tamilnadu Map 30

2.1 A scheme of sustainable development of the region 39

2.2 Tourism origin-destination model 48

2.3 Tourist area (destination) life cycle 52

3.1 The initial conceptual framework for rural tourismsupport

82

4.1 First order standardized CFA – model 1 159

4.2 Standardized CFA – model 2 161

4.3 Overall measurement model - Second order CFA 167

4.4 Structural model 173

4.5 Standardized Structural model 175

xvii

LIST OF ABBREVIATIONS

AFM - Absolute Fit measures

AGFI - Adjusted Goodness-of-Fit Index

AMOS - Analysis of Moment Structures

ANOVA - Analysis of Variance

CAGR - Compound Annual Growth rate

CFA - Confirmatory Factor Analysis

CFI - Comparative Fit Index

cr - Critical ratio

DF - Degrees of Freedom

DMO - Destination Management Organizations

EFA - Exploratory Factor Analysis

ESCOP - Economic and Social Commission for Asia

and the pacific

FEE - Foreign Exchange Earnings

FTA - Foreign Tourist Arrivals

GDP - Gross domestic product

GFI - Goodness-of-Fit Index

GOI - Government of India

IFM - Incremental Fit Measures

KMO - Kaiser-Meyer-Olkin

MS - Mean Square

xviii

ML - Maximum Likelihood

NFI - Normed Fit Index

NGO - Non Governmental Organization

OECD - Organization of Economic Co-Operation and

Development

PFNI - Parsimonious Normed Fit Index

PGFI - Parsimonious Goodness-of-Fit Index

RFI - Relative Fit Index

RMR - Root Mean Square Residual

RMSEA - Root Mean Square Error of Approximation

SD - Standard Deviation

SEM - Structural Equation Modeling

SPSS - Statistical Package for Social Sciences

SRMR - Standardized Root Mean Square Residual

SS - Sum of Squares

TALC - Tourist Area Life-Cycle

TLI - Tucker Lewis index

UNDP - United Nations Development Programme

UN - United Nations

USP - Unique Selling Proposition

WTO - World Tourism Organization

xix

LIST OF SYMBOLS

α - Cronbach's alpha

β - Beta estimate

1

CHAPTER I

INTRODUCTION

1.0 INTRODUCTION

Identification of stakeholders’ involvement in destination tourism

planning and development, as well as the factors that might influence their level

of involvement, is not only important for tourism destination planners, but also

the host community’s support for destination tourism development and

competitive strategies. Tourism destinations need to plan their development

strategies and actions to succeed internationally and gain a competitive

advantage (Dowling, 1993; Riege & Perry, 2000; Ritchie, 1993; Yuksel et al.,

1999). Places that do not develop strategic planning of their destinations can

suffer from economic, social, and environmental problems, as well as a decline

in their competitiveness as a tourism destination (Dowling, 1993).

This study presents an integrated approach to understanding the

competitiveness of rural tourism destinations, and attempts to extend the

theoretical and empirical evidence about the structural relationships among the

following constructs: 1) Tourism development impacts, 2) community

participation and 3) support for enhancement strategies for destination

competitiveness. This study was approached from the tourism stakeholders’

perspective about support for rural tourism destination competitiveness. Their

perceptions, attitudes and behaviors in terms of tourism were assessed as

critical sources of testing the proposed structural model in this study.

2

Worldwide tourism is ranked second highest revenue-generating

industry next to the oil industry. Tourism is one of the leading Global industries

(11% of global Gross domestic product GDP) of the world. The World Tourism

Organization (WTO) estimates that there will be 1.6 billion Tourists in the

World, representing 21% of world population. Tourism industry contributes

high priority goals of developing country’s income, employment, foreign

exchange earnings (primary source of foreign exchange earnings in 46 of 49

developing countries). Now, tourism is one of the largest service industries in

India, with a contribution of 6.23 per cent to the national GDP and 8.78 per cent

of the total employment in India. (ACNielsen ORG-MARG, Ministry of

Tourism, Government of India). Tourism also encourages preservation of

monuments and heritage properties and helps the survival of art forms, crafts

and culture.

Tourists are now looking for a balance between tourism, nature and

culture, between conservation and development in every place they visit.

Increasingly in the 1990s there has been a growth of new types of tourists in

rural spaces, with behavior patterns clearly different from the homecoming

motivation of traditional rural tourism (Brown & Hall, 2000, Perales, 2002).

This paves the opportunity for developing non-traditional tourist destination,

such as the countryside tourism. The tourists are more attracted by rural

tourism, which is developed at a smaller scale than mass tourism. Because of

tourist’s inclination towards novelty, culture, history, adventure, heritage and

interaction with local people, the policy makers are now aware of and anxious

to develop. Rural tourism is a new trend in tourism since it satisfies the current

needs of the tourists that are unhappy with mass tourism. It constitutes an

alternative to traditional mass tourism.

3

In the 10th five year plan (2003-2007), the government of India planned

to develop 39 rural tourism sites with the UNDP (United Nations Development

Programme) under the innovative Endogenous Tourism Project, focusing on the

rural tourism experience and based on rural art and craft skills, cultural and

natural heritage. The development of strong platform around the concept of

rural tourism is definitely useful for a country like India, where almost 74% of

the population sites in its 7 million villages (Ministry of Tourism, Government

of India). Each village has its own distinctive performing arts and handicrafts,

the customs and traditions, colorful festivals, cuisine as well as different

cultures and historical heritage. In 2004, the government of India has identified

31 villages across the country as rural tourist spots. Among these, Karaikudi in

Sivaganga district and Kazhugumalai in Thoothugudi district are the two rural

villages located in Tamilnadu.

Tamil Nadu is the top state in attracting the maximum number of foreign

tourists in India. In the year 2008, 646.58 lakhs tourists visited Tamil Nadu.

During the year 2009, the tourist arrival was 804.07 lakhs. When compared the

tourist arrivals for the above two years, it has recorded an increase of 157.49

lakhs in the year 2009. (Tamilnadu Tourism, policy note 2010-2011). Against

the background of the solid economic development, potential of international

tourism, UN WTO recommends the participation of local communities and

other stakeholders in Tourism development.

The basic concept of rural tourism is to benefit the local community

through entrepreneurial opportunities, income generation, employment

opportunities, diversify the economy providing a stable base for the local

community, conservation and development of rural arts and crafts, investment

4

for infrastructure development and preservation of the environment and

heritage, discourage the out migration of youth (Gannon, 1994; Greffe, 1994;

Opperman, 1996; Riberio & Marques, 2002; MacDonald & Jolliffe, 2003; Liu,

2006). Liu (2006) contemplates “the promotion of rural tourism is a derivative

of political will, because of the perceived need to reduce disparities between

urban and rural areas.”

The scope of this research is to find and examine the factors that may

affect Karaikudi’s stakeholders’ (Government authorities -tourism related and

non-tourism related, Businesses- tourism related and non-tourism related, local

community(residents), faculty and students and Tourists) attitudes and

perceptions, community participation and in turn support for competitive

destination strategies.

1.1 RESEARCH BACKGROUND

Rural areas across the developed world have encountered economic

decline due to trends of industrialization and urbanization (Lane, 1994).

Increasingly in the 1990s there has been a growth of new types of tourists in

rural spaces, with behavior patterns clearly different from the homecoming

motivation of traditional rural tourism (Perales, 2002). Rural tourism is

increasingly being used as a development strategy to improve the social and

economic well being of rural areas. Rural tourism includes a huge range of

activities, natural or manmade attractions, crafts and heritage, amenities and

facilities, transportation, marketing and information systems (Sharpley 2004).

5

The damaging effects of the declining economy have persuaded

governments to recognize these problems and tourism has been presented as a

catalyst to revitalize disadvantaged rural areas (Riberio & Marques, 2002).

Tourism often represents a means of generating revenue and increasing

employment opportunities.

For rural tourism to be successful, collaboration needs to exist amongst

entrepreneurs (Wilson et al., 2001). Useful integrated approaches to rural

studies include acknowledging the importance of locally controlled agendas to

reach centralization, awareness of the benefits for shared ideas and funding

developments, and creating appropriate tourism plans for rural areas

(MacDonald & Jolliffe, 2003). There are numerous challenges when attempting

rural tourism development: the total product package must be sufficient;

significant investment may be required; there is the adoption to a service role;

the quality of products and services and the availability of skills and resources

for effective marketing (Sharpley, 2000). Tourism development requires

attractions, promotion, infrastructure and services and hospitality (Wilson et al.,

2001).

The tourism plan has a strong marketing focus and gives little attention

to local community values and the social, cultural and environmental effects of

tourism. Understanding destination resident’s attitudes and perceptions towards

tourism development and the factors that may influence their reactions is

essential in achieving a host community's support for tourism development.

Therefore, many researchers have been extensively paid attention towards

residents' reactions towards tourism development. (Ap, 1992, Akis et al.,1996;

6

Perdue et al., 1990., Long et al., 1990, Liu et al., 1987, Lankford, 1994, Milman

& Pizam, 1988, Yoon et al., 2001, Liu, 2006, Vargane,2010)

Various literatures has identified the major impacts of tourism on

governments and host communities to be economic, social, cultural,

environmental, and political (Brunt & Courtney, 1999; Davis et al,1988; Hall,

2004; Lieu et al., 1987;Perdue et al., 1987;Yooshik Yoon et al., 2001, Telfer &

Sharpley, 2008). The authors go on to state that “the overall outcome of the

impacts will influence the contribution of tourism to development” (Telfer &

sharpley 2008).The research by Yooshik Yoon et al., (2001) shows that

community opposition against tourism will be based on perceived negative

environmental and social impacts of tourism development.

During the preparation of the Karaikudi Structure Plan, local residents

have been provided with an opportunity to give their comment and suggestion.

Nevertheless, based on his study, Din (1993) questioned the effectiveness of the

public participation process during, since local residents can only participate

without influence the decision making-process. Mohd Saad (1998) stated that

government administrator has made most of the decisions without public

consultation. Due to that, most of issues related to tourism planning and

development failed to address the need of local residents (Din 1993, 1997)

Therefore, Din (1993) suggested that local residents should be given greater

chances to voice their opinions or ideas, despite of shortcomings in

implementation approach and the lack of their understanding. Local residents

need to be informed of tourism development since the lack of knowledge of

tourism might result in the low level of awareness in the participation process

and could contribute to negative perceptions. One of the main strategies to

7

improve the living standard of the rural population, in the context of rural

tourism development, is the promotion of community enterprise. It is a

collective activity initiated by the community themselves to raise socio-

economic standards, improve their environment and subsequently uplift their

quality of life. Based on the concept of self-help, mutual help and common

ownership, the community enterprise encourages the participation of the local

community in conceptualizing their development needs and in the decision

making over control of scarce economic resources.

By summation, the tourism literature suggests that the support for

destination competitiveness can be enhanced by proper linkages between

tourism development impacts and community stakeholders’ participation.

1.2 RESEARCH PROBLEM

In recent study on tourism, researchers have introduced concepts and

relevant models about tourism destination competitiveness and focused on how

effectively and efficiently destination competitiveness can be improved to

respond to escalating market competition (Crouch & Ritchie, 1999; Hassan,

2000; Thomas & Long,2000).They have also discussed that creating or

integrating value-added destination products and services enhances tourism

attractiveness. The most common evaluation method of tourism attractiveness

is from visitors’ or tourists’ perspectives. (Formica, 2000; Milman & Pizam,

1995) argued that this method is somewhat limited due to the short period of

visiting time, and a limited knowledge of or familiarity with attractions existing

in a given region. Liu (1988) and Formica (2000) suggested that rather than

using visitors’ perspectives, the use of tourism experts such as tourism

8

stakeholders have potential results and benefits. Their solid knowledge and

experiences of the entire portfolio of existing tourism resources and attractions

is useful in evaluating destination competitiveness. Although a number of

studies have addressed concepts and relevant models concerning destination

competitiveness, no empirical study has developed an integrative model

capable of investigating the destination competitiveness of an area by

examining the structural relationships among tourism stakeholders’ beliefs and

attitudes toward tourism, their development preferences for tourism

attractions/resources, and their support of enhancement strategies for

destination competitiveness.

The bottom-up or community approach (Keogh, 1990) which focuses on

participation of the local community in the decision-making and

implementation processes is noticed less frequently. Managing and marketing

the tourism destinations is very difficult, due to the complexities and diversity

of the relationships between local stakeholders (e.g. government organisations,

residents, businesses – tourism and non-tourism, tourism employees, tourism

faculty and students) involved in the development and production of tourism

products (Sautter & Leisen, 1999). Development initiatives in a community

should take into account the interests of all stakeholder groups (Ioannides,

1995; Markwick, 2000; Vincent & Thompson, 2002).Hence, strategies adopted

for planning and development of destination tourism strategies includes the

desire of all those who can influence the development of strategies to ensure

their support for the enhancement of the destination’s competitive strategies.

9

Stakeholders also have different attitudes and perceptions in regard to

tourism development impacts, attachment to a particular place and level of

empowerment, and their level of involvement in planning decision- making.

Stakeholders’ experiences and knowledge could help in enhancing the process

of evaluating the destination’s possessed competitive resources and attractions.

Of particular relevance are their perceptions, attitudes and behaviours about the

influencing factors on the tourism planning and development process regarding

tourism impacts (economic, social, cultural, political, and environmental),

perceived power and community satisfaction. The above factors have received

little attention in the past (Hall, 2000). This study investigates the

interrelationships between these constructs and the favourable competitive

strategies stakeholders are willing to support.

The data were collected from Karaikudi’s tourism stakeholders such as

government authorities (tourism related and non-tourism related), businesses

(tourism related and non-tourism related), residents, tourism faculty and

students, and tourists. The main objective was to examine their perceptions and

opinions about the impacts of tourism development, and further to determine

their willingness to support the most appropriate development strategies of

competitiveness.

There is only a little empirical research on rural destination

competitiveness, especially from the perception of public, private and local

tourism organisations’ stakeholders (Dredge, 2006; Yoon, 2002). Further, there

is little literature about the concepts of power and empowerment related to

tourism development (Hall, 2000; Reid, 2004). This study attempted to close

these gaps by creating and testing a model based on previous research work in

10

the field to deal with the above-mentioned research problem. In investigating

the research problem, a number of hypotheses were developed. These

hypotheses resulted from the review of the extant tourism planning,

development and management literature.

1.3 THE CONCEPTUAL FRAMEWORK AND HYPOTHESIS

Figure 1.1 The initial conceptual framework for Rural Tourism Support

Source: Developed for this research with parts from Jurowski et al. (1997) and Yoon (2002)

TourismDevelopmentImpacts

RuralTourismSupport

Econom

Socio-cul

Environ

mental

Political

+H2

Communityparticipation

+H1 +H3

11

1.4 RESEARCH OBJECTIVES AND HYPOTHESES

1.4.1 Primary objectives of the study

1. To make a contribution to under-researched areas in the academic literature

related to tourism development impacts, community participation, and

stakeholder support for rural tourism.

2. Developing a theoretical structural model depicting the interrelationships

between (1) tourism development impacts, (2) community participation

(stakeholders’ perceived power) and (3) support for tourism destination.

3. Then, empirically testing the constructed model on a developing country

(India) domain, which illustrates the concept of destination competitiveness

from a national developing country perspective.

1.4.2 Primary Hypotheses

H1: There is a relationship between tourism development impacts (economic,

social-cultural, environmental and political,) and the community stakeholders’

participation.


social-cultural, environmental and political,) and the support for rural

destination competitive strategies.

H3: There is a relationship between community participation and the support

for rural destination competitive strategies.

H4: There is a relationship between economic impacts and tourism

development impacts

12

H5: There is a relationship between socio-cultural impact and tourism

development impacts.

H6: There is a relationship between political impacts and tourism development

impacts.

1.4.3 Secondary objectives of this study

1) To identify the dimensions of tourism development impacts of rural tourism.

2) To conduct an exploratory examination how demographic characteristics affectcommunity participation in tourism development

3) To examine how demographic characteristics affect community satisfaction.

4) To document whether support for tourism differed depending on socio-demographic variables.

5) To find the effect of economic impact, socio-cultural impact, environmentalimpact and political impact on tourism development.

6) To find the impact of tourism development and community participation ontourism support

1.4.4 Sub hypotheses

H7: There is no significant difference between male and female with respect to

community participation, tourism support and overall community satisfaction in

tourism development.

H8: There is no significant difference between tourism related and non-tourism

related business with respect to tourism support.

H9: There is no significant difference between closer to the destination or far

away with respect to tourism support.

13

H10: There is no significant difference among age group of the community

people with respect to community participation in tourism development

H11: There is no significant difference among occupation of the community

people with respect to community participation.

H12: There is no significant difference among marital status of the community


H13: There is no significant difference among length of residency of the

community people with respect to community participation.

H14: There is no significant difference between age group of the community

people with respect to overall community satisfaction


community people with respect to community satisfaction.


people with respect to tourism support strategies

H17: There is no significant difference among occupation of the people with

respect to tourism support strategies.

H18: There is no significant difference among education qualification of the

people with respect to tourism support strategies.

H19: There is no significant difference between length of residency with


H20: There is no association between years of residency and support for

tourism

14

1.5 THEORETICAL BACKGROUND

Social Exchange Theory have been utilized by most of the researchers in

their study, related to relationships between different stakeholders in

destination development and residents’ attitudes and perceptions, which has

been considered the appropriate framework to develop an understanding of

residents’ perceptions and attitudes (Ap, 1992; Perdue et al., 1990).

Ap (1990) in his Social Exchange Theory suggests that when an

exchange of resources between residents and tourism is high and balanced,

tourism impacts are viewed positively by residents and vice versa. Perdue et al.

(1990) briefly mentioned that social exchange theory is a basis for investigating

residents’ attitudes about tourism. They concluded that support for additional

development was positively related in the case of people who perceived

positive impacts from tourism, and negatively correlated in the case of people

who perceived negative impacts from tourism.

According to Yoon et al. (2000), who studied residents’ attitudes and

support for tourism development by using a structural model, local residents are

likely to participate in exchange (support tourism development) as long as the

perceived benefits of tourism exceed the perceived costs of tourism. Since

tourism stakeholders have been considered as important key players or

components that influence the success or failure of tourism in a region, their

participation and involvement should be considered in tourism planning and

development. Thus, social exchange theory provides a theoretical foundation

for identifying tourism stakeholders’ perceptions of the benefits and costs of

tourism.

15

1.6 RESEARCH METHODOLOGY

The study is explanatory and descriptive in nature. Both quantitative and

qualitative methodologies are applied to investigate the relationships between

different constructs proposed in Figure 1.1. The research study used survey

questionnaire quantitatively and focus groups qualitatively. The sample size

taken was 320.Convenience and quota sampling methods were adapted to

collect quantitative data from different tourism stakeholders across various

villages around Karaikudi. The survey instrument was developed by the

researcher to measure all constructs. These measurement scales were pre-tested

at different stages to establish validity and reliability. The data was then

analysed using structural equation modeling (SEM) with AMOS 21. The

statistical analyses were done using SPSS 16.

1.7 KEY FINDINGS AND CONTRIBUTIONS OF THE RESEARCH

The findings and contributions of this research are discussed from the

perspectives of theoretical and methodological contributions and practical

implications.

The results indicated the impacts of economic, socio cultural and

political effects, community participation and their support for destination

competitive strategies. This finding substantiates the necessity for involving the

stakeholders in community decision making process to achieve sustainability

and enhance destination competitiveness. In addition, the research demonstrates

some statistical significance between tourism development impacts people may

experience and their emotional and functional attachment to their communities,

16

and their desire for more empowerment and involvement in tourism benefits

and the decision-making process. These relationships may lead to people’s

continuous support for future tourism development in the community. With

regard to the relationship between tourism development impacts and

community participation, the study demonstrates a positive relationship

between the two constructs. The study also detected a negative relationship

between tourism development impacts and tourism support. This is an

indication of people’s dissatisfaction about the benefits they receive from

tourism development. Further, the study’s outcomes did not support the

existence of environmental impacts of tourism development in karaikudi.

Finally, the government’s potential role in tourism planning and development

was not supported by destination stakeholders’ respondents in this study, which

contradicts the findings of existing literature.

This study fills the various gaps in the tourism literature that specifically

dealt with the relationship between stakeholders’ attitudes and support fortourism development, stakeholders’ participation, and destinationcompetitiveness. The study advances the tourism literature by introducing

conceptual framework (model) explaining the relationship between tourism

development impacts, community participation and support for tourism

destination competitiveness from the stakeholders perspective. This conceptual

model will contribute new knowledge to the area of rural tourism research. This

study supported the majority of the hypothesized relationships.

This study included a wide array of stakeholders in the participation

process has not been comprehensive in tourism research, this study calls for a

broader list of tourism stakeholders to be included in the consultation process.

17

Social exchange theory relating to people’s perceptions and attitudes is

widely used in tourism research, and stakeholder theory has mainly been used

in management and less used in tourism. This study tried to combine the two

theories in explaining the role of socio-economic costs/benefits and

stakeholders’ roles in tourism planning and development.

This research used the structural equation modeling (SEM) method and

AMOS 21 software in data analysis. There is little tourism literature using this

method in rural tourism research. Thus, this study contributes by expanding the

use of SEM in analyzing empirical data in the rural tourism discipline in the

rigorous testing of relationships between key constructs. This study is one of few

recent studies that have attempted to explain the relationships between different

perceived tourism development impacts, community participation and support

for destination tourism planning, development and competitive strategies.

1.8 FUNCTIONAL DEFINITIONS

Destination: Destinations are places that attract visitors for a temporary stay,

and range from continents to countries to states and cities to villages to purpose

built resort areas [Pike, 2004].

Tourism development impacts: Result from a complex process of

interchanges between tourists, host communities, and destinations (Mathieson

& Wall, 1982).

Tourism stakeholders: Persons or groups who can affect and be affected by

the tourism business within a particular market or community and who have

interest in the planning process, delivery and outcomes of the tourism

18

business.(Donaldson & Preston, 1995; Sautter & Leisen, 1999).The examples

of tourism stakeholders are Government tourism authorities, local tourism

agencies, non-government organizations, community people, tourism related

associations and councils, tourism planning and development companies,

Business people, tourism related faculty and professionals, visiting and

information centers.

Competitiveness: Combination of assets and processes where assets are

inherited (e.g. natural resources) or created (e.g. infrastructure), and processes

transform assets to economic results (Crouch & Ritchie, 1999).

Tourism destination competitiveness: Destination’s ability to create value

and thus increasing national wealth by managing assets and processes,

attractiveness, and proximity, and by integrating these relationships into an

economic and social model (Ritchie & Crouch, 2000).

Community participation: The degree of ability of the public to participate in

community- based tourism planning decision-making for the benefit of tourism

development (Hall, 2000; Jamal & Getz, 1995).

1.9 TOURISM IN INDIA

1.9.1 Introduction

The second highest revenue-generating industry in the world is a tourism

industry next to the oil industry. Tourism is one of the leading global industries

(11% of global GDP) of the world. The World Tourism Organization (WTO)

estimates that there will be 1.6 billion tourists in the world, representing 21% of

19

world population. Tourism industry contributes high priority goals of

developing country’s income, employment, foreign exchange earnings (Primary

source of foreign exchange earnings in 46 of 49 developing countries). Tourism

also supports preservation of monuments and heritage properties and helps the

survival of art forms, crafts and culture. Now, tourism is one of the largest

service industries in India. Tourism contribution to the national Gross Domestic

Product (GDP) is 6.23 per cent and for the total employment in India is 8.78 per

cent in 2010.

1.9.2 India Tourism Statistics at a Glance 2011

In 2011, the number of Foreign Tourist Arrivals (FTAs) in India has

been increased to 6.31 million as compared to 5.78 million in 2010. The growth

rate in FTAs during 2011 over 2010 was 9.2% as compared to 11.8% during

2010 over 2009. The growth rate of 9.2% in 2011 for India was better than

growth rate of 5% for the international tourist arrivals in 2010.The share of

India in international tourist arrivals in 2011 was 0.64%, while being 0.61% in

2010. However, India's rank in the world improved to 38 in 2011 from 42 in

2010. (www.tourism.gov.in)

India accounted for 2.9% of the tourist arrivals in Asia Pacific Region in

2011, occupying 9th rank in the region. About 92.0% of the FTAs entered India

through air routes followed by 7.2% by land routes and 0.8% by sea routes.

Delhi and Mumbai airports accounted for about 55.5% of the total FTAs in

India. Fifteen major countries contributing significantly by higher number of

FTAs in India in 2011 were USA, UK, Bangladesh, Sri Lanka, Canada,

Germany, France, Malaysia, Japan, Australia, Russian Fed., China(Main),

20

Singapore, Nepal and Republic of Korea. These 15 countries accounted for

about 71.43% of total FTAs in India in 2011.(www.tourism.gov.in)

The top 10 States in terms of foreign tourist visits during 2011 were

mostly the same as in 2010, with marginal changes in relative ranks of States

except that the State Karnataka has replaced Goa. Figure 1.2 shows the

percentage share of Top 10 states for foreign tourist arrivals in India in 2011.

(Ministry of tourism, GOI)

Tourism sector continues to play an important role as a foreign exchange

earner for the country. In 2011, foreign exchange earnings (FEE) from the

tourism were US$ 16.56 billion as compared to US$ 14.19 billion in 2010,

registering a growth of 16.7%. Number of domestic tourist visits in India during

2011 was 850.86 million as compared to 747.70 million in 2010, with a growth

rate of 13.8 %. Number of Indian national departures from India during 2011

was 13.99 million as compared to 12.99 million in 2010, registering a growth

rate of 7.7%. (www.tourism.gov.in).

The top 10 States in terms of domestic tourist visits during 2011 were

the same as in 2010. The following figure 1.3 shows the percentage share of top

10 States in terms of domestic tourist visits in 2011.

21

Figure 1.2 Percentage shares of top 10 states in foreign tourist visits to

states (2011)

Source: Secondary data- India Tourism statistics 2011 at a glance

Figure 1.3 Percentage shares of top 10 States in domestic tourist visits

(2011)


22

Table 1.1 Shows the Foreign Tourist arrivals (FTAs) in India, from 1997 to

2011 (India tourism statistics at a glance 2010, Incredible India)

Table 1.1: Foreign Tourist arrivals (FTAs) in India, from 1997 to 2011


Table 1.1 presents the statistics foreign tourist visits to various States

during the years 1997 to 2011. The foreign tourist visits have been increasing

over the years, though there was a decline in the years 1998, 2001, 2002 and

2009. The foreign tourist visits to all States during 1991 to 2011 witnessed a

compound annual growth rate CAGR of 10.07%. During 2011, the visits by

foreign tourists registered a growth of 8.85% over 2010.

23

1.9.3 Rural Tourism in India

Rural tourism is a subset of tourism that would consist of wide range

things such as farm/agricultural tourism, cultural tourism, nature tourism,

adventure tourism, and eco-tourism. Any form of tourism that showcases the

rural life, art, culture and heritage at rural locations, thereby benefiting the local

community economically and socially as well as enabling interaction between

the tourists and the locals for a more enriching tourism experience can be

termed as rural tourism. Rural tourism is essentially an activity that takes place

in the countryside. Rural tourism creates experiences for tourist who enjoys

locations that are sparsely populated, it is predominantly in natural

environment, and it meshes with seasonality and local events and is based on

preservation of culture, heritage and traditions. Rural tourism has become quite

admired since the last few years. In the 10th five year plan (2003-2007),

Ministry of Tourism, Government of India planned to develop 39 rural tourism

sites with the UNDP (United Nations Development Programme) under the

innovative endogenous tourism project, focusing on the rural tourism

experience and the rural art and craft skills, cultural and natural heritage.

Rural tourism is a vital means of developing employment and income

and can assist social and economic development of rural communities

(Sharpley, 2001). The development of strong platform around the concept of

rural tourism is definitely useful for a country like India, where almost 74% of

the population sites in its 7 million villages (Ministry of Tourism, Government

of India). Each village has its own distinctive performing arts and handicrafts,

the customs and traditions, colorful festivals, cuisine as well as different

cultures and historical heritage. The project is being implemented at 31 rural

24

locations in 20 states with community participation through NGO or Panchayat

Partners, District Collectors as focal points and specialized stakeholders. The

rural tourism sites in India and their Unique Selling Proposition (USP) is

presented in Appendix-2

Some Rural tourism destinations in India.

Pochampalli (Nalgonda District, Andhra Pradesh

Raghurajpur (Puri District, Orissa):

Hodka (Kachchh District, Gujarat):

Pranpur (Ashok Nagar District, Madhya Pradesh):

Aranmula (Pathanamthitta District, Kerala):

Lachen (North District, Sikkim):

Nagarnar (Bastar District, Chattisgarh):

Karaikudi (Sivaganga District, Tamil Nadu):

Mana (Chamoli District, Uttaranchal):

1.9.4 Tourism in Tamil Nadu

The State of Tamil Nadu, situated in the southern part of the Indian

Peninsula has over 20 centuries of cultural heritage and historic significance. It

has the potential to become a preferred tourism destination world-wide. With an

area of 130,058 sq. km and a population of over 70 million (Figure 1.4), Tamil

Nadu is the eleventh largest populated and the third most industrialized state in

India. It possess successful tourism infrastructure in its Western border,

Karnataka, and also enjoys a long unbroken coastline in the Bay of Bengal.

25

Figure 1.4: Census 2011 Highlights for Tamilnadu

The ratio of rural to urban population has nearly reached parity and

stands, in percentage terms, at 51.6 in villages and 48.4 in cities. The

population distribution in rural areas stood at 3.72 crores, while urban

population was 3.49. Of the total increase of 9.7 million people in the last

decade, the contribution of rural areas was 2.3 million, whereas the contribution

of urban areas was 7.4 million. (www.tourism.gov.in).

Tamil Nadu is a wonderful tourist place for many reasons. First, the state

is meant for its glorious culture and history. Tamil Nadu has one of the oldest

civilizations of the world. It is the home of Dravidian art and culture,

characterized by its distinctive music and dances, its amazingly decorated

temples with their soaring towers and its plentiful and colorful festivals. There

is at least one festival per month, celebrating various events: summer, mangos,

teas, Hindu gods, dances, etc. Tamil Nadu is referred as the “Land of Temples”

26

because there are more than 30,000 temples in this state. Secondly, its natural

beauty in villages is very attractive to tourists. Next only to the pilgrimage and

heritage locations in Tamil Nadu comes the scenic beauty of nature in and

around the state in the form of forests, wildlife sanctuaries, hill stations and the

long bio-diverse coastline. These locations provide immense opportunities for

sightseeing, pleasure and leisure, to the visitors of various categories including

adventure tourists.

The number of tourists arriving in Tamil Nadu has increased 2½ times

since 1990. As per 2001 statistics, 245.8 lakh tourists arrived in the state of

which 238.1 lakh were domestic tourists and 7.7 lakh, foreign tourists. Where

the years 1991 and 1992 experienced an unprecedented growth of 18.7% and

18.8% respectively, years 1997, 1999, and 2001 saw steep declines in growth

rate 4.0%, 3.8%, and 3.4% respectively. (www.tamiltourism.org). Chennai,

Madurai, Ooty, Kodaikanal, Rameshwaram, and Kanyakumari have attracted

maximum tourists of all the tourist places in Tamil Nadu over the past several

years. A substantial number of pilgrims visiting Tamil Nadu has consistently

grown over the years. Pilgrim tourists make 30% of the total tourists arriving in

the state; places of scenic beauty attract 40%; rest is shared by other tourism

categories (heritage, adventure, festival, and leisure).

27

Table 1.2.: Tourist Visit in Tamilnadu in lakhs

State 2009(in lakhs)

Domestic Foreign

2010(in lakhs)

Domestic Foreign

2011(in lakhs)

Domestic Foreign

Rank

Tamilnadu 1157.558 23.691 1191.882 28.045 1375.130 33.739 III

Source: Indian Tourism Statistics-2010

The growth rate of domestic tourist arrivals is 6.0%. At this rate, the domestic

tourist arrival in 2022 shall be 809.4 lakhs, under the present setup and scene of

tourist activities, destinations and infrastructure. The foreign tourist arrival

(FTAs) is projected at 5.0%. There shall be 21.4 lakhs foreign tourist in 2022

given the present situation. In 2011, Tamilnadu ranks third in both domestic &

Foreign Tourist Arrivals (FTAs). Uttar Pradesh ranks first and AndraPradesh

ranks second in both domestic & Foreign Tourist Arrivals (FTAs). In 2011,

Tamilnadu ranks second in India in FTA and Maharastra stands first with

48.154 lakhs in 2011. Table 1.2 shows the visit of both domestic and foreign

tourist in Tamilnadu. The percentage shares of top 5 States were Maharashtra

24.7 per cent, Tamil Nadu 17.3 per cent, Delhi 11.1 per cent, Uttar Pradesh 9.7

per cent and Rajasthan 6.9 per cent. (www.tourism.gov.in)

Tourism is highly labour intensive as compared to any other industry.

According to an Economic and Social Commission for Asia and the Pacific

(ESCAP) report, 1.2 international tourist visits provide employment to one

person, whereas 17 domestic tourists generate employment for one person. In

addition, about 25,000 man-years of jobs will be created due to construction

activity. In the year 2022, there may be an additional inflow of 824.2 lakh

domestic tourists and 31.3 lakh foreign tourists in the state. The direct

employment on account of domestic and foreign tourists shall be 48.4 lakh and

28

40.4 lakh respectively. The indirect employment is estimated at 120.7 lakh. The

Government of Tamil Nadu has set ambitious goals for the tourism sector. It

predicts a tourist growth rate of 10-12 percent in lieu of the current 7-9 percent,

vows to increase the length of stay by at least 2-3 days and build good

infrastructural facilities at tourist spots. (www.incredibleindia.org)

1.9.5 Rural Tourism in Tamilnadu

Rural Tourism is a new concept in the field of tourism. The villages in

Tamil Nadu are a treasure of unadulterated culture, fine arts, martial arts,

handicrafts, herbal cures etc. The foreign tourists show keen interest in watching

the day-to-day activities of Indian villages. So Rural Tourism has a good chance of

development and popularity among domestic and foreign tourists. This shall help

in popularizing the rich cultural heritage of Tamil Nadu.

In 2004, the government of India has identified 31 villages across the

country as rural tourist spots. Among these, Karaikudi in Sivaganga district and

Kazhugumalai in Thoothugudi district are the two rural villages located in

Tamilnadu. Tamil Nadu is one of the top states which attract maximum number of

foreign tourists in India. During the year 2008, 646.58 lakhs tourists spent their

time in Tamil Nadu. The arrival of the tourist was 804.07 lakhs, during the year

2009. It has been found that the tourist arrival has an increase of 157.49 lakhs in

2009 when compared to the previous year. (Tamilnadu Tourism, policy note 2010-

2011). The tourist arrival was 926.28 lakhs and 987.75 lakhs for 2010 and 2011

respectively. (Tamilnadu Tourism, policy note 2011-2012, 2012-2013). Besides

the background of the economic development, potential of international tourism,

UN WTO recommends the participation of local communities and other

stakeholders in Tourism development. (www.tamiltourism.org)

29

The fundamental concept of rural tourism is to benefit the local

community by creating entrepreneurial opportunities, income generation,

employment opportunities, preservation and development of rural arts and

crafts, investment for infrastructure development and preservation of the

environment and heritage.

Development of “Rural Tourism” is undertaken with the assistance of

Government of India and United Nations Development Programme. Government

of India funds hardware infrastructure) component; United Nations Development

Programme funds software (Capacity Building) component and it is

implemented with the assistance of local NGOs. 18 Rural Tourism Projects have

been funded with a total outlay of Rs.6.21 Crores. Rural Tourism enables

exposure of children brought up in urban areas to rural life.

Rural Tourism spots in Tamilnadu

Karaikudi (Sivaganga district)

Kazhugumalai (Thoothukudi District)

Thadiyankudisai(Dindigul District),

Kurangani (Theni District),

30

1.9.6 Karaikudi’s destination competitiveness

Figure1.5: Karaikudi, Sivaganga District, Tamilnadu Map

:

Source: www.karaikudi.com/locationmap.html

This research focuses on the Karaikudi, Sivaganga District, Tamilnadu

(Figure 1.5). As per 2011 India census, Karaikudi had a population of 106,793

(Males 53,425 and Females 53,368). Karaikudi and surrounding areas are

generally referred to as "Chettinadu". Chettinadu literally 'Chetti land' in Tamil,

is a collection of 76 villages/towns. Karaikudi have experienced tremendous

development in public infrastructure and tourism facilities when the place was

declared as a Rural Tourism spot by Ministry of Tourism, Government of India.

Many construction projects in Karaikudi have only one purpose: to

31

accommodate rural tourism development. To guide the progress of rural

tourism development in Karaikudi, the government prepared the Structure Plan,

which outlined the government policies and strategy for socio-economic and

physical planning and development for rural tourism.

Karaikudi is the bastion of Chettinad culture, captivating the visitor with

spectacular mansions, refined woodcarving and tangy Chettinad cuisine. The

Chettiar community, torch-bearers of modern banking, has now laid open

several of their magnificent homes, offering unique home-stay insights to the

venturing Chettinad spirit of enterprise. The visitor is welcomed to the family’s

history, the quest for success and the drive that has yielded these grandiose

buildings, their egg plastering technique leading on that magnificence to fine

silver handicrafts, woven saris, palm leaf baskets and unique hand-made

Athangudi tiles.

Ten villages and towns of Chettinad had been identified for their various

specialties. While Kanadukathan and Pallathur were notified for architecture,

Pillaiyar Patti for heritage temples, Kottaiyur and Karaikudi were noted as

famous for kandangi saris and wood carving. Brass metal work was famous in

Ariyakudi. Silver ornament and stone carving had earned a name for Kandanur

and Sakkottai respectively. Handmade tiles were really attracting tourists at

Athankudi. The focus would be to make the tourists visit all networking areas

and villages to market the area wise products of Chettinad. Self-help groups

were promoted to make use of the advantages of Chettinad tourism.

32

For development of Chettinad, Sivaganga District a sum of Rs. 50.00

lakhs was sanctioned under rural tourism during 2003-2004. Apart from this,

during 2004-05 Government of India has sanctioned Rs. 20.00 lakhs for rural

tourism project in Chettinad (soft ware components - Government of India

United Nations Development Programme Endogenous tourism project). Under

this scheme, apart from tourism promotion activities, promotion of activity

based self-help groups, skill buildings, linkages etc would be taken up.

1.10 STRUCTURE OF THE THESIS

Chapter 1 – Introduction

This chapter introduces the background of the study and the research

problems upon which the study is based. The research objectives and

hypothesis that are investigated in this study were presented and the

methodology adopted is briefly introduced. The relevant concepts and theories

of support for tourism destination competitiveness are delineated. A description

of the structural model to be tested in this study is presented. Contributions of

the study are discussed. Finally, the functional definitions were provided and

the limitations of the study were identified.

Chapter 2 – Review of Literature

This chapter starts with an extensive review of literature on the basis of

theoretical reviews and research reviews. It provides the summary of

contribution of various researchers to the field of tourism development impacts,

community participation and tourism support, identifies gaps in the literature,

examines various constructs of the research, and develops a theoretical

framework.

33

Chapter 3 – Research Methodology

The research methodology chapter describes in detail about the research

design, sampling design, the development of the survey instrument and scale,

sample size determination, method of data collection, tools used for data

analysis and the total frame work about this research.

Chapter 4 – Data Analysis and Results

This chapter reports the results of the empirical analyses of the proposed

theoretical model that was tested for the hypotheses and introduces the final

structural model for this study. It also reports the outcome of the focus groups

interview.

Chapter 5 – Conclusions and Discussion

This Chapter discusses the findings of the study; the implications and

conclusions of the research are delineated and future research suggestions and

directions based on this study are presented.

34

CHAPTER II

LITERATURE REVIEW

2.1 INTRODUCTION

This chapter reviews the literature of tourism development impacts,

Community participation, and stakeholders’ support for tourism development

and destination competitiveness. It consists of four parts: Rural Tourism

background literature, theoretical background, conceptual framework including

hypotheses and Tourism in India and Tamilnadu. In the first part, relevant

concepts and systematic approaches to tourism development and destination

competitiveness will be reviewed. This section serves as the research

background for the research problem and objectives. The second part provides

the theoretical framework by an introduction to background theories, such as

social exchange theory and stakeholder theory. Third part provides the

necessary background for the field’s research by showing the inter-relationships

between the theoretical background and framework constructs. Finally, an

overview of India’s and Tamilnadu’s historical, economic, political, and

tourism aspects is introduced.

2.2 TOURISM BACKGROUND LITERATURE

2.2.1 Perspectives on Rural Tourism

Rural tourism is an important trend in tourism since it satisfies the

current needs of the tourists that are unhappy with mass tourism. It constitutes

an alternative to traditional mass tourism.

35

Tourism is an economic activity that has often been cited, in relation to

rural economies, as a key strategy for regional development (Cawley &

Gillmor, 2007; Saxena et al., 2007; Fleisher & Falenstein, 2000). Negrusa et al.,

(2007) defines rural tourism as that form of tourism offered by people from

rural areas, with accommodation on small-scale and with the implication of

important components of their rural activities and customs of life. According to

(Roy A. Cook et al., 2007), tourism should be blended with the environment

and the local culture of an area. Tourism should evolve from the area’s natural

and historical/cultural attractions .With regard to principle of ecotourism, high

proportion of local materials should be used to fulfill tourists’ needs, from

construction materials to foodstuffs (Roy A. Cook et al., 2007).

Opperman (1997) argued that rural tourism can be defined as tourism in

a “non-urban territory where human (land related economic) activity is going

on, primarily agriculture. There is a growing consensus as to what actually

constitutes rural development activities which has expanded to include nature

conservation, region-specific products and rural tourism (Van der Ploeg et al.,

2000). Fleisher and Falenstein (2000: 1007) specifically state that “the

promotion of small scale tourism is intuitively perceived as a suitable form of

economic development for rural areas”. Rural spaces are no longer associated

purely with agricultural commodity production but are seen as locations for the

stimulation of new socio-economic activity (Na Gan et al., 2011). Tourism has

many potential benefits for rural areas (Frederick, 1992).

According to the Organization of Economic Co-Operation and

Development (OECD), rural tourism is defined as tourism taking place in the

countryside (Reichel et al., 2000). There are a variety of terms used to describe

36

tourism in rural areas, including farm tourism, agritourism, soft tourism and

even ecotourism (Beeton, 2006).Rural tourism provides employment for local

residents and prevents their immigration to cities (Sarjit S Gill, 2009). Rural

tourism can revitalize the conventional concepts and views on tourism, and

bring in a new dimension in the sustainable development (Sarjit S Gill, 2009).

Rural areas attract tourists because of their mystique and their distinct cultural,

historic, ethnic and geographic characteristics (Edgell & Harbaugh, 1993).

Roads and accommodation infrastructures were cited as the two main barriers

for growing rural tourism development (Sarjit S Gill, 2009). In fact, marketers

who do not promote the unique attributes of their destination may fail to attract

the interest of tourists (Fakeye & Crompton, 1991).

Destinations with strong, positive images are more likely to be chosen in

the travel decision process (Goodrich, 1978; Woodside & Lysonski, 1989).

According to Bontron and Lasnier (1997) rural tourism impact varies greatly

among rural regions and depends on a host of factors including work force

characteristics and seasonality issues. A model of integrated rural tourism,

which took account of the various resources (cultural, social, environmental,

economic), their use, and the role of pertinent stakeholders, was developed to

explore effective methods of promoting tourism as part of a rural development

strategy(Mary Cawley et al., 2008). Set of community-based rural tourism

development indicators can serve as a starting point for devising a set of

indicators at the local and regional level in order to be useful rural tourism

sector manager and administrators (Duk- Byeong Park et al., 2011).Butler et al.

(1998) note economic and social forces operating at the global level are

determining both the nature and form of the rural landscape and how we value

and use it.

37

2.2.1.1 Rural tourism –A multi-faceted activity

Rural tourism is a multi-faceted activity: it is not just farm-based tourism.

It includes farm-based holidays but also comprises special interest nature

holidays and ecotourism, walking, climbing and riding holidays, adventure, sport

and health tourism, hunting and angling, educational travel, arts and heritage

tourism, and, in some areas, ethnic tourism. There is also a large general interest

market for less specialised forms of rural tourism. The major requirement of the

main holiday is the ability to provide peace, quiet and relaxation in rural

surroundings; Because rural areas themselves are multi-faceted and rarely either

static entities or self-contained, and free from urban influence, a working and

reasonably universal definition of the subject is difficult to find. However, in

almost every case rurality is the central and unique selling point in the rural

tourism package. The search for a definition must, therefore, begin with an

understanding of the concept of rurality itself.

The definition given by the European Commission divides the definition of

rural tourism into two trends. The distinction used is the percentage of revenue

benefiting to the local community. The term ‘rural tourism’ is used when the

rural culture is a key component of the product.

Depending on the key activity proposed by this product, the terms ‘nature’,

‘agri’, ‘green’, ‘eco’, etc. are used. A more precise definition of each term can

be given.’ Rural tourism’ is a kind of tourism where the rural culture is a key

component.

38

‘Nature tourism’ is a kind of tourism where the observation and appreciation of

nature is the principal component (World Tourism Organization, 2002).

In ‘green tourism’, the landscape is a key variable and the principal

objective is the integration of the visitor into the local natural and human

environment (Garcia Henche, 2003).

‘Agri-tourism’ is an important part of rural tourism since the aims of

developing rural tourism are often to increase the revenue of farmers. The first

characteristic of ‘agri-tourism’ is that it is the business of farmers. It has to be

related to the agricultural activities and to complement the revenue of farmers

(Garcia Henche, 2003).

‘Sports tourism’ uses the natural environment as a resource and a base for

the practice of a sport activity (Garcia Henche, 2003).

The term ‘eco-tourism’ is used when the priority is to preserve the natural

environment where the activity takes place (Garcia Henche, 2003).

A definition according to Mac Nulty, P., (2002) in WTO Seminar, oriented

towards the alternative that rural tourism represents to mass tourism. It explains

that tourists seek “rural peace”, that rural tourism “is tourism away from areas of

intensive tourism activity” and that “it is engaged in by visitors who wish to

interact with the rural environment and the host community, in a meaningful and

authentic way”.

39

Rural tourism has to be adapted to the needs of the tourist, respond to the

needs of the local communities, be socio-economic and culturally well planned

and environmentally sound. The tourism must offer products that are operated

in harmony with the local environment, community attitudes and culture so that

they become permanent beneficiaries and not the victims of tourism. The basic

cultural identity of these local people should not be adversely affected.

Sustainability also ensures economically sustainable development process in

the efficient management of resources and such management to ensure that the

resource supports the future as well as the present generation.

Thus sustainable rural tourism aims to:

Improve the quality of life of people.

Provide good experience to the tourists

Maintain the quality of environment that is essential for both tourists and

the local community.

A scheme of sustainable development of the region (Figure 2.1)

Figure 2.1 A scheme of sustainable development of the region

Source: [P. Y. Baklanov, 2007, “Model of SD"]

Rural tourism includes a large variety of guest housing ways, activities,

events, festivities, sports and entertainment, and all happen in a typically rural

environment. It is a concept which covers touristic activity organized and led

by rural local people and which generates from a tight contact with the natural

and human environment. The village is something special for urban people:

human dimension, local village life, local arts and crafts, local pub, school, the

church, places that have been marking people’s lives for centuries. Here live

40

craftsmen, marketers, small investors, local actors who make village life easier.

It also represents the cradle of the most beautiful feasts, wedding and

christening customs, or those specific to winter time. The farm, the rural village

and space, taken together or separately, represent the charm of rural tourism

through attractiveness. Rural tourism must be understood as a form of activity

that provides urban dwellers the most adequate conditions of therapy against

stress, created by the uproar of everyday life. This form of tourism is strongly

influenced by psychological factors and mainly addresses nature lovers, those

who know how to use it for the benefit of their own health and mental comfort,

without destroying it.

Major attractive rural events: trades and crafts; peasant clothes, dances

and songs; traditional feasts; peasant architecture and technical equipment;

human communities. Trades and crafts show a great regional diversity. The

way rural people make their lives differ from a climatic type to another. They

are so attractive because the way they are used is different, as well as the tools

that are used, or the final result of human activities. Such trades and crafts are:

Cuisines, farm animals breeding, wood working, hunting and fishing, bee-

breeding, gold and iron working, pottery, spinning, weaving, whitewashing, etc.

According to (Garcia Ramon et al. 1995), tourism would be the 'saver' to

improve the quality of life in the countryside and slow down the rural migration

especially in less developed regions. Tourism would generate additional income

for farm and rural families and create new jobs, lead to the stabilization of the

rural economy, provide support to existing business and services, and

contribute to creating new ones.

41

The shift in government policies was accelerated by the growing

numbers of city people wanting to spend their holidays in the country (Hummel

brunner and Miglbauer, 1994).Scenery, with its mix of agricultural landscapes,

forests, open spaces, and picturesque villages, and the human and cultural

capital of the local communities were and are the main ingredients of the 'rural

idyll' that attracts tourists to rural areas. As a consequence, various forms of

rural tourism: farm, village and agri-tourism began to flourish in rural areas.

Table 2.1A list of contrasting features between urban tourism and rural tourism

Urban Tourism Rural TourismLittle open space Much open spaceSettlements over 10 000 Settlements under 10 000Densely populated Sparsely populatedBuilt environment Natural environmentMany indoor activities Many outdoor activitiesInfrastructure - intensive Infrastructure – weakStrong entertainment/retail base Strong individual activity baseLarge establishments Small establishmentsNationally/Internationally ownedfirms

Locally owned businesses

Much full time involvement intourism

Much part-time involvement intourism

No farm/forestry involvement Some farm/forestry involvementTourism interests self supporting Tourism supports other interestsWorkers may live far from workplace Workers often live close to workplaceRarely influenced by seasonal factors Often influenced by seasonal factorsMany guests Few guestsGuest relationships anonymous Guest relationships personalProfessional management Amateur managementCosmopolitan in atmosphere Local in atmosphereMany modern buildings Many older buildingsDevelopment/growth ethic Conservation/limits to growth ethicGeneral in appeal Specialist appealBroad marketing operation Niche marketing

42

2.2.1.2 Tourism as a tool for local development

If rural tourism can partly be explained by the fact that it represents what

tourists need and want, the importance of rural tourism can also be explained by

the fact that it has been seen by the governments as a way to help rural areas to

develop.

Many researchers (e.g. Hall, Jenkins, 1998, etc) agree to say that tourism

is used to achieve several goals that can be:

- to sustain and create local income, employment and growth,

- to contribute to the costs of providing economic and social infrastructure,

- to encourage the development of other industrial sectors,

- to contribute to local resident amenities and services,

- to contribute to the conservation of environmental and cultural resources.

The main objective of rural tourism development is the increase of

quality of life for local residents through the achievement of social and

economic goals.

The tools of the governments to achieve these goals are framing policy

instruments that can influence the actions of the economic agents by providing

financial incentives for appropriate behavior or disincentives for inappropriate

ones (Hall and Jenkins, 1998).As rural tourism is part of local development, it is

a way to involve every people, not only because he can have a project, but also

“as a member of the local community and potential beneficiary of the expected

collective development” (Thibal, 1988).

According to Keane (2000) “lack of economic diversity is the main

reason for the rural development problem”. Economic diversification brings

43

stability and growth to the community. He insists on the fact that “in many

ways, development is something that occurs because of necessity”. Houee

(1989) has got the same point of view and insists on the fact that initiatives are

coming from the awareness that local community have of the problem. The

strength of rural tourism as a tool for development is that it is based on the

natural and human environment of the countryside. It is based on local

resources. Besides, the development of rural tourism not only leads to the

improvement of the structures for the tourists. Tourism is part of a global

process of improvement of the quality of life, for the tourists as well as for the

residents. In fact, if a territory is more attractive for tourists, it will also be more

attractive for new and current residents.

As a whole, tourism promises 16 potential benefits to rural development.

They are outlined in detail below.

1. Job retention is extremely important in rural areas where employment

decline is often common. Tourism cash flows can assist job retention in

services such as retailing, transport, hospitality and medical care. It can

also provide additional income for farmers, for foresters and Craftsmen.

Job retention helps the viability of small communities.

2. Job creation typically occurs in the hotel and catering trades, but can

also take place in transport, retailing, and in information/heritage

interpretation. Farmhouse accommodation and bed-and-breakfast, hotels

and caravan/campsites

3. Job diversity is encouraged by rural tourism development. Most rural

areas have little job variety outside farming and basic services. Better

job diversity enriches rural society, and helps retain population levels.

44

4. Pluriactivity is the term used when an individual or family carries out

more than one type of job to maintain their income. A part-time farmer

could also offer accommodation, assist the local administration in

service tasks and act as a ski-instructor. It is especially important in the

rural context because of the cultural importance of the family as a unit in

many traditional societies.

5. Service retention is very important in rural areas: rural tourism can

assist in three ways. Visitor information services can be provided by

existing outlets, such as shops, thus increasing income flows if payment

is made for acting as information outlets. Services can also benefit by the

additional customers which visitors provide. Finally, tourism’s

importance to national economies can strengthen the political case for

subsides to help retain services.

6. Farm support is a major issue on all political agendas. Many studies

have shown that farm incomes can be bolstered by rural tourism, through

accommodation enterprises of all kinds, by developing open farms and

other attractions, by increased sales of farm produce, and by increasing

female activity rates through additional off-farm employment. Visitors

bring variety and company to what can be a lonely and limited life style.

7. Forestry is an important activity in many upland and climatically

marginal regions. Rural tourism can assist forestry by diversifying

income sources for forest communities if the special qualities of the

forest environment for recreational use are realized and developed.

8. Landscape conservation has become an increasingly important form of

heritage protection. Landscape is of crucial importance to rural tourism

but, equally, visitor use is vital to the landscape conservation industry.

Visitor use brings political benefits, can bring economic gains, and can

45

provide jobs in maintaining and repairing traditional landscapes worn by

recreational activities.

9. Smaller settlements in the countryside have always been at greater risk

of losing viability because they are unable to support the many services

which now require larger threshold populations to support them. Rural

tourism can assist these smaller settlements to survive, because smaller

places have a special attraction for visitors. Careful management of this

process is required.

10. Rural arts and crafts have a special place in the cultural heritage of

regions and nations. Many commentators have noted that tourism can

assist arts and crafts, both by recognising their importance, and by

purchasing craft products. Income flows from these activities are well

documented. Support between the arts and tourism can be a two-way

process. Many communities now use arts and crafts festivals as a

marketing mechanism to encourage visitors to come to their areas.

11. Cultural provision has always been restricted in rural areas. The lack of

major facilities such as theatre, opera, music and galleries has been one of

the many factors encouraging rural depopulation. The festivals and other

events have enabled rural areas to broaden their cultural provision, buying

in artists and ensembles and supporting those purchases by ticket sales to

visitors.

12. Nature conservation, like landscape conservation, is a stated goal of

most modern governments. It is, however, an expensive process. Rural

tourism can valorize nature conservation in a monetary sense. Many

estimates have been made of the value of nature to tourism

13. The historic built environment can benefit from rural tourism in two

ways. Many historic properties now charge for admission in order to

46

maintain their fabrics and surrounding gardens and parklands. Secondly,

there are important buildings from the past which have become redundant.

The tourist industry can usually use these redundant buildings profitably

and imaginatively: they can become attractions in their own right.

14. Environmental improvements such as village paving and traffic

regulation schemes, sewage and litter disposal can be assisted by tourism

revenues and political pressures from tourism authorities. These help

develop pride of place, important in retaining existing population and

businesses, and in attracting new enterprises and families.

15. The role of women within the rural community was, in the past, a

restricted one. Farming, forestry and mining were very much male

occupations. Alternative jobs for women were few. Women were rarely

involved in local politics. The widespread liberation of women, coupled

with the possibilities which rural tourism offers, have together done much

in many areas to release the under-utilized talents and energies of the

female half of the population. The development of the role of women

could do much for the economic and social well-being of many rural

areas.

16. New ideas and initiatives will be essential if rural communities are to

prosper into the twenty-first century. Efforts to support agriculture,

forestry and service provision by state subsidies have done much to

develop a culture of dependency within the countryside. The new

challenges and the fiercely competitive nature of the tourism market

could do much to encourage enterprise and new methods. There is also

evidence that rural tourism can act as a catalyst to bring new businesses

of many kinds into rural communities.

47

2.2.2 Tourism and its Systematic approaches

A number of systematic approaches have been proposed in the tourism

literature to understand tourism components, and their functioning or

interactive roles (Leiper, 1979, 1990; Pearce, 1995; Mill & Morrison, 1995;

Witt & Moutinho, 1994). The researchers suggested two approaches: the origin

destination tourism system and the functioning tourism system in explaining

tourism as a system. In the origin-destination tourism system, tourism consists

of two types of region: an origin, is the region or country generating the

tourists, and a destination, is the locations visited by tourists. (Witt &

Montinho, 1994). An origin represents the demand-side of the tourism system

and a destination represents the supply-side of tourism, in that a certain region

or country may have specific powers of attraction to entice visitors (Uysal,

1998).

One of the core components of the regional and international tourism

system is the tourist destination. It comprises of multifaceted elements such as

natural resources (e.g. climate, water and landscape), authentic human

resources (e.g. culture and history) and industrial resources (e.g. museums,

theme parks, facilities, infrastructure and other physical attractions) (Butler

1999).

Murphy (1985) perceived tourist destinations as a marketplace where

supply and demand characteristics push for attention and consumption,

suggesting that the tourism resources base is a combination of physical and

human resources. Meanwhile, Hu and Ritchie (1993) conceptualized the tourist

destinations as “a package of tourism facilities and services, which like any

other consumer product, is composed of a number of multidimensional

attributes”. Smith (1994) acknowledged the importance of travel services in

48

creating a product experience, and described how inputs from various

destinations could produce experiential outputs for tourists.

The tourism literature focuses mainly on the economic, social, cultural,

and environmental impacts of tourism, and tourism development, but tends to

neglect the importance of market dynamics, political impacts, and the

requirements of the business community at both the destination and the place of

origin (Buhalis, 2000).

Leiper (1979) considered “paths linking generating regions with the

tourist destination region, along with tourists’ travel” as “transit routes” The

efficiency and characteristics that influence the quality of access to particular

destinations were emphasized, and accordingly, the influence of the size and

direction of tourist flows were described ( Figure 2.2).

Figure 2.2 Tourism origin-destination model

Source: Adapted from Leiper (1990)

49

2.2.3 Tourism Planning and Development concepts

In the context of planning and development, tourism is defined as an

interdisciplinary, multi-faceted phenomenon that entitles the interrelated

components of tourism products, activities, and services provided by the public

and private sectors (Gunn, 1994; Pearce, 1995). Tourism planning is a process

of evaluation and analysis of related issues, including not only the

determination of goals, but also the development of different methods and

actions to further decision-making. Murphy (1985) in his study said that

tourism planning should fit within existing systems and should be used in urban

and regional development strategies. He also added that, community

involvement should be there for the planning process.

To have comprehensive tourism planning, the existing components and

resources that include tourism attractions, destination management

organizations (DMO), markets, and local related businesses and services within

a given region or destination, should be considered.

Tourism planning requires certain systematic processes and approaches.

Inkeep (1991) described several different approaches to tourism planning. The

approach which is frequently applied in tourism planning and development is

the community approach shows maximum involvement and participation of the

local community in the tourism planning process is sought (Inkeep, 1991).

Specifically, two different perspectives of community participation have been

discussed, including the decision making process and the benefits of tourism

development to the community (McIntosh & Goeldner, 1986; Timothy, 1999).

50

Among the various theory and conceptual models associated with the

examination of resident reactions to tourism, Butler’s (1980) destination

lifecycle model, Doxey’s (1975) Irridex model and, insights derived from

recent social exchange theory described by Ap (1992), Nash, 1989; Perdue et

al., 1990) stand out as significant contributions. Synthesizing these different

perspectives of tourism models, two broad dimensions of the tourism

development/community interface upon which they focus have been identified:

(1)The extrinsic dimension, which refers to characteristics of the location with

respect to its role as a tourist destination — including the nature and stage of

tourism development in the area and, reflecting this, the level of tourist activity

and the types of tourists involved; and

(2) The intrinsic dimension, which refers to characteristics of members of the

host community that affect variations in the impacts of tourism within the

community.

The variables associated with each dimension are summarized in Table 2.2,

where their broad alignment with the theoretical perspectives is also indicated.

51

TABLE 2.2

A FRAMEWORK FOR ANALYSING THE SOCIAL IMPACTS OF

TOURISM

DIMENSIONS MODEL VARIABLES

EXTRINSIC

DIMENSION

TOURISM

DESTINATION

LIFE CYCLE

Stage of tourism

development

IRRIDEX MODEL

Tourist/resident ratio

Type of tourist

Seasonality

INTRINSIC

DIMENSION

SOCIAL

EXCHANGE THEORY

Involvement

Socio-economic

characteristics

Residential proximity

Period of residence

2.2.3.1 Tourism Destination Life Cycle

There are different phases of tourist destinations development like the

products and services. (Butler, 1980; Debbage, 1990; Doxy, 1975; Plog, 1973).

One of these is related to the destination life-cycle concept as defined by Plog

(1973). The concept is similar to the concept of product life cycle, in which all

products or services have an introduction stage in the market and ends with their

withdrawal from the market. Plog (1973) argued that there are two personality

types: allocentric and psychocentric. The allocentric relates to individuals who

prefer unfamiliar places and enjoy risks. They are the people who can be

52

considered pioneers of a destination. Once the destination becomes better known

and popular to a wider market, psychocentric types will generate a preference for

it (Leiper, 2004). Later Plog (2004) changed the term allocentric to ‘venturers’ to

express the group’s tendency to venture and seek new experiences, and

psychocentrics to ‘dependables’, the non-traveling type.

Butler (1980) proposed another theory in the tourism literature called

‘tourist area (destination) life-cycle’ (TALC). The theory considers destinations

as living objects and thus proposes that destinations experience the same life

cycle as animals and plants (Leiper, 2003). Butler (1980) in his TALC model

suggested that tourist areas as they evolve pass through different stages of

development, as illustrated in Figure 2.3.

Figure 2.3 Tourist area (destination) life cycle

53

Note:

Exploration: characterized by small numbers of tourists;

Involvement: the number of visitor increases and the local residents will start to

become

involved by providing facilities to visitors;

Development: identified with well-developed tourist market and planned

advertising by the tourist-generating areas;

Consolidation: the rate of increase in numbers of visitors will start to decline

even though the total number is increasing;

Stagnation: the peak numbers of visitors will have been reached; the area will

have

established its image but will no longer be attractive;

Decline: the area will not be able to compete with new attractions and new

entrants into the tourism market; and

Rejuvenation: may occur if new man-made attractions are added or advantage is

taken of unutilized natural resources.

Many researchers considered the TALC model as useless and misleading,

as it did not explain the fluctuation in tourist numbers. They also argued that it

cannot be applied to all destinations as each destination is a unique case, thus

enhancing the success of tourism planning.

The outcome of many researchers is TALC model can be used for the

purpose of planning and to identify alternative strategies for the development and

marketing of a tourist destination (Choy, 1992). Even though the model has not

been tested on the Tamilnadu rural tourism case, the tourism authority in India

has placed Karaikudi in the developmental stage (Ministry of Tourism, 2006).

54

2.2.3.2 DOXEY'S IRRIDEX MODEL (1975)

In order to clarify the relationship between the impacts of tourism and

residents’ attitudes toward tourism, several models have been developed. One of

the most influential models is Doxey’s Irridex model (1975) which suggests that

residents’ attitudes toward tourism may pass through a series of stages from

“euphoria,” through “apathy” and “irritation.” to “antagonism,” as perceived

costs exceed the expected benefits. (Table 2.3) This model is supported by Long

et al.’s (1990), which indicate residents’ attitudes are initially favorable but

become negative after reaching a threshold. The Irridex model indicates that

residents’ attitudes toward tourism would change over time within a predicable

one-way sequence. It suggests that residents’ attitudes and reactions toward

tourism contain a sense of homogeneity (Mason et al. 2000).

Doxey's irritation index model

suggests that communities pass through a sequence of reactions as the

impacts of an evolving tourism industry in their area become more

pronounced and their perceptions change with experience.

justifies residents' attitudes at different growth stages of a tourist

destination.

assesses host – guest interactions and relationships.

is not based on detailed empirical research, but mainly on conjecture.

Limitation of this framework is the assumption that homogeneity

characterises a community.

The model assumes that it is the whole community that becomes hostile to

tourism, but often communities are heterogeneous and different sections

of the community have different reactions.

55

Entrepreneurs are likely to welcome any growth in tourism, as might any

unemployed people.

the model does postulate that the more common an identity is felt by a

community, the more likely it is able to make a constructive response

about what levels and types of tourism it wishes to host.

is simplistic but it does indicate a telling factor in tourism development,

and that is unbridled development will create

These stages parallel the more generally applicable product life cycle and

they are, implicitly, accompanied by increasingly adverse effects on the

local community as the nature of tourism in the area becomes

progressively mass-tourism oriented

associated reciprocal reactions of the community influence the

progression of Stages by undermining the appeal of the area to tourists

and thus reducing its viability as a tourist destination.

56

TABLE 2.3DOXEY’S INDEX OF IRRITATION (IRRIDEX’)

Both the Doxey (Irridex) and Butler (Destination Life Cycle) models

assume a degree of homogeneity and uni-directionality in community reactions

which has been questioned. In particular, the inherent heterogeneity of

communities and the consequent variety of responses that can occur has been

emphasized by many researchers. However, the most valuable contribution to the

development of a theoretical analysis of variations in the response to tourism

within communities has come from AP’s (1992) adaptation of social exchange

theory.

57

2.3 THEORETICAL BACKGROUND OF TOURISM THEORIES

Though many different disciplines have addressed the issue of tourism

development in general, there is a lack of so-called 'tourism theory' (Jafari,

1990). Rural tourism, in particular seems to be the 'poor relation', although

there are some exceptions to this commonly ignored issue. In this theoretical

'gap', tourism development has been studied from perspectives that reflect

several disciplines (i.e. geography, sociology, anthropology and economy).

Of special interest were those perspectives on and models of tourism

development that address the relationship between tourism development and

the local community, especially from the point of view of the formulation of

tourism policy at the local level and its implementation. Most models are

discussed within the tourism planning field, although issues such as policy and

politics of tourism development at the local as well as national level, are

generally neglected (Hall, 1994). However, it could be observed that there is

growing recognition of the finite limitations to tourism development not only in

terms of the environmental but as well as social impacts. 'Residents' responsive

tourism' (Ritchie, 1993), 'community-based' or 'community-driven' tourism

(Murphy, 1988), and 'sustainable community tourism' (Joppe, 1996) are the

buzz words of tomorrow.

Many authors argue (Pearce et al., 1996; Inskeep, 1991) that the role of

the local community must be centrally placed in sustainable tourism

development. In order to give it this central role it is crucial to understand the

internal dynamics and politics before any development can be considered (Hall,

1994; Reed, 1997).The majority of works on sustainable tourism development

58

places emphasis on the physical environment, and the views of local people are

in most cases of only peripheral interest (Jones, 1993; Joppe, 1996). Studies

that do have an important human aspect either make reference to the impacts of

tourism on communities already involved in tourism, or lay emphasis on local

community's involvement in tourism development without coming to grips with

the reality in which tourism develops and in which it will be continued (Hall,

1994; Pearce et al., 1996).However, such studies do not give enough weight to

the fact that people are engaged in many other activities, of which rural tourism

is perhaps one of many possible directions or options for their own and their

community's development. Most models give scant attention to such factors,

seeing local actors as merely pawns in the game of rural tourism.

None of the models mentioned look at the development of rural tourism

from the perspective of the local community and its members. More

importantly none of them focuses on the ideas that the members of the local

community have in mind for developing their community and area which will

include opportunities as offered by the ideals of rural tourism. Rural tourism

does not develop in a vacuum and local recipients of tourism opportunities are

not passive recipients of the consequences or impacts of tourism. Therefore,

issues that need to be explored are namely, the social and political context and

relationships that provide the context of rural tourism development, and the

context in which local people themselves have agency, thus capabilities to

'make a difference'. Thus, the aim is to understand the process of rural tourism

development, especially in relation to the participation of different (local and

external) stakeholders of the rural destinations, to know how the terms of

development are negotiated among them.

59

Various theoretical conceptions and models have been developed my

many researchers to explain the nature of residents’ perceptions and attitudes

towards the impacts of tourism. Nevertheless, most of the studies related to

relationships between different stakeholders in destination development, and

residents’ attitudes and perceptions have utilized the social exchange theory.

This theory has put forth the way to develop an understanding of residents’

perceptions and attitudes (Ap, 1992; Perdue et al., 1990).

2.3.1 The Social Exchange Theory

The social exchange theory explains how people react to and support

tourism development (Ap, 1992; Jurowski et al., 1997; Perdue et al., 1990;

Yoon et al., 1999, 2000). Social exchange theory has its origin in many

disciplines like anthropology (Levi-Strauss, 1969), economics (Blau, 1968,

1991), behavior psychology (Homans, 1991), and social psychology

(Chadwick-Jones, 1976). The common assumption that can be found in those

theoretical thoughts is “utilitarianism”.

From the perspectives of economists’ the people were seeking to

maximize their material benefits, or utility, from transactions or exchanges with

others in a free and competitive market (Tuner, 1986). In addition, the

utilitarian principle proposes that people rationally weigh costs against benefits

to maximize material benefits” (Turner, 1986).

Blau (1968) highlighted that the assumptions of the economics of social

exchange are that people try new social associations in the expectation of

intrinsic and extrinsic rewards, even though they continue their older

60

associations with others while they find them to be rewarding. He outlined the

difference between social exchanges and economic exchanges as based on the

assertion that obligations and costs incurred in social transactions are not

specified in advance, as they are in economic transactions. His assumed that

people’s choice between different social relations does not imply that they have

to choose the one which yields them the most profit to maximize benefits (Blau,

1964; Chadwick-Johns, 1976).

Anthropologists have identified that social interaction is done in not only

economic exchanges but also in symbolic exchanges or social relationships.

Under social or structural patterns, exchanging commodities among peoples

serves to satisfy their basic economic needs. (Turner, 1996) viewed that

exchange theory involves sustaining exchange relations due to the forces of

psychological needs rather than economic needs. Symbolic exchange is

emphasized for both individual psychological processes and patterns of social

integration. Levi-Strauss (1967), who developed a structural exchange

perspective, said that exchange must be viewed according to its function in

integrating the larger social structure. The exchange behavior can be explained

by viewing the consequences or functions of norms and values. As a result, this

structural view of exchange contributes that various forms of social structure

are critical factors in explaining exchange relations.

Some social exchange theorists modify this principle by affirming

alternative assumptions. Homans (1967) in his study stated that “humans do not

pursue to maximize profits, but they always attempt to make some profit in

their social transaction with others. Humans are not perfectly rational, but they

do engage in calculations of costs and benefits in social transactions.

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Social exchange theory in the behavioral psychology perspective is

based on the principle that people are reward-seeking and they pursue

alternatives that will yield the most reward and the least punishment

(Chadwick-Jones, 1976). Psychological rewards and punishment are reconciled

with economic benefits (utility) and costs. Thus, the notion of reward and

punishment is used to reinterpret the utilitarian exchange heritage so that the

reward is used to reinforce or meet the needs of the people, and punishment is

used to deny reward. Thus, people will behave so as to yield the most reward

and the least punishment and also will repeat those behaviors that have proved

rewarding in the past.

2.3.2 The Social Exchange Theory and Tourism

In the tourism literature, a number of researchers have applied the

theoretical concepts of social exchange theory to explain residents’ reactions to

tourism planning and development (Ap, 1990, 1992; Jurowski et al., 1997;

Lindberg & Johnson, 1997; Madrigal, 1993; Mihalik, 1992; Perdue et al, 1987,

1990; Yoon, 1998; Yoon et al., 2000). Most of the studies have focused on how

residents assess the benefits and costs of tourism development and have

explained residents’ support for future tourism development in particular region

based on their evaluations of the benefits and costs of tourism (e.g. Jurowski et

al., 1997; Yoon et al., 2000).

Social exchange theory can be applied to residents’ attitudes on the basis

that residents seek various benefits in exchange for what they are able to offer

to different tourism agencies, such as resources provided to tourism developers,

tour operators, and tourists; support for tourism development; and being

62

tolerable towards the negative impacts created by tourism(Teye et al. 2002).The

community participation and involvement in tourism development and

decision-making processes tend to increase the viability of the exchange

process and create cohesiveness between residents’ expectations and tourism

development.

Harril,(2004) stated that the social exchange theory involves the trading

and sharing of tangible and intangible resources between individuals and

groups, where resources can be material, social, or psychological in nature.

Further many tourism researchers developed an interest in evaluating the

economic benefits of tourism development, which may come at the potential

detriment of social, cultural, and environmental impacts (Harril, 2004).

Perdue et al. (1990) revealed that social exchange theory is a basis for

investigating residents’ attitudes about tourism. They concluded that support for

additional development was positively related in the case of people who

perceived positive impacts from tourism, and negatively correlated in the case

of people who perceived negative impacts from tourism.

Madrigal (1993) revealed that this theory is related to an economic

analysis of interaction that focuses on the exchange and mutual dispensation of

rewards and costs between tourism actors. He also pointed out that the

underlying assumption of this exchange is a disposition to maximize the

rewards and

Participation of community (residents, government, and entrepreneurs)

in tourism development and the attraction of tourists to their communities is

63

mainly driven by the desire to improve the economic and social conditions of

the area (Ap, 1992).Since tourism stakeholders have been considered as

important key players who influence the success or failure of tourism in a

region, their participation and involvement should be considered in tourism

planning and development. Thus, social exchange theory provides a theoretical

foundation for identifying tourism stakeholders’ perceptions of the benefits and

costs of tourism.

Jurowski et al. (1997) explained how residents weigh and balance seven

components, and why residents of the same community have different views by

using the principles of social exchange theory and a path model. This path

model was designed to investigate how the potential economic gain, use of the

tourism resources, ecocentric attitude, and community attachment as the

exchange factors affect residents’ perceptions of tourism impacts, and affect

both directly and indirectly the support of tourism development.

Yoon et al. (2000), used structural model to find the relationship

between tourism impacts, residents’ attitudes and support for tourism

development, local residents are likely to participate in exchange (support

tourism development). As long as the perceived benefits of tourism exceed the

perceived costs of tourism. Their empirical findings support this statement in n

that the economic and cultural impacts were positively associated with the

“total impact of tourism,” while the social and environmental impacts

negatively affected the “total impact of tourism.” Further, the “total impact of

tourism” was positively associated with “the support for tourism development.”

Additionally, environmental impact was negatively associated with “the

support of tourism development.” As a result, if residents received benefits and

rewards from tourism, they were likely to support tourism development.

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On conclusion, among various theories that have been proposed to

examine peoples’ attitudes about tourism, Social exchange theory has provided

theoretical advantages in facilitating a logical explanation of both the positive

and negative aspects of tourism. The principles of the theory can enable an

explanation of the process involved in the exchanges between tourism resources

and people. It also explains how the exchange factors affect the results or

outcomes of the exchange process. Therefore, this proposed study will utilize

social exchange theory as the underpinning theory for examining the structural

relationships among the constructs (tourism impacts, community participation),

and their results, the support of rural tourism destination competitive strategies.

2.3.3 Stakeholder Theory

Ioannides (2001) applied a stakeholder framework concept to analyze varying

stakeholder attitudes toward tourism and sustainable development at different stages

of destination development. Stakeholder identification and involvement has been

recognized as a key step toward achieving partnerships and collaboration within

tourism in the studies of both Jamal and Getz (2000) and Bramwell (1999).

Stakeholder theory has used as an ethical tool in sustainable tourism marketing by

Walsh, Jamrozy, and Burr,(2001).The application of Stakeholder theory to tourism so

far has been mostly superficial, with the exception of Hary and Beeton(2001) who

applied Stakeholder theory both to identify stakeholder groups and understand their

perceptions of sustainable tourism.

Center and Jackson (1995) stated that the efforts of the small group in an

organization are supported by their perceived power to influence the

organization’s decision process or support from the larger group within the

organization. Large shareholders in an organization ultimately are the powerful

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stakeholder group. The existence of government bodies, such as tourism

planning and development agencies or Ministries, act as a safeguard or

guaranteeing agent to protect the interests of small groups (e.g. small

businesses, consumers) against the exploitation of larger groups (e.g. local

business elite or foreign investors).

Powerful stakeholder individuals or groups could be any organization’s

employees or interest groups (Bridges, 2004), who possess power to affect the

outcome of a particular issue in a particular organization (Carroll, 1991; Heath,

2003) because, they have access to the political process system or to the

influential mass media (Nasi et al., 1997). In conformity with stakeholder

theory logic, Heath (2003) suggested that any issue analysis must include an

analysis of the power of relevant stakeholder individuals or groups. The

stakeholders’ public includes both groups involved in the issue under

consideration itself and groups with a financial interest in supporting and

enhancing the development process (Hilgartrne & Bosk, 2003).

Post et al. (2002) suggested that the concept of stakeholder theory could

be an alternative to the input-output systems theory. While systems theory is

utilized to explain the communication behavior within and between

organisations (Farace et al., 1977), the stakeholder theory recognizes the mutual

benefits and interests of both the stakeholders and the organization.

As a strategic management tool, the stakeholder theory articulates that

the various stakeholder groups can and should have a direct influence on

managerial decision- making processes within an organization (Jones, 1995;

Suatter & Leisen, 1999). Management must pay close attention to the genuine

interests of all legitimate stakeholders to be effective (Donaldson & Preston,

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1995). Clarkson (1995), emphasized the importance of retaining the

participation of even a single primary stakeholder group, otherwise the

organization may become vulnerable to failure and fragmentation.

2.3.4 Stakeholder theory and tourism

Applying the stakeholder theory concepts to tourism would require tourism

planners to realize, and be concerned with, the perspectives of diverse stakeholder

groups involved in the tourism system, and to recognize that their interests are not

exclusively touristic (Suatter & Leisen, 1999). Tourism planning bodies must not

underestimate the importance of various tourism stakeholders groups, which affect

or are affected by the tourism development and services. Meanwhile, Ioannides

(2001) applied the stakeholder framework in conjunction with the destination life-

cycle concept to analyse varying stakeholders’ attitudes toward tourism

development at different stages of destination development, with particular

reference to some Mediterranean Islands.

The stakeholder theory has been utilized to a very little extent in the

tourism planning, policy and strategy development literature (Getz & Timur,

2004); however, it is conceptualized as a normative tourism-planning tool that

can be used to promote collaboration among key players in the tourism

planning system (Donaldson & Preston, 1995; Suatter & Leisen, 1999).

Proactive approaches should be used by the Planning bodies to accommodate

the interests of various stakeholders and their needs, and in addition must

effectively manage the relationships among stakeholders to promote better

collaboration and sustainable tourism development (Suatter & Leisen, 1999).

As tourism in Karaikudi, the rural area is in the early development stage,

it is necessary that the tourism development planning authority to accommodate

the interests of all relevant stakeholders to achieve its planning objectives. The

67

regional planning may also need to be decentralized to cater the local

communities’ interests and diversity in regional areas.

From the above literature the research gap is identified as follows.

The most common evaluation method of tourism attractiveness is from visitors’

or tourists’ perspectives. (Formica, 2000; Milman & Pizam, 1995) argued that

this method is somewhat limited due to the short period of visiting time, and a

limited knowledge of or familiarity with attractions existing in a given region.

Liu (1988) and Formica (2000) suggested that rather than using visitors’

perspectives, the use of tourism experts such as tourism stakeholders have

potential results and benefits. Their solid knowledge and experiences of the

entire portfolio of existing tourism resources and attractions is useful in

evaluating destination competitiveness. Although a number of studies have

addressed concepts and relevant models concerning destination

competitiveness, no empirical study has developed an integrative model

capable of investigating the destination competitiveness of an area by

examining the structural relationships among tourism stakeholders’ beliefs and

attitudes toward tourism, their development preferences for tourism

attractions/resources, and their support of enhancement strategies for

destination competitiveness.

2.4 CONCEPTUAL FRAMEWORK AND HYPOTHESES

The constructs of the conceptual framework is explained in the

following section such as, tourism development impacts, community

participation (stakeholders’ perceived power) and stakeholders’ support for

tourism. Then, finally the composed initial model to be tested in Chapter 4 and

the proposed hypotheses relationships are introduced.

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2.4.1 Tourism Development Impacts

Many researchers have observed the total development impacts of

tourism by stakeholders’. The stakeholders’ perceptions of total impact may be

influenced by the level of tourism development. The results of various studies

suggest that the stakeholders’ perception of the Tourism total impact is affected

by the perceived impact of costs and benefit factors on the stakeholders’ such

as economic, social and cultural, environmental (Yooshik Yoon et al.,2001 ;

McIntosh & Goeldner, 1990). Researchers have found residents perceive

positive and negative environmental impacts of tourism (Liu & Var, 1986; Liu

et al., 1987). Positive impacts include preservation of historic and cultural

resources, recreation opportunities for visitors and residents, and better roads

and public facilities. Negative environmental impacts include deterioration and

destruction of environment, pollution, and deterioration of cultural or historical

resources (Chen, 2000).

Allen et al. (1988: 16) have observed ‘Unfortunately, many state and

local governments attempt to optimize economic benefits of tourism with little

regard to the social and environmental cost associated with tourism expansion’.

To avoid the adverse effects, the impacts of tourism therefore need to be

monitored on a continuous basis for maximum benefits. This is necessary not

only for the purposes of protecting the community’s well-being, but also to

ensure that the quality and sustainability of the tourism product at individual

destinations is not undermined by adverse reactions of the resident population

(Getz, 1994; Inskeep, 1991).

The stakeholders perceived economic benefits as the most important

factor in support of tourism development (Akis et al., 1996). The economic

impact studies have mainly focused on job opportunities (Davis et al., 1988)

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and the benefits derived from tourism activities (Murphy, 1983). Many studies

conclude that host community view tourism provides socio cultural benefits to

the community such as tourism creates opportunities for cultural exchange

(McCool &Martin, 1994). Friedman (1984) also recognizes that political, social

and cultural processes are interdependent with economic processes but not

reducible to them, and are themselves able to bring about change. The extensive

growth of tourism in the late 1960s stressed a need planning (Saarinen, 2008).

Hall (1998) has observed “tourism has emerged as one of the central means by

which rural areas can adjust themselves economically, socially and politically

to the new global environment”. The tourism and its impacts are a

multidimensional phenomenon that encompasses economic, social, cultural,

ecological, environmental, and political forces (Singh et al., 2003)

Positive Economic Impact- This will create employment for the rural people

and generate income for them. The villagers will able to provide better food and

education for their children. The quality of life will improve. They will have an

additional source of income along with their agricultural income.

• Create employment for the rural youth.

• Rise of Income level.

• Foreign exchange generation.

• With Quality of life will increase for example, education, health etc will rise.

• The price of the land will rise.

• Increase in demand for local made goods and services.

• Improvement in the public services.

• Generate revenue for the government.

• Modernization of agriculture and other rural activities.

• Local small businessman will be benefited.

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Negative Economic Impact- The urban communities and entrepreneurs may be

benefited more. The rate of economic return to rural communities has been low.

The facilities provider and investors such as resorts, hotels and tour operators

will be mainly from cities; who will take away most of the profits. Most the

products will be imported from outside, not produced locally. There is a chance

that limited employment will be generated for the rural people due to their

limited knowledge and exposure.

• The rural people can be exploited.

• The rural people have to depend on the urban entrepreneur, so the benefit may

not reach them.

• The urban investor will take away most of the profit.

• Food, drink and necessary products will be imported from outside and not

produced locally.

• The entertainment tax will go to the government and the local people will not

get the benefit.

• Rural people may be under paid.

• Local artisan may not get benefited.

• Due to competition the local handicraft and farm produce products will be sold

at lower price.

• Demand for luxury items will increase.

• Increase in the price of local agro products.

Environmental Impact

The rural people can learn to build up the healthy environment with

proper sanitation, roads, electricity, telecommunication etc for better living.

Some times the tourist can exploit natural resources and have a negative impact

on the environment

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Positive Environmental Impact – The rural people will gain knowledge of how

to lead healthy and hygienic life from the urban people visitors.

• Infrastructure development will lead to healthy tourism.

• The impact of rural environment can improve the state of body and mind.

• Creation and maintenance of natural park.

• Preservation of natural resources.

• Developing healthy environment with proper sanitation, roads, electricity,

telecommunication, etc.

• Usage of modern tools and technology.

• Preservation of the natural habitats, bio-diversity historical monuments.

Negative Environmental Impact - The tourists may exploit natural resources

and it can have a heavy negative impact on the environment. Rural tourism

requires infrastructure, transportation and other facilities which can cause

environmental distortion.

• Development of infrastructure may distort the natural beauty.

• Tourist activities like trekking and camping can cause environmental pollution.

• Huge number of visitors may exploit the natural resources

• Natural ecology will be disturbed.

• Huge buildings for tourist can spoil the scenic beauty.

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Socio-cultural Impact

In spite of many negative effects, tourism has been accepted willingly in

many rural areas. This is due to the income from tourism is much higher than

what rural people can earn from agriculture. It is recognized that negative

impacts on rural communities have become more stronger, and that rural tourism

must be modified to give rural people its benefits.

Poorly planned tourism can mean that villages are invaded by foreign

visitors with different values, disrupting rural culture. The higher standards of

living in urban tourist destinations have caused emigration from nearby rural

neighbours, resulting in changes in the demographic structure and possible

culture shock. Furthermore, employment and education can have a negative

social impact. The younger generation may gain better prestige than their elders

as they gain experience, jobs and money from tourism.

Positive Socio-cultural Impact - The rural people can learn the modern culture.

And can come out of their traditional values and beliefs. They can adopt different

practice of modern society. The income from tourism is much higher than what

rural people can earn from agriculture and other allied services.

• Higher standard of living for the rural people.

• Improvement in education and health of the rural community

• Cultural understanding through fairs and festivals.

• Exchange of cultural beneficial.

• Demand for education will increase.

• Reduce migration of rural people to urban areas.

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• Market for agro products and handicrafts will develop in rural areas

• Farmers and artisans can develop a direct contact with the customers.

Negative Socio-cultural Impact - Poorly planned tourism can affect the

villagers. It can disrupt the rural culture. It may affect the traditional and cultural

practices, agriculture and other allied activities.

• Can create disharmony in development

• Modernization can affect their traditional values and cultural practices.

• Traditional products may be replace by modern products

• Traditional houses are replaced by modern buildings.

• Increase in the rate of crime

• Sexual harassment.

• Overcrowding in schools.

• Rural people may shift from traditional business to tourism activities.

• Rural people try to copy tourist can affect their daily life.

• Decline in participation in rural traditional and cultural practices follows.

Tourism political impacts

The level of power structure of the local population may determine the

differentiation of perceptions and responses to tourism development and

implementation strategies (Dogan, 1989). The local population is usually

divided into various political groups, each with a different policy focus, and

consequently their responses to tourism development differ based on their

political orientation. The costs and benefits of tourism are not distributed

evenly within the local community, and this inconsistency leads to internal

power and interest conflicts between them (Dogan, 1989), the formation of

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class and racial tensions in the society, the rich becoming richer and the poor

becoming poorer (Kadat, 1979), and redistribution of political power (those

negatively affected become hostile and angry toward the newly created elite),

which subsequently leads to resentment and unrest (Lundberg, 1990).

Thus, tourism development may lead to conflicts between different

interest groups, be they public, private businesses or nongovernmental

organisations, whose interests are differentially affected by tourism. Such

differences could develop further into hostilities and unrest, which ultimately

affect the safety and security of the destination

According to Snepenger and Johnson (1991) the residents who identified

themselves as ‘conservatives’ were more negatively disposed to tourism

development than those who identified themselves as ‘liberals’. Thus, the

political impacts of tourism are very much related to economic gain and

political power exerted by different groups. Tourism development depends on

government initiatives. Tourism cannot develop without active encouragement

of the state (Dogan, 1989).

The government plays a key role in visa policy, foreign exchange

requirements, and import regulations. It also supports facilitating regulations

for investment in the tourism industry, and providing the necessary incentives

for tourism development (e.g. infrastructure, supporting services). States’

efforts to minimize the negative consequences of tourism are also important

through educating local citizens to adopt friendly attitudes toward tourists, and

use of the media to promote positive images of the destination (Wood,

1980).Political balance among interest groups within a destination, political

75

freedom, and a government’s active role in regulating the industry are

important political factors for tourism development.

The study of political power arrangements is critically important in the

analysis of the political impacts of tourism (Hall, 1994), because power governs

“the interplay of individuals, organisations, and agencies influencing the

direction of policy”.

The positive impact is that the most advantaged persons within the

government circle may benefit at the expense of those less powerful in gaining

from development. On the negative side, it is most likely that the interests of

the politically powerful will win out over the interests of the politically weak

party (Hall, 1992). One of the negative political impacts of tourism is the loss

of local autonomy to international investors (Krippendorf, 1987).

2.4.2 Tourism support

The success of tourism depends on the active support of the local

population, without which the sustainability of the industry is threatened.

Residents should be the focal point of the tourism decision making process

(Choi & Sirakaya, 2005). The host community to tourists is vital in the visitor

experience and research proposes that it is impossible to sustain Tourism

destination that is not supported by the local people (Ahn, Lee & Shafer 2002;

Twinning-Ward & Butler 2002; McCool, Moisey & Nickerson 2001). The most

favorable perceptions toward tourism impacts are found to be associated with

economic and social and cultural aspects of tourism (Tatoglu et. al 2000). Many

researchers and professionals are currently suggesting for the inclusion of

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stakeholders in the planning process (Hardy & Beeton 2001). Sustainable

tourism development cannot be achieved if imposed without regarding the

stakeholders’ interests (Ioannidis, 1995). The relationship between the

community leaders’ perceptions toward tourism impacts and their effort in

building support for tourism in local communities (Fariborz & Ma’rof 2009).

2.4.3 Community participation

Community participation is an important element of tourism

development of a destination. In other words, community participation acts like

a backbone of a destination. A number of tourism related organizations around

the world promote “people” in the “community” as the “centre” or “heart” of

tourism development. Murphy (1985) argues that often there are conflicts of

opinion amongst residents; with some residents acknowledging the benefits of

tourism development, whilst others such as Harrill (2004) argue that tourism is

having a negative effect on their life style.

The importance of local community involvement and cooperation in the

planning process has been emphasized in the Tourism planning literature (Gunn

& Var, 2002; Telfer, 2003; Tosun, 2000). Stakeholders’ participation in tourism

planning is a prospective component of tourism planning approaches and

sustainability. Stakeholders can be defined as an individual or an identified

group who affects or affected by the achievement of corporate objectives (Getz

& Timur, 2004; Glicken, 2000; Ryan, 2002). The community’s approach to

tourism planning (Gunn, 1994) and the sustainability of tourism approaches

(Hall, 2000) depend on various destination stakeholders’ participation. The

importance of public involvement in tourism planning is a consequence of

tourism impacts on host communities.

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The outcome of several tourism studies (Liu & Var, 1986) substantiated

an increase of public participation in the decision-making process (i.e. higher

empowerment) through higher participation of stakeholders and collaboration

among concerned responsible authorities (Aas et al., 2005), by introducing a

more community-oriented approach to tourism planning and development

(Burns, 2004; Choi & Sirakaya, 2005; Fyall & Garrod, 2004; Hall, 2000;

Scheyvens, 2002).

Stakeholders’ participatory development approach would facilitate

implementation of principles of sustainable tourism development by creating

better opportunities for local people to gain larger and more balanced benefits

from tourism development taking place in their localities (Tosun, 2000),

resulting in more positive attitudes to tourism development and conservation of

local resources (Inskeep, 1994), and by increasing the limits of local tolerance

to tourism. Tosun (2000) states that community participation also has many

constrains like paternalism, racism, clientelism, lack of expertise and lack of

financial resources along with other structural problems in many developing

countries, which creates troubles in the actual process of community

participation..

Effective tourism planning requires resident involvement to overcome the

negative impacts and to channelise the benefits associated with tourism

development (Arnstein 1969).Ying and Zhou (2007) noted that community

participation in tourism can be examined from two viewpoints; first, the decision

making process, allowing residents to become empowered in tourism

development, expressing their concerns and desires; and secondly the tourism

benefits, example, the employment opportunities. According to Cook (1982),

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community involvement within the planning and development process is

important for sustainable tourism development.

Dredge (2006) argues that there is a need to involve wider community in

tourism planning instead of that local government claiming that they represent

the wider communities. According to Hillery (1995), there are three main points

in community participation; community involves group of people who live in

geographically distinct area; the quality of relationships within the groups, with

members tied together with common characteristics such as culture, values and

attitudes; and a group of people engaged in social interaction, such as

neighbouring.

(Cook 1982, Haywood 1988) argued public participation in planning at

the local level, is important if the social and environmental effects of tourism

development are to be avoided, as social and environmental effects are

associated with the local community. In order to involve local community in

the tourism development process, community managers and planners need to

provide educational information and programs (e.g. workshops, awareness

programs) to residents (Sirakaya,2001).

Community participation holds the potential to transform the attitudes of

local people from passivity to responsibility and forms a new relationship

between individual and destination, based on a sharing power and decision

making (Dinham, 2005). Cheong and Miller (2000) argue that local

communities should become proactive and resistant to unwanted change; there

should be negotiation in the plans and development so that they can ensure

development in their community in best possible way. If tourism is to develop

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within a community, the host community must become willing partners to

tourism development. Murphy(1981).

Community develops from creative processes (Day, 2006). The creative

processes determine whether a community continues or disappears. While

social institutions often support an initiative to build a community, it can only

come into being through interpretation of reality by community participants.

Interpretation of socio-economic elements of their environment occurs only due

to the process of social interaction. Community action emerges in result of

interactions among participants of social fields such as education, tourism and

recreation, environment, local governance, which are linked to specific rural

area (Theodori, 2005).

Wilkinson (1991) points up that interactional community development

stands for internal and external forces transforming social relationships among

community participants. Ties between the participants of different social fields

develop into local network of social ties, both formal and informal. Escalation

of the network usually impacts quality of information flow, also intensifying

overall interaction among social fields. Frequent interactions are empirical

demonstration of emerging community. Conflicts inside a community arise

from differences of interests and reflect heterogeneity of local society. Structure

and character of interaction also expose qualitative differences among

interactional communities. Increasing frequency and strengthening of

interactions increases potential for collective decision-making and realization of

locally delineated goal (Wilkinson, 1974), thus improves practice of local

democracy.

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According to Tosun (2000), and Aref and Redzuan (2008) there are

certain limitations for community participation in the decision-making process of

tourism development in the context of developing countries. The limitations

across three heads i.e. (i) Operational Limitations (ii) Structural Limitations and

(iii) Cultural Limitations to community participation in the tourism development

process in many developing countries although they do not equally exist in every

tourist destination.

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CHAPTER III

RESEARCH METHODOLOGY

3.1 INTRODUCTION

This chapter III features the research methodology used in the study to

empirically test the research hypotheses.

A conceptual framework shown in section 1.3 was tested empirically in

the case of karaikudi. In addition, the stakeholders’ perceptions, opinions, and

demographic attributes were collected from both secondary and primary

sources to help resolve the research problem. The study is explanatory and

descriptive in nature, and it is based on both quantitative and qualitative

analysis to investigate the relationships between tourism development impact

factors (economic, socio-cultural, political, environmental), community

participation (stakeholders’ perceived power), and in turn the support of

stakeholders for rural tourism competitive strategies.

3.2 RESEARCH FRAMEWORK

The proposed structural model (Figure 3.1) was tested in this study of

tourism stakeholders’ support of rural tourism destinations’ competitive

strategies as they relate to Tourism Development Impact factors (economic,

socio-cultural, political, environmental), community participation

(stakeholders’ perceived power). This study investigates the interrelationships

82

between these constructs and the favourable competitive strategies stakeholders

are willing to support. The main objective was to examine their perceptions and

opinions about the impacts of tourism development, and the community

participation further to determine their willingness to support the most

appropriate development strategies of competitiveness.

Figure 3.1 The initial conceptual framework for Rural Tourism Support

A thorough review of the existing literature has been performed to

achieve the objectives of the study, and consequently, gaps have been

discovered and a theoretical structural model was developed that incorporates

concepts from the fields of tourism, planning, and development. As presented

in Figure 3.1, the constructs in this study include tourism development impacts,

TourismDevelopmentImpacts

RuralTourismSupport

Econom

Socio-cul

Environ

mental

Political

+H2

Communityparticipation

+H1 +H3

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community participation and support for tourism destination competitive

strategies. Since tourism stakeholders’ participation and involvement are

essential in tourism planning and its decision-making process, their perceptions

and attitudes about tourism are a critical source of success in tourism

development.

The tourism literature has suggested that people’s support about tourism

development is likely to be affected by several factors. For example, if tourism

stakeholders have a positive perception of tourism development impacts, they

are likely to support tourism development. If they have high ecocentric attitudes

toward environmental concerns, they are likely to support tourism

development. Additionally, if tourism stakeholders have a high participation in

tourism, they are likely to support tourism development.

In this structural model, the support of rural tourism destination

competitive strategies is considered as the ultimate dependent or endogenous

construct. It is thought to be affected directly by the two exogenous constructs:

1) tourism development impacts and 2) community participation. The tourism

development impact is measured by the four factors economic impacts, socio-

cultural impacts, environmental impacts and political impacts. The direct effect

of these two constructs on the support for tourism destination competitive

strategies will be contingent upon the manner in which they affect development

preferences about tourism attractions/resources. The direction of the arrows

specifies the relationship between the constructs. Additionally, each linkage

represents a hypothesis that was empirically tested by estimating the degree of

the relationship in this study. It is also assumed that the two exogenous

84

constructs are not correlated with each other: tourism development impacts,

community participation.

The stakeholders’ perceptions, attitudes and behaviors about the

influencing factors on tourism planning and development process regarding

tourism impacts (economic, social, cultural, political, and environmental),

community participation have received little attention in the past (Hall, 1994;

Yoon, 2002). This study will explore the interrelationships between these

constructs in order to reach a conclusion about the favourable competitive

strategies the stakeholders are willing to support and the level of power and

degree of stakeholders’ participation in the decision-making process. So

community participation is added as an exogenous construct(independent

variable) in this proposed model.

3.3 RESEARCH HYPOTHESES


social-cultural, environmental and political,) and the community participation.


social-cultural, environmental and political,) and the support for rural


H3: There is a relationship between community participation and the support

for rural destination competitive strategies.

H4: There is a relationship between economic impacts and tourism

development impacts

H5: There is a relationship between socio-cultural impact and tourism

development impacts.

85

H6: There is a relationship between political impacts and tourism development

impacts.

H7: There is no significant difference between male and female with respect to

community participation, Tourism support and overall community satisfaction

in tourism development.

H8: There is no significant difference between tourism related and non-tourism

related business with respect to tourism support.

H9: There is no significant difference between closer to the destination or far

away with respect to tourism support.

H10: There is no significant difference among age group of the community

people with respect to community participation in tourism development

H11: There is no significant difference among occupation of the community


H12: There is no significant difference among marital status of the community





people with respect to overall community satisfaction


community people with respect to community satisfaction.


people with respect to tourism support strategies

H17: There is no significant difference among occupation of the people with


H18: There is no significant difference among education qualification of the

people with respect to tourism support strategies.

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H19: There is no significant difference between length of residency with


H20: There is no association between years of residency and support for

tourism

3.4 RESEARCH METHODS USED IN TOURISM RESEARCH

Qualitative research methods nowadays are widely used in market

research and are gaining wide acceptance in the social sciences (e.g. Bonoma,

1985; Easter by-Smith et al., 2002; Miles & Huberman, 1994; Walle, 1997). In

travel and tourism research, anthropologists and sociologists have used

qualitative research, with the exception of research in consumer behaviour

(Decrop, 1999; Riley & Love, 2000). According to Riley (1996, p.22), “The

majority of tourism marketing research has relied on structured surveys and

quantification”. The qualitative methods were used explicitly in the exploratory

stage to initiate and provide information for further quantitative investigation or

to subordinate and enhance the empirical findings. This research incorporated

quantitative and qualitative methods in a three-stage process:

Step 1: Stakeholders’ interviews to refine the research problem. The study

began with conducting and collecting cross-sectional secondary data from

different literature sources such as books, periodicals, national and international

newspapers, government records and other studies about the topic. This was

followed by a few face-to-face informal interviews with different stakeholders’

(Government officials) in Tamilnadu and Karaikudi to further refine the

research problem.

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Step 2: Pilot studies to develop and refine survey questions. At this stage, the

theoretical framework and the measurement scales were developed based on a

priori theories and review of the mass tourism literature. Then pilot was

conducted with various stakeholders’ to make sure it was understandable. A

few corrections were suggested and applied. The survey instrument established

its reliability which exceeded the recommended 0.7 level (Hair et al., 2003).

Step 3: (Interviewer-assisted) survey : The third stage was the collection of

primary data from various tourism stakeholders in Karaikudi. It involved

collecting and analyzing data quantitatively as the main part of this study to test

the proposed theoretical framework and hypotheses. . The data was then

integrated at the analysis and interpretation stages for presentation.

3.5 RESEARCH DESIGN

The study is explanatory and descriptive in nature, and it is based on

mixed methods design i.e. both quantitative and qualitative analysis to

investigate the relationships between tourism development impact factors

(economic, socio-cultural, political, and environmental), community

participation (stakeholders’ perceived power) and in turn the support for rural

tourism destination competitive strategies.

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3.5.1 Qualitative Data

Yin (1993) hat qualitative data can be represented by perceptual and

attitudinal dimensions, and real-life events are not readily converted to

numerical values. Moreover, opinions and expectations about tourism planning

and development strategies can differ depending on which population or

occupational groups are considered (Krippendorf, 1987). The participants for

face to face interviews were selected from three different stakeholder segments

(government related and non-related tourism officials and private sector

representatives). The following section explains the qualitative research

method used to further explain the research problem.

The main objectives:

1. To identify the approach of the public participation framework in the study

area.

2.To study the strategy used and problems identified when implementing public

participation.

3.To determine how far the residents are allowed to participate during the

involvement program.

3.5.1.1 Sampling method

Qualitative research usually uses small samples, based on purposeful

sampling, of participants who are studied in-depth through face to face in-depth

interviews, case studies, focus groups, and observations (Easterby-Smith et al.,

2002; Fern, 2001; Gummesson, 2000; Miles & Huberman, 1994; Patton, 1990).

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This study used face to face in-depth interviews. The data were collected

through open ended status questions from three different stakeholders’ about

their feelings, perceptions and opinions. The participants were the middle and

top management hierarchies in both government and private sector

organisations. They are the top planners and decision makers in their

organisations and, having been nominated by their superiors in the case of the

government groups, they were in addition the most knowledgeable about the

topic to be discussed.

3.5.1.2 Sample size

Gummesson (1991) proposed that it is not necessary to study a large

number of respondents to gain an in-depth understanding of the topic under

study. The sample size for the study is thirty participants who were selected on

the merits of their position, influence over decision-making processes,

experience, and involvement in the goal setting and strategy making of tourism

planning and development in Karaikudi. The response rate for this qualitative

research is 100%.

3.5.1.3 Data Analysis

In analyzing qualitative data, Miles and Huberman (1994) identified at

least three stages: data reduction, data display, and conclusion drawing and

verification. These stages would include certain analysis techniques (e.g.

contact summary sheet, codes and coding, pattern coding, memoing). In this

research project, the data was coded according to the predetermined themes

from literature and analysed using contact summary sheet and memoing.

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3.5.2 QUANTITATIVE DATA

3.5.2.1 Study Population

Population of the study can be defined as the entire group under study as

specified by the objective of the research (Pedhazur & Schmelkin, 1991,

Sekaran, 2000). The objective of this study was to investigate Karaikudi’s

tourism stakeholders’ perceptions, attitudes, and behavior toward tourism and

its development, the population of this study was tourism stakeholders. In

particular, the target population includes members or groups that are related or

are not related to tourism activities in the state Tamilnadu and in Karaikudi.

Examples include state and local government officials, tourism, local tourism

agencies, private businesses, residents, tourists and tourism faculties and

students (researchers).

3.5.2.2 Determination of Sample Size

The determination of sample size is a very important issue, because

samples that are too large may waste time, resources and money. While

samples that are too small may lead to inaccurate results. According to

(Saunders et al., 2000) researchers normally work to a 95 percent level of

certainty. This means that if sample are selected 100 times, at least 95 of these

samples would be certain to represent the characteristics of the population. The

margin of errors describes the precision of the estimation of the

population.

It is suggested that a minimum sample size should be at least 200 (or

more) to ensure appropriate use of SEM and to minimize the chance of getting

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exaggerated goodness-of-fit indices due to small sample size (Anderson &

Gerbing, 1988).

The sample size is determined by using the following formula

Sample size (n) = (ZS/E)2

Where

Z=Confidence interval (95%)

S=Standard deviation (from pilot study)

E=Error (5%)

Sample size n = [(1.96*0.48)/0.05]2

= 354

Sample size taken =365

No. of usable responses =320

Response rate =(320/365)*100

=87%

The research proposed to supply the instrument to 365 respondents in

which only 320 respondents were willing to turn back with fully filled

questionnaire. Therefore the response rate was 87%.

3.5.2.3 Sampling Technique

Sampling is a technique that uses a small number of units of a given

population for drawing conclusions about the whole population (Pedhazur &

Schmelkin, 1991; Zikmund, 1997). Sampling is an important method for

increasing the validity of the collected data and ensuring that the sample is

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representative of a population. Convenience and quota sampling methods were

adapted methods from identified and independent sample frames to collect

quantitative data from the respondents. Convenience sampling refers to

“sampling by obtaining units or people who are most conveniently available”,

while quota sampling is “to ensure that various subgroups in a population are

represented on pertinent sample characteristics to the exact extent that the

investigators desire” (Zikmund, 2000 pp.380, 383).

Data were collected through questionnaire from the stakeholders such as

government authorities; tourism related and not related tourism businesses,

tourism agencies, tourist, residents, tourism faculty and students. Depending on

the size of each category of stakeholder, a proportional sample from each

category was selected to represent that particular category and provide

sufficient data for statistical analysis. The selection of sampling units was based

on the researcher’s intuitive judgment, desire and knowledge (Hair et al.,

2003).

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3.5.2.4 Sample size:

TABLE 3.1

THE PROPORTIONATE NUMBERS OF SAMPLES

Stakeholders Numbers (n)

Government officers/Head of Department 30

Residents 170

Business: Tourism related and Non-Tourism

related

50

Tourists 50

Academic faculty and students 20

Total 320

3.5.2.5 Data Collection

Surveys are considered one of the most appropriate and commonly used

sources of information for tourism analysis, planning and decision-making

(Pizam, 1994; Simmons, 1994; Smith, 1995). This study utilized a self-

administered survey method and face-to-face interviews personally

administered surveys with the selected tourism stakeholders in Karaikudi.

However, prior to collecting the main data for the study, a pilot study was

conducted to test the measurement.

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3.6 MEASUREMENT SCALES AND RESEARCH INSTRUMENT

The conceptual framework of this study attempted to empirically test the

relationships proposed among two independent variables: Tourism

development impacts (economic, socio-cultural, political, environmental), and

community participation (stakeholders’ perceived power) and one ultimate

dependent variable was support for competitive destination strategies.

From the literature review and relevant theories the measurement scales

for this study were measured. The rating method, with a 5-point Likert scale

(ranging from 1=strongly disagree to 5=strongly agree, 1=strongly oppose and

5=strongly support) was used for the measurement of perceived tourism

development impacts, community participation (stakeholders’ perceived power)

and support for competitiveness strategies. The scale consists of a set of items

of equal value and a set of response categories constructed around a continuum

of agreement/ disagreement and support/oppose concerning a particular

attitudinal element to which respondents were asked to respond (Pizam, 1994;

Sarantakos, 1998; Zikmund, 2003).

For this study, the survey was divided into six parts: a) the socio-

demographic items b) tourism development impacts to measure the perceived

impacts of tourism development, c) community participation, to measure the

stakeholder’ perceived power d ) support for tourism e) overall community

satisfaction, and f) tourist opinion. Table 3.2 shows the different measured

variables with the sources of the measured scales.

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TABLE 3.2

MEASUREMENT OF VARIABLES

Se.No Part- I Tourism Development Impacts Sources1. Tourism increases job opportunities for the

local peopleBelisle & Hoy, (1980); Davis et al., (1988);Ko & Stewart (2002); Liu & Var (1986);Williams & Lawson (2001); Yoon et al.(1999, 2001)

2. Increase in income generation for localpeople, artisans and small businesses

(Davis et al., 1988; Murphy, 1983). Ko &Stewart (2002); Yoon et al.(1999,2001)

3. Wider promotion of handicraft items Jurowski (1994); Yoon (2002)4. Development of a common platform for

crafts persons to display and sell their localarts and crafts

Jurowski (1994); Yoon (2002)

5. Local labour, technology and resourcesoptimally utilized

Yoon (2002)

6. Tourism has created high investment,development, and infrastructure

Akis et al. (1996); Ko & Stewart (2002);Liu & Var (1986).

7. Tourism creates more jobs for outsidersthan for local people.

Akis et al. (1996)

8. Host community getting trained indifferent types of hospitality management,cuisine preparation, tourist handling

Yoon (2002)

9. Collaboration with different businessinstitutions for market tie-ups.

Yoon (2002)

10. Products are sold in the national andinternational markets

Yoon (2002)

11. Tourism causes changes to the traditionalculture of the community

Akis et al. (1996); Liu & Var(1986); Yoon et al. (1999, 2001)

12. Tourism has encouraged a variety ofcultural exchange between tourists andresidents

Liu & Var (1986); Liu et al. (1987); Teye etal. (2002); Yoon et al. (1999, 2001)

13. Increase in awareness on the importance ofthe site

Developed by the Researcher based onvarious literature

14. Mobilization of women artisans in theactive participation in the tourismprogramme


15. Formation of activity based groups andself help groups, benefiting womencommunity


16. Effective skill building of the womencommunity


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17. Development of institution like Gurukulplatform for learners and teachers


18. Documentation of the crafts, arts andfolklore

Yoon (2002)

19. Tourism benefits outweigh the negativeimpacts

Ap (1990); Johnson et al. (1994); Lankford& Howard (1994); Yoon et al. (1999, 2001)

20. Improved Solid waste managementfacilities like the garbage disposal system


21. Tourism encourages a variety of culturalactivities by the local population (e.g.,crafts, arts, music)

Liu et al. (1987); Williams &Lawson(2001); Yoon et al.(2001)

22. Tourism increases the availability ofentertainment (e.g., festivals, exhibitions,and events)

Akis et al. (1996); Liu & Var (1986)

23. Tourism provides an incentive for theconservation of historical buildings

McCool &Martin, (1994);Mathieson &Wall, (1982);Akis et al. (1996); Johnson etal.

24. Tourism has resulted in more crime rates Akis et al. (1996); Johnson et al.(1994); Liu& Var (1986); Perdue et al. (1987); Yoon etal. (2001)

25. Improvement in natural beauty of thevillage

Yoon (2002)

26. Improvement in hygiene conditions Yoon (2002)27. Construction of hotels and other tourist

facilities destroys the natural environmentAkis et al. (1996); Yoon et al.(1999, 2001)

28. Tourism improves public utilities (e.g.roads, telecommunication) in thecommunity.

Akis et al. (1996); Teye et al.(2002)

29. Tourism brings political benefits to society(eg. democratic values, tolerance)


30. The community should have authority tosuggest control and restrictions of tourismdevelopment in the country.

Perdue et al. (1987)

Community Participation1 The community people require a shared

vision about tourismDeveloped by the Researcher based onvarious literature

2 I would be willing to attend communitymeetings to discuss an important tourismissue


3 The government usually consults us abouttourism planning


4 The public lack power to participate andinfluence the decision making process


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5 Public involvement in planning anddevelopment of tourism will lead topreserving local culture, traditions, and lifestyle


6 Active Participation of the localcommunity and youth


7 I am willing to invest my talent or time tomake the community an even better placefor visitors


8 I would be affected by whatever happens(positive or negative) in the community


Tourism Support1. Development of heritage-based tourism

Jurowski (1994); Yoon (2002)

2. Development of cultural or historic-basedattractions (e.g. museums, folk villages,local historic sites, traditional markets).

3. Development of supporting visitor services(hotels, restaurants, entertainment, banksetc).

4. Development of small independentbusinesses (e.g. gift shops, guide services,camping grounds).

5. Development of cultural and folk events(e.g. concerts, art and crafts, dances,festivals).

6. Development of infrastructure (roads,transportation, and access facilities) fortourists.

The measurement scales and their items in measuring all the constructs in the

study were explained in the following section

3.6.1 Exogenous Construct: (Independent variables)

3.6.1.1Measurement of tourism development impacts

From the literature the measurement scales for assessing the economic,

socio-cultural, environmental and political development impacts of tourism

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were developed. This study investigated the residents’ perceptions of tourism

development in karaikudi. The investigation shows the relationships between

total tourism development impacts and tourism development. (e.g. Akis et al.,

1996; Ko & Stewart, 2002; Liu et al., 1987; Liu & Var, 1986; Yoon, 2002;

Yoon et al., 1999, 2001). From the previous studies, thirty statements were

adapted for the measurement scale of this construct (Table 3.2). Yoon (2002) in

his study produced 0.79 internal consistency of reliability on the scale. A five-

point Likert scale ranging from (1) strongly disagree to (5) strongly agree was

used (see Appendix 1 – Part A). The reliability of this measurement scale will

be discussed in Chapter 4.

3.6.1.2 Measurement of community participation (stakeholders’ perceived

power)

For this construct eight items have been used to represent the concepts of

stakeholders’ perceived power. Stakeholders’ perceived power has been

measured by three theoretical concepts: participation, collaboration, and

empowerment (Fyall et al., 2000;Gunn, 1994; Jamal & Getz, 1995; Murphy,

1985; Scheyvens, 1999; Simmons, 1994; Timothy, 1999; Tosun, 2000). Based

on the comprehensive literature review the eight items were developed by the

researcher . A five-point likert scale ranging from (1) strongly disagree to (5)

strongly agree was used to measure community participation/stakeholders’

perceived power items. Since these items are new measurement scales for this

study, the reliability and validity of the scale were evaluated through data

analysis.

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3.6.2. Endogenous Construct: (The dependent variable)

3.6.2.1 Measurement of Tourism Support

Six items are asked to the respondents to indicate if they supported or

opposed the proposed destination competitive strategies. The scale has been

based on Yoon’s (2002), the literature review, and tourism destination theories

(Buhalis, 2000; Crouch & Ritchie, 1999; Dwyer & Kim, 2001; Hassan, 2000;

Mihalic, 2000; Ritchie & Crouch, 1993, 2003; Ritchie et al., 2000). Yoon

(2002) reported reliability consistency of 0.94. A five-point Likert scale was

used to measure tourism destination competitive strategies and the degree of

support for or opposition to each suggested strategy. The scale ranges from (5)

strongly support to (1) strongly oppose.

3.6.2.2 Overall Community Satisfaction

The overall community satisfaction was measured with one item using a

five point likert scale ranging from (5) Highly satisfied to (1) Highly

dissatisfied.

3.6.3 DATA ANALYSIS

After data has been collected from the representative sample of the

population, the next step is coding of data and analyzing it to test the research

hypotheses. The statistical software SPSS 16(Statistical Package for Social

Sciences) and SEM (Structural Equation Modeling) with AMOS.21 (Analysis

of Moment Structures) software program was used for the quantitative data

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analysis. A scale purification process was conducted over all sample items to

edit data, using Cronbach’s coefficient alpha to delete any item where its item-

to-total correlation was such that its elimination improved the corresponding

alpha values (Lankford & Howard, 1994; Parasuraman et al., 1988). Using

coefficient alpha assisted in determining the internal consistency of the items to

be measured (Lankford & Howard, 1994). The use of the coefficient alpha

measure assisted in ensuring the convergent and discriminate validity, and

increased the reliability of the survey instrument (Pizam, 1994). This measure

is the most commonly accepted formula for assessing the reliability of a

measurement scale of multi-point items (Peter, 1979; Pizam, 1994).

Analysis of data was carried out in two steps.

1. Exploratory Factor Analysis (EFA) was used to explore the underlying

dimensions of Tourism development impacts

2. A Confirmatory Factor Analysis (CFA) was used to confirm the factor

structure of total development impacts.

3.7 STATISTICAL METHOD FOR THE HYPOTHESES TEST –

STRUCTURAL EQUATION MODELING (SEM):

This study adopted structural equation Modeling (SEM) as a statistical

method in testing hypotheses because SEM has been used as a tool in testing

relationships among observed latent variables (Byrne, 2001; Hoyle & Panter,

1995). SEM has been considered to be a confirmatory method of testing a

specified theory about relationships between theoretical constructs (Joreskog &

Sorbom, 1992).

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3.7.1 Measurement model or Confirmatory Factor Analysis (CFA)

The two components of the structural equation modeling are: 1) the

measurement model and 2) the structural equation model. First, the

measurement model is the component of a general model in which latent

constructs are prescribed (Yoon, 2002). It is considered as the ‘null model’

(Garson, 2005). The latent constructs are unobserved variables disguised by the

covariances among two or more observed indicators (Hoyel & Panter, 1995).

The measurement model is that part of the SEM model which deals with the

latent (unobserved) variables or constructs and their indicators (observed

variables). According to Garson (2005) the pure measurement model is “a

confirmatory factor analysis (CFA) model in which there is unmeasured

covariance between each possible pair of latent variables, there are straight

arrows from the latent variables to their respective variables, but there are no

direct effects (straight arrows) connecting the latent variables”.

Each construct in the model has to be evaluated and analysed separately

through a series of model identification steps. Further, when each construct has

shown an acceptable fit to the model, then all constructs should be evaluated

together to produce a final model that is meaningful as well as statistically

acceptable. The measurement model is evaluated using goodness-of-fit

measures. Thus, the measurement model has to be firstly approved as valid

before proceeding further to the structural model testing and analysis (Garson,

2005).

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3.7.2 Structural model

The structural model is the hypothetical model that prescribes

relationships among latent constructs and observed variables that are not

indicators of latent constructs (Hoyle & Panter, 1995). It is the set of exogenous

and endogenous variables in the model, together with direct effects (straight

arrows) connecting them (Garson, 2005). This model is the component of a

general model that relates the constructs to other constructs by providing path

coefficients (parameter values) for each of the research hypotheses.

Particularly, each estimated path coefficient can be tested for its statistical

significance for the hypotheses’ relationships, while including standard errors

(SE), and can calculate critical ratio (CR) or t-values (Bollen, 1989; Byrne,

2001; Hair et al., 1998).

In the structural model, a specific structure between latent endogenous

and exogenous constructs must be hypothesized, and the measurement model

for latent endogenous and exogenous constructs must be determined (Hair et

al., 1998; Mueller, 1996). Commonly, maximum likelihood (ML) is utilized for

the model estimation because these methods allow for the analysis of models

involving latent constructs and non-zero error covariances across structural

equations (Kline, 1998; Mueller, 1996). The structural model provides a

meaningful and parsimonious explanation for observed relationships within a

set of measured variables (MacCallum, 1995). The model also enables

explanations of direct, indirect, and total structural effects of the exogenous

latent constructs on the endogenous constructs.

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3.7.3 Structural equation modeling

Three major types of overall model fit measures are used while

evaluating measurement and structural models: Absolute Fit measures (AFM),

Incremental Fit measures (IFM) and (Byrne, 1998; Hair et al., 1998;Hu &

Bentler, 1995; Maruyama, 1998). First, an absolute fit index is used to directly

evaluate how well an a priori theoretical model fits the sample data. Indexes of

absolute fit typically gauge ‘badness-of-fit’, though optimal fit is indicated by a

value of zero (Hoyle & Panter, 1995). Second, incremental fit index assesses

the proportionate fit by comparing a target model with a more restricted, nested

baseline model. This index concerns the degree to which the model in question

is superior to an alternative model, and typically gauges ‘goodness-of-fit’

(Hoyle & Panter, 1995). Thirdly Parsimonious Fit index measures include the

parsimonious normed fit index (PNFI) and parsimonious goodness-of-fit index

(PGFI). These measures were used to evaluate whether model fit has been

obtained by “over fitting” the data with too many coefficients.

There are different indexes to measure and evaluate the structural

equation models. Most researchers who have evaluated and compared extant

indexes encouraged reporting multiple indexes of overall fit representing the

two above-mentioned measures (Bollen, 1998; Garson, 2005; Hoyle & Panter,

1995). Kline (1998) recommended at least four tests, such as chi-square;

goodness-of-fit index (GFI); normed fit index (NFI) or comparative fit index

(CF); non-normed fit index (NNFI); and standardised root mean square residual

(SRMR). In this study I used indexes such as chi-square (χ2); degree of

freedom (DF); Akaike information criterion (AIC); root mean square residual

(RMR); root mean square error of approximation (RMSEA); normed fit index

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(NFI); relative fit index (RFI); Tucker Lewis index (TLI); comparative fit index

(CFI); goodness-of-fit index (GFI); adjusted goodness-of-fit index (AGFI); and

Hoelter’s critical n (CN).

3.7.4 Reliability and Validity of the Measurement Scales

The internal consistency of the scale is usually assessed by using

Cronbach’s coefficient alpha, calculating the correlation between item to total,

and the overall Cronbach’s alpha of the measurement scale. The acceptable

level of reliability as recommended by Nunnally (1978) is when Cronbach’s

coefficient alpha is .70 or more. The Kaiser-Meyer-Olkin (KMO) value which

is a measure of sampling adequacy should be greater than 0.6, which indicates

that the sample was large enough to perform Factor analysis. (Hair et al., 1998)

The significance of the Bartlett’s Test of Sphericity indicates that the factor

analysis processes are correct and suitable for testing multidimensionality. The

Confirmatory factor analysis loadings also suggest that all the items taken for

scale construction qualify to develop the scale.

Further this study employed structural equation modeling as a statistical

method, the composite reliability was calculated for assessing the reliability of

a principle measure of each construct in the measurement model. A commonly

used cut-off point for composite construct reliability is 0.70 (Hair, Anderson,

Tatham, & Black, 1998; Gable & Wolf, 1993). However, values below 0.70

could be acceptable if the study is exploratory in nature. As another evaluation

method for construct reliability, the variance extracted measure can be

calculated to explain the overall variance in the indicators accounted for by the

latent construct. A higher variance extracted value explains that the indicators

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are truly representative of the latent construct, and is recommended to exceed

.50 (Hair et al., 1998). The formulas for construct reliability and variance

extracted are as follows.

Construct Reliability

(Sum of standardized loadings) 2

=

(Sum of standardized loadings)2 + Sum of indicator measurement error

Variance Extracted

Sum of squared standardized loadings

=

Sum of squared standardized loadings + Sum of indicator measurement error

Validity deals with the adequacy of a scale and its ability to predict

specific events, or its relationship to measures of other constructs (Devellis,

1991). In this study, the face/content validity was addressed by acquiring

information about the questionnaires from faculty members and graduate

students who are familiar with the concepts and content of tourism. Finally, the

construct validity was assessed through the structural equation modeling

process. Specifically, convergent validity was assessed in the measurement

model by confirmatory factor analysis by estimating t-tests of factor loadings,

as well as the corresponding significance (Anderson & Gerbing, 1988; Bagozzi

& Philips, 1982). As a result, if all factor loadings for the indicators in the same

construct are statistically significant, this can be evidence of the supporting

convergent validity of the constructs.

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3.8 Other statistical tools

The Statistical tools used for data analysis are

1. Student t-test is used to compare the means between two samples.

2. Analysis Of Variance (ANOVA) is applied to compare means of two

variables.

3. Chi-Square test for the association between independent and dependent

variable.

4. Correlation test is used to prove the relationship between two variables.

5. Multiple regression is used for predicting the unknown value of a variable

from the known value of two or more variables.

3.9 Software Used

SPSS 16 (Statistical Package for Social Science)

AMOS 21 (Analysis of Moment Structure)

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CHAPTER IV

ANALYSIS AND INTERPRETATION OF DATA

4.1 INTRODUCTION

The results and findings of data collection and statistical methods applied

are described and presented in this chapter. The preliminary tests of the collected

data are presented including the process of data coding and screening,

demographic profile of respondents. Next, the results of the descriptive statistics

of the measurement scales for the three constructs (1) tourism development

impacts, (2) community participation (stakeholders’ perceived power) and (3)

support for tourism destination competitiveness strategies are reported. Further,

Exploratory Factor Analysis (EFA) results of the three measurement scales are

reported, the overall measurement model versions are introduced, and validity

and reliability are approved. The results of the hypotheses tests applied using

Structural Equation Modeling (SEM) with AMOS version 21 are presented and

interpreted The other statistical tools like Student t-test, ANOVA, Chi-square,

Correlation and Regression analysis were applied using SPSS version 16 and

their results are reported. Finally, the qualitative data analysis is reported.

4.2 DATA COLLECTION AND RESPONSE RATE

The data is collected from the study samples of tourism stakeholders’

state and local government officials, local tourism agencies, private businesses,

residents, tourists and tourism faculties and students (researchers).This study

was limited to tourism stakeholders who reside in the state of Tamilnadu and in

the tourism destination Karaikudi. The self-administered survey questionnaire,

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which was finalized from the pilot study was used to collect the responses from

365 tourism stakeholders between September 2010 and November 2010.

(Appendix 1 - Survey Instrument). Out of 365 survey instruments, after

eliminating the unusable responses, only 320 responses were coded and used

for the preliminary data analysis. As a result, 87% response rate was obtained.

4.3 PROFILE OF RESPONDENTS

4.3.1 Demographic Characteristics of Tourism Stakeholders

The demographic characteristics of tourism stakeholders in this study

were measured by gender, age, education, occupation, income, marital status,

family size, ethnic group, income, length of residency in Karaikudi, nature of

business and closeness to the tourism spot. Respondents were asked to provide

their answers to questions that were designed by nominal scales. The summary

of demographic characteristics of respondents is reported.(Table 4.1)

The respondents comprised male (55.6 %) and female (44.4 %), due to

socio-cultural constraints; females were less willing to participate in the survey.

Age groups have been recoded after merging small segments; the results showed

that 41.9 % of respondents were aged between 25 and 44 years, followed by age

ranges of 15-24 years (27.2%), then 44-65 years (25.6%), and 65+years

(5.3%).The results indicated that the majority of respondents (41.9%) were

middle-aged (between 25 and 44 years old).

Education levels of tourism stakeholders showed that 37.8% of

respondents had secondary level school education, 30.6% had higher

qualification, 30% elementary education while 1.6% are uneducated. This

implies that the majority of respondents (37.8%) had secondary level school

education.

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In terms of respondents’ employment, it was found that 41.6% of the

respondents were engaged in self-employment, the government employs 6.2% of

respondents and 15.0% are employed by private sector organisations. The

students constitute 14.4 %, house-wives 7.2%, and the retired people were 4.7%.

The self help groups were 4.4% and the unemployed people were 6.6%.

From the monthly income level of the people, 40.9% have income

between Rs 5001 and Rs 10,000, followed by 24.7% less than Rs 5000. Then

20.6% of the people have Rs10,001 and Rs 15,000 and only 13.1% were above

Rs 15,000.From a marital status perspective, 61.6% of respondents were married,

and 30.3% were single. The widows and divorced respondents would constitute

only 8.1% of total respondents. 58.1% of the respondents had their family

members 4-6. Family members not more than 3 accounted for 31.6%. Only

10.3% of the respondents had their family members above seven.

In terms of respondents’ average length of residency in their place, the

nominal values revealed that 32.8% of respondents were residents of the same

place and living there for more than 20 years, followed by 6-10 years (21.2%).

17.2% of the respondents were living between 11-15 years and nearly 14% of the

respondents were between 0-5 years and 16-20 years. These results revealed how

closely the people are attached to their communities and are not frequent movers.

In terms of residence close to the tourist spots, 51.2% of the respondents

were living far away and 48.8% were living very close to the tourist spots. Of the

total respondents, 72.2 % considered themselves as working with non-tourism

related organisations; however, the remaining percentage was related directly or

indirectly to the tourism industry.

110

Table-4.1

DEMOGRAPHIC PROFILE OF RESPONDENTS (N = 320)

Variables Frequency Percentage

Gender Male 178 55.6

Female 142 44.4

Age Group 15-24 years 87 27.2

25-44 years 134 41.9

44-65 years 82 25.6

>65 years 17 5.3

Education Elementary 96 30

Secondary 121 37.8

Higher qualification 98 30.6

uneducated 5 1.6

Occupation Self-employed 133 41.6

Employed in

Government20 6.2

Self Help group 14 4.4

Employed in Private

sector48 15.0

Retired 15 4.7

House wife 23 7.2

Student 46 14.4

Unemployed 21 6.6

111

Monthly Income <Rs 5000 79 24.7

Rs 5001-10000 131 40.9

Rs 10001-15000 66 20.6

Rs15001-25000 18 5.6

>Rs25001 26 8.1

Marital Status Single 97 30.3

Married 197 61.6

Separated/Divorced 11 3.4

Widows 15 4.7

Family size 1-3 101 31.6

4-6 186 58.1

7-9 22 6.9

10 & above 11 3.4

Length of

residency

0-5 years 45 14.1

6-10 years 68 21.2

11-15 years 55 17.2

16-20 years 47 14.7

>20 years 105 32.8

Nature of

Business

Tourism Related 89 27.8

Non-Tourism Related 231 72.2

Residence close Very close 156 48.8

Far Away 164 51.2

112

4.4 DESCRIPTIVE ANALYSIS OF MEASUREMENT SCALES

4.4.1 Results of Tourism Development Impacts

The descriptive statistics for the different constructs of the conceptual

framework of this study were explained in this section. A higher mean score

indicates a high respondents’ rating of the item after recoding the order of the

measurement.

The results of the descriptive statistics analysis for the tourism

development impacts scale are presented in Table 4.2. This measurement scale

consisted of 30 items reflecting the perceived economic, socio-cultural,

environmental and political impacts of tourism development. Respondents were

asked to provide answers to each item based on a five-point Likert scale ranging

from 5=strongly agree to 1=strongly disagree.

Based on the descriptive statistic analysis, the mean score of each item

shows that from an economic perspective, respondents tended to disagree that

tourism increases job opportunities for the people of Karaikudi (M=2.79,

SD=1.39), and they agreed that Host community getting trained on hospitality

management (M= 3.43, SD=1.106). Additionally, they disagree the promotion of

handicraft items (M=2.65, SD=1.25). They also disagreed that Increase in

income generation to local people and small businesses (M=2.54, SD=1.10).

From a socio-cultural perspective, respondents tended to strongly agree

that tourism encourages formation of activity based groups (M=4.38, SD=1.10),

and further strongly agreed that tourism increases skill building of the women

community (M=4.30, SD=1.17). Additionally, respondents agreed that tourism

113

causes changes to the traditional culture of the community (M=3.70, SD=1.116)

in terms of, for example, lifestyle and language. Further, they strongly disagreed

that tourism Improved Solid waste management facilities like the garbage

disposal system (M=1.20, SD=1.12)

From an environmental perspective, respondents disagreed getting

incentive for the conservation of historical buildings (M=2.93, SD=1.20); on the

other hand they also disagreed that when people interfere with nature, disastrous

consequences may result such as environmental degradation and the

disappearance of certain species (M=2.75, SD=1.19). However, respondents

disagreed that the development of tourism improves public (M=2.62, SD=1.27).

From a political perspective, respondents disagree on political benefits to

society authority (M=2.36, SD=1.13) further disagreed on that they have control

and restrictions on tourism development (M=2.28, SD=1.12).

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TABLE 4.2

DESCRIPTIVE ANALYSIS OF TOURISM DEVELOPMENT IMPACT

Se.No

VariablesMean

StandardDeviation

(SD)Part –I Tourism Development ImpactsEconomic Impact

1. Increases job opportunities 2.79 1.390

2. Increase in income generation 2.54 1.104

3. promotion of handicraft items 2.65 1.254

4. common platform to sell 2.45 1.157

5. optimally utilization of tech 1.60 1.235

6. created high investment 2.65 1.221

7. more jobs for outsiders 2.43 1.218

8. Host community trained on hospitalitymanagement

3.43 1.106

9. Collaboration for market tie-ups. 2.52 1.155

10. national and international markets 2.30 1.245

Socio-Cultural Impact11. changes to the traditional culture 3.70 1.116

12. cultural exchange between tourists andresidents

3.38 1.101

13. Increase in awareness on the importance ofthe site

1.12 1.016

14. Mobilization of women artisans 3.43 1.096

15. Formation of activity based groups 4.38 1.101

16. skill building of the women community 4.30 1.175

17. Gurukul platform to learners 2.25 1.202

18. Documentation of the crafts, arts 2.53 1.189

19. benefits outweigh negative impacts 2.33 1.166

20. Improved Solid waste management facilitieslike the garbage disposal system

1.02 1.121

115

21. encourages a variety of cultural 2.55 1.194

22. availability of entertainment 2.57 1.153

23. incentive for the conservation of historicalbuildings

2.93 1.200

24. resulted in more crime rates 2.35 1.066

Environmental Impact25. Improvement in natural beauty 2.52 1.096

26. Improvement in hygiene conditions 2.45 1.122

27. destroys the natural environment 2.75 1.192

28. improves public utilities 2.62 1.273

Political Impact29. political benefits to society 2.36 1.138

30. authority to control and restrictions 2.28 1.120

Note: Measurement scale, 1= Strongly Disagree and 5 = Strongly Agree

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4.4.2 Results of community participation (stakeholders’ perceived power)

The results of the descriptive statistics for stakeholders’ perceived power

is presented in Table 4.3. A total of 8 items were measured on a five-point Likert

scale ranging from 5=strongly agree to 1=strongly disagree. Higher mean scores

indicate a higher perceived level of participation, collaboration and

empowerment of tourism stakeholders. The aim of this scale is to measure the

level of satisfaction stakeholders generally have with their level of participation

in tourism planning and decision-making process, the level of collaboration

between stakeholders, and the level of empowerment granted to them by the

planning authority in Tamilnadu.

Based on respondents’ data analysis about their satisfaction with the level

of participation required a shared vision about tourism (M=4.05, SD=.91). They

also agreed that the public should have the opportunity, and even be encouraged,

to participate in planning and decision-making (M=3.98, SD=.82).

Further the respondents believed that public involvement in the planning

and development of tourism would lead to preserving local culture, traditions,

and lifestyle (M=3.62, SD=.85). Further, respondents expressed their willingness

to attend community meetings to discuss important tourism issues if they were

asked to do so (M=3.89, SD=.82). The government usually consults us about

tourism planning’ (M=3.82, SD=.60). These results indicate that respondents areseeking better involvement in tourism planning and they are sceptical about

government objectives of involving the community in the decision-making

process.

117

Table- 4.3

DESCRIPTIVE ANALYSIS OF COMMUNITY PARTICIPATIONPart-II Community Participation Mea

n

StandardDeviation

(SD)1. community require a shared vision about

tourism4.05 0.91

2. willing to attend community meetings 3.89 0.82

3. government consults us about tourismplanning

3.82 0.60

4. public lack power to participate in thedecision making process

3.98 0.821

5. Public involvement in planning anddevelopment

3.62 0.852

6. Active Participation of the local communityand youth

2.09 1.131

7. willing to invest my talent or time 3.45 1,15

8. would be affected by whatever happens in thecommunity

2.09 1.23

Note: Measurement scale, 1= Strongly Disagree and 5 = Strongly Agree

4.4.3 Results of Tourism Support Strategies

The results of the descriptive statistics for strategies favoured by

respondents to support destination competitive strategies are presented in Table

4.4. A total of 6 items were measured on a five-point Likert scale ranging from

5= strongly support and 1 = strongly oppose. Higher mean scores indicate high

of respondents on each item of the various competitive strategies.

The measurement scores of the different items shown on Table 4.4

indicate a mean scores range of between 2.01 and 4.69. The highest mean score

indicates that the strongly supportive strategy was ‘Development of cultural or

118

historic-based attractions (M=4.69, SD=1.14), followed by ‘development of

small independent businesses’ (M=3.84, SD=1.17) ‘development of heritage-

based tourism (M=3.64, SD=1.09), ‘development of cultural and folk events’,

(M=3.56 SD=1.19). Additionally, the lowest mean scores indicating strongly

opposing strategies were ‘development of supporting visitor services’ (M=2.04,

SD=1.23), followed by the second lowest score: ‘development of infrastructure

(roads, transportation, and access facilities) for tourists. (M=2.01, SD=1.21).

Table 4.4

DESCRIPTIVE ANALYSIS OF TOURISM SUPPORT STRATEGIES

Part- III Tourism Support(TS)Mea

n

StandardDeviation

(SD)1. heritage-based tourism 3.64 1.092

2. cultural or historic-based attractions 4.69 1.144

3. supporting visitor services 2.04 1.232

4. small independent businesses 3.84 1.172

5. cultural and folk events 3.56 1.199

6. Infrastructure for tourists. 2.01 1.218

Note: Measurement scale, 1= strongly oppose and 5 = strongly support.

The above results indicate that tourism stakeholders in Karaikudi were

highly supportive towards tourism sustainability, promotion of new

businesses and education for both locals and visitors about the local culture

and environment. These strategies as expressed by respondents explaining the

nature of the tourism industry in Karaikudi. The tourism industry in

Karaikudi is considered in its infancy, a stage where people are more

sensitive towards nature and culture.

119

The results of supporting tourism competitive strategies reflected

respondents’ knowledge and awareness level of the tourism industry and the

level of tourism development in the country. In addition to the above-mentioned

supportive strategies, tourism stakeholders in the interviews have mentioned

other strategies which they believed to be of more importance to the country as

well. These strategies are: ‘maintaining and promoting the exposure of a clean

environment’, ‘creating more facilities’ like rest-houses and other amenities,

‘encouraging local investments’, ‘good infrastructure’, providing proper signs in

English’, ‘increasing the number of small and middle range hotels and good

restaurants in the internal regions’, ‘utilization of many touristic sites not yet

utilized’, and ‘providing proper training for tour operators staff’.

4.5 RELIABILITY AND VALIDITY OF MEASUREMENT SCALES

4.5.1 Reliability of Measurement Scales

Reliability is a fundamental measure of any measurement scale. One of

the most popular reliability statistics is Cronbach's alpha (Cronbach, 1951).

Cronbach's alpha (α) determines the internal consistency or average correlation

of items in a survey instrument to gauge its reliability. The meaning of internal

consistency is the extent that its items are inter-correlated. The recommended

Cronabach’s coefficient (α) is above 0.70 (Nunnaly, 1978) and is acceptable as

an internally consistent scale so that further analysis can be possible. However, if

the scale has a coefficient alpha below 0.70, the scale should be examined for

any sources of measurement errors such as inadequate sampling of items,

administration errors, situational factors, sample characteristics, number of items,

and theoretical errors in developing a measurement scale.

120

TABLE- 4. 5

SUMMARY OF THE MEASUREMENT RELIABILITY(CRONBACH’S ALPHA)

Factors No of Items Cronbach’s alpha(α)

Tourism Development

Impacts

28 0.94

Economic impact (EC) 10 0.91

Socio Cultural impacts (SC) 12 0.84

Environmental impacts (EN) 4 0.89

Political impacts (P) 2 0.86

Community Participation

(CP)

8 0.89

Tourism Support (TS) 6 0.84

The reliability for the measurement scales for the three constructs

proposed in this study, the Cronbach’s alpha coefficients were calculated in

SPSS 16 and presented in Table 4.5. All of the measurement scales for the

constructs obtained an acceptable level of a coefficient alpha above 0.70,

indicating that the measurement scales are reliable and appropriate for further

data analysis.

As another approach for assessing the reliability, the composite reliability

and variance extracted were calculated and reported in the next section of

Confirmatory Factor Analysis (CFA). Composite reliability refers to a measure

of the internal consistency of indicators to the construct, depicting the degree to

which they indicate the corresponding latent construct (Hair, Anderson, Tatham,

121

& Black, 1998). An acceptable level of composite reliability is .70. If the

composite reliability is above .70, the indicators for the latent construct are

reliable and are measuring the same construct. As a complementary measure of

the composite reliability, the variance extracted can be calculated to explain the

overall amount of variance in the indicators accounted for by the corresponding

latent construct. A commonly used acceptable value is .50. If the variance

extracted values are high, the indicators are truly representative of the latent

construct.

4.5.2 Validity of Measurement Scales

Validity refers the extent to which the indicators or the measurement

items measure what they are intend to measure (Hair et al., 1998).

Construct validity deals with the adequacy of a scale as a measure of a

specific variable. In general, there are two types of evidence for scale validity:

judgmental and empirical evidence (Gable & Keilty, 1998).

Judgmental validity can be obtained before the measurement scale is

administered to the target study population. It is mainly used as a method for

examining the adequacy of the conceptual and operational definition of the

measurement scale on the basis of the theoretical background. The face or

content validity provides evidence for the judgmental validity.

To verify the face or content validity, the measurement scales for the

constructs were examined by various professors, state tourism officers, economic

development specialists from the public service program, and also the director

from an NGO. Through examination of the contents of the measurement scales,

122

the content validity was achieved and further procedures and research for this

study were supported.

For the empirical evidence, after the measurement scale is administered to

the study population, the relationships among the items within the measurement

scale are examined as well as relationships to the measurements. The empirical

evidence for validity can be obtained by criterion-related validity and construct

validity.

Convergent validity was used to measure the extent to which items

implying to measure one construct indeed converge. This type of validity

evidence can be assessed by examining the t-tests for confirmatory factor

analysis loadings, since statistically significant t-tests for all confirmatory factor

loadings indicate effective measurement of the same construct (Hair et al., 1998).

The construct validity can be obtained by Exploratory Factor Analysis

(EFA). EFA provides a formal and well structured statistical basis for specifying

the minimum number of concepts required to describe the observed phenomena

with the specified degree of accuracy (Horst 1966). Factor analysis analyses a

large set of variables by identifying the common sets of variances called factors

or components. This technique helps the researcher to reduce information to a

manageable number of related variables prior to using them for further analyses

such as multiple regression or multivariate analysis of variance. Factor analysis

can be either exploratory in nature, where data are searched for the underlying

structure and to explore the interrelationships among a set of variables, or

confirmatory, where the researcher seeks to confirm a structure that has already

been identified by previous research aiming to confirm hypotheses or theories

123

concerning the structure of the underlying set of variables. In this study the

objective was to use exploratory factor analysis (EFA) and confirmatory factor

analysis (CFA) for data reduction purposes by using the Maximum Likelihood

Estimation (ML) method. Maximum likelihood estimation (ML) is an estimation

method commonly used in structure equation models (Chou & Bentler, 1995). It

is a procedure which iteratively

improves the parameter estimates to minimize a specified fit function (Hair et

al.,1998).

Before proceeding with the factor analysis, the issues related to the

factorability of data are the inspection of Bartlett’s test of sphericity whichshould be significant (p<. 05), and the Kaiser-Meyer-Olkin (KMO) measure of

sampling adequacy which should range from 0 to 1, with 0.6 suggested as the

minimum value for a good factor analysis (Hair et al., 1998, Tabachnick &

Fidell, 2001). The next assessment measure is the factor rotation and

interpretation. The most frequently used method is the Varimax method which

attempts to minimize the number of variables that have a high loading on each

factor (Tabachnick & Fidell, 2001). The greater the loading, the more the

variable is a pure measure of the factor. Comrey and Lee (1992) suggested that

loadings in excess of 0.71 (50% overlapping variance) are considered excellent,

.63 (40% overlapping variance) very good, 0.55 (30% overlapping variance)

good, 0.45 (20% overlapping variance) fair, and 0.32 (10% overlapping

variance) poor. The choice of the cut-off point for the size of loading is left to the

researcher’s preference.

124

4.6 EXPLORATORY FACTOR ANALYSIS FOR TOURISM

DEVELOPMENT IMPACTS

The measurement scale for tourism development impacts consisted of 30

items. Factor analysis was used for the purpose of condensing the number of

items in a small number of factors. Maximum likelihood estimation method was

used with varimax rotation, so the results were independent and not correlated.

The Kaiser-Meyer-Olkin (KMO) value which is a measure of sampling

adequacy is found to be 0.846, which indicates that the sample was large enough

to perform Exploratory Factor analysis. That is, a 10 to 1 ratio of the sample size

(N=320) is commonly found acceptable (Hair et al., 1998). The results of the

Bartlett’s Test of Sphericity are also significant, which indicates that the factor

analysis processes are correct and suitable for testing multidimensionality.

The 30 items were exposed to factor analysis to identify the underlying

factors, and latent root criterion (eigenvalue) value of above 1.0 (Pett et al.,

2003) and a factor loading of 0.40 were used as a benchmark for including items

in a factor. EFA was performed on the sample using the 30 variables related to

the Tourism Development Impacts. From EFA, four factors Economic impact

(EC), Socio Cultural impacts (SC)

Environmental impacts (EN) Political impacts (P) were extracted

accounting for 63.8 percent of the total variance explained. 28 items loaded

properly (Factor loadings>0.4). Two items, namely “Increase in awareness on

the importance of the site” and “Improved Solid waste management facilities like

the garbage disposal system” were removed because they did not load good

125

(Factor loading less than 0.4)on any of the factors. The factor loadings are

presented in the Table 4.6. Confirmatory factor analysis (CFA) loadings also

suggest that all the items taken for scale construction qualify to develop the

scale. The four factors are labeled as below.

Factor 1, labeled ‘Economic Impact (EC)’, accounted for 17.796 percent

of variances with 10 items. This factor shows the issues related to job

opportunities, income generation, and promotion of handicrafts. The item having

the highest loading was ‘Increases job opportunities’ followed by ‘Increase in

income generation, and promotion of handicraft items’ and ‘common platform to

sell’.

TABLE 4.6

ROTATED FACTOR MATRIX FOR TOURISM DEVELOPMENTIMPACTS

Factors Factors Measurementitems

Factor loadings

EconomicImpact(EC)

EC1 Increases jobopportunities

.784

EC2 Increase in incomegeneration

.762

EC3 promotion ofhandicraft items

.684

EC4 common platform tosell

.665

EC5 optimally utilizationof tech

.608

EC6 created highinvestment

.604

EC7 more jobs foroutsiders

.590

EC8 Host communitytrained on

.565

126

hospitalitymanagement

EC9 Collaboration formarket tie-ups.

.542

EC10 national andinternationalmarkets

.532

Socio-CulturalImpact(SC)

SC11 changes to thetraditional culture

.852

SC12 cultural exchangebetween tourists andresidents

.823

SC13 Mobilization ofwomen artisans

.813

SC14 Formation ofactivity basedgroups

.790

SC15 skill building of thewomen community

.775

SC16 Gurukul platform tolearners

.774

SC17 Documentation ofthe crafts, arts

.773

SC18 benefits outweighnegative impacts

.632

SC19 encourages a varietyof cultural

.605

SC20 availability ofentertainment

.576

SC21 incentive for theconservation ofhistorical buildings

.536

SC22 resulted in morecrime rates

.510

EnvironmentalImpact (EN)

EN23 Improvement innatural beauty

.690

EN24 Improvement inhygiene conditions

.659

EN25 destroys the natural .641

127

environmentEN26 improves public

utilities.621

PoliticalImpact(P)

P27 political benefits tosociety

.765

P28 authority to controland restrictions

.595

Factor 2, ‘Socio-Cultural Impact (SC)’ accounted for 14.858 percent of variances

with 12 items. The item having the highest loading was ‘Tourism causes changesto the traditional culture’ followed by ‘cultural exchange between tourists and

residents’, then ‘tourism has created Mobilization of women artisans’.

Factor 3, ‘Environmental impact (EN)’, explained 10.432 percent of variances

with 4 items. The highest loading item in this component is ‘Improvement in

natural beauty’ followed by Improvement in hygiene conditions’ and ‘destroys

the natural environment’.

Factor 4, ‘Political Impact (P)’ accounted for 20.714 percent of variances with 2

items. The item having the highest loading was ‘Tourism brings political benefits

to society’ followed by ‘authority to control and restrictions’.

4.7 DEMOGRAPHIC PROFILE ANALYSIS

The other statistical tools like Student t-test, Analysis of Variance

(ANOVA), Chi-square, Correlation and Multiple Regression analysis were

applied and their results are reported.

The Statistical tools used for data analysis are

1. Student t-test is used to compare the means between two samples.

128

2. Analysis Of Variance (ANOVA) is applied to compare means of two

variables.

3. Chi-Square test for test the association between independent and

dependent variable.

4. Correlation test is used to prove the relationship between two variables.

5. Multiple regression is used for predicting the unknown value of a variable

from the known value of two or more variables.

4.7.1 Students t-test

Differences between two groups in the mean scores of variables are

studied using Student t test was discussed in this section.

Null Hypothesis-7: There is no significant difference between male and female

with respect to community participation in Tourism development.

TABLE 4.7

GENDER WITH COMMUNITY PARTICIPATION IN TOURISMDEVELOPMENT

GENDER RESPONDENTS MEAN SD t value p value

Male 178 3.71 0.798

.122 0.903Female 142 3.72 0.799

Table 4.7 reveals the mean score and standard deviation between the

two groups male and female based on community participation in tourism

development. Since P value is greater than 0.05, the null hypothesis-7 is

accepted at 5 percent level of significance. Hence it is concluded that there is

no significant difference between male and female with respect to community

participation in the development of tourism. Both male and female actively

participate in tourism development.

129

There is no significant difference between male and female with respect to

overall community satisfaction.

TABLE 4.8

GENDER WITH OVERALL COMMUNITY SATISFACTION


Male 178 2.43 1.14

1.038 0.192Female 142 2.59 1.08


two groups male and female based on tourism support. Since P value is

greater than 0.05, the null hypothesis is accepted at 5 percent level of

significance. Hence it is concluded that there is no significant difference

between male and female with respect to community satisfaction. Overall,

both male and female are dissatisfied with the tourism development in the

area. They fell that even though they are the primary gainers from tourism,

they are also the ones who suffer most from its effects.

There is no significant difference between male and female with respect to

tourism support.

TABLE 4.9

GENDER WITH TOURISM SUPPORT


Male 178 3.22 0.85

0.053 0.958Female 142 3.23 0.93

130


two groups male and female based on tourism support. Since P value is

greater than 0.05, the null hypothesis is accepted at 5 percent level of

significance. Hence it is concluded that there is no significant difference

between male and female with respect to tourism support. Both male and

female stakeholders support tourism strategies in their destination.

Null Hypothesis-8: There is no significant difference between tourism related

and Non-Tourism related business with respect to tourism support.

Table 4.10

NATURE OF BUSINESS and TOURISM SUPPORT

GENDER RESPONDENTS MEAN SD t

value

p value

Tourism related 178 3.33 0.877

1.285 0.200Non-Tourism

Related142 3.19

0.889


two groups tourism related business and non tourism related business based

on tourism support. Since P value is greater than 0.05, the null hypothesis-8

is accepted at 5 percent level of significance. Hence it is concluded that there

is no significant difference between tourism related or non tourism related

business with respect to tourism support. They stands neutral i.e., they neither

support nor oppose tourism in their area.

131

Null Hypothesis-9: There is no significant difference between closer to the

destination or far away with respect to tourism support.

Table 4.11

CLOSER TO THE DESTINATION OR FAR AWAY and TOURISM

SUPPORT


Very close 178 3.37 0.80

2.814 0.005**Far away 142 3.09 0.945


two groups’ people closer to the destination and far away from the destination

based on tourism support. Since P value is lesser than 0.01, the null

hypothesis-9 is rejected at 1 percent level of significance. Hence it is

concluded that there is significant difference between closeness to the

destination and faraway from the destination with respect to tourism support.

The people who are very close show more support than the people who are

far away from the destination.

132

Table 4.12

STUDENT t- TEST - CONSOLIDATED RESULT

Hypothesis DIMENSIONS Result

H7 Gender with Community Participation,Tourism Support and CommunitySatisfaction

Not Significant

H8 Nature of business with TourismSupport strategies

Not Significant

H9 Closeness to the spot with TourismSupport strategies

Significant

4.7.2 Analysis of Variance (ANOVA)

Null Hypothesis-10: There is no significant difference among age group of the

community people with respect to community participation in Tourism

development

Table 4.13

AGE WITH COMMUNITY PARTICIPATION IN TOURISM

DEVELOPMENT

SOURCE SS D F M S F p value

Between groups 12.557 3 4.186 6.944 0.000**

Within groups 190.482 316 0.603

**- Significant at 1 % level

133

Table – 4.13.1

OVERALL MEAN AGREEABILITY SCORE

Age Group Mean SD F value p value

15-24 years 3.53ab 0.776

6.944 0.000**25-44 years 3.72bc 0.836

45-65 years 3.99c 0.665

>65 years 3.27a 0.793

Note: Different alphabet between age group denotes significant at 5% level using

Duncan Multiple Range test

From the table 4.13.1, P value is less than 0.01; the null hypothesis-10

is rejected at 1 percent level of significance. Hence it is concluded that there

is significant difference between age group of the community people with

respect to community participation in Tourism development. Based on

Duncan Multiple Range test, people with the age between 46-65 years show

higher participation (Mean=3.99) in tourism development than people with

the age groups 15-24 years and 25-44 years. The older people who are above

65 years show lower participation (Mean=3.27) in the tourism development.

134

ANOVA for significant difference among occupations of the people with

respect to community participation.

Null Hypothesis-11: There is no significant difference among Occupation of the


Table 4.14

OCCUPATION WITH COMMUNITY PARTICIPATION

SOURCE SS DF MS F p value

Between groups 17.751 7 2.536 4.270 0.000**

Within groups 185.288 312 0.594


Table 4.14.1


Occupation Mean SD F value p value

Self-employed 3.76bc 0.837

4.270 0.000**

Employed in Govt 3.27a 0.786Self Help group 3.55abc 0.868Employed in Privatesector

4.02c 0.576

Retired 3.13a 0.712House wife 3.86bc 0.710Student 3.52ab 0.852Unemployed 3.94bc 0.490

Note: Different alphabet among occupation denotes significant at 5% level using


135

Since P value is less than 0.01, the null hypothesis-11 is rejected at 1

percent level of significance. Hence it is concluded that there is significant

difference between occupations of the people with respect community

participation. Based on Duncan Multiple Range test, government employee

and retired people showed less participation (Mean=3.13, Mean=3.27) in

tourism development. People working in private sector and unemployed were

participating more (Mean=4.02, Mean=3.94) in the tourism development.

ANOVA for significant difference between marital status of the people with


Null Hypothesis-12: There is no significant difference among marital status of

the community people with respect to community participation.

Table 4.15

MARITAL STATUS WITH COMMUNITY PARTICIPATION


Between groups 20.152 3 6.717 11.606 0.000**

Within groups 182.887 316 0.579


136

Table – 4.15.1


Marital

Status

Mean SD F value p value

Single 3.46b 0.785

11.606 0.000**Married 3.86bc 0.766

Separated 2.85a 0.653

Divorced 4.01c 0.556



Since P value is less than 0.01, the null hypothesis-12 is rejected at 1


difference between marital status of the people with respect community

participation. Based on Duncan Multiple Range test, the divorced people

showed more participation (Mean=4.01) in tourism development than the

other group of people who are staying alone and married ones. The separated

group of people showed less participation in tourism development.

ANOVA for significant difference between length of residency of the people

with respect to community participation.

Null Hypothesis-13: There is no significant difference among length of residency

of the community people with respect to community participation.

137

Table 4.16

LENGTH OF RESIDENCY WITH COMMUNITY PARTICIPATION


Between groups 10.372 4 2.593 4.239 0.002*

Within groups 192.667 315 0.612


Table 4.16.1


Length of residency MEAN SD F value p value

0-5 years 3.70ab 0.856 4.239 0.002*6-10 years 3.59ab 0.82511-15 years 3.42a 0.898

16-20 years 3.83bc 0.700

>20 years 3.91c 0.683



Since P value is less than 0.01(Table:4.16.1), the null hypothesis - 13 is

rejected at 1 percent level of significance. Hence it is concluded that there is

significant difference among length of residency of the people with respect to

community participation. Based on Duncan Multiple Range test, the people who

live more than 20 years are more participative in the tourism development

followed by 16-20 years of residents. The people who are new to the place or

whose length of residence is less than 10 years showed less participation in


138

ANOVA for significant difference between age group of the people with


Null Hypothesis-14: There is no significant difference between age group of the

community people with respect to overall community satisfaction

Table 4.17

AGE WITH OVERALL COMMUNITY SATISFACTION

SOURCE SS D F M S F p value

Between groups 16.035 3 5.345 4.399 0.005**

Within groups 383.965 316 1.215


Table 4.17.1



15-24 years 2.61a 1.252

4.399 0.005**

25-44 years 2.54a 1.087

45-65 years 2.48a .970

>65 years 2.02b .993



Since P value is less than 0.01, the null hypothesis -14 is rejected at 1


difference between age group of the community people with respect to overall

community satisfaction. Based on Duncan Multiple Range test, the older people

who are above 65 years were less satisfied (Mean=2.02) when compared to all

other age groups of people.

139

Null Hypothesis-15: There is no significant difference among length of residency

of the community people with respect to community satisfaction.

Table 4.18

LENGTH OF RESIDENCY WITH COMMUNITY SATISFACTION


Between groups 6.988 4 1.747 1.400 0.234

Within groups 393.012 315 1.248


Table 4.18.1



0-5 years 2.29 1.141 1.400 0.2346-10 years 2.51 1.24011-15 years 2.75 1.236

16-20 years 2.32 1.105

>20 years 2.53 0.951



Since P value is greater than 0.01, the null hypothesis – 15 is accepted

at 1 percent level of significance. Hence it is concluded that there is no


140

community satisfaction. The people are less satisfied with the tourism

development in the area irrespective of the period of residence.

ANOVA for significant difference between age group of the community

people with respect to Tourism Support strategies

Null Hypothesis-16: There is no significant difference between age group of the

community people with respect to Tourism Support strategies.

Table 4.19

ANOVA- AGE WITH TOURISM SUPPORT STRATEGIES

SOURCE SUM OF

SQUARES

DF MEAN

SQUARE

F p value

Between groups 7.826 3 2.609 3.391 0.018*

Within groups 243.943 316 0.769

*- Significant at 5 % level

Table 4.19.1



15-24 years 2.98a 0.852

3.391 0.018*25-44 years 3.35c 0.910

45-65 years 3.30b 0.836

>65 years 3.17a 0.934



141

Since P value is less than 0.05 (Table 4.19.1), the null hypothesis -16

is rejected at 5 percent level of significance. Hence it is concluded that there

is significant difference between age group of the community people with

respect to tourism Support strategies. The people with the age group between

15-24 years and above 65 years show less support for tourism. The people

with the age group between 25-44 years show high support for the tourism

Support strategies. The people with the age group between 45-65 years

neither support nor oppose the tourism strategies. The younger generation

people and elderly people are less supportive for tourism than the middle

aged people.

ANOVA for significant difference among occupation of the people with

respect to Tourism Support strategies

Null Hypothesis-17: There is no significant difference among occupation of the

people with respect to Tourism Support strategies.

Table 4.20

ANOVA- OCCUPATION WITH TOURISM SUPPORT STRATEGIES


Between groups 35.499 7 5.071 7.344 0.000**

Within groups 215.444 312 0.691


142

Table 4.20.1


Occupation Mean SD F value p value

Self-employed 3.31ab 0.835

7.344 0.000**

Employed in Govt 3.06bc 0.804Self Help group 3.55a 0.625Employed in Privatesector

3.35ab 0.853

Retired 2.83c 0.651House wife 3.55a 1.085Student 2.76c 0.865Unemployed 3.99a 0.665



Since P value is less than 0.01 (Table 4.20.1), the null hypothesis-17 is


significant difference among the occupation of the people with respect to

tourism Support strategies. Based on Duncan Multiple Range test, Self help

groups, housewives and unemployed people showed more support to tourism

strategies. Retired people and the students are less supportive for the tourism

Support strategies. People employed in government and private sectors and

retired people shows medium support for the tourism in the area.

143

ANOVA for significant difference among education qualification of the

people with respect to Tourism Support strategies

Null Hypothesis-18: There is no significant difference among education

qualification of the people with respect to Tourism Support strategies.

Table 4.21

ANOVA- EDUCATION WITH TOURISM SUPPORT STRATEGIES


Between groups 13.662 3 4.554 6.065 0.001**

Within groups 237.281 316 0.751


Table 4.21.1


Education Mean SD F value p value

Elementary 3.43c 0.849

6.065 0.001**Secondary 3.30c 0.905Higher qualification 2.95ab 0.852Uneducated 2.67a 0.000





significant difference among education qualification of the people with

respect to tourism Support strategies. Based on Duncan Multiple Range test,

144

the people who have the elementary education were more supportive for the

tourism development in their area than the people with higher qualification.

The uneducated people show less support for tourism development.

ANOVA for significant difference between length of residency with respect

to Tourism Support strategies

Null Hypothesis-19: There is no significant difference between lengths of

residency with respect to Tourism Support strategies.

Table 4.22

ANOVA- LENGTH OF RESIDENCY WITH TOURISM SUPPORT

STRATEGIES


Between groups 35.560 4 8.890 13.002 0.000**

Within groups 215.383 315 0.684


Table 4.22.1



0-5 years 2.76a 0.659 13.002 0.000**6-10 years 2.99ab 0.63211-15 years 3.02ab 0.956

16-20 years 3.30b 0.872

>20 years 3.66c 0.904



145




tourism Support strategies. Based on Duncan Multiple Range test, the people

who live more than 20 years are more supportive for the tourism development

in their area. The people who are new to the place or whose length of

residence is between 0-5 years show less support for tourism development.

Table 4.23

ANOVA - CONSOLIDATED RESULT

Hypothesis DIMENSIONS Result

Community Participation

H12 Age group with Community Participation Significant

H13 Occupation with Community Participation Significant

H14 Marital Status with CommunityParticipation

Significant

H15 Length of residency with CommunityParticipation

Significant

Community Satisfaction

H16 Age group with Community Satisfaction Significant

H17 Length of residency with CommunitySatisfaction

Not Significant

Tourism Support strategies

H18 Age group with Tourism Support strategies Significant

H19 Occupation with Tourism Support strategies Significant

H20 Education with Tourism Support strategies Significant

H21 Length of residency with Tourism Supportstrategies

Significant

146

4.7.3 Chi-Square test

Null Hypothesis-20: There is no association between years of residency and support for

tourism

Table 4.24

Chi-square test for association between years of residency and support for

tourism

Length of

residency

Support for Tourism Total Chi-square

Value

p value

Low Average High

0-5 years 7

(16.3)

[11.7]

18

(41.9)

[22.0]

18

(41.9)

[31.0]

43

36.869 0.000**6-10 years 8

(19.5)

[13.3]

23

(56.1)

[28.0]

10

(24.4)

[17.2]

41

11-15

years

4

(10.8)

[6.7]

17

(45.9)

[20.7]

16

(43.2)

[27.6]

37

16-20

years

14

(53.8)

[23.3]

10

(38.5)

[12.2]

2

(7.7)

[3.4]

26

>20 years 27

(50.9)

[45.0]

14

(26.4)

[17.1]

12

(22.6)

[20.7]

53

Total 60 82 58 200

Note: 1. The value within ( ) refers to Row Percentage

2. The value within [ ] refers to Column Percentage

147

sSince P value is less than 0.01 (Table 4.24), the null hypothesis-20 is

rejected at 1 percent level of significance. Hence it was concluded that there is

association between years of residency and support for tourism. Based on the

row and column percentages, the length of residency greater than 20 years shows

less support for tourism. The older people are not interested in the development

of tourism. They want to conserve the culture and heritage of the place.

4.7.4 Correlation Analysis

In order to study the relationship between the items of economic impacts

or the inter-correlation matrix of explanatory variables namely EC1, EC2, EC3,

EC4, EC5, EC6, EC7, EC8, EC9 and EC10 is furnished in the table given below.

TABLE 4.25

INTER-CORRELATION MATRIX OF ECONOMIC IMPACT

VARIABLES

Variables EC1 EC2 EC3 EC4 EC5 EC6 EC7 EC8 EC9 EC10

EC1 1 .498** .618** .476** .621** .303** .585** .452** .518** .384**

EC2 1 .526** .576** .415** .369** .404** .395** .336** .312**

EC3 1 .623** .653** .361** .568** .443** .635** .521**

EC4 1 .457** .465** .444** .402** .292** .386**

EC5 1 .406** .606** .579** .597** .399**

EC6 1 .366** .498** .273** .297**

EC7 1 .395** .567** .237**

EC8 1 .507** .594**

EC9 1 .600**

EC10 1

**-Significant at 1 % level

148

It is seen from the above table 4.25 the correlation between all the

explanatory variables are highly significant and positive.

The inter-correlation matrix of explanatory variables namely SC11, SC12,

SC13, SC14, SC15, SC16, SC17, SC18, SC19, SC20, SC21, and SC22 is

furnished in the table 4.26 given below.

TABLE 4.26

INTER-CORRELATION MATRIX OF SOCIO-CULTURAL IMPACT

VARIABLES

Variables SC11 SC12 SC13 SC14 SC15 SC16 SC17 SC18 SC19 SC20 SC21 SC22

SC11 1 .218** .539** .236** .462** .400** .336** .254** .221** .239** .208** .409**

SC12 1 .364** .617** .338** .353** .364** .312** .411** .461** .296** .126*

SC13 1 .447** .680** .428** .505** .387** .452** .387** .341** .319**

SC14 1 .446** .481** .328** .450** .341** .379** .208** .251**

SC15 1 .306** .512** .464** .405** .445** .247** .312**

SC16 1 .426** .297** .207** .236** .239** .322**

SC17 1 .402** .521** .372** .416** .377**

SC18 1 .306** .521** .287** .371**

SC19 1 .546** .490** .215**

SC20 1 .492** .247**

SC21 1 .210**

SC22 1

**Significant at 1 % level

* Significant at 5 % level

It is seen from the above table 4.26 the correlation between all the socio

cultural variables are highly significant and positive.

149

TABLE 4.27

INTER-CORRELATION MATRIX OF ENVIRONMENTAL IMPACT

VARIABLES

Variables EN1 EN2 EN3 EN4

EN1 1 .439** .289** .381**

EN2 1 .294** .398**

EN3 1 .333**

EN4 1



environmental variables are highly significant and positive.

TABLE 4.28

INTER-CORRELATION MATRIX OF COMMUNITY PARTICIPATION

VARIABLES

Variables CP1 CP2 CP3 CP4 CP5 CP6 CP7 CP8

CP1 1 .462** .547** .335** .352** .339** .428** .403**

CP2 1 .526** .471** .436** .410** .377** .451**

CP3 1 .428** .526** .353** .521** .368**

CP4 1 .387** .386** .296** .395**

CP5 1 .411** .573** .501**

CP6 1 .471** .580**

CP7 1 .608**

CP8 1



community participation are highly significant and positive.

150

TABLE 4.29

INTER-CORRELATION MATRIX OF TOURISM SUPPORT

STRATEGIES

Variables TS1 TS2 TS3 TS4 TS5 TS6

TS1 1 .369** .588** .409** .358** .412**

TS2 1 .412** .505** .516** .591**

TS3 1 .489** .621** .606**

TS4 1 .400** .542**

TS5 1 .552**

TS6 1


It is seen from the above table 4.29 the correlation between all the tourism

support strategies are highly significant and positive.

4.7.5 Regression Analysis

Regression Analysis of Support for Tourism on Community Participation

and Impact of Tourism

Regression is the determination of statistical relationship between two

or more variables. In simple regression two variables are used. One variable

(independent) is the cause of the behavior of another one (dependent). When

there are more than two independent variables the analysis concerning

relationship is known as multiple correlations and the equation describing

such relationship is called as the multiple regression equation.

151

Regression analysis is concerned with the derivation of an appropriate

mathematical expression is derived for finding values of a dependent variable

on the basis of independent variable. It is thus designed to examine the

relationship of a variable Y to a set of other variables X1, X2, X3………….An.

the most commonly used linear equation in Y=b1 X1 + b2 X2 +……+ ban An +

b0

Here Y is the dependent variable, which is to be found. X1 , X2 ,… and

An are the known variables with which predictions are to be made and b1, b2

,….ban are coefficient of the variables.

In this study, the dependent variable is support for tourism, independent

variables are tourism development impacts (economic, socio-cultural,

Environmental and political impact of tourism) and community participation.

The analysis is discussed as follows:

Dependent variable : Support for tourism (Y)

Independent variables : 1. Tourism Development Impacts (X1)

2. Community Participation (X2)

Multiple R value : 0.616

R Square value : 0.379

F value : 60.165

P value : 0.000**

152

TABLE 4.30

VARIABLES IN THE MULTIPLE REGRESSION ANALYSIS

Variables Unstandardized

co-efficient

SE of B Standardized

co-efficient

t value P value

X1 0.101 0.012 0.510 8.507 0.000

X2 0.751 0.216 0.209 3.485 0.001

Constant 10.102 0.865 - 11.676 0.000

The multiple correlation coefficient (Multiple R value) is 0.616 measures

the degree of relationship between the actual values and the predicted values

of the Tourism Support. Because the predicted values are obtained as a linear

combination of Tourism Impact (X1) and Community Participation (X2), the

coefficient value of 0.616 indicates that the relationship between Tourism

Support and the two independent variables is quite strong and positive.

The Coefficient of determination R-square measures the goodness-of-fit

of the estimated Sample Regression Plane (SRP) in terms of the proportion of

the variation in the dependent variables explained by the fitted sample

regression equation. Thus, the value of R square is 0.379 simply means that

about 39.9% of the variation in adjustment is explained by the estimated SRP

that uses tourism impact and community participation as the independent

variables and R square value is significant at 1 % level.

The multiple regression equation is

Y = 10.102 + 0.101X1 + 0.751X2 - - - - - - - - - - 1

153

Here the coefficient of X1 is 0.101 represents the partial effect of Tourism

impact on support for tourism, holding community participation as constant.

The estimated positive sign implies that such effect is positive that support

for tourism would increase by 0.101 for every unit increase in Tourism

impact and this coefficient value is significant at 1% level. The coefficient of

X2 is 0.751 represents the partial effect of community participation on

support for tourism, holding tourism impact as constant. The estimated

positive sign implies that such effect is positive that support for tourism

would increase by 0.751 for every unit increase in community participation

and this coefficient value is significant at 1% level.

4.7.6 Discriminant Analysis

Discriminant analysis is used to distinguish between demographic

variables and the support for tourism and the most important results are

presented in this paper. The tests of equality of group means measure each

independent variable's potential before the model is created. Wilks' lambda,

the F statistic and its significance level are presented in the following Table

4.31

154

Table 4.31

F TESTS OF EQUALITY OF GROUP MEANS

Wilks'

Lambda F value P value

Gender 0.985 3.023 0.084

Age Group 0.998 0.309 0.579

Education 0.981 3.739 0.055

Occupation 0.980 3.987 0.047

Monthly Income 0.972 5.785 0.017

Marital Status 0.985 3.078 0.081

Family size 1.000 0.092 0.762

Length of

residency0.918 17.571 0.000**

Nature of

Business0.996 0.746 0.389

Residence close 0.931 14.775 0.000**

The above test displays the results of a one-way ANOVA for the

independent variable using the grouping variable as the factor. According to

the results in the table, out of 10 variables, only 2 variables in discriminant

model is significant, since P value is less than 0.01. Wilks' lambda is another

measure of a variable's potential. Smaller values indicate the variable is better

at discriminating between groups. The table shows that the closeness of the

residence to the tourist spots decides the support for tourism, followed by

length of residency.

155

TABLE 4.32

CANONICAL DISCRIMINANT FUNCTION UNSTANDARDISED

COEFFICIENTS

Variables Function

1

Gender(X1) -0.644

Age Group(X2) 0.220

Education(X3) -0.293

Occupation(X4) 0.172

Monthly Income(X5) 0.509

Marital Status(X6) -0.188

Family size(X7) 0.689

Length of residency(X8) -0.409

Nature of Business(X9) -0.515

Residence close(X10) 1.500

(Constant) -1.687

CONNANICAL DISCRIMINANT FUNCTION FITTED

Based on the Canonical Discriminant Function coefficient, the linear

discriminant equation can be written as

Y = -1.687-0.644 X1 + 0.220 X2 – 0.293 X3 +0.172 X4 + 0.509 X5 – 0.188 X6

+ 0.689 X7 - 0.409 X8 -0.515 X9 + 1.500 X10 ……………………………………2

156

Test Functions

Eigen value: 0.320

Percentage of variation explained: 100

Wilks Lambda = 0.758

Chi-square = 53.526

P =0.000

Cannonical Correlation: 0.492

TABLE 4.33

DISCRIMINANT ANALYSIS CLASSIFICATION RESULTS

Original

Group

Predicted Group Membership

Total

No support High support

No support 149

(74.5)

51

(25.5)200

High support 34

(28.3)

86

(71.7)120

Note: 1. 74.5% of original grouped cases correctly classified.

2. The value within bracket refers to row percentage

The classification Table 4.33 shows the practical results of using the

discriminant model. Of the cases used to create the model, 149 of the 200 non

supportive community groups (74.5 %) are classified correctly. 86 of the 120

high supportive community groups (71.7%) are classified correctly.

157

Thus out of total 320 respondents, 149 respondents were correctly

classified. Hence the percentage of correct classification is (149/200)*100 %

or 74.5 per cent. Overall, 74.5% of the cases are classified correctly based

demographic variables. The significant F value as well as the percent of

correct classification of community group using the observed observation

clearly indicates the overall significance and adequacy of the model.

4.8 MEASUREMENT MODEL

4.8.1 First order confirmatory factor analysis (CFA)

The four factors of Tourism Development Impacts (TDI) identified

through exploratory factor analysis, Community Participation (CP) and Tourism

Support (TS) were then exposed to confirmatory factor analysis (CFA) to

determine the underlying factor loadings of the items in each factor. A first order

confirmatory factor analysis (CFA) is used to test the measurement model

specifying the posited relations of the observed variables to the underlying

constructs. This approach examines whether the collected data are consistent

with a hypothesized model, or a priori specified model (Byrne, 1998; Maruyama,

1997). Thus, CFA allows identification and clustering of the observed variables

in a pre-specified, theory-driven hypothesized model to evaluate to what extent a

particular collected data set confirms what is theoretically believed to be its

underlying constructs (Mueller, 1996).

The confirmatory factor analysis was performed using AMOS 21. Model

fit indices such as Absolute Fit Measures (AFM), Incremental Fit Measures

(IFM), and Parsimonious Fit Measures (PFM) are utilized to evaluate the

158

proposed model. Maximum likelihood (ML) method of parameter estimation was

utilized because the collected usable sample was quite large (N=320). The ML

estimation method has been used in structural equation modeling because this

estimation method has been found to be acceptable even if the normal

distributions of the observed variables are violated (Chou & Bentler, 1995). The

results are presented in Table 4.34.

The first order standardized CFA – model 1 was done with four-factors of

tourism development impacts, community participation and tourism support

illustrated in Figure 4.1 Model 1 featured some high correlations between error

terms, as indicated by the modification indices. Consequently, the model

presented misfit and needed modification. Therefore, initial model-1 was

modified based on Squared multiple indices (SMC) and modification indices

(M.I). Model -2 was arrived after excluding the variable Environmental impact,

Economic impact items EC2, EC4, EC6, EC10, Socio cultural impact items

SC11, SC12, SC14, SC16, SC18, SC20, Community Participation items CP1,

CP4 and Tourism Support items TS1 with each of these decisions based on the

strength of association of that item with other items. The deletion of the items

produced an adequate better fitting model as demonstrated in Figure 4.2 and

Table 4.34.

159

Figure 4.1 First order standardized CFA – model 1

160

The results of the initial estimation of the CFA (model -1) of the tourism

development impacts construct, community participation and Tourism support

constructs were not acceptable since there was a Chi-square value of 3540.973

with 804 degrees of freedom (p < .001) and a Root Mean Square Error of

Approximation (RMSEA) of 0.113. RMSEA explains the error of approximation

in the population; values should be less than .05 for a good fit. The other fit

indices also indicated a poor fit and suggested that the estimate parameters

should be modified.

Figure 4.3 illustrates the standardized revised model-2 based on three

variables of tourism development impacts, six items of community participation

and five items of tourism Support. The First order standardized CFA – model 1

solution was completely unacceptable (see Table 4.34). However, under these

conditions, the standardized CFA – model 2 exhibited significantly more

acceptable goodness-of-fit (see Table 4.34) than the model-1 as per the chi-

square difference test, as well as minimizing the set of out-of-range parameter

values.

As in Table 4.34, a range of estimates of goodness-of-fit for the revised

model (model-2) was highly acceptable. The initial step was to examine the

effect of dividing the chi-square value (CMIN) by the degrees of freedom (DF).

This operation results in a ratio (CMIN/DF) with an ideal value of 2.538 which is

in the 0-3 range and is significant at the level of .05 (p= .05). In the initial model

(model-1), this value exceeded the threshold value and it shows a poor fit.

RMSEA value is 0.08. Values less than 0.6 to 0.8 shows mediocre fit

(MacCallum, Browne and Sugawara (1996). From this measure, the model

shows an acceptable fit. The other fit indices also indicated a mediocre fit (see

table 4.34 for acceptance limit for model fit indices)

161

Figure 4.2 Standardized CFA – model 2

162

Table 4.34

MODEL FIT INDICES- First order CFA

Model Fit indices Model -1 Model -2 Standardised Values

Absolute Fit Measures

Chi-square of estimate model

df

(X 2 /df)

Probability

3540.973

804

4.404

.000

1505.034

593

2.538

0.05

<5 (Ullman 1996) good fit

P<0.05

Goodness-of-fit index (GFI) .631 .743 0-1.Value close to 1 is good fit

(Byrne, 1995; Hu & Bentler,

1995)

Root mean square residual

(RMR)

.113 .097 <1 (Hu & Bentler, 1999)

Root mean square error of

approximation

(RMSEA)

.103 .08 0.08 (mediocre fit)

(MacCallum, Browne and

Sugawara, 1996)

Incremental Fit Measures

Adjusted goodness-of-fit index

(AGFI)

.585 .696 0-1.Value close to 1 is good fit


1995)

Parsimonious Fit Measures

Comparative fit index (CFI)

.667 .791 0-1.Value close to 1 is good fit


1995

Note: All t-value were significant at the level of .05.

163

X2 = Chi-Square; df = degrees of freedom; GFI = goodness-of-fit index;

AGFI = adjusted goodness-of-fit; CFI = comparative fit index; RMR = Root

Mean Square; RMSEA = root mean square error of approximation.

Table 4.35

I ORDER - STANDARDIZED REGRESSION WEIGHT FACTOR

LOADINGS

ItemA

Direction Item B βEstimate S.E. C.R. P

EC1 <--- EC .754 061 15.379 ***EC3 <--- EC .827 .065 15.387 ***EC5 <--- EC .817 .061 15.279 ***EC7 <--- EC .705 .061 12.900 ***EC8 <--- EC .671 .058 12.122 ***EC9 <--- EC .752 .061 13.838 ***SC13 <--- SC .710 .089 12.488 ***SC15 <--- SC .672 .066 15.331 ***SC17 <--- SC .659 .087 11.488 ***SC19 <--- SC .642 .085 11.187 ***P28 <--- P .841 .091 12.085 ***P27 <--- P .639 .067 10.800 ***CP8 <--- CP .693 .097 11.057 ***CP7 <--- CP .724 .093 12.086 ***CP6 <--- CP .652 .099 11.003 ***CP5 <--- CP .723 .096 12.228 ***CP3 <--- CP .680 .086 11.454 ***CP2 <--- CP .653 .102 10.850 ***TS6 <--- TS .774 .071 13.789 ***TS5 <--- TS .720 .071 13.289 ***TS4 <--- TS .661 .071 12.046 ***TS3 <--- TS .791 .073 14.241 ***TS2 <--- TS .741 .071 12.983 ***

164

The examination of estimates of model fit was supplemented by checking

the significance of standardised regression weights. As shown in Table 4.35,

latent variable 1 Economic impacts (EC)) was significantly associated with 6 of

the 10 items, latent variable 2 socio-cultural impacts (SC) was significantly

associated with 4 items and latent variable 4 political impacts (P) was

significantly associated with 2 items. The latent variable 3 environmental

impacts (EN) were not significant. It is clear from the above that these factor

loadings were large relative to their standard errors.

An examination of the standardised residuals showed that most of the

items approximate between -1 and 1.9, with none of the residuals approximating

values of 2 or 3. As none of the standardised residuals exhibited extreme values,

this examination also suggested that the model fits the data fairly well.

Additionally, the highest squared multiple correlation (SMC) for Tourism

development impacts which assessed the extent to which the measurement model

was adequately represented by the observed measures was .707 (Item P28 ‘The

community should have authority to suggest control and restrictions of tourism

development in the country’), and the lowest squared multiple correlation was

.408 (Item P27 ‘Tourism brings political benefits to society’). Similarly the

highest squared multiple correlation for community participation variables was

.524 (Item CP7 ‘I am willing to invest my talent or time to make the community

an even better place for visitors’). The lowest SMC was .425 (Item CP6 ‘Active

Participation of the local community and youth’). The tourism support variable

shows .626 as the highest SMC (‘Development of supporting visitor services’).

The lowest SMC score was .437 (TS4 ‘Development of small independent

businesses’).

165

Further, it could be interpreted that approximately 70% of the variance of

Item P28 was explained by the tourism development impacts. Additionally, the

item indicated the highest standardized loading of .841 (Table 4.35), meaning

that the item was the highest relative indicator in measuring tourism

development impacts. However, attention should be given to Item P27 having the

lowest loading (.639), because this item could contribute to a poor fit in the

overall measurement model (Table 4.35).

Similarly 52% of the variance is explained by the item CP7 of community

participation construct. The item CP7 indicated the highest standardized loading

of .724, meaning that the item was the highest relative indicator in measuring the

strength of community participation. The community people are willing to invest

their talent or time to make the community a even better place for visitors. More

attention should be given to Item CP6 having the lowest loading .656, because

this item shows poor fit to the model (Table 4.35).

Approximately 63% of the variance is explained by the Item TS3 of

tourism support construct. The item TS3 indicated the highest standardized

loading of .791, meaning that the item was the highest relative indicator in

measuring the support for tourism development in the destination. The

stakeholders are strongly in support of developing supporting visitor services.

More attention should be given to Item TS4 having the lowest loading .661,

because this item shows poor fit to the model (Table 4.35).

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4.8.2 Second Order Confirmatory Factor Analysis (CFA)

Next the researcher ran a second order confirmatory factor analysis on the

measurement model (Figure 4.3) consisting of the Tourism Development impacts

(TDI) as a latent construct. The measurement model revealed an adequate model

fit to the data (See Table 4.36).

Table 4.36

MODEL FIT INDICES - II ORDER CFA

Model Fit indices II orderModel

Standardised Values

Absolute Fit MeasuresChi-square of estimate modeld.f(X 2 /df)Probability

577.5292012.873.000

p<5 (Joreskog & Sorbom, 1996)

Goodness-of-fit index (GFI) .865 0-1.Value close to 1 is good fit(Byrne, 1995; Hu & Bentler,1995)

Root mean square residual(RMR)

.078 <1 (Hu & Bentler, 1999)

Root mean square error ofapproximation(RMSEA)

.08 0.08 (mediocre fit)(MacCallum, Browne andSugawara, 1996)

Incremental Fit MeasuresAdjusted goodness-of-fit index(AGFI)

.814 0-1.Value close to 1 is good fit(Byrne, 1995; Hu & Bentler,1995)

Parsimonious Fit MeasuresComparative fit index (CFI)


167

Figure 4.3: Overall Measurement model - II Order CFA

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Table 4.37 II order CFA - Standardised Regression Weight Factor Loadings

Variables Direction Item B βEstimate

S.E. C.R. P

EC1 <--- EC .741 .061 13.563 ***EC3 <--- EC .818 .068 14.703 ***EC5 <--- EC .836 .064 15.308 ***EC7 <--- EC .687 .063 12.259 ***EC8 <--- EC .672 .060 11.835 ***EC9 <--- EC .746 .063 13.582 ***SC13 <--- SC .718 .091 11.465 ***SC15 <--- SC .676 .067 14.745 ***SC17 <--- SC .692 .087 11.904 ***SC19 <--- SC .698 .086 11.863 ***P28 <--- P .883 .082 11.765 ***P27 <--- P .631 .063 10.732 ***CP8 <--- CP .655 .097 11.760 ***CP7 <--- CP .742 .095 12.832 ***CP6 <--- CP .633 .096 11.750 ***CP5 <--- CP .745 .111 11.470 ***CP3 <--- CP .659 .097 10.354 ***CP2 <--- CP .653 .119 10.100 ***TS6 <--- TS .407 .283 4.098 ***TS5 <--- TS .741 .377 5.053 ***TS4 <--- TS .673 .348 4.979 ***TS3 <--- TS .793 .401 5.088 ***TS2 <--- TS .717 .345 5.023 ***

The examination of estimates of model fit was supplemented by checking

the significance of standardised regression weights. As shown in Table 4.37

latent variable 1 Economic impacts (EC)) was significantly associated with 6 of

the 10 items, latent variable 2 socio-cultural impacts (SC) was significantly

associated with 4 items and latent variable 4 political impacts (P) was

significantly associated with 2 items. The latent variable 3 environmental

169

impacts (EN) were not significant. It is clear from the above that these factor

loadings were large relative to their standard errors.

An examination of the standardised residuals showed that most of the

items approximate between -1 and 1.9, with none of the residuals approximating

values of 2 or 3. As none of the standardised residuals exhibited extreme values,

this examination also suggested that the model fits the data fairly well.

4.9 STRUCTURAL MODEL FOR TOURISM SUPPORT

The Structural model consists of three exogenous variables: Economic

impacts, socio-cultural impacts, and political impacts (Tourism development

impacts), and two endogenous variables community participation and Support

for tourism destination (Figure 4.5). The goodness-of-fit statistics for the

structural model produced reasonable results, as shown in Table 4.38 below. The

results of the structural equation modeling indicate an adequate model fit to the

data.

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Table 4.38

MODEL FIT INDICES – STRUCTURAL MODEL

Model Fit indices StructuralModel

Standardized Values

Absolute Fit MeasuresChi-square of estimate modeld.f(X 2 /df)Probability

661.7172063.212.069

<3 (Byrne 1990)p<.05 (Joreskog & Sorbom,1996)

Goodness-of-fit index (GFI) .848 0-1.Value close to 1 is good fit(Byrne, 1995; Hu & Bentler,1995)

Root mean square residual(RMR)

.087 <1 (Hu & Bentler, 1999)

Root mean square error ofapproximation(RMSEA)

.08 0.08 (mediocre fit)(MacCallum, Browne andSugawara, 1996)

Incremental Fit MeasuresAdjusted goodness-of-fit index(AGFI)


Parsimonious Fit MeasuresComparative fit index (CFI)


Note: All t-value were significant at the level of .05.

The structural equation model for tourism support showed a strong

goodness-of-fit and its estimation yielded a chi-square value of 661.717 with 206

degrees of freedom (p< .05), which was not statistically significant. The model

fit indices are shown in Table 4.38 supported the structural model as a well-

fitting model to the data and suggested that this model could be a final structural

model to be tested for the proposed hypotheses in this study. The statistical

indices shown in Table 4.38 were all within the acceptable threshold for a well-

fitted acceptable model.

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The structural model was examined by using measurement indices

representing the three types of fit indices: absolute fit indices, incremental fit

indices, and parsimonious fit indices. The results are shown in Table 4.38 above.

The absolute fit indices measure how well an a priori model reproduces the

collected sample data, in other words, how closely the model compares to a

perfect fit (Bollen, 1989; Hu & Bentler, 1995). These indices include chi-square

of the estimated model, goodness-of-fit (GFI), root mean square residual (RMR),

and root mean square error of approximation (RMSEA). The chi- square value of

661.717 with 206 degrees of freedom was not statistically significant at p=.069,

therefore suggesting that the structural model with three constructs was

appropriate and should be accepted. The goodness-of-fit (GFI) index that was

used to compare the structural model with no model at all yielded a value of

0.848.This index takes a value from zero to 1.00, with the value closest to 1.00

being indicative of good fit (Byrne, 1995; Hu & Bentler, 1995). The result of

GFI for this study exceeded the acceptable level of model fit. Next, the value of

root mean square residual (RMR) was .087. This value indicates the average

value across all standardised residuals ranging from zero to 1.00. In order to have

a well fitting model, this value has to be less than .05. Accordingly, the RMR

value in this study was acceptable with mediocre fitting hypothesized model.

Lastly, the root mean square error of approximation (RMSEA) represents an

index to quantify model misfit, suggesting that a value of less than .05 indicates a

good fit (Hu & Bentler, 1995), 0.8 indicates a mediocre fit (MacCallum, Browne

and Sugawara, 1996). The value of RMSEA for this hypothesized measurement

was .08, which is within the acceptable level indicates an adequate degree of

goodness-of-fit. In summary, the examinations of the absolute fit statistics

indices suggested that the hypothesized model represented a mediocre fitting

model to the data.

172

The second estimated goodness-of-fit statistics, the incremental-fit-

indices, were examined. These were used to evaluate the proportionate

improvement in fit by comparing a target model with a more restricted, nested

base line model (Hu & Bentler, 1995). The fit indices Average goodness-of-fit

indices (AGFI) value was 0.80. This index takes a value from zero to 1.00, with

the value closest to 1.00 being indicative of good fit (Byrne, 1995; Hu & Bentler,

1995). The result of AGFI for this study is close to 1.00 and it is within the

acceptable level of model fit.

Finally, the parsimony fit indices provide information about a comparison

between models of differing complexity, by evaluating the fit of the model

versus the number of estimated coefficients needed to achieve the level of fit.

This measure includes indices such as the comparative fit index (CFI). The

values of the CFI range from zero to 1.00, the value closest to 1.00 being

indicative of good fit (Byrne, 1995; Hu & Bentler, 1995). The values of CFI is

0.90, suggesting that this values are sufficient to support a well fitting model.

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Figure 4.4 – Structural model

174

Note:Economic Impact (EC)EC1-Tourism increases job opportunities for the local peopleEC3-Wider promotion of handicraft items made in the villageEC5-Local labour, technology and resources being optimally utilizedEC7-Tourism creates more jobs for outsiders than for local peopleEC8-Host community getting trained on different types of hospitalitymanagement, cuisine preparation, tourist handlingEC9-Collaboration with different business institutions for market tie-ups.Socio-Cultural Impact (SC)SC13-Mobilization of women artisans in the active participation in the tourismprogrammeSC15-Effective skill building of the women communitySC17-Documentation of the crafts, arts and folk loreSC19-Tourism encourages a variety of cultural activities by the local populationPolitical impact (P)P27-Tourism brings political benefits to societyP28-The community should have authority to suggest control and restrictions oftourism development in the country.Community ParticipationCP2-I would be willing to attend community meetings to discuss an importanttourism issueCP3-The government usually consults us about tourism planningCP5-Public involvement in planning and development of tourismCP6-Active Participation of the local community and youthCP7- willing to invest talent or time to make the community an even better placefor visitorsCP2-I would be affected by whatever happens (positive or negative) in thecommunityTourism Support (TS)TS2- Development of cultural or historic-based attractions.TS3- Development of supporting visitor services.TS4- Development of small independent businesses.TS5- Development of cultural and folk events.TS6- Development of infrastructure for tourists.

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Figure 4.5- Standardized Structural model

176

This assessment of estimates of fit was supplemented by an examination

of the significance of completely standardised factor loadings. These

standardised loadings were used to determine the relative importance of the

observed variables as indicators of the constructs. Table 4.39 shows the

relationships between all the endogenous and exogenous constructs are highly

significant. There exists a negative relationship (-0.584) between tourism

development impacts (TDI) and support for tourism strategies (TS)

The latent variable Economic impact (EC) was significantly associated

with Tourism development impacts (TDI), the latent variable socio-cultural

impacts (SC) was significantly associated with Tourism development impacts

(TDI), the latent variable political impacts (P) was significantly associated with

Tourism development impacts (TDI), the latent variable Tourism development

impacts (TDI) was significantly associated with ‘community participation’ (CP).Tourism support (TS) was significantly associated with ‘communityparticipation’ (CP). Tourism support (TS) was significantly associated with

Tourism development impacts (TDI). All path relationships show significant

positive relationships, except the relationships between Tourism support (TS) ←Tourism development impacts (TDI) which showed significant negative

relationships.

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Table 4.39

STRUCTURAL MODEL - STANDARDISED REGRESSION WEIGHT

FACTOR LOADINGSItem A Direction Item B β

EstimateS.E

. C.R. P

CP <--- TDI .897 .077 9.551 ***EC <--- TDI .879SC <--- TDI .983 .076 11.678 ***P <--- TDI .835 .072 8.434 ***

TS <--- TDI -.584 .222 -2.456 .014TS <--- CP .984 .286 4.128 ***

EC1 <--- EC .746EC3 <--- EC .802 .068 14.462 ***EC5 <--- EC .833 .064 15.132 ***EC7 <--- EC .702 .063 12.505 ***EC8 <--- EC .649 .059 11.523 ***EC9 <--- EC .745 .062 13.461 ***CP2 <--- CP .621CP3 <--- CP .669 .082 11.008 ***CP5 <--- CP .744 .103 10.822 ***CP6 <--- CP .663 .104 9.928 ***CP7 <--- CP .738 .100 10.582 ***CP8 <--- CP .711 .093 10.310 ***TS2 <--- TS .754TS3 <--- TS .831 .104 11.515 ***TS4 <--- TS .639 .082 10.763 ***TS5 <--- TS .731 .085 12.165 ***TS6 <--- TS .721 .080 12.166 ***

SC13 <--- SC .743SC15 <--- SC .695 .065 15.149 ***SC17 <--- SC .697 .082 12.204 ***SC19 <--- SC .656 .080 11.487 ***P27 <--- P .614P28 <--- P .860 .149 9.917 ***

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4.10 OUTCOMES OF HYPOTHESES TESTING

The results of structural equation analysis by AMOS were used to test the

proposed hypotheses in this study. The relationships between constructs were

examined based on t-value or critical ratio (c.r.) values associated with path

coefficients between constructs. If an estimated c.r. is greater than a certain

critical value (p<.05, c.r. = 1.96) (Mueller, 1996), the null hypothesis that the

associated estimated parameter is equal to 0 was rejected; otherwise, the

hypothesis was supported. The summary of the hypotheses testing is presented in

Table 4.40.

Table 4.40

SUMMARY OF HYPOTHESES TESTING

Hypothesis Relationship

estimate

BetaEstimate

c.r value Results

CP <--- TDI 0.897 9.218 Supported

EC <--- TDI 0.884 8.709 Supported

SC <--- TDI 0.975 11.152 Supported

P <--- TDI 0.825 8.503 Supported

TS <--- TDI -0.520 -2.257 Not Supported

TS <--- CP 0.994 4.065 Supported

In this proposed model, a total of 6 hypotheses were proposed and tested

by using structural equation modeling. From the outcome of EFA, CFA

structural equation modeling the hypotheses were all tested and the results

reported in Chapter 5. The final model has been tested and found to be a good fit

the data and the possible model for this study.

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4.11 RELIABILITY AND VALIDITY OF THE MEASUREMENT

INSTRUMENT

TABLE 4.41

RELIABILITY AND VALIDITY OF THE MEASUREMENT INSTRUMENT

Convergent validity is achieved when multiple indicators are associated

with one another in a consistent way to form a single measure (Neuman, 2003).

A measure has convergent validity when it is highly correlated with different

measures of similar constructs. In other words, convergent validity is established

when a CFA model fits satisfactorily and all factor loadings are significant, and

preferably high (Bagozzi & Baumgartner, 1996). For construct validity

unidimensionality must be established. Either exploratory or confirmatory factor

analysis is used to provide support for unidimensionality (Gerbing & Anderson,

1988). The results of both the exploratory and confirmatory factor analysis

established the unidimensionality of this study’s items. n the case of the

measurement scales for this study, all the constructs provided Cronbach’s

coefficient alpha above the acceptable level of 0.60 (Morgan & Griego, 1998) as

shown in Table 4.41.

Reliability and Validity Values Acceptable limits

Cronbach’s alpha 0.84 >0.7 (Hair et all.)

The Composite Reliability (CR) 0.936 0.70

(Carmines and Zeller, 1988)

The Indicator Reliability (IR) All constructs

greater than 0.5

> 0.5

(Bollen, 1989).

The convergent validity

(Average Variance Extracted -

AVE)

0.79 >= 0.5

(Fornell and Larcker, 1981).

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4.12 THE SUMMARY OF THE STRUCTURAL MODEL

HYPOTHESES FINDINGS

TABLE 4.42

THE SUMMARY OF THE STRUCTURAL MODEL HYPOTHESES

FINDINGS

HYPOTHESIS

NO

HYPOTHESES RESULT

H1

There is a relationship between tourism

development impacts and the community

stakeholders’ participation.

Accepted

H2

There is a relationship between tourism

development impacts and the support for rural


Rejected

H3

There is a relationship between community

participation and the support for rural

destination competitive strategies

Accepted

H4There is a relationship between economic

impacts and tourism development impacts.Accepted

H5There is a relationship between socio-cultural

impact and tourism development impacts.Accepted

H6There is a relationship between political

impacts and tourism development impacts.Accepted

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4.13 THE SUMMARY OF THE SUB HYPOTHESES FINDING –DEMOGRAPHIC PROFILE

TABLE 4.43THE SUMMARY OF THE SUB HYPOTHESES FINDINGS

DEMOGRAPHIC PROFILE

HYPOTHESISNO SUB HYPOTHESES RESULTS

H7

There is no significant difference between maleand female with respect to communityparticipation, tourism support and overallcommunity satisfaction in tourismdevelopment.

Accepted

H8There is no significant difference betweentourism related and non-tourism relatedbusiness with respect to tourism support.

Accepted

H9There is no significant difference betweencloser to the destination or far away withrespect to tourism support

Rejected

H10

There is no significant difference among agegroup of the community people with respect tocommunity participation in Tourismdevelopment

Rejected

H11There is no significant difference amongoccupation of the community people withrespect to community participation

Rejected

H12There is no significant difference amongmarital status of the community people withrespect to community participation.

Rejected

H13There is no significant difference among lengthof residency of the community people withrespect to community participation

Rejected

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H14There is no significant difference between agegroup of the community people with respect tooverall community satisfaction

Rejected

H15There is no significant difference among lengthof residency of the community people withrespect to overall community satisfaction

Accepted

H16There is no significant difference between agegroup of the community people with respect totourism support strategies

Rejected

H17There is no significant difference amongoccupation of the people with respect to tourismsupport strategies

Rejected

H18There is no significant difference amongeducation qualification of the people withrespect to tourism support strategies

Rejected

H19There is no significant difference betweenlength of residency with respect to tourismsupport strategies

Rejected

H20There is no association between years ofresidency and support for tourism

Rejected

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4.14 DATA ANALYSIS OF FOCUS GROUP INTERVIEW

4.14.1 Stakeholders Views on the Community Participation Implementation

Stakeholder interviews identified three problems in the community

participation processes in Karaikudi. The first relates to government control in

the decision-making processes. Excessive control by the government limited the

public involvement in the decision making process.

One of the government officers (Respondent 6) explained: ...if the public

is not satisfied with the plan they can make an enquiry to the State Planning

Committee. That was the highest level of participation in any development plan

in this country...even though, the state planning committee considered the

enquiry, the committee was still free to make a decision which they held to be

relevant. Fortunately, the residents understood how the decisions were made.

One of the community leaders (Respondent 12) stated his regrets: The

decision was made at the top level of administration without any involvement

from the local level. Even when the government officials went to the local level,

the approach used was not effective because we were not able to be actively

involved. Second, the weaknesses of the existing participation approach were

another major concern for most of the interviewees.

A community leader (Respondent 13) explained his views on that

situation: ― the priorities given in the participation process was just to inform

the residents but not to look at their response...actually, some of the residents

had objections but the problem was that they didn‘t have proper means for

184

expressing their objections. We were only involved in the early stages of

participation.

The officer (Respondent 6) remarked how the limitation exists: ―One of

the failures was the consultant carried out the household survey among the

community and they claimed that was public participation but it was only a one-

way communication approach. I mean the residents just filled the questionnaire

without having a discussion with the consultant to draft the plan together.

Finally, the attitude of residents also contributed to the ineffectiveness and low

response to the public participation process. The government officials blamed the

residents’ negative attitudes for not participating in the involvement process.

One of the government officers (Respondent 23) explained: ―The

residents did not participate because of their attitude; people will not react

unless something happens...they just wait to see what will happen to the

development before giving their feedback. However, the community leaders

claimed that the residents were not involved because of insufficient information.

They stressed that the government needs to inform and educate the residents

prior to any participation process.

One of the community leaders (Respondent 24) explained: ―The

residents were not involved because they don’t know anything about the

project...it is so frequent for us to find out about any project only after they had

started their work...

The NGO representative in a contrary statement blamed the government

for not educating the residents, he stated that: We have insisted the state and

local government to educate local community about rural tourism development,

185

the benefits to get involve and the consequences from the development. We

suggest them to organise more seminar for local community.

4.14.2 COMPARING THE RESIDENTS AND STAKEHOLDERS VIEWS

In a comparison of the findings, the quantitative and qualitative results show that

the three main problems of the participation process are as follows:

1. Government control in the decision making process. This issue was

influenced by the administration system and bureaucracy constraints. The

legislation limitation was also a major issue since many of the important

regulations and procedures were designed to maintain government control.

2. The implementation weaknesses resulted in the simplicity in the existing

participation approach. The level of knowledge among the government officials

also contributed to these problems.

3. Residents’ attitudes. Some of the residents had a negative attitude towards

the government program and the participation process. However, the significant

findings were that the limited information of the participation processes and the

level of education caused those problems. Since the limitation of information

decreased the number of participants, a low level of education resulted in the

failure to increase the quality of comments or suggestions.

Despite of the problem, the majority of respondents supported a greater

involvement for future public participation processes. Survey results show that

most of the respondents want to have more information (84%) and take part in

the consultation process (83%). Although the current practice in Karaikudi does

not include the participants in the decision-making process, the respondents want

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to be involved in the decision-making process (76%). They want to share the

responsibility in making the decision (78%) and more than half of the

respondents (54%) want to have complete control in the decision-making

process. However, the stakeholders reacted differently to the survey respondents,

regarding the suggestion of greater public involvement. Most of them suggested

that several aspects should be considered before the residents could be involved

at higher levels of participation.

A government officer (Respondent 2) stated: - we must educate the public

about the participation process and what they should do when they come to

participate. However, I think at this moment our citizens are not ready for a

higher level of involvement yet, maybe in the next 5 or 10 years. The highest

level they can make a contribution is at the consultation level.

Community leaders (Respondent 21) supported this position: ―I think

our community is only ready to be involved at the consultation level because we

have to consider their level of education and many of them still cannot

understand the purpose of the participation itself. What we need to do is to

educate them and after that we can think about the next level.

However, another government officer (Respondent 4) explained that the

problem not only existed among the residents but also within the government

staff: ―We at the government level were also still in the learning process

especially within local government, because we need to train and expose staff to

the participation process.

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CHAPTER V

CONCLUSION AND DISCUSSION

5.1 INTRODUCTION

This research study was conducted to theoretically develop and

empirically test a structural equation model of support for the tourism destination

from the tourism stakeholders’ perspective. The proposed hypotheses that

attempted to identify the structural relationships between the three constructs in

the model were examined through a series of analyses in AMOS. This chapter

provides the findings and conclusions of the study in relation to its secondary

objectives, hypotheses and research problem. The sub hypotheses identified in

the report are tested by applying student’s t-test, one way ANOVA, chi-square,

correlation tests, and regression tests by applying SPSS version 16.

The important principle of this study was that the support of tourism

stakeholders for tourism planning and development is a key element for the

successful operation, management, and long-term sustainability of tourism

destinations. Tourism stakeholders’ attitude, knowledge and experiences in

tourism management and industry, professional involvement and participation in

tourism planning and development, and their long-term community observation

and interactions have played an important role in a tourism destination

management. Therefore, their perceptions, attitudes, and behaviors regarding

tourism management and the tourism industry were major sources of testing the

proposed structural model and hypotheses.

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5.2 DISCUSSION OF THE RESEARCH FINDINGS

5.2.1 General Findings and Discussion

This study overviewed a theoretical background and empirical studies that

exist in the literature in an attempt to cover studies related to the research

problem. The objective of the study was to develop a theoretical model about

stakeholders’ support for tourism destination and to empirically test

interrelationship between the various constructs that are likely to affect

community participation in tourism development and their support of destination

competitive strategies (endogenous constructs). The exogenous construct

(tourism development impact) includes Economic impacts, Socio-cultural

impact, Environmental impact and political impact. The structural model of

support for rural tourism destination also addressed the influence of tourism

development impacts and community participation on stakeholders’ support of

tourism destination.

Based on convenience sampling method, with the total usable sample

size 320 the respondents were surveyed from very diverse tourism stakeholder

segments, including government authorities; tourism related and not related

tourism businesses, tourism agencies, residents, tourists, tourism faculty and

students. The results also showed that the survey questionnaires were collected

from a wide range of geographically distributed areas covering the entire places

of Karaikudi.

Based on the theoretical review and empirical research, all measurement

scales for each construct of the proposed model were developed and utilized to

investigate the relationships between the constructs. An assessment of reliability

189

and validity of the measurement scales revealed that the measurement scale for

each construct was reliable and valid in terms of the internal consistency and

accuracy of what they intended to measure. The newly developed measurement

scale for community participation, which was composed of 8 items, generated a

Cronbach’s coefficient’s alpha of 0.89. This indicates that this measurement

scale was reliable in assessing stakeholders’ wish for involvement in community

decision- making processes about tourism planning and development.

Structural equation modeling was used to analyze the fit of the proposed

theoretical model. First, exploratory factor analysis (EFA) was conducted to

tourism development impact (TDI) construct to condense the measurement

scales. Secondly, confirmatory factor analysis (CFA) was conducted to refine the

predicted relationships of the observed indicators to the constructs. The multi-

dimensionality of each construct was confirmed and the reliability for each

construct was calculated. The reliability scores were: economic impact (.91),

socio-cultural impact (.84) environmental impact (.89), political impact (.86),

community participation (.89), and Stakeholders’ tourism support (.84). All these

reliabilities exceeded the recommended level 0.7 (Hair et al. (1989).

5.2.2 DEMOGRAPHIC CHARACTERISTICS OF THE RESPONDENTS

The respondents comprised male (55.6 %) and female (44.4 %), due to

socio-cultural constraints; females were less willing to participate in the survey.

Age groups have been recoded after merging small segments; the results showed

that 41.9 % of respondents were aged between 25 and 44 years, followed by age

ranges of 15-24 years (27.2%), then 44-65 years (25.6%), and 65+years

(5.3%).The results indicated that the majority of respondents (41.9%) were

middle-aged (between 25 and 44 years old).

190

Education levels of tourism stakeholders showed that 37.8% of

respondents had secondary level school education, 30.6% had higher

qualification, 30% elementary education while 1.6% are uneducated. This

implies that the majority of respondents (37.8%) had secondary level school

education.

In terms of respondents’ employment, it was found that 41.6% of the

respondents were engaged in self-employment, the government employs 6.2% of

respondents and 15.0% are employed by private sector organisations. The

students constitute 14.4 %, house-wives 7.2%, and the retired people were 4.7%.

The self help groups were 4.4% and the unemployed people were 6.6%.

From the monthly income level of the people, 40.9% have income

between Rs 5001 and Rs 10,000, followed by 24.7% less than Rs 5000. Then

20.6% of the people have Rs10,001 and Rs 15,000 and only 13.1% were above

Rs 15,000.From a marital status perspective, 61.6% of respondents were married,

and 30.3% were single. The widows and divorced respondents would constitute

only 8.1% of total respondents. 58.1% of the respondents had their family

members 4-6. Family members not more than 3 accounted for 31.6%. Only

10.3% of the respondents had their family members above seven.

In terms of respondents’ average length of residency in their place, thenominal values revealed that 32.8% of respondents were residents of the same

place and living there for more than 20 years, followed by 6-10 years (21.2%).

17.2% of the respondents were living between 11-15 years and nearly 14% of the

respondents were between 0-5 years and 16-20 years. These results revealed how

closely the people are attached to their communities and are not frequent movers.

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In terms of residence close to the tourist spots, 51.2% of the respondents

were living far away and 48.8% were living very close to the tourist spots. Of the

total respondents, 72.2 % considered themselves as working with non-tourism

related organisations; however, the remaining percentage was related directly or

indirectly to the tourism industry.

5.2.3 DIMENSIONS OF TOURISM DEVELOPMENT IMPACTS OF

RURAL TOURISM.

The Kaiser-Meyer-Olkin (KMO) value which is a measure of sampling

adequacy is found to be 0.846, which indicates that the sample was large enough

to perform Exploratory Factor analysis. That is, a 10 to 1 ratio of the sample size

(N=320) is commonly found acceptable (Hair et al., 1998). The results of the

Bartlett’s Test of Sphericity are also significant, which indicates that the factor

analysis processes are correct and suitable for testing multidimensionality.

The 30 items were exposed to factor analysis to identify the underlying

factors, and latent root criterion (eigenvalue) value of above 1.0 (Pett et al.,

2003) and a factor loading of 0.40 were used as a benchmark for including items

in a factor. EFA was performed on the sample using the 30 variables related to

the Tourism Development Impacts. From EFA, four factors Economic impact

(EC), Socio Cultural impacts (SC) Environmental impacts (EN) Political impacts

(P) were extracted accounting for 63.8 percent of the total variance explained. 28

items loaded properly (Factor loadings>0.4). Two items, namely “Increase in

awareness on the importance of the site” and “Improved Solid waste

management facilities like the garbage disposal system” were removed because

they did not load good (Factor loading less than 0.4)on any of the factors. The

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Factor loadings are presented in the Table 4.6. Confirmatory factor analysis

(CFA) loadings also suggest that all the items taken for scale construction qualify

to develop the scale. The four factors are labeled as below.

Factor 1, labeled ‘Economic Impact (EC)’, accounted for 17.796 percent

of variances with 10 items. This factor shows the issues related to job

opportunities, income generation, and promotion of handicrafts. The item having

the highest loading was ‘Increases job opportunities’ followed by ‘Increase in

income generation, and promotion of handicraft items’ and ‘common platform to

sell’.

Factor 2, ‘Socio-Cultural Impact (SC)’ accounted for 14.858 percent of

variances with 12 items. The item having the highest loading was ‘Tourismcauses changes to the traditional culture’ followed by ‘cultural exchange between

tourists and residents’, then ‘tourism has created Mobilization of women

artisans’.

Factor 3, ‘Environmental impact (EN)’, explained 10.432 percent of

variances with 4 items. The highest loading item in this component is

‘Improvement in natural beauty’ followed by Improvement in hygiene

conditions’ and ‘destroys the natural environment’.

Factor 4, ‘Political Impact (P)’ accounted for 20.714 percent of variances

with 2 items. The item having the highest loading was ‘Tourism brings political

benefits to society’ followed by ‘authority to control and restrictions’.

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5.2.4 IMPACT OF DEMOGRAPHIC CHARACTERISTICS ON

COMMUNITY PARTICIPATION

To analyze the impact of the demographic characteristics on the community

participation in tourism development, the researcher has applied student’s t test

ANOVA and arrived with the following findings.

a) Impact of Gender on Community Participation in Tourism Development

It was observed that there is no significant difference between male

and female with respect to community participation in the development of

tourism. Both male and female actively participate in tourism development.

b) Impact of age group on Community Participation in Tourism

Development

It was concluded that there is significant difference between age group

of the community people with respect to community participation in Tourism

development. The people with the age between 46-65 years show higher

participation in tourism development than people with the age groups 15-24

years and 25-44 years. The older people who are above 65 years show lower

participation in the tourism development.

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c) Impact of occupation on Community Participation in Tourism

Development

It was found that the government employee and retired people showed

less participation in tourism development. People working in private sector

and unemployed were participating more in the tourism development.

d) Impact of marital status on Community participation in Tourism

Development

It was concluded that there is significant difference between marital

status of the people with respect community participation. The divorced

people showed more participation in tourism development than the other

group of people who are staying alone and married ones. The separated group

of people showed less participation in tourism development.

e) Impact of marital status on Community Participation in Tourism

Development

The people who live more than 20 years are more participative in the

tourism development followed by 16-20 years of residents. The people who

are new to the place or whose length of residence is less than 10 years

showed less participation in tourism development.


OVERALL COMMUNITY SATISFACTION

a) Impact of gender on overall community satisfaction

The researcher has identified that there is no significant difference

between male and female with respect to overall community satisfaction.

195

Overall, both male and female are dissatisfied with the tourism development

in the area. They fell that even though they are the primary gainers from

tourism, they are also the ones who suffer most from its effects.

b) Impact of age on overall community satisfaction

It is concluded that there is significant difference between age group of

the community people with respect to overall community satisfaction. The

older people who are above 65 years were less satisfied when compared to all

other age groups of people. Their lives not dependent on rural tourism, but

the respondents thought rural tourism would be a good way for preserving

rural life.

c) Impact of length of residency on overall community satisfaction

It is found that there is no significant difference among length of

residency of the people with respect to community satisfaction. The people

are less satisfied with the tourism development in the area irrespective of the

period of residence.


TOURISM SUPPORT

a) Impact of gender on Tourism support

There is no significant difference between male and female with

respect to tourism support. Both male and female stakeholders support

tourism strategies in their destination.

196

b) Impact of age on Tourism support

The researcher has found that there is significant difference between

age group of the community people with respect to tourism support strategies.

The people with the age group between 15-24 years and above 65 years show

less support for tourism. The people with the age group between 25-44 years

show high support for the tourism Support strategies. The people with the age

group between 45-65 years neither support nor oppose the tourism strategies.

The younger generation people and elderly people are less supportive for

tourism than the middle aged people.

d) Impact of occupation on Stakeholders’ Tourism Support

It is observed that there is significant difference among the occupation

of the people with respect to tourism support strategies. The self help groups,

housewives and unemployed people showed more support to tourism

strategies. Retired people and the students are less supportive for the tourism

support strategies. People employed in government and private sectors and

retired people shows medium support for the tourism in the area.

d) Impact of education on stakeholders’ Tourism Support

It is found that the people who have the elementary education were

more supportive for the tourism development in their area than the people

with higher qualification. The uneducated people show less support for


e) Impact of Nature of Business on stakeholders’ Tourism Support

The researcher has identified that there is no significant difference

between tourism related or non tourism related business with respect to

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tourism support. They stands neutral i.e., they neither support nor oppose

tourism in their area.

f) Impact of length of residency on stakeholders’ Tourism Support

It is concluded that there is significant difference among length of

residency of the people with respect to tourism Support strategies. The people

who live more than 20 years are more supportive for the tourism development in

their area. The people who are new to the place or whose length of residence is

between 0-5 years show less support for tourism development.

g) Impact of closer to the destination or far away on Tourism Support

It was found that there is significant difference between closeness to

the destination and faraway from the destination with respect to tourism

support. The people who are very close show more support than the people

who are far away from the destination. This result was quite contradictory

with the findings of Harrill (2004). In his research he found that residents

who live close to the core of tourism activity have more negative attitudes

towards tourism development. Harrill and Potts (2003) investigated the

relationships between neighborhood, economic dependency, and tourism,

finding that those neighborhoods close to the tourism core had the most

negative attitudes towards tourism while neighborhoods further away

perceived tourism more positively.

198

5.3 FINDINGS OF STRUCTURAL EQUATION MODELING

A structural equation modeling was used to test the hypotheses proposed

in this study in an attempt to identify the structural relationships between

dependent and independent constructs. Five of the six proposed relationships

within the three major hypotheses were strongly supported, based on the

outcome of the final structural model. Those hypotheses that were supported

generated a significant level of critical ratio (t-value) and standardised coefficient

scores. The following discussion presents the findings for each hypothesis.

1) Influence of tourism development impacts on community participation.

The hypothesis H1 proposed that tourism development impacts (economic,

social-cultural, environmental and political,) influence stakeholders’

participation in community decision-making processes. The outcome of SEM

analysis strongly supported the hypothesis. . The findings related to H1 indicated

that when community members feel that they are negatively affected by tourism

developments in their region, they are more likely to call for a greater

participation in planning and decision-making processes. The person

encountering negative socio-cultural impacts is increasing due to rising inbound

and domestic tourist numbers in karaikudi.

(2)Influence of tourism development impacts on tourism support The

‘tourism development impacts’ constructs (H2) held significant negative

relationships with the construct of ‘tourism support’. This finding was consistent

with the previous studies results which concentrated only on the environmental

and political benefits to tourism development (e.g. Davis et al., 1988; Lankford

& Howard, 1994). However, the findings also contradicted those studies which

199

demonstrated that if tourism stakeholders perceived economic benefits and

socio-cultural from tourism activities, they were more likely to support further

tourism development (e.g. Jurowski, et al., 1997; Ko & Stewart, 2002; Perdue et

al., 1987; Yoon 2002; Yoon et al., 1999, 2001). Hence, it is likely to expect

stakeholders to support tourism that maximize the economic benefits and social

to them. It was evident from the empirical data that the younger generation

people and elderly people are less supportive for tourism than the middle aged

people.

(3) Influence of community participation on tourism support It was

hypothesized in H3 that tourism stakeholders who have a desire and interest in

participating in tourism planning and benefits are more likely to support tourism

development. The results of the SEM analysis supported the hypothesis. In

addition, the results showed a significantly strong positive relationship between

the constructs ‘community participation’ and ‘stakeholders’ support for

destination competitive strategies’.

(4) Influence of ECI,SCI,PI on tourism development impacts The findings

confirmed the existence of a significant relationship (H4,H5,H6) between

‘economic impacts’, ‘socio-cultural impacts’ and ‘political impacts’ and as a

factor of TDI construct (e.g. Goudy, 1977; Jurowski et al., 1997; More & Graefe,

1994;Um & Crompton, 1987), Meanwhile, the study’s findings did not show any

relationship between the ‘environmental impacts’ construct as a construct of

‘tourism development impacts.’ After excluding the environmental impact items

during the CFA exercises, due to their loadings on more than one factor, three

development impact indicators emerged: socio-cultural, economic, and political.

These indicators provided an acceptable goodness-of-fit to the model. This

200

shows the importance that stakeholders place on socio-cultural matters. In fact,

tourism officials at both the Ministry of Tourism and private businesses stressed

the importance of culture and stakeholder’s involvement in decision making for

promoting karaikudi as a tourist destination.

5.4 CONTRIBUTIONS AND IMPLICATIONS OF THE RESEARCH

FINDINGS

This research suggests several theoretical contributions, new insights to

methodological approaches and practical implications.

5.4.1 Theoretical contribution

The various gaps in the tourism literature that specifically dealt with the

topics of the relationship between stakeholders’ attitudes and support for tourism

development, stakeholders’ participation, and destination competitiveness. Thisresearch attempted to close those gaps. The study advances the tourism literature

by introducing conceptual framework (model) explaining the relationship

between tourism development impacts, community participation and support for

tourism destination competitiveness from the stakeholders perspective. This

conceptual model will contribute new knowledge to the area of rural tourism

research. This study supported the majority of the hypothesized relationships.

5.4.2 Utilization of SEM for key constructs relationship testing.

This research used the structural equation modeling (SEM) method and

AMOS software in data analysis. There is little tourism literature using this

method in rural tourism research. Thus, this study contributes by expanding the

use of SEM in analyzing empirical data in the rural tourism discipline in the

rigorous testing of relationships between key constructs. This study is one of few

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recent studies that have attempted to explain the relationships between different

perceived tourism development impacts, community participation and support

for destination tourism planning, development and competitive strategies.

5.4.3 Development of measures and scales.

A number of scale items were developed to test the community

participation construct empirically. Scale development for this construct was one

of the primary purposes for this research. Therefore, this study contributed

methodologically to the tourism literature and stakeholders’ theory by

developing a scale, which could be used in consequent research to substantiate

the arguments proposed in this study. Therefore, researchers can replicate this

scale in different settings or destinations for validation.

5.4.4 Managerial implications

Findings provide some guidance to tourism planners, developers, and

policy decision-makers to better evaluate and understand which tourism

resources and attractions key stakeholders preferred to see developed (e.g.

development of nature-based tourism, development of small independent

businesses, and development of cultural or historic-based attractions). These

results are likely to help tourism stakeholders and marketers to collect

information and plan appropriate competitive strategies based on the tourism

attractions they prefer to develop before the implementation stage. For the local

communities, stakeholders’, rural local official entities, public and privateservice providers, the anticipated outcomes should offer an insight into the

potential for rural area sustainability to help to provide a good rural experience

and offer a good level of service quality.

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For the tourists, if they perceived the experience to be beyond their

expectations, then they will be satisfied and trust in the local rural tourism

population, entities, and facilities. They will be more inclined to return to the

place or will try to find a similar rural tourism experience. Thus, the overall

image will be positively encoded in their minds.

5.5 SUGGESTIONS AND RECOMMENDATIONS

5.5.1 General suggestions

The rural communities have the potential resources, ability to attract and the

opportunity to exploit the growing tourism industry. Tourism enhances the

quality of life for local residents.

1. New restaurants and cottages can enhance recreation and entertainment

opportunities for the local residents.

2. Rural tourism development can give rise to several new economic

activities, more demands, competition for services and some times more

crime. With the arrival of rural tourism, regions will not be the same place

as in the past.

3. To develop the rural tourism, a goal has to be set for the entire

community.

4. Ministry of tourism should allocate funds for promoting rural tourism.

5. The government should encourage every state to involve the local people

in the rural areas to participate in tourism related projects, which may

preferably be formulated by the tourism department officials in

consultation with local people and NGOs. These projects could be in the

nature of providing glimpse of the village ambience to the tourists with

local cuisine with local art and culture.

6. The people should be dress in local costumes.

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7. Moderate, but clean, accommodations for tourists should be constructed

by the villagers in traditional design and architecture.

8. A democratic movement should be formed which helps people at all

levels to participate in tourism development.

9. The need for education and proper understanding for both tourists and

local people is necessary for tourism development .The villagers not only

have to educate themselves but they have to understand Hindi to interact

with the Indian customer and English to communicate with the foreign

customers.

10. The guide should be intelligent to handle different type of tourist, good

communication skill and good rapport building attitude

5.5.2 Suggestion from findings

Since rural tourism destinations involve multi-faceted components of

natural/cultural tourism resources and a multiplicity of man-made tourism

businesses, a systematic analysis and understanding of stakeholders’ attitude and

perceptions for tourism support destination competitiveness is required.

1. Increasing the education level of residents to understand their right and

need for greater participation in the decision-making process.

2. The tourism destination management organizations may need to play an

important role as facilitators between local government and agencies for

tourism planning and development.

3. The development of the leadership of destination management

organizations for local government and agencies, to make an extensive

use of team work in all initiatives.

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4. Additionally, the establishment of effective linkages between local

government and agencies was recommended in order to improve

destination competitiveness in the long run.

5. The findings have many arguments that have been presented to support

and oppose rural tourism development. The pros and cons need to be

carefully considered by local villagers while considering rural tourism as

an economic diversification strategy. Argument in support of tourism

includes new jobs opportunities and additional income begins injected

into the local economy. It will attract outsiders who bring dollars to spend.

6. The government needs to focus on occupation training, handicraft

promotion to increase the villagers' quality of life by creating a healthy

environment.

7. From the findings destination competitive strategies supported by tourism

stakeholders may be associated with community participation. So a closer

examination of the community attitudes has to be carried out.

8. The success of rural tourism totally depends on the quality of service

provided to the tourist. To develop the manpower government has to take

initiative to open various short training courses for imparting knowledge

and skill, so that they can discharge their duties effectively.

9. Certain marketing programs and activities to overcome seasonality in

tourists’ visits should be considered. The development of strong linkages

with tourism wholesalers and retailers could be suggested. they should

ensure a stable work market for handicrafts and services developed

10. This study also found that the respondents (tourism stakeholders)

supported the development of advanced technology and information

systems. Thus, it is recommended to focus on information technology

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5.5.3 Recommendations

Rural tourism can help in creating sustainable development in some of our

villages in rural areas. Governments should recognize importance of rural

tourism at priority and help in creating healthy competitive business

environment. Government should try to generate data for decision-making bodies

investing for developing the human resources, create adequate facilities and

suitable infrastructure like accommodation, roads, airport facilities, rail facilities,

local transport, communication links and other essential amenities become

essential for development of rural tourism.

Some of the essential services required for rural tourism are

• Confidence building in safety and security.

• Sustainable growth plan for of rural tourism

• New technology investment.

• Business must balance economics with people, culture and environment.

• Development of local heritage and lifestyles.

• Improve traditional folk and festivals.

• Promote traditional handicraft products.

• Make the tourist to participate in local farming activities.

• Demonstrate the local folk dances and traditional rural practices to the tourists.

• Improve quality, value of rural tourism.

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5.6 LIMITATIONS AND DIRECTIONS FOR FUTURE RESEARCH

Limitations of this study were found and it was addressed to encourage

more sound research in the future. The major limitations derived from this study

are: 1) research scope and boundaries of the research, 2) selected observed

indicators and constructs, 3) lack of residents’ and tourists’ opinions, 4) limited

analysis of performance of destination competitive strategies 5) longitudinal

characteristics,

This study investigated the structural relationships of tourism destination

competitiveness from tourism stakeholders’ perspectives. The surveyed data

were only collected in the state of Tamilnadu. The scope of this study is limited

to Karaikudi (first identified spot) and results may not be regionally generalized.

This geographically limited survey may produce different results and

conclusions in terms of the magnitude and directions of relationships among the

constructs studied in this research. These findings cannot be generalized to all

rural spots in India, since tourism stakeholders differ with respect to perceptions

toward sustainable tourism development and destination competitive strategies.

Tourism stakeholders in other rural destinations may have different perceptions,

attitudes and behaviours in regard to tourism planning and development

approaches and strategies. Other rural tourism destinations and research scopes

should be explored to see if similar findings and results could be addressed.

Thus, it is suggested that data be collected from other competitive destinations to

Karaikudi to compare the obtained results.

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This study has been limited in its selection of observed indicators,

variables, and constructs. Even though vast literature review has been explored

there may exist further insights of destination competitiveness. Specific variables

and constructs that address international competitive strategies are limited. The

variables and constructs that are related to tourism information systems or

management information systems were abbreviated. In current tourism markets,

any tourism destination may need to pay more attention to advanced

technologies and techniques so that quality products and services are delivered

effectively and efficiently. Therefore, future studies may address destination

competitiveness that includes information technology and techniques such as

tourism information systems.

Another limitation to this study is related to the respondents. Generally, in

the tourism literature, tourism stakeholders may include residents, tourists, and

tourism experts such as people who are involved in organizations, associations,

destination management and attractions such as the respondents for this study.

The findings of this study are limited by the nature of the sample. The NGO’s

and international business people can also be included in the sample. Each

measurement scale for the constructs can be refined and validated. This study

might reflect ongoing transformations that could influence the relationships

between the constructs for future research. Moreover, a longitudinal analysis of

the structural model of tourism destination competitiveness may reveal what

competitive strategies do a better job in increasing destination competitiveness

and performance. This study also is limited in terms of longitudinal

characteristics. The data were collected for a three-month period (September to

November 2010).Consequently, the above-mentioned limitations should be

considered as essential and critical suggestions for future research. Future studies

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should take into account these limitations to produce more complete research

results.

Rural women in rural tourism are a most recent research interest in the

tourism literature than that of research about women and tourism in general.

Therefore the association between economic, socio cultural, political and gender

issues can also be included for further research.

Future research should test the model on several rural areas in India. This

comparison between various rural areas should enable one to detect common

features, as well as specificities, and refine the model, thus providing a broader

insight for both researchers and managers.

5.7 CONCLUDING COMMENTS

It is a fact that, there is a limited number of empirical studies on support

for rural tourism destination, this study developed and empirically tested a

structural equation model of tourism destination competitiveness and its relevant

constructs from the perspectives of tourism stakeholders. As a result the research

findings, it is hoped that this study has made valuable contributions to the

insights about support for rural tourism destination. From the results of the

comprehensive data analyses and procedures, this study may conclude that in

successful tourism development and management for destination

competitiveness, a more thorough understanding of tourism stakeholders’

attitudes and behaviors toward tourism should be made. As key players in

tourism destination competitiveness, support for destination competitive

strategies should be understood so that more competitive destination

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environments and positions can be achieved. Finally, even though the results and

findings of this study are somewhat exploratory in nature, it is expected that the

information produced and the implications of the study may be of help to tourism

planners, policy-makers, and marketers to build more competitive tourism

destination environments and positions in the state of Tamilnadu.

Rural tourism in India has great future, since it not only provides natural

elements of beauty but also the indigenous local traditions, customs and foods.

Direct experience with local people can be a unique selling proposition to attract

tourists. Every state in India has some unique handicraft, traditions and foods.

The Rural tourism should not go for a mass marketing. Rural tourism should

develop different strategy for different segment to make it successful.

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APPENDIX -1

RESEARCH ON RURAL TOURISM

Part- A- Demographic Profile

1. Gender: Male Female

2. Age Group: 15-24 Years 25-44 Years 44-65 years > 65 years

3. Educational Qualification: Elementary Secondary Higher qualification

4. Occupation: Self-employed Employed in government

Self help group Employed in private sector

Retired Housewife Student Unemployed

5. Monthly income of your family:

< Rs. 5000 Rs.5001 to Rs.10000 Rs.10001 to Rs.15000

Rs. 15001to Rs.25000 > Rs. 25001

6. Martial status: Single Married Separated / Divorced

Widowed

7. Size of the family: 1-3 4-6 7-9 10&above

8. Length of Residency:

0-5 years 6-10 years 11-15 years 16-20 years >20 years

9. Nature of business: Tourism related Non-tourism related

10. How close your residence from the tourist spot: Very close

Far away

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Part B- LOCAL COMMUNITY AND EXPERTS ATTITUTE

5. Strongly Agree 4. Agree 3. Neither agree nor Disagree 2.Disagree 1. Strongly Disagree

Se.No Part- I Tourism Development ImpactsEconomic Impact

1. Tourism increases job opportunities for thelocal people

1 2 3 4 5

2. Increase in income generation for local people,artisans and small businesses

1 2 3 4 5

3. Wider promotion of handicraft items made inthe village

1 2 3 4 5

4. Development of common platform for craftspersons to display and sell their local arts andcrafts

1 2 3 4 5

5. Local labour, technology and resources beingoptimally utilized

1 2 3 4 5

6. Tourism has created high investment,development, and infrastructure

1 2 3 4 5

7. Tourism creates more jobs for outsiders thanfor local people.

1 2 3 4 5

8. Host community getting trained on differenttypes of hospitality management, cuisinepreparation, tourist handling

1 2 3 4 5

9. Collaboration with different businessinstitutions for market tie-ups.

1 2 3 4 5

10. Products are sold in the national andinternational markets

1 2 3 4 5

Socio-Cultural Impact11. Tourism causes changes to the traditional

culture of the community1 2 3 4 5

12. Tourism has encouraged a variety of culturalexchange between tourists and residents

1 2 3 4 5

13. Mobilization of women artisans in the activeparticipation in the tourism programme

1 2 3 4 5

14. Formation of activity based groups and selfhelp groups, benefiting women community

1 2 3 4 5

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15. Effective skill building of the womencommunity

1 2 3 4 5

16. Development of institution like Gurukulplatform to learners and teachers

1 2 3 4 5

17. Documentation of the crafts, arts and folk lore 1 2 3 4 518. Tourism benefits outweigh negative impacts 1 2 3 4 519. Tourism encourages a variety of cultural

activities by the local population (e.g., crafts,arts, music)

1 2 3 4 5

20. Tourism increases the availability ofentertainment (e.g., festivals, exhibitions, andevents)

1 2 3 4 5

21. Tourism provides an incentive for theconservation of historical buildings

1 2 3 4 5

22. Tourism has resulted in more crime rates 1 2 3 4 5Environmental Impact

23. Improvement in natural beauty of the village 1 2 3 4 524. Improvement in hygiene conditions 1 2 3 4 525. Construction of hotels and other tourist

facilities destroys the natural environment1 2 3 4 5

26. Tourism improves public utilities (e.g. roads,telecommunication) in the community.

1 2 3 4 5

Political Impact27. Tourism brings political benefits to society (eg.

democratic values, tolerance)1 2 3 4 5

28. The community should have authority tosuggest control and restrictions of tourismdevelopment in the country.

1 2 3 4 5

5. Strongly Agree 4. Agree 3. Neither agree nor Disagree 2.Disagree 1. Strongly DisagreePart II: Community Participation:

1. The community people require a shared visionabout tourism

1 2 3 4 5

2. I would be willing to attend communitymeetings to discuss an important tourism issue

1 2 3 4 5

3. The government usually consults us abouttourism planning

1 2 3 4 5

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4. The public lack power to participate andinfluence the decision making process

1 2 3 4 5

5. Public involvement in planning anddevelopment of tourism will lead to preservinglocal culture, traditions, and life style

1 2 3 4 5

6. Active Participation of the local community andyouth

1 2 3 4 5

7. I am willing to invest my talent or time to makethe community an even better place for visitors

1 2 3 4 5

8. I would be affected by whatever happens(positive or negative) in the community

1 2 3 4 5

5. Strongly Support 4. Support 3. Neutral 2.Oppose 1. Strongly OpposePart IV: Support for Tourism:

1. Development of heritage-based tourism 1 2 3 4 52. Development of cultural or historic-based

attractions (e.g. museums, folk villages, localhistoric sites, traditional markets).

1 2 3 4 5

3. Development of supporting visitor services(hotels, restaurants, entertainment, banks etc).

1 2 3 4 5

4. Development of small independent businesses(e.g. gift shops, guide services, campinggrounds).

1 2 3 4 5

5. Development of cultural and folk events (e.g.concerts, art and crafts, dances, festivals).

1 2 3 4 5

6. Development of infrastructure (roads,transportation, and access facilities) fortourists.

1 2 3 4 5

Part III: Overall Community Satisfaction:

1. What is the overall satisfaction rating about tourism development?

1. Highly Satisfied 2. Satisfied 3. Neutral 4. Dissatisfied 5. Highly Dissatisfied

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Part IV: Tourists’ perceptions (Tourists only):

1. How satisfied are you with this trip to karaikudi in general?


2. How would you evaluate the attractiveness of karaikudi as a ruraltourism destination?

1. Highly Attractive 2. Attractive 3. Neutral 4. Not Attractive 5. Not Attractive at all.

3. How about Local governments’ tourism planning & development?


4. Was this visit worth your time and effort?

1. Definitely worthy 2. Worthy 3. Neutral 4. Not worthy 5. Definitely not worthy

Thank you for filling out the survey

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Appendix- 2

LIST OF RURAL TOURISM SITES IN INDIA

States Sl.No.

Name of the Villages Unique selling proposition

1. Andhra Pradesh 1. Pochampalli, Nalgonda Cotton & Silk Sarees

2. Konaseema Village, East Godavari Eco-tourism (Coastal Development)

3. Puttaparthi, .Anantapur Culture (Spiritual life)

4. Chinchinada, East Godavari Eco-tourism (Coast development)

5. Srikalahasti, Chittoor Kalamkari work

6. Village Etikoppaka, Vishakhapatanam Wood Craft

7. Village Dharmavaram, Anantapur Handlooms & Craft

8. Village Kuchipudi, Krishna Culture & Dance form

9. Village Nirmal, Adilabad Paintings

2.Arunachal Pradesh 10. Village Rengo, East Siang. Culture and Bamboo Cane handicraft

11. Ligu village, Upper Subansiri Culture

12. Village Ego-Nikte. West Siang Culture

13. Village Nampong, Changlang Culture

3. Assam 14. Durgapur, Golaghat Bamboo Craft and Cuisine

15. Dehing-Patakai Kshetra, Tinsukia Culture and Eco- tourism

16. Sualkuchi in Distt. Kamrup Patta and Moga Silk weaving

17. Village Asharikandi, Distt. Dhubri Terracota Craft

4. Bihar 18. Nepura Village, Distt. Nalanda Tusser Silk weaving

5. Chhattisgarh 19. Village Chitrakote, Distt. Bastar Chitrakote Water falls

20. Village Chitrakote, Distt. Bastar Chitrakote Water falls

21. Nagarnar, Distt. Bastar Bell Metal/ Terracota

22. Kondagaon, Distt. Bastar Bell Metal/Terracota

23. Mana-Tuta, Distt. Raipur Adventure Tourism

24. Village Chilpi, Distt.Kabirdham Silk weaving and Baiga tribe cuilture

25. Village Odh, Distt. Raipur Terracotta

6. Delhi 26. Kotla Mubarakpur Historical

27. Nangli, Razapur, Delhi Historical

7. Gujarat 28. Heritage village at Tera Heritage

29. Village Hodka, Distt. Kachchh Mirror work/ Embroidery

30. Navagaon and Malegaon villages, Dang Culture & Eco-tourism

31. Nageshwar, Distt. Jamnagar Mirror Work and Heritage

216

32. Dandi Village, Distt. Navsari Mahatma Gandhi Heritage

8. Haryana 33. Jyotisar, Distt. Kurukshetra Dari weaving

9. Himachal Pradesh 34. Nagar, Distt. Kullu Topi and Shawl weaving

35. Paragpur, Distt. Kangra Valley Himachal Heritage

36. Village Baroh, Distt Kangra Gurukul Culture

10. Jammu & Kashmir 37. Village Drung, Distt. Baramula Adventure

38. Surinsar, Distt. Jammu Adventure (Trekking)

39. Gagangir, Distt. Srinagar Adventure

40. Village Pahalgam, Distt. Anantnag Pilgrimage

41. Village Jheri, Distt. Jammu Adventure

42. Village Akingaam, Distt. Anantnag Culture (Folk Dance)

43. Village Vasaknag Adventure

44. Village Dori Degair Cuture

45. Village Watlab, Distt. Baramula Adventure (Water Sports)

46. Village Agar Jitto, Distt. Udhampur Culture & Craft

47. Village Chahel & Sahakote, Baramula Gaba Saji Craft

48. Manasbal, Distt. Srinagar Carpet weaving

49. Village Rafiabad Craft

50. Village Nowgam Culture

51. Village Shar-Shalli Culture

52. Village Tegar Semor, Distt Leh Handloom & Craft

53. Village Marwari karool, Distt. Doda Pilgrimage

54. Wader Wader Bala, Distt Kupwara Culture

55. Village Bhawani ,Rajouri Culture

56. Village Naranag, Distt. Gandherbal Culture & Craft.

57. Village Hirpora, Distt Sophian Adventure (trekking)

58. Village Dandmoh, Distt Baramulla Kangri , basket making, carpet weaving

59. Village Gohan, Distt Baramulla Pilgrimage

60. Village Litter, Distt. Pulwama Pilgrimage11. Jharkhand 61. Amadubi Art “Pyatkar” painting

62. Deuridih, Distt. Saraikela Kharsawan Chhau Dance12. Karnataka 63. Kokkare Bellur, Distt. Bellur Eco-tourism

64. Attiveri Bird Sanctuary,Uttar Kannada Eco-tourism

65. Banavasi Distt., Uttar Kannada Stone machinery, Wood Carving and

Musical instruments

66. Anegundi, Distt. Koppal Banana Fibre Craft

67. Coorg, Distt. Kodagu Coffee Plantation

217

13. Kerala 68. Kumbalangi, Distt. Ernakulam Ethnic Cuisinetraditional boat carpentry

69. Arnamula, Distt. Pathanamthitta Mural Paining

70. Balrampur in Thiruvananthapuram Weaving of traditional sarees

71. Villege Kalady, Distt. Ernakulam Spices Village

72. Village Anakkara, Distt. Idukki Spice Village

73. Village Clappana Fishing

14.Madhya Pradesh 74. Chaugan, Distt. Mandla Lantana Craft

75. Pranpur, Distt. Ashoknagar Chanderi Sarees

76. Orchha, Distt. Tikamgarh Historical and Adventure

77. Amla, Distt. Ujjain Historical

78. Village Devpur, Distt. Vidisha Spiritual heritage

79. Seondha, Distt. Datia Craft on stone and wood

80. Budhni, Distt. Sehore Historical, Spiritual, Craft on Woodwork

15. Maharashtra 81. Sulibhanjan-Khultabad , Aurangabad Sufi tradition and Culture

82. Morachi Chincholi Farming

16. Manipur 83. Khongion, Distt. Thoubal Manipur Dance

84. Village Noney, Distt. Tamenglong Manipur Dance

85. Andro, Distt. East Imphal Bamboo Craft

86. Village Liyai, Distt Senapati Ethnic culture

17. Meghalaya 87. Village lalong, Distt. Jaintia Hills Adventure

88. Village Sasatgre, West Garo Hills Bamboo Craft

89. Village Mawlynnong, East Khasi Hills Eco-tourism

18. Nagaland 90. Mopunchupket, Distt. Mokokchung Shawl weaving

91. Avachekha, Distt. Zunheboto Tribal Culture

92. Changtongia, Distt. Mokokchung Tribal Culture

93. Leshumi, Distt. Phek Tribal Culture & Adventure

94. Thetsumi, Distt. Phek Tribal Culture

95. Kuki Dulong, Distt. Dimapur Tribal Culture

96. Longsa, Distt. Mokokchung Tribal Culture

97. Mitikhru, Distt. Phek Art &, Handloom

98. Chungli Yimti DisttTuensang Historical & Tribal Culture99. Zunheboto Village Craft /Handloom/ Culture100 Shena Old, Village Zunheboto Adventure (trekking and bird-watching)101 Longidang, Wokha Wood craft and carving

19. Orissa 102 Raghurajpur, Distt. Puri Stone Craft and Pattachitra

103 Pipli in Puri Distt. Applique work

218

104 Khiching, Distt. Mayurbhanj Folk Music, Stone Craving

105 Barpali, Distt. Bargarh Sambalpuri sarees

106 Hirapur, Distt. Khurda Historical

107 Padmanavpur, Distt. Ganjam Puppet Dance, Tiger Dance

108 Deuljhari, Distt. Angul, Spiritual

109 Gurukul of Konark Natya Mandap Stone Craft and Gurukul20. Puduchery 110 Village Alankuppam Craft21. Punjab 111 Boothgarh, Distt. Hoshiarpur Glass Work

112 Rajasansi, Distt. Amritsar Carpet weaving

113 Chamkaur, Sahib, Distt. Ropar Spiritual

114 Jainti Majri, Distt. Mohali Woodcraft

115 Village Chhat Phulkari Embroidery

22. Rajasthan 116 Neemrana, Distt. Alwar Historical

117 Samode Village, Distt. Jaipur Lac Work, Pepper painting, Gems stone

painting

118 Haldighati, Distt. Rajsamand, Historical

23. Sikkim 119 Lachen in North Distt. Rugs and Carpet

120 Chumbung, Distt. West Sikkim Eco-tourism (Home stay)

121 Tingchim, Distt. West sikkim Trekking, Bird watching

122 Maniram Bhanjgyang Culture

123 Village Rong Culture

124 Village Jaubari, Distt. South Sikkim Adventure & Eco- tourism

125 Village Tumin, Distt.East Culture

126 Village Srijunga Martam, Distt. West Culture

127 Village Darap, Distt West Sikkim Eco Tourism

128 Village Pastenga Gaucharan, East Sikkim Culture and Ethnic Lifestyle

129 Village Pendam Gadi Budang, East Sikkim Culture

24. Tamil Nadu 130 Kazhugumalai, Distt Thoothukudi Spiritual and Pottery making

131 Theerthamalai, Distt. Dharmapuri Historical

132 Karaikudi, Chettinadu, Distt.Sivaganga

Palm leave baskets, Jewelry,cuisine

133 Devipattinam Navbhashnam in

Ramnathpuram

Stone Carving

134 Thirukurungudi, Distt. Tirunelveli Historical

135 Thiruppudaimaurthur, Tirunelveli Historical

136 Village Kombai., Distt. Theni Spice

137 Thadiyankudissai, Distt. Dindigul, Spice Village

219

138 Village Vedanamalli, Distt.

Kancheepuram

Eco-tourism

25. Tripura 139 Kamlasagar, Distt. West Tripura Historical

140 Jampui Hills, Distt. North Tripura Eco-tourism

141 Durgabari, Distt. West Tripura Tea Gardens

142 Devipur, Distt. West Tripura Farming

143 Malayanagar, Distt. West Tripura Tribal Culture, Eco- tourism

144 Village Banabithi, Dist West Tripura Eco-tourism and tea gardens

145 Village Harijula, Dist South Tripura Eco-tourism

146 Village Kalapania, Distt Sonamara Religious

147 Village Sarsima, Distt Belonia Eco-tourism

148 Village Bagbari, Distt. Sadar Eco - Tourism

26. Uttarakhand 149 Jageshwar, Distt. Almora Spiritual

150 Agora Village (Dodital). Uttar Kashi Eco-tourism

151 Mottad& its satellite station, Uttarakashi Eco-tourism

152 Chekhoni Bora, Distt. Champawat. Adventure

153 Koti, Indroli, Patyur, Distt. Dehradun Eco-tourism

154 Mana, Distt. Chamoli Trekking Adventure

155 Village Sari, Distt. Rudraprayag Eco-tourism

156 Village Adi Kailash, Distt. Nainital Adventure

157 Padmapuri,Distt. Nainital Adventure

158 Nanakmatta, Distt. U.S.Nagar Spiritual

159 Tryuginarayan, Distt. Rudraprayag Spiritual and Adventure

27. Uttar Pradesh 160 Bhitar Gram, Distt. Rae Bareli. Historical Culture

161 Mukhrai, Distt. Mathura Folk Dance

162 Bhaguwala, Distt. Saharanpur Ban Grass Craft

163 Village Barara, Distt. Agra Handicraft

28. West Bengal 164 Ballabhpur Danga, Distt. Birbhum Folk Dance

165 Sonada Village, Distt. Darjeeling Heritage

166 Mukutmonipur, Distt. Bankura Sari weaving

167 Village Antpur, Distt. Hoogly Sari weaving

168 Village Kamarpukur, Distt. Hoogly Spiritual & Craft

220

Appendix- 3

SNAPSHOTS OF THE RURAL TOURISM

KARAIKUDI - CHETTINAD HOUSE FOR ARCHITECHURE

221

ARTISAN WOODEN WORK IN CHETTINAD

HERITAGE PLACES PALM LEAF PRODUCT

222

KARAIKUDI CUISINE

WOOD CARVING MARRIAGE FUNCTIONS

223

KANDANGI HANDLOOM SAREES ATHANKUDI HAND MADE TILES

GOLD & SILVER SMITH UTENSILS

224

VILLAGE GREENERY

VILLAGE FESTIVALS

225

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LIST OF PUBLICATIONS

PUBLICATIONS IN NATIONAL AND INTERNATIONAL JOURNALS

1. Yavana Rani.S and M.Jeyakumaran “Community participation in decisionmaking of Rural Tourism”, Prabandhan: Indian Journal ofManagement, Listed in EBSCO Database, Vol 3, No 3, March2010,.ISSN: 0975-2854, pp 32-36.

2. Yavana Rani.S and M.Jeyakumaran “An Empirical Study on StakeholdersSupport for Rural Tourism-A Case of Karaikudi, Tamilnadu, India”, AsiaPacific Journal of Research in Business Management, Listed inPROQUEST, Volume 2, Issue 7 (July, 2011), ISSN 2229-4104.

3. Yavana Rani.S and M.Jeyakumaran “An Empirical Study on ResidentsAttitude and Support for Rural Tourism Development-A case ofKaraikudi, Tamilnadu, India” Indian Streams Research Journal ImpactFactor: 0.2105, ISSN No: 2230-7850Vol II Issue XI Dec 2012.

4. Yavana Rani.S and M.Jeyakumaran “A Structural Model of Stakeholders’Attitude For Rural Tourism Development” accepted for publication inAPJIHT, Malaysian Journal.

PAPER PRESENTED IN INTERNATIONAL CONFERENCE

1. Yavana Rani.S and M.Jeyakumaran “A Structural Model OfStakeholders’ Attitude For Rural Tourism Development”, 4th Asia EuroConference 2012 in Tourism, Hospitality and Gastronomy’ TAYLOR’SUNIVERSITY, MALAYSIA, Nov 28-Dec-1, 2012.

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CURRICULUM VITAE (in Brief)

1 Name S.YAVANA RANI

2 Designation Research scholar

3 Official Address Kalasaligam University

Krishnan koil, Srivilliputtur

Virudhunagar District,

Tamilnadu, India.

4 Phone Mobile: 9486572737

5 E-mail ID [email protected]

6 Educational Qualification B.E, M.B.A, M.Phil

7 Total Teaching Experience

Industrial Experience

10 years

1 years

8 Research Articles Published 3- International level

1 - National Level

9 Paper presented in conference National – 12

International level - 4

(Tourism conference, Malaysia )

10 Special Lectures Delivered 3

11 Field of research studies Services Marketing

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