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ASSESSMENT OF CUSTOMER PERCEPTIONS
TOWARDS FRONTLINE SERVICE EMPLOYEES’
ROLE BEHAVIOURS
By
Phiangdao Chaoluck
A thesis submitted in fulfilment of the requirements for the
degree of Doctor of Philosophy
School of Marketing and Management
Adelaide Business School
The University of Adelaide
December 2016
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TABLE OF CONTENTS
KEY TERMS, DEFINITIONS AND ABBREVIATIONS ................................................. 19
ABSTRACT ............................................................................................................................ 25
DECLARATION.................................................................................................................... 27
LISTS OF REFEREED CONFERENCE PROCEEDINGS.............................................. 29
ACKNOWLEDGEMENTS .................................................................................................. 31
Chapter 1 INTRODUCTION ............................................................................................... 33
1.1 Frontline Service Employee and their Role Behaviours .................................... 34
1.2 Service-Roles and Expectations ......................................................................... 37
1.3 In-Role and Extra-Role Behaviours ................................................................... 39
1.4 The Importance of the Service Sector ................................................................ 40
1.5 Research Problems ............................................................................................. 41
1.6 Research Approach: Ontology, Epistemology, and Methodology Paradigms ... 42
1.7 Mixed Methods Research ................................................................................... 44
1.8 Outline of the Thesis ........................................................................................... 46
Chapter 2 LITERATURE REVIEW ................................................................................... 49
2.1 Service Quality, Customer Encounter, Satisfaction and Value .......................... 49
2.1.1 Services ............................................................................................................... 49
2.1.2 Service Quality ................................................................................................... 50
2.1.3 Service Experience ............................................................................................. 51
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2.1.4 Service Encounter ............................................................................................... 53
2.1.5 Customer Service Satisfaction ............................................................................ 55
2.1.6 Customer Value Perception ................................................................................ 58
2.2 Role and Frontline Service Employee Behaviours ............................................. 60
2.2.1 Role Theory and Roles ....................................................................................... 60
2.2.2 Role Behaviours ................................................................................................. 64
2.2.3 Service-Role and Expectations ........................................................................... 65
2.2.4 Service-Role Behaviours of Frontline Service Employee .................................. 67
2.2.5 In-Role Behaviours towards Customers ............................................................. 68
2.2.6 Extra-Role Behaviours towards Customers ........................................................ 70
2.2.7 Helping, Prosocial and Altruistic Behaviours .................................................... 74
2.3 Chapter Summary ............................................................................................... 81
Chapter 3 QUALITATIVE METHODOLOGY ................................................................. 85
3.1 Research Design for the Qualitative Research ................................................... 85
3.1.1 Phenomenological Interviewing ......................................................................... 86
3.2 Participant Selection ........................................................................................... 87
3.3 Semi-Structured Interviews ................................................................................ 89
3.4 Interview Question Design ................................................................................. 89
3.5 Data-Analysis Technique and Procedure ........................................................... 93
3.6 Chapter Summary ............................................................................................... 95
Chapter 4 QUALITATIVE DATA ANALYSIS AND DISCUSSION .............................. 97
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4.1 Theme Identification ........................................................................................... 97
4.2 Themes in the Behaviour of FSEs ...................................................................... 98
4.2.1 Theme One: Being an Expertise is Part of the FSEs’ Role ................................ 99
4.2.2 Theme Two: FSEs Meet the Job Requirement ................................................. 103
4.2.3 Theme Three: FSEs Show a Considerate Manner to Customers ...................... 105
4.2.4 Theme Four: FSEs Present a Personal-Involvement Expression ..................... 107
4.2.5 Theme Five: FSEs Show Empathy to the Customers ....................................... 110
4.2.6 Theme Six 6: FSEs Build Rapport with the Customers ................................... 114
4.2.7 Theme Seven: FSEs Help without Concern for the Duty Boundary ................ 116
4.3 Analysis and Categorising the Themes ............................................................ 119
4.4 Chapter Summary ............................................................................................. 121
Chapter 5 HYPOTHESES AND CONCEPTUAL FRAMEWORK ............................... 123
5.1 Research Hypotheses ........................................................................................ 123
5.1.1 Expertise ........................................................................................................... 124
5.1.2 Job Requirement ............................................................................................... 126
5.1.3 Considerate Manner .......................................................................................... 127
5.1.4 Personal-Involvement Expression .................................................................... 128
5.1.5 Empathy ............................................................................................................ 129
5.1.6 Rapport ............................................................................................................. 132
5.1.7 Helping without Concern for the Duty Boundary ............................................ 133
5.2 Conceptual Framework ..................................................................................... 135
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5.3 Chapter Summary ............................................................................................. 136
Chapter 6 QUANTITATIVE METHODOLOGY ............................................................ 137
6.1 Research Design ............................................................................................... 137
6.2 Unit of Analysis ................................................................................................ 138
6.3 Data Collection Method .................................................................................... 138
6.4 Pre-Test Study .................................................................................................. 139
6.4.1 Sampling ........................................................................................................... 140
6.4.2 Data Collection Procedure for Pre-Test ............................................................ 140
6.5 Main Study: A Financial Service Firm ............................................................. 141
6.5.1 Sampling ........................................................................................................... 141
6.5.2 Data Collection Procedure for Main Study ...................................................... 142
6.6 Questionnaire Design ....................................................................................... 143
6.6.1 Questionnaire Structure of Main Study ............................................................ 144
6.6.2 Scaling .............................................................................................................. 145
6.7 Operationalisation of the Constructs ................................................................ 146
6.7.1 FSEs’ Expertise ................................................................................................ 155
6.7.2 FSEs’ Job Requirement .................................................................................... 155
6.7.3 FSEs’ Considerate Manner ............................................................................... 156
6.7.4 FSEs’ Personal-Involvement Expression ......................................................... 157
6.7.5 FSEs’ Empathy ................................................................................................. 158
6.7.6 FSEs’ Rapport ................................................................................................... 159
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6.7.7 FSEs’ Helping without concern for the Duty Boundary .................................. 160
6.7.8 Customer Service Satisfactions ........................................................................ 161
6.7.9 Customer Value Perception .............................................................................. 161
6.8 Ethics and Information Confidentiality ............................................................ 162
6.9 Data Entry ......................................................................................................... 163
6.10 Data Analysis Plan ............................................................................................ 163
6.11 Chapter Summary ............................................................................................. 164
Chapter 7 DATA ANALYSIS ............................................................................................. 167
7.1 Description of Sample Groups ......................................................................... 167
7.2 Data Entry and Screening ................................................................................. 168
7.3 Normality .......................................................................................................... 169
7.4 Structural Equation Modelling Process ............................................................ 171
7.5 Measurement Model Validity Test: Confirmatory Factor Analysis ................. 172
7.5.1 Unidimensionality ............................................................................................ 172
7.5.2 Construct validity ............................................................................................. 172
7.6 Chapter Summary ............................................................................................. 190
Chapter 8 HYPOTHESIS TESTING................................................................................. 191
8.1 Measurement Models for FSEs’ Service-Role Behaviours .............................. 191
8.1.1 Role-Prescribed Behaviours: Testing the Expertise and Job Requirement
Constructs ......................................................................................................... 191
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8.1.2 Beyond Role Behaviours: Testing the Considerate Manner, Personal
Involvement, and Rapport Constructs .............................................................. 194
8.1.3 Helping Behaviours: Testing the Construct Helping without Concern for the Duty
Boundary .......................................................................................................... 197
8.1.4 CFA Model – All Independent Variables - First Model Step ........................... 198
8.1.5 CFA Model – All Independent Variables - Second Model Step ...................... 201
8.1.6 CFA Model – All Constructs ............................................................................ 203
8.2 Structural Models ............................................................................................. 206
8.2.1 The Structural Model Specification .................................................................. 206
8.2.2 The Structural Model Identification ................................................................. 207
8.2.3 The Structural Model Validity .......................................................................... 207
8.3 Structural Model – Modification Process ......................................................... 209
8.3.1 First Model ....................................................................................................... 209
8.3.2 Second Model ................................................................................................... 212
8.3.3 Third Model ...................................................................................................... 215
8.4 Hypothesis Testing and Discussion .................................................................. 217
8.5 Chapter Summary ............................................................................................. 221
Chapter 9 DISCUSSION AND CONCLUSION ............................................................... 223
9.1 Summary of Findings ....................................................................................... 223
9.1.1 Role-Prescribed Behaviours ............................................................................. 223
9.1.2 Beyond Role Behaviours .................................................................................. 225
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9.1.3 Helping Behaviours .......................................................................................... 227
9.2 Theoretical Implications ................................................................................... 227
9.3 Managerial Implications ................................................................................... 233
9.3.1 Focusing on Good Training .............................................................................. 234
9.3.2 Empowering FSEs with the Discretionary Independence ................................ 235
9.3.3 Recruiting Genuine FSEs ................................................................................. 235
9.3.4 Reviewing and Developing Policies and Infrastructure ................................... 235
9.4 Limitation and Future Research Directions ...................................................... 236
9.5 Conclusion and Overall Contributions ............................................................. 238
APPENDIX A: previous Studies of In-Role and Extra-Role Behaviours ....................... 243
APPENDIX B: MAIN STUDY QUESTIONNAIRE ........................................................ 245
APPENDIX C: SUMMARY OF PREVIOUS LITERATURE FOR MEASUREMENT
AND SOURCES OF SCALING TECHNIQUES ............................................................. 253
APPENDIX D: DESCRIPTION OF SAMPLE GROUPS ............................................... 261
D1. Description of Sample Groups ........................................................................................ 261
D2. T-Test Comparing between Genders and Frequency of Visiting the Bank in a Month of Sample
Groups ................................................................................................................................ 262
D3. The effect Size for Independent-Samples T-Test Calculation ........................................... 262
D4. One-Way ANOVA Comparing between Frequency of Visiting the Bank in a Month of Sample
Groups and Service Satisfaction/Value Perception ................................................................. 263
APPENDIX E: NORMALITY............................................................................................ 269
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E1. Case Processing Summary Table .................................................................................... 269
E2. Descriptives Table of Normality ..................................................................................... 270
E3. Tests of Normality Table ................................................................................................ 281
E4. Histogram of Variables ................................................................................................... 282
APPENDIX F: OUTLIERS ................................................................................................ 289
F1. 29 Extreme-Point Outliers .............................................................................................. 289
F2. Normality Descriptives Table Presenting only the Extreme Points of Outliers of Dependent
Variables ............................................................................................................................. 290
F3. Box-Plots of Extreme Outliers ........................................................................................ 292
APPENDIX G: HOMOSCEDASTICITY ......................................................................... 299
G1. Scatterplots of FSEs’ Expertise Affects Customers’ Service Satisfaction .......................... 299
G.2 Scatterplots of FSEs’ Role Behaviour Meeting their Job Requirement Affects Customers’
Service Satisfaction .............................................................................................................. 300
G.3 Scatterplots of FSEs’ Considerate Manner Affecting Customers’ Service Satisfaction ...... 301
G.4 Scatterplots of FSEs’ Personal-Involvement Expression Affecting Customers’ Service
Satisfaction .......................................................................................................................... 302
G.5 Scatterplots of FSEs’ Having a Rapport with Customers Affects their Service Satisfaction 303
G.6 Scatterplots of FSEs’ Helping without Concern for the Duty Boundary Affects Customers’
Service Satisfaction .............................................................................................................. 304
G.7 Scatterplots of FSEs’ Expertise Affects Customers’ Value Perception .............................. 305
G.8 Scatterplots of FSEs’ Role Behaviour Meeting their Job Requirement Affects Customers’
Value Perception .................................................................................................................. 306
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G.9 Scatterplots of FSEs’ Considerate Manner Affects Customers’ Value Perception .............. 307
G.10 Scatterplots of FSEs’ Personal-Involvement Expression Affects Customers’ Value Perception
............................................................................................................................................ 308
G.11 Scatterplots of FSEs’ Having a Rapport with Customers Affects their Value Perception .. 309
G.12 Scatterplots of FSEs’ Helping without Concern for the Duty Boundary Affects Customers’
Value Perception .................................................................................................................. 310
APPENDIX H: MULTICOLLINEARITY ....................................................................... 311
H.1 Verifications of Multicollinearity .................................................................................... 311
H.2 Verifications of Multicollinearity: Tolerance and VIF Conducted in Terms of Service
Satisfaction (SS) which is Dependent Variable ...................................................................... 313
H.3 Verifications of Multicollinearity: Tolerance and VIF Conducted in Terms of Value Perception
(VP) which is Dependent Variable ........................................................................................ 314
APPENDIX I: CORRELATION MATRIX FOR FINAL INDICATORS (AMOS) ..... 315
REFERENCES ..................................................................................................................... 317
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LIST OF FIGURES
Figure 5-1: Conceptual Framework ....................................................................................... 135
Figure 7-1: Measurement Model – Expertise ........................................................................ 176
Figure 7-2: Measurement Model – Job Requirement ............................................................ 177
Figure 7-3: Measurement Model – Considerate Manner ....................................................... 178
Figure 7-4: Measurement Model – Personal-Involvement Expression ................................. 179
Figure 7-5: Measurement Model – Rapport ........................................................................... 180
Figure 7-6: Measurement Model – Helping without Concern for the Duty Boundary ......... 181
Figure 7-7: Measurement Model – Service Satisfaction ........................................................ 182
Figure 7-8: Measurement Model – Value Perception ............................................................ 183
Figure 7-9: Construct Reliability and Average Variance Extracted (AVE) Formulas .......... 185
Figure 8-1: CFA Model – Expertise and Job Requirement ................................................... 193
Figure 8-2: CFA Model – Considerate Manner, Personal-Involvement Expression, and Rapport
................................................................................................................................................ 195
Figure 8-3: CFA Model – All Independent Variables - First Model Step ............................. 198
Figure 8-4: CFA Model – All Independent Variables - Second Model Step......................... 201
Figure 8-5: CFA Model – All Constructs .............................................................................. 203
Figure 8-6: First Model .......................................................................................................... 209
Figure 8-7: Second Model ..................................................................................................... 212
Figure 8-8: Third Model ........................................................................................................ 215
Figure 8-9: Hypothesised Model Tested ................................................................................ 218
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Figure 9-1: Relationships of Service-Role Behaviours of FSEs to Customers and the Firm 230
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LIST OF TABLES
Table 2-1: The Distinctions between In-Role and Extra-Role Behaviours ............................. 73
Table 2-2: Definitions of Prosocial Behaviour ........................................................................ 76
Table 2-3: Summary of Three Term-Comparisons .................................................................. 81
Table 3-1: Demographic Profile of Face-to-Face Participants ................................................ 88
Table 4-1: Theme Identification .............................................................................................. 98
Table 4-2: Themes by Participant ............................................................................................ 98
Table 4-3: Being an Expertise is Part of the FSEs’ Role ......................................................... 99
Table 4-4: FSEs Meet the Job Requirement .......................................................................... 104
Table 4-5: FSEs Show a Considerate Manner to Customers ................................................. 105
Table 4-6: FSEs Present a Personal-Involvement Expression to the Customers ................... 107
Table 4-7: FSEs Show Empathy to the Customers ................................................................ 110
Table 4-8: FSE Build Rapport with the Customers ............................................................... 114
Table 4-9: FSEs Help the Customers without Concern for the Duty Boundary .................... 116
Table 4-10: Theme Identification according to Category Classification of Service-Role
Behaviours ............................................................................................................................. 120
Table 5-1: Customer-Employee Rapport and Customer Satisfaction .................................... 133
Table 6-1: Measuring Customer Perceptions towards FSEs’ Expertise during Service
Encounter ............................................................................................................................... 147
Table 6-2: Measuring Customer Perceptions of FSEs Undertaking Job Requirement .......... 148
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Table 6-3: Measuring Customer Perceptions of FSEs Considerate Manner to Customers during
Service Encounter .................................................................................................................. 148
Table 6-4: Measuring Customer Perceptions of FSEs’ have Personal-Involvement Expression
during Service Encounter ....................................................................................................... 149
Table 6-5: Measuring Customer Perceptions of FSEs’ Empathy during Service Encounter 150
Table 6-6: Measuring Customer Perceptions of FSEs’ Having a Rapport with Customers during
Service Encounter .................................................................................................................. 151
Table 6-7: Measuring Customer Perceptions of FSEs’ Helping-Role Behaviour without
Concern for the Duty Boundary during Service Encounter ................................................... 152
Table 6-8: Measuring Customer Service Satisfaction ........................................................... 153
Table 6-9: Measuring Customer Value Perception ................................................................ 154
Table 6-10: Measuring Expertise ........................................................................................... 155
Table 6-11: Measuring Job Requirement ............................................................................... 156
Table 6-12: Measuring Considerate Manner ......................................................................... 157
Table 6-13: Measuring Personal-Involvement....................................................................... 158
Table 6-14: Measuring Empathy ........................................................................................... 159
Table 6-15: Measuring Rapport ............................................................................................. 160
Table 6-16: Measuring Helping without Concern for the Duty Boundary ............................ 160
Table 6-17: Measuring Service Satisfaction .......................................................................... 161
Table 6-18: Measuring Value Perception .............................................................................. 162
Table 7-1: Descriptive Statistics of Normality (99% Confidence Interval) .......................... 170
Table 7-2: Model Fit Indices and Standard Thresholds ......................................................... 175
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Table 7-3: Goodness-of-Fit Indices for Expertise ................................................................. 176
Table 7-4: Goodness-of-Fit Indices for Job Requirement ..................................................... 177
Table 7-5: Goodness-of-Fit Indices for Considerate Manner ................................................ 178
Table 7-6: Goodness-of-Fit Indices for Personal-Involvement Expression .......................... 179
Table 7-7: Goodness-of-Fit Indices for Rapport .................................................................... 180
Table 7-8: Goodness-of-Fit Indices for Helping without Concern for the Duty Boundary ... 181
Table 7-9: Goodness-of-Fit Indices for Service Satisfaction ................................................. 182
Table 7-10: Goodness-of-Fit Indices for Value Perception ................................................... 183
Table 7-11: Reliability, Validity, and Standard Indices ........................................................ 186
Table 7-12: Summary of CFA Model Testing for All Constructs ......................................... 189
Table 8-1: Goodness-of-Fit Indices for Expertise and Job Requirement .............................. 193
Table 8-2: Summary of CFA Model – Reliability and Validity Measures for Expertise and Job
Requirement ........................................................................................................................... 194
Table 8-3: Goodness-of-Fit Indices for Considerate Manner, Personal-Involvement
Expression, and Rapport ........................................................................................................ 196
Table 8-4: Summary of CFA Model – Reliability and Validity Measures for Considerate
Manner, Personal-Involvement Expression, and Rapport ..................................................... 197
Table 8-5: Summary of CFA Model – Reliability and Validity Measures for Helping without
Concern for the Duty Boundary ............................................................................................. 198
Table 8-6: Goodness-of-Fit Indices for Independent Variables - First Model Step .............. 199
Table 8-7: Summary of CFA Model – Reliability and Validity Measures Independent Variables
- First Model Step .................................................................................................................. 200
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Table 8-8: Goodness-of-Fit Indices for All Independent Variables - Second Model Step .... 202
Table 8-9: Summary of CFA Model – Reliability and Validity Measures for All Independent
Variables - Second Model Step.............................................................................................. 202
Table 8-10: Goodness-of-Fit Indices for All Constructs ....................................................... 203
Table 8-11: Summary of CFA Model – Reliability and Validity Measures for All Constructs
................................................................................................................................................ 205
Table 8-12: Standard Thresholds ........................................................................................... 208
Table 8-13: Goodness-of-Fit Indices for Structural Model - First Model ............................. 209
Table 8-14: Summary of Structural Model – CFA Estimates, Validity and Reliability – First
Model ..................................................................................................................................... 211
Table 8-15: Goodness-of-Fit Indices for Structural Model – Second Model ........................ 213
Table 8-16: Summary of Structural Model – CFA Estimates, Validity and Reliability – Second
Model ..................................................................................................................................... 214
Table 8-17: Goodness-of-Fit Indices for Structural Model – Third Model ........................... 216
Table 8-18: Summary of Structural Model – CFA Estimates, Validity and Reliability – Third
Model ..................................................................................................................................... 216
Table 8-19: Regression Weights and Summary of Hypothesis 1a – 7b ................................ 220
Table 9-1: Overall Contributions of the Study ...................................................................... 240
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KEY TERMS, DEFINITIONS AND ABBREVIATIONS
To provide clarity and to set certain terminologies for the context in which they were utilised
in this study, the definitions of selected terms are listed below.
Service quality:
“A measure of how well the service level delivered matches customer expectations
(Parasuraman, Zeithaml, & Berry, 1985: p. 42).” This thesis focuses on the service quality
provided by frontline service employees.
Frontline service employees (FSEs):
The FSEs have personal contact with the customers and so are considered as the face and the
voice of a service business (Elmadağ, Ellinger, & Franke, 2008). FSEs represent two actors,
being the representatives of a firm (Bettencourt & Gwinner, 1996) and representing for
themselves, but also focusing on their customers as well as their firm.
Service encounter:
A period of time in which FSEs and customers focus on a service (Carlzon, 2000). Apart from
embodying the firm, the FSE also represents his/her self. Thus, one side of the dyad in a service
encounter represents two actors.
Customer service satisfaction:
“The customer's response to the evaluation of the perceived discrepancy between prior
expectations (or some other norm of performance) and the actual performance of the product
as perceived after its consumption (Tse & Wilton, 1988: p. 204).”
Customer value perception:
Service value perception refers to the customer’s assessment of the differences between the
sacrifice and the level of quality of the service s/he received (Park, Park, & Dessouky, 2013).
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Perceptions of service value are not only a perceptual matter, but are also relative to past
experience. However, without a perception of value customers are also unlikely to return.
Role behaviours:
Role performance, or behaviour performance is the outcome of several forces (Levinson,
1959). Both internal and external stimuli and/or motive can arouse an individual to perform
role behaviour.
Service-role behaviours:
Both the service offering of the firm and the way in which the services are delivered can be
customised by FSEs (Bettencourt & Gwinner, 1996). FSE may undertake a role separate from
that required by the firm, but one which is more aligned to a customer.
In-role behaviours:
In service settings, in-role behaviours of FSEs may arise from explicit obligations as specified
in the service firm documents such as performance evaluation forms and job descriptions, or
from implicit norms in the workplace (Choi, Baek, & Kang, 2013; Liu, Liu, & Geng, 2013;
Tsaur, Wang, Yen, & Liu, 2014).
Extra-role behaviours:
Extra-role behaviours refer to FSEs positive, voluntary, and discretionary acts that go outside
the scope of role prescriptions (Kang, Stewart, Kim, & Lim, 2012; Liu et al., 2013; Raub &
Robert, 2010; Schepers, Falk, Ruyter, Jong, & Hammerschmidt, 2012).
Prosocial behaviours:
“Designate helping, sharing, and other seemingly intentional and voluntary positive behaviour for
which the motive is unspecified, unknown, or not altruistic (Ross, Patterson, & Stutts, 1992: p.
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94).” The behaviours that an individual performing prosocial behaviours benefits the society,
including oneself and others.
Altruistic behaviours:
“The act is unilaterally directed for the benefit of others and the bestower neither expects nor
expresses a desire for a comparable return (Millon, 2003: p. 20).” One characteristic aspect of
altruism is that people act altruistically without expectation of any external rewards (Eisenberg
et al., 1999).
Role-prescribed behaviours:
The services that the FSEs provide to meet customers’ basic need(s) and queries within their
duty statement (definition in this thesis, page 87 Chapter 4). In this thesis, the role-prescribed
behaviours include FSEs expertise and job requirement.
Expertise (EX):
The service role performance in which FSEs show their professional knowledge, required
skills, abilities, suggestions, providing recommendations, adaptability, giving advice and
quality of explanation, and competence during the process of service interaction (Barnes,
Ponder, & Dugar, 2011; Dagger & Sweeney, 2007; Lin & Hsieh, 2011; Stock & Hoyer, 2005).
Job Requirement (JR):
The performance standards set by the firms are explicitly based on customer expectations,
interests, and expectations (Liao & Chuang, 2004).
Beyond role behaviours:
Beyond role behaviours are those when the FSEs exhibit a personal positive feeling and attitude
towards their job and customers (definition in this thesis, page 87 Chapter 4). In this thesis, the
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beyond role behaviours comprised four themes: considerate manner, personal-involvement
expression, empathy, and rapport.
Considerate manner (CC):
The courtesy of FSEs involves integrity, politeness, consideration, kindness, being well
mannered, and friendliness (Chonko, 2015; Froehle, 2006; Lam & Zhang, 1999; Rego &
Cunha, 2008; Zaim, Bayyurt, & Zaim, 2010). For this thesis, the components of a considerate
manner are courteous and/or kind behaviour of FSEs towards the customer during a service
encounter (definition in this thesis, page 92 Chapter 5).
Personal-involvement expression (PE):
For this thesis, the employees have enjoyment, a positive attitude, job satisfaction, and are
personally connected with their jobs and service roles (definition in this thesis, page 93 Chapter
5).
Empathy (EM):
Refers to interpersonal process (Wieseke, Geigenmüller, & Kraus, 2012) of an individual to
sense and understand another’s feelings, thoughts, ideas, experiences, and perspectives (Pilling
& Eroglu, 1994; Wieseke et al., 2012). The Interpersonal Reactivity Index explains four
separate aspects of empathy: perspective taking, fantasy, empathic concern, and personal
distress (Davis, 1980, 1983). This thesis uses two of these four dimensions to explain the
empathy, namely perspective taking and empathic concern (page 95 in Chapter 5).
Rapport (RA):
“A customer’s perception of having an enjoyable interaction with a service provider employee,
characterised by a personal connection between the two interactions (Gremler & Gwinner,
2000: p. 92).” Rapport is an indicator of relationship quality (Delcourt, Gremler, van Riel, &
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van Birgelen, 2013). FSE is the key role in building and keeping relationships with customers
(Fatima, Razzaque, & Di Mascio, 2015).
Helping behaviours:
Helping behaviours are when FSEs volunteer to help customers outside of their duty boundary
(definition in this thesis, page 87 Chapter 4). In this thesis, the helping behaviour includes only
one theme, the performance of tasks that are outside of the formal tasks.
Helping without concern for the duty boundary (WC):
Helping behaviours are an action that provides benefit to a person(s) in need of aid and when there
is no prior promise to give a reward in return (Bar-Tal, 1982). Helping behaviours are a
voluntarily act. However, there is no guarantee that the recipient will give an external reward
in return.
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ABSTRACT
This thesis investigates the perceptions of customers towards service-role behaviours, both in-
role and extra-role. These two sets of role behaviours have been studied by a number of
researchers. Nevertheless, the definitions and distinctions in the role behaviours have received
considerable criticisms. Several studies explain that the boundary between both behaviours was
poorly defined and led to multiple interpretations. Differentiating in- and extra-role behaviours
must be emphasised owing to its importance for both academic and managerial contributions.
Role definition is also a powerful factor to encourage extra-role behaviours. Further, in
previous studies, both in-role and extra-role behaviours have been considered in the context of
employees and supervisors to improve FSEs’ performance to meet the firm’s interests. Very
few studies on FSE role behaviours are placed in the context of customers. The absence of a
research focus on customers’ perspectives is a reason why the distinction between in-role and
extra-role behaviours remain unclear. This thesis, therefore, aims to redefine and clarify the
distinctions between in-role and extra-role behaviours by involving the customers.
A mixed method approach was used to conduct this study. First, a qualitative study focused on
how FSEs consider firm regulations and rules, what factors drive them to perform role
behaviours and how they see their roles towards customers. This study for the first time reveals
that there is a three-category classification of service-role behaviours: role-prescribed, beyond
role, and helping behaviours. FSEs undertake role-prescribed behaviours to meet the formal
role requirements imposed by the firm and customers. On the other hand, beyond role
behaviours involve the FSEs’ feelings and attitude expression towards their jobs, roles,
themselves, and customers. For helping behaviours, the FSEs volunteer to help customers
outside of their firm’s duty boundary.
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The second study, based on a quantitative survey and a structural equation model, investigated
how customers perceive the three-category classification of service-role behaviours. The study
proposes seven constructs, which reflect a three-category classification of service-role
behaviours, to examine how these behaviours affect customer satisfaction and value perception.
The empirical evidence demonstrates that the helping behaviours affect value perception,
whereas the considerate manner construct of beyond role behaviours has an impact on
customer service satisfaction. Interestingly, another construct of beyond-role behaviours,
rapport, positively influences both satisfaction and value perception. This suggests rapport
acts as a bridging behaviour that links the FSEs actions and emotions to customer perception.
However, role-prescribed behaviours had non-significant effects on customer satisfaction and
value perception. This thesis contributes to the knowledge of service literature and managerial
implications by suggesting that the beyond role and helping behaviours of FSEs have crucial
positive effects on customer satisfaction and value perception. Improved perceptions may help
to build long-term relationships, customer retention, word of mouth intentions, and customer
loyalty.
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DECLARATION
I certify that this work contains no material which has been accepted for the award of any other
degree or diploma in my name, in any university or other tertiary institution and, to the best of
my knowledge and belief, contains no material previously published or written by another
person, except where due reference has been made in the text. In addition, I certify that no part
of this work will, in the future, be used in a submission in my name, for any other degree or
diploma in any university or other tertiary institution without the prior approval of the
University of Adelaide and where applicable, any partner institution responsible for the joint
award of this degree.
I give consent to this copy of my thesis, when deposited in the University Library, being made
available for loan and photocopying, subject to the provisions of the Copyright Act 1968.
I also give permission for the digital version of my thesis to be made available on the web, via
the University’s digital research repository, the Library Search and also through web search
engines, unless permission has been granted by the University to restrict access for a period of
time.
Signature: ___________________________ Date: December 12, 2016
(Phiangdao Chaoluck)
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LISTS OF REFEREED CONFERENCE PROCEEDINGS
The following publications are based upon the research presented in this thesis, and may
contain materials presented herein.
Chaoluck, P., Medlin, C. J., & Conduit, J. 2012. The Distinction between Helping Behaviour,
Prosocial Behaviour, and Altruism: Improving Service Quality. Paper presented at the
Australia and New Zealand Marketing Academy Conference (ANZMAC), Adelaide,
South Australia, Australia
Chaoluck, P., Medlin, C. J., & Conduit, J. 2013. The Distinctions between In-Role and Extra-
Role Behaviours in Service Quality: The Perceptions of Frontline Service Employees
and Customers. Paper presented at the Australia and New Zealand Marketing Academy
Conference (ANZMAC), Auckland, New Zealand.
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ACKNOWLEDGEMENTS
I would like to acknowledge generous supports from these people during my PhD journey.
First and foremost, I would like to express my sincere and deep gratitude towards my principal
supervisor, A/Prof Christopher J Medlin, who has relentlessly guided me on the track and
trained up my research skill. He has dedicated his personal times, even during travel or
vacation, to provide careful comments on my drafts. He has gone beyond academic supports
to mentally encourage me from the beginning till the end. Another key person to whom I am
strongly indebted is my co-supervisor, A/Prof Jodie Conduit. She has provided professional
guidance and critical comments that are of great importance to my thesis.
I would like to thank Dr Christopher Smith who supported my attendance to an essential SEM
workshop.
Importantly, I feel sincerely thankful to all the participants who have shared their valuable time
for the interviews, resulting in critical information for this thesis. Appreciation is also due to
the financial service firm in Adelaide (non-disclosure agreement) that allowed me to collect
crucial data for one month. I owe very much to the manager and cheerful staff members there.
Without them, I would not come this far.
I would like to acknowledge supports from the University of Adelaide for my Adelaide
Scholarships International (ASI) for postgraduate research study.
Mental supports and encouragement from my relatives and friends in Thailand and Australia
deserve a big thank here too. Specially these people include my paternal grandmother, uncle,
and aunts.
I feel very thankful to my father and mother who have always nurtured me with love and
encouragements. Last, I would like to thank my husband, Withawat, who has given me love,
caring, and useful academic guidance throughout my journey. You are my inspiration.
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CHAPTER 1
INTRODUCTION
This thesis opens a new understanding of the Frontline Service Employees (FSEs) different
role behaviours in ensuring quality and satisfaction within service encounters. Services are
defined as acts, performances, processes, or deeds provided by one party to another (Zeithaml,
Bitner, & Gremler, 2009). Eiglier, Langeard, Lovelock, Bateson, and Young (1977: p. 91)
define FSEs as “the individuals employed by a service business who are in direct contact with
the client...” Service encounters refer to person-to-person interactions between customers and
FSEs, usually within a period of time (Shostack, 1985a; Surprenant & Solomon, 1987).
Service encounters for retail stores and many other environments are a key attribute of quality
and value perceptions. Every service encounter is unique (Bianchi, 2001). Most often, studies
of service encounters focus on the firm and a customer, with the FSE being the face of the firm
(e.g. Lloyd & Luk, 2011; Ma & Dubé, 2011; Surprenant & Solomon, 1987). In this thesis, the
role of the FSE is to act on behalf of the service firm and so the encounter is conceptualised as
dyadic: firm and customer. From within a firm perspective, research is usually focused on how
to improve the efficiency and effectiveness of the encounter so as to maintain customer loyalty
(Grandey, Fisk, Mattila, Jansen, & Sideman, 2005). Presented in this thesis is an alternative
conceptualisation, one where the FSE is more independent and so is free to create value and
satisfaction for the customer through helping behaviour.
Helping behaviour is defined as “an act which benefits others with no external rewards
promised a priori in return.” (Bar-Tal, 1982: p. 102) In the service encounter helping behaviour
occurs when a FSE goes beyond simply following the role requirements of their firm. Helping
is a form of altruistic behaviour, which is defined as “an action motivated by a concern for the
wellbeing or interests of others” (Manner & Gowdy, 2010: p. 757). The distinctions of a FSE
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going beyond their required role to perform a helping activity within a service encounter has
been hardly researched. Up to the present, relevant research that addresses these issues has for
a long time been focused on in-role and extra-role behaviours (e.g. MacKenzie, Podsakoff, &
Ahearne, 1998; Yap, Bove, & Beverland, 2009; Yavas, Babakus, & Karatepe, 2013). In-role
behaviours “concern the duties and responsibilities that are formally assigned as part of a work
role” (Raub & Robert, 2010: p. 1746), and extra-role is defined as the behaviours that extend
above explicit role requirements and that the employees perform without explicit rewards
(Wallace, De Chernatony, & Buil, 2011). Thus, extra-role behaviours refer to the discretionary
behaviours extending above formally specified role requirements (Choi et al., 2013). The FSEs
are not assigned to perform extra-role behaviours as they are not part of the job description.
The employees voluntarily take additional actions and activities with the intention of helping
the customers and the firm (Brief & Motowidlo, 1986; Choi et al., 2013). Importantly, the
research on FSE roles has remained focused on the firm’s perspective of service provision. In
this thesis, the focus shifts to the service encounter, and so there are three parties actively
involved: the firm, a FSE and a customer. Thus, a different and three-part conceptualisation of
roles is uncovered.
This introductory chapter covers the background to the research, the research problems and
research methods, research approach, mixed method research, and finally an outline of the
thesis structure.
1.1 Frontline Service Employee and their Role Behaviours
In previous literature, the word ‘frontline employee’ (Bettencourt & Gwinner, 1996; Singh,
2000) was used interchangeably with several similar terms. Those terms are such as ‘customer
contact personnel’ (Julian & Ramaseshan, 1994; Pappas & Flaherty, 2008), ‘contact employee’
(Bettencourt & Brown, 1997; Van Dolen, De Ruyter, & Lemmink, 2004), and ‘frontline service
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employee’ (Ekinci & Dawes, 2009; Elmadağ et al., 2008). To maintain the uniformity in this
thesis, the term ‘frontline service employee (FSE)’ will be used.
The quality of a service encounter between a FSE and a customer helps to establish customer
satisfaction (Liao & Chuang, 2004) and value perception (Gould-Williams, 1999). FSEs are
regarded as important partners of the firm and play a key role in customer value and customer
satisfaction (Karatepe, 2012). In a service firm, FSEs are considered the source of
differentiation and competitive advantage (Sabiote & Román, 2009). The FSEs have personal
contact with the customers and so are considered as the face and the voice of a service business
(Elmadağ et al., 2008). Thus, how the role of FSEs is conceptualised will have significant
effects on customer perceptions of value and satisfaction.
Hartline, Maxham III, and McKee (2000) state that customers generally build their impression
of the firm mainly on the service encounter with FSEs. Customers use both intrinsic and
extrinsic cues to infer quality of a service (Zeithaml, 1988). Intrinsic cues are those which are
a part of the physical composition of a service encounter (Hartline & Jones, 1996). Thus, the
performance of a FSE may be considered as one of the most crucial of all the intrinsic cues. To
create positive service outcomes, FSEs need to respond to the customers’ requests with
appropriate knowledge and control in different situations (Bitner, Booms, & Tetreault, 1990).
These responses represent the role requirements of the firm. But the way that the FSEs represent
the performance by assisting and serving the customers also shapes perception of service
quality (Farrell, Souchon, & Durden, 2001; Liao & Chuang, 2004; Wu, Liang, Tung, & Chang,
2008; Yap et al., 2009). According to Sabiote and Román (2009), FSEs’ amiable behaviours,
such as caring, responsiveness, helpfulness, understanding, trustworthiness, or friendliness are
important to service quality. In the service literature, these different FSE responses are
addressed through distinguishing between in-role and extra-role behaviours.
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However, the in-role and extra-role concepts are also applied in literature addressing
employees’ behaviours within the firm and according to different foci. According to Kelley
and Hoffman (1997), prosocial behaviours are the performances acted out by employees of the
firm while carrying out their role, in order to benefit the welfare of others. Importantly,
prosocial behaviour is not to benefit oneself (Batson & Powell, 2003). The standard actions of
prosocial behaviour include, for example, helping, sharing, cooperating, volunteering,
donating, comforting, and caring acts (Brief & Motowidlo, 1986; McNeely & Meglino, 1994).
These activities may be a part of the employee’s job requirement or extend above task
specifications (McNeely & Meglino, 1994). Bettencourt and Brown (1997) also note that
prosocial behaviours of the employees have been classified into two groups, in-role and extra-
role behaviours.
However, in-role and extra-role behaviours of employees do not all focus on behaviour towards
customers. In fact, many studies have focused on the ‘organisational citizenship’ effect on the
firm of in-role and extra-role behaviours by FSEs. Organisational citizenship refers to
behaviours not directly or explicitly recognised in a firm’s formal reward system, but which
are discretionary and promote a firm’s effectiveness (Feather & Rauter, 2004; Williams &
Anderson, 1991). The purpose of these studies was to understand the factors encouraging
employees to perform better in meeting the firm’s outcomes. Thus, in-role and extra-role
behaviours are associated in research with job satisfaction (Yap et al., 2009), job burnout
(Yavas et al., 2013), role conflict, role ambiguity, organisational commitment, turnover
(MacKenzie et al., 1998), job status, job insecurity, work value (Feather & Rauter, 2004), or
trust (Reychav & Sharkie, 2010). The focus of the in-role and extra-role behaviours in these
studies was often on other employees or the firm. There are only a few studies focusing on the
customers’ side. In this thesis, the focus is on the customers’ perceptions towards FSEs’ role
behaviours.
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A review of the studies seeking to understand the effects and/or associations of in-role/extra-
role behaviours with other factors reveals that most do not have behaviour towards the
customer as a focus (see Table A1 in Appendix A). Instead the focus is on the perspectives of
an employee and manager, for example, how the two behaviours affect their job/service
performance and/or the firm. In the service literature context, there is no direct study that
explores how customers perceive the employee’s in-role and extra-role behaviours, yet the
customer is a very important reason for the distinction. Further, if customers do not distinguish
between in-role and extra-role behaviours, how can a manager or a FSE evaluate different
performances during a service encounter?
Another important issue in the literature is the continuing overlapping definitions between in-
role and extra-role behaviours. Several studies found that the boundary between in-role and
extra-role behaviours was poorly defined and varied according to employees and between them
and their supervisors (Cohen & Kol, 2004; Vigoda, 2000). The research on extra-role
reconceptualization was noted long ago by Morrison (1994). This issue deserves immediate
attention. The focus of this thesis on the role behaviours of FSEs towards customers within a
service encounter should allow a tight/clear distinction.
1.2 Service-Roles and Expectations
Schuler, Aldag, and Brief (1977) state that role theory can function as a conceptual framework
to examine the behaviour of individuals in firms and/or relate or join the properties of the firm
and the individual. Brookes, Davidson, Daly, and Halcomb (2007) explain that these ideas
establish role theory as a means to investigate the attitudes and perceptions of individuals who
interact within a firm to deliver service to consumers. From this premise, these scholars advise
that role theory in a service context may propose a valuable framework for investigating the
perceptions of employees and/or customers.
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For business, Shivers-Blackwell (2004) adds that role theory is a mechanism that explains the
relationship between role behaviour and organisational context. Every work environment
contains a set of roles or activities (Shivers-Blackwell, 2004). This set is defined as possible
behaviours to be taken into account with a particular job (Shivers-Blackwell, 2004). Each
individual who works in a certain job for any firm has his/her own specific role behaviour.
The perspective of role theory in marketing is important in the context of the dynamic process
of marketing exchange and for individuals’ enactment of behaviours in a service encounter
(Broderick, 1998; Parker & Ward, 2000; Solomon, Surprenant, Czepiel, & Gutman, 1985).
Broderick (1999) adds that role theory increases the understanding of the behavioural and
relational principles of marketing exchange by interpreting interactions. This interpretation of
interactions occurs inside social exchanges from the viewpoint of interdependent roles
(Broderick, 1999). Thus, role theory may help the researcher to understand more the behaviours
of FSEs and the resulting customer perception of quality during the service encounter.
Role theory has been discussed in the service marketing and in service encounter contexts
(Broderick, 1998; Solomon et al., 1985). Broderick (1998; 1999) notes that role theory has
been applied in a professional services environment, e.g. legal practice, education, financial
services, airlines, public services, and social services. Broderick (1999) states that role theory
has an underlying contribution to focus on the interpersonal behavioural dimensions within
service encounters and so allows service firms to comprehend and manage role patterns.
Sharma, Tam, and Kim (2012) add that role theory also proposes that interpersonal service
encounters entail social interactions between both customers and employees with clearly
defined roles and scripts.
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1.3 In-Role and Extra-Role Behaviours
Both in-role and extra-role behaviours have been studied by a number of researchers (Barnes,
Collier, Ponder, & Williams, 2013; e.g. Beatty et al., 2015; Chebat & Kollias, 2000; Katz,
1964; Raub & Robert, 2010; Yap et al., 2009). The concepts of in-role and extra-role
behaviours have also been variously defined. Katz (1964) implies that in-role and extra-role
behaviours of FSEs include joining and staying within the system, accomplishing their role
tasks, and overriding the line of duty (Katz, 1964). What is learned and inferred from Katz’s
(1964) study is that the behaviours conducted to complete assigned tasks may be considered as
in-role. Conversely, the performance that overrides the role specifications or requirements
could be extra-role behaviours. The extra-role behaviours include those that are not required
for organisational functions. Other scholars have described in-role behaviours of employees as
the performances expected by firms (Chien & Lin, 2013) and/or customers (Barnes et al., 2013;
Chebat & Kollias, 2000). It is evident that the lines between in-role and extra-role are blurred.
Also, many previous studies have paid particular attention to the FSEs’ interactions with the
supervisors inside the firm (e.g. Chan & Wan, 2012) (e.g. Chan & Wan, 2012; Maxham III,
Netemeyer, & Lichtenstein, 2008; Netemeyer & Maxham III, 2007). In those studies, the focal
theoretical attention, again, comes back to the firm. For example, Netemeyer and Maxham III
(2007) examines predictive validity differences of service employee versus supervisor rating
of employee performance in relation with customer satisfaction. Similarly, Maxham III et al.
(2008) studied how retail employee’s job perceptions (i.e. conscientiousness, organisational
identification, and perceived organisational justice) interactively affect employee job
performance (i.e. in-role performance, extra-role performance towards customers, and extra-
role performance towards the firm). Another study by Chan and Wan (2012) investigated
whether work stress undermines service employee’s role performance from the perspectives of
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FSEs and their supervisors. What is missing in these studies is an examination of the direct
interaction between FSE and customer from a customer’s perspective.
However, other scholars (e.g. Grönroos, 1984; Parasuraman et al., 1985; Vargo & Lusch, 2004)
have studied how customers perceive the FSEs’ performances during the service encounters
but they look in the different service phenomena. For example, Grönroos (1984) studied how
technical and functional quality of services are perceived by customers. The technical quality
is ‘what’ the customer gets, and functional quality is ‘how’ s/he gets it (Grönroos, 1984).
Comparably, Eisingerich and Bell (2008) examine how technical and functional service quality
impact customer’s trust in a firm. Nevertheless, these studies paid no attention to how
customers perceive the service quality through the FESs’ role behaviours.
At the end of this thesis, the researcher aims to contribute clear definitions of extra-role
behaviours of FSEs towards customers, and to examine how customers differentiate and
perceive in-role and extra-role behaviours. Distinguishing these two behaviours enables the
researcher to understand FSEs’ role behaviours, how FSEs and customers perceive these
behaviours, and how these behaviours can improve service quality.
1.4 The Importance of the Service Sector
Over the last decade, the service sector has become one of the main parts of the Australian
economy. The economy produced goods and services value at $1.6 trillion in 2014-15
(Australia Government, 2015). The service sector dominated the Australian economy, being
worth $970 billion, representing nearly 60% of the GDP (Australia Government, 2015).
Services make up the majority of today’s economy, not only in Australia where a service-based
economy representing around 82 per cent of real Gross Value Added (GVA) (Australian
Government, 2015), but also in other countries throughout the world (Spohrer & Maglio, 2008).
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Australia’s services sector has increased by an average of 3.5 per cent per year, out pacing the
all-industries average of 3.3 per cent (Australian Government, 2015). The service sector is
responsible for a majority of the job growth in developed countries (Lovelock & Wright, 1999).
More than eighty-five per cent of Australians are employed in the service sector (Australian
Government, 2015). The significance of the service industry has led to issues that mean that
more research needs to be addressed for sustained service growth (Ostrom et al., 2010). These
issues include the achievement of firms, the welfare of societies, and the quality of consumers’
lives (Ostrom et al., 2010). This thesis focuses on the role behaviours of FSEs, which are an
important factor in enhancing service quality and the achievements of firms.
1.5 Research Problems
The central purpose of this thesis is to examine how customers perceive FSEs’ service-role
behaviours, both in-role and extra-role. The primary research problems addressed in this thesis
are:
(i) During service encounters, how do customers differentiate the FSEs’ extra-role and in-
role behaviours?
(ii) How do in-role and extra-role behaviours of FSEs affect customer evaluations?
The results of the study concern theoretical and managerial contributions for service marketing,
which will enhance the service performance of FSEs and service quality of the firm. However,
before the examination of customer perceptions towards the employees’ service-role
behaviours, qualitative research is employed to confirm how FSEs see their role performances.
In developing the conceptual framework (Chapter 5), two corresponding research questions are
identified.
Research Question 1: How do FSEs perceive their role behaviours while they are providing
service to the customers?
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Research Question 2: How do customer perceptions of FSE role behaviours affect their service
satisfaction and value?
1.6 Research Approach: Ontology, Epistemology, and Methodology
Paradigms
The selection of research activities and methodology is guided by a paradigm. A paradigm is a
basic set of philosophical assumptions that guides the formulation of theoretical concepts,
shapes data collecting, and guides the research procedures (Lovelock & Gummesson, 2004).
There are three connected components that guide research activities. These components are
ontology, epistemology, and methodology (Tuli, 2011). Ontology refers to the statements with
regard to the nature and structure of being (Rawnsley, 1998: p. 2), of what exists, and of what
is thinkable (Resca, 2008). Ontology involves the nature of being, existence, becoming, or
reality (Annells, 1996; Resca, 2008). The fundamental questions of ontology relate to the form
and nature of reality, and interpretations of reality (Annells, 1996; Guba & Lincoln, 1994).
The epistemology which informs the research involves the philosophy of knowledge or how
we claim to know (Krauss, 2005: p. 758). Epistemology constitutes the questions about the
relationship between the knower and would-be knower and the subject to be known (Guba &
Lincoln, 1994). Thus, epistemology focuses on the knowledge that can be acquired on entities
under examination. Hence, epistemology has implications for methods, theories, concepts,
rules, and procedures used in a discipline to extract knowledge (Resca, 2008).
On the other hand, methodology is the strategy underlying the choice and use of particular
methods. Methodology is related to the details of data collection and analysis. Methodology is
a way to substantiate a researcher’s belief concerning hypotheses (Scotland, 2012).
Methodology relates to a process to develop the research design and to choose particular
methods, and to justify their relation to the research project, (King & Horrocks, 2010). At a
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smaller scale, methods are particular techniques and procedures for data collection and analysis
(Scotland, 2012). The collected data will be either qualitative or quantitative (Scotland, 2012).
All paradigms can employ both quantitative and qualitative data (Scotland, 2012).
There are four different paradigms to research methodology; positivism, critical theory,
constructivism, and realism (Guba & Lincoln, 1994; Healy & Perry, 2000; Riege, 2003).
Positivist research predominates in science and attempts to measure independent facts about a
single apprehensible reality (Healy & Perry, 2000; Riege, 2003). Positivist research views the
world through a one-way mirror (Guba & Lincoln, 1994; Healy & Perry, 2000). The
researchers separate themselves from the object they study (Healy & Perry, 2000). Positivism
believes that the object, which is such as data and its analysis, is an independent entity and
should be value-free (Riege, 2003).
In contrast to positivism, the researcher within a critical theory paradigm believes that a virtual
or historical reality is shaped by social political, cultural, economic, ethnic, and gender values
(Guba & Lincoln, 1994; Healy & Perry, 2000; Riege, 2003). The investigated subjects and
researchers are not separated, but linked interactively (Riege, 2003). By contrast for
constructivism, there are multiple local and specific constructed realities (Guba & Lincoln,
1994; Riege, 2003). The constructed reality depends on the interactions between and among
the respondent(s) and as interpreted by researcher(s)/interviewer(s) (Healy & Perry, 2000). For
constructivism, knowledge is theory-driven and researcher and research subject/object cannot
be separated (Riege, 2003). According to Healy and Perry (2000) and Riege (2003), similar to
critical theory, the methodology of constructivism emphasises an understanding and
reconstruction of the ideologies, values, and beliefs that people have in their minds.
Finally, with realism, reality is imperfectly and probabilistically apprehensible (Healy & Perry,
2000). The researcher acknowledges differences between the reality and their view of it.
Realists try to construct various views of the real world and aim to understand phenomena
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regarding which ones are relative in place and time. Moreover, realism relies on inductive
research enquires for building theory rather than testing theory (Riege, 2003). This thesis
applies a realist ontology and epistemology. Thus, both qualitative and quantitative
methodologies are applied. In the qualitative method, a phenomenological approach is taken
based on interviewing. In the empirical quantitative method, Structural Equation Modelling
(SEM) meets the criteria that reality is probabilistically apprehensible. The research aims to
build up an understanding of the meanings of experiences (Riege, 2003), analyse, and explain
a marketing phenomenon in a financial service firm.
1.7 Mixed Methods Research
The approach for this research is to use a mixed method (Brannen, 2005), conducted in two
sequential parts. Data collection of the two parts was limited to within South Australia. The
first part is a qualitative study seeking to understand how FSE role behaviours might be
conceptualised. To understand whether or not FSEs’ customer roles could be best understood
as in-role and extra-role behaviours; a semi-structured interview (Legard, Keegan, & Ward,
2003) was conducted. This thesis suggests a three-category classification of service-role
behaviours that; (i) FSEs saw their role towards customer to include the requirements of the
firm, (ii) FSEs perform role which focused on their own identity, and (iii) finally, FSEs help
customers to achieve their requirement. Thus, a three-part role classification seems more
appropriate than a simple in-role and extra-role categorisation.
The second part of the research applied a quantitative method to test the categorisation by using
a cross-sectional survey instrument with bank customers, who were interviewed immediately
after a service encounter. An alternative approach might have been to survey a sample of FSE’s,
but this was considered too complicated to implement. Thus, the customers of FSEs were
surveyed. The logic of this choice was that if the categories of service roles did not have some
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effect on customers, then a simpler categorization based only on the firm and the FSE was
theoretically more parsimonious.
The empirical setting of service encounters was conducted at a bank branch, where 10 staff
dealt with 250 customers in periods ranging from a few minutes up to one-third of an hour. The
customers were approached right after the encounter and asked to complete a web-based
instrument on a tablet device. The questions and scales were developed from existing literature
on the basis of the qualitative study and re-worded to focus on the customer perspective. The
questions were pre-tested with a sample of 200 university students in South Australia, so that
the final instrument was able to be completed, with research aid, in less than ten minutes.
This mixed qualitative and quantitative approach represents a form of methodological
pluralism, which, according to Johnson and Onwuegbuzie (2004), provides superior results
compared to a mono-method. Important to note is that the different methods are performed in
a sequence (Creswell, 2009; Ivankova, Creswell, & Stick, 2006; Morgan, 1998), and so the
term mixture is not technically correct. The mixed method might equally reverse the order for
a different research problem.
In the research presented here, the qualitative approach seeks to open new understandings of
how the behaviours of FSEs are guided, what the is the structure that provides the roles that
guide their behaviour, and how they saw their customer role, rather than seeing the role as a
part of the firm’s function. The approach is to get inside the world of the FSEs by applying a
phenomenological approach (Bevan, 2014; Goulding, 2005).
In the quantitative research, customers are surveyed to test a model explaining satisfaction and
value perception according to theoretical constructs developed to measure perception of FSE
role behaviours. In this part of the thesis, the perceptions of customers are apprehended using
interval scales, and individual answers do not represent reality. Rather, the frequencies of the
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sample responses are assumed to provide a measure, along with errors, of how the population
reflects the hypothesised theoretical model.
1.8 Outline of the Thesis
The outline of this thesis is based on the recommendations of Perry (1998) with regard to the
standard structure of doctoral thesis. The thesis comprises nine chapters, which are outlined
and briefly described below.
Chapter 2: Literature Review – Discusses, in two main parts, the nature of services and the
customer’s part in the service encounter. The first part reviews the importance and
conceptualisations of service quality, the growing interest in service research of the customer
experience and encounter, and finally the anticipated links with value perception and customer
satisfaction. The second part discusses role theory, roles, role expectations, and role behaviours
of FSEs. The differences between two kinds of service-role behaviours, in-role and extra-role,
are elaborated. The last section of the chapter discusses the alternative possible FSE responses
within a service encounter: helping, prosocial, and altruistic behaviours.
Chapter 3: Qualitative Methodology – Describes the research design and methodology used
to examine Research Question One. This chapter explains the research design,
phenomenological interviewing, semi-structured interviews, interview question design, and
data analysis technique and procedure.
Chapter 4: Qualitative Data Analysis and Discussion – Presents the key findings of a
quantitative data analysis displayed for each major theme and its components. The analysis and
the theme categorisation are discussed at the end of the chapter.
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Chapter 5: Conceptual Framework and Hypotheses – Reviews the theoretical foundation of
service-role behaviour studies. The seven sets of hypotheses and a conceptual framework are
also introduced.
Chapter 6: Quantitative Methodology – Presents details of quantitative methodology, research
design, unit of analysis, and data collection method. Sampling and data collection procedures
of the pre-test and the main study are described. This chapter presents the descriptions of
questionnaire designs with a focus on the structure of the questionnaires. The operationalisation
of the constructs and measurement scales are also discussed. The chapter concludes with the
data analysis plan.
Chapter 7: Data Analysis – Describes preliminary analysis of sample groups. Data entry,
screening procedures, the assessments of outliers and the assumption of normality are also
presented. This chapter concludes with an examination of the construct reliability and validity
of the measures used in the main study.
Chapter 8: Hypothesis Testing – Outlines each step of data analysis to address the research
hypotheses of the quantitative study. The results from the hypothesis testing are discussed at
the end of the chapter.
Chapter 9: Discussion and Conclusion – Discusses the key findings from the literature review
and results. Significant research contributions of this thesis for both theoretical as well as
managerial implications are presented. This chapter also explains the study limitations and
future research directions.
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CHAPTER 2
LITERATURE REVIEW
The literature is discussed in two main sections. In the first section the focus is on the nature
of services, and the customer’s part in the service encounter. The second section focuses on the
role behaviours of frontline service employees (FSEs).
2.1 Service Quality, Customer Encounter, Satisfaction and Value
In this first section of the literature review the topics covered include: the importance and
conceptualisations of service quality, the growing interest in service research of the customer
experience and encounter, and finally the anticipated links with customer satisfaction (Barger
& Grandey, 2006; Jüttner, Schaffner, Windler, & Maklan, 2013) and value perception
(Helkkula & Kelleher, 2010).
2.1.1 Services
Services are defined as acts, performances, processes, or deeds provided by one party to another
(Zeithaml et al., 2009). Lovelock and Wright (1999: p. 6) add that “services are economic
activities that create value and provide benefits for customers at specific times and places.”
Grönroos (1982) emphasises that service is an activity rather than a thing. There are four
traditional characteristics of services that are consistently cited in the literature (Gummesson,
1995). The characteristics of heterogeneity, intangibility, inseparability of production and
consumption, and perishability are considered to distinguish services from tangible goods
(Wyckham, Fitzroy, & Mandry, 1975; Zeithaml, Parasuraman, & Berry, 1985).
However, the division between goods and services is increasingly becoming unclear (Rust &
Chung, 2006). Zeithaml et al. (2009) argue that services should not be viewed as unique and
different from goods. From a customer’s perspective goods or services are not so relevant, as
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they purchase the ‘offerings’. The offerings render services, which create customer value
(Gummesson, 1995). Importantly, what customers purchase are benefits; they buy
satisfactions, expected service provision, and symbolic meanings (Vargo & Lusch, 2004).
2.1.2 Service Quality
Service quality is regarded as an important strategy for firms to distinguish themselves in
progressively competitive markets (Chen & Hu, 2010; Elmadağ et al., 2008). A firm which has
poor service quality and performance may fail to retain their customers (Allred & Addams,
2000). Parasuraman et al. (1985: p. 42) define service quality as “a measure of how well the
service level delivered matches customer expectations. Delivering quality service means
conforming to customer expectations on a consistent basis.” According to Zeithaml, Rust, and
Lemon (2001), improvement of service quality may lead to enhanced overall customer
satisfaction, positive word-of-mouth, repurchase intention, increased usage, and improved
financial outcomes.
Perceived service quality is defined by Zeithaml (1988: p. 3) as “the consumer’s judgement
about a product’s or service’s overall excellence or superiority.” Compared to goods, service
quality is more difficult for the consumers to evaluate (Lewis & Booms, 1983; Parasuraman et
al., 1985) because evaluations involve assessments of the process of service delivery and are
also made on the outcome of a service (Parasuraman et al., 1985).
There are divergent conceptualisations of what is assessed in a service quality. For example,
the Nordic school’s perspective characterises service quality in two process dimensions:
‘technical quality’, which is what is delivered or what the customers get as a result of their
interactions with the service employee (Berry, Zeithaml, & Parasuraman, 1985; Grönroos,
1984); and a ‘functional quality’ dimension, which is how services are delivered or how
customers receive and view the services they have received (Berry et al., 1985; Grönroos,
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1984). Another perspective is the SERVQUAL (Parasuraman, Zeithaml, & Berry, 1988) which
is a popularly applied scale to measure customer expectations and perception of face-to-face
service quality (Asubonteng, McCleary, & Swan, 1996). The SERVQUAL scale comprises
five dimensions: tangibles, reliability, responsiveness, assurance, and empathy (Zeithaml et al.,
2009). However, SERVQUAL has been criticised for its drawbacks relating to the
performance-minus-expectations which have an inadequate basis of practical applications and
theoretical support (Carman, 1990; Cronin Jr & Taylor, 1994).
Finally, customer perceptions of service quality have been extensively studied during the last
few decades (Martínez & Martínez, 2010). Customers’ perceptions of the service
performance/quality may relate to value perception (Zeithaml, 1988) and customer satisfaction
(Tarn, 1999). Nevertheless, in competitive markets, satisfying customers may no longer be
sufficient to make the firms prevail (Barnes et al., 2013). Firms may take service quality beyond
customer satisfaction to customer delight or even customer loyalty.
2.1.3 Service Experience
According to Berry, Wall, and Carbone (2006), when customers interact with the firm, whether
in person or indirectly over a telephone, they always have a service experience. Bolton,
Gustafsson, McColl-Kennedy, Sirianni, and Tse (2014) describe the customer experience as all
interactions, including through in person, electronic, and other channels, with the firm. Jüttner
et al. (2013: p. 738) define experience quality as “the perceived excellence or superiority of
the holistic encounter.” Those interactions are between the customer and the firm’s employees,
other customers, and the servicescape (Bolton et al., 2014) which is a combination of services
and landscape (Sandström, Edvardsson, Kristensson, & Magnusson, 2008). Thus, Bolton et al.
(2014) suggest that the firms need to strategically design and manage the consumption
experience to make differences to their clients.
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Additionally, McColl-Kennedy, Cheung, and Ferrier (2015) describe that there are three main
traditional approaches of service experiences. First, service experience is regarded as ‘moments
of truth’ which are the dyadic interactions or the encounters between the customer and the firm.
Second, a customer experience map describes how customers engage with the service and the
firm to reach their goal from the beginning to the end. Third, a service experience blueprint
displays the (i) service system, (ii) customer actions, (iii) onstage and backstage contact
employee actions and support processes. Also customers can impact other clients’ decisions
and so they as well form a part of a firms’ internal service processes (McColl-Kennedy et al.,
2015). However, these three approaches are largely from the perspectives of firms.
There are two differences in consumption between physical product and services. For physical
goods, consumers consume the outcome of the production process because they make use of
the product itself (Grönroos, 1998). On the other hand, the customers’ service experience is a
process rather than an outcome consumption (Bolton et al., 2014; Grönroos, 1998). When
customers consume services, they also perceive the process of service production (Grönroos,
1998). The consumption process is an important part of the service experience (Grönroos,
1998).
Customers evaluate service experiences based on performances rather than objects. When
choosing services and assessing service experiences, customers consider several clues that are
attached to performance (Berry et al., 2006). Anything the customers can hear, smell, see, or
taste is a clue (Berry et al., 2006). The customers perceive the clues, either its presence or
absence, in the service experience. customers employ these clues when making decision to
purchase a service and when evaluating the service (Berry et al., 2006). Wall and Berry (2007)
note that customers conceive perceptions based on functional, mechanical, and humanic clues.
The technical performances of the service or ‘functional clues’ are the ‘what’ of the service
experience (Berry et al., 2006). This clue is the core service solution that concerns the technical
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quality of the offering customers are buying (Berry et al., 2006). The mechanical clues, or
tangibles, associated with the service originate from actual objects or the environment (Berry
et al., 2006). Finally, the human clues appear from the service employees’ behaviour and
appearance, including words, comments, tone of voice, level of enthusiasm, friendly manner,
gestures, suitable outfit, or neatness (Berry, Carbone, & Haeckel, 2002). Berry et al. (2006)
conclude that both rational and emotional perceptions of service quality of customers are
influenced by these three clues. There seems little doubt that the customer perspective of FSEs
is important for understanding service satisfaction, because they generate the key human clues
and service experience.
2.1.4 Service Encounter
The encounter is a short period of time, called ‘moments of truth’ (Carlzon, 2000), in which
FSEs and customers focus on a service. FSEs use these critical moments to create an
unforgettable impression between the firm, themselves, and the customers (Beaujean,
Davidson, & Madge, 2006; Gil, Berenguer, & Cervera, 2008). The impression can help to
transform a wary or sceptical customer into strong and committed brand/firm follower
(Beaujean et al., 2006). During an encounter a customer can make an assessment of service
quality and decide whether or not to do business with the firm again (Bettencourt & Brown,
1997; Gil et al., 2008; Gummesson, 2007). Thus, firms must ensure that FSEs will deliver a
quality service to the customer(s) (Lee, Nam, Park, & Lee, 2006).
The term service encounter also refers to how a customer directly interacts with a FSE during
a given period of time (Shostack, 1985b: p. 243). The service encounter is a dyadic and person-
to-person interaction between a customer and a FSE during the consumption of the service
(Gummesson, 2007; McKechnie, Grant, & Bagaria, 2007; Surprenant & Solomon, 1987;
Wallace & De Chernatony, 2009). The dyadic nature of the interaction underlines the mutuality
of behaviours and notes the service encounter as a form of social exchange in the marketplace
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(Solomon et al., 1985). However, one might also consider that the FSE, apart from embodying
the firm, also represents his/herself. Thus, one side of the dyad in a service encounter is
representing two actors.
Sheth (1976) also partly elaborates this distinction in noting that a service encounter has two
distinct communication dimensions: content and style. Content communication represents the
considerable aspects of the intentions for which the two parties have assembled. This content
communication involves suggesting, promoting, negotiating, and offering a set of
service/product benefits and their expectations (Sheth, 1976). However, style communication
constitutes a format- and mannerism-behaviour pattern, which is adopted and shaped by the
customer and FSE in their encounter. The communication style of an encounter represents the
highly individualistic preferences and normative expectations of each of the two parties in the
interaction process (Sheth, 1976). Thus, it is implied that the FSE can bring their own way of
interacting into a service encounter.
Solomon et al. (1985) also see that service encounters are human interactions and role
behaviours. Thus, service encounters are a mutual process and so are interactive in nature
between FSE and customer, rather than linear (Solomon et al., 1985). Every service experience
depends upon the coordination of both parties (Solomon et al., 1985). According to Solomon
et al. (1985), participants follow a learned role, or a set of behaviours, that are suitable for the
situation and will enhance the possibility of goal achievement. But the mutuality also means
that each encounter is different for a customer and a FSE. The distinctions of perceptions and
mutuality between firm, FSE and customer along with the heterogeneity of each encounter
suggest that the notions of service value and customer satisfaction are contextually interpreted
and experienced. The next sections address these issues.
According to Johnson, Herrmann, and Gustafsson (2002), customer satisfaction has been
classified into two types: transaction-specific satisfaction and overall or cumulative
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satisfaction. Transaction-specific satisfaction is an immediate evaluation by a customer of a
particular service encounter (Johnson et al., 2002). Jones and Suh (2000) add that the level of
transaction-specific satisfaction of certain service encounters is various because the service
quality differs from experience to experience. On the other hand, overall satisfaction refers to
the evaluation of entire consumption experiences with the service/firm (Garbarino & Johnson,
1999; Johnson, Anderson, & Fornell, 1995). For Jones and Suh (2000), the overall satisfaction
was aggregated from all previous transaction-specific satisfactions. Customers modernise each
specific transaction after each encounter (Boulding, Kalra, Staelin, & Zeithaml, 1993). The
overall satisfaction may be generally evaluated based on several or few transactions depending
on the frequency that customers have interacted with a particular FSE (Parasuraman, Zeithaml,
& Berry, 1994). For example, a customer may have a low transaction-specific satisfaction
because of a single dissatisfying experience, but s/he still feels satisfied with the firm due to
numerous former satisfactory encounters. Due to the nature of consumer banking, customers
and the FSEs tend to have an ongoing relationship rather than a single business transaction.
However, this thesis focuses on the customer’s transaction-specific satisfaction towards the
service that is affected by the FSE’s service-role behaviour. In this way, this thesis can capture
the perceptions of customer shortly after receiving the service.
2.1.5 Customer Service Satisfaction
Customer satisfaction is regarded as a dominant goal for service firms. Accomplishing
customer satisfaction promotes the client retention, positive word-of-mouth, lower marketing
disbursement, and enhance profits (McDougall & Levesque, 2000). There are diverse
definitions of customer satisfaction in the literature. Bitner and Hubbert (1994) consider
customer satisfaction as both the outcome of a transaction-specific (individual or transient) and
overall (prolonged or cumulative) evaluations of the service encounters. The transaction-
specific evaluation is apprehended after each service encounter, while an overall one is from a
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prolonged perspective of a service firm after multiple buying occurrences (Ekinci & Dawes,
2009; Lee, Park, Park, Lee, & Kwon, 2005; Wang, Lo, & Yang, 2004).
For Tse and Wilton (1988: p. 204), customer satisfaction is “the customer's response to the
evaluation of the perceived discrepancy between prior expectations (or some other norm of
performance) and the actual performance of the product as perceived after its consumption.”
This definition is the so-called expectancy/disconfirmation paradigm. This paradigm
contributes the grounding for the majority of satisfaction studies and includes four constructs:
expectations, performance, disconfirmation, and satisfaction (Churchill Jr & Surprenant, 1982;
Oliver, 1980; Oliver & DeSarbo, 1988; Tse & Wilton, 1988).
The expectations as a standard for a comparative judgement are formed before the service
experience occurs (De Ruyter, Bloemer, & Peeters, 1997; Oliver, 1980). Expectations are
distinguished by the nature of the service, the sacrifices and effort in obtaining benefits and the
social benefits or costs (Churchill Jr & Surprenant, 1982). Disconfirmation is the result of the
discrepancies between prior expectations and actual performance (Caruana, Money, &
Berthon, 2000). Positive disconfirmation takes place when the performance of product/service
goes beyond expectations. A negative disconfirmation arises when the product/service
performance is below expectations (Lee et al., 2005). Zero disconfirmation or confirmation
occurs when a product/service performs as expected (Caruana et al., 2000; De Ruyter et al.,
1997). These hint that the standard of expectations of each individual are different, and the
satisfaction occurs when received service surpasses his/her judgement. But the performance
that just meets the anticipation may or may not generate the satisfaction.
Several researchers state that customer satisfaction in addition to having a cognitive dimension
also has an affective one (Cronin Jr, Brady, & Hult, 2000; Rust & Oliver, 1993; Woodside,
Frey, & Daly, 1990). Oliver (1999: p. 34) defines satisfaction “as pleasurable fulfilment” of a
customer. Rust and Oliver (1993) add that the cognitive and affective dimensions are not
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restricted to a mere situation, but can also relate to an experience and that each fills out
differently into situation and experience. Thus, a high level of arousal and pleasure can coexist
with simple satisfaction based on a distinction between experience and situation. This
understanding provides an additional meaning to service satisfaction, beyond that of
satisfaction with a good. Differently to product satisfaction, a service experience can be
customised to surpass expectations on both the surprise and pleasure aspects (Rust & Oliver,
1993). But here the FSE takes a particular and specific part in the service encounter, one that
must go beyond a simple provision of a service.
However, other researchers consider satisfaction is a combination of both cognitive and
affective dimensions (i.e. Chen & Chen, 2010; Hu, Kandampully, & Juwaheer, 2009; Lee et
al., 2005; Malik, 2012). This formulation is a holistic one and so different parts of a service
encounter (e.g. content versus communication style) are not distinguished by a customer. Thus,
when the perceived performance meets or exceeds expectations, the result is a positive effect
on satisfaction (Chen & Chen, 2010; Hu et al., 2009; Lee et al., 2005). However, Sheth (1976),
Rust and Oliver (1993), and Solomon et al. (1985) state that service encounters are full of
different parts. Communication elements are one of them (Sheth, 1976; Solomon et al., 1985).
The differences of the content and the style of communication also create a more complex
multiple perspective that is likely to affect the customer service satisfaction.
Another research issue in a service context is whether quality of encounter is alone an
antecedent of satisfaction (De Ruyter et al., 1997; Murray & Howat, 2002; Spreng & Mackoy,
1996). For example, De Ruyter et al. (1997) found that customer’s service satisfaction is a
direct function of service quality and also is a perception and disconfirmation. By contrast other
studies have shown that the performance of service has a direct influence on satisfaction or
leads to customer satisfaction (Caruana et al., 2000; Cronin Jr et al., 2000; Kuo, Wu, & Deng,
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2009). These different results indicate that service encounters warrant research on the basis of
different perspectives.
A study by Ekinci, Dawes, and Massey (2008) examined, in both hotel and restaurant settings,
how actual self-, ideal self-, and desires congruence, with perceptions of service physical
quality and employee behaviour, affected customer satisfaction. Their results indicate that
employee behaviour had the strongest influence on customer satisfaction. Therefore, it is
logical to consider the influence of FSE’s behaviour on customer service satisfaction.
2.1.6 Customer Value Perception
Creating, delivering, and maintaining customer value is one of the important strategies for any
firm in the service sector due to the crucial influence on customers’ behaviour intentions (Park
et al., 2013; Wang et al., 2004). Customer value appears to be highly subjective, idiosyncratic,
and may differ from one person to another (Hu et al., 2009; Zeithaml, 1988). Accordingly,
value perception is perceived by personal preference, judgement, and evaluation of individual
customers (Rust & Oliver, 1993; Walker, Johnson, & Leonard, 2006) rather than objectively
determined by sellers or service employees (Hu et al., 2009). Therefore, “customer value
perception is the preference and overall assessment of the utility of the product, attribute
performances, and consequences arising from use that facilitate achieving the customers’
goals and purposes in use situations” (Wang et al., 2004: p. 327).
According to Zeithaml (1988), the meanings of value are diverse. She illustrates four
definitions of value based on a transactional view: (i) low price; (ii) the benefits people receive
from the product; (iii) a trade-off between cost and quality; and (iv) all relevant ‘get’
components as well as all those of ‘give’. By contrast Parasuraman and Grewal (2000) see four
different types of value according to the timing within a service encounter: (i) acquisition value
is the benefits, comparative to monetary costs, the customers believe they are getting by
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obtaining a service; (ii) transaction value is the enjoyment of acquiring a bargain; (iii) in-use
value is a usefulness gained from using the service; and (iv) redemption value is a remaining
benefit at the time after a service.
In the service context, Cronin Jr et al. (2000) and Parasuraman and Grewal (2000) indicate that
quality is an essential driver of customer value perception. Service value perception refers to
the customer’s assessment on the differences between the sacrifice and the level of quality of
the service s/he received (Park et al., 2013). The sacrifice comprises monetary cost (e.g. price)
and nonmonetary costs such as time, effort, and risk (Lee et al., 2005). However, customers do
not always buy a quality service nor purchase a service at the lowest cost (Park et al., 2013).
According to Zeithaml (1988), there is a trade-off between perceived service cost and perceived
quality in purchasing a service. Thus, if perceived sacrifice is less than perceived service
quality, customer value is high and vice versa (Malik, 2012). Therefore, perceptions of service
value are not only a perceptual matter, but are also relative to past experience. However,
without a perception of value customers are also unlikely to return.
This thesis examines how customer value perception is affected by FSEs’ service-role
behaviours. This assumption is supported by the findings of Hartline and Jones (1996)’s study.
They found that the performance of FSEs (i.e. front desk and room service employees) had a
significant effect on overall value. Hartline and Jones identified five employee groups within
the hotel experience where customers had contact with FSEs who might influence their
perceptions of quality and value. They found that in most service encounters in the business
such as hotel, the front desk is a main contact that serves guests, and these customers are the
ones who are likely to form the quality and value perceptions.
After reviewing previous research, this thesis posits that value perception refers to overall
evaluation of customers towards the product and/or service (Sweeney & Soutar, 2001;
Zeithaml, 1988). Several authors (i.e. Boksberger & Melsen, 2011; Bolton & Drew, 1991;
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Woodruff, 1997) state that customer value perceptions are based on the trade-off between what
they receive (e.g. attribute performance, and results in terms of their purposes or goals) and
what they sacrifice, which are monetary and nonmonetary costs.
2.2 Role and Frontline Service Employee Behaviours
This part of the literature review focuses on role theory, roles, role expectations, and the role
behaviours of FSEs. The review in this section focuses on two kinds of service-role behaviours:
in-role and extra-role. Next the differences between these two behaviours are elaborated and
particularly the discussion covers the importance of redefining the extra-role behaviour of
FSEs. The final sections discuss alternative possible FSE responses within a service encounter:
helping, prosocial, and altruistic behaviours.
2.2.1 Role Theory and Roles
Role theory is the study of role and social behaviour of humans who have dyadic and multi-
person interactions to each other. Role theory emphasises the nature of people as social
performers whose behaviours are suitable to their positions in society (Solomon et al., 1985).
Role theory associates with many disciplines including business and marketing.
Role theory was originally proposed by social psychologists to describe “how in any given
situation individuals are assigned and normally follow certain roles” (Hughes, 2001: p. 1).
Hughes’s definition of role theory refers to the concepts that predict how an individual will
enact an expected behaviour in a given circumstance. Also, in the work of Broderick (1999),
role theory is described as a study of behaviours of individuals within contexts that are in
relation to these actions (Biddle, 1979: p. 11).
Role theory is based on a theatrical metaphor (Biddle, 1986; Parker & Ward, 2000; Solomon
et al., 1985). Role theory is not only a metaphorical characterisation of human behaviour, but
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also includes the study of interaction of human behaviour (Webb, 2000). Stier (2004) adds that
role theory holds that human behaviour is non-random and meaningful. There are three
constructs that comprise role theory: identities that are assumed by social participants;
patterned and characteristic social behaviours; and scripts or expectations for behaviour
comprehended and observed by all actors (Biddle, 1986; Guirguis & Chewning, 2005; Jackson,
1998). Therefore, role theory is the study of the characteristics and behaviours of the
individuals which are defined and allocated by the social context, position, participation,
interaction, and expectation. Role theory emphasises the notions and deeds of people while
they have a social interaction.
Broderick (1999) adds that role theory is the study of role – dyadic and multi-person
interactions, dyadic social exchanges, or more generalised social exchanges. Role theory makes
intelligible and interprets forms of social reciprocal action and social integration (Broderick,
1999). Role theory explains peoples’ interaction by considering: the role that individuals
adjusted in a specified social encounter; the role adjusted by other people in the encounter; and
the expectations of roles obligated by those occupied in the encounter (Broderick, 1999). Thus,
during the social exchanges, after participants interpret the interaction and take a role, they then
enact a set of behaviours which are associated with that persona.
In addition, role theory focuses on social behaviour in a specific surrounding (Solomon et al.,
1985). Most social behaviour includes joint activity (Solomon et al., 1985). This joint activity,
which is crucial for the interacting persons, is a coordination of proper behaviour between them
(Solomon et al., 1985). If social behaviour is considered as the performance, the reactions of
performers are linked to parts and scripts understood by social actors (Biddle, 1986). Biddle
(1986) adds that the ways people behave may be diverse or rely upon the situation and their
social positions. Furthermore, role theory acknowledges that during a social exchange, once a
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role has been adopted by the participants, the set of behaviours and patterns of interactions
connected with that role will be performed (Parker & Ward, 2000).
Additionally, roles are sets of behaviours connected with social positions/statuses (Biddle,
1979; Major, 2003). Role only occurs in relation to other; that is, the concept of roles is the
idea of complementarity, for instance, customer and sales person, doctor and patient, or mother
and son (Mohr & Bitner, 1991). Ackerman (1958: p. 1) defines the concept of role as “a bridge
between the processes of intra-psychic life and those of social participation.” Southall (1959:
p. 19) defines the meaning of role as “any position differentiated in terms of given social
structure, whether the position be institutionalised or not.” Later, Burnette (1999: p. 50),
described role as a set of expectations associated with a particular combination of ‘actor-other’
identities.”. Hughes (2001: p. 34) adds that “role provides categories into which individuals
can fit data about people and make some assumptions.” These definitions show that an
individual’s role is defined and expected by the society and situation of the enactment.
Lynch (2007) notes that it is essential to understand social roles, so that the activities of
everyday life in which individuals are engaged can be appreciated. Social roles are well-known
social psychological territories which prescribe social expectations, obligations, and positions
in a social structure (Stier, 2004). Social roles also institute a practically comprehended, shared
sense of reality as they provide the foundation for the recognition of certain kinds of persons
and equivalent kinds of agency or knowledge (Lynch, 2007). Hence social roles include
regularities in the cultural surroundings in which individuals engage (Lynch, 2007).
Additionally, social roles are systematic, predictable, patterned, and meaningful for the
participants (Ebaugh, 1988). Stier (2004) describes that every individual bonds to an array of
different, situational and dynamic roles, negotiated in social functionality and interplay that
also relies on the ability of role-interchange. Thus, successful enactment through roles requires
a constant vigilance for a need to change to another part.
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Spehar, Frich, Kjekshus, Dickinson, and Robinson (2015) and Bitner, Booms, and Mohr (1994)
state that role is defined by a position in a social space. Generally, a social position aids in
forming a person’s identity (Biddle, 1979). This identity indicates a set of common recognitions
and corresponding kinds of knowledge, agency, and even a cultural environment for an
individual (Biddle, 1979; Lynch, 2007). However, Lynch (2007) notes that role identities are
not separate psychological phenomena. Rather roles are social phenomena, which individuals
can perform in their own idiosyncratic manner so long as they stay within the boundaries of
what is socially acceptable. However, in practical terms, individuals are often experienced with
several role choices and are simultaneously held responsible for their membership in different
social categories.
Roles in the work domain are considered a central institution in people’s lives (Major, 2003).
Roles act as the boundary between the employee and the firm. Also, roles can help to connect
the employee to the firm and vice versa (Schuler et al., 1977). More specifically, employees
take particular behavioural expectations from the social system that accommodates the role
(Major, 2003; Schuler et al., 1977). Major (2003) adds that role can become personalised for
an individual (or employee). For example, employee’s behaviour is not all conditional upon a
similar expectation, and individuals do not all perform the role in an identical manner (Major,
2003). Levinson (1959) proposes that individuals’ values, characteristics and other personality
attributes, childhood experiences, formal education and apprenticeship, influence their ideas
about their occupational role. Thus, how employees perform their role depends on their
experience and view of life.
To understand more about the individuals’ actions in their occupational role of the
organisational and/or social position, role behaviour/performance needs to be discussed in the
next section.
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2.2.2 Role Behaviours
Role performance, or behaviour, is clearly the fulfilment of formal role-norms (Levinson,
1959). Levinson (1959) notes that like any form of human behaviour, role performance is the
outcome of several forces. Some of these forces arise from the organisational matrix, such as
role requirements, the pressures of authority, informal group influences, and forthcoming
deterrents (Levinson, 1959). Other factors are within the individual, for example his/her role-
relevant personality characteristics and role-conceptions (Levinson, 1959). This means that
both internal and external stimuli and/or motive can arouse an individual to perform role
behaviour.
Role behaviour is related to the psychological level of attachment between self and role.
Attachment is the degree of emotional intensity that the individual attaches to his/her specific
role (Ebaugh, 1988; Stier, 2004). Intensity of attachment can be low or high (Ebaugh, 1988;
Spehar et al., 2015). At low intensity, an individual’s role behaviour is undertaken with
minimum effort and with little engagement of self in the role (e.g. behaviour towards a
bystander on a street) (Ebaugh, 1988; Spehar et al., 2015). However, when intensity towards
attachment is high the individual’s behaviour reflects a very strong integration of self and role
(e.g. parent) (Ebaugh, 1988; Spehar et al., 2015). Thus, attachment intensity describes how
much an individual connects or is bound internally to a specific role. Also, because an
individual can assume multiple roles there is some form of prioritisation across these in any
situation.
Related to attachment is the concept of an externally focused ‘side-bet’, which might be a
friendship, emotional attachment to a career or an assured future, status, or monetary rewards
(Ebaugh, 1988; Stier, 2004). Side-bets make exiting a role difficult and they can increase role
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attachment (Ebaugh, 1988; Stier, 2004). Accordingly, both internal and externally motivated
factors may affect whether an individual stays in a role or switches in a given situation.
2.2.3 Service-Role and Expectations
Broderick (1999) argues that role theory extends the domains relating to service encounter in
three perspectives. First, role theory introduces the individuals’ role performance in a service
encounter which is a key factor of future interactions (Broderick, 1999). This suggests an
implicit causal link between the appropriateness of the behaviour adopted in a present service
encounter and the probability of success in a future one (Broderick, 1999). Second, role theory
is an integrated pattern of social interaction in marketing exchange, where the internal role
within organisations corresponds to external role performance with customers (Broderick,
1999). Third, role theory examines service encounters as a continuous sequence with
significant internal and external exchanges (Broderick, 1999). Therefore, role theory is a study
that extends the understanding of the enactment of role by employees and customers in a
service encounter. Thus, the dyadic interaction between the service employee and customer is
open to analysis using the concept of role or behaviour associated with a particular position.
In a dyadic service context, role behaviours are interdependent during service encounters
(Sharma et al., 2012; Solomon et al., 1985). Sharma et al. (2012) and Solomon et al. (1985)
add that a successful outcome of a purposive transaction is dependent on mutually coordinated
actions of both participants, customers and employees. Solomon et al. (1985) note that the
service encounter is similar to many other types of dyadic interactions; no one can predict the
quality of outcomes from knowledge of only one actor’s behaviour. Thus, the success and
quality of service interaction are determined during service action and relies on both parties.
Role expectations are a conceptual bridge between social structure and individual role
behaviour (Lynch, 2007). Role expectations are not associated with the people themselves, but
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with specific positions (Lynch, 2007; Mohr & Bitner, 1991). One individual can engage any
number of social positions gradually, and behaviour will be expected to change properly (Mohr
& Bitner, 1991). Thus, role expectations are the standards for behaviour that are perceived by
everyone and usually closely followed by actors (Bitner et al., 1994; Mohr & Bitner, 1991).
Role expectations consist of rights, privileges, responsibilities, duties, and obligations of any
occupant of a social position, as considered by an individual occupying another position in a
social structure (Lynch, 2007; Solomon et al., 1985). Shivers-Blackwell (2004: p. 42) describes
role expectations as “the degree to which all members of the role set develop beliefs and
attitudes about what that individual should and should not do as part of his/her role.” Thus,
role expectations are an important element of a social interaction, given by a specific social
context.
A role set is a contextually bound concept. Shivers-Blackwell (2004) adds that role set refers
to the mutual dependence on each other that each member of an organisation or group has with
others. Solomon et al. (1985) and Mohr and Bitner (1991) add that the role set is the entirety
of complementary roles of service provider that would include, for example, co-workers,
manager, and customers. Therefore, when people have the position of a person in a role set in
their mind, they expect s/he should perform his/her parts.
According to role theory, all individuals have expectations for their own behaviours and those
of other human beings (Biddle, 1986). This is especially the case in a service marketing context
where customers have certain expectations towards service employees. According to Broderick
(1998), from a role theory perspective, when service employees have clear understandings of
how customers expect them to perform and what particular behaviours affect the ability of
clients to participate in a role script, a successful service provision and interaction may occur.
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Nevertheless, role expectations may not be met and this can lead to misunderstanding and low
customer satisfaction, for example if an employee lacks experience, or has poor customer-
orientation (Mohr & Bitner, 1991). Also, a customer who lacks script knowledge or who has
inflated role expectations can perceive negative results (Mohr & Bitner, 1991). Moreover, the
role expectations and the objectives of the customers must be met in the encounter; otherwise
the outcome may likely be unsuccessful (Broderick, 1998). Therefore, to meet their role
expectation, both employees and customers need to learn and understand their potential roles.
Miscommunication can be solved by a high level of pre-established role agreement. Mohr and
Bitner (1991) explain that people who regularly interact are likely to have mutually acceptable
reciprocal role behaviours. Thus there is less need for role expectations to be communicated
(Mohr & Bitner, 1991). Mohr and Bitner (1991) add that role expectations create less chance
for communication failure than when backgrounds are divergent and the role occupants have
not previously interacted. Thus, the relationships and past service interactions between
employees and customers may reduce a role expectation gap and lessen miscommunication.
In the next section frontline service employees’ roles are discussed in relation to firm and
customers.
2.2.4 Service-Role Behaviours of Frontline Service Employee
FSEs have duties towards both customers and firm and connect both parties together. In direct
interaction with the customers, FSEs can customise in real-time the service encounter
(Bettencourt & Gwinner, 1996; Leavitt, 1996). Both the service offering of the firm and the
way in which the services are delivered can be customised by FSEs (Bettencourt & Gwinner,
1996). Coelho, Augusto, and Lages (2011) add that the privileged position of FSEs, close to
customers, allows the employees to assemble first-hand customer information. The FSE is a
good source of information to match customer’s needs and often has a better understanding of
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their problems than any others in a firm (Bitner et al., 1994; Bowers, 1989; Ellinger, Elmadağ,
& Ellinger, 2007; Lages & Piercy, 2012). Equally FSEs have a responsibility to meet the
requirements of the firm within their role (Turnley, Bolino, Lester, & Bloodgood, 2003; Yoon
& Suh, 2003). What is intriguing is how a FSE might also undertake a role separate from that
required by the firm, but more aligned to a customer. The FSE in their linking position between
customer and firm also has more than one role they might adopt. FSEs usually adjust their
behaviours from moment to moment on the basis of feedback they receive while providing
service to customers (Bitner et al., 1994). That a FSE might switch between roles, even within
the one service encounter; this opens whole new avenues for research.
According to Lewis (1991), customers are the persons who evaluate and compare the quality
of service providers and their services. This service quality evaluation process is undertaken
within the interaction between FSE and customers (Lewis, 1991). Hence, to satisfy and retain
the customers, FSEs need to understand and to provide services that meet their customers’
expectations. The degree to which these needed behaviours are within a required role, as set by
a firm, or are within the individual role of the FSE, is an open question. Equally, the customer
can behave in such a way that the FSE switches their role.
2.2.5 In-Role Behaviours towards Customers
Different terms have been used to name in-role behaviour by researchers, for example role-
prescribed (service) behaviours, expected employee behaviours, role-prescribed (customer
service) performance, or within-role behaviours. However, the definitions of these terms are
rarely different.
In service settings, expectations for in-role behaviours of FSEs may arise from explicit
obligations as specified in the service firm documents such as performance evaluation forms
and job descriptions, or from implicit norms in the workplace (Choi et al., 2013; Liu et al.,
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2013; Tsaur et al., 2014). According to Liu et al. (2013), for FSEs the list of in-role behaviours
can be limited to legitimate aspects of frontline service job performance. This interpretation
means that, according to their work role, FSEs act in-role behaviours to provide basic service
and from a firm’s perspective there is only a need to meet the customers’ primary expectations.
Similarly, Bowling (2010), and Liu et al. (2013) write that in-role behaviours are effective
performance by employees that are needed to do their official duties. These core task
behaviours are expected, required, assigned, and assessed as a part of the duty and fundamental
responsibilities of an employees’ work role and job description (Barksdale & Werner, 2001;
Kang et al., 2012; Maxham III et al., 2008; Tsaur et al., 2014). Firms expect employees to
understand their policies and to present standard services (Barnes et al., 2013), and to increase
the businesses’ profit by cross-selling of services to customers (Chebat & Kollias, 2000). Thus,
the firm view of in-role behaviours is fairly clear: fulfil the firm’s requirements as a FSE.
Following the focus on a firm’s requirement of in-role behaviours, Lindgreen, Hingley, En
Yap, Bove, and Beverland (2009) note that an absence of proper behaviour may result in an
employee being admonished, receiving a negative financial consequence, or being dismissed.
In-role behaviours are recognised by a service firm’s formal reward systems (Tsaur et al.,
2014). Thus, in-role behaviours are apparently regarded as compulsory for FSEs to follow and
perform. There seems little doubt that a firm’s perspective of what in-role behaviours are can
be quite tight.
Thus, for in-role behaviour, FSEs provide the expected service with a skill and knowledge and
at a level that can be reasonably anticipated by the customer/management/firm (Barnes et al.,
2013). Choi et al. (2013) add that in-role behaviour refers to normal activities that fulfil basic
job requirements. These expected customer service behaviours include, according to Choi et
al. (2013) and Tsaur et al. (2014), exhibiting common courtesy, addressing customers by name,
having and demonstrating accurate knowledge of policies and products, cross-selling firm
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services, saying ‘thank you’ to customers, and answering calls within three rings. Further, Van
Dolen, Lemmink, de Ruyter, and de Jong (2002) and Price, Arnould, and Tierney (1995b)
suggest in addition that expected service behaviours include ensuring safety for customers,
handling the details, meeting customer service requirements, and helping customers to
complete their goals.
However, in-role behaviours may also derive from explicit obligations or unambiguous norms
in the workplace (Chebat & Kollias, 2000). Thus, FSEs might also undertake behaviours
beyond the written script.
2.2.6 Extra-Role Behaviours towards Customers
Extra-role behaviours refer to FSEs positive, voluntary, and discretionary acts that go outside
the scope of role prescriptions (Kang et al., 2012; Liu et al., 2013; Raub & Robert, 2010;
Schepers et al., 2012). Extra-role behaviour is not formally compensated or rewarded, and is
not punished if not performed (Beatty et al., 2015; Wallace et al., 2011; Williams & Sanchez,
1998). For Cho and Dansereau (2010: p. 411), extra-role behaviours are “above and beyond
their call of duties.”
Employees can perform extra-role behaviours towards their firm, co-workers, and also
customers (Yap et al., 2009). An issue is the perspective of who is examining and who is the
focus of the extra-role behaviour. For the firm, extra-role performance is completed with the
intention of promoting the firm’s welfare (Maxham III et al., 2008), and so co-workers are a
suitable focus. On the other hand, extra-role performance towards customers is where FSEs
voluntarily carry out behaviours above the call of their duties, or go an extra mile to help the
firm serve customers during a service encounter (Liu et al., 2013; Maxham III et al., 2008;
Schepers et al., 2012). But an alternative not considered is where a FSE, for some reason,
performs above expected role behaviour to help a customer, and that may even come at a cost
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to the firm. Changing from a managerial focus to the alternative possibilities within a service
encounter may open new avenues of understanding.
This broader focal perspective is commented on in the literature. For example, Barnes et al.
(2013) and Chan and Wan (2012) comment that extra-role behaviours are the actions that go
above what the customers or firms expect, and may include doing more than what other people
require. These behaviours towards customers reflect participation and service delivery
(Maxham III et al., 2008). Maxham III et al. (2008) explain that participation beyond a role
implies voluntary acts that enhance service when interacting with customers, and that such
service delivery indicates extra efforts to fulfil customer queries. These previous studies
indicate that it depends on an individual FSE whether there is a willingness to perform his/her
duty above or beyond what is expected by the firm, or by the customer.
Pimpakorn and Patterson (2010) found that to provide an outstanding service, employees must
be willing or engaged and have positive attitude; and they are able or possess the capability or
have the confidence in their ability to accomplish tasks. According to Chan and Wan (2012),
FSEs who perform extra-role behaviour pleasurably serve the customers and have internal
drive to be involved in mutually satisfying encounters. Liu et al. (2013) add that these duties
performed above the work role-prescribed by the service firm may be attributed to the
employees’ good intentions and his/her commitment to the customer. Schepers et al. (2012)
note that these behaviours comprise extra efforts of employees to take opportunities that
improve service during interactions or conscientious endeavours to respond to customer
concerns. Thus, extra-role behaviours are desirable performances provided by FSEs to serve
customers that are above their explicitly existing role descriptions. But what motivates extra-
role behaviours may come from either the FSEs’ duty to the firm, themselves and their
characteristics, or from something within the customer.
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Even though extra-role behaviours are not particularly assigned to FSEs as activities to be
performed as part of their job, they are of considerable significance to successful service
delivery (Liu et al., 2013). Chebat and Kollias (2000) state that these little extra, spontaneous
exceptional, and unexpected service behaviours might increase customer satisfaction and
positive emotional responses.
Conversely, Barnes et al. (2013) hint that employees’ performance, without engaging in extra-
role performance, may result only in customer satisfaction, and not in customer delight, which
is a higher level of satisfaction. Similarly Lee et al. (2006) and Netemeyer and Maxham III
(2007) agree that extra-role performances could result in the highest level of satisfaction and
customer delight . This means that service extra-role behaviours are worthy of greater research
emphasis.
Distinguishing In- and Extra-Role Behaviours towards Customers
Van Dyne and LePine (1998) believe that the distinction between in-role and extra-role
behaviours is essential. However, Castro, Armario, and del Río (2005) express that it may be
difficult to distinguish these two behaviours. For example, Raub and Robert (2010: p. 1756)
define in-role behaviours that “follow service guidelines and standard operating procedures
with extreme care. In-role behaviours follow through in a conscientious manner on promise to
customers.” This could be interpreted as both in-role and extra-role behaviours, because a
conscientious manner focused on a customer will lead to distinctly different behaviours than
one where the focus is that of the firm. Table 2-1 present previous studies and attempts to
resolve the overlapping of in- and extra-role definitions. A conclusion drawn from even a
simple examination of the table is that while in-role behaviour may be well defined, extra-role
definitions deserve further clarification.
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Table 2-1: The Distinctions between In-Role and Extra-Role Behaviours
Definition* In-Role Extra-
Role Authors
Behaviours that are recognised by the
firm’s formal reward systems. Yes No Barksdale and Werner (2001)
FSEs perform the expected behaviour
derived from implicit and explicit norms
in the workplace or from explicit
obligations specified in documents as
goal statements, performance appraisal
forms, and job descriptions.
Yes Yes Brief and Motowidlo (1986)
Fundamental responsibilities that
employees are hired to perform in
exchange for their compensation
package.
Yes No Cohen and Keren (2008: p.
433)
Follows service guidelines and standard
operating procedures. Follows through in
a conscientious manner on promises to
customers.
Yes Yes Raub and Robert (2010: p.
1755)
Extrinsic rewards and sanctions, both
formal and informal by firm Yes No Morrison (1994)
Informal rewards, individual financial
incentives, and individual social
recognition have an indirect motivational
effect on role behaviours towards
customers.
Yes No Yap et al. (2009: p. 290); Yavas et al. (2013)
Intrinsic rewards Possible Possible Morrison (1994)
Customers receive service or product
above and beyond what was purchased.
No Yes Barnes et al. (2013)
FSEs provide little extras and
spontaneous exceptional service during
the service encounter.
No Yes Lee et al. (2006)
Role performances that include
prosocial behaviour.
No Yes MacKenzie et al. (1998)
Voluntary behaviours that go above job
requirements.
No Yes Raub and Robert (2010)
Employee behaviours that promote
customers’ emotional needs and foster
their interpersonal relationships. These
behaviours are such as presenting
empathy, and being welcoming, mindful,
and earnest.
No Yes Van Dolen et al. (2002)
* Italics note the possibility of different degrees and different foci for extra-role components
Now looking specifically at the extra-role component of the definitions in Table 2-1, it is apparent
that there is a range of very different human behaviours. For example, mindfulness, empathy and
prosocial are distinctly affective characteristics of behaviours which might arise inside a service
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encounter. Also, these behaviours focus specifically on a customer, and open to interpretation is
the degree to which they are still in the interests of the firm. The next part of this section explores
prosocial behaviour.
2.2.7 Helping, Prosocial and Altruistic Behaviours
Helping, prosocial, and altruistic behaviours refer to possible behaviours in the service sector
(Bettencourt & Brown, 1997; Guy & Patton, 1989). However, helping, prosocial, and altruistic
behaviours are not identical.
2.2.7.1 Helping Behaviours
From the helper’s perspective, a goal of helping behaviour is to benefit another(s) (Bar-Tal, 1982).
The motives that drive the helper to act are unselfishness, a feeling of obligation, a possible
compensation, and an expectation of a reciprocal exchange (Bar-Tal, 1982). Although the helper
might not gain support in return, (Feger, 1991), rewards could encourage the helping behaviours
(Sproull, Conley, & Moon, 2005). There is no guarantee that the recipient will give an external
reward in return.
According to Bar-Tal (1982), other motives, such as altruism, expectation of external rewards,
financial obligation, and compliance with a request or threat could also lead to helping. Aiding and
sharing are examples of helping behaviour. Penner, Dovidio, Piliavin, and Schroeder (2005)
suggested that individuals are motivated to increase their rewards yet to decrease their costs before
helping. People weigh the possible costs for helping and for not helping (Diamond & Kashyap,
1997). The cost of helping includes effort, expenditure or personal risk. Therefore, rewards and
costs may defer or facilitate helping activities.
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2.2.7.2 Prosocial Behaviours
Batson and Powell (2003) note that the word ‘prosocial’ was conceived by social scientists.
According to Batson and Powell (2003) the word prosocial was fashioned as an antonym for
‘antisocial’ and their thought was that defining antisocial might improve understanding of
prosocial. Millon (2003: p. 22) states that “antisocial personalities counter the indifference or the
expectation of pain from others; this is done by actively engaging in duplicitous or illegal
behaviours in which they seek to exploit others for self-gain.” Antisocial behaviour involves
exploitative, dishonest, unkind, and selfish activity, or violation of the social norms and mores
of society (Hornstein, LaKind, Frankel, & Manne, 1975; Mayer, 1995). Thus, antisocial
behaviour is about self-gain, and this suggests prosocial behaviour is about gain for many
others.
Prosocial behaviours influence the wellbeing of both benefiter(s) and recipients (Weinstein &
Ryan, 2010). A prosocial person might consider the cost to oneself. Performing prosocial
behaviours is rational because, in the long term, the benefits to others can be tremendous
(Twenge, Baumeister, DeWall, Ciarocco, & Bartels, 2007). Miller, Bernzweig, Eisenberg, and
Fabes (1991) also explain that the reasons individual performs prosocial behaviours could be
various, ranging from concern for others, social approval, to self-gain. These internal motives
are important for pleasure and satisfaction that individuals may receive from prosocial
behaviours (Weinstein & Ryan, 2010). It is clear that an individual performing prosocial
behaviours benefits the society, including oneself and others.
However, prosocial behaviour has been defined in a number of ways. For example, Brown and
Singhal (1993) said that prosocial behaviour includes an action that benefits society. Hornstein
et al. (1975) also note that prosocial behaviour includes benevolent, honest, kind, or selfless
behaviour. Table 2-2 offers a range of definitions.
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Table 2-2: Definitions of Prosocial Behaviour
Author Definition
Ackfeldt and Wong
(2006)
Prosocial behaviours represent discretionary behaviours which employees
direct at external customers to aid service quality and recovery, and
internally, at their colleagues in the firm they work for.
Batson and Powell
(2003)
Prosocial behaviour is a general range of acts that aim to benefit one or more
people other than oneself.
Brief and Motowidlo
(1986)
Prosocial behaviour is a social act engaged in to benefit others or to maintain
and raise the person’s or persons’ well-being.
Decety, Bartal,
Uzefovsky, and Knafo-
Noam (2016: p. 4)
“Prosocial behaviour is any performance acted by one person to ease
another’s need or improve his/her welfare.”
Eisenberg et al. (1999:
p. 1360) “Prosocial behaviour is a voluntary behaviour intended to benefit another.”
George (1991: p. 299) “Prosocial behaviours are helping behaviours performed to benefit or help
another individual.”
Penner et al. (2005) Prosocial behaviour is a general category of performances that is commonly
beneficial to others.
Twenge et al. (2007) Prosocial behaviour aims to benefit others, rather than benefit oneself.
According to Table 2-2, Penner et al. (2005) suggest that prosocial behaviour would need to
benefit many others, whereas other researchers have accepted that behaviour can be deemed
prosocial if just one other person benefits (Batson & Powell, 2003; Brief & Motowidlo, 1986;
Eisenberg et al., 1999). However, if prosocial is the antonym of antisocial, the focus should be
only behaviour that ultimately benefit society.
2.2.7.3 Altruism
According to Hopkins and Powers (2009), altruism is a motivation with an ultimate goal of
enhancing the welfare of another. Robinson and Curry (2005) describe altruism as the purest
form of caring, selfless, and non-contingent upon reward, and thus a predecessor of prosocial
cognitions and behaviours. Pure altruism is a social act, an expression of a selfless act, ‘to live
for others (Comte, 1851: p. 556)’. For Robinson and Curry (2005), altruism is a true
selflessness with no expectation in any kind of advantage to oneself.
Teng, Wu, and Liu (2015) propose that a person who performs altruistic behaviour feels what
is ‘right’ and ‘morally correct’ to do the right thing. Underwood and Moore (1982) also terms
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altruistic behaviour as self-giving, voluntary, and an action done willingly without expectation
of material or social reward. However, these authors do not explicitly exclude internal reward,
such as feeling good about oneself, from altruistic behaviour.
Eisenberg et al. (1999: p. 1360) regard altruism as ‘intrinsically motivated’. They define
altruism as “a voluntary behaviour intended to benefit another-that is, behaviour motivated by
concern for others or by internalised values, goals, and self-rewards rather than by the expectation
of concrete or social rewards, or the desire to avoid punishment or sanctions.” Also, Schwartz
and Howard (1982: p. 329) view altruism as “motivated by personal (as opposed to social)
norms, situation specific behavioural expectations generated from one’s own internalised
values, backed by self-administer sanctions and rewards.” For Eisenberg et al. (1999) and
Schwartz and Howard (1982), altruism includes the possibility of internal reward.
Batson and Shaw (1991) indicate a more nuanced understanding of altruism by considering the
differences between two types of motives within the individual, altruism and egoism (Batson
& Shaw, 1991). Egoism is a self-serving motive that drives an individual to pursue self-benefit
and self-gratification, while pure altruism is a motivational state to benefit another (Batson &
Shaw, 1991). Batson and Shaw (1991) add that the ultimate goal of altruism is to increase
another’s wellbeing or to relieve others of suffering, whereas egoism’s ultimate desire is to
gain benefits for oneself. However, Batson and Shaw (1991) note that self-benefit could occur
with an altruistic motivation, if it is an unintended consequence of benefiting the other, and not
the ultimate goal.
Batson and Shaw (1991) note that a ‘single’ motive could not be both altruistic and egoistic.
Regardless of whether an act would benefit the self or another, the act without a goal could not
be either altruistic or egoistic (Batson & Shaw, 1991). Hence, it can be said that altruism is an
intentional behaviour driven by an ultimate goal and a motivation that purposes to benefit only
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another (Batson & Shaw, 1991). The exception is where an internal benefit is gained by
accident.
2.2.7.4 Comparing Helping and Prosocial Behaviours
Helping behaviour and prosocial behaviour are similar but not identical. Bierhoff (2002) believes
that helping behaviour is the broadest term, while prosocial behaviour is a narrower term. Every
form of interpersonal support consists of helping behaviour (Bierhoff, 2002). In contrast, Hinde
and Groebel (1991) state that prosocial behaviour is generally used for all behaviours that benefit
others, including helping. Thus, whether helping or prosocial behaviour is the broadest term is not
clear.
The act of helping requires at least two people or more (Feger, 1991). Both parties might know or
not know each other (Tesser & Smith, 1980). The relationship between the helper and the help-
recipient(s) of helping behaviour might be direct, friend to friend(s), or a person to a stranger(s).
Differently, prosocial behaviour, as the opposite to antisocial behaviour, should impact on more
than an individual. Eisenberg and Fabes (1990) note that prosocial behaviour is a voluntary
behaviour intended to benefit ‘others’. Sproull et al. (2005) add that prosocial behaviours can act
through mediators, such as public volunteer workgroups. The mediator reduces the fear of the
benefiter for any ongoing demands from the recipients.
Helping behaviours aim to benefit other(s). However, the individual who evinces both behaviours
may receive rewards as a response. For helping behaviours, the motives that drive the helper to act
out helping behaviour are unselfishness, feeling of obligation, possible compensation, and
expectation of a reciprocal exchange (Bar-Tal, 1982). Although it is not necessary that the helper
would gain support in return (Feger, 1991), rewards could reinforce the helping behaviours (Sproull
et al., 2005). There is no guarantee from the recipient to give an external reward in return.
Conclusively, external and internal rewards may be the motives of helping behaviour.
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Prosocial behaviours influence the wellbeing of both benefiter(s) and recipients (Weinstein &
Ryan, 2010). Performing prosocial behaviours is rational because in the long term the benefits to
others can be tremendous (Twenge et al., 2007). Miller et al. (1991) comments that individuals
perform prosocial behaviour for many reasons; ranging from concern for others, social approval,
to self-gain. These internal motives are important for the satisfaction that individuals may receive
from prosocial behaviours (Weinstein & Ryan, 2010). It is clear that an individual performing
prosocial behaviours benefits the society, including oneself and others.
2.2.7.5 Comparing Helping Behaviours and Altruism
Previous studies show that there are similarities and differences between helping and altruistic
behaviours. According to the definitions, there are two people or more, the helper(s) and the
help-recipient(s), involved in the case of both altruism and helping behaviours. The benefit of
both behaviours is to be provided from a person to another or from person(s) to others.
The helping act might involve costs and rewards to the helper. Helping behaviours’ quality is
manifested in one’s motivation to perform (Bar-Tal, 1982). The quality of helping behaviours
of the helper could develop over time (Bar-Tal, 1982). Even though the helper may develop
the quality of his/her helping behaviours towards altruism, any helping act done for a quid pro
quo purpose cannot be regarded as altruistic behaviour. Weiner (1980) agrees that it cannot be
called ‘altruistic act’ if the helper has cost-benefit concerns. Conversely, altruism refers to
unselfishness and concern for another person(s) (Hinde & Groebel, 1991). However, an
altruistic person may receive internal reward when benefiting other(s). The altruistic person
might also benefit by accident.
2.2.7.6 Comparing Prosocial and Altruism
The review of previous studies suggests that the motivations of both prosocial behaviour and
altruism have much in common. Both terms encompass the actions that aim to benefit another.
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However, Miller et al. (1991) note that motives and emotional reactions, and internal
occurrence or sympathy, might make it difficult to confirm whether an individuals’ prosocial
behaviour is altruistic behaviour. Brief and Motowidlo (1986) also state that it might be
inappropriate to consider prosocial behaviour and altruism as the same thing.
Ross et al. (1992) notes that prosocial behaviour and altruism are different. Ross et al. (1992:
p. 94) express that prosocial behaviour is commonly considered to “designate helping, sharing,
and other seemingly intentional and voluntary positive behaviour for which the motive is
unspecified, unknown, or not altruistic.” On the other hand, Millon (2003: p. 20) terms altruism
as “the act is unilaterally directed for the benefit of others and the bestower neither expects nor
expresses a desire for a comparable return.” Based on the definitions of prosocial behaviour and
altruism, this thesis considers that these two terms are not exchangeable, and not so difficult to
distinguish. Miller et al. (1991) state that altruistic behaviour is a subordinate type of prosocial
behaviour. People who perform prosocial behaviours reciprocally pursue them to support, to
aid, or sometimes to love or like each other (Twenge et al., 2007). Contrarily, altruism is the
essence of the prosocial personality. Eisenberg et al. (1999) note that one characteristic aspect
of altruism is that people act altruistically without expectation of any external rewards.
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Table 2-3: Summary of Three Term-Comparisons
Helping Behaviours Prosocial Behaviours Altruistic Behaviours
Purpose of
the
Behaviours
Benefit other(s) (in specific
term)
Benefit others (in general
term); Increase the well-being
of both benefiter(s) and
recipients
Benefit other(s) (in
specific term); Increase the
well-being of recipients
People
Involved in
Behaviours
Two people or more;
The helper(s) - recipient(s)
Two people or more, but
expect to impact on society;
The benefiter(s) - recipients
Two people or more;
The giver(s) - recipient(s)
Path Direct Direct/Indirect Direct/Indirect
External
Reward
Expectation
Can be expected but no
promise; One can help to
win approval and
friendship, power gain,
monetary reward, and
others (Weiner, 1980).
Low expected, can be refused;
Career improvement, social
recognition, love,
encouragement from others,
social support/relationship
(Twenge et al., 2007)
None; Absence of
expectation or expression
in any external reward
(Millon, 2003)
Internal
Reward
Expectation
Consider
Consider;
Intendedly and unintendedly
Consider;
Very low
Nature of
Internal
Reward
Feeling of praise and
honour in their own eyes
(Diamond & Kashyap,
1997)
Understanding development
and social responsibility
(Weinstein & Ryan, 2010)
Accidental receiving;
Anxiety and guilt
avoidance, an internalised
ideal conformity (Ross et
al., 1992)
Cost Consider Consider Not consider
2.3 Chapter Summary
This chapter provided an overview of relevant literature and identified contributions of the
study. The pertinent issues related to: the importance of services and service quality; the strong
link between service quality and service encounter; the nature of customer service satisfaction
and value perception; the concepts of role theory, role behaviours, role expectations, and
service-role behaviours of FSEs, and the differences between prosocial and altruism.
From the literature review, the several studies (e.g. Cohen & Kol, 2004; George & Jones, 1997;
Mayer & Gavin, 2005; Parker & Collins, 2010) state that the demarcation and categorisations
of in-role and extra-role behaviours are unclear and the definitions vary from one employee to
the other and between employees and supervisors. There could be, however, several issues that
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question the FSEs’ role behaviours, such as the explicit distinctions between in-role and extra-
role behaviours, or the recognition of FSEs and customers of these distinctions. The concept
and definition of extra-role behaviours may need to be better specified.
The researchers explain that the confusion and difficulty in distinguishing between in-role and
extra-role behaviours of employee cause the overlapping definitions (Morrison, 1994;
Podsakoff, MacKenzie, Paine, & Bachrach, 2000). The overlap of both role behaviours’
definitions is still presented in several studies. Morrison (1994) examined how 317 clerical
workers differed in what they defined as in-role and extra-role behaviours related to
commitment and social cues. She found that the boundary between in-role and extra-role
behaviours was poorly defined, and caused multiple interpretations. Griffin, Parker, and Neal
(2008) also state that the borders between in-role and extra-role behaviours are weak at best;
terms alter as stated by observers, the extent to which the behaviour is discretionary is unclear,
and motivational state influences what is perceived to be in-role.
The role definitions of employees may not be constant and may change over time, as people
may modify their jobs and so remove, change, or add tasks (Coyle‐Shapiro, Kessler, & Purcell,
2004; Semmer, Tschan, Meier, Facchin, & Jacobshagen, 2010). The distinction between in-
role and extra-role behaviours needs clarifying. Further, any distinctions in extra-role
behaviours are yet to be determined. In addition, there is a need to focus research of in-role and
extra-role on the customer, rather than look only from the firm perspective. The gaps have been
identified that this thesis seeks to redefine with regard to the definition of extra-role behaviours.
Moreover, as presented in Table A1 (see Appendix A) a majority of previous studies examined
these two role behaviours from employee and/or supervisor perspectives. There are no
measures in the literature for how a customer perceives and differentiates the FSEs’ service-
role behaviours. The lack of research focused on a customer’s perspective might be one reason
why the distinction between in-role and extra-role behaviours remains unclear.
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The next chapter provides a detailed description of the qualitative methodology undertaken to
explore Research Question One. Chapter three includes the research design, phenomenological
interviewing, participant selection, semi-structured interviews, interview question design, and
data analysis technique and procedure.
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CHAPTER 3
QUALITATIVE METHODOLOGY
This chapter presents the qualitative methodology used to explore the behaviours of FSEs, and
so to bring under consideration whether roles are a relevant way to categorise behaviours. The
chapter presents the rationale for choosing a phenomenological approach to examine the
experience of participants on their service-role behaviours. Then, participant selection and
interview question design are also explained. This is followed by the interview analysis
procedure. The chapter finishes with a conclusion.
3.1 Research Design for the Qualitative Research
This thesis aims to capture the voices, stories, viewpoints, experiences, and meanings of FSEs
in the way they undertake and approach service encounters. Thus, qualitative research is an
appropriate approach because the authenticity of human experience is maintained and people’s
everyday behaviour is opened to the researcher (Silverman, 2010). Several academics suggest
that if any scholar seeks to have an ‘experience near’ which is close to other people and
accounts for a social setting, then only qualitative methods are relevant (Warren & Karner,
2010).
Before explaining the reason why this thesis employed phenomenological approach, a
background is given. Phenomenology is both a philosophy and a methodology (Goulding,
2005). Phenomenology considers each human’s life and experience as a situated reality (Riege,
2003). From this philosophical position, a researcher must listen and maintain the truth that is
heard from individual experiences (Goulding, 2005). In the phenomenological approach, the
context relevant to why people experience the world in the way that they do is important
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(Lewis-Beck, Bryman, & Liao, 2004; Smith, 2008). The individual experience and reality is at
the centre of a phenomenological approach.
Lewis-Beck et al. (2004: p. 3) provide a definition of phenomenology as a “descriptive study
of how things appear to consciousness, often with the purpose of identifying the essential
structures that characterise experience of the world.” Goulding (2005) adds that
phenomenology is not a study of subconscious motivation, but is a critical researcher’s
interpretation and reflection on a conscious experience of a person. In addition, an essential
concept of phenomenology is to describe the constitutive features of the natural world, how
individuals come to experience that world and so how they share their individual reality
(Lewis-Beck et al., 2004). According to Lewis-Beck et al. (2004), the person and the objects
of their reality are intrinsically inter-related. The implication is that experiencing subject and
object cannot be separated from one another. Thus, phenomenology focuses on an interest in
comprehending social occurrences from the actors’ own perspectives (Kvale & Brinkmann,
2009). Consequently, a researcher is a person who delineates the world as experienced by the
subjects and assumes that the essential reality is what people perceive their world experience
to be (Kvale & Brinkmann, 2009). Thus, the purpose of phenomenological research is to
explore, describe, clarify, and analyse persons’ everyday experience.
3.1.1 Phenomenological Interviewing
Phenomenological interviewing is a specific form of interviewing where researchers seek to
elicit a specific kind of content (Roulston, 2010). Phenomenological interviewing aims to
depict the signification of a notion or phenomenon that individuals share (Marshall & Rossman,
2011). The interview technique for the research reported here adopted the three interview
stages that constitute phenomenological inquiry suggested by Seidman (2012). The three stages
let the researcher and participant examine the participant’s experience, put it in a context, and
reflect on its meaning (Seidman, 2012).
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The key purpose of phenomenological interviewing is to obtain descriptions of FSEs’
experiences and how participants perceive and distinguish their service-role behaviours, and to
interpret the meaning of a concept or phenomenon that the FSEs shares with the researcher
(Kvale & Brinkmann, 2009; Marshall & Rossman, 2011; Roulston, 2010).
Thus, the researcher started the interviews with the participants by asking about their life
history with the phenomenon of interest (Seidman, 2012). This allowed the researcher to place
the participant’s experience in a context, which then allowed questioning on a specific topic.
In this first exploration of FSEs’ perceptions towards their service-role behaviours, the
researcher asked participants about their education, previous service training, and career history
before they became FSEs.
Next the interview focused on the details of the individual’s present experience with their
service-role behaviours (Seidman, 2012). The researcher asked participants what they actually
do on the job and to elaborate the service-role experiences upon which their opinions might be
built (Seidman, 2012). In this stage, the researcher attempted to identify the essence of each
FSEs’ work life as phenomena (Marshall & Rossman, 2011). At the end of each interview,
each participant was encouraged to reflect on the meaning and understanding of his/her
experience with the roles (Seidman, 2012). The questions addressed the emotion, cognition,
and perception of participants’ customer service-role behaviours. Participants were asked to
select and reflect events from their past experience (Seidman, 2012). Thus, many examples of
roles and why they were undertaken were uncovered.
3.2 Participant Selection
A purposeful selection of participants was used to recruit ten participants (Marshall, 1996). As
Morse (2000) recommended, the number of participants should be at least six to ten people for
a phenomenological study. The interview numbers stopped when saturation had been reached
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(Glaser & Strauss, 2009) and the last interview provided no new insights. Thus, ten
interviewees were sufficient. All interviewees were screened to ensure they worked as FSEs.
Two service managers were also included, because these participants also undertook face-to-
face service with customers in exactly the same way as the FSEs. Because of the need for
respect for the persons involved, participants were fully informed about the research procedure
and gave their consent to participate in the research before data collection began (King &
Horrocks, 2010). All interviewees’ identities and information are kept confidential and
anonymous (King & Horrocks, 2010). The demographics of participants are provided in Table
3-1.
Table 3-1: Demographic Profile of Face-to-Face Participants
Demographics University (7 Participants)
One branch of a
Financial Firm at a
Hospital (3 Participants)
Age Range 20-40 Years 4 2
Age Range 41-65 Years 3 1
Gender Female 5 3
Gender Male 2 -
FSEs 6 2
Service Managers of FSEs 1 1
The interviews were conducted over two periods of time. In the first period, the researcher
interviewed six FSEs who worked in different university departments at the reception desks.
The different sites were chosen because the service encounters ranged from substantial to
reasonably short. The different sites also provided service encounters with different customer
purposes, although both are similar in that a service mentality is quite strong. The experience
of the researcher during interviews was quite similar despite the difference in service products.
Later, the analysis of interviews at both sites revealed similar results.
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According to Smith and Osborn (2008), people normally feel most comfortable in their familiar
environment. Therefore, all the interviews were conducted at the places of business where the
participants worked.
3.3 Semi-Structured Interviews
Semi-structured interviews were conducted in this thesis according to an interview guide that
included suggested questions and pointed to role behaviours. A semi-structured interview is
characterised by an interactional exchange of conversation; and is topic-centred and creates a
type of narrative (Lewis-Beck et al., 2004). Semi-structured interviews allow participants the
opportunities to flexibly develop in a conversational approach the issues they feel are essential
(Lewis-Beck et al., 2004; Longhurst, 2010; Roulston, 2010). All responses were digitally
recorded and transcribed shortly after by a paid transcriber. The researcher then determined the
accuracy by listening to the records and reading the transcriptions at the same time.
3.4 Interview Question Design
The interview guide with a list of topics and questions was prepared, and all questions followed
an open format. Open questions are those that furnish a broad boundary within which
participants can fully express in their own words, viewpoints, and experiences in relation to the
topic stated by interviewer (Roulston, 2010; Turner, 2010). The researcher avoided asking
questions beginning with ‘Why?’ Instead, the researcher began the question with ‘How?’ or
asked them to provide the reasons for their acts or questioned the participants and asked them
to explain more about their behaviour. The questions were, for example: ‘Could you tell me
more about...’; or ‘Could you please give me some examples of…’ so that participants could
tell a story and give detailed descriptions about their customer service-role behaviours. The
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quality and trustworthiness of interview questions have been substantiated by the studies of
Kvale and Brinkmann (2009), Moustakas (1994), and Yin (2003).
The topic of the interview questions relates to the past and present experiences of FSEs and
their opinions about role behaviours in customer service. The interview questions were not
shared with the participants beforehand. The researcher introduced the purpose of the interview
to the participants. Thus, the participants only knew that the researcher wanted to know how
they perceived work policy, role, and their duty. This approach meant that participants were
not aware of the researcher’s purpose of the study.
The average time for each interview ranged from approximately twenty to forty minutes,
depending on the participants’ narrative and talkativeness. The interview questions were
arranged into four groups, with approximately thirty questions in total, according to the
following purposes and the reasons. These four groups included building rapport, in-role
behaviours, extra-role behaviours, and FSEs’ opinion questions.
3.4.1 Building a Rapport Questions
‘Building a rapport’ questions were designed to understand the characteristics of the subjects
and develop the informal environment. To avoid questions that might cause discomfort to the
interviewees, the researcher proceeded from the most general questions. These questions
prepare participants to talk further and so were not nervous or intimidated (Qu & Dumay,
2011): for example: “What is your position?”; “How long have you worked for the bank?”;
and “How many people in your team?” In this way, the researcher was able to gain some
rapport with the interviewees in the beginning part of the interviews, and then the more detailed
questions were included later on.
In this part, the researcher also asked about FSEs’ past experiences related to their customer
service-role behaviours; for example: “Have you received customer service or hospitality
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education or training?”; “What kind of training/education you had?”; or “Can you explain a
little bit about your training/education?” The purpose of the questions is to have participants
reconstruct and narrate a range of essential events in their past careers and work experiences
that indicate their understanding of service-role behaviours (Seidman, 2012).
3.4.2 In-Role Behaviour Questions
For the ‘in-role behaviour’, the interview questions were modified to suit the context which
was relevant to the FSEs. The interview guide was adapted from the studies of Stock and Hoyer
(2005) and Netemeyer and Maxham III (2007). The purpose of these questions is to recall a
participant’s memory on any service-role behaviour they provided to customers (Moustakas,
1994). The questions helped to reflect the issue of how in-role behaviour of FSEs may either
derive from implicit norms and/or explicit obligations. The examples of in-role behaviour
issues were: “What are the basic requirements of your duties?”; “How do you know the basic
requirements of your duties?”; or “What are the policies you must follow?”
The FSE participants were questioned in a way that elicits details about their present
experiences involving the in-role behaviours when providing services to customers. These
specific probing questions (Kvale & Brinkmann, 2009; Lewis-Beck et al., 2004) were about
their organisations’ policies, roles, duties, responsibilities, and feelings about their job
descriptions. These probing questions help the researcher learn how FSEs know about their
service provision in-role behaviours, for example: “How do you know you have done is meeting
formal performance requirements when serving customers?”; “You mentioned about
providing customer service, how do you think about the formal performance requirements
when serving customers?”; or “How did you feel when you fulfil responsibilities to customers
as specified in your job descriptions?”
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3.4.3 Extra-Role Behaviour Questions
‘Extra-role behaviour’ questions refer to FSEs present discretionary behaviours which
extended from their in-role behaviours. The purpose of the questions is to learn how FSEs
distinguish extra-role from in-role behaviours, and what influences encouraged them to surpass
their in-role behaviours. The interview guide was adapted from the studies of Rego and Cunha
(2008) and Tsaur and Lin (2004). The purpose of these questions is to recall a participant’s
memory on any extra-role behaviour they provided to customers (Moustakas, 1994). The actual
interview questions applied for this research were for example: “Could you give me some
examples of providing services that are not in your required duties?”; “Could you give me the
reasons of doing that service provision?”; or “How do you feel when you provide services that
are not in your required duties to customers?”
Further, the researcher also delved deeper into the topic, for example; FSEs’ relationships with
their customers, their feeling about interacting with customers, and the reasons for providing
service without considering their job descriptions. Those questions were, for example: “What
make you providing service that is not your required duties for customers?”; “How did you
feel when you provide service out of your job descriptions?”
Both in-role and extra-role behaviour questions were designed to probe into participants’
present experiences (Kvale & Brinkmann, 2009; Lewis-Beck et al., 2004). Probing questions
were established on their responses to the pre semi-constructed questions (Turner, 2010). These
questions allowed the researcher to adapt and pursue the interviewees’ answers and to
investigate their content (Kvale & Brinkmann, 2009). However, the researcher did not state
what aspects were to be taken into consideration (Kvale & Brinkmann, 2009). The questions
were, for example; “Please provide a recent experience about how you assist the customers?”,
or “Can you explain a little bit about it?”
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Additionally, probing questions allow the researcher to ask specific questions, in an attempt to
have more correct descriptions, and to ask operationalise questions by ferreting from the
general statements (Kvale & Brinkmann, 2009). Samples of questions were: “Have you
assisted customers without being asked?”; “Have you experienced this yourself?”; “what do
think about that experience?”; and “How do you feel about that experience?” The direct
questions after the interviewees had presented their spontaneous descriptions were also
conducted (Kvale & Brinkmann, 2009). The researcher directly presented and indicated the
topics and dimensions of the phenomena which were central to the subjects (Kvale &
Brinkmann, 2009), for instance: “You mentioned about providing customer service above your
formal tasks, how do you know what you did is above the formal performance requirements?”
3.4.4 Other Information Questions
The questions were designed to obtain the interviewees’ questions, suggestions, and opinions
about the entire study, and to involve information beyond the narrow scope of the study from
the participants (Yin, 2003). The researcher anticipated this by adopting the advice about
considering the limitation of the research. The questions were: “What do you think this
research interview is about?” and “Would you like to add any other comments to the
research?”
3.5 Data-Analysis Technique and Procedure
The interviews were transcribed to form the material for the analysis (Kvale & Brinkmann,
2009; Warren & Karner, 2010).
A manual content analysis is conducted on interview texts, in order to look for groupings of
behaviours (Malhotra & Birks, 2007). Undertaking a manual content analysis depends on
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sensitivity towards connections in a text. According to Malhotra and Birks (2007), a manual
search of statements is more sensitive to themes and connections between participant beliefs.
Analysis is a process, according to Corbin and Strauss (2015). The interview is already a sense
making process by the participant, as they seek to answer the questions of the researcher.
Already the lived world is being reified in the interview process. The next step of analysis is a
further reification by the researcher. The aim of interpretation was to understand the beliefs of
the participants according to their talk and telling of stories in response to the interview
situation (Smith & Osborn, 2008).
Analysis requires understanding of ideas, their extent of development, and a balance between
conceptualisation and description (Corbin & Strauss, 2015). Analysis involves making
interpretations after careful consideration. The very notion of interpreting implies that a
concept is the understanding of the researcher on the implicit meaning of participants’ words
and actions (Denzin, 1998). Interpretation is a transformation that refines and clarifies the
meanings from a text, object, or experience (Denzin, 1998).
The participants’ accounts presented pieces of their identities and role behaviours. One cannot
directly access the participant’s world (Smith & Osborn, 2008). Already the interview situation
creates reification of the participant’s world (Smith & Osborn, 2008). Further, in the
interpretation the researcher’s own conceptions come into play in order to make sense of the
participant’s responses to the interview (Smith & Osborn, 2008). Smith and Osborn (2008: p.
53) state the issues well: “the participants are trying to make sense of their world; the
researcher is trying to make sense of the participants trying to make sense of their world.”
Thus, the researcher must be sensitive to the participant and their way of elaborating their
behaviours. At the same time, the text interpretation must be sensitive to the nuances, as the
themes and concepts are brought to the surface in the analysis phase. As Smith and Osborn
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(2008) note, there is no definite way to conduct phenomenological interpretation, so the
researcher must find the proper way that works for the study.
According to Marshall and Rossman (2011), the gathered data are interpreted around themes
that describe the ‘textures of the experience’, in this case behaviours. To arrive at a structural
synthesis, the researcher explored possible meanings, which are related to theory, and divergent
perspectives (Marshall & Rossman, 2011). In this thesis the researcher seeks to understand the
roles of FSEs, and how those roles might be categorised according to a structure (Marshall &
Rossman, 2011).
Thus, the analysis seeks to understand the various roles of FSEs and to categorise or structure
the behaviours within roles, as given by the alternate ways that FSEs see their work world. But
already the researcher is aware of the in-role and extra-role concepts and how these categories
are created by the position of a firm as a reason for a service encounter. That is, the service
encounter is a firm managed situation or context, and the FSE must perform according to that
context. These concepts are formed by the researchers as they enter the field, as the interviews
are conducted, and in the interpretation phase, the concepts still inform possible analysis
results.
3.6 Chapter Summary
This chapter has outlined the research methodology, research design, and techniques employed
in this thesis. A phenomenological interviewing that fits with the realism view (Riege, 2003) is
chosen to understand the reality of FSEs’ voices, stories, viewpoints, experiences, and
meanings in the way they undertake and approach service encounters. Semi-constructed
interviews were conducted to allow a flexible conversation with the FSEs. The interview
question design includes four parts; building the rapport, in-role behaviour, extra-role
behaviour, and other information questions. The questions were designed to evoke a
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comprehensive account of the FSEs’ past and present experiences of the phenomenon
(Moustakas, 1994). The topic of the interview questions is related to their opinions about role
behaviours towards customer service. The manual content analysis was undertaken following
the grounded theory technique of Corbin and Strauss (2015). The results of analysis are
presented in the next chapter.
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CHAPTER 4
QUALITATIVE DATA ANALYSIS AND DISCUSSION
This chapter reports the results of a qualitative study of FSE role behaviour. The study focuses
on: (1) how FSEs consider rules and policies towards customer service and what those
regulations mean to them and; (2) what motives and/or factors urge FSEs to act role behaviours.
After this study, the researcher expects to: (i) discover the factors that may drive each role
performance of FSEs in their customer service; (ii) understand the differences in FSEs’ role
behaviours during service provision to customers and; (iii) apply the findings to clarify the
forms of role behaviours.
The chapter is structured in the following manner. First, the key findings of an analysis of the
interviews with FSEs are presented for each major theme and its related components. Each
theme and component gives details on the sense of their personal and social world, the
meanings of particular experiences, perceptions, and individual points of views – in this case,
their customer service-role behaviours. The final section of the chapter argues that FSEs’
service roles might be categorised according to a three-category classification. These three
perspectives are role-prescribed, beyond role and helping behaviours.
4.1 Theme Identification
Regarding research question one - How do FSEs perceive their role behaviours while they are
providing service to the customers? - the key findings and discussions follow. There were seven
major themes that emerged from the data analysis. Table 4-1 summarises the seven important
elements of the FSEs’ service-role behaviours as found in the interview data.
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Table 4-1: Theme Identification
Theme 1 - Being an expert is part of the FSEs’ role.
Theme 2 - FSEs meet the job requirement.
Theme 3 - FSEs show a considerate manner to customers.
Theme 4 - FSEs express their personal involvement towards their jobs to the customers.
Theme 5 - FSEs show empathy to the customers.
Theme 6 - FSEs build rapport with the customers.
Theme 7 - FSEs help the customers without concern for their duty boundary.
All seven themes were suitable to the research purposes, problems and methods (Sandelowski,
1998). These themes may answer research question two: How do customer perceptions of FSE
role behaviours effect their service satisfaction and value? However, these issues will be
discussed later in Chapter 5.
The next sections present the findings from the analysis of the collected data. The focus of
these sections is to elaborate on the FSEs’ perceptions and experiences of their service
provision to their customers.
4.2 Themes in the Behaviour of FSEs
This section describes each theme, which emerged from the data analysis. Table 4-2 presents
the participants whose interview reflected each theme.
Table 4-2: Themes by Participant
Themes FSEs’ Role Behaviours Participants
1 Being an expert is part of the FSEs’ role. 1, 2, 3, 5, 6, 7, 8, 9, 10
2 FSEs meet the job requirement. 1, 2, 3, 5, 7, 8, 9, 10
3 FSEs show a considerate manner to customers. 3, 6, 8, 9
4 FSEs present a personal-involvement expression to
the customers.
1, 2, 3, 4, 6
5 FSEs show empathy to the customers. 1, 2, 3, 4, 5, 8, 9, 10
6 FSEs build rapport with the customers. 8, 9, 10
7 FSEs help the customers without concern for the
duty boundary.
2, 3, 4, 6, 9
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4.2.1 Theme One: Being an Expertise is Part of the FSEs’ Role
A significant proportion of the respondents (90%) agreed that being an expert is important for
their services. As a summary, Table 4-3 describes the components that emerged from the data
about the FSEs’ expertise in their service role and duty.
Table 4-3: Being an Expertise is Part of the FSEs’ Role
Theme Components
Being an expert is a part of the FSEs’ role. This includes: service training; skill development;
updating information; giving advice; and
checking and preparing quality of information.
4.2.1.1 Training
Most of the participants (2, 5, 7, 8, 9, and 10) described that as part of their role they needed to
have service training and skill development before commencing and during their position. As
Participant 7 stated: “We get training. When you are standing behind the service desk, …every
different area we have a manual with all our policies in there.” Solomon et al. (1985) support
that, in the learning process, service providers may take an apprenticeship or a training program
to achieve their role requirements.
4.2.1.2 Skill Development
The interviews also showed that FSEs learn skills from their colleagues and supervisors. As
expressed by Participants 2 and 9:
“I did a short course with XXX (name) where I did a customer service skills
course. But a lot of the training was on the job through the contact centre.”
And “I learn from co-workers, listen to what other people say, and pick it up
while doing the role” (Participant 2).
And:
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“Through training, XXX (name) was telling me all the time...When I started,
we had four weeks training...Then we had modules that we do through our own
little illumination, our own little intranet...We have refreshers on our basic
training. If anything new comes in, someone will come here before work and
address us. If it is overly, like if it is big, we then get sent over to the training
centre to learn” (Participant 9).
Several studies support this finding. Chiaburu and Harrison (2008) found that co-workers are
important for their colleagues’ roles, attitudes, and effectiveness. Schillewaert, Ahearne,
Frambach, and Moenaert (2005) state that co-workers support the role of other colleagues by
providing performance feedback, communicating, and offering mutual assistance and
collaboration. Further, Chiaburu and Harrison (2008) add that co-workers provide information,
are involved in behavioural support for some activities, and shape colleague’s roles and beliefs
about what s/he should or should not do.
4.2.1.3 Updating Information
Furthermore, the FSEs also had a designated role to continually update, maintain, and improve
the changing information, knowledge, service skills and their abilities to meet customer needs.
Participant 5, 6, 8, 10 stated:
“...We try and gather the same data. We look at how trends are changing in
service delivery. Then from that we find out specific areas that we need…We
think we might be interested in or need more information. We drill down in
those areas” (Participant 5).
And:
“...We communicate a lot with other faculties. Just to keep up to date with the
information we give out to the students” (Participants 6).
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And:
“...It is called “e-training on line.” Basically, when we are due to basically re-
do it. It will come up say in six months that you need to be trained in this or
you do a refresher pack or if you need to know about security or little things
that change or updates. They go on with those every month, and they follow it
through. Sometimes you do it every six months and other times they will tell us
every two to three weeks what is changed, what we need to know and then we
apply it…We have to do a lot of training...Our initial training is two weeks
full-time... You do initial training where they show you how to use your
machine and tell you all the principles…Once we have done that, then we come
back and we do another two weeks on sales. Initially, they set you up just to be
able to do customer service. Then you come back and do the sales as well”
(Participant 8).
Moreover:
“We have training on different things that come up. They upgrade things and
we have to do what they call re-skilling...There might be a new product come
out. They just to go over things for the staff, saying this has changed or that
has changed; and that can vary when it comes out. We do have a retail update
once a week that I print off. They must read it and sign it because procedures
might have changed in certain aspects of accounts or the way we process credit
card payments or just different things. They must read that every week if there
are any changes that happen” (Participant 10).
This theme is well supported in the literature. Ackfeldt and Malhotra (2013) note that if FSEs
do not have sufficient and up-to-date knowledge and training, this might impair their
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confidence and sense of accomplishment. Further, Harris and Bonn (2000) support that
employees must continually update their skills, knowledge, and abilities to meet customer
demands. Updating different kinds of trainings, such as technology, reading, writing, and
customer-relations skills, is necessitated to assist the varying needs of employees, as well as
requirements of their own positions (Harris & Bonn, 2000).
4.2.1.4 Giving Advice
The interviews suggested that other than training and developing skills, the FSEs had duties to
provide information, advice, and acknowledge customers about their services/products.
Participants 1 and 2 expressed about how they keep the customer advised and informed:
“Once a student comes into the student accommodation office, I will explain to
them how to look for accommodation. Then I always introduce the student to
how to use our rental database in the website, to have a look at the shared
accommodation and property if they look for it” (Participant 1).
And:
“...I give course advice about undergraduate degrees. I also organise the credit
transfer when students apply for it. And I run the undergraduate mentoring
program…Generally students will come in and ask a question and it might lead
on to further questions. It is really just talking to them and they might need
something they do not even realise that they need. In that way we often give
more information because they might not be aware of some services that are
available.” And “I guess that sometimes students need something right away.
So, we will do our best to facilitate that...” (Participant 2)
Avkiran (1999) supports that service employees need to have competence in their knowledge
of services and products.
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4.2.1.5 Checking and Preparing Quality of Information
The FSEs are responsible for reviewing information about their services and preparing
themselves before having interactions with customers. As Participants 1 and 3 stated:
“...The accommodation on that rental database is how it works. It is just
normal landlord. If they wanted to list their property or their room, they put it
in their website. Then the student is looking at that website, and then they
contact the landlord. I am not involving with that. But before students see it, I
have to confirm it. We never know that some landlords try to misuse the
students. To avoiding that, we are actually checking them before students see
the accommodations. That is a big concern about that. I do not need to do any
research or anything. I am just checking that databases...” (Participant 1).
And:
“...You get periods where you are going to get repetitive type of questions from
students’ clashes at the beginning of semester, exam requests, viewing exam
scripts. You get those sorts of things happening. You get used to that; you
familiarise yourself with that and you are prepared” (Participant 3).
Berry and Lampo (2000) support these findings that employees can prepare ahead of time for
customers’ special requests and so serve customers more effectively.
4.2.2 Theme Two: FSEs Meet the Job Requirement
This section examines the data related to theme two which is differentiated by the focus on role
and obligation, directed towards a customer’s queries and problems. As a summary, Table 4-4
explains the components of the FSEs’ job requirement that emerged from the data.
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Table 4-4: FSEs Meet the Job Requirement
Theme Components
FSEs meet the job requirement. This includes: responding to customers’ needs
and enquiries; and helping customers within the
duty boundary.
In this theme FSEs were entrusted and involved in the responsibility of service, as required by
the firm to perform their job. Several components were found when FSEs performed their role
according to their formal duty. The components were several actions to respond to customer
needs and queries and helping within the duty boundary. For example:
“...It is important to find out and exactly understand what they ask and then
addressing that…I think it is important that you understand what the person is
enquiring about. Then, you can either help them with the information you know
about the school. Or if it does not involve the school and it is another person
or another office; you direct them to the correct people…I will answer queries
at the reception counter. That may be from a student or from visitors, or other
people in the university might come and ask questions. I will either answer
directly if I can. Or I find out from other people the information that they need.
I also then answer the phone and direct queries” (Participant 3).
And:
“…We do not try to sell what they do not need. We just try to give them what
they want. And because our focus is the customer is number one, so, we are
trying to satisfy their needs rather than ours...If we are going to do customer
service, we need to do what is provided from us, and that is help the customer
satisfy their needs” (Participant 8).
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Basically, FSEs know that their behaviours during the service encounter have a great influence
on the customers’ perceived quality and satisfaction (Bitner et al., 1990). As Participant 7
stated:
“...We have got to try and help the students as much as we can, but we cannot
bend the policies of the University because it has to be right…”
Even though the participants tried to do their best for the customer, they needed to follow the
firms’ rules and policies (Liu et al., 2013).
4.2.3 Theme Three: FSEs Show a Considerate Manner to Customers
This section explores the data related to the theme of a considerate manner of FSEs, while they
were serving the customers. As a summary, Table 4-5 describes the related components which
are: courtesy; politeness; friendliness; niceness; and respect.
Table 4-5: FSEs Show a Considerate Manner to Customers
Theme Components
FSEs show a considerate manner to customers. This includes: courtesy; politeness; friendliness;
niceness; and respect.
The data revealed that the considerate manner or courtesy of FSEs occurred when they perform
the activities, which are characterised by the respects for and considerations of the customers
(Gotlieb, Levy, Grewal, & Lindsey‐Mullikin, 2004). As Participant 3, 6, and 8 stated:
“...It is basically always being courteous to people... I always try and make
sure that we are courteous and I think all the girls (her co-workers) here are
wonderful. They all try hard to do that…I think, just being polite. That is not a
policy, but it is just an understanding” (Participant 3).
And:
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“Number one is student-centric service, we have to cater for their needs and
be friendly, obviously, and courteous” (Participant 6).
Further:
“...When you see someone comes to the counter and they are grump. Well, there
must be a reason they are grumpy. Obviously, they have been treated wrong,
but all you can do is be nice. If they do not like it, at least you have tried…I
have got one lady who comes in. She does not swear but she throws the book
at you. And I just say to her, ‘what can I help you with?’ in a nice manner…If
I want to be treated with respect, I expect to do the same to other people. Do
you know what I mean? If you want that kind of respect from people, you have
got to give the same thing back; otherwise you will not get it” (Participant 8).
Examples of considerate manner include being courteous, polite, friendly, nice, and respectful
(Froehle, 2006; Rego & Cunha, 2008; Zaim et al., 2010). Based on Maloney (2002) and Froehle
(2006), a considerate manner may affect customer satisfaction and strengthen the rapport and
assurance dimensions of service quality. A considerate manner helps to create a personal and
trusting relationship between the customers and the FSEs (Froehle, 2006).
The FSEs also tried to avoid displaying unfavourable attitudes and behaviours that would lead
to service encounter failure. As expressed by Participant 9:
“...We used to get all the international students. I mean that was a big customer
service thing there. It is very overwhelming coming and leaving your family.
Then coming here and having someone is rude. A lot of the students were here
for three or four years. So, no, we should be not like that…”
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Several authors (i.e. Helms & Mayo, 2008; Sutton & Rafaeli, 1988; Tax, Brown, &
Chandrashekaran, 1998) support that rudeness and a negative attitude of FSEs represents poor
service quality, causes customer anger, and reduces customer retention.
4.2.4 Theme Four: FSEs Present a Personal-Involvement Expression
This section explores the data related to theme four, which revealed that half of the participants
liked, enjoyed, and felt good about their jobs. As a summary, Table 4-6 delineates how FSEs
show their feelings, attitude, and personal involvement while doing their roles.
Table 4-6: FSEs Present a Personal-Involvement Expression to the Customers
Theme Components
FSEs express their personal involvement towards
their jobs to the customers.
This includes: enjoyment; interest; liking;
happiness; and good feeling.
Participants 1, 2, 4, and 8 thought that the nature of their work was intrinsically interesting
and/or pleasurable (McMillan, Brady, O'Driscoll, & Marsh, 2002; Ngoc Tram Anh, Tien Dung,
Uyen Tram, & Ngoc Thuy, 2016). Ryan and Connell (1989) and Graves, Ruderman, Ohlott,
and Weber (2012) state that intrinsic motivation is an important aspect of enjoyment of work,
which comprises the affective components such as interest or pleasure. As Participant 2 and
other FSEs (4 and 8) expressed, they found their jobs interesting and nice and they liked and
were happy with their work.
“With my job, there is a lot of routine which is nice…I am working directly
with students and running events for first year students. Like next week we have
a pancake day which I will be running. It is just a little bit of interesting work
amongst the process work as well as customer service which is always
interesting as well…I really enjoy it. I have worked in roles before where I did
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not have that and I really missed it because it makes the day interesting, and it
gives you a more rewarding part of your job…I really like my work. I guess I
am a carer and nurturer. If there is any way that I can help somebody, I will
generally try to do that. I guess that’s why I would not just say no, I would
always try to say yes if I am allowed to” (Participant 2).
And:
“I like this job very much, I do, because I am a people person and I think you
have to be a people person to be in this job” (Participant 3). And: “I am a
people person. I like to talk. I am always enjoying it. I talk too much
sometimes” (Participant 8).
Further:
“It is actually a nice variety in this job because otherwise you are doing a lot
of paperwork and on the computer and it is really nice sometimes when
someone comes to the counter and you think, ‘Oh, hi,’ you have got someone
to talk to. So, it mixes up the job which I enjoy…I am happy to be at the counter
as long as I need to be to talk with them or to help; it is important - I think it is
very important. If I was going somewhere and asking for help, I would
appreciate help. On the flip side, I can understand they are coming because
they need something or want to find somebody. So, we want to help them”
(Participant 4).
Participant 1 stated that she wanted to share her experiences that might be useful to the
customers.
“I think it is fun to work with students. I am happy to work for the students
because I know how they are feeling because I also came over here as an
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overseas student. And I have experience, so I wanted to share my experience
with all the students. That is why it is a very good job that I can help at least.
It is not a big thing that I am helping them but at least I can help them with all
my knowledge and my experience. I am happy with it…I decided to study in
hospitality, because obviously hospitality is helping. It is a customer student
service, so always helping the student. Because I have experience at going to
the hotel and then in my country…When I worked in hotels or any restaurants,
some people is not that helpful. I did not really like it. From that period of time,
I was like, ‘Why are they like that?’...I was happy to help people because
obviously if I know something, I wanted to tell them, tell them everything, share
all of my experience, and then they understand about it…”
Ngoc Tram Anh et al. (2016) add that the employees who have a positive disposition and job
involvement (Mudrack, 2004) are inclined to think more positively of other people. Also,
enjoyment of work is related to a positive affect that enhances work attitude and behaviour
(Graves et al., 2012; Sok, Sok, & De Luca, 2016). As Participant 6 expressed:
“...I like meeting new people and even the difficult ones since they are
interesting characters. It is really lovely to meet people from all over the
world...I like people-watching if that does not sound creepy…I think the team
is really good and that is definitely what makes the job a lot easier. Everybody
supports each other and if you do have to deal with a difficult customer then
somebody is always happy to step in and help out. It is a really good job.”
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4.2.5 Theme Five: FSEs Show Empathy to the Customers
This section explores the data related to theme five, which revealed that FSEs express their
empathy while they are serving customers. As a summary, Table 4-7 delineates the components
of FSEs’ empathy that emerged from the data.
Table 4-7: FSEs Show Empathy to the Customers
Theme Components
FSEs show empathy to the customers. This includes: understanding the customers;
concern for welfare; caring; and being
sensitive/showing compassion.
4.2.5.1 Understanding the Customers
The interviews revealed that while FSEs were performing their service roles they demonstrated
their feelings and understanding of the customers’ needs. As expressed by Participant 3:
“...You try and explain it several times and sometimes it might seem that it is a
long time. And you might be annoyed, but then you think; well, this is not their
(students’) country. It is not their language. They need reassurance. It does not
bother me at all. And I just hope that the student walks away assured that things
are okay. Everything will be done correctly, or whatever I said will be done...”
And:
“I do not mind because if we have to sit down with them it is not easy to just sit
down for one or two minutes. Sometimes it takes a little time or more because
everyone interprets things differently. I could talk to you about something and
you might understand it really well. But I might go to someone else and they
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may not quite get it. Sometimes you need to be patient and explain properly
and thoroughly how to do things” (Participant 8).
4.2.5.2 Concern for Welfare
The data also revealed that FSEs showed their empathy by being concerned for their customer’s
welfare. Several authors (i.e. Ahearne, Jelinek, & Jones, 2007; Fisher, Vandenbosch, & Antia,
2008; McBane, 1995; Wieseke et al., 2012) support that empathy includes an affective
dimension in which the FSEs demonstrate an interest and concern for the welfare of their
customers. As expressed by Participant 4:
“Very clearly the motivating factor is people and their welfare. Prior to this
job that is what I have done and about counselling. I think that is just something
that is important to me. Some of that may come over into this role. When you
do have opportunities to be with other people then some of that might come
through.”
And:
“…Obviously in here as well, I am trying to make the student happy and feel
comfortable staying in Adelaide. Because it is their first time, and this is going
to be a first image forever that they are going to have of their stay in Adelaide.
I am trying to make it happy. I am trying to help them maximise. So, they feel
comfortable and that is my concern” (Participant 1).
4.2.5.3 Caring
Other than concern for the customer’s welfare, the interviews revealed another empathic
behaviour of FSEs, which was caring. Gerlach, Rödiger, Stock, and Zacharias (2016) support
that customers perceive the FSEs’ empathy and appreciate that they care about them as
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individuals. Ahearne et al. (2007) add that FSEs should consistently demonstrate their care for
customers. As Participants 1, 3, 8, 9, 10 stated:
“I am trying to take care of my customer. If they come in as my customer, I am
trying to maximise my customer service to them...” (Participant 1).
And:
“...I am a people person. I like my social activities. I find students interesting
too because sometimes they might be a little shy…or maybe a bit scared…So,
you try and make them feel comfortable and try and help them...and make them
feel like you are interested in their future. It is important” (Participant 3).
And:
“...You will not get everyone that comes in sick as well (A branch of a financial
firm is in a hospital), you know, that sort of thing. Other people have just had
operations; other people are dying of cancer. You see a lot of that and it is not
a nice thing to see, especially, at Christmas time. It is not nice to see, but you
just try to be caring for what they need and help them” (Participant 8).
In addition:
“...You want to do your job properly. And your job properly is servicing your
customers…you want to make them feel comfortable” (Participant 9).
And:
“...It is about interacting with people and having them feel comfortable talking
to you... it is about a customer opening up to you because they are
comfortable...I believe that is important to customers being happy”
(Participant 10).
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4.2.5.4 Being Sensitive/Showing Compassion
Furthermore, the interviews revealed that FSEs were also sensitive and showed their
compassion to the customers during the service encounter. The ability to feel as others do or
be emotionally sensitive to customers’ situation is an affective aspect of empathy (Gerlach et
al., 2016; McBane, 1995). As Participant 8 and 10 expressed:
“... You have got to be a little bit more empathic because it is a hospital (A
branch of a financial firm is in a hospital). Sometimes you get people that are
obviously not very well. So, you need to make sure that you are sensitive with
customers...” (Participant 8).
And:
“…One lady told me that she was going to be here (A branch of a financial
firm is in a hospital) for four hours today having an MRI…That was first thing
this morning. You have to be careful what you say or how you ask. Some people
you see all the time...You empathise with them and try and give them a solution
that they are happy with...You try to put yourself where they are and say, ‘Hey,
perhaps we can fix this, so, it will not happen again.’ I mean that is all you can
do - show them a bit of empathy and try and find a solution to fix it” (Participant
10).
Wieseke et al. (2012) add that empathy helps to reinforce the ability of FSEs to interact with
customers and present behaviours that are suitable for a specific person or situation. The
interviews revealed that FSEs not only perform their formal roles and duties, but they also
expressed their concern, caring, and displayed sensitivity or compassion to their customers.
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4.2.6 Theme Six 6: FSEs Build Rapport with the Customers
As a summary, Table 4-8 describes two components of rapport by FSEs. The interviews
revealed that Participant 8, 9, and 10 built rapport with their customers.
Table 4-8: FSE Build Rapport with the Customers
Theme Components
FSE build rapport with the customers. This includes: relationship, appreciation; and
trust.
As Participants 9 and 10 stated:
“...I have been here a while. I have gotten to know the customers and you just
offer that service. You get to know your regulars. I could be moved somewhere
else, but it might take me a while to build the rapport with someone…I have
got one lady that comes in here, XXX (name), and she always comes up and
sees me. She is probably in her fifties. She is got a daughter, that is in her
twenties, was studying and now she is working. I do a lot of banking for her
daughter via email...I send them (forms) back to be signed, but she cannot get
into the bank. So, XXX always knows that I will service YYY (XXX’s daughter),
her daughter. And then I will say, ‘Look, this product is out. We have changed
this to this, show YYY, see what she thinks.’ Just things like that and she emails
me back that she appreciates it because she cannot come in. For other
customers that I know, they will wait in line until I am free and then they will
come in” (Participant 9).
And:
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“I built that rapport up with the elderly lady who then brought her daughter
into see me...Then there is the one that comes in with the baby. Here is the next
generation…I used to call in and see a lady that went into a nursing home on
my way home some nights, just up on Portrush Road. And I found a letter the
other day from her brother thanking me for visiting her there. I used to only
pop in perhaps once a month on my way home from work just to say, ‘Hello,
how are you going?’ but apparently, she appreciated that...” (Participant 10).
This type of rapport behaviour is noted in the literature (Macintosh, 2009). The customer may
even have an emotional attachment to a certain employee (Coulter & Ligas, 2004). Further,
Participants 8, 9, and 10 stated that they also build trust with customer.
“…It is something that you want to do because there are customers that come
in regularly and that you build a rapport with them basically. When you build
a rapport with certain customers, they only want to deal with you. They do not
want to deal with someone else. That way if you are following it through with
them, you are building that trust with them. Then, they want to invest their
money with you because they know that they trust that we are giving them the
best options. Some people just want to sell, and other people will just say,
‘Okay, take this, it is best for you: take this, take that.’ But if you look at what
the profile is on the customer and you look at overall, you will know that this
part is missing or that part is missing. And you try to fill that gap and help them
with that” (Participant 8).
And:
“…Until you get to build that rapport with someone, and trust, when they come
in here” (Participant 9).
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And:
“I was on leave just a while ago and when I got back. There was an email from
one of the staff saying this customer did not want to talk to anybody else. He
will wait until I was coming back from holidays. Then he will ring. And, he did
at 10:30 the first day I was back after having a month off. I have done a whole
lot of things for him and his wife or his partner and his children. Probably two
years ago, he said, ‘Where have you been? Nobody ever told me about all this
and that and the other.’ So, he only ever wants to deal with me…And I am
thinking that is the customer relationship you build up. That is the rapport.
They always say that you do one thing wrong and 50 people will know, but if
you do one thing right they will tell five friends” (Participant 10).
FSEs build rapport with customers because they want to. The emotions of rapport play a
specific role in a service encounter, as they build up an affective feeling within a customer and
employee relationship (Biedenbach, Bengtsson, & Wincent, 2011). However, FSEs do not
break the rules and policies of the firm because of the relationships they have with customers.
The interviews revealed that the rapport needs time to build. According to previous literature
(i.e. Czepiel, 1990; Dagger & O'Brien, 2010; Gremler & Gwinner, 2000), service encounters
between FSEs and customers need to be repeated over time to build rapport.
4.2.7 Theme Seven: FSEs Help without Concern for the Duty Boundary
Five out of ten participants (50%) performed helping behaviours without concern for their
required duty.
Table 4-9: FSEs Help the Customers without Concern for the Duty Boundary
Theme Components
FSEs help the customers without concern for their
duty boundary.
This includes: volunteering to help
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Analysis of the data revealed that FSEs volunteered to help customers even though these needs
were outside of the employees’ formal tasks. Participant 2, for example, helped a customer
when the issue was urgent and could not be solved in the office hours by staying late to
complete the task. One might consider that this was simply in-role behaviour, but Participant
2 makes it clear that the benefit is towards the customer:
“Sometimes it might mean that I have to make my day a little bit longer. If a
student needs to graduate, or they need a transcript straight away, and I
understand they are applying for something else, I might stay a little bit later
and do that for them. It really depends on the situation, but we always try to
help out students’ needs within reason.”
Similarly, Participant 6 commented how she would help customers who appeared lost, even
though she was not required to do so. She thought that was a decent thing to do. She said if she
ignored them, they would not know what they should do.
“Sometimes people just look completely lost. It is much better to just go up and
ask if they are okay. If you overhear someone looking for something, you just
go ahead.” And “I have had people, music students, asking me because I have
been a music student. You go a bit further really and give them advice on which
ensembles are better than others. It probably is not what I should do but I think
it helps students out. Especially, first-years, they do not know what they are in
for. I think if you can make that transition easier because it was hard for me
personally, to transition from high school to university. It is just a good thing
to do” (Participant 6).
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Participant 3 felt sorry because of a customer’s background. When the student went back to his
country and needed a document, the FSE helped and even paid the postage. The student’s
family member sent a gift in gratitude but the FSE did not expect that.
“The student was visiting Australia as a - I do not think he was an exchange
student. He was here to do a few studies. He did a few subjects…I used to speak
Italian with him sometimes because that is my second language, Italian. He
liked the fact that I could talk Italian to him and we developed a friendship…
He had talked to me about his terrible conditions living in Albania with the
fighting and the machine guns and it was terrible…He went back overseas. He
needed a document from the office somewhere. I went to the student centre and
paid for the document and posted it to him because we had developed a sort of
friendship here at the school. I was helping him out and he was very grateful
for that. That was just something I did out of kindness because he was in
another country now.” (Participant 3).
Participant 4 also performed acts of helpfulness and goodwill.
“There was one PhD student who had been experiencing some pain in her
mouth and teeth. And another student had come to the counter and was asking
if someone could check on her because she was not doing very well…I needed
to see what was wrong and then see what she needed…She was very emotional
and she was in a lot of pain. So, I went down to where this person was, and sat
with them and spoke with them to try to identify what was going on. She was in
a lot of pain because she had actually just pulled her tooth out. It is very
distressed and a lot of blood. I took this particular student down to the
university doctor, and made sure then that she could see a doctor there and
then be advised of what she should do next”
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Participant 9 helped customers from competitors, which was something implicitly counter to
business policy. This FSE did this because she thought it was a right thing to do. As Participant
9 stated:
“...We got a new ATM and XXX (a competitor bank) Bank customers would
come in here and not know how to use it. So, we would go out there and show
them how to use it. Or some really sick people cannot – you know, just need
some help. We do not say, ‘No.’ even if it is another bank, we still go out there
and help them. Even if a customer comes in from another bank and they do not
know where YYY (another competitor bank) is; we get on the computer and
Google and tell them...”
That FSEs take extra attention and provide spontaneous and exceptional services has been
noted previously (Bettencourt & Brown, 1997; Raub, 2014). Also that FSEs volunteer to do
extra jobs for customers is noted by Chow, Lai, and Loi (2015) and Beatty et al. (2015). What
is noted in this research is the willingness of FSEs to help customers by taking on tasks outside
of their job boundary.
4.3 Analysis and Categorising the Themes
The seven themes identified in the interviews show that FSEs present themselves strongly in
their service encounters. The first two themes are evidently roles required by the firm and meet
the definition of in-role behaviours found in the literature. However, from the themes and their
components a better term is role-prescribed behaviours, where the firm is requiring that the
FSE have expertise and meet the job requirement. The role is prescribed by the firm, given the
service encounter.
To categorise the remaining themes as simply extra-role does not seem to do justice to the ways
the FSEs personalise and present themselves in the service encounter. An examination of the
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components from Table 4-5 onwards shows that these themes are more about the FSEs
representing themselves. The behaviour is from and by the FSEs, and within the service
encounter. The service encounter and the role of the FSE as an individual within that social
context suggest that this is not simply an extra-role, rather the FSE is taking on an individual
role inside the encounter.
However, that summary does not hold for the helping theme, which is instead focused on the
customer. The change in focus to the customer for the helping behaviours suggest that themes
three to seven might be categorised into two sets. Thus, following the criteria that the focus is
on the FSE, rather than the firm, the themes (iii) considerate manner, (iv) personal-involvement
expression, (v) empathy and (vi) rapport are designated as beyond role. The helping role seems
to stand alone, being focused on the customer and in some way not necessarily in the interest
of the firm nor the FSE. The way the customer fits within the service encounter sometimes can
bring forward helping behaviour from FSEs.
Table 4-10 summarises the seven important elements of the FSEs’ service-role behaviours
according to role-prescribed, beyond, and helping role categories.
Table 4-10: Theme Identification according to Category Classification of
Service-Role Behaviours
Research Question One: How do FSEs perceive their role behaviours while they are providing service
to the customers?
Role-
prescribed
Theme 1 Being an expert is part of the FSEs’ role.
Theme 2 FSEs meet the job requirement.
Beyond role Theme 3 FSEs show a considerate manner to customers.
Theme 4 FSEs present a personal-involvement expression to the customers.
Theme 5 FSEs show empathy to the customers.
Theme 6 FSEs build rapport with the customers.
Helping role Theme 7 FSEs help the customers without concern for the duty boundary.
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4.4 Chapter Summary
This chapter has presented the findings of the qualitative data analysis, which suggest that the
FSEs’ service-role behaviours are classified into three groups: role-prescribed, beyond role,
and helping. The findings show that two themes fit with role-prescribed behaviours: FSEs
expertise and job requirement. FSEs perform these behaviours to meet the formal and
prescribed role requirements of the firms and customers. The beyond role behaviours
comprised four themes: considerate manner, personal-involvement expression, empathy, and
rapport. When FSEs perform beyond role, they also express their attitudes and feelings towards
their roles, jobs, and themselves but most importantly towards a customer.
The expressions of positive attitudes and feelings within beyond role behaviours may affect
the customer’s perceptions of how the FSE performs and also influence perceptions of service
quality. The helping behaviour was found to include only one theme, the performance of tasks
that are outside of the formal tasks.
The next chapter presents hypotheses based on the insights developed in this chapter. The
constructs found in the qualitative research are tested and presented in Chapter 6 to 8.
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CHAPTER 5
HYPOTHESES AND CONCEPTUAL FRAMEWORK
The purpose of this chapter is to review the theoretical foundation of service-role behaviour
studies and to develop hypotheses concerning how customers perceive role behaviour and
dependent variables of interest to service firms. Thus, the focus of the thesis switches now to
customer perceptions of role behaviours.
The body of literature reviewed here encompasses the theoretical underpinnings of the
constructs which are the findings from the qualitative data analysis in Chapter four. The seven
constructs include expertise, job requirement, considerate manner, personal-involvement
expression, empathy, rapport, and helping without concern for the duty boundary. The review
leads to the development of the conceptual model used and examined in the study. These
constructs reflect three service-role classifications of FSEs; role-prescribed, beyond role, and
helping behaviours. This chapter also elaborates how the seven constructs affect customer
service satisfaction and value perception. Previous studies have described that there are solely
two role behaviours of FSEs which are in-role and extra-role behaviours. The purpose of the
remainder of this thesis is to examine whether a three-way classification of FSE service-role
behaviour is useful conceptually and managerially.
5.1 Research Hypotheses
The results of analysis in Chapter four show that FSE role-prescribed behaviours, comprising
expertise and job requirement, are likely to conform to past literature. There are various
typologies of role-prescribed behaviours, and the main idea underlying this performance is the
job specific context (Netemeyer & Maxham III, 2007). According to Choi et al. (2013: p. 148),
firm prescribed behaviours are the normal activities associated with fulfilling the basic job-
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requirements and the expected employee performances in serving the firm’s customers.
Bettencourt and Brown (1997: p. 42) also describe that their ‘role-prescribed customer service’
comprises presenting accurate knowledge of policies and products, greeting customers, cross-
selling the firm’s services, and other tasks. Moreover, to perform role-prescribed behaviours,
FSEs also need to meet and complete all those expected tasks and/or requirements for customer
(Bettencourt & Brown, 1997).
5.1.1 Expertise
In previous studies, expertise has been called different terms, such as assurance (Dabholkar,
Thorpe, & Rentz, 1996; Parasuraman et al., 1988), skills (Lewis & Entwistle, 1990), knowledge
and abilities (Lin & Hsieh, 2011), service training (Liao & Chuang, 2004), or competences
(Dellande, Gilly, & Graham, 2004; Parasuraman et al., 1985). However, the term ‘expertise’ is
used in this thesis to illustrate when the FSEs perform the service role by showing their
professional knowledge, required skills, abilities, suggestions, providing recommendations,
adaptability, giving advice and quality of explanation, and competence during the process of
service interaction (Barnes et al., 2011; Dagger & Sweeney, 2007; Lin & Hsieh, 2011; Stock
& Hoyer, 2005).
Expertise is important for service quality perceptions (Dagger & Sweeney, 2007). Brady and
Cronin Jr (2001) consider expertise as one sub-dimension of interaction service quality. Tsaur
and Lin (2004) explain that the FSEs should have suitable capability to provide a good service
for customers. Correspondingly role behaviour that supports perception of expertise by
customers is important to the awareness of service quality.
Dellande et al. (2004) explain that the FSEs who perform expertly can influence customers’
reactions to persuasive communication more than inexpert ones. FSEs with a low level of
expertise may have a limitation in ability to assist customers because they cannot deal with
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customer questions sufficiently (Stock & Hoyer, 2005). On the other hand, employees with a
high level of expertise are adept in effective problem-solving, managing in complicated
domains, and having an adroit knowledge of the company’s product/service and customer
needs (Stock & Hoyer, 2005). Expertise is significantly crucial for the businesses such as
insurance, banking, brokerage, legal, or medical services, which are perceived by customers as
high risk or where they feel doubtful in their ability to assess the outcomes (Zeithaml et al.,
2009).
Previous studies state that the expert behaviour, or the efficient and professional response of
FSEs, affects productivity and links to positive service evaluation and service quality, and so
leads to customer satisfaction (Barnes et al., 2011; Bitner et al., 1990; Dagger & Sweeney,
2007; Liao & Chuang, 2004). Dagger and Sweeney (2007) tested the effect of expertise and
outcome on overall perception of service quality of customers, and that expertise and service
quality were salient drivers of service satisfaction.
Additionally, the expertise of FSEs can also influence customer value perception. Wu and
Liang (2009) state that consumer appreciation of the FSEs’ expertise and service reliability is
measurable via customer value perception. Employees who have multi-skills and can perform
a range of duties during high and low demand periods in different facilities’ service operations
can increase customer value perception (Johnston & Jones, 2004). Thus, this suggests that
FSEs’ expertise directly impacts customer satisfaction and value perception. These lead to the
first set of hypotheses of this study:
H1a: Perception of expertise has a positive effect on customer service satisfaction.
H1b: Perception of Expertise has a positive effect on customer value perception.
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5.1.2 Job Requirement
Job requirement refers to FSEs’ role-prescribed behaviours in which their performances are
required as a part of undertaking the obligations and responsibilities of an assigned work and
job description, as expected by the firm and customers (Liao & Chuang, 2004; Tsaur et al.,
2014). Role-prescribed behaviours have been formed along two dimensions, productivity and
quality (Netemeyer & Maxham III, 2007). Productivity represents quantifiable output (i.e.
customer contacts and backroom functions), while the quality dimension includes formally
required behaviours during the FSEs and customer encounter (Netemeyer & Maxham III,
2007). The quality dimensions of role-prescribed behaviours are the ‘script rules’ or ‘job
descriptions’ that FSEs must perform (Netemeyer & Maxham III, 2007). Liao and Chuang
(2004) add that raising good questions, hearing customers’ needs, being able to assist them
when needed, and pointing out and relating service and/or product to their requirement are the
examples of service-role behaviours.
According to Raub and Liao (2012) role-prescribed behaviours are the essential factor in
affecting customer satisfaction. Customer satisfaction is generally based on the experience that
customers have with FSEs during the service encounter (Raub & Liao, 2012). To clarify this,
Liao and Chuang (2004) explain that the performance standards set by the firms are explicitly
based on customer expectations, interests, and expectations. Addressing these elements
encourages FSEs to engage themselves in behaviours while serving the customers (Liao &
Chuang, 2004). The performance and engagement in role behaviours of FSEs that reach the
customers’ expectation are important in achieving desirable outcomes and directly influence
their satisfaction (Liao & Chuang, 2004, 2007).
Furthermore, the study of Netemeyer and Maxham III (2007) states that employee behaviours
influenced both customer satisfaction and value perception. Thus, customers perceive that
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satisfaction and value arise from the performance of FSEs. Therefore, the following hypotheses
are proposed:
H2a: Perception of the job requirement positively affects customer service satisfaction.
H2b: Perception of the job requirement positively affects customer value perception.
5.1.3 Considerate Manner
The components of a considerate manner are courteous and/or kind behaviour of FSEs towards
the customer during a service encounter. According to several researchers (i.e. Chonko, 2015;
Froehle, 2006; Lam & Zhang, 1999; Rego & Cunha, 2008; Zaim et al., 2010), the courtesy of
FSEs involves integrity, politeness, consideration, kindness, being well mannered, and
friendliness. Maloney (2002) and McCain, Jang, and Hu (2005) add that respect and good
interpersonal skills are the key to courtesy. Showing consideration and a courteous manner
helps to build the service impression (Bokhari & Chowdhury, 2014) and creates rapport for a
favourable service encounter with the customers (Ford, 1995). Courtesy has been identified as
one of the ten dimensions of the basic structure of the service quality domain developed by
Parasuraman et al. (1988)’s SERVQUAL scale.
The behaviour of considerate manner includes verbal and non-verbal responses. Verbal or
phatic speech (Ford, 1995) includes two kinds of responses and small talk: (i) greeting words
such as “good morning”, “hello”, “see you later”; and (ii) courteous words such as “thank you”,
“please”, “can I help you?”, and “I am sorry” (Cockerell, 2013; Elizur, 1987). Non-verbal
responses include smiling, light laughter, head nods, forward leaning, touch, body orientation,
hand shaking, finger pointing, eye contact, and physical distance (Elizur, 1987; Ford, 1995;
Sundaram & Webster, 2000). Ford (1995) adds that nonverbal responses help to lessen the
psychological distance and increase friendlier relations between two entities.
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Ford (1995) found that customers provided more positive evaluations of service when FSEs
displayed a considerate manner. Several scholars (i.e. Lam & Zhang, 1999; Maloney, 2002;
Yang & Fang, 2004) support that considerate/courteous manner tends to make a significant
contribution to the customer satisfaction. Zaim et al. (2010)’s study examined the service
quality in the health care industry in Turkey, and found that courtesy is significant for customer
satisfaction. Further, a considerate/courteous manner is one of the attributes that customers
value highly from the firm (Crane & Clarke, 1988; Gotlieb et al., 2004; Smith, Bolton, &
Wagner, 1999). Tax et al. (1998) support that a rude or insincere manner by FSEs can affect
the value of the outcomes of a service encounter, especially in the complaint handling
experience and recovery. The following hypotheses can be drawn from this discussion above:
H3a: Perception of FSE considerate manner affects customer service satisfaction positively.
H3b: Perception of FSE considerate manner affects customer value perception positively.
5.1.4 Personal-Involvement Expression
Personal-involvement expression of FSEs in this study means the employees have enjoyment,
a positive attitude, job satisfaction, and are personally connected with their jobs and service
roles. The personal-involvement expression of FSEs may affect customer service satisfaction
and value perception. Previous literature supports these notions.
According to Sok et al. (2016) enjoyment of work refers to the aspiration of an employee to
pursue tasks which are enjoyable or interesting to him/her. When a FSE enjoys their work they
have a passionate involvement and gain fulfilment from their service goals (Sok et al., 2016).
Lyubomirsky, King, and Diener (2005) and Graves et al. (2012) state that employees who enjoy
their works are more likely to present surpassing performance and productivity.
Based on several authors (i.e. Brady & Cronin Jr, 2001; Dimitriades, 2007; Payne & Webber,
2006; Tornow & Wiley, 1991), the attitudes of the service employee establish the perceptions
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of a service encounter, define the quality of the delivered service, influence customer attitudes,
and affect customer satisfaction. Payne and Webber (2006) add that the attitudes of FSEs are
communicable to customers. On the other hand, if FSEs express poor attitudes, ignore, or treat
the customers impersonally, then dissatisfaction may occur during the service encounter
(Bitner et al., 1990). Bitner et al. (1990) note more examples of behaviours associated with
poor attitudes, such as failing to provide information, not regarding needs, not caring about
customers’ comfort, and being impatient.
According to Gounaris and Boukis (2013) and Payne and Webber (2006), employees’ job
satisfaction can influence the customer’s perception of service quality and satisfaction. The
satisfied FSEs tend to have a good mood, behave sensitively, care for others, and achieve a
higher performance level than those who have lower job satisfaction (Ackfeldt & Wong, 2006;
Boshoff & Allen, 2000). Malhotra and Mukherjee (2004) add that unhappy and dissatisfied
FSEs cannot deliver outstanding service to satisfy customers.
For service value perception of customers, Gil et al. (2008) found that the service encounter
can directly and significantly influence perceived value. For example, FSEs who are satisfied
in their job express positive attitudes which later affects the customer perceptions. The
discussions lead to the following hypotheses:
H4a: Perception of FSE personal-involvement expression has a positive effect on customer
service satisfaction.
H4b: Perception of FSE personal-involvement expression has a positive effect on customer
value perception.
5.1.5 Empathy
In general, empathy refers to a personal trait (Duan & Hill, 1996), or interpersonal process
(Wieseke et al., 2012) of an individual to sense and understand another’s feelings, thoughts,
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ideas, experiences, and perspectives (Pilling & Eroglu, 1994; Wieseke et al., 2012). Empathy
involves putting oneself in that person’s situations (Lazarus, 1991). For Batson (1987),
empathy also means an affective response that one person appropriately gives to another’s
circumstance rather than one’s own. At a theoretical level, empathy includes a set of
multidimensional components, both cognitive and emotional (Davis, 1980, 1983; Kerem,
Fishman, & Josselson, 2001). Based on the multidimensional concept Davis (1980, 1983)
proposes the Interpersonal Reactivity Index to explain four separate aspects of empathy;
perspective taking, fantasy, empathic concern, and personal distress. Two of these four
dimensions, namely perspective taking and empathic concern, explain the empathy construct
of this thesis.
The ‘perspective taking’ dimension is based on an intellectual or cognitive apprehension
(Hogan, 1969) and reflects an ability of an individual to anticipate the others’ thoughts,
behaviour, and reactions from diverse cues (Davis, 1983) and equally address another’s
perceived needs, opinions, or motivations (Wieseke et al., 2012). According to Davis (1980),
an individual steps outside the self when associating with other people. Empathy also refers to
the emotional component which includes empathic concern and emotional contagion aspects
(Coke, Batson, & McDavis, 1978). ‘Empathic concern’ refers to the degree to which the
individual expresses feelings of warmth, compassion, and concern for other people (Davis,
1980). Thus, when people express their empathy both a cognitive and an emotional view are
present.
Empathy is important in a service encounter, because it helps FSEs predict, interpret, and
anticipate the actions and reactions of customers (Håkansson & Montgomery, 2003; Pilling &
Eroglu, 1994; Redmond, 1989). In a service marketing context, empathy is one of the five
dimensions of the multi-item scale for measuring service quality or SERVQUAL
(Parasuraman, Berry, & Zeithaml, 1991). Several studies (e.g. Gould-Williams, 1999; Murray
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& Howat, 2002; Wang et al., 2004) examined how empathy in SERVQUAL affects customer
satisfaction and/or value perception.
For customer service satisfaction, many researchers (e.g. Aggarwal, Castleberry, Ridnour, &
Shepherd, 2005; Arambewela & Hall, 2006; Bloemer, De Ruyter, & Peeters, 1998; Culiberg
& Rojšek, 2010; Gerlach et al., 2016) found that empathy is significantly associated with
customer satisfaction. For example, Yavas, Bilgin, and Shemwell (1997) found that empathy
is a significant predictor of customer satisfaction. Kim, Kaplowitz, and Johnston (2004) found
that perceived physician empathy significantly influenced patient satisfaction. Also, Hocutt,
Chakraborty, and Mowen (1997) investigated how service recovery efforts impact the level of
dissatisfaction following a service failure. They found that after the service failure experience,
customers were most satisfied when FSEs showed high levels of empathy. Sparks and McColl-
Kennedy (2001) support that empathy by a service provider is a crucial factor of service quality
and customer satisfaction assessment. Sparks and McColl-Kennedy suggest that the FSEs
should demonstrate their concern during the service encounter because how customers feel
they are treated will influence their perceptions.
Additionally, empathy of FSEs is also essential for customer value perception. Wang et al.
(2004) found that empathy has a significantly positive influence on customer value in China’s
mobile communication market. Thus, the findings from previous studies suggest that empathy
of FSEs directly influences customer satisfaction and value perception. The research cited
supports the following hypotheses:
H5a: Perception of FSE empathy positively affects customer service satisfaction.
H5b: Perception of FSE empathy positively affects customer value perception.
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5.1.6 Rapport
Rapport has been defined variously by different researchers. For example, Tickle-Degnen and
Rosenthal (1990: p. 286) suggest that individuals experience rapport when they ‘click’ or had
‘chemistry’ to each other during an interaction. LaBahn (1996: p. 30), whose study examined
the rapport between advertising agencies and clients, supports the definition of Tickle-Degnen
and Rosenthal (1990) that “rapport is the customer’s perception that the personal relationships
have the right ‘chemistry’ and are enjoyable.” For, Dell (1991: p. 101) rapport is how good
customers feel in general about their interactions with the seller. Bernieri, Gillis, Davis, and
Grahe (1996: p. 113) define rapport as a quality in the relation or connection between actors,
especially relations ‘marked by harmony, conformity, accord, and affinity.’ While Oly Ndubisi,
Haryati Shaikh Ali, and Oly Ndubisi (2011) describe rapport as an antecedent to relationship
quality. Contemplating all of these definitions, Gremler and Gwinner (2000) conceptualise that
rapport occurs when two parties had enjoyable interaction and personal connection between
each other. Gremler and Gwinner (2000: p. 92) define rapport as “a customer’s perception of
having an enjoyable interaction with a service provider employee, characterised by a personal
connection between the two interactions.” Macintosh (2009) suggest that building customer
rapport is an essential intermediate step in the relationship building process.
In the service context, Fatima et al. (2015) state that FSE is a key role in building and keeping
relationships with customers. Additionally, rapport is an indicator of relationship quality
(Delcourt et al., 2013). They add that the quality of relationship experience due to rapport is
characterised by reciprocal understanding and gratifying communication. Rapport also
includes the interpersonal facet of service quality and is a crucial factor of customer satisfaction
(Hennig-Thurau, Groth, Paul, & Gremler, 2006) and value (Gremler & Gwinner, 2000). Fatima
et al. (2015) add that rapport may have a positive effect on overall satisfaction and leads to
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better understanding and clearer expectations for customers, and that it may strengthen a
greater satisfaction. Several researchers have found the relationships between customer and
employee have a positive effect on customer satisfaction. The summary of those findings is
shown in Table 5-1.
Table 5-1: Customer-Employee Rapport and Customer Satisfaction
References Samples Methodology Findings
Fatima et al.
(2015) Bank customers
A survey
methodology
Rapport can strengthen one’s
commitment and can re-evaluate
his/her satisfaction. Their findings
confirmed the strong effect of rapport
on satisfaction.
Gremler and
Gwinner (2000)
Bank customers
and dental patients
A self-report
questionnaire
They found that the two dimensions of
rapport, enjoyable interaction and
personal connection, have positive
relationships with satisfaction.
Kim and Ok
(2010)
Staff members of a
University
A self-report
questionnaire
They found that the rapport between
the customer and the service employee
has a positive influence on customer
satisfaction.
Macintosh (2009) Dental patients A survey
methodology
Rapport is related to customer
satisfaction
Based on the discussions presented above the rapport of FSEs directly influences customer
satisfaction and value perception. The following hypotheses are posited:
H6a: Perceived rapport affects customer service satisfaction positively.
H6b: Perceived rapport affects customer value perception positively.
5.1.7 Helping without Concern for the Duty Boundary
According to the Oxford Dictionaries (ANON, 2012), ‘help’ means “to make it easier or
possible for someone to do something by offering them one’s services or resources.” Helping
behaviours are an action that provides benefit to a person(s) in need of aid and when there is no
prior promise of reward (Bar-Tal, 1982). This implies that helping behaviours are a voluntary
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act. Also, Raub and Robert (2010) state that helping behaviours are an example of associated
extra-role behaviours that focus on supporting other person(s) even though it is not required.
Both prosocial behaviours and altruism are possible behaviours in the service sector (Bettencourt
& Brown, 1997; Guy & Patton, 1989). However, helping behaviours, prosocial behaviours, and
altruism are not identical. Previous studies have different definitions and confound the
characteristics of these three terms. This is despite each term representing an important and
complementary role in the delivery of service quality.
Of the three constructs helping behaviour, prosocial behaviour, and altruistic behaviour, this
thesis pursues the first for several reasons. First, both prosocial and altruistic behaviours hold
other people outside of the behaviour as important and as a reason for acting, whereas helping
is concerned only with the individual(s) inside the actions. Second, helping, being focused only
within the behaviour, is appropriate for a two-party action. In helping behaviour, both sides
may benefit, but the helper(s) does not expect or require a reward. In the views of Diamond
and Kashyap (1997) and Weiner (1980), the helper(s), which is FSE(s) in this study, considers
internal reward, which is a feeling of praise and honour, and external rewards, which can be
the approval and friendship, power gain, and monetary. Of course, whether a FSE does perform
a helping activity is also dependant on the firm giving permission, but equally, as a service
encounter can never be fully controlled, helping behaviour remains always a discretionary
possibility. Given the research focus is on the service encounter, and not on wider society,
helping behaviour is the focus of this thesis.
In a service context, FSE helping behaviour is likely to have a direct effect on both customer
satisfaction and value perception. According to Choi et al. (2013) customer satisfaction and
positive emotional response is increased by exceptional service. Choi et al. (2013) note that
role-prescribed behaviour is less critical to customer satisfaction than helping behaviours.
Similarly Walz and Niehoff (1996) found that helping behaviours can increase service quality
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and that this enhances customer satisfaction and reduces the likelihood of complaint in limited-
menu restaurants. Helping behaviour thus seems important to customer satisfaction and so also
to perception of service value. Based on the discussions presented above, the following
hypotheses are posited:
H7a: Perception of helping without concern for the duty boundary positively affects customer
service satisfaction.
H7b: Perception of helping without concern for the duty boundary positively affects customer
value perception.
5.2 Conceptual Framework
The conceptual framework in Figure 5-1 summarises the hypotheses.
Figure 5-1: Conceptual Framework
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5.3 Chapter Summary
This chapter introduces seven sets of hypotheses and a conceptual framework. Based on
previous literature, seven roles of FSEs were argued to be associated with customer satisfaction
and value. These seven independent variables include: expertise, job requirement, considerate
manner, personal-involvement expression, empathy, rapport, and helping without concern for
the duty boundary. The next chapter elaborates the quantitative methodology adopted in this
thesis.
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CHAPTER 6
QUANTITATIVE METHODOLOGY
This chapter provides a discussion of the methodological approach. First, the research design,
unit of analysis, and data collection method are established. Next, sampling and data collection
procedures of the pre-test and post-test (main) studies are described. Next, follow the
descriptions of questionnaire designs with a focus on the structure of the questionnaires.
Subsequently, the operationalisation of the constructs and measurement scales are discussed.
Following the ethics and information confidentiality, data entry is explained. Finally, the data
analysis plan is outlined.
6.1 Research Design
The purpose of the quantitative study is to examine the conceptual model which comprises path
diagrams showing associations between different variables. These variables were identified
from the results of qualitative data analysis and adapted from extant literature to investigate the
hypotheses posited in the study. Quantitative data help to structure and explain the relationships
between variables (Hopkins, 2008), which are considered in the model.
A cross-sectional approach was employed in both pre-test and post-test surveys. Cross-
sectional research involves collecting data from a given one or more sample(s) of population
elements (Malhotra & Birks, 2007). This approach gives a snapshot of the variables of interest
at a single point of time (Malhotra & Birks, 2007) and allows for analysis of the variables with
structural equation modelling.
A questionnaire was developed and distributed in two study stages. The measurement scales
used to represent each of the constructs were adapted to suit the research contexts. Specifically,
constructs previously addressed to frontline service employees were rewritten for presentation
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to customers. The pre-test was administered to university students. The data from the pilot
study was employed to conduct confirmatory factor analysis of scale items of the constructs.
The questionnaire was then adjusted on the underlying support of these findings before the start
of the main study. The post-test, a main study, was conducted in a financial service firm in
Adelaide, South Australia.
6.2 Unit of Analysis
The unit of analysis is the entity that is being studied, such as an individual person, the society
or agglomeration of individuals (Yurdusev, 1993). An important study research objective is to
examine the perceptions of customers towards service-role behaviours of Frontline Service
Employees (FSEs) during the service encounter. Most prior business and marketing research
has focused on how employees perceived their own role and/or their own service-role
behaviours in the firm context (Ahearne, Bhattacharya, & Gruen, 2005). Therefore, considering
the objective and research gap of this thesis, individual customers who had a service encounter
with FSEs at a financial service firm in Adelaide constitute the unit of analysis for the main
study.
6.3 Data Collection Method
The customer respondents completed a self-administered questionnaire using Qualtrics, an on-
line survey platform. For the main study, after customers had interacted with the FSEs, the
researcher handed them a computer-tablet device and let them answer the questionnaire
privately. This gave the respondents a feeling of comfort and anonymity (Denissen, Neumann,
& van Zalk, 2010). A self-administered survey questionnaire may receive some inaccurate
responses (Malhotra & Birks, 2007), but this method reduces social desirability bias by
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isolating the subject from the researcher (Nederhof, 1985). The method assured respondent
anonymity and that the researcher did not further influence the respondents.
The online survey was deemed the most appropriate for this research for the following
additional reasons. First, an online survey is a simple and economical method, which eliminates
the cost and time of printing and data entry (Denissen et al., 2010; Malhotra & Birks, 2007;
Wright, 2005). The thirty-seven questions of this thesis could be completed within a very short
period of time. Second, there was no missing data due to routing and skipping errors (De
Leeuw, Hox, & Kef, 2003). Based on previously given answers, the Qualtrics program directs
respondents to the next question based on programmed logic and guides them through the
questionnaire (De Leeuw et al., 2003). Third, the data were able to be checked in a timely
manner (De Leeuw et al., 2003). The ability to check was important on the first day of
surveying, as it was found that the three, five, or seven point scales did not allow the
respondents to discriminate the high levels of service perceived (Friedman & Amoo, 1999).
Once this issue was understood, the researcher increased the scales to 11 points. Nevertheless,
online surveys have a common limitation of technical problems (Malhotra & Birks, 2007).
During data collection, there were very brief periods of software delay and poor internet
connection, but these issues did not affect data collection.
6.4 Pre-Test Study
The main purpose of conducting the pre-test was to conduct a preliminary factor analysis of
the observed variables and the constructs’ reliability and validity. Factor analysis allows for
the identification of measurement items with low unstandardized factor loadings. These items
have poor internal consistency with the other items representing the construct and diminish the
construct validity. Therefore, these items were excluded from the scales before the
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commencement of main study. The items removed are asterisked with the questionnaire of the
constructs in section 6.7.
6.4.1 Sampling
A non-probability sampling technique was employed for the pre-test study (Sreejesh,
Mohapatra, & Anusree, 2014). Convenience sampling included university students, both
undergraduate and postgraduate who studied in Adelaide, South Australia. Student samples
have been noted for the absence of external validity and generalisability by several researchers
(Calder, Phillips, & Tybout, 1982; Cunningham, Anderson, & Murphy, 1974), however, the
choice of pre-testing on university students ensured a high response rate and overcame time
and budget limitations (Chowdhury & Ahmed, 2009). Moreover, the primary focus in this early
stage of research was internal validity considerations (Chowdhury & Ahmed, 2009; McKay,
Hair Jr, Johnston, & Sherrell, 1991; Parvin & Chowdhury, 2006).
6.4.2 Data Collection Procedure for Pre-Test
Data was collected both online and with a paper survey (at the university). Students were
offered the opportunity to choose between a Web-based online or a paper based survey. The
researcher approached the students. They were informed of the nature and purpose of the
research. Then they were invited to join the research survey. They also were further informed
of the purpose and nature of research and were asked if they had any questions. In the
questionnaire, the respondents were asked about their perceptions of one service encounter
where they interacted with the FSE for at least a few minutes or better if even longer in the last
seven days. Both pre-test and post-test surveys share the same constructs.
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6.5 Main Study: A Financial Service Firm
The main study of this thesis was conducted at a financial service firm (i.e. a bank). The
objective of the main study was to assess the hypothesis explicated in Chapter 5.
6.5.1 Sampling
The current study is a pioneering initiative to identify the service-role behaviours of FSEs in
the eyes of customers and how their perceptions affect service satisfaction and value
perception. The target population of this thesis included any customers who received service
and had an interaction with the FSEs. Sample respondents were selected from amongst the
customers in a single branch of one of Australia’s largest financial service firms. The standard
profiles of respondents matched the typical customers of Australia financial service firms,
representing a cross-section of customers from various demographic backgrounds. The
descriptions of customers’ demographic backgrounds are presented in Chapter 7.
The ideal is to use a probability sampling technique to increase reliability and generalizability
(Malhotra & Birks, 2007). However, random sampling was not feasible given the time and
resource constraints of administering the survey within the window of opportunity afforded by
the firm and the FSEs. A judgemental sampling technique was employed, by which the
population elements were selected to match a normal customer profile, by the researcher
(Malhotra & Birks, 2007). The researcher chose the elements to be included in the sample
because those individuals were believed that they were appropriate and representative of the
population of interest (Malhotra & Birks, 2007). For example, the researcher approached and
asked customers to participate in the survey after they had the interactions with FSEs. The
researcher was the only one who administered data collection at the financial service firm for
the entire period (approximately thirty days).
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This research will conduct Structural equation modelling (SEM) method to analyse the data.
SEM is a multivariate approach which is quite sensitive to sample size (Hair, Black, Babin, &
Anderson, 2010). A small sample size is less than 100 (Kline, 2005); 200 provides a medium
sample size and basis for estimation (Hair et al., 2010). After screening and discarding the
incomplete responses and missing values, 250 usable surveys, out of 345 administered, were
available for analysis. This represents an approximate completion rate of 72.5%. This number
of surveys meets the sample size of 200 or more suggested by (Hoelter, 1983) for analysis with
the Maximum Likelihood Estimator (MLE). In relation to model size, the least sample size
should be greater than the elements in the correlation matrix (Teo, Tsai, & Yang, 2013). A
desirable ratio of sample size to the number of model parameters should be 10:1 or 20:1, but
5:1 is acceptable (Kline, 2005). Therefore, the sample size of this research is acceptable, but
relatively small.
6.5.2 Data Collection Procedure for Main Study
To initiate the survey procedure, the researcher contacted the managers of three service
organisations in Adelaide, South Australia. Only one firm agreed to participate and was willing
to allow the researcher to conduct the study in person at one busy branch of the financial service
firm. The required sample size was one issue that the other firms gave for non-approval.
After a manager and frontline service employees of this firm agreed to participate in the study,
the researcher went to the branch of the firm and had a meeting with all the staff. The FSEs
were informed of the nature and the purpose of research. The FSEs were instructed to ask the
customers to voluntarily participate in the data collection. The data collection process started
one week after the meeting when all FSEs understood the procedure.
With regard to the guidance of FSEs about the nature and the purpose of research before the
customer encounters, the researcher was aware and concerned that a social desirability bias
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might be created. This social desirability may occur when the FSEs act their service-role
behaviours that they believe to be acceptable rather than how they really feel or behave
(Malhotra & Birks, 2007). Therefore, prior to data collection, the researcher informed the FSEs
that their details and behaviours during the study and the answers from the customer
respondents will be anonymous and will not affect the employees’ work and their future
promotions.
During the data collection, the employee used his/her judgement to ask that customer for their
consent to participate in an online questionnaire with the researcher before the customer
finished the service encounter. At that time, the researcher again introduced the purpose of the
study to each customer respondent, provided information regarding the survey process, and
asked for his/her consent. If the customer respondent concurred, s/he then completed the self-
administered online questionnaire using an internet enabled tablet device (Ipads), which was
provided by the researcher. On any day, there were four to five FSEs per session. Thus, the
total number of employees who participated in the research was nine people. The time
commitment of data collection by the researcher was six to seven hours per day, including
waiting time, and was for approximately thirty days.
6.6 Questionnaire Design
The questionnaire is included in Appendix B. The questionnaire was designed to avoid any
ambiguous wording and/or question. Ordinary words and vocabulary were employed in the
questionnaire. No technical marketing words were employed. The screen layout of the
questionnaire was set up in a logical order to reduce the error rate and encourage complete
responses (Malhotra & Birks, 2007). From the pre-test, several improvements were made,
including corrections of wordings and grammar, instruction clarification, and layout setup to
reduce the time, effort, and frustration in completing the questionnaire (Brace, 2008). This
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meant all respondents could easily understand the questions without assistance from the
researcher.
The questionnaire was designed to capture the perceptions of respondents towards the FSEs’
service-role behaviours during the service encounter and how the customers perceived
satisfaction and value perception. To collect the perceptual data, the majority of the questions
applied multiple-item scales (Hair Jr & Lukas, 2014). Other structured questions were
dichotomous and multiple-choice questions.
In addition, a force-response logic was employed on all questions to ensure respondents did
not miss any particular item. All the questions were structured inside sections with instructions
(Malhotra & Birks, 2007). The instructions informed the respondents to answer all questions
even if the multiple-item scales of each construct looked repetitive. The repetition may cause
weariness and/or confusion to the respondents, but is a requirement of the latent construct
measurement. As the questionnaire contains a numbers of statement scales, fatigue effect can
occur to the respondents (Brace, 2008). In order to alleviate inattention and pattern responding
bias, the presentation of the statements was presented in a random order (Brace, 2008). To
avoid the confusion, the statement scales were separately randomised only within the similar
theoretical concept.
6.6.1 Questionnaire Structure of Main Study
First Section – This section captured the introduction and instructions. The introduction
included a brief outline of the research project and researcher’s identity and contact details.
Respondents were instructed that questions relate to solely the interaction they just had with
the FSEs, not the numerous prior interactions that they may have had with the employees. The
respondents were advised that their personal information was not needed for this research and
that the study was academic research that was not sponsored by a third party.
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This part also identified that the respondents were more than 18 years of age. This age is old
enough to provide one’s own consent to participate the research (Australian Government, 2007;
Government of South Australia, 2014).
Second Section – This section represented the scale items of each of the constructs. The
respondents were asked to answer the attitude statement-scale questions. Items of the eight
constructs were presented to capture the respondent’s perceptions towards the employee’s
service-role behaviours during the service encounter s/he just had.
Last Section – Questions of gender and frequency of visiting the financial service firm per
month were included at the end of the questionnaire. The responses of these two questions were
explained as the description of sample groups in Chapter 7.
6.6.2 Scaling
All the items/questions defining various constructs used in this thesis were measured by using
an interval scale of measurement, ranging from 1 representing strongly disagree to 11 as
strongly agree. Interval scales provide a straightforward way of ranking and distance
information of the attitudinal and perception information of each item, but does not allow a
ratio analysis (Brace, 2008). The interval scale has numerically equal distances (Brace, 2008;
Malhotra & Birks, 2007), meaning the respondents perceive an equal-sized range between the
points on the scale (Friedman & Amoo, 1999). The purpose of this thesis is to have well-spaced
anchor points indicating the possible range (Devlin, Dong, & Brown, 1993) of
opinions/perceptions about the service-role behaviours.
Choosing an odd number of intervals allowed a middle point, which increases the scale’s
sensitivity in comparing responses of various respondents (Myers & Warner, 1968). The
interval scales were an appropriate measurement for analysis using the mean, standard
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deviation, factor analysis, correlations, regression, ANOVA, and t-test (Brace, 2008; Malhotra
& Birks, 2007). These analyses are examined in the next chapters.
6.7 Operationalisation of the Constructs
This section introduced the operational definitions of the individual constructs employed in
this thesis. The definitions explain how constructs have been operationalised for the specific
context of the study, and the perceptions of customers towards the FSEs’ service-role
behaviours. The main constructs of this survey are classified into three groups; role-prescribed,
beyond role, and helping behaviours. FSEs’ expertise and customer/job requirement constructs
are grouped into role-prescribed behaviours. Considerate manner, personal-involvement
expression, empathy, and rapport constructs are categorised into beyond role behaviours.
Helping without concern for the duty boundary construct depicts the helping behaviour. The
dimensions of three groups of service-role behaviours influence the customer service
satisfaction and value perception constructs.
The researcher operationalised a construct by selecting and adapting measurement scale items
and scale types from prior research. The scale items of the constructs have been adapted from
different past literature with minor modifications, where appropriate, to complement this
research. As all the constructs of this thesis came from the outcomes of qualitative analysis in
Chapter 4, the scale items of the previous studies might not precisely come from the identical
dimensions. However, the researcher chose the scales which were the most appropriate and
applicable to the new research context. The modifications ensured that most of the items still
maintained their original meaning, but were adapted with appropriate wording and linguistic
style of expression to reflect the situation of service encounter between FSEs and customers
and from the customer’s perspective. The scale items were adapted for two different contexts
of sample groups: a university student for a pre-test, then customers for the main study.
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The summary details of measurement and sources of scales from previous studies are presented
in Appendix C. This thesis adapted the selected scales from the literature that previously
performed well on reliability measures (i.e. Cronbach’s alpha ranging from 0.70 to 0.93) and
on validity measures (i.e. factor loading ranging from 0.63 to 0.97), exceeding the
recommended minimum values of 0.60 and 0.50 respectively (Hair et al., 2010). These
measurement scale items are presented in Table 6-1 to Table 6-9.
Table 6-1: Measuring Customer Perceptions towards FSEs’ Expertise during Service Encounter
Item
codes Source Dimension
Item Description from
Previous Studies
(Cronbach’s Alpha/
Standardized Loadings)
Item Description of this
Study
EX1
Dabholkar
et al.
(1996)
Assurance (Personal
Interaction/Inspiring
confidence)
Employees in this store
have the knowledge to
answer customers’
questions. (0.90)
The service employee had
the knowledge about
product/service to answer
my questions.
EX2
Liao and
Chuang
(2004)
Service Training
Providing an accurate
guest check. [all the items
of Liao and Chung had
high “loadings” (average
loading .85) on the single
factor]
The service employee
provided accurate
information during the
service encounter.
EX3
Providing quick and
prompt service. [all the
items of Liao and Chung
had high “loadings”
(average loading .85) on
the single factor]
During the service
encounter, the service
employee provided quick
and prompt service.
EX4*
Stock and
Hoyer
(2005)
Salespeople's
Expertise (customer
survey)
This salesperson is very
well organized. (.87)
The service employee was
very well organised during
the service encounter.
EX5
This salesperson knows
his or her company's
product and/or service
range very well. (.89)
The service employee
knew a lot about
services/products.
* Item was removed after pre-testing analysis.
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Table 6-2: Measuring Customer Perceptions of FSEs Undertaking Job Requirement
Item
codes Source Dimension
Item Description from
Previous Studies
(Cronbach’s Alpha)
Item Description of this
Study
JR1
Netemeyer
and
Maxham III
(2007)
Customer In-Role
Performance-
Employee Rated
Themselves
I met formal performance
requirements when serving
customers. (.83)
The service employee
completed his/her required
service tasks.
JR2
I performed all those tasks
for customers that were
required of me. (.83)
The service employee
performed all the tasks that
were required by me.
JR3
I adequately completed all
expected customer service
behaviours. (.83)
The service employee
completed all expected
customer-service tasks.
JR4 Tsaur and
Lin (2004)
Role-Prescribed
Service Behaviour
I help customers with those
things which are required
of him/her. (Cronbach’s
Alpha of all items ranged
form 0.82-0.93)
The service employee
completed all those things
which were required by
me.
Table 6-3: Measuring Customer Perceptions of FSEs Considerate Manner to Customers during Service
Encounter
Item
codes Source Dimension
Item Description from
Previous Studies
(Cronbach’s Alpha)
Item Description of this
Study
CC1
Rego and
Cunha (2008)
Courtesy toward
Customers
They treat customers with
respect. (≥.70)
The service employee
treated me with respect.
CC2 They are kind and polite
with every customer. (≥.70)
The service employee was
kind and polite to me.
CC3
They speak courteously
and earnestly with every
customer (i.e. regardless of
their social status and/or
socio-economic
background). (≥.70)
The service employee was
courteous and sincere to
me.
CC4
Tsaur and
Lin (2004);
Parasuraman
et al. (1988)
Assurance
The employees have good
manners and kind attitude.
(Cronbach’s Alpha of all
items ranged form 0.82-
0.93)
The service employee had
good manners and a kind
attitude.
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Table 6-4: Measuring Customer Perceptions of FSEs’ have Personal-Involvement Expression during
Service Encounter
Item
codes Source Dimension
Item Description from
Previous Studies
(Cronbach’s Alpha/
Standardised Loadings)
Item Description of this
Study
PE1 Ackfeldt and
Wong (2006) Job Satisfaction
I am happy that I took this
job. [All of the factor
loadings exceed .50 and are
significant (p < .01)]
The service employee
looked happy during the
interaction.
PE2*
Bettencourt,
Gwinner, and
Meuter
(2001)
Service
Orientation
It is natural for me to be
considerate of others’
needs. (All items of this
construct are .77, .88)
It looked natural for the
service employee to be
considerate of my needs.
PE3*
I enjoy helping others. (.77,
.88) The best job I can
imagine would involve
assisting others in solving
their problems. (All items
of this construct.77, .88)
During the service
encounter, the service
employee seemed to enjoy
doing his/her job.
PE4
I pride myself in providing
courteous service. (All
items of this construct.77,
.88)
During the interaction, the
service employee took
pride in providing
courteous service.
PE5
Dimitriades
(2007) Job Involvement
I am very much personally
involved in my job. (Range
from 0.68 to 0.86)
The service employee was
personally involved in
his/her job.
PE6
The major satisfaction in
my life comes from my job.
(Range from 0.68 to 0.86)
The service employee
looked satisfied in his/her
job. * Items were removed after pre-testing analysis.
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Table 6-5: Measuring Customer Perceptions of FSEs’ Empathy during Service Encounter
Item
codes Source Dimension
Item Description from
Previous Studies
(Cronbach’s Alpha)
Item Description of this
Study
EM1*
Stock and
Hoyer
(2005)
Salespeople’s
Empathy
(customer survey)
This salesperson has a high
level of empathy with
respect to our needs as
customers. (.93)
The service employee had
a high level of empathy
with respect to my needs.
EM2*
It is not difficult for this
salesperson to find out our
needs. (.91)
During the service
encounter, the service
employee found out my
needs easily.
EM3*
This salesperson tries to
find out our needs by
adopting our perspective.
(.92)
During the service
encounter, the service
employee tried to find out
my needs by adopting my
point of view.
EM4*
This salesperson is able to
adapt his or her interaction
to our needs in different
situations. (.93)
During the service
encounter, the service
employee was able to adapt
the interaction to my needs.
EM5* Tsaur and
Lin (2004) Empathy
The employees consider the
individual needs of the
customers and offer them
personalised service.
(Cronbach’s Alpha of all
items ranged form 0.82-
0.93)
During the service
encounter, the service
employee considered my
needs and offered me
personalised service.
* Construct and items were removed after pre-testing.
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Table 6-6: Measuring Customer Perceptions of FSEs’ Having a Rapport with Customers during
Service Encounter
Item
codes Source Dimension
Item Description from
Previous Studies
(Standardised Loadings)
Item Description of this
Study
RA1
Gremler
and
Gwinner
(2000)
Enjoyable
Interaction
In thinking about my
relationship with this
person, I enjoy interacting
with this employee.
(.927/.942)
I enjoyed interacting with
the service employee.
RA2*
This employee creates a
feeling of “warmth” in our
relationship. (.913/.910)
The service employee
created a feeling of
“warmth” during the
service encounter.
RA3 This employee relates well
to me. (.908/.926)
The service employee
related well with me.
RA4
I am comfortable
interacting with this
employee. (.773/.729)
I was comfortable
interacting with the service
employee.
RA5*
Personal
Connection
I feel like there is a “bond”
between this employee and
myself. (.887/.882)
I feel like there is a “bond”
between the service
employee and myself.
RA6 I have a close relationship
with this person (.789/.875)
I have a close relationship
with the service employee.
RA7*
This person has taken a
personal interest in me.
(.851/.808)
The service employee has
taken a personal interest in
me. * Items were removed after pre-testing analysis.
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Table 6-7: Measuring Customer Perceptions of FSEs’ Helping-Role Behaviour without Concern for the
Duty Boundary during Service Encounter
Item
codes Source Dimension
Item Description from
Previous Studies
(Cronbach’s Alpha/
Standardised Loadings)
Item Description of this
Study
WC1 Axtell,
Parker,
Holman,
and
Totterdell
(2007)
Helping
Behaviour
towards
Customers
Help customers with a
problem or enquiry even
when it is personally
inconvenient. (All factor
loadings were above .70)
The service employee
helped me solve my
problem/request even when
it was personally
inconvenient.
WC2
Go beyond what is
normally expected in order
to help customers. (All
factor loadings were above
.70)
The service employee went
above what was normally
expected in order to help
me.
WC3
Rego and
Cunha
(2008)
Helping
Behaviours
toward Customers
They help customers, even
when this is not part of
their jobs. (.74)
The service employee
helped me even when it
was not part of his/her jobs.
WC4 Tsaur and
Lin (2004)
Extra-Role
Behaviour
I voluntarily assist
customers even if it means
going beyond job
requirements. (Cronbach’s
Alpha of all items ranged
form 0.82-0.93)
The service employee
voluntarily assisted me
even if it was going above
his/her required tasks.
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Table 6-8: Measuring Customer Service Satisfaction
Item
codes Source Dimension
Item Description from
Previous Studies
(Standardised Loadings)
Item Description of this
Study
SS1
Dagger,
Sweeney,
and
Johnson
(2007)
Service
Satisfaction
My feelings towards the
clinic very positive. (CFA
loadings .91 - .97)
My feelings towards the
service employee were
very positive.
SS2
I feel good about coming to
this clinic for my treatment.
(CFA loadings .91 - .97)
I feel good about the
service of this place.
SS3
Overall I am satisfied with
the clinic and the service it
provides. (CFA loadings
.91 - .97)
Overall I am satisfied with
the service s/he provided.
SS4
I feel satisfied that the
results for my treatment are
the best that can be
achieved. (CFA loadings.91
- .97)
I feel satisfied that my
needs were achieved.
SS5*
Leisen
Pollack
(2009)
Overall Service
Quality
I would say they provide
superior service. (All factor
loadings ranged from .70 -
.90)
I would say the service
employee provided
superior service.
SS6*
I believe they offer
excellent service. (All
factor loadings ranged from
.70 - .90)
I believe the service
employee offered excellent
service.
* Items were removed after pre-testing analysis.
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Table 6-9: Measuring Customer Value Perception
Item
codes Source Dimension
Item Description from
Previous Studies
(Cronbach’s Alpha/
Standardised Loadings)
Item Description of this
Study
VP1*
Gil et al.
(2008) Service Value
The service provider is
reliable. (.814)
The service employee was
reliable.
VP2* The service provider is
professional. (.812)
The service employee was
professional.
VP3 The service provider shows
interest. (.823)
Compared to other financial
institutes, the service
employee has shown
interest in my
enquiries/problems.
VP4* The service provider
responds quickly. (.785)
The service employee
responded quickly.
VP5* I trust the service provider.
(.835) I trust the service employee.
VP6 The service provider solves
problems for me. (.633)
Compared to other financial
institutes, the service
employee solved my
problems.
VP7
Keith, Lee,
and Leem
(2004)
Perceived Service
Value
Using this service provider
gives me the best value I
can get. (.935)
Compared to other financial
institutes, the service
employee gave me the best
value I could get.
VP8
This service provider
delivers good quality for
what I give up in order to
get this service. (.935)
Compared to other financial
institutes, the service
employee delivered good
quality for what I gave up in
order to get this service.
VP9*
I get the most for my
money by using this service
provider. (.935)
Consider what I gave up to
receive the service (e.g.
effort, time, money); I got a
lot in return.
VP10 I get a good value by using
this service provider. (.935)
Compared to other financial
institutes, I received a good
value by using this service
provider. * Items were removed after pre-testing analysis.
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6.7.1 FSEs’ Expertise
The objective indication of expertise was adopted to capture the customers’ perceptions of
FSEs’ professionalism or skilfulness. This role-prescribed behaviour refers to the knowledge
of the product/service, professional information provision, and/or quick and prompt service
delivery of FSEs during the encounter. Van Dolen et al. (2004) state that the expertise of the
FSEs is the resource of the employees during the encounter. Customers who are not experts in
product/service expect the employees to give them advice and information. Items for this scale
have been adapted from the works of Dabholkar et al. (1996), Liao and Chuang (2004), and
Stock and Hoyer (2005). The questionnaire items of measurement of expertise are presented in
Table 6-10.
Table 6-10: Measuring Expertise
Item Codes
in the
Measurement
Model
Item Description Modified for this Thesis Original Sources
EX1 The service employee had the knowledge about
product/service to answer my questions. Dabholkar et al. (1996)
EX2 The service employee provided accurate information
during the service encounter. Liao and Chuang (2004)
EX3 During the service encounter, the service employee
provided quick and prompt service.
EX4* The service employee was very well organised during the
service encounter. Stock and Hoyer (2005)
EX5 The service employee knew a lot about services/products. * Item was removed after pre-testing.
6.7.2 FSEs’ Job Requirement
In this thesis, the job requirement dimension refers to a role-prescribed behaviour of FSEs that
follows the formalised job descriptions, guidelines, core tasks, and scripts used as standard
service procedures when dealing with customers (Raub & Liao, 2012). The objective of job
requirement indicators is to capture the customers’ perceptions of how the FSEs perform and
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complete the general service tasks which are expected and required from them during the
encounter. Questionnaire items have been taken from the works of Netemeyer and Maxham III
(2007) and Tsaur and Lin (2004). Table 6-11 presents the measure items and their sources.
Table 6-11: Measuring Job Requirement
Item Codes
in the
Measurement
Model
Item Description Modified for this Thesis Original Sources
JR1 The service employee completed his/her required service
tasks.
Netemeyer and Maxham
III (2007) JR2
The service employee performed all the tasks that were
required by me.
JR3 The service employee completed all expected customer-
service tasks.
JR4 The service employee completed all those things which
were required by me. Tsaur and Lin (2004)
6.7.3 FSEs’ Considerate Manner
In this thesis, considerate manner denotes a beyond role behaviour of FSEs during the service
encounter with customers. For this dimension, FSEs present their behaviour in an attentive,
thoughtful, courteous, polite, patient, kind, sincere, and/or respectful manner. Having these
kinds of considerate manners can create a positive climate between employees and customers
and may aid in achieving customer satisfaction. The objective of the considerate manner
indicators is to apprehend the customers’ perceptions, whether and how they can differentiate
this dimension from those of role-prescribed behaviours. The items have been taken from the
Rego and Cunha (2008) and Tsaur and Lin (2004) studies. The questionnaire items are shown
in Table 6-12.
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Table 6-12: Measuring Considerate Manner
Item Codes
in the
Measurement
Model
Item Description Modified for this Thesis Original Sources
CC1 The service employee treated me with respect.
Rego and Cunha (2008) CC2 The service employee was kind and polite to me.
CC3 The service employee was courteous and sincere to me.
CC4 The service employee had good manners and a kind
attitude.
Tsaur and Lin (2004);
Parasuraman et al.
(1988)
6.7.4 FSEs’ Personal-Involvement Expression
This dimension focuses on the customers’ perceptions of personal-involvement expression. In
this thesis, personal-involvement expression refers to a beyond role behaviour of FSEs
presenting how much they engage in and/or are involved in their service roles. A FSE may
express a strong relationship with their job and role. Also, they may seem to have a positive
mood, enjoy what they are doing, and/or engage themselves more in service delivery and
participation behaviour with customers. Items have been taken from the studies conducted by
Ackfeldt and Wong (2006), Bettencourt et al. (2001), and Dimitriades (2007). Table 6-13
below presents the items used in operationalising the variable.
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Table 6-13: Measuring Personal-Involvement
Item Codes
in the
Measurement
Model
Item Description Modified for this Thesis Original Sources
PE1 The service employee looked happy during the encounter. Ackfeldt and Wong
(2006)
PE2* It looked natural for the service employee to be considerate
of my needs.
Bettencourt et al. (2001) PE3* During the service encounter, the service employee
seemed to enjoy doing his/her job.
PE4 During the encounter, the service employee took pride in
providing courteous service.
PE5 The service employee was personally involved in his/her
job. Dimitriades (2007)
PE6 The service employee looked satisfied in his/her job. * Items were removed after pre-testing.
6.7.5 FSEs’ Empathy
In this research, empathy denotes the ability to understand and anticipate the expectations and
needs of customers during the service encounter. These indicators aimed to capture the
customers’ perceptions of this beyond role behaviour. Wieseke et al. (2012) support that
empathic employees may reinforce and obtain reciprocal attitudes and behaviours between
themselves and customers. As a result, customers may gain more appropriate service delivery
behaviours (Bettencourt et al., 2001). Questionnaire items have been taken from Stock and
Hoyer (2005) and Tsaur and Lin (2004). The items operationalising FSE empathy are shown
in Table 6-14.
After conducting the Confirmatory Factor Analysis (CFA) with all constructs, the results
indicated that all sets of indicators of constructs are highly reliable. All construct reliability
scores exceed the threshold of ≥ 0.7 (De Vaus, 2002). All average variance extracted (AVE)
values exceeded the threshold of ≥ 0.05 suggesting adequate convergent validity (Hair et al.,
2010). Discriminant validity was examined comparing the values between AVE and the highest
squared correlation estimates of constructs (Hair et al., 2010). However, the results showed
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that all constructs but the empathy had AVE scores that exceeded those of the highest squared
correlation estimate. The AVE value at 0.67 of empathy did not exceed the highest squared
correlation estimate at 0.90. Therefore, empathy construct was removed from the questionnaire.
As empathy construct has been removed from the analysis, thus the hypothesis H5a (empathy
positively affects service satisfaction) and H5b (empathy positively affects value perception)
were no longer examined.
Table 6-14: Measuring Empathy
Item Codes
in the
Measurement
Model
Item Description Modified for this Thesis Original Sources
EM1* The service employee had a high level of empathy with
respect to my needs.
Stock and Hoyer (2005)
EM2* During the service encounter, the service employee found
out my needs easily.
EM3* During the service encounter, the service employee tried to
find out my needs by adopting my point of view.
EM4* During the service encounter, the service employee was
able to adapt the interaction to my needs.
EM5* During the service encounter, the service employee
considered my needs and offered me personalised service. Tsaur and Lin (2004)
* Construct and items were removed after pre-testing.
6.7.6 FSEs’ Rapport
The construct rapport has two important facets, an enjoyable interaction and personal
connection (Gremler & Gwinner, 2000). In this thesis, rapport is considered as a beyond role
behaviour. The Rapport indicators intend to measure the customers’ perceptions of both
dimensions. This thesis denotes enjoyable interaction as the feeling of care, friendliness, and
pleasure that customers get while interacting with the FSEs, while personal connection is
regarded as a bond or strong affiliation between the two parties. All the scale items have been
taken from the work of Gremler and Gwinner (2000). Scale items of rapport are shown in Table
6-15.
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Table 6-15: Measuring Rapport
Item Codes
in the
Measurement
Model
Item Description Modified for this Thesis Original Sources
RA1 I enjoyed interacting with the service employee.
Gremler and Gwinner
(2000)
RA2* The service employee created a feeling of “warmth”
during the service encounter.
RA3 The service employee related well with me.
RA4 I was comfortable interacting with the service employee.
RA5* I feel like there is a “bond” between the service employee
and myself.
RA6 I have a close relationship with the service employee.
RA7* The service employee has taken a personal interest in me. * Items were removed after pre-testing.
6.7.7 FSEs’ Helping without concern for the Duty Boundary
Helping without concern for the duty boundary represents the discretionary or voluntary acts
of FSEs in serving customers that go above formal role requirements. In this research, the
indicators capture the customers’ perceptions of FSEs’ helping performance that exceed their
expectations during the service encounter. The FSEs enact this behaviour without concern to
their duty boundaries. This helping behaviour is not formally rewarded. If the FSEs do not
perform, they are not punished by the firm. Items of this scale have been adapted from the
works of Axtell et al. (2007), Rego and Cunha (2008), and Tsaur and Lin (2004). The items
employed in operationalising the variable shows below.
Table 6-16: Measuring Helping without Concern for the Duty Boundary
Item Codes
in the
Measurement
Model
Item Description Modified for this Thesis Original Sources
WC1
The service employee helped me solve my
problem/request even when it was personally
inconvenient. Axtell et al. (2007)
WC2 The service employee went above what was normally
expected in order to help me.
WC3 The service employee helped me even when it was not part
of his/her jobs. Rego and Cunha (2008)
WC4 The service employee voluntarily assisted me even if it
was going above his/her required tasks. Tsaur and Lin (2004)
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6.7.8 Customer Service Satisfactions
In this thesis, customer service satisfaction, one of the dependent variables in this study, is “the
customers’ fulfilment response” (Oliver, 2015: p. 8) which is an evaluation as well as an
emotional-based reaction to a service and/or product relative to their expectations of
performance. This dimension focuses on customers’ perception and a pleasurable level of
service experience, including under- or over-fulfilment (Leisen Pollack, 2009), with the FESs.
Questionnaire items have been taken form the works of Dagger et al. (2007) and Leisen Pollack
(2009). The questionnaire items are presented in Table 6-17.
Table 6-17: Measuring Service Satisfaction
Item Codes
in the
Measurement
Model
Item Description Modified for this Thesis Original Sources
SS1 My feelings towards the service employee were very
positive.
Dagger et al. (2007) SS2 I feel good about the service of this place.
SS3 Overall, I am satisfied with the service s/he provided.
SS4 I feel satisfied that my needs were achieved.
SS5* I would say the service employee provided superior
service. Leisen Pollack (2009)
SS6* I believe the service employee offered excellent service. *Items were removed after pre-testing.
6.7.9 Customer Value Perception
Customer Value perception is the other dependent variable in this thesis. The Value perception
dimension for this thesis denotes the customers’ assessment of what they received (e.g. service
quality, other conveniences and/or benefits) compared to what they sacrificed (e.g. time, effort,
outlay, other monetary and nonmonetary costs) during the service encounter with FSEs. Tam
(2004) states that value is a trade-off between perceived benefits and costs. The items have
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been taken from the Gil et al. (2008) and Keith et al. (2004) studies. Scale items are summarised
in Table 6-18.
Table 6-18: Measuring Value Perception
Item Codes
in the
Measurement
Model
Item Description Modified for this Thesis Original Sources
VP1* The service employee was reliable.
Gil et al. (2008)
VP2* The service employee was professional.
VP3 Compared to other financial institutes, the service
employee has shown interest in my enquiries/problems.
VP4* The service employee responded quickly.
VP5* I trust the service employee.
VP6 Compared to other financial institutes, the service
employee solved my problems.
VP7 Compared to other financial institutes, the service
employee gave me the best value I could get.
Keith et al. (2004)
VP8
Compared to other financial institutes, the service
employee delivered good quality for what I gave up in
order to get this service.
VP9* Consider what I gave up to receive the service (e.g. effort,
time, money); I got a lot in return.
VP10 Compared to other financial institutes, I received a good
value by using this service provider. * Items were removed after pre-testing.
6.8 Ethics and Information Confidentiality
This research was granted ethics approval by the University of Adelaide Human Research
Ethics Committee. As human subjects were involved, information was provided for
respondents in the introduction of the questionnaire. The information included the statement of
consent to participate in the survey where respondents were told they could withdraw from the
project at any time. Also, expressed in the introduction were a brief description of the nature
and the purpose of study, the researcher’s identity, contact details of the Human Research
Ethics Committee to register any complaint, and the assurance of confidentiality. All responses
and submissions made by respondents were kept confidential by the researcher. Respondents’
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identities, personal and financial information have not been collected. The organisation’s
identity also remains undisclosed. The anonymity of all parties was a principal issue that was
guaranteed.
6.9 Data Entry
The structure of the questionnaire and the number of responses per question has been
appropriately assigned in the Qualtrics online survey software. All data from the questionnaires
was directly imported from Qualtrics into a SPSS file. Although numerals of questions and
responses were automatically coded, these numbers were later modified for easier readability
and analysis in SPSS23. Two thorough reviews of data entry were conducted to eliminate errors
and ensure accuracy.
6.10 Data Analysis Plan
The description of sample respondents is provided in the next chapter. All of the necessary
tests to check data cleaning and an assumption of outliers and normality, including
homoscedasticity and multicollinearity, have been performed to facilitate data analysis. Factor
analysis was tested to discard several scale items which had low factor loadings. The set of
scale items were revised, reduced, and developed before post-testing. The revised set was
employed for conducting CFA by Structural Equation Modelling (SEM) using AMOS 23
software.
SEM is a statistical modelling technique which can specify the theoretical relationships among
observed and latent variables and represent them by regression coefficients between the factors
(Teo et al., 2013). SEM can be viewed as a combination of two multivariate techniques; factor
analysis and multiple regression or path analysis (Hair et al., 2010). In Chapter 7 and 8, the
measurement model validity was examined by verifying an acceptable level of goodness-of-fit
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indices such as chi-square, degree of freedom, normed chi-square, Goodness-of-Fit Index
(GFI), Normed fit index (NFI), Tucker-Lewis Index (TLI), Comparative Fit Index (CFI), and
the Root Mean Square Error of Approximation (RMSEA). The convergent validity and
discriminant validity measurement are presented in the next two chapters. Finally, the
interpretations of SEM analysis are provided in Chapter 8.
6.11 Chapter Summary
This chapter provided a comprehensive description of the quantitative methodology employed
in this research. The unit of analysis was the individual person who had interaction with
frontline service employee (FSEs). The research design was employed to collect the data from
both pre-test and post-test studies.
A pre-test study included university students, both undergraduate and postgraduate who studied
in Adelaide, South Australia. The purpose of conducting a pre-test study was to conduct
preliminary factor analysis of the observed variables and the constructs’ reliability and validity.
Item with low unstandardized factor loadings were excluded from the measured scales before
the commencement of the post-test or main study.
The main study was conducted in a single branch of a financial-service firm in Adelaide, South
Australia. The main target population included any customers who received service and had an
interaction with the FSEs. The online survey acted as the primary method for data collection,
with 250 useable surveys resulting from customer respondents.
The individual constructs employed in this thesis were described in the operational definition
section. The main constructs of this survey are classified into three groups; role-prescribed,
beyond role, and helping behaviours. The dimensions of these three groups influence the
customer service satisfaction and value perception constructs. At the end of this chapter the
ethics and information confidentiality, data entry, and data analysis plan were outlined
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The next chapter describe the description of sample groups, data entry, and screening. Then
the results of the measurement model validity and confirmatory factor analysis are presented.
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CHAPTER 7
DATA ANALYSIS
This chapter provides the description of sample groups with a detailed breakdown of their
gender and frequency of visiting the financial service firm in the past month. The data entry
and screening procedures and the assessments of outliers and the assumptions of normality are
described next. Then, the discussions on Confirmatory Factor Analysis (CFA) as well as the
reliability and validity of the measures are presented.
7.1 Description of Sample Groups
In total 250 usable customer service interactions were obtained with an individual customer
survey and a short FSE survey. All customer respondents were over 18 years of age. The
majority of respondents were women (61.2% female and 38.8% male). An independent-sample
T-test was conducted to compare, for males and females, the frequency of visiting the financial
service firm in the past month. There was no a statistically significant difference in the mean
scores for males, M = 1.82, SD = 1.118 and females, M = 1.70, SD = .932; t = .958, df = 248,
p = .339 (two-tailed). The magnitude of the differences in the means was very small (means
difference = .125, 95% CI: -.132 to .383, Eta squared = .0037). Eta squared indicated that only
0.37 per cent of the variance in frequency of visiting the firm was explained by gender. Also,
the significance level of Levene’s test is p = .700. These tests mean that the variances for the
two groups, males/females, are the same and that the sample should not be treated as two groups
(see Appendix D).
In terms of the frequency of visiting the firm within the past month, most of the respondents
(50%) visited 1-2 times, 34.8% visited 3-5 times, and 22.4% visited 6 times and over (see
Appendix D). As the researcher observed the respondents at the firm during the survey/data
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collection, the reasons for visiting the firm were observed to depend on personal and businesses
requirement: for general transactions; such as exchanging foreign money, withdrawing or
depositing cash, depositing a cheque; and for personalised services such as opening a firm
account, investing money, or completing a car/home loan.
The frequency of visiting the firm was investigated to see if customer perceptions on the service
roles of FSEs were influenced. The results revealed that there was no statically significant
difference between groups towards customer service satisfaction as determined by one-way
ANOVA [F(5,244)] = .469, p = .799]. An analysis of variance on customer value perception
also showed the frequency of visiting the firm within the past month was not significant,
[F(5,244)] = 1.014, p = .410]. Thus, the sample should not be treated as separate groups
according to frequency of visiting the firm (see more results in Appendix D).
7.2 Data Entry and Screening
All data from the questionnaires was directly imported from the web-based survey software
(Qualtrics.com) into a SPSS file. The data entry was carefully checked twice to ensure
accuracy. Next, data files were screened. A careful examination of the raw research data
identified 3 incomplete questionnaires. These cases were removed from further analysis
(Pallant, 2007; Schumacker & Lomax, 2004). Therefore, there were a total of 250 completed
cases.
The data file was screened to ensure suitability for Structural Equation Modelling (Kline,
2005). The data was checked for outliers as West, Finch, and Curran (1995) note that these
may impact the results of the structural equation modelling, even when the remainder of the
data is well distributed. Outliers are cases with a unique combination of values or
characteristics distinguishable as markedly different from the majority of other observations
(Hair et al., 2010; Pallant, 2007). The method used was Tukey’s graphical device in SPSS; the
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‘Box-and-Whisker Plot’ or ‘Box-plot’ (Schinka & Velicer, 2003). Box-plot defined the
extreme outliers if they extend more than 3 Interquartile Range (IQR) from the edge of the box
or the hinges (Pallant, 2007; Schinka & Velicer, 2003). A total of 29 outliers were identified,
this being 12.4% of the total sample. These 29 cases were the extreme-point outliers, indicated
with an asterisk *, and were those that extended more than 3 IQR’s or three box-lengths from
the edge of the box (Pallant, 2007).
Pallant (2007) suggests a further test of outliers is to examine the Descriptives Table (see
Appendix E Normality and Appendix F Outliers) and compare the mean values with the 5%
Trimmed Mean. The trimmed mean and mean values of all outliers were not too different from
the remaining distribution, and so the researcher decided to retain these 29-cases in the data
file. In addition, Hair et al. (2010) supported that if the outliers are deleted, the researcher may
take the risk of improving the multivariate analysis, yet limiting its generalisability.
7.3 Normality
Next, the data was examined for normality, which is an essential assumption in multivariate
analysis (Hair et al., 2010; Tabachnick & Fidell, 2007). Presented in Table 7-1 are the mean
statistic, standard deviation, and standard error for both the skewness and kurtosis values of the
data, with an asterisk noting the variables where non-normality is an issue. For more details of
normality/non-normality results see Appendix E.
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Table 7-1: Descriptive Statistics of Normality (99% Confidence Interval)
Item Codes Mean
Std.
Deviation Skewness Kurtosis
Statistic Statistic Statistic Std. Error Statistic Std. Error
EX1 9.83 1.730 -1.409 .154 .556 .307
EX2 9.92 1.632 -1.591 .154 1.254 .307
EX3 10.44 .900 -2.210 .154 7.187* .307
EX5 9.68 1.837 -1.197 .154 -.118 .307
JR1 10.50 .777 -1.602 .154 2.049 .307
JR2 10.49 .856 -2.492 .154 9.397* .307
JR3 10.40 .969 -2.039 .154 4.826* .307
JR4 10.44 .935 -2.589* .154 9.308* .307
CC1 10.54 .750 -2.008 .154 4.797* .307
CC2 10.55 .760 -2.142 .154 5.578* .307
CC3 10.53 .745 -1.696 .154 2.875* .307
CC4 10.54 .728 -1.947 .154 4.776* .307
PE1 10.50 .777 -1.771 .154 3.438* .307
PE4 10.46 .953 -2.457 .154 7.003* .307
PE5 10.36 1.041 -2.037 .154 4.306* .307
PE6 10.36 .990 -1.985 .154 4.490* .307
RA1 10.41 .945 -2.107 .154 5.173* .307
RA3 10.39 .980 -2.106 .154 5.137* .307
RA4 10.31 1.115 -1.989 .154 4.127* .307
RA6 10.12 1.461 -2.399 .154 7.430* .307
WC1 8.26 2.300 .074 .154 -1.790 .307
WC2 8.82 2.228 -.475 .154 -1.173 .307
WC3 8.22 2.307 .119 .154 -1.787 .307
WC4 8.65 2.322 -.314 .154 -1.432 .307
SS1 10.52 .817 -2.066 .154 4.789* .307
SS2 10.54 .919 -3.584* .154 20.262 .307
SS3 10.57 .737 -2.025 .154 4.808* .307
SS4 10.54 .787 -2.029 .154 4.646* .307
VP3 9.88 1.702 -1.505 .154 .849 .307
VP6 9.67 1.879 -1.198 .154 -.169 .307
VP7 9.88 1.723 -1.583 .154 1.398 .307
VP8 9.71 1.854 -1.236 .154 -.064 .307
VP10 10.31 1.491 -2.176 .154 4.337* .307 * Non-normal distributions
According to Hair et al. (2010), the severity of non-normality is based on two aspects: the
shape of the distribution and the sample size. According to Hair et al. (2010), unbalanced
skewness or high (or flat) kurtosis indicate non-normality. Normality is assured if the value of
skewness as well as kurtosis is between +2.58 and – 2.58 (Hair et al., 2010). For sample sizes
of 200 observations or more, the problem of departures from normality impacting on the results
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may be negligible (Hair et al., 2010). Since this research has an acceptable sample size of 250,
the assumption of normal distribution was accepted.
Assuming normal distribution was also considered reasonable as the data analysis applied the
Maximum Likelihood algorithm for factor analysis and a correlation matrix in structural
equation modelling. According to Babakus, Ferguson Jr, and Jöreskog (1987), when using
correlation measures as input to Maximum Likelihood factor analysis to estimate model
parameters, non-normally distributed indicators did not strongly affect the model betas.
Therefore, an assumption of normal distribution of the data was accepted, so that structural
equation modelling could proceed. In addition, Kaplan (1990) proposed that data related
problems, including non-normality contributing to model misfit, can be improved through
methods of model modification. The modification indices (MI) of the AMOS (Byrne, 2013)
were used in the analysis to specify and respecify the error covariance parameter, to test the
model, and to improve the fit during the modification process.
A check for homoscedasticity with scatterplots (Hair et al 2010), revealed the data was
acceptable for continuing the analysis (see Appendix G). Next multicollinearity was
determined by assessing the tolerance (1 - R2smc) (Kline, 2005). Appendix H presents the tests.
Only the variable CC3 displayed an issue with multicollinearity. This was resolved during the
AMOS analysis in Chapter 8. Scatterplots (Hair et al., 2010) revealed the data was acceptable
for continuing the analysis (see Appendix G). Scatterplots showed the normal distributions
which exhibited acceptably equal dispersion across all data values (Hair et al., 2010).
7.4 Structural Equation Modelling Process
A structural equation modelling process involves two steps: (i) preparing the measurement
model, and (ii) structural model tests (Bollen, 1989; Hair et al., 2010). First, the measurement
model test uses confirmatory factor analysis (CFA) to specify the indicator variables of each
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construct based on a covariance matrix (Hair et al., 2010). The measurement model assesses
the construct validity (Hair et al., 2010). The measurement model needs to represent how the
measured variables come together and have met the required measurement standards to
represent the latent constructs (Hair et al., 2010). Second, the structural model test is
undertaken and the hypothesised associations are assessed (Hair et al., 2010). An issue in
testing the model is multiple dependence among independent and dependent variables (Hair et
al., 2010). The second step, the structural model analysis, is presented in Chapter 8.
7.5 Measurement Model Validity Test: Confirmatory Factor Analysis
Confirmatory factor analysis (CFA) using AMOS 23 and the Maximum Likelihood Estimation
(MLE) algorithm was conducted to estimate factor loadings for the population that maximised
the likelihood of sampling the observed correlation matrix (Tabachnick & Fidell, 2007). Before
assessing the validity and reliability, unidimensionality of each construct is clarified.
7.5.1 Unidimensionality
Unidimensionality means a set of indicators measures only one construct (Hair et al., 2010).
Unidimensionality confirms that there are no covariances between error terms and cross-
loadings while running CFA models.
7.5.2 Construct validity
An assessment of construct validity was conducted to reveal whether measured variables
accurately reflect the theoretical construct. Convergent validity and discriminant validity are
two subtypes of validity to measure construct validity (Hair et al., 2010).
7.5.2.1 Convergent Validity
To evaluate convergent validity, the indicators of a specific construct were measured to see
whether they share a high proportion of variance in common (Hair et al., 2010). To ensure that
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the measurement model is convergent, one-factor congeneric measurement models and their
fit indices of each factor were computed by CFA (see Figure 7-1 to 7-8).
Goodness-of-fit (GOF) in the SEM is used for indicating how well the model reproduces the
observed covariance matrix among the measured variables (Hair et al., 2010). The measures of
GOF are classified into three groups; absolute measures, incremental measures, and parsimony
fit measures. There are multiple fit indices underlying the GOF measures, however, the rules
of thumb direct the basic elements that should be included in the model fit assessment. Multiple
fit indices include: the χ2 value and the associated df; one absolute fit index (i.e. GFI, RMSEA,
or SRMR); one incremental fit index (i.e. NFI, TLI, or CFI); one goodness-of-fit index (GFI,
CFI, TLI), and one badness-of-fit index (RMSEA or SRMR) (Hair et al., 2010).
Chi-Square (χ2) value is the fundamental statistic measure for assessing overall model fit
(Hooper, Coughlan, & Mullen, 2008) and evaluates ‘the magnitude of discrepancy between the
sample and fitted covariance matrices’ (Hu & Bentler, 1999: p. 2). The use of the Chi-Square
has several limitations. First, multivariate normality and serious deviations from normality may
cause model rejections (Hooper et al., 2008). Second, the Chi-Square is sensitive to sample
size. The Chi-Square usually rejects the model when there are large samples (Bentler & Bonett,
1980) and lacks power when there are small samples (Kenny & McCoach, 2003). These may
cause the lack of the discrimination between good fitting and poor fitting models (Hooper et
al., 2008). Moreover, the complex model with a large number of observed variables will cause
the χ2 values to increase and lose the power to achieve model fit (Hair et al., 2010). The Normed
Chi-Square is a ratio of χ2 to the degrees of freedom for a model, and generally is 3:1 (Hair et
al., 2010). The goodness-of-fit index (GFI) was created as an option to the Chi-Square test
(Hooper et al., 2008). GFI calculates the proportion of the observed variances and covariances
accounted for the model (Teo et al., 2013).
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Normed fit index (NFI) is the incremental fit index which evaluates the Chi-Square value of
the fitted model and a null model divided by the χ2 of the null model (Hair et al., 2010). The
Tucker-Lewis Index (TLI) compares the normed Chi-Square values for the a proposed model
and the null model (Hair et al., 2010; Schumacker & Lomax, 2004; Teo et al., 2013).
Comparative Fit Index (CFI) indicates “the relative lack of fit of a specified model versus the
baseline model (Teo, Tsai, & Yang, 2013: p. 15).”
The Root Mean Square Error of Approximation (RMSEA) is a badness-to-fit index which
attempts to correct for the tendency of the Chi-Square to reject models with large sample size
or a great number of variables (Hair et al., 2010; Teo et al., 2013).
In short, this research reports the principal goodness-of-fit indices which are the Chi-Square
χ2, Normed Chi-Square (CMIN/df), Goodness-of-fit Index (GFI), Normed Fit Index (NFI),
Tucker Lewis Index (TLI), Comparative Fit Index (CFI), and Root Mean Square Error of
Approximation (RMSEA). A key series of goodness-of-fit indices and standard thresholds
(outlined in Table 7-2) were examined to verify the measurement model.
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Table 7-2: Model Fit Indices and Standard Thresholds
Model Fit Indices
(Abbreviated form)
(Type)
Acceptable Fit Interpretation
Standardised
Regression Weights
(Model fit)
≥ 0.5 (≥ 0.7 Ideal) Factor loadings should have minimum value at 0.5
and preferably 0.7 or higher (Hair et al., 2010).
Probability level of
Chi-Square Significant
(CMIN, χ2)
P-value for testing
model fitness p ≥ 0.05
(Hooper et al., 2008)
χ2 tests whether the observed sample and SEM
estimated covariance matrices are equal or not. If
they are, these mean that the model fits (Hair et al.,
2010).
P-value for testing
hypotheses, p < 0.05
To support a hypothesis p-value should be less
than 0.05 (Hair, Black, Babin, Anderson, &
Tatham, 2006).
Normed Chi-Square
(CMIN/df, χ2/df, NC)
(Absolute fit index)
CMIN/df < 5.0 Normed Chi-Square which is more than 5.0
reflects a need for improvement (Schumacker &
Lomax, 2004).
Goodness-of-Fit Index
(GFI) (Absolute fit
index, goodness-to-fit
index)
GFI ≥ 0.90 (≥ 0.95)
The range of GFI values is from 0 (no fit) to 1
(perfect fit), with higher values indicating better fit
than the lower ones (Schumacker & Lomax,
2004). Traditional cut-off point > 0.90 is
considered good (Hooper et al., 2008). However, if
factor loadings and sample sizes are low, a cut-off
of 0.95 is more appropriated (Hair et al., 2010; Teo
et al., 2013).
Normed Fit Index
(NFI) (Incremental fit
index)
NFI ≥ 0.90 (≥ 0.95) The range of NFI values is from 0 (no fit) to 1
(perfect fit), with higher values indicating better fit
than the lower ones (Hair et al., 2010; Schumacker
& Lomax, 2004).The cut-off criteria of NFI should
be close to 0.95 reflecting a good model fit (Hu &
Bentler, 1999; Schumacker & Lomax, 2004), but
0.90 is acceptable (Hooper et al., 2008).
Tucker Lewis Index
(TLI) (Incremental fit
index, goodness-to-fit
index)
TLI ≥ 0.90 (≥ 0.95) The range of TFI values is from 0 (no fit) to 1
(perfect fit), with higher values indicating better fit
(Hair et al., 2010; Schumacker & Lomax, 2004).
Values close to 0.95 reflect a good model fit
(Schumacker & Lomax, 2004). Teo et al. (2013)
add that models with a good fit should have values
that are close to 1.0.
Comparative Fit Index
(CFI) (Incremental fit
index, goodness-to-fit
index)
CFI ≥ 0.90 (≥ 0.95) The range of CFI values is from 0 (no fit) to 1
(perfect fit), with higher values indicating better fit
(Hair et al., 2010).The values greater than 0.90
indicate that the model has good fit (Hair et al.,
2010; Kline, 2005), while Hu and Bentler (1999)
suggest that values of ≥ 0.95 present a good model
fit.
Root Mean Square
Error of
Approximation
(RMSEA) (Absolute
fit index, badness-to-fit
index)
0.03 – 0.08 Values equal and/or less than 0.05 - 0.08 indicate
good fit (Byrne, 2013; Kline, 2005). However,
Hair et al. (2010) state that the RMSEA with 0.03 -
0.08 values are 95% confidence. RMSEA ≥ 0.10
suggests poor fit (Kline, 2005).
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Next, the one-factor congeneric measurement models of eight constructs were assessed for the
convergent validity and GOF to ensure that they share a high proportion of variance in common
(Hair et al., 2010) (see Figure 7-1 to 7-8 and Table 7-3 to 7-10).
➢ FSEs’ Expertise
Figure 7-1: Measurement Model – Expertise
Table 7-3: Goodness-of-Fit Indices for Expertise
CMIN (χ2) df CMIN/ df p GFI NFI TLI CFI RMSEA
1.166 2 .583 .558 .998 .997 1.007 1.000 .000
The expertise congeneric measurement model achieved acceptable fit with the data, although
CMIN/DF > 5.0 extends beyond the threshold value required at < 5.0 (Schumacker & Lomax,
2004). Three factor loadings of item EX1, EX2, and EX5 met the ideal threshold value of ≥
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0.70 supporting convergent validity of the model (Hair et al., 2010; Kline, 2005). Item EX3
had poor factor loadings = 0.43. The inadequate standardised factor loading of scale item EX3
is the cause of this poor model fit. Consequently, item EX3 was dropped from the model. The
model was rerun with acceptable fit statistics (CMIN (χ2) = 0.623, df = 1, CMIN/df = 0.623, p
= 0.430, GFI = 0.998, NFI = 0.998, TLI = 1.003, CFI = 1.000, and RMSEA = 0.000).
➢ FSEs’ Undertaking their Job Requirement
Figure 7-2: Measurement Model – Job Requirement
Table 7-4: Goodness-of-Fit Indices for Job Requirement
CMIN (χ2) df CMIN/df p GFI NFI TLI CFI RMSEA
14.014 2 7.007 .001 .974 .980 .949 .983 .155
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Job requirement congeneric measurement model achieved acceptable fit with data, although
CMIN/DF > 5.0 extends beyond the threshold value required at < 5.0 (Schumacker & Lomax,
2004), RMSEA is above the < 0.08 threshold (Hair et al., 2010), and p-value is below the
desired threshold value (p ≥ 0.05). All observed variables achieved the ideal threshold value of
≥ 0.70, supporting the convergent validity of the model (Hair et al., 2010). However, further
investigation was undertaken and is presented in Chapter 8.
➢ FSEs’ Considerate Manner to Customers
Figure 7-3: Measurement Model – Considerate Manner
Table 7-5: Goodness-of-Fit Indices for Considerate Manner
CMIN (χ2) df CMIN/df p GFI NFI TLI CFI RMSEA
2.337 2 1.168 .311 .995 .998 .999 1.000 .026
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The considerate manner congeneric measurement model achieved satisfactory goodness-of-fit
with respect to the fit indices presented in Table 7-5. Four observed variables achieved the
ideal factor loadings (threshold being ≥ 0.7), indicating convergent validity (Hair et al., 2010).
➢ FSEs’ Personal-Involvement Expression
Figure 7-4: Measurement Model – Personal-Involvement Expression
Table 7-6: Goodness-of-Fit Indices for Personal-Involvement Expression
CMIN (χ2) df CMIN/df p GFI NFI TLI CFI RMSEA
4.898 2 2.449 .086 .991 .994 .989 .996 .076
The personal-involvement expression congeneric measurement model in role-service
behaviours achieved satisfactory goodness-of-fit with respect to the fit indices presented in
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Table 7-6. Four observed variables achieved the ideal factor loadings (threshold being ≥ 0.7),
indicating convergent validity (Hair et al., 2010).
➢ FSEs’ Rapport
Figure 7-5: Measurement Model – Rapport
Table 7-7: Goodness-of-Fit Indices for Rapport
CMIN (χ2) df CMIN/df p GFI NFI TLI CFI RMSEA
12.706 2 6.353 .002 .974 .984 .958 .986 .147
The rapport congeneric measurement model achieved acceptable fit with data, although
CMIN/DF > 5.0 extends beyond the threshold value required (< 5.0) (Schumacker & Lomax,
2004), RMSEA is above the < 0.08 threshold (Hair et al., 2010), and c is below the desired
threshold value (p ≥ 0.05). All observed variables achieved the ideal threshold value of ≥ 0.70,
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supporting convergent validity of the model (Hair et al., 2010; Kline, 2005). However, further
investigation was undertaken and is presented in Chapter 8.
➢ FSE’s Helping without Concern for the Duty Boundary
Figure 7-6: Measurement Model – Helping without Concern for the Duty Boundary
Table 7-8: Goodness-of-Fit Indices for Helping without Concern for the Duty Boundary
CMIN (χ2) df CMIN/df p GFI NFI TLI CFI RMSEA
3.426 2 1.713 .180 .993 .994 .992 .997 .054
Helping without concern for the duty boundary congeneric measurement model achieved
satisfactory goodness-of-fit with respect to the fit indices presented in Table 7-8. All observed
variables achieved the ideal factor loadings of ≥ 0.7, indicating convergent validity (Hair et al.,
2010).
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➢ Customer Service Satisfaction
Figure 7-7: Measurement Model – Service Satisfaction
Table 7-9: Goodness-of-Fit Indices for Service Satisfaction
CMIN (χ2) df CMIN/df p GFI NFI TLI CFI RMSEA
2.424 2 1.212 .298 .995 .998 .999 1.000 .029
The customer service satisfaction congeneric measurement model achieved satisfactory
goodness-of-fit with respect to the fit indices presented in Table 7-9. All indicators achieved
factor loadings ≥ 0.70, indicating convergent validity (Hair et al., 2010).
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➢ Customer Value Perception
Figure 7-8: Measurement Model – Value Perception
Table 7-10: Goodness-of-Fit Indices for Value Perception
CMIN (χ2) df CMIN/df p GFI NFI TLI CFI RMSEA
21.336 5 4.267 .001 .967 .969 .953 .976 .115
The customer value perception congeneric measurement model achieved acceptable fit with
the data, although the p - value is below the desired threshold value at ≥ 0.05 and RMSEA is
above the threshold value at < 0.08 (Hair et al., 2010). This model was considered acceptable
as four factor loadings of item VP3, VP6, VP7, and VP10 met the ideal threshold value of >
0.70 which indicates convergent validity (Hair et al., 2010; Kline, 2005). Even though item
VP8 did not exceed the threshold of ≥ 0.70, the scale still achieved an acceptable factor loading
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of above > 0.50 (Hair et al., 2010). In addition, the inclusion of this indicator might provide an
additional theoretical nuance to the construct. Therefore, item VP8 was retained in the model.
Further investigation was undertaken and is presented in Chapter 8.
7.5.2.2 Reliability and Discriminant Validity
In this section, an overall measurement model was tested to confirm the model validity. All
constructs and their respective measured variables were analysed for their reliability and
discriminant validity (Hair et al., 2010).
Reliability was investigated to see how well a set of indicators of construct was internally
consistent in their measurements (Hair et al., 2010). The indicators of highly reliable constructs
are highly interrelated, indicating that they all seem to measure the same thing (Hair et al.,
2010) and are free from random measurement error (Kline, 2005). Both Cronbach’s coefficient
alpha and construct reliability were conducted to determine reliability (Hair et al., 2010). The
Cronbach’s alpha test was also conducted to check the internal consistency and the reliability
of the selected scale items (Pallant, 2007). Construct reliability value is used in conjunction
with structural equation modelling models. This thesis conducted the construct reliability along
with the Cronbach’s coefficient alpha as the latter measure has been criticised. Even though
Cronbach’s alpha is the most widely used measurement of the reliability, the construct loadings
of this estimator are constrained to be equal (Hair et al., 2010; Peterson & Kim, 2013).
Therefore, the measure underestimates true reliability. While construct reliability allows the
construct loadings to vary (Peterson & Kim, 2013). SME has the ability to assess and overcome
the assumptions’ limitation of Cronbach’s alpha (Peterson & Kim, 2013).
Discriminant validity was examined to ensure that the scale items of a particular construct were
truly distinct from those of other constructs (Hair et al., 2010). The Average Variance Extracted
(AVE) was calculated to measure the discriminant validity (Hair et al., 2010). AVE should be
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greater than the highest squared correlation estimate to achieve discriminant validity (Hair et
al., 2010). This is based on the notion that a latent construct should explain more of the variance
in its item measures that it shares with another construct (Hair et al., 2010: p. 686). Individual
measured items should represent solely one construct.
All constructs have been measured for Cronbach’s alpha by using SPSS 23. While construct
reliability and AVE were computed manually using inputs form the AMOS 23 output after
conducting CFA. The formulas used for calculating construct reliability and AVE are presented
in the Figure 7-9 (Hair et al., 2010: p. 687).
Figure 7-9: Construct Reliability and Average Variance Extracted (AVE) Formulas
* Li = Factor loadings, ei = Error variance terms for a construct (Hair et al., 2010: p. 687)
The reliability, validity, and standard indices and analysis thresholds were outlined in Table 7-
11 to verify the measurement model validity.
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Table 7-11: Reliability, Validity, and Standard Indices
Reliability and Validity
Indicators Threshold Comments
Squared Multiple
Correlation (SMC)
From 0 to 1 (Schumacker &
Lomax, 2004)
SMC indicates how well the indicators
serve as measures of the latent factors
(Hair et al., 2010). The SMC’s values
perform as an indication of the strength
of the structural relationships
(Schumacker & Lomax, 2004: p. 72).
SMC is similar to the R2 value which is
used as a model fit criterion in multiple
regression analysis (Schumacker &
Lomax, 2004). SMC scales range from
0 to 1 (Schumacker & Lomax, 2004).
SMC was computed as one minus the
ratio of the error variance over the total
variance (Kline, 2005).
Cronbach’s Coefficient
Alpha
≥ 0.7 (De Vaus, 2002;
Pallant, 2007)
Cronbach’s coefficient alpha assesses the
consistency of all scales (Hair et al., 2010)
– how groups of variables are related to
groups of other variables (De Vaus,
2002).
Construct Reliability ≥ 0.7 (Hair et al., 2010)
Construct reliability is computed from the
squared sum of factor loadings for each
construct (Hair et al., 2010).
Average Variance
Extracted (AVE) ≥ 0.5 (Hair et al., 2010)
AVE is calculated as the mean variance
extracted for the items loading on a
construct and is a summary indicator of
convergence. Average variance extracted
should exceed the squared correlation
estimate to provide good evidence of
discriminant validity (Hair et al., 2010).
Table 7-12 presented the results of CFA model for all constructs. The results indicated that all
sets of indicators of constructs are highly reliable. All Cronbach’s alpha and construct
reliability scores exceed the threshold of ≥ 0.7 (De Vaus, 2002). On average, the estimates of
true reliability of the construct reliability were greater than those produced by coefficient alpha
(Peterson & Kim, 2013). All average variance extracted (AVE) values exceeded the threshold
of ≥ 0.05 suggesting adequate convergent validity (Hair et al., 2010). Discriminant validity was
examined comparing the values between AVE and the highest squared correlation estimates of
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constructs (Hair et al., 2010). The results showed that all but three constructs had AVE scores
that exceeded those of the highest squared correlation estimate.
The considerate manner (CC) construct and the personal-involvement expression (PE)
construct attained convergent validity and reliability (De Vaus, 2002; Hair et al., 2010; Pallant,
2007). However, these two constructs did not achieve discriminant validity (see Table 7-12).
These two constructs had high estimated correlations to each other. Even though the researcher
defined the operational definitions of these two constructs quite distinctively, they appear to
share common traits of courtesy and a positive approach towards customers (see Chapter 6,
Table 6-12 and Table 6-13). The lack of discriminant validity suggested that the CC and the
PE constructs might represent only one construct (Hair et al., 2010). As explained in previous
chapters, the constructs of this research were built from the outcomes of qualitative data
analysis, and they were operationalized with items adapted from previous research that
measured the service employee-perspective while this thesis has focused on the customer-
perspective. This may explain the unachieved discriminant validity.
For customer service satisfaction (SS), this construct achieved convergent validity and
reliability (De Vaus, 2002; Hair et al., 2010; Pallant, 2007), yet not discriminant validity with
personal-involvement expression (PE). A strong relationship between these variables could be
expected as from the literature, FSEs’ attitudes, personality, and involvement could affect their
service delivery and service behaviours (Ackfeldt & Wong, 2006; Bettencourt et al., 2001;
Dimitriades, 2007). Others added that the behaviours of FSEs can enhance the customers’
perception of service quality (Farrell et al., 2001; Frazer Winsted, 2000; Lloyd & Luk, 2011)
and that the perception of service quality could lead to customer satisfaction (Brady &
Robertson, 2001; Dagger et al., 2007; Leisen Pollack, 2009; Lloyd & Luk, 2011). In addition,
these two constructs were identified differently in a structural model which will be tested in
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Chapter 8; PE was a predictor (exogenous construct) and SS was an outcome (endogenous
construct). Thus, these two constructs were distinguished in the model.
However, unachieved discriminant validity and the high estimated correlations (< 0.90)
between PE and SS, and PE and CC indicated that personal-involvement expression indicators
might not measure the construct distinct from those of CC and SS. In Chapter 8, all exogenous
constructs measured in the CFA model will be presented; this will enable the confirmation of
the convergent and discriminant validity. If PE fails the test of discriminant validity in the next
analysis, this construct will be eliminated from the mode
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Table 7-12: Summary of CFA Model Testing for All Constructs
Scales Items
Standardised
Regression
Weights
(Factor
Loadings)
Squared
Multiple
Correlations
Cronbach’s
Coefficient
Alpha (α)
Construct
Reliability
Average
Variance
Extracted
(AVE)
Highest
Squared
Correlation
Estimate
Expertise
0.853 0.857 0.667 0.312
EX1 0.858 0.736
EX2 0.819 0.671
EX5 0.771 0.594
Job
Requirement
JR1 0.939 0.882 0.906 0.911 0.719 0.681
JR2 0.866 0.750
JR3 0.795 0.632
JR4 0.782 0.612
Considerate
Manner
0.969 0.969 0.886 0.935
CC1 0.937 0.878
CC2 0.936 0.875
CC3 0.954 0.910
CC4 0.938 0.879
Personal-
involvement
expression
0.926 0.929 0.766 0.935
PE1 0.936 0.876
PE4 0.838 0.703
PE5 0.871 0.758
PE6 0.852 0.725
Rapport
0.898 0.919 0.740 0.731
RA1 0.882 0.777
RA3 0.952 0.906
RA4 0.855 0.731
RA6 0.738 0.545
Helping
without
Concerning
to the Duty
Boundary
0.882 0.883 0.653 0.358
WC1 0.778 0.606
WC2 0.790 0.624
WC3 0.805 0.648
WC4 0.857 0.735
Customer
Service
Satisfaction
0.936 0.943 0.808 0.823
SS1 0.883 0.78
SS2 0.77 0.593
SS3 0.969 0.940
SS4 0.959 0.919
Customer
Value
Perception
0.887 0.891 0.623 0.358
VP3 0.816 0.665
VP6 0.766 0.587
VP7 0.867 0.751
VP8 0.684 0.468
VP10 0.802 0.644
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7.6 Chapter Summary
This chapter described the preliminary analysis. Data screening was conducted, resulting in
three responses being removed from the sample collected for the main data analysis. One-factor
congeneric measurement models were run to evaluate the model fit of each construct. One
indicator was excluded from the data due to its poor factor loadings which were below the
minimum threshold of 0.50. All constructs and their respective measured variables were
analysed for their reliability and discriminant validity. The results showed all sets of indicators
of constructs were highly reliable and had adequate convergent validity. However, all but three
constructs achieved the discriminant validity. All constructs and their respective measured
variables will be further investigated in the next chapter. The next chapter will discuss the main
data analysis which includes structural model testing, path model identification, and thesis
hypothesis investigation.
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CHAPTER 8
HYPOTHESIS TESTING
This chapter outlines each step of data analysis to address the research hypotheses in Chapter
5. The collected data was analysed with structural equation modelling (SEM) using AMOS23.
The first section investigates the discriminant validity and reliability by applying the
Confirmatory Factor Analysis (CFA) to all independent and dependent variables. In addition,
measurement models of the three service-role behaviours are also presented. In section two,
the relationships between the theoretical constructs in the structural model are presented. The
results from the hypothesis testing are discussed in the fourth and final section.
8.1 Measurement Models for FSEs’ Service-Role Behaviours
In chapter 4, the analysis of FSE interviews revealed that there were three types of service-role
behaviours; role-prescribed, beyond role, and helping behaviours. Chapter five developed the
research hypotheses based on these three role behaviours. This section investigates the
measurement model of the three FSE service-role behaviours using confirmatory factor
analysis.
8.1.1 Role-Prescribed Behaviours: Testing the Expertise and Job Requirement
Constructs
The results of qualitative data analysis in Chapter 4 showed that when FSEs perform role-
prescribed behaviours, having expertise and undertaking their job requirement are necessary.
In Chapter 7, these one-factor congeneric measurement models were needed to achieve
convergent validity.
In most of the previous literature, expertise has been conceptualised from the employee and
customer perspectives as interaction quality (Gazzoli, Hancer, & Park, 2010), service
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quality/personal interaction (Dabholkar et al., 1996), product-market expertise (Chiou &
Droge, 2006), employee skills (Barnes et al., 2011), or service training (Liao & Chuang, 2004),
although Maxham III et al. (2008) explain that expertise is a FSE’s core job responsibility.
There is little consistency in the literature, but more interesting is that the perception and
measurement of FSEs’ expertise from the customer perspective has not been studied.
Undertaking job requirement is documented in the literature as the FSE performance of role-
prescribed behaviours (Bettencourt & Brown, 1997; Raub & Liao, 2012; Tsaur et al., 2014).
However, to the knowledge of the author, there is no literature measuring this construct as
perceived and measured from the customer perspective. According to the previous literature
(i.e. Netemeyer & Maxham III, 2007; Tsaur & Lin, 2004; Yoo, 2013), most of the studies have
investigated role-prescribed behaviours from the employees’ side.
8.1.1.1 Discriminant Validity and Reliability Testing of Expertise and Job Requirement
Constructs
The constructs of expertise and FSEs’ undertaking their job requirement were included in a
confirmatory factor analysis to investigate the discriminant validity and reliability. These CFA
models of role-prescribed behaviours were checked to ensure that they were reliable constructs
and truly distinct from each other (Hair et al., 2010).
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Figure 8-1: CFA Model – Expertise and Job Requirement
The CFA model (Figure 8-1 and Table 8-1) revealed reasonable model fit, in terms of the
various fit measures. That the significance value was relatively small (0.003, threshold ≥ 0.05)
suggests further model modification is necessary when these two constructs are included in a
full model. The remaining fit indices suggested model fit and all factor loadings were greater
than 0.70, confirming convergent validity (Hair et al., 2010).
Table 8-1: Goodness-of-Fit Indices for Expertise and Job Requirement
CMIN (χ2) df CMIN/df p GFI NFI TLI CFI RMSEA
31.203 13 2.400 .003 .966 .973 .974 .984 .075
The results of the discriminant validity and reliability of the constructs are presented in Table
8-2. Reliability was tested by Cronbach’s alpha, Construct Reliability, and Average Variance
Extracted (AVE) values. The results showed that Cronbach’s alpha and construct reliability
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were well above the conventional threshold limit (≥ 0.7) and the values of AVE (0.67 and 0.72)
were larger than 0.50, confirming reliability (De Vaus, 2002; Hair et al., 2010). Discriminant
validity was investigated by the difference between the AVE and the squared correlation
estimate (Hair et al., 2010). Table 8-2 showed that the AVE estimates for the two constructs
exceeded the highest squared correlation estimate values, indicating discriminant validity (Hair
et al., 2010). Therefore, the expertise and job requirement constructs achieved reasonable
model fit, construct validity, and reliability.
Table 8-2: Summary of CFA Model – Reliability and Validity Measures for Expertise and Job
Requirement
Scales Items
Standardised
Regression
Weights
(Factor
Loadings)
Squared
Multiple
Correlations
Cronbach’s
Coefficient
Alpha
Construct
Reliability
Average
Variance
Extracted
(AVE)
(Highest)
Squared
Correlation
Estimate
Expertise
EX1 0.869 0.755 0.853 0.857 0.667 0.311
EX2 0.824 0.679
EX5 0.752 0.566
Job
Requirement
JR1 0.944 0.890 0.906 0.911 0.720 0.311
JR2 0.849 0.721
JR3 0.802 0.642
JR4 0.791 0.625
8.1.2 Beyond Role Behaviours: Testing the Considerate Manner, Personal Involvement,
and Rapport Constructs
The results of qualitative data analysis in Chapter 4 revealed that while FSEs were providing
services to customers, they did not only perform their official routine tasks following their job
descriptions, but they also expressed their personal attitudes, feelings, involvement, or
considerations into their roles during the encounters.
Previous studies have measured and focused on the organisation’s, manager’s, and/or
employee’s perspectives of the group of constructs (ex. MacKenzie et al., 1998; Sosik,
Juzbasich, & Chun, 2011; Williams & Anderson, 1991). There is neither consistency in the
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literature nor in the measures from the customer perspectives on FSEs’ service-role behaviours.
Therefore, this thesis aims to examine one-factor congeneric measurement models for
considerate manner, personal-involvement expression, and rapport as dimensions of beyond
role behaviours as perceived by customers.
8.1.2.1 Discriminant Validity and Reliability Testing of Considerate Manner, Personal-
Involvement Expression, and Rapport Constructs
The results of one-factor congeneric measurement models testing for considerate manner,
personal-involvement expression, and rapport are described below. These three constructs
were included in a confirmatory factor analysis model to investigate the discriminant validity
of the constructs.
Figure 8-2: CFA Model – Considerate Manner, Personal-Involvement Expression, and Rapport
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The CFA model of considerate manner, personal-involvement expression, and rapport (Figure
8-2 and Table 8-3) achieved reasonable fit with the data. P-value was below the acceptable fit
values (p ≥ 0.05) and the RMSEA was above the desired threshold values (0.03 – 0.08). Thus,
further probing was necessary.
Table 8-3: Goodness-of-Fit Indices for Considerate Manner, Personal-Involvement Expression, and
Rapport
CMIN (χ2) df CMIN/df p GFI NFI TLI CFI RMSEA
148.275 51 2.907 .000 .918 .960 .966 .974 .088
From Table 8-4, all the values of Cronbach’s alpha (0.969, 0.926, and 0.898), construct
reliability (0.97, 0.93, and 0.92), and AVE (0.89, 0.77, and 0.74) were well above the
recommended acceptable values of ≥ 0.7 and ≥ 0.5, respectively, which confirms reliability
(De Vaus, 2002; Hair et al., 2010; Pallant, 2007). The rapport measurement model achieved
discriminant validity as the AVE exceeded the highest squared correlation estimate. This
demonstrates that rapport was a robust construct and is distinct from others (Hair et al., 2010).
However, the AVE values of the constructs considerate manner and personal involvement did
not exceed the highest squared correlation estimate. Their estimated correlations were higher
than 0.90, thus the eight indicators can hardly be said to measure two distinct constructs (Kline,
2005). The results suggest that either the considerate manner or the personal-involvement
expression construct might be excluded during the further model modification step.
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Table 8-4: Summary of CFA Model – Reliability and Validity Measures for Considerate Manner,
Personal-Involvement Expression, and Rapport
Scales Items
Standardised
Regression
Weights
(Factor
Loadings)
Squared
Multiple
Correlations
Cronbach’s
Coefficient
Alpha
Construct
Reliability
Average
Variance
Extracted
(AVE)
Highest
Squared
Correlation
Estimate
Considerate
Manner
CC1 0.940 0.883 0.969 0.969 0.886 0.937
CC2 0.935 0.874
CC3 0.950 0.903
CC4 0.940 0.884
Personal-
involvement
expression
PE1 0.934 0.872 0.926 0.929 0.766 0.937
PE4 0.844 0.713
PE5 0.871 0.758
PE6 0.850 0.723
Rapport
RA1 0.886 0.785 0.898 0.918 0.739 0.702
RA3 0.950 0.902
RA4 0.854 0.729
RA6 0.736 0.541
8.1.3 Helping Behaviours: Testing the Construct Helping without Concern for the Duty
Boundary
For helping behaviours, there is only a single one-factor congeneric measurement model
(helping without concern for the duty boundary), which was presented in Chapter 7. All values
in Table 7-8 achieved satisfactory goodness-of-fit. The evidence from Table 8-5 shows that the
values of Cronbach’s alpha, construct reliability, and AVE satisfied their respective cut-off
threshold of ≥ 0.70, ≥ 0.70, and ≥ 0.50 (De Vaus, 2002; Hair et al., 2010) assuring reliability
of scale items. The factor loadings of all the scale items were well above the ideal threshold of
≥ 0.70 confirming convergent validity (Hair et al., 2010).
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Table 8-5: Summary of CFA Model – Reliability and Validity Measures for Helping without Concern
for the Duty Boundary
Scales Items
Standardised
Regression
Weights
(Factor
Loadings)
Squared
Multiple
Correlations
Cronbach’s
Coefficient
Alpha
Construct
Reliability
Average
Variance
Extracted
(AVE)
Helping
without
Concern for
the Duty
Boundary
0.882 0.883 0.653
WC1 0.778 0.606
WC2 0.783 0.614
WC3 0.808 0.653
WC4 0.860 0.739
8.1.4 CFA Model – All Independent Variables - First Model Step
Next all FSEs’ service-role behaviours were tested with confirmatory factor analysis to
investigate discriminant validity. This CFA model included two constructs of role-prescribed,
three of beyond role, and one of helping behaviours.
Figure 8-3: CFA Model – All Independent Variables - First Model Step
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While some measures revealed acceptable fit with the data (e.g. CMIN/df = 2.045; NFI = 0.927;
TLI = 0.954; CFI = 0.961; and RMSEA = 0.065), all factor loadings met the ideal threshold
value of ≥ 0.70 (Table 8-6) confirming convergent validity of the model (Hair et al., 2010).
The p = .000 and GFI = .874 suggest that the CFA model (Figure8-3 and Table 8-6) was a poor
fit (threshold ≥ 0.05 and ≥ 0.90 respectively). Further investigation was needed of the
measurement model.
Table 8-6: Goodness-of-Fit Indices for Independent Variables - First Model Step
CMIN (χ2) df CMIN/df p GFI NFI TLI CFI RMSEA
439.625 215 2.045 .000 .874 .927 .954 .961 .065
Table 8-7 clearly showed that Cronbach’s alpha and composite reliability values of the six
constructs were well above the conventional threshold limit (≥ 0.7)(De Vaus, 2002; Pallant,
2007), indicating the existence of internal consistency (Hair et al., 2010). All the values of AVE
were larger than the 0.5, suggesting adequate convergence. Four constructs had AVE values
exceeding the highest squared correlation estimate (Hair et al., 2010), confirming each
construct had empirical and conceptual distinction. However, the AVE values of two
constructs, considerate manner (CC) and personal-involvement expression (PE), did not
exceed the highest squared correlation estimate. In Chapter six, the conceptual recognition of
both constructs was defined quite distinctively, but they were closely related to each other.
They were both assigned into the elements of beyond role behaviours by the results of
qualitative data analysis in Chapter four. The researcher decided to remove the PE construct
from the next analysis. The reasons for excluding this construct were (i) the discriminant
validity of PE and CC also failed in the testings of CFA model in Table 7-12 (Chapter seven)
and Table 8-4, and (ii) in the results of CFA model testing in chapter seven, PE had estimated
correlations with CC and service satisfaction (SS) higher than 0.90 (Kline, 2005). These results
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suggest that the indicators of PE measure essentially the same constructs as CC and SS. As the
PE construct was removed from the analysis, hypotheses H4a (Perception of FSE personal-
involvement expression has a positive effect on customer service satisfaction) and H4b
(Perception of FSE personal-involvement expression has a positive effect on customer value
perception) were no longer investigated.
Table 8-7: Summary of CFA Model – Reliability and Validity Measures Independent Variables - First
Model Step
Scales Items
Standardised
Regression
Weights
(Factor
Loadings)
Squared
Multiple
Correlations
Cronbach’s
Coefficient
Alpha
Construct
Reliability
Average
Variance
Extracted
(AVE)
Highest
Squared
Correlation
Estimate
Expertise
0.853 0.857 0.667 0.326
EX1 0.861 0.741
EX2 0.821 0.673
EX5 0.766 0.587
Job
Requirement
0.906 0.910 0.719 0.679
JR1 0.943 0.889
JR2 0.860 0.739
JR3 0.797 0.635
JR4 0.782 0.612
Considerate
Manner
0.969 0.969 0.886 0.935
CC1 0.937 0.878
CC2 0.935 0.874
CC3 0.954 0.909
CC4 0.939 0.882
Personal-
involvement
expression
0.926 0.93 0.77 0.94
PE1 0.932 0.869
PE4 0.843 0.711
PE5 0.873 0.763
PE6 0.851 0.725
Rapport
0.898 0.919 0.741 0.704
RA1 0.884 0.781
RA3 0.947 0.896
RA4 0.858 0.735
RA6 0.742 0.550
Helping
without
Concern for
the Duty
Boundary
0.882 0.883 0.653 0.279
WC1 0.774 0.6
WC2 0.792 0.628
WC3 0.803 0.644
WC4 0.860 0.740
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8.1.5 CFA Model – All Independent Variables - Second Model Step
For this CFA model, personal-involvement expression construct was removed from further
analysis. A series of goodness of fit measures for all independent variables in the second model
modification step (Figure 8-4 and Table 8-8) demonstrated an acceptable fit with the data. The
Standardised factor loadings for each indicator were above 0.70 (threshold ≥ 0.70) (Table 8-9)
indicating convergent validity (Hair et al., 2010). One exception was that the p-value was below
the acceptable fit value (p ≥ 0.05). However, the complexity of the model and the relatively
small sample size suggest that the Chi-square statistic can lack power (Hooper et al., 2008;
Kenny & McCoach, 2003). Given the values of the other goodness of fit measures the second
step model was accepted for further analysis.
Figure 8-4: CFA Model – All Independent Variables - Second Model Step
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Table 8-8: Goodness-of-Fit Indices for All Independent Variables - Second Model Step
CMIN (χ2) df CMIN/df p GFI NFI TLI CFI RMSEA
246.004 142 1.732 .000 .907 .946 .971 .976 .054
In Table 8-8, Cronbach’s alpha and construct reliability values of each construct exceeded the
conventional threshold limits of 0.70 confirming their reliability (De Vaus, 2002; Hair et al.,
2010; Pallant, 2007). Convergent validity was achieved (AVE ≥ 0.5) and discriminant validity
was confirmed as AVE values were well above the highest squared correlation estimates,
indicating that each construct was empirically and conceptually distinct from others (Hair et
al., 2010).
Table 8-9: Summary of CFA Model – Reliability and Validity Measures for All Independent Variables
- Second Model Step
Scales Items
Standardised
Regression
Weights
(Factor
Loadings)
Squared
Multiple
Correlations
Cronbach’s
Coefficient
Alpha
Construct
Reliability
Average
Variance
Extracted
(AVE)
Highest
Squared
Correlation
Estimate
Expertise
0.853 0.857 0.667 0.327
EX1 0.860 0.739
EX2 0.820 0.672
EX5 0.768 0.590
Job
Requirement
0.906 0.910 0.719 0.679
JR1 0.941 0.885
JR2 0.863 0.745
JR3 0.796 0.633
JR4 0.782 0.611
Considerate
Manner
0.969 0.969 0.886 0.679
CC1 0.937 0.878
CC2 0.938 0.880
CC3 0.950 0.903
CC4 0.939 0.882
Rapport
0.898 0.919 0.741 0.658
RA1 0.884 0.782
RA3 0.946 0.895
RA4 0.858 0.736
RA6 0.742 0.550
Helping
without
Concern for
the Duty
Boundary
0.882 0.883 0.653 0.280
WC1 0.774 0.600
WC2 0.793 0.629
WC3 0.802 0.644
WC4 0.860 0.739
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8.1.6 CFA Model – All Constructs
After excluding the personal-involvement expression construct, all constructs, both exogenous
and endogenous, were measured for goodness-of-fit and other evidence of construct validity in
this section.
Figure 8-5: CFA Model – All Constructs
Table 8-10: Goodness-of-Fit Indices for All Constructs
CMIN (χ2) df CMIN/df p GFI NFI TLI CFI RMSEA
614.581 329 1.868 .000 .854 .914 .952 .958 .059
The measurement model of all constructs achieved fit with the data (Table 8-10). Significance
was not achieved as p-value was not ≥ 0.5. Nevertheless, model fit was accepted because with
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complex models and small samples, the χ2 lacks power to differentiate models (Hooper et al.,
2008; Kenny & McCoach, 2003). The GFI value was also below the threshold of ≥ 0.90;
however, when a model contains an increased number of measured variables and parameter
estimates, the cut-off values on key goodness-of-fit measures become unrealistic (Hair et al.,
2010). The remaining fit indices indicated an acceptable model fit and all factor loadings were
greater than 0.7, confirming convergent validity (Hair et al., 2010).
The results from the measurement model (Table 8-11) indicated that all constructs achieved
discriminant validity and reliability. Cronbach’s alpha and construct reliability were
satisfactory with values > 0.7 (De Vaus, 2002; Hair et al., 2010; Pallant, 2007), indicating the
existence of internal consistency (Hair et al., 2010). All the AVE values exceeded ≥ 0.5,
confirming convergent validity (Hair et al., 2010). The discriminant validity of all constructs
were achieved as the AVE values were greater than the highest squared correlation estimates
(Hair et al., 2010), showing that each construct was truly distinct from others. Next, in Section
8.2, all constructs are examined in structural models.
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Table 8-11: Summary of CFA Model – Reliability and Validity Measures for All Constructs
Scales Items
Standardised
Regression
Weights
(Factor
Loadings)
Squared
Multiple
Correlations
Cronbach’s
Coefficient
Alpha
Construct
Reliability
Average
Variance
Extracted
(AVE)
Highest
Squared
Correlation
Estimate
Expertise
0.853 0.857 0.667 0.326
EX1 0.857 0.734
EX2 0.818 0.669
EX5 0.773 0.598
Job
Requirement
0.906 0.940 0.755 0.682
JR1 0.936 0.877
JR2 0.871 0.758
JR3 0.793 0.629
JR4 0.781 0.611
Considerate
Manner
0.969 0.969 0.886 0.780
CC1 0.938 0.879
CC2 0.940 0.883
CC3 0.952 0.906
CC4 0.935 0.875
Rapport
0.898 0.919 0.740 0.731
RA1 0.882 0.777
RA3 0.952 0.906
RA4 0.855 0.731
RA6 0.738 0.545
Helping
without
Concern for
the Duty
Boundary
0.882 0.883 0.653 0.358
WC1 0.778 0.606
WC2 0.790 0.624
WC3 0.805 0.648
WC4 0.857 0.735
Service
Satisfaction
0.936 0.944 0.808 0.780
SS1 0.882 0.779
SS3 0.771 0.594
SS4 0.968 0.936
SS6 0.961 0.923
Value
Perception
0.887 0.891 0.623 0.358
VP3 0.816 0.665
VP6 0.766 0.587
VP7 0.867 0.752
VP8 0.684 0.467
VP10 0.802 0.643
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8.2 Structural Models
The structural model is the second stage of testing theoretical associations within a structural
equations methods (SEM) (Hair et al., 2010). Similar to the measurement model (CFA), the
structural model examines the relationships between theoretical constructs and measures the
concepts in a reliable and valid manner (Schumacker & Lomax, 2004). However, the structural
model also includes the assessment of the significance of causal relationships between
independent and dependent variables in multiple regression analysis (Hair et al., 2006).
Before the SEM analysis process begins, some basic principles of testing structural theory need
to be determined, including model specification, model identification, and model validity (Hair
et al., 2010; Kline, 2005).
8.2.1 The Structural Model Specification
This stage involves the unit of analysis, a path diagram, hypothesised relationships, and a
recursive model (Hair et al., 2010). First, the unit of analysis was at the individual level, testing
the associations between perceptions of customer towards service-role behaviours and service
satisfaction and value. Second, the theory is illustrated by visual path diagrams. The structural
relationships between exogenous constructs (predictors) and endogenous constructs
(outcomes) are represented empirically by the structural parameter estimate or a path estimate
(Hair et al., 2006). Third, the proposed theory of this thesis is examined by checking the effect
of five exogenous constructs - expertise, job requirement, considerate manner, rapport, and
helping without concern for the duty boundary - on two endogenous constructs, service
satisfaction and value perception. Fourth, the paths between constructs proceeded only from
the predictor constructs to the dependent or outcome constructs (Hair et al., 2010).
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8.2.2 The Structural Model Identification
An identified model refers to the theoretical possibility to derive a unique estimate of each
parameter (Kline, 2005). If the basic requirements for the identification of an SEM are not met
or the model is not identified, the SEM cannot be estimated by an algorithm and the analysis
is ineffective (Kline, 2005). There are two essentials for the model identification that need to
be performed (i) the number of observations must be at least be equal to the number of model
parameters; and (ii) all latent variables must be assigned a scale (Kline, 2005). The model of
this thesis was designed to meet these two requirements.
8.2.3 The Structural Model Validity
The structural model uses the overall and relative model fit, CFA estimates, and regression
coefficient to assess whether the data fit the hypothesised paths and models or not (Byrne,
2013; Hair et al., 2010). Good fit alone is not enough to support a proposed structural theory;
the individual parameter estimates are also examined against the corresponding hypotheses in
the structural model (Hair et al., 2010). CFA estimates were also presented to confirm the
validity of the indicator variables in the structural model analysis. Table 7-2 in Chapter 7 and
Table 8-12 summarises the goodness-of-fit indices and estimation used for all structural
equation models. All standard measures except standard error of the estimate (SE), critical ratio
(CR), standardised residuals, and modification indices (MI) were described in Chapter 7. These
last five measures are explained below.
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Table 8-12: Standard Thresholds
Reliability and
Validity Indicators Threshold Comments
Standard error (SE)
There are no definitive
criteria of ‘small’ and
‘large’ standard error
(Byrne, 2013: p. 67).
SE is a measure of the statistical precision of an
estimate of parameter, with small values indicating
accurate estimation (Byrne, 2013),while extreme
large standard errors indicate parameters cannot be
determined (Byrne, 2013).
Critical ratio (CR) > 1.96
The Critical ratio (CR) for a pair of parameter
estimates provides an assessment of the hypothesis
that the two parameters are equal (Byrne, 2013).
Based on a significance level of 0.05, any critical
ratio that is greater than 1.96 in magnitude, the
covariance between a pair of parameter estimates is
significant (Arbuckle, 2010). CR is acquired by
dividing the covariance estimate by its standard error
(Arbuckle, 2010).
Standardised
Residuals
< 2.0 (Jöreskog &
Sörbom, 1984),
(20 – 4.0 needs some
attention) (Hair et al.
2010)
The standardised residuals are obtained by the raw
residuals divided by the standard error of the residual
(Hair et al., 2010). Residuals which are greater than
4.0 suggest an unacceptable degree of error (Hair et
al., 2010). Standardised residuals are useful in
diagnosing problems with a model due to its
independence from the actual measurement scale
range (Hair et al., 2010).
Modification indices
(MI)
MI of about 4.0 or
greater indicate the
reduced amount of X2
value that resulted from
the corresponding path
(Hair et al., 2010: p.
689)
MI are assessed for all parameters that are not
estimated in a model (Hair et al., 2010). MI identify
the error term correlations and correlational
relationships between constructs (Hair et al., 2010).
The corresponding paths that are substantially larger
than the others represent misspecified error
covariances (Byrne, 2013). These measurement error
covariances indicate systematic measurement error in
item responses which are obtained from (i)
characteristics specific either to the measured scales
or to the respondents (e.g. social desirability bias) or
(ii) a high degree of overlap or redundancy in item
content (Byrne, 2013: p. 110).
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8.3 Structural Model – Modification Process
8.3.1 First Model
Figure 8-6: First Model
The results of the first structural model (Table 8-13) demonstrated a poor GFI = 0.853
(threshold ≥ 0.90) and relatively small p-value = 0.000 (threshold p ≥ 0.05). Further
investigation was deemed necessary.
Table 8-13: Goodness-of-Fit Indices for Structural Model - First Model
CMIN (χ2) df CMIN/df p GFI NFI TLI CFI RMSEA
618.758 330 1.875 .000 .853 .914 .951 .957 .059
Careful investigation identified that some items were suspect because of higher standardised
residual covariance, weak path coefficient values, lower factor loadings when compared to
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other items in the constructs, or larger and multiple presences in modification indices (i.e. JR1,
JR2, JR3, JR 4, CC4, RA6, and VP6). These items were removed from the next CFA model
(Second model, Figure 8-7). The removal of all items for the Job Requirement (JR) construct,
hypotheses H2a (Perception of the degree of job requirement met positively affects customer
service satisfaction) and H2b (Perception of the degree of job requirement met positively
affects customer value perception) were removed from the thesis.
From Table 8-14 the Cronbach’s alpha values of all constructs were well above the threshold
score of 0.7, indicating construct reliability. All values of AVE achieved the threshold measure
of ≥ 0.5. All factor loadings were greater than 0.5, confirming convergent validity (Hair et al.,
2010). Discriminant validities of all exogenous constructs were achieved as the values of AVE
exceeded those of highest squared correlation estimate.
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Table 8-14: Summary of Structural Model – CFA Estimates, Validity and Reliability – First Model
Construct Item
Code
CFA Estimates Reliability and Validity Measures
Standardised
Regression
Weights
(Factor
Loadings)
Standard
Error
(SE)
Critical
Ratio
(CR)
Squared
Multiple
Correlation
(SMC)
Construct
Reliability
Cronbach’s
Coefficient
Alpha
Average
Variance
Extracted
(AVE)
Highest
Squared
Correlation
Estimate
Expertise
EX1 0.857 x x 0.734
0.857 0.853 0.667 0.325 EX2 0.818 0.061 14.713 0.670
EX5 0.773 0.072 13.278 0.598
Job
Requirement
JR1 0.936 x x 0.877
0.940 0.906 0.754 0.682
JR2 0.870 0.048 21.351 0.757
JR3 0.793 0.060 17.617 0.630
JR4 0.782 0.059 16.952 0.611
Considerate
Manner
CC1 0.938 0.035 29.221 0.879
0.969 0.969 0.886 0.682
CC2 0.939 0.036 29.263 0.882
CC3 0.952 0.034 30.956 0.906
CC4 0.935 x x 0.875
Rapport
RA1 0.881 0.054 14.347 0.776
0.918 0.898 0.739 0.654
RA3 0.952 0.055 15.657 0.907
RA4 0.854 0.063 14.033 0.730
RA6 0.738 x x 0.544
Helping
without
Concern
for the
Duty
Boundary
WC1 0.779 0.064 13.966 0.607
0.883 0.882 0.653 0.281
WC2 0.790 0.061 14.424 0.625
WC3 0.805 0.062 14.976 0.648
WC4 0.857 x x 0.734
Service
Satisfaction
SS1 0.882 x x 0.779
0.943 0.936 0.808 -
SS2 0.770 0.062 15.766 0.593
SS3 0.968 0.038 25.894 0.937
SS4 0.961 0.041 25.536 0.923
x – This regression weight was fixed at 1.000, not estimated.
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Table 8-14: Summary of Structural Model – CFA Estimates, Validity and Reliability – First Model
(Continued)
Construct Item
Code
CFA Estimates Reliability and Validity Measures
Standardised
Regression
Weights
(Factor
Loadings)
Standard
Error
(SE)
Critical
Ratio
(CR)
Squared
Multiple
Correlation
(SMC)
Construct
Reliability
Cronbach’s
Coefficient
Alpha
Average
Variance
Extracted
(AVE)
Highest
Squared
Correlation
Estimate
Value
Perception
VP3 0.816 x x 0.666
0.891 0.887 0.623 -
VP6 0.767 0.076 13.636 0.589
VP7 0.866 0.070 15.397 0.750
VP8 0.684 0.079 11.535 0.467
VP10 0.801 0.062 13.838 0.642
x – This regression weight was fixed at 1.000, not estimated.
8.3.2 Second Model
Figure 8-7: Second Model
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The second structural model with the remaining 21 items resulted in a better fit with GFI =
0.906, NFI = 0.943, TLI = 0.972, CFI = 0.977, and RMSEA = 0.051. P-value was still = .000
(threshold p ≥ 0.05). However, to further improve model fit, the residuals and modification
indices were probed. The items EX5 (The service employee knew a lot about
services/products), WC4 (The service employee voluntarily assisted me even if it was going
above his/her required tasks), SS4 (I feel satisfied that my needs were achieved), and VP7
(Compare to other financial institutes, the service employee gave me the best value I could get)
were removed due to weak path coefficient, high standardised residual covariance, or
significant change in MIs due to the presence of large cross-loadings.
Table 8-15: Goodness-of-Fit Indices for Structural Model – Second Model
CMIN (χ2) df CMIN/df p GFI NFI TLI CFI RMSEA
286.917 175 1.640 .000 .906 .943 .972 .977 .051
The evidence from Table 8-16 shows the values of AVE, construct reliability, and Cronbach’s
alpha of all the constructs satisfy their respective cut-off values of 0.50, 0.70, and 0.70
respectively, assuring reliability and convergent validity (De Vaus, 2002; Hair et al., 2010).
All scale items had factor loadings above the accepted value of 0.05 confirming convergent
validity (Hair et al., 2010). Also, all the values of AVE of exogenous constructs were well
above those of the highest squared correlation estimates; the discriminant validity was
achieved.
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Table 8-16: Summary of Structural Model – CFA Estimates, Validity and Reliability – Second Model
Construct Item
Code
CFA Estimates Reliability and Validity Measures
Standardised
Regression
Weights
(Factor
Loadings)
Standard
Error
(SE)
Critical
Ratio
(CR)
Squared
Multiple
Correlation
(SMC)
Construct
Reliability
Cronbach’s
Coefficient
Alpha
Average
Variance
Extracted
(AVE)
Highest
Squared
Correlation
Estimate
Expertise
EX1 0.854 x x 0.729
0.857 0.853 0.667 0.318 EX2 0.821 0.062 14.563 0.673
EX5 0.774 0.073 13.150 0.598
Considerate
Manner
CC1 0.931 0.034 29.479 0.868
0.958 0.958 0.884 0.679 CC2 0.941 0.033 30.635 0.886
CC3 0.948 x x 0.899
Rapport
RA1 0.888 0.048 18.499 0.788
0.924 0.917 0.803 0.679 RA3 0.952 0.047 21.180 0.906
RA4 0.846 x x 0.716
Helping
without
Concern
for the
Duty
Boundary
WC1 0.779 0.073 13.240 0.606
0.883 0.882 0.653 0.281
WC2 0.788 0.071 13.248 0.622
WC3 0.807 x x 0.651
WC4 0.857 0.071 14.979 0.735
Service
Satisfaction
SS1 0.882 x x 0.777
0.943 0.936 0.808 -
SS2 0.770 0.062 15.750 0.593
SS3 0.968 0.038 25.823 0.936
SS4 0.961 0.041 25.511 0.924
Value
Perception
VP3 0.785 x x 0.616
0.873 0.867 0.635 -
VP7 0.886 0.078 14.730 0.784
VP8 0.678 0.085 11.018 0.460
VP10 0.824 0.068 13.584 0.678
x – This regression weight was fixed at 1.000, not estimated.
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8.3.3 Third Model
Figure 8-8: Third Model
The third structural model was run with 17 items showing satisfactory model fit indices for all
measures (Table 8-16), GFI = 0.929, NFI = 0.954, TLI = 0.976, CFI = 0.982, and RMSEA =
0.050. Although the p-value was not significant, the value obtained was considered sufficient.
Figure 8-8 and Table 8-18 confirmed the reliability and convergent validity of all the items (De
Vaus, 2002; Hair et al., 2010; Pallant, 2007). Standardised factor loadings for each indicator
were above the ideal threshold of 0.70, indicating convergent validity (Hair et al., 2010).
Additionally, all exogenous constructs clearly showed the existence of discriminant validity as
the values of AVE were greater than those of the highest squared correlation estimates (Hair et
al., 2010).
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Table 8-17: Goodness-of-Fit Indices for Structural Model – Third Model
CMIN (χ2) df CMIN/df p GFI NFI TLI CFI RMSEA
170.068 105 1.620 .000 .929 .954 .976 .982 .050
Finally, no large standardised residual covariance or any heavy modification indices were
present in the AMOS advice text. Since further checks of all possible alternative relationships,
by removing/adding items and/or respecified the model, failed to produce a better model fit
with satisfactory path coefficient values, further modification or re-specification was
considered unnecessary. The overall indices of GOF implied that no further CFA iteration was
necessary and the inputs from the results were ready for testing the hypotheses.
Table 8-18: Summary of Structural Model – CFA Estimates, Validity and Reliability – Third Model
Construct Item
Code
CFA Estimates Reliability and Validity Measures
Standardised
Regression
Weights
(Factor
Loadings)
Standard
Error
(SE)
Critical
Ratio
(CR)
Squared
Multiple
Correlation
(SMC)
Construct
Reliability
Cronbach’s
Coefficient
Alpha
Average
Variance
Extracted
(AVE)
Highest
Squared
Correlation
Estimate
Expertise
EX1 0.853 x x 0.727
0.836 0.835 0.718 0.297
EX2 0.842 0.087 10.714 0.709
Considerate
Manner
CC1 0.930 0.033 29.433 0.864
0.958 0.958 0.884 0.681 CC2 0.941 0.033 30.764 0.885
CC3 0.950 x x 0.902
Rapport
RA1 0.889 0.048 18.555 0.790
0.924 0.917 0.803 0.681 RA3 0.950 0.047 21.145 0.902
RA4 0.847 x x 0.718
x – This regression weight was fixed at 1.000, not estimated.
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Table 8-18: Summary of Structural Model – CFA Estimates, Validity and Reliability – Third Model
(Continued)
Construct Item
Code
CFA Estimates Reliability and Validity Measures
Standardised
Regression
Weights
(Factor
Loadings)
Standard
Error
(SE)
Critical
Ratio
(CR)
Squared
Multiple
Correlation
(SMC)
Construct
Reliability
Cronbach’s
Coefficient
Alpha
Average
Variance
Extracted
(AVE)
Highest
Squared
Correlation
Estimate
Helping
without
Concern
for the
Duty
Boundary
WC1 0.805 0.084 12.168 0.647
0.834 0.833 0.626 0.251 WC2 0.784 0.082 11.758 0.614
WC3 0.784 x x 0.615
Service
Satisfaction
SS1 0.876 x x 0.768
0.908 0.899 0.769 - SS2 0.775 0.063 15.662 0.600
SS3 0.969 0.041 24.249 0.939
Value
Perception
VP3 0.798 x x 0.636
0.810 0.804 0.588 - VP8 0.716 0.093 10.548 0.512
VP10 0.785 0.077 11.220 0.616
x – This regression weight was fixed at 1.000, not estimated.
The correlation matrix of the final indicators of the selected model is presented in Appendix I,
to allow an independent verification (Baumgartner & Homburg, 1996).
8.4 Hypothesis Testing and Discussion
All the hypotheses posited in this thesis have been tested in this section. To test for significance,
every path in the structural equations modelling result was examined on the basis of the critical
ratio (CR), p-value, and standard error (SE). The standard threshold of CR was set at > 1.96
(Arbuckle, 2010; Byrne, 2013) and p-value for accepting a hypothesis were set at the < 0.05
level to allow for a smaller chance of being wrong (Arbuckle, 2010; Byrne, 2013; Hair et al.,
2010),while SE indicates the precision with which a parameter has been evaluated. Although
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there are no definitive criteria of small or large SE value, an extremely large or small value
suggests a poor result (Byrne, 2013).
Figure 8-9: Hypothesised Model Tested
Standardised Parameter Estimate’s outputs are in the square boxes.
The hypothesis results in Figure 8-9 and Table 8-19 present how the constructs of role-
prescribed, beyond role, and helping behaviours affect the dependent variables of customer
satisfaction and value perception. The hypotheses associated with role-prescribed behaviours
reveal that the effect of expertise on customer service satisfaction and value perception appear
to be non-significant, prompting rejection of H1a (CR = 0.459, p-value = 0.646) and H1b (CR
= 0.225, p-value = 0.822).
Two constructs, considerate manner and rapport, of beyond role behaviours have a significant
effect on customer service satisfaction. These results support hypotheses H3a and H6a (CR =
H1a, 0.021
H3a, 0.603
H7b, 0.436
H6b, 0.329
H7a, 0.010
H3b, 0.055
H6a, 0.345
H1b, 0.020
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9.393, and 5.011 respectively, at p-value < 0.001 level). The result further indicates that rapport
also has an influence on customer value perception. This supports hypothesis H6b (CR = 2.618,
at p-value < 0.05 level) However, the effect of considerate manner on customer value
perception is non-significant (CR = 0.479, p-value = 0.632), which prompts the rejection of
hypothesis H3b.
For helping behaviours, the effect of helping without concern for the duty boundary on
customer service satisfaction is non-significant (CR = 0.250, p-value = 0.803), which leads to
rejecting hypothesis H7a. Nevertheless, the impact of helping without concern for the duty
boundary has a significant influence on customer value perception. Therefore, hypothesis H7b
(CR = 5.222, at p-value < 0.001 level) is supported.
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Table 8-19: Regression Weights and Summary of Hypothesis 1a – 7b
Hypotheses Paths
AMOS Output
Results Standardised
Parameter
Estimate
S.E. C.R. P-Value
H1a: Perception of expertise
has a positive effect on
customer service satisfaction.
EX SS 0.021 0.022 0.459 0.646 Not
Supported
H1b: Perception of Expertise
has a positive effect on
customer value perception.
EX VP 0.020 0.083 0.225 0.822 Not
Supported
H3a: Perception of FSE
considerate manner affects
customer service satisfaction
positively.
CC SS 0.603 0.065 9.393 *** Supported
H3b: Perception of FSE
considerate manner affects
customer value perception
positively
CC VP 0.055 0.219 0.479 0.632 Not
Supported
H6a: Perceived rapport
affects customer service
satisfaction positively.
RA SS 0.345 0.052 5.011 *** Supported
H6b: Perceived rapport
affects customer value
perception positively. RA VP 0.329 0.181 2.618 0.009** Supported
H7a: Helping without
concern for the duty
boundary has a positive
effect on service satisfaction.
WC SS 0.010 0.016 0.250 0.803 Not
Supported
H7b: Helping without
concern for the duty
boundary has a positive
effect on value perception.
WC VP 0.436 0.063 5.222 *** Supported
*** indicates p-value at the significance level of p < 0.001; ** indicates p-value at the significance level of p < 0.05.
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8.5 Chapter Summary
This chapter detailed the results of the quantitative research for this thesis. In section one, six
constructs of FSEs’ service-role behaviours were tested with CFA to investigate reliability and
validity. Next, the CFA models, including all variables, were investigated for reliability and
validity. The CFA models comprised six independent variables, which are two constructs of
role-prescribed, three of beyond role, and one of helping behaviours, and two dependent
variables, which are customer service satisfaction and value perception. The personal-
involvement expression (PE) construct was removed from the analysis in a structural model
due to the failure of discriminant validity and high correlations with considerate manner (CC)
and service satisfaction (SS). Section two determined the basic principles of testing structural
theory, including model specification, model identification, and model validity. In section three
the structural models were presented in three stages of modification. These included the
evaluations of causal relationships between independent and dependent variables in multiple
regression analysis. The third model showed that the overall indices of GOF, the reliability,
convergent validity, and discriminant validity were all achieved and implied that further CFA
iteration was unnecessary. The last section demonstrated all the hypotheses posited in this
thesis. The results showed that the considerate manner and rapport constructs have an effect
on customer service satisfaction, supporting hypotheses H3a and H6a. Both rapport and
helping with concern for the duty boundary constructs affect customer value perception,
supporting hypotheses H6b and H7b. Finally, expertise does not have any significance on either
customer service satisfaction or value perception, so leading to the rejection of H1a and H1b.
The next chapter is devoted to the discussion, interpretation, and conclusion of the research
results and findings. The theoretical and managerial implications are also discussed, as well as
the limitations and directions for future research.
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CHAPTER 9
DISCUSSION AND CONCLUSION
The research in this thesis focused on customer perceptions towards the role behaviours of
frontline service employees. Both qualitative and quantitative research was conducted to draw
attention to all of the factors that may explain distinctions between the causes and reasons for
FSEs’ role behaviours and how customers might perceive them. A three-category classification
of service-role behaviours was uncovered. The categorisation is theoretically parsimonious in
accounting for the roles of the firm, FSEs, and also the customer in a service encounter, and so
is useful for management. This final chapter begins with the main findings and conclusions of
this thesis, set out according to the three-way categorisation of FSE role behaviours. Next is a
discussion of the theoretical contributions of this thesis towards the academic literature. This
is followed by a discussion of managerial implications. A final section includes the limitations
of the study, along with possible future research directions.
9.1 Summary of Findings
The findings of the research presented in Chapter 8 are discussed in accordance with the second
research question: How do customer perceptions of FSE role behaviours effect their service
satisfaction and value? The findings are summarised in the paragraphs below, according to a
three-way FSE role classification:
9.1.1 Role-Prescribed Behaviours
The research attests to a non-significant effect of the FSEs’ expertise on customer service
satisfaction (H1a) and value perception (H1b). The results of the SEM investigation show that
there were no significant effects between expertise and these two dependent variables. Since
FSE expertise is logically necessary for customers to gain service satisfaction and a value
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perception, this result suggests that a required level of expertise is met. Thus, expertise seems
to play a hygiene part in the customer’s perception of FSE role behaviour; it is necessary and
required to gain satisfaction and value, but also does not have a direct effect.
Interestingly, the knowledge about product/service, accurate information provision, quick and
prompt service, and the organisation of FSEs did not affect customer satisfaction and value
perception in this context. This contrasts with the previous studies of expertise on customer
satisfaction by Alexandris, Zahariadis, Tsorbatzoudis, and Grouios (2004), Shanka (2012), and
Ramasubbu, Mithas, and Krishnan (2008).
There are a number of likely reasons why the findings of this thesis differed from the previous
literature. This thesis tested the direct effect of expertise of FSEs on customer service
satisfaction and value perception, and in a fast service encounter context. By contrast
Alexandris et al. (2004) tested the customer perception on the employee’s service quality in a
private health club. They found only one expertise item, of the six tested (i.e. influence of
interaction quality), that effected weakly customer satisfaction. They stated that this issue
needed further investigation.
The study by Shanka (2012) examined the quality of service offered by private banks operating
in Ethiopia. In that study, assurance, a component of expertise, had a positive impact on overall
customer satisfaction. However, in that study, assurance measured the level of courtesy in
addition to the knowledge or skill of an employee. Thus, Shanka’s study confounds the
measurement of expertise.
Ramasubbu et al. (2008) investigated customer satisfaction of the employees who used the
system support services of IT firms. They found that the technical skills or knowledge of
customer support representatives played a major role influencing overall customer satisfaction.
Nevertheless, technical skills contributed to improved customer satisfaction only when they
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were coupled with a high degree of behavioural skills or courtesy. This result is intuitively
correct in the context of the IT service sector where employee knowledge, skill, and experience
are perceived as the main resource which makes the most crucial contribution to a firm’s
success. Evidently, the service context is important in explaining how expertise perceived by a
customer affects service quality and value perception. In the case of bank transactions, which
vary in length from a few minutes to up to twenty minutes, expertise was not found to be
significant in explaining customer satisfaction or value perception. The results of the study in
this thesis point to expertise being a hygiene factor, necessary but not significant.
Ramasubbu et al. (2008) found that for repeat customers, the expertise of the employees was
valued and not valued for new customers. This means that the customer value perception
towards expertise of FSEs may mostly occur in the situation of loyal customers.
The lack of a significant finding for expertise in the bank transaction situation with a FSE might
also be explained by the mediating role of computer and software technology. Customers may
perceive the FSE role as a fairly straightforward one, where the level of expertise required is
not so great. Thus, the context of the service encounter and the number of repeating encounters
likely are important variables in future research.
9.1.2 Beyond Role Behaviours
9.1.2.1 Considerate manner
The quantitative study found a significant effect of considerate manner on customer service
satisfaction (H3a). Considering the size of the construct reliability and p-value, this result
suggests that considerate manner has a strong positive effect on service satisfaction. This
finding shows that customers are satisfied when FSEs treat customers with respect; are kind,
courteous, sincere, and polite; and have a good manner and a considerate attitude towards
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customers. This is consistent with many authors, such as Frazer Winsted (2000), Kong and
Jogaratnam (2007), Liao (2007), Ramasubbu et al. (2008), and Zaim et al. (2010).
However, contrary to expectation, considerate manner had no significant effect on customer
value perception (H3b). Even though very little empirical research has examined the direct
effect of considerate manner or courtesy on customer value perception, previous studies state
that customers value the courtesy of FESs (Bell & Menguc, 2002; Walker, 2001). According
to Gruber (2011), the considerate manner is one of the attributes that play a key role in creating
customer perception of service quality (Bell & Menguc, 2002; Walker, 2001) and evaluating
personal services. Gruber, Szmigin, and Voss (2009) add that when the customers are being
friendly, courteous, and respectful to the FSEs, customers also expect mutual courtesy and
respect in a believable way from employees. This might help explain why customers do not
perceive value from service encounters in a bank transaction. Customers only gain a perception
of value when FSE considerate manner is extraordinary, and in all other cases is simply
expected.
9.1.2.2 Rapport
In this thesis, rapport was the only independent variable which affected both dependent
variables, service satisfaction and value perception, so supporting H6a and H6b. Similar to
previous studies (i.e. Guenzi & Pelloni, 2004; Hennig-Thurau et al., 2006; Macintosh, 2009;
Price & Arnould, 1999; Reynolds & Beatty, 1999; Schakett, Flaschner, Gao, & El-Ansary,
2011), H6a supports the finding that the FSE-to-customer rapport positively affects the service
satisfaction of the clients. Further, the rapport between FSEs and customers also has an impact
on value perception, but the effect is smaller than customer satisfaction. The study of Wafaa
and Abderrezzak (2014) has a similar finding. These authors also found that the rapport
between employees and customers had a positive indirect effect on customer satisfaction.
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However, in their study, the rapport has a positive effect on customer satisfaction through the
perceived value. This indirect effect was not hypothesised in the thesis study, but in analysing
the data, no such association was found. A study by Reynolds and Beatty (1999) did not
examine the effect of rapport on value perception, but they stated that rapport provides benefits
and value to customers, leading to satisfaction, loyalty, word of mouth, and share of purchases.
Thus, the results of the study in this thesis imply that rapport helps to build a long-term
relationship tying FSEs with the customers by providing them with both satisfaction and value.
9.1.3 Helping Behaviours
Surprisingly, the finding indicates that helping without concern for the duty boundary had no
significant effect on customer service satisfaction, leading to rejection of H7a. The finding is
contrary to the study of Maxham III and Netemeyer (2003). However, the study of Maxham
III and Netemeyer focused on the customers who registered telephone complaints about the
electronic products they purchased. Customers already had a negative experience from the
product failure (Petzer, Mostert, & Fourie, 2014). According to Maxham III and Netemeyer
(2003), when the employees perform a helping behaviour to recover a complaint, the customers
feel as if they perceive justice. This implies that customers may perceive a type of value.
The thesis study supports that customers perceiving helping without concern for the duty
boundary gained a value perception, so supporting H7b. These findings suggest that providing
service directed at solving a customer’s issues, so providing a ‘little extra’, leads to value
perception. That helping without concern for the duty boundary affects value perception and
not customer satisfaction in an intriguing result to be discussed further in the next section.
9.2 Theoretical Implications
This section outlines the contributions to theory made in undertaking both the qualitative and
quantitative studies.
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First, the research presented in this thesis suggests a need to reclassify the service-role
behaviours of FSEs. Both in-role and extra-role behaviours have received much academic
attention, especially in managerial perspectives. However, there are very few studies that focus
on the boundary between these two behaviours (Lai, Lam, & Lam, 2013). According to
Yoshikawa and Hu (2015), the distinctions between the two behaviours are comparatively
difficult to draw. Both employees and managers find them hard to recognise (Podsakoff et al.,
2000), and their definitions are still inconsistent, unclear, and overlapping (Morrison, 1994).
Lai et al. (2013) add that extra-role behaviours have been perceived variously across situations,
which causes an unclear perception of the expected behaviours.
Van Dyne and LePine (1998) state that differentiating in- and extra-role behaviours is
important for both academic and managerial contributions. Several studies (e.g. Kamdar,
McAllister, & Turban, 2006; Morrison, 1994; Tepper, Lockhart, & Hoobler, 2001; Wu, Tang,
Dong, & Liu, 2015) add that role definition directly influences the attitudes and motivation of
extra-role behaviours. Therefore, this thesis has aimed to redefine the terms of both behaviours,
especially those outside of the in-role.
The first part of the thesis was a qualitative study. This qualitative study emphasised how FSEs
consider regulations, and what factors drive them to perform role behaviours. The qualitative
evidence revealed seven elements of FSEs’ service-role behaviours; expertise, job requirement,
considerate manner, personal-involvement expression, empathy, rapport, and helping without
concern for duty. The themes expertise and job requirement are evidently presented as the in-
roles required by the firm. To note that these roles are firm directed they are termed as role-
prescribed behaviours.
The themes considerate manner, personal-involvement expression, empathy, and rapport are
more about how FSEs express their personal feelings/attitudes and involvement towards the
formal tasks, themselves, and the customers. These four themes do not appear to be an extra-
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role as the FSEs still perform their roles within the required tasks. Rather these themes are
related to how the FSE interprets and define themselves as they perform their prescribed role
within a service encounter. The service encounter becomes effectively the place where the
FSEs express themselves, and this is not classified as extra roles. Therefore, these four themes
are categorised and termed as beyond role behaviours.
The last theme, helping without concern for the duty boundary, shows that this role is an
alternative performance that the FSEs might undertake apart from their formal job requirement.
This theme focuses on the customer’s needs and is not an extra-role from the firm’s perspective.
Instead this role may even be counter to the requirements of the firm, and so is described, to
note the focus on the customer, as a helping role.
This classification of roles moves away from a simple firm view of the service encounter, to
classify the FSEs’ service-role behaviours into three categories, not just two: (i) Role-
prescribed behaviours are determined by a firm. FSEs undertake role-prescribed behaviours
under the written scripts for maximising the benefits of a firm and meeting their customers’
expectations within the duty boundary. (ii) Beyond role behaviours are when the FSEs not only
act the required role, but they also present themselves and their personality in the service
encounter. For the FSEs, the beyond role behaviour is about themselves as an individual
different from any others, and so their personality and life being is brought forward in the
encounter. (iii) For helping behaviours, FSEs act this role in their own way and alter their
behaviours according to the reactions and feedback they receive in order to help the customers
during the service encounter. The reasons and motivations of performing a helping role may
arrive from the FSEs’ altruism, themselves, their characteristics, or a moral responsibility
within the firm. These three behaviours show that FSEs represent two actors, being the
representatives of a firm (Bettencourt & Gwinner, 1996) and representing themselves, but also
focusing on their customers as well as their firm. Thus, the service encounter acts as a boundary
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between the FSE and their firm (see Figure 9-1). The time and space of the service encounter
stands apart from the firm to some extent, so that the FSE might perform three categories of
roles.
Figure 9-1: Relationships of Service-Role Behaviours of FSEs to Customers and the Firm
Second, this thesis also presents a quantitative study that contributes to the theoretical
foundation of service-role behaviour studies and that confirms the qualitative findings and three
hypotheses. To investigate the overlapping conceptual definitions of the different forms of in-
role and extra-role behaviours, Podsakoff et al. (2000) suggested a future study test rigorously
on the discriminant validity of the constructs and their measures. This thesis has provided the
evidence that the measures of each construct of all service-role behaviours are reliable and
valid, and they are also distinct from measures of closely related constructs.
Further, the majority of previous literature has focused on the FSE role behaviours only from
the perspectives of the employee, supervisor, and/or firm (e.g. Eldor & Harpaz, 2016;
MacKenzie et al., 1998; Van Dyne & LePine, 1998; Williams & Anderson, 1991; Yavas et al.,
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2013). According to Anderson and Williams (1996) and Turnipseed and Wilson (2009), this
may be the reason why the boundary between in-role and extra-role behaviours appeared to be
poorly defined and varied among researchers. To the best of the researcher’s knowledge, this
thesis is the first to examine the perceptions of the service-role behaviours of FSEs from the
customer’s side and to see how that performance affects clients’ service satisfaction and value
perceptions. The seven constructs from the qualitative themes were operationalised by
selecting and adapting measurement scale items and scale types from previous studies (e.g.
Ackfeldt & Wong, 2006; Dabholkar et al., 1996; Dagger et al., 2007; Gil et al., 2008; Gremler
& Gwinner, 2000; Stock & Hoyer, 2005; Tsaur & Lin, 2004). The constructs were examined
to see how they affected customer service satisfaction and value perception.
Third, the quantitative results provide empirical evidence about how customers perceive FSEs’
service-role behaviours. None of the constructs of role-prescribed behaviours, expertise and
job requirement, affect the independent variables. The explanations of the role-prescribed
behaviours’ findings may be delineated by the Herzberg’s Motivator and Hygiene Factor
Theory (Herzberg, 1966). Herzberg proposes two distinct sets of factors for satisfaction:
satisfiers or motivators, and dissatisfiers or hygiene factors (Chan & Baum, 2007). One set,
satisfier or motivators, causes satisfaction when they are sufficiently fulfilled. In contrast, the
other set, dissatisfiers or hygiene factors, contribute dissatisfaction when there is an absence
(DeShields Jr, Kara, & Kaynak, 2005). According to Rust, Stewart, Miller, and Pielack (1996),
satisfaction is not opposite to dissatisfaction. The opposite of satisfaction is no-satisfaction, not
dissatisfaction (Pizam & Ellis, 1999). And the opposite of dissatisfaction is no-dissatisfaction,
not satisfaction. The present results for role-prescribed behaviours suggest that the use of a
scale from satisfaction to dissatisfaction might be suspect. Further research should examine
this issue.
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In applying Herzberg’s theory to this thesis, the perception of customers is that role-prescribed
behaviours are the normal, expected and required service provision. The absence of role-
prescribed behaviours may cause customer dissatisfaction.
The most interesting theoretical result from the thesis is that beyond role and helping
behaviours have a different impact, with the former effecting customer satisfaction and the later
having an effect on customer value perception in the context of a bank service encounter. That
beyond role behaviours affect perceptions of satisfaction indicates that customers feel that the
service encounter is conducted to a reasonable conclusion when the FSE behaves in a
considerate manner and with rapport. That is, the service encounter is completed in a
satisfactory manner because of the personal attention given by the FSE to completing a
prescribed role. Thus, the hygiene factor of the prescribed role is activated as a result of the
FSEs beyond role behaviours.
On the other hand, value perception follows helping behaviour, which focuses on the
customer’s needs and not those of either the firm or the FSE. But helping behaviour also
requires role-prescribed behaviour to be met. Thus, the hygiene factor of role-prescribed
behaviour is lifted by helping behaviour to provide a value perception.
The confounding issue in this interpretation of the quantitative results is that rapport, a beyond
role behaviour, also has an effect on customer value perception. This suggests that rapport
holds an interesting theoretical position as a bridging behaviour, which is not only a result of
the FSEs actions and emotions, but is also a customer connected behaviour. This makes
theoretical sense given that rapport is focused from the FSE towards the feeling and emotions
of the customer (Wacker, 1998). Thus, customers are the ones gaining from the FSEs’ actions
and this might provide an explanation of the effect on perceived value.
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The helping without concern for the duty boundary construct of helping behaviours surprisingly
has an effect only on value perception. There is no clear explanation of why helping behaviours
do not affect customer service satisfaction right now. However, the effect of helping behaviours
on customer value perception is explained by the FSE’s discretionary or voluntary acts being
above customer expectations. Additionally, the effect of rapport is relatively smaller than that
of helping without concern for the duty boundary. These results may imply that the little extra
service is more valuable than the relationships the customer has with either the bank or the
FSEs. But according to the helping role definition, that extra service needs to focus on the
customer’s needs, rather than the FSEs motivation to present themselves within a banking
service encounter.
Finally, in the relationship marketing paradigm, satisfaction has been found to have a strong
positive effect on long-term relationships and customer retention (Ranaweera & Prabhu,
2003a). Customer satisfaction is also one of the most important criteria for customer loyalty
(Heskett & Schlesinger, 1994). Further, customer value perception is suggested to lead to
customer loyalty (Deng, Lu, Wei, & Zhang, 2010). While role-prescribed behaviours do not
impact either customer service satisfaction or value perception, they are logically required.
Thus, since the role-prescribed behaviours of bank FSEs may not create long-term
relationships, build customer retention, or keep a customer’s loyalty, the beyond and helping
roles of FSEs have far greater importance.
9.3 Managerial Implications
The sample respondents were selected from amongst the customers in a single branch of a
financial service firm in South Australia. Thus, the results may not be generalizable in other
settings. For other industries, future studies are necessary.
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This current study has important managerial implications especially for the management of the
FSEs. In past research both value perception and service satisfaction have positively associated
with repurchase, customer retention, and word-of-mouth intentions (Hartline & Jones, 1996;
Molinari, Abratt, & Dion, 2008; Ranaweera & Prabhu, 2003b). But the present study suggests
that role-prescribed behaviour, while necessary, does not affect value perception or customer
satisfaction. Further, value perception is affected by helping behaviours, which do not affect
customer satisfaction. However, beyond role behaviours have different effects; considerate
manner affects customer service satisfaction, while rapport affects both satisfaction and value
perception. Since both satisfaction and value perception increase customer loyalty/retention
and so impact profits (Levesque & McDougall, 1996), the results present interesting
managerial implications. The thesis findings can be used as valuable inputs in developing the
bank’s future service policies. According to Wallace et al. (2011) and Levesque and
McDougall (1996) customers perceive little distinction when comparing the offerings and
services provided by other financial institutions. The following starting points are suggested
for managerial implications.
9.3.1 Focusing on Good Training
Importantly, a manager should inform and encourage FSEs to meet or exceed the expectations
of customers in order to avoid the trap of meeting only hygiene factors. Moreover, a manager
should also provide suitable training to help the FSEs provide more efficient services to
customers. Management of customer expectations (Barnes et al., 2013), socialisation (Hartline
& Jones, 1996), and behavioural and emotional practices (Lemmink & Mattsson, 2002) are
examples of training that may enhance and bring out the capabilities of FSEs. Especially
important is emotional training, and managers should emphasise the important of a ‘human
touch (Wallace et al., 2011: p. 47)’ within the FSE-customer encounter.
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9.3.2 Empowering FSEs with the Discretionary Independence
Manager should consider loosening the rigid regulations and job descriptions (Chan & Wan,
2012) and give more control to the FSEs (Barnes et al., 2013). Hence, they can shape the service
interaction and provide a customised experience to a specific customer. During the service
encounter, FSEs should be allowed to have the discretionary independence to satisfy and create
service value to the customers. They should be empowered to make their own decisions, go off
script (Barnes et al., 2013), and be able to enact helping behaviours. According to Barnes et al.
(2013), giving the FSEs the discretionary independence to satisfy customers helps to establish
happiness among customers, and creates a feeling of accomplishment with their (the
employees’) performance.
9.3.3 Recruiting Genuine FSEs
Providing behavioural and emotional training to FSEs may have limits. Customers can sense a
fake display of emotions from FSEs (Groth, Hennig-Thurau, & Walsh, 2009). Thus, firms
should hire individuals with a helping mentality (Beatty et al., 2015) who are intrinsically
willing to help customers and present positive and genuine emotions (Gruber, 2011). People
who have interpersonal skills usually have considerate-manners such as friendliness, sincerity,
respectfulness, courtesy, and listening skills (Gruber, 2011). Individuals who have listening
skill have the abilities of sensing to both verbal and non-verbal cues, processing the mind and
meaning of others’ messages, and responding the correct information back to the speakers
(Comer & Drollinger, 1999). However, listening skills can be trained after recruiting (De
Ruyter & Wetzels, 2000).
9.3.4 Reviewing and Developing Policies and Infrastructure
The employer or manager should give precedence to the FSEs’ emotional labour during the
service encounter (Liu et al., 2013). Helping behaviours should not be hindered by strict
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policies. The definition of helping behaviours to focus on the customer’s needs, rather than the
FSEs motivation to present themselves (beyond role behaviours) should be specified in the
customer service policies of the firm. FSEs who perform helping behaviours that are valued by
customers should be acknowledged and rewarded by the firm (Bettencourt & Brown, 1997).
Also, an appropriate infrastructure should be developed and updated to ensure that the FSEs
can meet or exceed customer expectations. Barnes et al. (2013) suggest feedback and
compensation systems for the administration. In this case, these two systems may help to
indicate the customer expectations and directly connect these to customer service satisfaction
and value perceptions. Consequently, managers can allocate resources according to where they
are needed (Levesque & McDougall, 1996). Furthermore, managers should also provide
adequate staff members (Avkiran, 1999) in order to minimise the tension of customer traffic
during busy hours and the ability of staff to exhibit beyond role and helping behaviours. An
empirical study of Houston, Bettencourt, and Wenger (1998) indicated a strong negative effect
of waiting time on customer evaluations of the quality of a service. However, where there is a
shortage of staff members, the manager or supervisor may temporality assume the role of the
employees to fulfil arising service requests. In this case, the negative feeling of waiting time
could be alleviated.
9.4 Limitation and Future Research Directions
There are a number of limitations to the study presented here that may provide numerous
opportunities for further research on FSEs’ service-role behaviours.
First, the main study was conducted in one branch of a financial firm. A comparison of the
results presented here with other financial firms would be useful. There are different types of
financial firms in Australia such as retail banks, customer-owned banking association, and
foreign banks. Each type of financial firm would have different managerial styles, policies, and
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regulations of how to treat or approach customers. Hence, the findings of the study based only
on the responses of a sample in one banking firm are unlikely to represent the Australia banking
industry. Comparing the customer perceptions towards FSEs’ role behaviours from different
types of financial firms in further research would be worthwhile.
Second, the sample of the main study was collected from service encounters in a banking firm,
which is a limitation of the study. The service encounters are often routinized and occur
quickly, but may also be up to twenty minutes of a long and complicated procedure. Other
service encounters, for example restaurants, hotels, hospitals, airlines, retail outlets, or public
sector offices present completely different patterns of behaviour. Therefore, a broader test of
the model and the results are required. Replicating this thesis in other service organisations
would be valuable for future research, which would improve understanding of the conceptual
boundaries between these three service-role behaviours.
Third, the study uses a non-probability sampling procedure and a relatively small sample.
Accordingly, future research should consider using a probability sampling design with a larger
sample size.
Fourth, the measurement scale items operationalised in this thesis are selected and adapted
from different literature to complement this research. However, the selected scales were
prepared in past studies for evaluating employee’s performance. Even though the items were
adapted with appropriate linguistic style to reflect the situation of a service encounter between
FESs and customers, further research might develop scales specifically for a customer’s
perspective of a service encounter.
Fifth, several of the measurement items demonstrated non-normality. While this was
considered to be within acceptable levels due to the sample size of 250 (Hair et al., 2010), other
statistical approaches and/or standardisation of the response levels could have been conducted.
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Sixth, according to the finding of this thesis, rapport has a significant effect with customer
value perception. The reasons behind this result are not certainly clear. Future research could
investigate the effect of rapport on perceived value.
Seventh, this thesis does not distinguish FSE-customer service encounter in terms of frequency
(Hartline & Jones, 1996), time duration (Price et al., 1995b), busy or crowded environment
(Price, Arnould, & Deibler, 1995a; Pugh, 2001), and complexity of interactions (Surprenant &
Solomon, 1987). These factors may moderate the effect of FSEs’ emotion, behaviour, and
performance on customers’ satisfaction and value perception. Thus, future research studies
might include these dimensions along with the constructs measured in this thesis to thoroughly
examine the moderators responsible for the development of customer service satisfaction and
value perception.
Finally, this thesis measured only the perception of customers towards FSEs’ role-prescribed,
beyond role, and helping behaviours. Future research might compare both the FSE and
customer perceptions of the three role behaviours within the single service encounter. Such a
study would determine if FSE and customer have at least partly the same interpretation of a
specific service encounter. The present study does not consider the issue of similarity of
perception for the FSE behaviour by the employee and the customer. The degree to which
perceptions are equivalent has managerial implications.
9.5 Conclusion and Overall Contributions
This thesis centres on redefining and clarifying the definitions of service-role behaviours, and
especially extra-role behaviours which have received considerable criticism (Cohen & Kol,
2004; Vigoda, 2000). In previous studies, both in-role and extra-role behaviours have been
focused on the employees’ and supervisors’ side in order to improve their performance to meet
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the firm’s interests. Very few studies in this context explore the customers’ side of FSE role
behaviours.
Both qualitative and quantitative studies were conducted in this thesis. Qualitative
methodology was employed to examine how FSEs saw their role towards customers, rather
than seeing the role as only a part of the firm’s function. The findings revealed that there is a
three-category classification of service-role behaviours; role-prescribed, beyond role, and
helping behaviours. FSEs carry out role-prescribed behaviours to meet the formal role
requirement of the firms and customers. In contrast, beyond role behaviours involve the FSEs’
feelings and attitude expression towards their roles, jobs, themselves, and customers. Finally
helping behaviours are the performance of tasks for customers that are outside the job
descriptions required by the firm.
The quantitative study was conducted to examine how a sample of customers perceive the
FSEs’ three-category classification of service-role behaviours and how that effects satisfaction
and value perception. The results show that the considerate manner construct of beyond role
positively affects customer satisfaction. And the rapport, another construct of beyond role,
positively impacts both service satisfaction and value perception. The helping behaviours
positively affect value perception. However, the role-prescribed has no effect on either
dependent variable. This suggests that the beyond and helping roles of FSEs are of importance
in creating long-term relationships, building customer retention, or keeping a customer’s
loyalty, at least in a banking context.
The qualitative and quantitative studies lead to the development and definitions of the three-
category classification of service-role behaviours. The overall contribution of this thesis is
summarised in Table 9-1. The table comprises three parts; theoretical contribution, contribution
towards the body of knowledge, and contribution to practice.
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Table 9-1: Overall Contributions of the Study
Contribution
Originally
Proposed/Related
Studies
Comments
A. Theoretical Contribution
Three-Category
Classification of
Service-Role
Behaviours
Brief and Motowidlo
(1986); Bettencourt and
Brown (1997); Chan
and Wan (2012)
Previous literature has categorised employees’
role behaviours into two groups: in-role and extra-
role (Maxham III et al., 2008; Netemeyer &
Maxham III, 2007) and has focused on the
employees’ performance in meeting the firm’s
outcomes. By contrast, the study presented in this
thesis focuses on the role behaviours of FSEs
towards customers. The findings reveal a three-
category classification of service-role behaviours:
role-prescribed, beyond role, and helping role.
Beyond Role
Behaviours
Zaim et al. (2010);
Graves et al. (2012);
(Sok et al., 2016);
Batson (1987); Gremler
and Gwinner (2000)
For the first time in role behaviour studies, this
thesis found a three-category classification of
service-role behaviours. The role-prescribed
behaviours are the formal role required by the
firm and meet the definition of in-role behaviours
found in the literature. The beyond role
behaviours are the role that FSEs express their
attitude and feelings towards their jobs,
themselves, and a customer. The helping
behaviours are the performance of tasks for
customers that are outside of the formal tasks.
The Boundary of FSEs’
Role Behaviours
Morrison (1994);
Podsakoff et al. (2000)
Several studies found that the boundary of in-role
and extra-role behaviours was poorly defined and
varied (Griffin et al., 2008). This thesis has
redefined the terms of both behaviours, especially
those outside of the in-role behaviours.
The Development and
Definitions of a Three-
Category Classification
of Service-Role
Behaviours.
Raub and Robert (2010) This thesis has developed the definitions of a
three-category classification of service-role
behaviours: (i) Role-prescribed behaviours are the
required performance that the FSEs provide
service to meet customer basic need(s) and query
within their duty statement; (ii) Beyond role
behaviour are when the FSEs have a personal
positive feeling and attitude towards their job and
customers for the employee self-reward and
satisfaction; and (iii) Helping behaviours are when
FSEs volunteer to help customers outside of their
duty boundary.
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Table 9.1: Overall Contributions of the Study (Continued)
Contribution
Originally
Proposed/Related
Studies
Comments
B. Contribution towards the Body of Knowledge
Categorisation of
Constructs
Parasuraman et al.
(1988); Batson (1987);
Gremler and Gwinner
(2000)
For the first time, categorisation of some
constructs has been applied in FSEs’ service-role
behaviours, i.e. considerate manner, personal-
involvement expression, empathy, and rapport.
Customer Perceptions
towards Service-Role
Behaviours
Lin and Hsieh (2011);
Netemeyer and
Maxham III (2007);
Zaim et al. (2010);
Graves et al. (2012);
Sok et al. (2016);
Batson (1987); Gremler
and Gwinner (2000);
Bar-Tal (1982)
For the first time, the study proposes seven
constructs which reflect a three-category
classification of service-role behaviours to
examine how they affect customer satisfaction and
value perception. The findings show that the
helping behaviours affect value perception. The
considerate manner construct of beyond role
behaviours impacts on customer service
satisfaction. Interestingly, rapport, which affects
both satisfaction and value perception, acts as a
bridging behaviour that links the FSEs actions and
emotions to customer perception.
C. Contribution to Practice
Specifying the
Definition of Helping
Behaviours into the
Customer Service
Policies
Yap et al. (2009);
Nguyen, Groth, Walsh,
and Hennig‐Thurau
(2014); Yavas et al.
(2013)
Previous studies focused on extra-role behaviours
in order to encourage employees to perform better
in meeting the firms’ outcomes. This thesis
attempts to provide clear definitions of FSEs’
helping behaviours towards customers.
-242-
-243-
APPENDIX A: PREVIOUS STUDIES OF IN-ROLE AND EXTRA-ROLE BEHAVIOURS
Table A1: Previous Studies of In-Role and Extra-Role Behaviours
Previous
Studies
Area of
Study
Independent
Variable(s) Mediator(s) Dependent Variable(s) Findings
Maxham III
et al. (2008) Retail sector
Job perceptions
(conscientiousness,
perceived
organizational
justice, and
organizational
identification)
Job
performances
(in-role
performance,
extra-role
performance
toward customer,
and extra-role
performance
toward the
organisation),
customer
evaluation
Retail store performance
(comparable store sales
growth, average customer
transaction value)
Three job perceptions have interactive effects on three
dimensions of job performance. These performance
dimensions exert influence on customer evaluations of
the retailer. Also, employee’s job perceptions exert a
direct effect on customer evaluations. These customer
evaluations impact retail store performance.
Sosik et al.
(2011)
Business
sector
Moral development,
management level
(lower and upper
echelon)
N/A
Charismatic leadership,
in-role job performance,
extra-role job
performance
Their study reveals that upper-echelon managers
displayed higher levels of charismatic leadership and
extra-role performance than lower ones.
Yap et al.
(2009) Retail sector
Reward programs
(individual and
group financial
incentives)
N/A In-role behaviour, extra-
role behaviour
They found that reward programs motivated sales
associates to engage in both in-role and extra-role
behaviours.
Yavas et al.
(2013)
Banking
sector
Burnout
(disengagement,
exhaustion)
Hope (as a
moderator)
In-role performance,
extra-role performance
Burnout has significant relationships to frontline
employees’ in-role and extra-role performance and also
hope moderates these associations.
-244-
-245-
APPENDIX B: MAIN STUDY QUESTIONNAIRE
Thank you for the agreement to participate in this questionnaire.
The following survey will ask you questions about the service you received from the service
employee(s). We invite you to complete the survey, remembering that your participation is voluntary
and that you can withdraw from the study at any time. It should take you no longer than ten minutes to
complete. Please answer the questions honestly; we follow your thoughts and opinions. There are no
right or wrong answers.
Your input will help a Marketing PhD student from the University of Adelaide in her study. This survey
is undertaken by Phiangdao Chaoluck. Any questions pertaining to this study can be directed to
Your name will not be requested at all during this study, and therefore your responses can in no way be
traced back to you. The information obtained is for the purpose of helping to improve service providers’
service roles and service quality. Human research ethics committee approval number: H-2015-134.
You can read more details about this study from the Participant Information sheet. Any concerns about
the conduct of this study should be directed to Dr. Chris Medlin’s or Dr. Jodie Conduit’s emails
[email protected], or [email protected]. Or contact the Human Research
Ethics Committee’s Secretariat on phone +61 8 8313 6028 or by email to [email protected].
-246-
Direction: The following sets of statements require you to think about the recent service
encounters that you just had with the service employees. Please select the answers that
match the service behaviours of the service employee whom you have just interacted with.
There are no right or wrong answers—all we are interested in is the behaviour that best
shows your perceptions about employee’s service role. Please answer all questions even if
some appeared similar or abstract.
Are you 18 years old and over?
Yes
No
Description
Str
on
gly
Dis
agre
e
1
2
3
4
5
6
7
8
9
10
Str
on
gly
Agre
e 11
The service employee had the
knowledge about product/service
to answer my questions.
The service employee provided
accurate information during the
service encounter.
During the service encounter, the
service employee provided quick
and prompt service.
The service employee knew a lot
about services/products.
-247-
Description
Str
on
gly
Dis
agre
e
1
2
3
4
5
6
7
8
9
10
Str
on
gly
Agre
e 11
The service employee completed
his/her required service tasks.
The service employee performed
all the tasks that were required by
me.
The service employee completed all
expected customer-service tasks.
The service employee completed all
those things which were required
by me.
Description
Str
on
gly
Dis
agre
e
1
2
3
4
5
6
7
8
9
10
Str
on
gly
Agre
e 11
The service employee treated me
with respect.
The service employee was kind and
polite to me.
The service employee was
courteous and sincere to me.
The service employee had good
manners and a kind attitude.
-248-
Description
Str
on
gly
Dis
agre
e
1
2
3
4
5
6
7
8
9
10
Str
on
gly
Agre
e 11
The service employee looked happy
during the interaction.
During the interaction, the service
employee took pride in providing
courteous service.
The service employee was
personally involved in his/her job.
The service employee looked
satisfied in his/her job.
Description
Str
on
gly
Dis
agre
e
1
2
3
4
5
6
7
8
9
10
Str
on
gly
Agre
e 11
I enjoyed interacting with the
service employee.
The service employee related well
with me.
I was comfortable interacting with
the service employee.
I have a close relationship with the
service employee.
-249-
Description
Str
on
gly
Dis
agre
e
1
2
3
4
5
6
7
8
9
10
Str
on
gly
Agre
e 11
The service employee helped me
solve my problem/request even
when it was personally
inconvenient.
The service employee went above
what was normally expected in
order to help me.
The service employee helped me
even when it was not part of
his/her jobs.
The service employee voluntarily
assisted me even if it was going
above his/her required tasks.
Description
Str
on
gly
Dis
agre
e
1
2
3
4
5
6
7
8
9
10
Str
on
gly
Agre
e 11
My feelings towards the service
employee were very positive.
I feel good about the service of this
place.
Overall, I am satisfied with the
service s/he provided.
I feel satisfied that my needs were
achieved.
-250-
Description
Str
on
gly
Dis
agre
e
1
2
3
4
5
6
7
8
9
10
Str
on
gly
Agre
e 11
Compared to other financial
institutes, the service employee has
shown interest in my
enquiries/problems.
Compared to other financial
institutes, the service employee
solved my problems.
Compared to other financial
institutes, the service employee
gave me the best value I could get.
Compared to other financial
institutes, the service employee
delivered good quality for what I
gave up in order to get this service.
Compared to other financial
institutes, I received a good value
by using this service provider.
-251-
Frequency of visiting this place per month:
1-2 times
3-5 times
6-10 times
11-15 times
15-20 times
20 times and over
Gender:
Male
Female
Thank you very much for your assistance!!!
-252-
-253-
APPENDIX C: SUMMARY OF PREVIOUS LITERATURE FOR MEASUREMENT AND
SOURCES OF SCALING TECHNIQUES
Measuring Customer Perceptions of FSEs’ Expertise to Customer during Service Encounter
Variables Previous Work Area of Study Sector Measurement Scale Measurement
Scale for this Study
FSEs’ Expertise during
Service Encounter
Dabholkar et al.
(1996)
A measure of service quality
for retail stores
Retail stores (a mix of
goods and services)
1 items measured in 5-
point scale (adapted from
assurance/personal
interaction/inspiring
confidence)
5 items measured
for pre-test; 4 items
measured for main
study (post-test) Liao and Chuang
(2004)
Factors influencing
employee service
performance and customer
outcomes
Restaurants
13 items measured in 11-
point scale (adapted from
service training)
Stock and Hoyer
(2005)
Attitude-behaviour of
salespeople’s customer
oriented and customer
satisfaction
Insurance and financial
services
9 items measured in 5-
point scale [adapted from
salespeople's expertise
(customer survey)]
-254-
Measuring Customer Perceptions of FSEs’ Undertaking Job Requirement
Variables Previous Work Area of Study Sector Measurement Scale Measurement
Scale for this Study
FSEs’ Role Behaviour Met
their Job Requirement
Netemeyer and
Maxham III (2007)
Service employee versus
supervisor rating of
employee performance
Retail customer service
sector
3 items measured in 7-
point scale (adapted from
customer in-role
performance-employee
rated themselves) 4 items measured
for pre-test and main
study (post-test)
Tsaur and Lin
(2004)
Service quality: the role of
HRM practices and service
behaviour
Tourist hotels in Taiwan
3 items measured in 5-
point scale (adapted from
assurance) and 3 items in
5-point scale (adapted
form role-prescribed
service behaviour)
-255-
Measuring Customer Perceptions of FSEs’ Considerate Manner to Customers during Service Encounter
Variables Previous Work Area of Study Sector Measurement Scale Measurement
Scale for this Study
FSEs’ Considerate Manner
to Customers during Service
Encounter
Rego and Cunha
(2008)
Organisational citizenship
behaviour and effectiveness
Small insurance
companies
3 items measured in 7-
point scale (adapted from
courtesy toward
customers) 4 items measured
for pre-test and main
study (post-test) Tsaur and Lin
(2004)
Service quality: the role of
HRM practices and service
behaviour
Tourist hotels in Taiwan
4 items measured in 5-
point scale (adapted from
assurance)
-256-
Measuring Customer Perceptions of FSEs’ Personal-Involvement Expression during Service Encounter
Variables Previous Work Area of Study Sector Measurement Scale Measurement
Scale for this Study
FSEs’ Personal-Involvement
Expression during Service
Encounter
Ackfeldt and Wong
(2006)
The antecedents of prosocial
service behaviours
Travel service
organisation
6 items measured in 7-
point scale (adapted from
job satisfaction)
6 items measured
for pre-test; 4 items
measured for main
study (post-test)
Bettencourt et al.
(2001)
Service-oriented
organisational citizenship
behaviours
Service company and a
university library
5 items measured in 7-
point scale (adapted from
service orientation)
Dimitriades (2007)
Inter-relationship between
service climate and job
involvement
Service settings (retailing,
banking, entertainment,
business and public
services)
2 items measured in 7-
point scale (adapted from
job involvement)
-257-
Measuring Customer Perceptions of FSEs’ Empathy during Service Encounter
Variables Previous Work Area of Study Sector Measurement Scale Measurement
Scale for this Study
FSEs’ Empathy during
Service Encounter
Stock and Hoyer
(2005)
Attitude-behaviour of
salespeople’s customer
oriented and customer
satisfaction
Insurance and financial
services
5 items measured in 5-
point scale (adapted from
salespeople’s empathy) 5 items measured
for pre-test
Tsaur and Lin
(2004)
Service quality, service
behaviour
Customers and
employees in Tourist
hotels
5 items measured in 5-
point scale (adapted from
empathy)
Measuring Customer Perceptions of FSEs’ Having a Rapport with Customers during Service Encounter
Variables Previous Work Area of Study Sector Measurement Scale Measurement
Scale for this Study
FSEs’ Having a Rapport
with Customers during
Service Encounter
Gremler and
Gwinner (2000) Customer –employee rapport
Bank and dental clinic
11 items measured in 7-
point scale (adapted from
personal connection)
7 items measured
for pre-test; 4 items
measured for main
study (post-test)
-258-
Measuring Customer Perceptions of FSEs’ Helping-Role Behaviour without Concern for The Duty Boundary during Service Encounter
Variables Previous Work Area of Study Sector Measurement Scale Measurement
Scale for this Study
FSEs’ Helping-Role
Behaviour
Axtell et al. (2007) Customer-oriented
perspective Service agents
4 items measured in 5-
point scale (adapted from
Helping behaviour
towards customers)
4 items measured
for pre-test and main
study (post-test)
Rego and Cunha
(2008)
Organisational citizenship
behaviour and effectiveness
(employee-customer)
Small insurance
companies
3 items measured in 7-
point scale (adapted from
courtesy toward
customers)
Tsaur and Lin
(2004)
Service quality, service
behaviour
Customers and
employees in Tourist
hotels
3 items measured in 5-
point scale (adapted from
extra-role behaviour)
-259-
Measuring Customer Service Satisfaction
Variables Previous Work Area of Study Sector Measurement Scale Measurement
Scale for this Study
Customer Service
Satisfaction
Dagger et al. (2007) Service quality
Private outpatient
oncology clinics and
general practice clinics
5 items measured in 7-
point scale (adapted from
service satisfaction) 6 items measured
for pre-test; 4 items
measured for main
study (post-test) Leisen Pollack
(2009)
Service quality, customer
satisfaction and loyalty
Hairdresser/barber
service, local phone
service subscribers
2 items measured in 7-
point scale (adapted from
overall service quality)
-260-
Measuring Customer Value Perception
Variables Previous Work Area of Study Sector Measurement Scale Measurement
Scale for this Study
Customer Value Perceptions
Gil et al. (2008)
Roles of service encounters,
service value, and job
satisfaction in achieving
customer satisfaction in
business relationships
Banking sector
10 items measured in 5-
point scale (adapted from
service value) 10 items measured
for pre-test; 4 items
measured for main
study (post-test)
Keith et al. (2004)
The effect of relational
exchange between service
provider and the customer on
the customer’s perception of
value
Hair stylists, medical care
providers, and financial
consultants
6 items measured
(adapted from perceived
service value)
-261-
APPENDIX D: DESCRIPTION OF SAMPLE GROUPS
D1. Description of Sample Groups
Description of Sample Groups
Demographic
Factors
Frequency
Gender
Male
Female
97
153
Frequency of
Visiting the
Bank in a
Month
1-2 times
3-5 times
6-10 times
11-15 times
15-20 times
20 times and
over
125
87
26
5
2
5
0 20 40 60 80
Female Male
50%
34.8%
10.4%
2% 0.8% 2%
1-2 times 3-5 times 6-10 times
11-15 times 15-20 times 20 times and over
-262-
D2. T-Test Comparing between Genders and Frequency of Visiting the Bank in
a Month of Sample Groups
Group Statistics
Gender: N Mean
Std.
Deviation Std. Error
Mean
Frequency of visiting this
place per month: Male 97 1.82 1.118 .114
Female 153 1.70 .932 .075
Independent Samples Test
Levene's Test
for Equality
of Variances t-test for Equality of Means
F Sig. t df Sig. (2-
tailed) Mean
Difference Std. Error
Difference
95%
Confidence
Interval of the
Difference
Lower Upper
Frequency
of visiting
this
place per
month:
Equal
variances
assumed .149 .700 .958 248 .339 .125 .131 -.132 .383
Equal
variances
not
assumed
.920 177.527 .359 .125 .136 -.144 .394
D3. The effect Size for Independent-Samples T-Test Calculation
The formula for eta squared is as follows:
Eta squared = 𝑡2
𝑡2+(𝑁12+𝑁2−2)
Eta squared = 0.9582
0.9582+(97+153−2)
Eta squared = .0037
-263-
D4. One-Way ANOVA Comparing between Frequency of Visiting the Bank in
a Month of Sample Groups and Service Satisfaction/Value Perception
Service Satisfaction
Descriptives
SS (Service Satisfaction)
N Mean Std.
Deviation Std.
Error
95% Confidence
Interval for Mean
Minimum Maximum Lower
Bound Upper
Bound
1-2 times 125 42.0240 3.23655 .28949 41.4510 42.5970 28.00 44.00 3-5 times 87 42.3678 2.66377 .28559 41.8001 42.9355 31.00 44.00 6-10 times 26 42.0769 2.89721 .56819 40.9067 43.2471 36.00 44.00 11-15 times 5 43.2000 1.78885 .80000 40.9788 45.4212 40.00 44.00 15-20 times 2 40.0000 5.65685 4.00000 -10.8248 90.8248 36.00 44.00 20 times
and over 5 42.4000 3.57771 1.60000 37.9577 46.8423 36.00 44.00
Total 250 42.1640 2.99684 .18954 41.7907 42.5373 28.00 44.00
Test of Homogeneity of Variances
SS (Service Satisfaction)
Levene
Statistic df1 df2 Sig.
1.016 5 244 .409
ANOVA
SS (Service Satisfaction)
Sum of
Squares df Mean Square F Sig.
Between Groups 21.272 5 4.254 .469 .799 Within Groups 2215.004 244 9.078 Total 2236.276 249
Robust Tests of Equality of Means
SS (Service Satisfaction)
Statistica df1 df2 Sig.
Welch .388 5 7.768 .844 Brown-Forsythe .328 5 3.992 .873
a. Asymptotically F distributed.
-264-
Multiple Comparisons
Dependent Variable: SS (Service Satisfaction) Tukey HSD
(I)
Frequency of
visiting this
place per
month:
(J) Frequency of
visiting this
place per month:
Mean
Differen
ce (I-J) Std. Error Sig.
95% Confidence
Interval
Lower
Bound Upper
Bound
1-2 times 3-5 times -.34382 .42067 .964 -1.5522 .8646
6-10 times -.05292 .64944 1.000 -1.9184 1.8126
11-15 times -1.17600 1.37412 .956 -5.1232 2.7712
15-20 times 2.02400 2.14746 .935 -4.1446 8.1926
20 times and over -.37600 1.37412 1.000 -4.3232 3.5712 3-5 times 1-2 times .34382 .42067 .964 -.8646 1.5522
6-10 times .29089 .67342 .998 -1.6435 2.2253
11-15 times -.83218 1.38561 .991 -4.8124 3.1480
15-20 times 2.36782 2.15483 .882 -3.8219 8.5576 20 times and over -.03218 1.38561 1.000 -4.0124 3.9480
6-10 times 1-2 times .05292 .64944 1.000 -1.8126 1.9184
3-5 times -.29089 .67342 .998 -2.2253 1.6435
11-15 times -1.12308 1.47130 .973 -5.3494 3.1032 15-20 times 2.07692 2.21090 .936 -4.2739 8.4278
20 times and over -.32308 1.47130 1.000 -4.5494 3.9032
11-15 times 1-2 times 1.17600 1.37412 .956 -2.7712 5.1232 3-5 times .83218 1.38561 .991 -3.1480 4.8124
6-10 times 1.12308 1.47130 .973 -3.1032 5.3494
15-20 times 3.20000 2.52082 .801 -4.0411 10.4411
20 times and over .80000 1.90556 .998 -4.6737 6.2737 15-20 times 1-2 times -2.02400 2.14746 .935 -8.1926 4.1446
3-5 times -2.36782 2.15483 .882 -8.5576 3.8219
6-10 times -2.07692 2.21090 .936 -8.4278 4.2739
11-15 times -3.20000 2.52082 .801 -10.4411 4.0411 20 times and over -2.40000 2.52082 .932 -9.6411 4.8411
20 times and
over 1-2 times .37600 1.37412 1.000 -3.5712 4.3232
3-5 times .03218 1.38561 1.000 -3.9480 4.0124
6-10 times .32308 1.47130 1.000 -3.9032 4.5494
11-15 times -.80000 1.90556 .998 -6.2737 4.6737
15-20 times 2.40000 2.52082 .932 -4.8411 9.6411
-265-
Homogeneous Subsets
SS (Service Satisfaction)
Tukey HSDa,b
Frequency of visiting
this place per month: N
Subset for
alpha = 0.05
1
15-20 times 2 40.0000 1-2 times 125 42.0240 6-10 times 26 42.0769 3-5 times 87 42.3678 20 times and over 5 42.4000 11-15 times 5 43.2000 Sig. .417
Means for groups in homogeneous subsets are displayed.
a. Uses Harmonic Mean Sample Size = 6.263.
b. The group sizes are unequal. The harmonic mean of the
group sizes is used. Type I error levels are not guaranteed.
-266-
Value Perception
Descriptives
VP
N Mean Std.
Deviation Std.
Error
95% Confidence
Interval for Mean
Minimum Maximum Lower
Bound Upper
Bound
1-2 times 125 48.3440 7.86592 .70355 46.9515 49.7365 28.00 55.00 3-5 times 87 49.7586 6.96831 .74708 48.2735 51.2438 30.00 55.00 6-10 times 26 50.8846 4.82764 .94678 48.9347 52.8345 40.00 55.00 11-15 times 5 52.0000 2.73861 1.22474 48.5996 55.4004 50.00 55.00 15-20 times 2 52.0000 4.24264 3.00000 13.8814 90.1186 49.00 55.00 20 times
and over 5 51.0000 6.51920 2.91548 42.9053 59.0947 40.00 55.00
Total 250 49.2560 7.20096 .45543 48.3590 50.1530 28.00 55.00
Test of Homogeneity of Variances
VP (Value Perception)
Levene
Statistic df1 df2 Sig.
2.695 5 244 .022
ANOVA
VP (Value Perception)
Sum of
Squares df Mean Square F Sig.
Between Groups 262.823 5 52.565 1.014 .410 Within Groups 12648.793 244 51.839 Total 12911.616 249
Robust Tests of Equality of Means
VP (Value Perception)
Statistica df1 df2 Sig.
Welch 1.436 5 8.139 .307 Brown-Forsythe 1.748 5 28.151 .156
a. Asymptotically F distributed.
-267-
Multiple Comparisons
Dependent Variable: VP (Value Perception) Tukey HSD
(I)
Frequency of
visiting this
place per
month:
(J) Frequency of
visiting this
place per month:
Mean
Differen
ce (I-J) Std.
Error Sig.
95% Confidence
Interval
Lower
Bound Upper
Bound
1-2 times 3-5 times -1.41462 1.00527 .723 -4.3023 1.4730
6-10 times -2.54062 1.55195 .575 -6.9986 1.9174
11-15 times -3.65600 3.28368 .876 -13.0884 5.7764
15-20 times -3.65600 5.13170 .980 -18.3969 11.0849
20 times and over -2.65600 3.28368 .966 -12.0884 6.7764 3-5 times 1-2 times 1.41462 1.00527 .723 -1.4730 4.3023
6-10 times -1.12599 1.60925 .982 -5.7486 3.4966
11-15 times -2.24138 3.31115 .984 -11.7527 7.2699
15-20 times -2.24138 5.14932 .998 -17.0328 12.5501 20 times and over -1.24138 3.31115 .999 -10.7527 8.2699
6-10 times 1-2 times 2.54062 1.55195 .575 -1.9174 6.9986
3-5 times 1.12599 1.60925 .982 -3.4966 5.7486
11-15 times -1.11538 3.51592 1.000 -11.2149 8.9841 15-20 times -1.11538 5.28332 1.000 -16.2918 14.0610
20 times and over -.11538 3.51592 1.000 -10.2149 9.9841
11-15 times 1-2 times 3.65600 3.28368 .876 -5.7764 13.0884 3-5 times 2.24138 3.31115 .984 -7.2699 11.7527
6-10 times 1.11538 3.51592 1.000 -8.9841 11.2149
15-20 times .00000 6.02391 1.000 -17.3037 17.3037
20 times and over 1.00000 4.55365 1.000 -12.0804 14.0804 15-20 times 1-2 times 3.65600 5.13170 .980 -11.0849 18.3969
3-5 times 2.24138 5.14932 .998 -12.5501 17.0328
6-10 times 1.11538 5.28332 1.000 -14.0610 16.2918
11-15 times .00000 6.02391 1.000 -17.3037 17.3037 20 times and over 1.00000 6.02391 1.000 -16.3037 18.3037
20 times and
over 1-2 times 2.65600 3.28368 .966 -6.7764 12.0884
3-5 times 1.24138 3.31115 .999 -8.2699 10.7527
6-10 times .11538 3.51592 1.000 -9.9841 10.2149
11-15 times -1.00000 4.55365 1.000 -14.0804 12.0804
15-20 times -1.00000 6.02391 1.000 -18.3037 16.3037
-268-
Homogeneous Subsets
VP (Value Perception)
Tukey HSDa,b
Frequency of visiting
this place per month: N
Subset for
alpha = 0.05
1
1-2 times 125 48.3440 3-5 times 87 49.7586 6-10 times 26 50.8846 20 times and over 5 51.0000 11-15 times 5 52.0000 15-20 times 2 52.0000 Sig. .947
Means for groups in homogeneous subsets are displayed.
a. Uses Harmonic Mean Sample Size = 6.263.
b. The group sizes are unequal. The harmonic mean of the
group sizes is used. Type I error levels are not guaranteed.
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APPENDIX E: NORMALITY
E1. Case Processing Summary Table
Case Processing Summary
Cases
Valid Missing Total
N Percent N Percent N Percent
EX1 250 100.0% 0 0.0% 250 100.0% EX2 250 100.0% 0 0.0% 250 100.0% EX3 250 100.0% 0 0.0% 250 100.0% EX5 250 100.0% 0 0.0% 250 100.0% JR1 250 100.0% 0 0.0% 250 100.0% JR2 250 100.0% 0 0.0% 250 100.0% JR3 250 100.0% 0 0.0% 250 100.0% JR4 250 100.0% 0 0.0% 250 100.0% CC1 250 100.0% 0 0.0% 250 100.0% CC2 250 100.0% 0 0.0% 250 100.0% CC3 250 100.0% 0 0.0% 250 100.0% CC4 250 100.0% 0 0.0% 250 100.0% PE1 250 100.0% 0 0.0% 250 100.0% PE4 250 100.0% 0 0.0% 250 100.0% PE5 250 100.0% 0 0.0% 250 100.0% PE6 250 100.0% 0 0.0% 250 100.0% RA1 250 100.0% 0 0.0% 250 100.0% RA3 250 100.0% 0 0.0% 250 100.0% RA4 250 100.0% 0 0.0% 250 100.0% RA6 250 100.0% 0 0.0% 250 100.0% WC1 250 100.0% 0 0.0% 250 100.0% WC2 250 100.0% 0 0.0% 250 100.0% WC3 250 100.0% 0 0.0% 250 100.0% WC4 250 100.0% 0 0.0% 250 100.0% SS1 250 100.0% 0 0.0% 250 100.0% SS2 250 100.0% 0 0.0% 250 100.0% SS3 250 100.0% 0 0.0% 250 100.0% SS4 250 100.0% 0 0.0% 250 100.0% VP3 250 100.0% 0 0.0% 250 100.0% VP6 250 100.0% 0 0.0% 250 100.0% VP7 250 100.0% 0 0.0% 250 100.0% VP8 250 100.0% 0 0.0% 250 100.0% VP10 250 100.0% 0 0.0% 250 100.0%
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E2. Descriptives Table of Normality
Descriptives
Statistic Std. Error
EX1 Mean 9.83 .109 99% Confidence Interval
for Mean Lower Bound 9.62
Upper Bound 10.05
5% Trimmed Mean 9.98
Median 11.00
Variance 2.992
Std. Deviation 1.730
Minimum 6
Maximum 11
Range 5
Interquartile Range 2
Skewness -1.409 .154 Kurtosis .556 .307
EX2 Mean 9.92 .103 99% Confidence Interval
for Mean Lower Bound 9.72
Upper Bound 10.13
5% Trimmed Mean 10.08
Median 11.00
Variance 2.665
Std. Deviation 1.632
Minimum 6
Maximum 11
Range 5
Interquartile Range 1
Skewness -1.591 .154 Kurtosis 1.254 .307
EX3 Mean 10.44 .057 99% Confidence Interval
for Mean Lower Bound 10.32
Upper Bound 10.55
5% Trimmed Mean 10.55
Median 11.00
Variance .809
Std. Deviation .900
Minimum 5
Maximum 11
Range 6
Interquartile Range 1
Skewness -2.210 .154 Kurtosis 7.187 .307
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EX5 Mean 9.68 .116 99% Confidence Interval
for Mean Lower Bound 9.45
Upper Bound 9.91
5% Trimmed Mean 9.81
Median 11.00
Variance 3.375
Std. Deviation 1.837
Minimum 6
Maximum 11
Range 5
Interquartile Range 2
Skewness -1.197 .154 Kurtosis -.118 .307
JR1 Mean 10.50 .049 99% Confidence Interval
for Mean Lower Bound 10.40
Upper Bound 10.60
5% Trimmed Mean 10.60
Median 11.00
Variance .604
Std. Deviation .777
Minimum 8
Maximum 11
Range 3
Interquartile Range 1
Skewness -1.602 .154 Kurtosis 2.049 .307
JR2 Mean 10.49 .054 99% Confidence Interval
for Mean Lower Bound 10.39
Upper Bound 10.60
5% Trimmed Mean 10.60
Median 11.00
Variance .733
Std. Deviation .856
Minimum 5
Maximum 11
Range 6
Interquartile Range 1
Skewness -2.492 .154 Kurtosis 9.397 .307
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JR3 Mean 10.40 .061 99% Confidence Interval
for Mean Lower Bound 10.28
Upper Bound 10.52
5% Trimmed Mean 10.53
Median 11.00
Variance .939
Std. Deviation .969
Minimum 6
Maximum 11
Range 5
Interquartile Range 1
Skewness -2.039 .154 Kurtosis 4.826 .307
JR4 Mean 10.44 .059 99% Confidence Interval
for Mean Lower Bound 10.32
Upper Bound 10.56
5% Trimmed Mean 10.56
Median 11.00
Variance .874
Std. Deviation .935
Minimum 5
Maximum 11
Range 6
Interquartile Range 1
Skewness -2.589 .154 Kurtosis 9.308 .307
CC1 Mean 10.54 .047 99% Confidence Interval
for Mean Lower Bound 10.45
Upper Bound 10.63
5% Trimmed Mean 10.64
Median 11.00
Variance .563
Std. Deviation .750
Minimum 7
Maximum 11
Range 4
Interquartile Range 1
Skewness -2.008 .154 Kurtosis 4.797 .307
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CC2 Mean 10.55 .048 99% Confidence Interval
for Mean Lower Bound 10.46
Upper Bound 10.65
5% Trimmed Mean 10.65
Median 11.00
Variance .578
Std. Deviation .760
Minimum 7
Maximum 11
Range 4
Interquartile Range 1
Skewness -2.142 .154 Kurtosis 5.578 .307
CC3 Mean 10.53 .047 99% Confidence Interval
for Mean Lower Bound 10.44
Upper Bound 10.62
5% Trimmed Mean 10.62
Median 11.00
Variance .555
Std. Deviation .745
Minimum 7
Maximum 11
Range 4
Interquartile Range 1
Skewness -1.696 .154 Kurtosis 2.875 .307
CC4 Mean 10.54 .046 99% Confidence Interval
for Mean Lower Bound 10.45
Upper Bound 10.63
5% Trimmed Mean 10.64
Median 11.00
Variance .530
Std. Deviation .728
Minimum 7
Maximum 11
Range 4
Interquartile Range 1
Skewness -1.947 .154 Kurtosis 4.776 .307
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PE1 Mean 10.50 .049 99% Confidence Interval
for Mean Lower Bound 10.41
Upper Bound 10.60
5% Trimmed Mean 10.60
Median 11.00
Variance .604
Std. Deviation .777
Minimum 7
Maximum 11
Range 4
Interquartile Range 1
Skewness -1.771 .154 Kurtosis 3.438 .307
PE4 Mean 10.46 .060 99% Confidence Interval
for Mean Lower Bound 10.34
Upper Bound 10.57
5% Trimmed Mean 10.60
Median 11.00
Variance .908
Std. Deviation .953
Minimum 6
Maximum 11
Range 5
Interquartile Range 1
Skewness -2.457 .154 Kurtosis 7.003 .307
PE5 Mean 10.36 .066 99% Confidence Interval
for Mean Lower Bound 10.23
Upper Bound 10.49
5% Trimmed Mean 10.50
Median 11.00
Variance 1.083
Std. Deviation 1.041
Minimum 6
Maximum 11
Range 5
Interquartile Range 1
Skewness -2.037 .154 Kurtosis 4.306 .307
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PE6 Mean 10.36 .063 99% Confidence Interval
for Mean Lower Bound 10.24
Upper Bound 10.49
5% Trimmed Mean 10.50
Median 11.00
Variance .979
Std. Deviation .990
Minimum 6
Maximum 11
Range 5
Interquartile Range 1
Skewness -1.985 .154 Kurtosis 4.490 .307
RA1 Mean 10.41 .060 99% Confidence Interval
for Mean Lower Bound 10.29
Upper Bound 10.53
5% Trimmed Mean 10.54
Median 11.00
Variance .893
Std. Deviation .945
Minimum 6
Maximum 11
Range 5
Interquartile Range 1
Skewness -2.107 .154 Kurtosis 5.173 .307
RA3 Mean 10.39 .062 99% Confidence Interval
for Mean Lower Bound 10.27
Upper Bound 10.51
5% Trimmed Mean 10.53
Median 11.00
Variance .961
Std. Deviation .980
Minimum 6
Maximum 11
Range 5
Interquartile Range 1
Skewness -2.106 .154 Kurtosis 5.137 .307
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RA4 Mean 10.31 .071 99% Confidence Interval
for Mean Lower Bound 10.17
Upper Bound 10.45
5% Trimmed Mean 10.46
Median 11.00
Variance 1.244
Std. Deviation 1.115
Minimum 6
Maximum 11
Range 5
Interquartile Range 1
Skewness -1.989 .154 Kurtosis 4.127 .307
RA6 Mean 10.12 .092 99% Confidence Interval
for Mean Lower Bound 9.93
Upper Bound 10.30
5% Trimmed Mean 10.32
Median 11.00
Variance 2.135
Std. Deviation 1.461
Minimum 1
Maximum 11
Range 10
Interquartile Range 1
Skewness -2.399 .154 Kurtosis 7.430 .307
WC1 Mean 8.26 .145 99% Confidence Interval
for Mean Lower Bound 7.97
Upper Bound 8.54
5% Trimmed Mean 8.25
Median 8.00
Variance 5.292
Std. Deviation 2.300
Minimum 3
Maximum 11
Range 8
Interquartile Range 5
Skewness .074 .154 Kurtosis -1.790 .307
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WC2 Mean 8.82 .141 99% Confidence Interval
for Mean Lower Bound 8.55
Upper Bound 9.10
5% Trimmed Mean 8.88
Median 10.00
Variance 4.965
Std. Deviation 2.228
Minimum 1
Maximum 11
Range 10
Interquartile Range 5
Skewness -.475 .154 Kurtosis -1.173 .307
WC3 Mean 8.22 .146 99% Confidence Interval
for Mean Lower Bound 7.94
Upper Bound 8.51
5% Trimmed Mean 8.21
Median 7.50
Variance 5.323
Std. Deviation 2.307
Minimum 3
Maximum 11
Range 8
Interquartile Range 5
Skewness .119 .154 Kurtosis -1.787 .307
WC4 Mean 8.65 .147 99% Confidence Interval
for Mean Lower Bound 8.36
Upper Bound 8.94
5% Trimmed Mean 8.70
Median 10.00
Variance 5.392
Std. Deviation 2.322
Minimum 1
Maximum 11
Range 10
Interquartile Range 5
Skewness -.314 .154 Kurtosis -1.432 .307
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SS1 Mean 10.52 .052 99% Confidence Interval
for Mean Lower Bound 10.42
Upper Bound 10.62
5% Trimmed Mean 10.63
Median 11.00
Variance .668
Std. Deviation .817
Minimum 7
Maximum 11
Range 4
Interquartile Range 1
Skewness -2.066 .154 Kurtosis 4.789 .307
SS2 Mean 10.54 .058 99% Confidence Interval
for Mean Lower Bound 10.42
Upper Bound 10.65
5% Trimmed Mean 10.67
Median 11.00
Variance .844
Std. Deviation .919
Minimum 3
Maximum 11
Range 8
Interquartile Range 1
Skewness -3.584 .154 Kurtosis 20.262 .307
SS3 Mean 10.57 .047 99% Confidence Interval
for Mean Lower Bound 10.48
Upper Bound 10.66
5% Trimmed Mean 10.66
Median 11.00
Variance .544
Std. Deviation .737
Minimum 7
Maximum 11
Range 4
Interquartile Range 1
Skewness -2.025 .154 Kurtosis 4.808 .307
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SS4 Mean 10.54 .050 99% Confidence Interval
for Mean Lower Bound 10.44
Upper Bound 10.64
5% Trimmed Mean 10.64
Median 11.00
Variance .619
Std. Deviation .787
Minimum 7
Maximum 11
Range 4
Interquartile Range 1
Skewness -2.029 .154 Kurtosis 4.646 .307
VP3 Mean 9.88 .108 99% Confidence Interval
for Mean Lower Bound 9.66
Upper Bound 10.09
5% Trimmed Mean 10.03
Median 11.00
Variance 2.896
Std. Deviation 1.702
Minimum 6
Maximum 11
Range 5
Interquartile Range 1
Skewness -1.505 .154 Kurtosis .849 .307
VP6 Mean 9.67 .119 99% Confidence Interval
for Mean Lower Bound 9.43
Upper Bound 9.90
5% Trimmed Mean 9.80
Median 11.00
Variance 3.532
Std. Deviation 1.879
Minimum 6
Maximum 11
Range 5
Interquartile Range 2
Skewness -1.198 .154 Kurtosis -.169 .307
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VP7 Mean 9.88 .109 99% Confidence Interval
for Mean Lower Bound 9.66
Upper Bound 10.09
5% Trimmed Mean 10.04
Median 11.00
Variance 2.968
Std. Deviation 1.723
Minimum 3
Maximum 11
Range 8
Interquartile Range 1
Skewness -1.583 .154 Kurtosis 1.398 .307
VP8 Mean 9.71 .117 99% Confidence Interval
for Mean Lower Bound 9.48
Upper Bound 9.94
5% Trimmed Mean 9.84
Median 11.00
Variance 3.436
Std. Deviation 1.854
Minimum 6
Maximum 11
Range 5
Interquartile Range 2
Skewness -1.236 .154 Kurtosis -.064 .307
VP10 Mean 10.13 .094 99% Confidence Interval
for Mean Lower Bound 9.94
Upper Bound 10.31
5% Trimmed Mean 10.33
Median 11.00
Variance 2.225
Std. Deviation 1.491
Minimum 3
Maximum 11
Range 8
Interquartile Range 1
Skewness -2.176 .154 Kurtosis 4.337 .307
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E3. Tests of Normality Table
Tests of Normality
Kolmogorov-Smirnova Shapiro-Wilk
Statistic df Sig. Statistic df Sig. EX1 .298 250 .000 .680 250 .000 EX2 .289 250 .000 .669 250 .000 EX3 .359 250 .000 .659 250 .000 EX5 .285 250 .000 .701 250 .000 JR1 .380 250 .000 .667 250 .000 JR2 .372 250 .000 .629 250 .000 JR3 .353 250 .000 .663 250 .000 JR4 .349 250 .000 .628 250 .000 CC1 .382 250 .000 .640 250 .000 CC2 .390 250 .000 .625 250 .000 CC3 .391 250 .000 .660 250 .000 CC4 .382 250 .000 .648 250 .000 PE1 .378 250 .000 .666 250 .000 PE4 .360 250 .000 .612 250 .000 PE5 .347 250 .000 .659 250 .000 PE6 .340 250 .000 .676 250 .000 RA1 .346 250 .000 .660 250 .000 RA3 .346 250 .000 .661 250 .000 RA4 .351 250 .000 .663 250 .000 RA6 .303 250 .000 .652 250 .000 WC1 .309 250 .000 .747 250 .000 WC2 .237 250 .000 .773 250 .000 WC3 .316 250 .000 .738 250 .000 WC4 .261 250 .000 .755 250 .000 SS1 .389 250 .000 .631 250 .000 SS2 .385 250 .000 .547 250 .000 SS3 .401 250 .000 .627 250 .000 SS4 .397 250 .000 .629 250 .000 VP3 .294 250 .000 .666 250 .000 VP6 .293 250 .000 .687 250 .000 VP7 .299 250 .000 .678 250 .000 VP8 .297 250 .000 .684 250 .000 VP10 .309 250 .000 .626 250 .000
a. Lilliefors Significance Correction
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E4. Histogram of Variables
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APPENDIX F: OUTLIERS
F1. 29 Extreme-Point Outliers
Extreme-Point Outliers
Case ID of Respondents Numbers of Extreme
Outliers in each Scale Items
7 071 1
12 076 1
22 086 1
34 097 2
49 026 1
66 474 2
73 481 1
100 209 1
103 161 1
121 192 2
132 167 1
134 222 1
135 223 1
141 228 1
142 229 3
151 255 2
155 258 1
189 131 2
198 139 1
215 153 1
216 157 1
224 243 4
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228 247 2
231 248 4
232 249 7
235 182 2
236 251 2
237 252 1
240 184 3
Total 29 53
F2. Normality Descriptives Table Presenting only the Extreme Points of
Outliers of Dependent Variables
Normality Descriptives with the Extreme Points of Outliers of Dependent Variables
Item Codes Mean Statistic
EX2
95% Confidence Interval of Mean
5% Trimmed Mean
9.92
10.08
EX3
95% Confidence Interval of Mean
5% Trimmed Mean
10.44
10.55
JR2
95% Confidence Interval of Mean
5% Trimmed Mean
10.49
10.60
JR3
95% Confidence Interval of Mean
5% Trimmed Mean
10.40
10.53
JR4
95% Confidence Interval of Mean
5% Trimmed Mean
10.44
10.56
PE4
95% Confidence Interval of Mean
5% Trimmed Mean
10.46
10.60
PE5
95% Confidence Interval of Mean
5% Trimmed Mean
10.36
10.50
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PE6
95% Confidence Interval of Mean
5% Trimmed Mean
10.36
10.50
RA1
95% Confidence Interval of Mean
5% Trimmed Mean
10.41
10.54
RA3
95% Confidence Interval of Mean
5% Trimmed Mean
10.39
10.53
RA4
95% Confidence Interval of Mean
5% Trimmed Mean
10.31
10.46
RA6
95% Confidence Interval of Mean
5% Trimmed Mean
10.12
10.32
SS2
95% Confidence Interval of Mean
5% Trimmed Mean
10.54
10.67
VP3
95% Confidence Interval of Mean
5% Trimmed Mean
9.88
10.03
VP7
95% Confidence Interval of Mean
5% Trimmed Mean
9.88
10.04
VP10
95% Confidence Interval of Mean
5% Trimmed Mean
10.13
10.33
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F3. Box-Plots of Extreme Outliers
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APPENDIX G: HOMOSCEDASTICITY
G1. Scatterplots of FSEs’ Expertise Affects Customers’ Service Satisfaction
Sum EX (Expertise) with sum SS (Service Satisfaction)
Four EX (Expertise) variables with sum SS (Service Satisfaction)
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G.2 Scatterplots of FSEs’ Role Behaviour Meeting their Job Requirement
Affects Customers’ Service Satisfaction
Sum JR (Job Requirement) with sum SS (Service Satisfaction)
Four JR (Job Requirement) variables with sum SS (Service Satisfaction)
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G.3 Scatterplots of FSEs’ Considerate Manner Affecting Customers’ Service
Satisfaction
Sum CC (Considerate Manner) with sum SS (Service Satisfaction)
Four CC (Considerate Manner) variables with sum SS (Service Satisfaction)
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G.4 Scatterplots of FSEs’ Personal-Involvement Expression Affecting
Customers’ Service Satisfaction
Sum PE (Personal-Involvement Expression) with sum SS (Service Satisfaction)
Four PE (Personal-Involvement Expression) variables with sum SS (Service Satisfaction)
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G.5 Scatterplots of FSEs’ Having a Rapport with Customers Affects their
Service Satisfaction
Sum RA (Rapport) with sum SS (Service Satisfaction)
Four RA (Rapport) variables with sum SS (Service Satisfaction)
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G.6 Scatterplots of FSEs’ Helping without Concern for the Duty Boundary
Affects Customers’ Service Satisfaction
Sum WC (Helping without Concern for the Duty Boundary) with sum SS (Service Satisfaction)
Four WC (Helping without Concern for the Duty Boundary) variables with sum SS (Service
Satisfaction)
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G.7 Scatterplots of FSEs’ Expertise Affects Customers’ Value Perception
Sum EX (Expertise) with sum VP (Value Perception)
Four EX (Expertise) variables with sum VP (Value Perception)
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G.8 Scatterplots of FSEs’ Role Behaviour Meeting their Job Requirement
Affects Customers’ Value Perception
Sum JR (Job Requirement) with sum VP (Value Perception)
Four JR (Job Requirement) variables with sum VP (Value Perception)
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G.9 Scatterplots of FSEs’ Considerate Manner Affects Customers’ Value
Perception
Sum CC (Considerate Manner) with sum VP (Value Perception)
Four CC (Considerate Manner) variables with sum VP (Value Perception)
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G.10 Scatterplots of FSEs’ Personal-Involvement Expression Affects
Customers’ Value Perception
Sum PE (Personal-Involvement Expression) with sum VP (Value Perception)
Four PE (Personal-Involvement Expression) variables with sum VP (Value Perception)
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G.11 Scatterplots of FSEs’ Having a Rapport with Customers Affects their
Value Perception
Sum RA (Rapport) with sum VP (Value Perception)
Four RA (Rapport) variables with sum VP (Value Perception)
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G.12 Scatterplots of FSEs’ Helping without Concern for the Duty Boundary
Affects Customers’ Value Perception
Sum WC (Helping without concern for the Duty Boundary) with sum VP (Value Perception)
Four WC (Helping without concern for the Duty Boundary) variables with sum VP (Value
Perception)
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APPENDIX H: MULTICOLLINEARITY
H.1 Verifications of Multicollinearity
Collinearity of Multicollinearity
Independent Collinearity Statistics
Items Tolerance VIF
EX1 .364 2.750
EX2 .373 2.684
EX3 .347 2.881
EX5 .433 2.311
JR1 .163 6.154
JR2 .198 5.046
JR3 .351 2.852
JR4 .368 2.718
CC1 .111 9.022
CC2 .122 8.174
CC3 .099* 10.149*
CC4 .120 8.303
PE1 .121 8.240
PE4 .257 3.893
PE5 .212 4.726
PE6 .256 3.906
RA1 .231 4.329
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RA3 .157 6.364
RA4 .265 3.777
RA6 .385 2.601
WC1 .428 2.338
WC2 .420 2.383
WC3 .414 2.414
WC4 .353 2.834
a. Tolerance and VIF have been conducted in terms of ‘Service Satisfaction (SS)’ and ‘Value Perception
(VP)’ which are two dependent variables in this study.
b. All the items of construct except dependent variables ‘Service Satisfaction (SS)’ and ‘Value Perception
(VP)’.
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H.2 Verifications of Multicollinearity: Tolerance and VIF Conducted in Terms
of Service Satisfaction (SS) which is Dependent Variable
Coefficientsa
Model
Collinearity Statistics
Tolerance VIF
1 EX1 .364 2.750
EX2 .373 2.684
EX3 .347 2.881
EX5 .433 2.311
JR1 .163 6.154
JR2 .198 5.046
JR3 .351 2.852
JR4 .368 2.718
CC1 .111 9.022
CC2 .122 8.174
CC3 .099 10.149
CC4 .120 8.303
PE1 .121 8.240
PE4 .257 3.893
PE5 .212 4.726
PE6 .256 3.906
RA1 .231 4.329
RA3 .157 6.364
RA4 .265 3.777
RA6 .385 2.601
WC1 .428 2.338
WC2 .420 2.383
WC3 .414 2.414
WC4 .353 2.834 a. Dependent Variable: SS
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H.3 Verifications of Multicollinearity: Tolerance and VIF Conducted in Terms
of Value Perception (VP) which is Dependent Variable
Coefficientsa
Model
Collinearity Statistics
Tolerance VIF
1 EX1 .364 2.750
EX2 .373 2.684
EX3 .347 2.881
EX5 .433 2.311
JR1 .163 6.154
JR2 .198 5.046
JR3 .351 2.852
JR4 .368 2.718
CC1 .111 9.022
CC2 .122 8.174
CC3 .099 10.149
CC4 .120 8.303
PE1 .121 8.240
PE4 .257 3.893
PE5 .212 4.726
PE6 .256 3.906
RA1 .231 4.329
RA3 .157 6.364
RA4 .265 3.777
RA6 .385 2.601
WC1 .428 2.338
WC2 .420 2.383
WC3 .414 2.414
WC4 .353 2.834 a. Dependent Variable: VP
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APPENDIX I: CORRELATION MATRIX FOR FINAL
INDICATORS (AMOS)
Table I1 summarised the characteristics and showed the intercorrelations among all final
indicators using Pearson product-moment correlation coefficient. The results revealed that all
indicators were significant at the 0.01 level. In addition, each variable had a large relationship
(≥ 0.5) with the members of the same construct and was low correlated (< 0.5) with others of
the different factors. Although, the scale items of SS (service satisfaction), CC (considerate
manner), and RA (rapport) constructs had large relationships (≥ 0.5) among each other, their
intercorrelations were not too high (< 0.90) (Kline, 2005). The variables of SS (endogenous
construct), CC, and RA (exogenous constructs) still measured different factors (Kline, 2005).
Moreover, the large relationships (≥ 0.5 but < 0.90) between CC and RA confirmed that they
are the dimensions that significantly contribute to beyond role behaviour.
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Table I1: Correlation Matrix of the Indicators
EX1 EX2 CC1 CC2 CC3 RA1 RA3 RA4 WC1 WC2 WC3 SS1 SS2 SS3 VP3 VP8 VP10
EX1 1.000
EX2 0.718 1.000
CC1 0.374 0.411 1.000
CC2 0.395 0.377 0.877 1.000
CC3 0.395 0.387 0.885 0.891 1.000
RA1 0.384 0.408 0.725 0.753 0.734 1.000
RA3 0.432 0.440 0.708 0.725 0.717 0.847 1.000
RA4 0.417 0.432 0.619 0.673 0.674 0.725 0.814 1.000
WC1 0.361 0.285 0.201 0.222 0.183 0.249 0.250 0.308 1.000
WC2 0.363 0.365 0.271 0.269 0.260 0.341 0.373 0.379 0.631 1.000
WC3 0.341 0.301 0.241 0.243 0.222 0.297 0.304 0.311 0.637 0.608 1.000
SS1 0.372 0.379 0.706 0.726 0.751 0.670 0.754 0.650 0.249 0.317 0.268 1.000
SS2 0.348 0.367 0.633 0.650 0.655 0.580 0.602 0.600 0.180 0.246 0.178 0.686 1.000
SS3 0.400 0.420 0.808 0.829 0.837 0.755 0.777 0.692 0.245 0.301 0.244 0.847 0.752 1.000
VP3 0.391 0.406 0.348 0.311 0.312 0.346 0.424 0.399 0.421 0.379 0.429 0.376 0.379 0.370 1.000
VP8 0.251 0.281 0.313 0.283 0.284 0.293 0.363 0.307 0.388 0.330 0.389 0.336 0.297 0.328 0.558 1.000
VP10 0.175 0.210 0.380 0.391 0.401 0.433 0.460 0.425 0.324 0.332 0.308 0.396 0.422 0.452 0.625 0.577 1.000
All variables are significant at the 0.01 level (2-tailed).
-317-
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