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The Rise of Co-Creative Consumers:
User Experience Sharing Behaviour in
Online Communities
A thesis submitted in fulfilment of the requirements for admission to the
degree of
Doctor of Philosophy (PhD)
in
Marketing
at the
School of Advertising, Marketing and Public Relations
Queensland University of Technology
Brisbane, Australia
by
Chien-Hung Tom Chen
October 2011
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KEY WORDS: Consumer-to-Consumer Interaction, Service-Dominant
Logic, Sharing, Value Co-Creation, Consumer Engagement, Online
Community, Convergent Mobile Online Services
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STATEMENT OF ORIGINAL AUTHORSHIP
The work contained in this thesis has not been previously submitted to meet
requirements for an award at this or any other higher education institution. To the
best of my knowledge and belief, the thesis contains no material previously
published or written by another person except where due reference is made.
____________________
Chien-Hung Tom Chen
October 2011
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ABSTRACT
This thesis examines consumer initiated value co-creation behaviour in the context
of convergent mobile online services using a Service-Dominant logic (SD logic)
theoretical framework. It focuses on non-reciprocal marketing phenomena such as
open innovation and user generated content whereby new viable business models are
derived and consumer roles and community become essential to the success of
business.
Attention to customers‟ roles and personalised experiences in value co-creation has
been recognised in the literature (e.g., Prahalad & Ramaswamy, 2000; Prahalad,
2004; Prahalad & Ramaswamy, 2004). Similarly, in a subsequent iteration of their
2004 version of the foundations of SD logic, Vargo and Lusch (2006) replaced the
concept of value co-production with value co-creation and suggested that a value co-
creation mindset is essential to underpin the firm-customer value creation
relationship. Much of this focus, however, has been limited to firm initiated value
co-creation (e.g., B2B or B2C), while consumer initiated value creation, particularly
consumer-to-consumer (C2C) has received little attention in the SD logic literature.
While it is recognised that not every consumer wishes to make the effort to engage
extensively in co-creation processes (MacDonald & Uncles, 2009), some consumers
may not be satisfied with a standard product, instead they engage in the effort
required for personalisation that potentially leads to greater value for themselves, and
which may benefit not only the firm, but other consumers as well. Literature
suggests that there are consumers who do, and as a result initiate such behaviour and
expend effort to engage in co-creation activity (e.g., Gruen, Osmonbekov and
Czaplewski, 2006; 2007 MacDonald & Uncles, 2009).
In terms of consumers‟ engagement in value proposition (co-production) and value
actualisation (co-creation), SD logic (Vargo & Lusch, 2004, 2008) provides a new
lens that enables marketing scholars to transcend existing marketing theory and
facilitates marketing practitioners to initiate service centric and value co-creation
oriented marketing practices. Although the active role of the consumer is
acknowledged in the SD logic oriented literature, we know little about how and why
consumers participate in a value co-creation process (Payne, Storbacka, & Frow,
2008). Literature suggests that researchers should focus on areas such as C2C
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interaction (Gummesson 2007; Nicholls 2010) and consumer experience sharing and
co-creation (Belk 2009; Prahalad & Ramaswamy 2004). In particular, this thesis
seeks to better understand consumer initiated value co-creation, which is aligned
with the notion that consumers can be resource integrators (Baron & Harris, 2008)
and more. The reason for this focus is that consumers today are more empowered in
both online and offline contexts (Füller, Mühlbacher, Matzler, & Jawecki, 2009;
Sweeney, 2007). Active consumers take initiatives to engage and co-create solutions
with other active actors in the market for their betterment of life (Ballantyne &
Varey, 2006; Grönroos & Ravald, 2009).
In terms of the organisation of the thesis, this thesis first takes a „zoom-out‟ (Vargo
& Lusch, 2011) approach and develops the Experience Co-Creation (ECo)
framework that is aligned with balanced centricity (Gummesson, 2008) and Actor-
to-Actor worldview (Vargo & Lusch, 2011). This ECo framework is based on an
extended „SD logic friendly lexicon‟ (Lusch & Vargo, 2006): value initiation and
value initiator, value-in-experience, betterment centricity and betterment outcomes,
and experience co-creation contexts derived from five gaps identified from the SD
logic literature review. The framework is also designed to accommodate broader
marketing phenomena (i.e., both reciprocal and non-reciprocal marketing
phenomena).
After zooming out and establishing the ECo framework, the thesis takes a zoom-in
approach and places attention back on the value co-creation process. Owing to the
scope of the current research, this thesis focuses specifically on non-reciprocal value
co-creation phenomena initiated by consumers in online communities. Two emergent
concepts: User Experience Sharing (UES) and Co-Creative Consumers are proposed
grounded in the ECo framework. Together, these two theorised concepts shed light
on the following two propositions: (1) User Experience Sharing derives value-in-
experience as consumers make initiative efforts to participate in value co-creation,
and (2) Co-Creative Consumers are value initiators who perform UES. Three
research questions were identified underpinning the scope of this research:
RQ1: What factors influence consumers to exhibit User Experience Sharing
behaviour?
RQ2: Why do Co-Creative Consumers participate in User Experience Sharing as part
of value co-creation behaviour?
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RQ3: What are the characteristics of Co-Creative Consumers?
To answer these research questions, two theoretical models were developed: the User
Experience Sharing Behaviour Model (UESBM) grounded in the Theory of Planned
Behaviour framework, and the Co-Creative Consumer Motivation Model (CCMM)
grounded in the Motivation, Opportunity, Ability framework. The models use SD
logic consistent constructs and draw upon multiple streams of literature including
consumer education, consumer psychology and consumer behaviour, and
organisational psychology and organisational behaviour. These constructs include
User Experience Sharing with Other Consumers (UESC), User Experience Sharing
with Firms (UESF), Enjoyment in Helping Others (EIHO), Consumer Empowerment
(EMP), Consumer Competence (COMP), and Intention to Engage in User
Experience Sharing (INT), Attitudes toward User Experience Sharing (ATT) and
Subjective Norm (SN) in the UESBM, and User Experience Sharing (UES),
Consumer Citizenship (CIT), Relating Needs of Self (RELS) and Relating Needs of
Others (RELO), Newness (NEW), Mavenism (MAV), Use Innovativeness (UI),
Personal Initiative (PIN) and Communality (COMU) in the CCMM. Many of these
constructs are relatively new to marketing and require further empirical evidence for
support.
Two studies were conducted to underpin the corresponding research questions. Study
One was conducted to calibrate and re-specify the proposed models. Study Two was
a replica study to confirm the proposed models. In Study One, data were collected
from a PC DIY online community. In Study Two, a majority of data were collected
from Apple product online communities. The data were examined using structural
equation modelling and cluster analysis. Considering the nature of the forums, the
Study One data is considered to reflect some characteristics of Prosumers and the
Study Two data is considered to reflect some characteristics of Innovators. The
results drawn from two independent samples (N = 326 and N = 294) provide
empirical support for the overall structure theorised in the research models.
The results in both models show that Enjoyment in Helping Others and Consumer
Competence in the UESBM, and Consumer Citizenship and Relating Needs in
CCMM have significant impacts on UES. The consistent results appeared in both
Study One and Study Two. The results also support the conceptualisation of Co-
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Creative Consumers and indicate Co-Creative Consumers are individuals who are
able to relate the needs of themselves and others and feel a responsibility to share
their valuable personal experiences. In general, the results shed light on “How and
why consumers voluntarily participate in the value co-creation process?. The
findings provide evidence to conceptualise User Experience Sharing behaviour as
well as the Co-Creative Consumer using the lens of SD logic. This research is a
pioneering study that incorporates and empirically tests SD logic consistent
constructs to examine a particular area of the logic – that is consumer initiated value
co-creation behaviour. This thesis also informs practitioners about how to facilitate
and understand factors that engage with either firm or consumer initiated online
communities.
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DEDICATION
To my family
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ACKNOWLEDGEMENTS
Friends and colleagues often ask me why I wanted to pursue a PhD. I tell them that it
has been my goal since I was a child. It may sound silly, given that a PhD is not even
a job title, but for some reason, this was always my dream. When I finally had the
chance to follow this dream, it was not an easy ride. There were many hurdles and
much stress along the way. However, not for a moment did I entertain the thought of
relinquishing my goal or forgetting why I was undertaking the degree in the first
place. I have always believed that through earning a PhD I would be able to make
my own small contribution to society.
To me, the importance of marketing goes beyond the functions that shape, create and
operate in markets. Marketing is also about how we understand the diffusion of ideas.
Therefore, when there are ideas that can enhance the lives of individuals or society at
large, marketing can be used to facilitate the diffusion of these ideas. This thinking
has been reflected in my thesis title, User-experience-sharing.
I would like to thank my University, the Queensland University of Technology for
their generosity in supporting me throughout my PhD journey.
Foremost, I would like to thank my supervisors Professor Judy Drennan, Dr Lynda
Andrews and Professor Gillian Sullivan Mort for believing in me, and for sharing
your scholarly thoughts and life experiences to nurse me and inspire me. I would
also like to thank Dr Stephen Cox for his sound guidance along my PhD journey.
I would like to acknowledge Caroline Frost, Trina Robbie, Associate Professor Paul
Steffens, Dr Cameron Newton, Dr Edwina Luck, Dr Ursula-Sigrid Bougoure, Prof.
Brett Martin and Dr Judy Matthews for their marvellous support. I would like to
thank Associate Professor Debra Grace for providing me the opportunity to lecture at
Griffith University. To all of my colleagues at QUT International, friends I met from
ANZMAC conferences and my fellow PhD candidates in Z701, I have really
appreciated your support and friendship.
The reason my thesis has a focus on Service-Dominant logic is due to my admiration
for the scholarly works of Professor Stephen Vargo and Professor Robert Lusch. I
admire their abilities in integrating scholarly thought, and for taking the initiative to
provide a new lens and a new lexicon that provides a starting point to service and
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accommodate theories and business models derived from a betterment mindset that
focuses on the sustainability of resources (competences) and relationships (reciprocal
marketing phenomena). Your work provided a foundation for my conceptual
contribution that focuses on experience and non-reciprocal marketing phenomena.
Therefore, I thank you both.
I would also like to thank the many people during my PhD candidature who have
shared their experience, and have helped me enormously. They are: Dr Sharon
Brown, Dr Mitchell Ross, Dr Usha Pillai-McGarry, Associate Professor Bernie
Carroll, Jessica O‟Neill, Dr Laknath Jayasinghe, Trent Hennessey, Christophe
Garonne, Dr Ingo Karpen, Dr Cheryl Leo, Dr Clinton Weeks, Zoe Hancock and
Claire Illman. Thank you all for putting in the effort that has encouraged and
strengthened me and that has enriched my scholarly thoughts and my life. I will
always remember your generosity and kindness.
Finally, I would like to dedicate this thesis to my parents, my sister and Daniel
Brown who are, and who will always be such an important part of my life.
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TABLE OF CONTENTS
STATEMENT OF ORIGINAL AUTHORSHIP ....................................................... iii
ABSTRACT ................................................................................................................ iv
DEDICATION ......................................................................................................... viii
ACKNOWLEDGEMENTS ........................................................................................ ix
TABLE OF CONTENTS ............................................................................................ xi
LIST OF TABLES .................................................................................................... xvi
LIST OF FIGURES ................................................................................................. xvii
CHAPTER ONE INTRODUCTION ......................................................................... 18
1.1 Research Background ....................................................................................... 18
1.2 Research Rationale ........................................................................................... 20
1.3 Research Context: Convergent Mobile Online Services .................................. 23
1.4 Overview of Research Question and Design .................................................... 24
1.5 Summary of Contributions to Theory and Practice .......................................... 26
1.6 Structure of the Thesis ...................................................................................... 27
1.7 Conclusion ........................................................................................................ 28
CHAPTER TWO LITERATURE REVIEW ............................................................. 29
2.0 Introduction ...................................................................................................... 29
2.1 Service-Dominant Logic – An Introduction ..................................................... 29
2.2 Service-Dominant Logic – Service Centricity and Value Co-Creation ........... 30
2.2.1 Service-for-Service Exchange ................................................................... 30
2.2.2 Sharing as Resource Integration ................................................................ 32
2.2.3 From Exchange to Interaction.................................................................... 34
2.2.4 Value Creation is Value Co-Creation ........................................................ 35
2.2.5 Meaning of Value Creation........................................................................ 37
2.2.6 Customers‟ Role as Service Providers ....................................................... 41
2.2.7 Overarching Research Question ................................................................ 42
2.3 Extending the Service-Dominant Logic Lexicon and Framework ................... 43
2.4 Value Initiation and Value Initiator .................................................................. 43
2.5 Value-In-Experience as an Effort-Based Meaning of Value Creation ............. 48
2.6 Betterment Centricity and Betterment Outcomes............................................. 50
2.7 An Outcome-Process Driven Value Co-Creation Process ............................... 52
2.8 Experience Co-Creation Framework ................................................................ 53
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2.9 User Experience Sharing .................................................................................. 54
2.9.1 Conceptualising User Experience Sharing ................................................ 55
2.9.2 Comparing UES with Customer-to-Customer Know-How Exchange ...... 56
2.9.3 Comparing User Experience Sharing to Word-of-Mouth.......................... 57
2.10 Co-Creative Consumers.................................................................................. 59
2.11 Summary ........................................................................................................ 62
CHAPTER THREE THEORETICAL FRAMEWORKS AND MODEL
CONCEPTUALISATION ......................................................................................... 64
3.0 Introduction ...................................................................................................... 64
3.1 Theory of Planned Behaviour ........................................................................... 64
3.2 Self-Determination Theory ............................................................................... 67
3.3 Motivation, Opportunity, and Ability Framework ........................................... 67
3.4 User Experience Sharing Behaviour Model ..................................................... 68
3.4.1 Attitudes toward User Experience Sharing ................................................ 69
3.4.2 Subjective Norm ........................................................................................ 70
3.4.3 Consumer Competence .............................................................................. 70
3.4.4 Intention to Engage in User Experience Sharing ....................................... 73
3.4.5 Enjoyment in Helping Others .................................................................... 73
3.4.6 Consumer Empowerment .......................................................................... 74
3.5 Co-Creative Consumer Motivation Model ....................................................... 77
3.5.1 Opportunity to Co-Create Value – Newness ............................................. 78
3.5.2 Motivation for Co-Creation Value – Consumer Citizenship ..................... 78
3.5.3 Ability to Co-Create Value – Relating Needs ........................................... 80
Consumer Characteristics ................................................................................... 83
3.5.4 Use Innovativeness .................................................................................... 84
3.5.5 Mavenism................................................................................................... 85
3.5.6 Personal Initiative ...................................................................................... 87
3.5.7 Communality ............................................................................................. 88
3.6 Conclusion ........................................................................................................ 91
CHAPTER FOUR METHODOLOGY ...................................................................... 92
4.0 Introduction ...................................................................................................... 92
4.1 Philosophical Orientation ................................................................................. 92
4.2 Research Design ............................................................................................... 93
4.3 Research Method .............................................................................................. 94
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4.4 Measurement .................................................................................................... 95
4.4.1 Items Pool and Expert Panel ...................................................................... 95
4.4.2 Measurements – User Experience Sharing ................................................ 96
4.4.3 Measurements – User Experience Sharing Behaviour Model ................... 98
4.4.4 Measurements – Co-Creative Consumer Motivation Model ................... 102
4.4.5 Pilot Study................................................................................................ 107
4.5 Online Questionnaire Designs ........................................................................ 108
4.5.1 Survey Instrument .................................................................................... 108
4.5.2 Justifications for Using Web-based Online Surveys ............................... 109
4.5.3 Considerations of Online Questionnaire Design ..................................... 110
4.5.4 Implementing the Online Questionnaire .................................................. 112
4.6 Sampling ......................................................................................................... 113
4.6.1 Population and Sampling Frame .............................................................. 113
4.6.2 Sampling Procedures ............................................................................... 114
4.6.3 Numbers of Sampling Cases .................................................................... 114
4.7 Implementation of Sampling Method ............................................................. 115
4.7.1 Data Collection ........................................................................................ 115
4.7.2 Recruitment .............................................................................................. 116
4.7.3 Characteristics of Samples ....................................................................... 116
4.7.4 Cost, Survey Solicitation and Survey Access Control ............................. 117
4.7.5 Survey Incentives ..................................................................................... 118
4.8 Statistical Analysis Method ............................................................................ 118
4.9 Ethical Consideration ..................................................................................... 118
4.10 Limitations and Delimitations ...................................................................... 119
4.11 Conclusion .................................................................................................... 120
CHAPTER FIVE STUDY ONE RESULTS ............................................................ 121
5.0 Introduction .................................................................................................... 121
5.1 Sample Characteristics ................................................................................... 121
5.2 Data Preparation and Preliminary Analysis ................................................... 122
5.3 Test of Measurement Model for User Experience Sharing Behaviour Model
.............................................................................................................................. 123
5.3.1 Measurement Model for User Experience Sharing .................................. 124
5.3.2 Measurement Model for Attitudes toward User Experience Sharing ...... 124
5.3.3 Measurement Model for Subjective Norm .............................................. 125
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5.3.4 Measurement Model for Consumer Competence .................................... 125
5.3.5 Measurement Model for Intention to Engage in User Experience Sharing
.......................................................................................................................... 126
5.3.6 Measurement Model for Enjoyment in Helping Others .......................... 126
5.3.7 Measurement Model for Consumer Empowerment................................. 127
5.4 User Experience Sharing Behaviour Full Measurement Model ..................... 127
5.5 Reliability and Validity Analysis for UESBM ............................................... 130
5.6 User Experience Sharing Behaviour Full Structure Equation Model ............ 132
5.7 Test of Hypotheses for User Experience Sharing Behaviour Model ............. 134
5.8 Test of Measurement for Co-Creative Consumer Motivation Model ............ 134
5.8.1 Measurement Model for User Experience Sharing .................................. 135
5.8.2 Measurement Model for Newness ........................................................... 135
5.8.3 Measurement Model for Consumer Citizenship ...................................... 135
5.8.4 Measurement Model for Relating Needs ................................................. 136
5.8.5 Measurement Model for Use Innovativeness .......................................... 136
5.8.6 Measurement Model for Mavenism ......................................................... 137
5.8.7 Measurement Model for Personal Initiative ............................................ 137
5.8.8 Measurement Model for Communality.................................................... 138
5.9 Full Measurement Model for Co-Creative Consumer Motivation Model...... 139
5.10 Reliability and Validity Analysis for Co-Creative Consumer Motivation
Model .................................................................................................................... 142
5.11 Co-Creative Consumer Motivation Full Structural Equation Model ........... 144
5.12 Test of Hypotheses for Co-Creative Consumer Motivation Model ............. 147
5.13 Summary ...................................................................................................... 147
CHAPTER SIX STUDY TWO RESULTS ............................................................. 148
6.0 Introduction .................................................................................................... 148
6.1 Study Two Sample Characteristics ................................................................. 148
6.2 Data Preparation and Preliminary Analysis ................................................... 149
6.3 Reliability and Validity Analysis for User Experience Sharing Behaviour
Model .................................................................................................................... 150
6.4 User Experience Sharing Behaviour Full Structure Equation Model ............ 152
6.5 Test of Hypotheses for User Experience Sharing Behaviour Model ............. 153
6.6 Reliability and Validity Analysis for Co-Creative Consumer Motivation Model
.............................................................................................................................. 156
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6.7 Co-Creative Consumer Motivation Full Structure Equation Model .............. 158
6.8 K-means Cluster Analysis .............................................................................. 160
6.9 Test of Hypotheses for Co-Creative Consumer Motivation Model ............... 162
6.10 Conclusion .................................................................................................... 165
CHAPTER SEVEN DISCUSSION AND CONCLUSION ..................................... 167
7.0 Introduction .................................................................................................... 167
7.1 Overview of Findings ..................................................................................... 167
7.2 User Experience Sharing Behaviour Model ................................................... 170
7.2.1 Enjoyment in Helping Others (EIHO) ..................................................... 170
7.2.2 Consumer Empowerment (EMP) ............................................................ 171
7.2.3 Consumer Competence (COMP) ............................................................. 172
7.2.4 Theory of Planned Behaviour Factors ..................................................... 173
7.3 Co-Creative Consumer Motivation Model ..................................................... 174
7.3.1 Co-Creation Opportunity – Newness (NEW) .......................................... 174
7.3.2 Co-Creation Motivation – Consumer Citizenship (CIT) ......................... 174
7.3.3 Co-Creation Ability – Relating Needs (REL).......................................... 175
7.3.4 Use Innovativeness (UI) .......................................................................... 176
7.3.5 Mavenism (MAV).................................................................................... 178
7.3.6 Personal Initiative and Communality (PIN and COMU) ......................... 178
7.4 Co-Creative Consumer Clusters ..................................................................... 179
7.5 Reflection on Conceptual Findings ................................................................ 182
7.5.1 ECo Framework ....................................................................................... 182
7.5.2 Betterment Centricity ............................................................................... 182
7.6 Contribution to Theory ................................................................................... 183
7.7 Implications for Marketing Practice ............................................................... 186
7.8 Limitations and Delimitations ........................................................................ 189
7.9 Directions for Future Study ............................................................................ 190
7.10 Conclusion .................................................................................................... 192
APPENDIX A - GLOSSARY OF TERMS ............................................................. 194
APPENDIX B – LIST OF ITEMS AND SOURCES DERIVED ........................... 200
APPENDIX C – USER EXPERIENCE SHARING QUESTIONNAIRE ............... 212
REFERENCES ......................................................................................................... 230
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LIST OF TABLES
Table 2.1 Service-Dominant Logic Foundational Premises ...................................... 29
Table 3.1 Hypotheses for User Experience Sharing Behaviour Model ..................... 77
Table 3.2 Hypotheses for the Co-Creative Consumer Motivation Model ................. 90
Table 4.1 A General Construct Development/ Scale Measurement Process ............. 95
Table 4.2 Numbers of Posts and Members in the Participant Online Communities 115
Table 5.1 Sample Characteristics of Respondents ................................................... 121
Table 5.2 Fit Indices ................................................................................................. 123
Table 5.3 User Experience Sharing Model Fit ......................................................... 124
Table 5.4 Attitudes toward User Experience Sharing Model Fit ............................. 125
Table 5.5 Subjective Norm Model Fit...................................................................... 125
Table 5.6 Consumer Competence Model Fit ........................................................... 126
Table 5.7 Intention to Engage in User Experience Sharing Model Fit .................... 126
Table 5.8 Enjoyment in Helping Others Model Fit.................................................. 127
Table 5.9 Consumer Empowerment Model Fit ........................................................ 127
Table 5.10 UESBM Full Measurement Model ........................................................ 128
Table 5.11 Reliability of Measures for UESBM ...................................................... 130
Table 5.12 UESBM Model Fits ............................................................................... 132
Table 5.13 Hypotheses Testing for UESBM............................................................ 134
Table 5.14 Newness Model Fit ................................................................................ 135
Table 5.15 Consumer Citizenship Model Fit ........................................................... 135
Table 5.16 Relating Needs Model Fit ...................................................................... 136
Table 5.17 User Innovativeness Model Fit .............................................................. 136
Table 5.18 Mavenism Model Fit .............................................................................. 137
Table 5.19 Personal Initiative Model Fit ................................................................. 138
Table 5.20 Communality Model Fit ......................................................................... 138
Table 5.21 Full Measurement Model using Higher Order REL .............................. 139
Table 5.22 Full Measurement Model using Lower Order RELS and RELO........... 139
Table 5.23 Reliability of Measures for CCMM ....................................................... 142
Table 5.24 CCMM Full SEM Model ....................................................................... 144
Table 5.25 Test of Hypotheses for CCMM .............................................................. 147
Table 6.1 Sample Characteristics of Respondents ................................................... 148
Table 6.2 Reliability of Measures for UESBM ........................................................ 150
Table 6.3 UESBM Model Fits ................................................................................. 152
Table 6.4 Hypotheses Testing for UESBM ............................................................. 155
Table 6.5 Reliability of Measures for CCMM ......................................................... 156
Table 6.6 CCMM Full SEM Model ......................................................................... 158
Table 6.7 Co-Creative Consumer Cluster Results ................................................... 162
Table 6.8 Test of Hypotheses for CCMM ................................................................ 165
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LIST OF FIGURES
Figure 1.1 Value-in-Exchange Based Value Creation Relationship .......................... 18
Figure 2.1 Value-in-Use Based Value Co-Creation Relationship ............................. 38
Figure 2.2 Service-for-Service Co-Creation Relationship and the Gap ..................... 46
Figure 2.3 Experience-for-Experience Co-Creation Relationship ............................. 47
Figure 2.4 An Outcome-Process Driven Value Co-Creation Process........................ 53
Figure 2.5 Experience Co-Creation Framework ........................................................ 54
Figure 3.1 Theory of Planned Behaviour ................................................................... 65
Figure 3.2 User Experience Sharing Behaviour Model (UESBM) ............................ 76
Figure 3.3 Co-Creative Consumer Motivation Model (CCMM) ............................... 90
Figure 4.1 The Survey Development Process ............................................................ 94
Figure 5.1 UESBM Full Measurement Model ......................................................... 129
Figure 5.2 User Experience Sharing Behaviour Full SEM Model........................... 133
Figure 5.3 CCMM Higher Order Full Measurement Model .................................... 140
Figure 5.4 CCMM Lower Order Full Measurement Model .................................... 141
Figure 5.5 CCMM Lower Order Full SEM Model .................................................. 145
Figure 5.6 CCMM Higher Order Full SEM Model ................................................. 146
Figure 6.1 User Experience Sharing Behaviour Full SEM Model........................... 153
Figure 6.2 CCMM Lower Order Full SEM Model .................................................. 159
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CHAPTER ONE INTRODUCTION
1.1 Research Background
Mass marketing, grounded in the exchange paradigm with its focus on the trading of
goods and services, has guided marketing research over previous decades (Sheth &
Uslay, 2007). In practice, mass marketing operates in a manner of segmentation of
consumers into groups, targeting those segments and market positioning and
supposingly by doing so, leads to identify and then satisfy human needs (Beckett &
Nayak, 2008). This transactional and segmentation oriented mentality is also the
dominant business logic that powers marketing theory. It has been referred to as the
Goods-Dominant logic (GD logic) by Vargo and Lusch (2004).
Under GD logic, the meaning of value refers to value-in-exchange, such that
marketing is seen as a process of “exchange of units of output”, and “exchange of
output embedded with value” (Vargo & Lusch, 2006, p. 48). The relationship is an
exchange between a supplier and its customer. Figure 1.1 illustrates a value-in-
exchange based relationship: A supplier creates value-in-exchange for a customer.
Figure 1.1 Value-in-Exchange Based Value Creation Relationship
Thus, consumers are largely seen as passive or merely facilitators of value
propositions offered by an organisation.
Concerns have been raised regarding the inefficiency of associated mass marketing
practices and subsequent costs on society at large, but these have not yet been fully
addressed (Beckett & Nayak, 2008). As marketing practices guided by GD logic fall
short of today‟s more complex and competitive market (De Marez & Verleye, 2004),
interest in exploring an alternative paradigm has been raised (Sheth & Uslay, 2007;
Vargo & Lusch, 2004). Sheth and Uslay (2007) reflect on the definition of marketing
published by the American Marketing Association in 2004 and suggest an emergent
paradigm shift toward co-creative value creation. They argue that through a value
CustomerCreate
value-in-exchangeSupplier
P a g e | 19
creation lens marketers consider consumers as users rather than selectors/buyers.
They suggest that meaning of value can go beyond value-in-exchange (Sheth &
Uslay, 2007). They further elaborate that the notion of value creation should be
challenged and that marketers should take one step further, and consider value co-
creation. Vargo and Lusch (2008) provide ten foundational premises to further
address the notion of value creation and suggest that consumers are always value co-
creators. As Prahalad and Ramaswamy (2004) first suggested, value is not created
for consumers but is rather co-created with consumers. Sheth and Uslay (2007)
summarise reasons in support of the need for a broader marketing concept, namely
value co-creation, including that the current conceptualisation: (1) overlooks
marketing‟s social impact and is too focused on business outcomes, (2) fails to
recognise/reflect complex network interactions, (3) neglects the value of marketer-
customer interactions, and (4) is limited to a focus on the buyer-seller relationship.
A mindset that supports the idea of co-creative relationships between firms and
customers is service dominant logic (Lusch & Vargo, 2006; Vargo & Lusch, 2004;
Vargo & Lusch, 2008). Eight foundational premises (FPs) of SD logic were initially
proposed by Vargo and Lusch in 2004 and further extended to ten FPs in 2008.
Vargo and Lusch (2008) believe that the continuous evolution of SD logic can serve
as the new mentality of marketing theory. By far, it is the most recognised school of
thought arguing for a paradigm shift toward value co-creation. Most importantly,
Vargo and Lusch (2004) first revised the meaning of value creation as value-in-use,
that is „there is no value unless it is used by customers‟. A further iteration extended
this meaning to „value in context‟ to reflect the idea that value is always co-created
and determined by a customer depending on a given context (Vargo & Lusch, 2008).
Both notions highlight the recognition of the essential role of consumers in a value
co-creation process. Nevertheless, debates on the role of the consumer in value co-
creation arises in the literature (Grönroos, 2008; Grönroos & Ravald, 2009).
In the literature, lead users (Von Hippel, 1986), considered as indirect value co-
creators (Lusch, Vargo, & O‟Brien, 2007) and Prosumers, perceived as co-producers
(Edvardsson, Gustafsson, Kristensson, & Witell, 2010; Vargo & Lusch, 2004) may
be the closest concepts to underpin the characteristics of consumers who actively
participate in the value co-creation process. These two consumer profiles reflect that
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firms view consumers and their insights as resources in the delivery of service
offerings as well as co-producing value propositions. That is, consumers are seen as
"workers" for business (Cova & Dalli, 2009; Zwick, Bonsu, & Darmody, 2008)
which implies (1) the potential for double exploitation (Cova & Dalli, 2009), and (2)
overlooking of consumers' active roles as resource integrators (Baron & Harris,
2008). What appears to be missing from the discussion is why such consumers
voluntarily participate in this co-creation of value and how they do it. As a result, an
overarching question is asked in this thesis:
“How and why do consumers voluntarily participate in the value co-creation
process?”
In addressing this question, the program of research in this thesis proposes that there
is a need to explore the roles and associated behaviour of consumers when they
engage in a value co-creation process. For the purpose of this thesis, SD logic is used
as the theoretical framework through which to better understand consumers‟ roles in
the process of value co-creation.
1.2 Research Rationale
Customer-to-Customer Interaction as Value Co-Creation
Value co-creation is a process of service for service through relationships within the
value network (Grönroos, 2009; Vargo & Lusch, 2008). It defines the integrity of
new logic under the co-creation paradigm. While SD logic continues to evolve, an
SD logic friendly lexicon, new theory and empirical testing of the new theory are
encouraged (Gummesson, Lusch, & Vargo, 2010; Lusch & Vargo, 2006) to explain
new, innovative and versatile marketing phenomena in the consumer market.
Gummesson (2007) suggests that in view of positive customer-to-customer
interaction (CCI), customers can provide „service‟ and co-create value with each
other. Importantly, he suggests that “[CCI] and the customers' role in both the value
proposition and value actualisation is a growing area for research and practical
applications” (Gummesson, 2007, p. 11). Nicholls (2010) conducted a review of
CCI and further suggests that an understanding of CCI is essential to answer research
questions through the lens of the SD logic paradigm. This thesis focuses on
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exploring emergent consumer-to-consumer interaction to help provide an insight into
the active role that consumers play in value co-creation.
Reciprocal and Non-Reciprocal Marketing Phenomena: Consumerism and
Sharing
Consumers have engaged in non-reciprocal value creation processes through sharing
in many ways throughout human history (Belk, 2009). These types of sharing often
occur naturally. Such sharing activities may not necessarily be performed to achieve
a certain outcome, and are performed voluntarily. For example, we share food with
friends and families, donate money to charity and sponsor children to go to school.
In these settings, some forms of sharing are one-way and some are two-way in the
non-reciprocal outset. Belk (2009) suggests that in marketing, sharing activities are
also a part of marketing phenomena. In particular, there are cases that suggest that
sharing is important to service providers. In this context, „sharing‟ can be more
structured and attached to specific purposes or outcomes. For example, opinion
leaders and Market Mavens share their learned market information with others (Chan
& Misra, 1990; Feick & Price, 1987; Nicola & Wayne, 2009). Lead users share their
knowledge with service providers to develop value propositions in the innovation
process (Jeppesen & Laursen, 2009; Von Hippel, 1986). Prosumers share their skills
and resources to produce offerings or value propositions with firms (Ritzer &
Jurgenson, 2010; Toffler, 1980).
Since the concept of „sharing‟ as a non-reciprocal marketing phenomenon has only
recently started to gain attention in marketing research (Belk, 2009), there is limited
research to explore whether people who share consciously feel a sense of
psychological ownership of the activity, or pay attention to possible outcomes that
benefit themselves or others through the sharing process. However, the literature
does raise the question of why customers want to share with service providers and
other consumers (i.e., knowledge sharing) (Chennamaneni, 2007; Chiu, Hsu, &
Wang, 2006; Hendriks, 1999; Hsu, Ju, Yen, & Chang, 2007; Koh & Kim, 2004; Lee,
Cheung, Lim, & Sia, 2006; Limpisook, 2009; Reychav & Weisberg, 2010).
In today‟s rapidly developing technological environment, online sharing activities
have become a new and dominant non-reciprocal marketing phenomenon in
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consumer markets (e.g., Facebook, and YouTube). In addition, open innovations and
user generated content highlight non-reciprocal marketing practices enabled by cloud
sourcing, crowd sourcing, and social networking, which have become viable
business models. In this context, consumers have stepped up and become service
providers (i.e., self service). For example, consumers produce user generated content
in interactive online environments (e.g., Twitter, Flickr, and online gaming sites …
etc.). In these cases, consumers could have roles as both a value benefactor and
beneficiary. Sharing has now become a core marketing phenomenon.
To better understand consumers' roles as sharers and to conceptualise the sharing
experience as a key activity to render value apart from consumption would add value
to the developing new marketing theory, particularly within an SD logic framework.
As sharing is aligned with co-creation by definition, and consumers do have a role as
value creators, this thesis investigates consumers' roles in a co-creation paradigm. In
particular it focuses on sharing as consumer-to-consumer interaction in the context
of open innovations and user generated content. The findings are expected to lead to
a better understanding of consumers‟ co-creation behaviour, motivations for value
creation behaviour, and the identification of the characteristics of those consumers
that engage in this behaviour. The results will help to gain insights into those
consumers who willingly and actively engage in behaviours to co-create value with
others consumers.
Better Manage Co-Creation of Value
As Prahalad and Ramaswamy (2004) suggest, more informed, connected,
empowered, and active consumers are aware of their capability to initiate value at the
point of the exchange of values. Proactive consumers want to have a co-creation
relationship with companies because they desire to be able to share their views and
to create their own experiences in contribution to their betterment of life. In
extending the notion of the role of consumers in value co-creation, Bouwman, De
Vos and Haaker (2008) suggest the development of mobile service innovations
should be a user-driven co-creation, where the individual user influences the way
new services are created and incorporated into their day-to-day routines. In
particular, services such as convergent mobile online services (CMOS) provide new
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value propositions (Olla & Patel, 2002) in a social context through integrated mobile
devices and Internet technologies (Gilbert & Kendall, 2003).
Consumers do not usually expect CMOS to provide only one core value, but expect
several combined values through the evolution of versatile needs and greater
competition. As consumers‟ empowerment increases and they grow smarter in
regard to technological innovations, their insights should also be taken into account
in the design process so that designers adopt users‟ value-in-use. Gilbert and Kendall
(2003) argue that consumers develop new use behaviours to more fully appreciate
the new value propositions offered by the service provider. The authors identify
these behaviours as: “(1) Acquiring the enabling technology; (2) Learning to use it;
(3) Applying it to solve problems or add value in everyday life; (4) Communicating
what one has learned about it to other prospective users” (p. 9). By the same token,
Prahalad & Ramaswamy (2004) provide support for this view and propose that
consumer-to-consumer experience sharing provides consumers with an alternative
source of information and perspective apart from the communication of the firms.
The program of research undertaken in this thesis draws these behaviours together by
proposing and testing a concept named User Experiences Sharing (UES) that will
enhance the understanding of consumer initiated value co-creation behaviour in an
online community context.
1.3 Research Context: Convergent Mobile Online Services
As noted above, a suitable context to examine consumer co-creation behaviour is
CMOS. CMOS refers to online services that are offered to mobile phone users. It is
argued that CMOS users are more likely to encounter services that fulfil desired
outcomes in their everyday life, for example, they can access Facebook, location
based services or email accounts at anytime and anywhere.
Convergent practices in technology development assist a base mobile product to
offer consumers seamlessly integrated uses of the device and of relevant services.
Such convergent mobile devices have enabled the extension of uses of mobile online
services through bundling new functionalities (i.e., the mobile TV service) with an
existing convergent base product, for example an iPhone (Gill, 2008). Like the
Internet, convergent mobile online services (CMOS) (e.g., Facebook and Twitter)
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empower consumers and have gradually become indispensible for many people in
their everyday life (Hoffman, Novak, & Venkatesh, 2004). In many ways, CMOS
allows users to use their device beyond what is intended by service providers. In
other words, CMOS enables consumers to personalise services to suit their everyday
routines or use services in a context that may not have been intended by service
providers. The diffusion of CMOS also leads to an evolution of marketing practice.
For example, open innovations and user generated content create non-reciprocal
market phenomena where consumers share their experiences with each other to co-
create value. In this thesis, CMOS will be adopted as the research context.
1.4 Overview of Research Question and Design
This thesis sets out to study an increasing number of consumers who co-create value
and their transforming value co-creation behaviour. In turn, this thesis will provide
conceptualisations of User Experience Sharing and Co-Creative Consumers and
examine these two proposed concepts.
Notably, SD logic suggests consumers are not reactive receivers of offerings (Michel,
Vargo, & Lusch, 2008). The view of offering is shifted from the company output to
the process of value co-creation (Michel, et al., 2008). In other words, consumers are
valuable to companies more than ever before and have an essential role to play in
participating in the value co-creation process. It is suggested here that consumers are
more active in a value co-creation process today (Vargo & Lusch, 2004) for the
betterment of life (Ballantyne & Varey, 2006). Thus, consumers may be more
willing to participate in value co-creation. From the discussion above, this thesis
seeks to employ SD logic as a lens to investigate consumer initiated co-creation
behaviour and motivations and to identify characteristics of consumers who co-
create value with others in a value co-creation process.
This thesis proposes an overall research question extended from Payne, Storbacka
and Frow‟s (2008) suggestion:
“How and why do customers voluntarily participate in a value co-creation process?”
Particularly, the main purpose of this study is to better understand consumer initiated
value co-creation. The program of research focuses on examining User Experience
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Sharing as value co-creation behaviour and identifying the characteristics of the Co-
Creative Consumer. As a result, this body of work will address the following three
research questions:
RQ1: What factors influence consumers to exhibit User Experience Sharing
behaviour?
RQ2: Why do Co-Creative Consumers participate in User Experience Sharing as part
of value co-creation behaviour?
RQ3: What are the characteristics of Co-Creative Consumers?
Research Design
The research first proposes an extended lexicon of SD logic and a theoretical
framework within which to ground the research. This framework has been named the
Experience Co-Creation (ECo) Framework. Informed by the framework, two models
were developed. The first model, the User Experience Sharing Behaviour Model
(UESBM) is based in the theory of Planned Behaviour. The second model, the Co-
Creative Consumer Motivation Model (CCMM) is based in the theory of Motivation,
Opportunity and Ability. The constructs contained in each model are aligned with
SD logic and other relevant literature.
The research uses a quantitative two-study single method design. The research
method involves online surveys to collect data. The sampling frame is Apple iPhone
Apps users who participate in online communities. Data from two separate samples
are collected to examine the relationships proposed in the two models. One sample is
used in study one to calibrate the two structural models and the second sample is
used in study two to confirm the models. The analysis method selected in the two
studies involves structural equation modelling to test the relationships in the two
proposed models, together with K-mean cluster analysis to examine the
characteristics of the Co-Creative Consumer.
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1.5 Summary of Contributions to Theory and Practice
Contribution to the theory
This research makes key contributions to theory by providing both further
conceptual extensions and empirical support to the literature on SD logic.
The first major contribution to theory is the conceptualisation of the Experience Co-
Creation (ECo) Framework embedded with a new lexicon reflecting five gaps
identified from a review of relevant literature related to SD logic.
The second contribution is the conceptualisation of User Experience Sharing that
represents emergent consumer initiated value co-creation behaviour under the ECo
framework.
The third contribution of the research is the conceptualisation of the Co-Creative
Consumer that represents an emerging value-co-creation oriented consumer profile.
The fourth contribution of the research is the presentation of two theoretical models
grounded in the theories of TPB and MOA to answer the overarching research
question “how and why consumers voluntarily participate in a value co-creation
process?” and the secondary research questions posed.
The fifth contribution is that this research is an early study that incorporates and
empirically examines SD logic relevant constructs into TPB and MOA frameworks
to examine a particular area of the logic – that is value co-creation behaviour.
Implications for marketing practice
In terms of High Tech CMOS, the current program of research should help
practitioners to identify Co-Creative Consumers who are more likely to contribute
value driven user generated content and open innovation.
This thesis informs practitioners about how to facilitate and understand factors that
engage with either firm or consumer initiated online communities.
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1.6 Structure of the Thesis
Chapter One provides an overview of the program of research in this thesis. It
provides the background to, and rationale for undertaking the research. The research
context and research question are identified together with a discussion of the
research method undertaken. Finally, a summary of the contributions to theory and
practice are provided.
Chapter Two reviews the literature relevant to the research. The research study sheds
light on SD logic and in particular focuses on consumer initiated value co-creation.
This review also identifies five gaps in the literature that are addressed in the
research. Two emergent concepts, User Experience Sharing and Co-Creative
Consumer, are proposed from the review and research question are posed to better
understand the overarching research question: “how and why do consumer
voluntarily participate in a value co-creation process?”
Chapter Three is the model development chapter. The Theory of Planned Behaviour,
Self Determination Theory and Motivation, Opportunity, Ability Theory were
reviewed. Then two theoretical models were developed with explanations for each
construct. The hypotheses to test the relationship in each of the models were also
identified.
Chapter Four presents the research design and method. This chapter outlines the
method, survey design, sampling and data collection. Method limitations and
delimitations are also discussed.
Chapter Five reports the result of Study One. Using the first data set collected, this
study examines the measurement structure, as well as calibrating the full structure of
each of the two models developed in Chapter Three.
Chapter Six reports the results of Study Two. This confirmatory study re-examines
the structure of the two models using the second data set. This chapter also reports
on the K-means cluster analysis results and outlines the results of hypothesis testing
for both study one and study two.
Chapter Seven provides a discussion of the findings from Study One and Two. The
contributions to theory and practice are also identified. The chapter concludes with
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an identification of the limitations and delimitations, together with recommended
research directions for future study.
1.7 Conclusion
This chapter provides an overview of this research program. It explains research
motivation and rationale. It provides information on the research context and the
research questions proposed. The research method is discussed together with the
analysis approach. A summary of contributions to theory and practice is also
provided. The next chapter provides the literature review.
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CHAPTER TWO LITERATURE REVIEW
2.0 Introduction
The previous chapter presented an overview of this thesis. The purpose of this
chapter is to present an overview of literature relevant to this research program. This
chapter is organised as follows. First, an introduction of Service-Dominant logic (SD
logic) is presented in Section 2.1. Then further review on SD logic is conducted and
five gaps in the literature are identified in Section 2.2 and 2.3. Section 2.4 to 2.7
present an extended lexicon of SD logic. A synthesis framework is proposed in
Section 2.8. Finally, two emergent concepts are introduced in 2.9 and 2.10. A
conclusion is presented in Section 2.11.
2.1 Service-Dominant Logic – An Introduction
Driving the paradigm shift from exchange to value creation (Sheth & Uslay, 2007),
the evolving SD logic seeks to move marketing thinking away from GD logic (Lusch
& Vargo, 2006; Vargo & Lusch, 2004, 2008). Eight foundational premises (FPs)
were originally developed, forming the initial basis of SD logic in 2004. They have
since been revised and extended to ten FPs (Lusch & Vargo, 2006; Vargo & Lusch,
2008), shown in Table 2.1: Service-Dominant Logic Foundational Premises.
Table 2.1 Service-Dominant Logic Foundational Premises
(FP1) Service is the fundamental basis of exchange
(FP2) Indirect exchange masks the fundamental nature of exchange
(FP3) Goods are distribution mechanism for service provision
(FP4) Operant resources are the fundamental source of competitive advantage
(FP5) All economies are service economies
(FP6) The customer is always a co-creator of value
(FP7) The enterprise cannot deliver value, but only offer value propositions
(FP8) A service-centered view is inherently customer oriented and relational
(FP9) All economic and social actors are resource integrators
(FP10) Value is always uniquely and phenomenologically determined by the
beneficiary
Source: (Vargo & Lusch, 2008, p. 7)
SD logic is a mindset proposing that exchange of service is the fundamental concern
of organizations, markets, and society (Alter, 2010; Cova, Ford, & Salle, 2009). SD
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logic is not a theory, but rather, it is a perspective to guide marketing theory and
practice (Lusch & Vargo, 2008; Maglio, Vargo, Caswell, & Spohrer, 2009; Vargo &
Lusch, 2006; Vargo & Lusch, 2008), and serves as a lens through which to view
value creation.
It is suggested here that the ten FPs can be classified into two themes that represent
the essence of SD logic: The first five FPs underpin the concept of a service-centred
orientation, or a service centricity. The remaining five FPs underpin the concept of
value co-creation. These two themes represent the fundamental thoughts of SD logic:
(1) service is always exchanged for service, and (2) value is always co-created.
Service centricity represents the concept that value creation is a function of „service-
for-service‟ exchange, and value co-creation represents the concept that value
creation is always a co-creation process. In the view of SD logic, service refers to the
application of competences for the benefit of another entity or the entity itself, and
co-creation of value refers to value-in-use, which is determined through application
(e.g., use or integration) of resources (Lusch & Vargo, 2006; Vargo & Lusch, 2004,
2008). Further discussion on these two fundamental perspectives of SD logic, service
centricity and value co-creation, are presented below.
2.2 Service-Dominant Logic – Service Centricity and Value Co-Creation
This section looks at the two fundamental perspectives of SD logic: Service
Centricity and Value Co-Creation. In total, five gaps derived from the literature
review are presented in this section.
2.2.1 Service-for-Service Exchange
According to Vargo and Lusch (2006), in order to address relational value creation in
marketing, a shift to a service centred model is essential. This orientation of SD logic
is identified as service centricity. The premise suggests that what lies behind service
centricity is the notion that service is always exchanged for service through
relationships (Vargo & Lusch, 2008). In other words, SD logic sees value creation as
a relational process of „service-for-service exchange‟ (Vargo & Lusch, 2006; Vargo,
Maglio, & Akaka, 2008).
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An exchange of „service-for-service‟ implies all parties are both value-creators and
value beneficiaries (Lusch & Vargo, 2006), and as a result, distinctions between
firms and customers become blurred. According to Lusch and Vargo (2006), “the
offerer/customer and supply/ demand distinction vanishes” (p. 285). Lusch and
Vargo disagree with the notion proposed in the relationship literature of totally
abandoning the concept of exchange. Instead, they suggest that SD logic is about
aligning with relational models of exchange, not eliminating its connection with
exchange (Vargo & Lusch, 2006). They insist that in terms of value creation, service
is more fundamental than relationship (Vargo & Lusch, 2006), and that “service [is]
a process of the co-creation of reciprocal value, where the output of an entity is
viewed as an input into a continuing process of resource integration” (Vargo &
Lusch, 2008, p. 1). This reciprocal process-driven view is entirely different from GD
logic‟s view of value as value-in-exchange where value is created through exchange
of units of output (Vargo & Lusch, 2006). Vargo and Lusch (2006), claim that the
idea that value is derived from exchange of output (i.e., traditional classification of
goods and services) is flawed. Instead, they suggest an input view and see “services
as the application of specialized competences (knowledge and skills) through deeds,
processes, and performances for the benefit of another entity or the entity itself”
(Vargo & Lusch, 2004, p. 2).
Adopting this perspective, the concept of service is proposed as the core of SD logic
(Vargo & Lusch, 2004). It offers a new mindset to draw focus toward value creation
and resource integration, and away from debates between goods and services
(Gummesson, et al., 2010). This service world-view has received wide support in the
literature (Ballantyne & Varey, 2008; Grönroos, 2006; Gummesson, 2008; Lusch &
Vargo, 2006). As Grönroos (2009) points out, service centric logic enables
marketing to go beyond conventional marketing framework and models.
SD logic‟s current service centric view refers to service-for-service exchange, is
process driven, and focuses on reciprocal market phenomena. Such thinking can also
be viewed as a limitation. As mentioned in Chapter One (Section 1.3), when
discussing the research context for this thesis, non-reciprocal based marketing
practices and business models are continuously growing. By non-reciprocal, what is
meant, is marketing practices that are based on sharing (Belk, 2009), and do not
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involve an obligated reciprocity or exchange with service providers and other
consumers such as with open innovation and user-generated content (UGC). This is
especially the case in the context of convergent mobile online services (CMOS), for
example, Facebook, YouTube and Twitter. The need to consider non-reciprocal
market phenomena is also supported by Belk (2009), who notes that such
phenomena are important not only to online, but also offline consumption.
2.2.2 Sharing as Resource Integration
While it is agreed that service is the essence of value creation, this thesis argues that
there is a need to consider the applicability of SD logic in relation to non-reciprocal
market phenomena. This has not been actively addressed or explored in the SD logic
literature to date.
As a result of scholarly discussions after the initial presentation of SD-Logic in 2004,
Vargo and Lusch (2006) noted that it was important to address the idea of resource
integration. This led to the development and further refinement of FP9, that „all
economic and social actors are resource integrators‟, recognising the contributing
roles of individuals and households to marketing (Vargo & Lusch, 2006). However,
Lusch and Vargo (2006) have indicated that this FP still requires further elaboration
and refinement. It is argued in this thesis that the notion of experience sharing, as
part of resource integration, can form part of this ongoing work. An example of
experience sharing would be consumers sharing their personalised ways of using
applications with other consumers in iPhone online communities.
The value of experience sharing is supported by Belk (2009), who notes that sharing
is the most important non-reciprocal market phenomenon. He defines sharing as “the
act and process of distributing what is ours to others for their use, and/or the act and
process of receiving or taking something from others for our use” (p. 717). As such,
sharing (as with user experiences sharing) can be seen as a form of resource
integration in the context of non-reciprocal market phenomena. Sharing, particularly
by social actors, is yet to be considered when accounting for value creation, and
value integration in SD logic. It is argued in this thesis that SD logic has not fully
considered non-reciprocal based service-for-service market phenomena, and that
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considering sharing as a component of resources integration is important. Thus, Gap
One is identified:
GAP One: SD logic has not fully addressed the phenomenon of non-reciprocal
marketing and the role of sharing in value creation.
SD logic distinguishes itself from GD logic by shifting the focus from outputs to
processes. This process focus is drawn from services marketing (Vargo and Lusch
2006). It takes a process-outcome driven approach (i.e., value co-creation process)
(Lusch & Vargo, 2006) rather than taking an outcome-process driven approach, and
sees value as created in terms of the outcomes desired. SD logic currently focuses on
value creation processes without first taking into account possible asymmetric
desired outcomes (e.g., of firms and customers). It can be interpreted that because of
its reciprocal focus, SD logic assumes that actors (firms and customers) within a
value network desire symmetric outcomes (Vargo & Lusch, 2006). This SD logic
perspective is based on the notion that the firm should always facilitate value
creation with customers by focusing on resource integration and competencies to
elevate those value propositions that enhance customers‟ value (Vargo & Lusch,
2004). Vargo and Akaka (2009) acknowledge that firms often set their priorities
based on “efficiency for the benefit of the focal service system” (p. 40), that is,
efficiency for the benefit of themselves. This of course potentially places less
emphasis on the “effectiveness for the benefiting service system” (p. 40), that is, less
emphasis on the effectiveness for the benefiting customer. Such an approach may in
reality indicate that the desired outcomes between firms and customers are
asymmetric. Moreover, Grönroos (2009) argues that customers value service
offerings that fulfil their desired outcomes, not the process of rendering value to
deliver the promise, and that the use of a service by a customer is about becoming
„better off‟ (Grönroos & Ravald, 2011, p. 7). The notion of being „better off‟ is
important because it resembles SD logic‟s „solution mind-set‟ (Sawhney, 2006, p.
367).
Thus, it is argued here that SD logic can benefit from taking an outcome-process
driven approach instead of a process-outcome driven approach. The service-for-
service relationship should be based on the notion of being „better off‟ (Grönroos &
Ravald, 2011; Gummesson, 2008) as an outcome for the economic and social actors,
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rather than the processes that drive efficiency benefits for the firm over the
effectiveness of benefits for the customer. In this thesis, the term „betterment‟ is used
to represent this „better off‟ concept. The notion of „betterment‟ and its relation to an
outcome-process driven view will be further explained in Section 2.6. Thus, Gap
Two is identified:
GAP Two: SD logic needs to consider an outcome-process driven approach, and the
notion of „betterment‟ as the centre of the service-for-service relationship.
2.2.3 From Exchange to Interaction
Grönroos (2006) argues that the service-for-service relationship should go beyond
exchange to consider interaction, and points out that the interaction concept and its
implications for value creation have not been examined sufficiently. Grönroos (2006)
suggests that value creation is based on service-for-service interaction, and makes
the case that interaction should be a substitute for exchange theory. Moreover, he
argues that service-for-service interaction comes from a customer perspective, and
service-for-service exchange comes from a firm perspective. In this instance,
interaction refers to a “… mutual or reciprocal action where two or more parties have
an effect upon on another”, and that during this “… the customers‟ and the firms‟
processes are simultaneously occurring” (Grönroos, 2009, p. 14). Grönroos (2009)
further suggests that market interactions can go beyond the parties who are in direct
contact with each other. He points out that through technological facilitation, there
are new types of interactions where a customer can also interact with systems or
infrastructure (e.g., as with search engines like Google). In short, Grönroos argues
that value creation is a process of service-for-service interaction, where the notion of
interaction refers to activities that two or more parties take, reflecting mutual or
reciprocal actions that influence the course of each other‟s value creation processes.
Grönroos (2006) points out that there is a need to recognise customers as value
creators in the value-creation process. In an earlier work, he argues that customers
can be the „sole creator of value‟(Grönroos, 2006, p. 324). That is, while firms can
actively engage in customers‟ value creation processes and create value for
customers, customers can also create value for themselves (e.g., by initiating the
development of new resources (Grönroos, 2009)). This would be particularly
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relevant in a CMOS context where certain customers initiate the creation of personal
value from the applications (or „Apps‟) provided, but do not directly interact with the
firm providing the apps to share their value creation. This view is further supported
by Baron and Harris (2008), who outline that consumers can be resource integrators
through consumption and co-consumption.
The service-for-service relationship in SD logic needs to go beyond exchange, and
toward interaction, to further recognise consumers‟ active roles as initiators and
mutual participants in the value creation process (a view shared by Grönroos (2006)).
Thus it is argued here that SD logic currently overlooks the customer‟s active role in
terms of taking initiative in creating value in the service-for-service relationship, and
thus, Gap Three is identified:
GAP Three: SD logic has not fully reflected customer initiated value creation
phenomena.
Further insights regarding service-for-service interaction and customers‟ initiation of
value creation will be discussed in the later part of Section 2.4.
2.2.4 Value Creation is Value Co-Creation
This section discusses the other fundamental perspective of SD logic, namely value
co-creation. Originally, Vargo and Lusch (2004) used the term value co-production
to underpin firm-customer relationships, and this was seen as complementary to the
notion of service centricity through service-for-service exchange. This highlighted
consumers‟ active roles in value creation processes, although it objectified
consumers as resources. This notion was criticised for not going far enough to
recognise consumers‟ active roles as resource integrators for themselves (Day et al.,
2004; Peñaloza & Venkatesh, 2006). Prahalad (2004) suggested further work was
needed to understand how customers engage themselves in the value-creation
process. In response, Vargo and Lusch (2006) have updated their views by moving
from value co-production to value co-creation. They suggest that value is always co-
created, and that value creation refers to co-production and co-creation of value
(Lusch & Vargo, 2006). In more recent iterations of SD-Logic Vargo and Lusch
propose FP9, which makes the point that „all social and economic actors are resource
integrators‟ (Vargo & Lusch, 2008) reflecting that value is always co-created .
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Vargo and Lusch (2004) have proposed that the meaning of value creation, termed
value-in-use, is the essence of SD logic. They suggest that service has no value
unless it is used or consumed by a consumer and therefore, the concept of customers
as value co-creators in a value-creating process is at the core of marketing (Lusch &
Vargo, 2006). In a later iteration, they propose value-in-context (Vargo & Lusch,
2008) which is complementary to value-in-use. Value creation refers to service-for-
service as a co-creation process, and was integrated into FP6; that „customers‟ are
always value co-creators‟ (Vargo & Lusch, 2008).
The notion of value co-creation is continuing to evolve in SD logic. Grönroos and
Ravald (2011; 2009) continue to argue that value co-creation requires further
clarification and development, and that FP6 and FP9 are too simplistic. They suggest
that there is a distinct difference between resources (e.g., goods) and value. While
the concept of customers being co-producers of resources with firms is clear,
Grönroos and Ravald note that the concept of customers being co-creators of value
remains fuzzy and confusing. They suggest that questions such as how and for whom
value is created have not been explained under Vargo and Lusch‟s notion of value
co-creation, and claim that "the concept of value co-creation has to date been treated
on a level of abstraction too far removed from theoretical and practical analysis"
(2011, p. 4). These authors outline the need to further conceptualise value co-
creation in terms of "analysis of the scope, content and nature of value co-creation
and of the roles of suppliers and customers in a service logic based view of value
creation" (2011, p. 4). Grönroos and Ravald (2011) suggest that to better understand
value co-creation, it is essential to further analyse customers‟ roles as value creators.
These ideas further highlight the third GAP identified in Section 2.2.3; that SD logic
currently overlooks customer initiated value creation phenomena (Gap 3).
It can be concluded from the discussion above, that although consumers‟ active roles
have been implied in FP6 and FP9, their roles and efforts in terms of initiation of
value creation need refinement and elaboration. As Arnould, Price and Malshe (2006)
suggest, firms must understand how consumers integrate both their and the firm‟s
resources to overcome their operant resource shortcomings. To address this, and to
further explore customers‟ active roles in the value co-creation process, the concept
of value co-creation can be considered from the perspectives of value creation as
P a g e | 37
value-in-use, and the firm-customer co-creation relationship. These are discussed
separately in the following sections.
2.2.5 Meaning of Value Creation
Fundamentally, in the view of SD logic, value creation resides in the notion of value-
in-use (Vargo & Lusch, 2004). Vargo and Lusch state that value is “a joint function
of the actions of the providers and the consumers but is always determined by
consumers” (Vargo & Lusch, 2006, p. 44). The rationale is that “there is no value
until an offering is used - experience and perception are essential to value
determination” (Vargo & Lusch, 2006, p. 44). The meaning of value creation as
value-in-use is relational and reciprocal, and based on perceptions and experiences as
captured in the idea that the customer is always a co-creator of value (FP6) (Vargo &
Lusch, 2008).
In a recent iteration of SD logic, Vargo and Lusch extend the concept of value-in-use,
and propose value-in-context to further address the experiential nature of value as
captured in FP10 (Vargo & Lusch, 2008). Value-in-context encompasses the idea
that a customer‟s meaning of an experience is attached to produce/service bundles in
relation to the context in which they are used (Vargo & Lusch, 2008). In other words,
rather than viewing value as being contained in a product, value-in-use can be
extended to capture the phenomenological experience perceived by a customer
interacting with bundles of products/services in use situations (Woodruff & Flint,
2006). Thus these two notions are complementary rather than mutually exclusive,
and they can be used concurrently.
For the purpose of this thesis, the discussion here is focused on value-in-use because
it provides a new mindset for the contemporary marketing paradigm and theory, and
it opens up the black box of post consumption (Grönroos, 2006). It also highlights
customers‟ essential roles in a value creation process because it implies that the firm
as a service provider, provides a service offering that is used and evaluated by
consumers, and that an offer has no value until it is used by a customer.
Current SD logic (Vargo & Lusch, 2008) refers to service as the application of
competencies for the benefit of others (implying a service provider-service user
relationship). It implies that firms are service providers and provide service for the
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benefit of others (e.g., customers) (i.e., firm centricity), and customers are service
users, and use service for the benefit of themselves. Figure 2.1 is constructed to
illustrate firm-customer relationships under the different interpretations of value
creation processes. It shows how a service provider provides service to a service user
and how a service user co-creates value with a service provider. It illustrates a value-
in-use based service-for-service relationship.
Figure 2.1 Value-in-Use Based Value Co-Creation Relationship
In the following sections, firm and customer perspectives of value creation are
discussed.
Firm initiative efforts toward value creation It is argued that although value-in-
use is built upon the notion service-for-service reciprocal exchange through a
relationship initiated by a firm in a value creation process, this current rationale
seems to ignore that a firm may directly or indirectly create value for customers.
Grönroos (2008; 2009) agrees that the meaning of value creation is captured through
value-in-use but argues also that firms can co-create value (indirectly create value)
with customers through service-for-service interactions. It is argued here however,
that it is also possible that a firm directly creates value for customers. When
consumers respond in exactly the way that is intended by service providers, the value
propositions are fully appreciated by customers as they use the offering. For example,
the iPhone and iPad provide many innovative experiences that consumers would not
have otherwise experienced or sought to experience. When consumers use these
technologies, they may say something like “I did not know what I wanted before, but
this is even better that I could have imagined”. Or, “I didn‟t even know I wanted this,
but now I find it‟s essential”.
Service Exchange
Service interaction
Service ProviderCo-create
Value-in-useService User
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It can be said that firms evaluate the level of resource integration required to be
competitive, and at the same time profitable in the market. This evaluation has an
effect on the level of effort (marketing effort) made in relation to the provision of
service. That is, before value is perceived and evaluated by consumers and becomes
a part of the consumer experience, the level of effort made to create value
propositions embedded in a service offering is made and evaluated by the firms.
Firms can endeavour to integrate these customers‟ efforts into their value creating
process as value co-creators (Prahalad & Ramaswamy, 2004). In this thesis it is
argued that the meaning of value creation in a co-creation process should not be
based on current interpretations of value-in-use (e.g., Lusch, et al., 2007), which is
that “value can only be created with and determined by the user in the „consumption‟
process”. Instead, here it is proposed that the meaning of value creation should take
into account efforts made and evaluated by firms.
Consumer initiative efforts toward value creation Another reason for highlighting
the need to further explore the meaning of value is to account for consumer initiative
efforts toward value creation. It is said that value is not created and delivered by the
supplier, but emerges during usage in the customer‟s process of value creation
(Ballantyne & Varey, 2006; Grönroos, 2008; Gummesson & Gouthier, 2007). In
other words, the value-in-use concept states that value for customers is created
during the use of resources (Grönroos & Ravald, 2011). Thus, it is important to
know how consumers employ their resources to both determine and enhance their
own consumption experiences, individually or collectively (Arnould, et al., 2006;
Baron & Harris, 2008). As noted, the current meaning of value creation in a co-
creation process (value-in-use and value-in-context) implies evaluation efforts made
by customers e.g., value is always determined by consumers depending on the
context (Vargo & Lusch, 2008). It is argued here that SD logic has only partially
reflected the initiative efforts (i.e., evaluation efforts) made by customers in their
value-creating process.
This thesis argues that there are two layers of value co-creation efforts made by
consumers as service providers. The first layer of value co-creation efforts is
captured by value-in-use from a firm dominant service provision perspective (B2B).
Consumers integrate resources through service exchange which most of the time is
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masked by monetary transactions. The second layer, as proposed by this thesis, is
captured by value-in-experience from a consumer centred service provision
perspective (C2C). In this case, consumers as service providers „share‟ their
experiences of integrating resources either due to lack of resources or for betterment.
For betterment outcomes, therefore, this type of value co-creation process is most
likely to occur in a non reciprocal relationship. These efforts have not yet been fully
captured by SD logic.
It can be argued that under SD logic, the relationship between value and value
propositions is a linear function because firms can only produce value propositions,
and that value is a function of value propositions in a service-for-service exchange
process of value creation (Vargo & Lusch, 2008). Any value derived from outside an
exchange process is neglected. This would be the case with value derived from
customers‟ use initiation (Szmigin & Foxall, 1998), and creative ways of using an
offering for a solution that is not intended or offered by service providers (e.g., the
use of Gmail as an online backup hard drive). Such value need not necessarily be
advocated by firms, nor indeed, be legal. Also overlooked would be value derived
from customer-to-customer interaction (Nicholls, 2010), such as that seen with
online communities, virtual worlds like Second Life, or with contributing video
replies on sites like YouTube. It is argued here that in a value co-creation process,
customers‟ efforts are not limited to the evaluation of perceived value propositions,
and so should include initiative efforts made to create and co-create value, value
propositions and offerings.
The point to be made from all of this is that the current meaning of value creation in
SD logic does not explicitly accommodate all efforts made by firms and customers.
The meaning of value creation in a value co-creation process should neither focus on
competencies to exchange resources (GD logic), nor competencies as resources for
exchange (SD logic), instead, it should focus on competencies to integrate resources
as co-creation. The meaning of value creation underpinning value co-creation should
go beyond evaluation based meaning, and towards an effort-based meaning of value
creation. Gap Four is thus identified:
GAP Four: SD logic has not been extended to cover effort-based meaning of value
creation reflecting the reality of value co-creation.
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2.2.6 Customers’ Role as Service Providers
Under SD logic, value is always co-created, and customers are endogenous rather
than exogenous entities to the value co-creation process (Lusch, et al., 2007). This
can be considered in two parts: co-creation of value and co-production (Lusch, et al.,
2007). In terms of a firm-customer relationship, Grönroos and Ravald (2011) argue
that the current notions of value creation and value co-creation, as elaborated in SD
logic, are “confusing” because SD logic “[mixes] service co-production with value
creation” (p. 11). They additionally criticise its “all-encompassing use of the
expression value co-creation” (p. 11), and suggest that the idea that customers are
always value co-creators needs further clarification. Under the interaction
perspective, Grönroos and Ravald (2009) also disagree with SD logic on its premise
that “ firms can only produce value propositions” (Vargo & Lusch, 2004, p. 5).
Instead, customers are value creators, and firms, on the other hand, are value
facilitators and value co-creators (Grönroos & Ravald, 2009). In some cases,
consumers themselves generate new experiences out of the use of service offerings,
and use them in ways that are not intended or proposed by the service providers. In
other cases, service providers do create value for customers when customers have
new experiences outside of their expectations and imaginations.
In more recent iterations of SD logic, Vargo and Lusch (2008) characterise all actors
within service systems as resource integrators (FP9). This extended notion of all
actors as resource integrators implies that value co-creation involves complex
interactions among firms, customers and other value-network partners (Lusch, et al.,
2007; Vargo & Lusch, 2008). With reference to the previous discussion on service
centricity, the service-for-service perspective has been extended to interactions
within and among all service systems (Vargo & Lusch, 2008), and all actors are both
providers and beneficiaries under the service-ecosystems (Vargo, 2009).
This thesis draws away from this firm-customer perspective and the debates on the
confusing nature of value creation roles (cf., value creators, value facilitators or
value co-creators), and focuses on customer initiated value co-creation phenomena
(e.g., co-creating value through customer-to-customer interactions). As mentioned in
Section 2.2.2 (Gap 1) and Section 2.2.3 (Gap 3), SD logic currently also overlooks
customer initiated value creation, and non-reciprocal market phenomena in the
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process of value co-creation. Non-reciprocal marketing phenomena such as open
innovations and user-generated content demonstrate the importance of paying
attention to customer initiated value creation processes. In the context of non-
reciprocal market phenomena, customers provide services to benefit themselves and
others, and thus, customers can be value creators as well as value facilitators in a
value co-creation process. Customers can be service providers in customer initiated
value creation phenomena. The act of initiating value creation can be equated to
service provision for the beneficiaries. SD logic currently overlooks customers‟ roles
as service providers because it focuses on firm initiated reciprocal value creation
phenomena, and does not appear to acknowledge customer initiated non-reciprocal
value creation phenomena. Gap Five is therefore identified:
GAP Five: SD logic currently has not been extended to recognise customers‟ roles as
service providers in the value co-creation process.
2.2.7 Overarching Research Question
The five gaps identified above highlight the need to depart from the ten updated FPs
(Vargo & Lusch, 2008) to explore the context of customer initiated non-reciprocal
value creation phenomena to better understand:
“How and why customers voluntarily participate in a value co-creation process?”.
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2.3 Extending the Service-Dominant Logic Lexicon and Framework
As Gummesson, Lusch and Vargo (2010) have suggested, to avoid “… being too
narrow or not matching the conditions of contemporary and expected future business
and social reality [, …it is essential] to further develop a language and lexicon to
describe the management of service and market economy mechanisms, consistent
with a service-centred mindset” (p. 18).
It is proposed that in terms of service centricity, SD logic can move towards a
balanced centricity (Gummesson, 2008), rather than a customer centricity.
Gummesson (2008) suggests that the current customer centric marketing concept
cannot fully reflect contemporary marketing phenomena and “has not –and cannot –
but partially be implemented in practice” (p. 15). He argues that a balanced centric
lens should be applied to reflect the complexity of marketing which is aligned with
the recent evolution of SD logic that says that actor-to-actor (A2A) orientation
should be adopted to reflect network-based value systems (Vargo & Lusch, 2011).
As a result, it is suggested here that there is an opportunity in this thesis to refine SD
logic by extending the existing lexicon of terms and language used and developing
an additional framework that reflects some of this thinking.
As part of this ambitious project, new additions to the lexicon of SD-logic are
presented: value initiation and value initiator, value-in-experience, and betterment
centricity and betterment outcomes. Firstly, the concept of „value initiation‟ reflects
consumers‟ role as service providers. Secondly, value-in-experience reflects an
effort-based meaning of value creation. Thirdly, betterment centricity reflects an
outcome-process driven lens of a value co-creation process. The following sections
will discuss these additions.
2.4 Value Initiation and Value Initiator
This section will present an argument for introducing the concepts of value initiation
and the value initiator into SD logic. According to SD logic‟s view (FP9), all
economic and social actors are resource integrators (Vargo & Lusch, 2008).
However, as identified in GAP3 and GAP5, SD logic (Vargo & Lusch, 2008) has not
fully addressed customer initiated value creation, and customers‟ roles as service
providers.
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This thesis argues that concepts of initiation of value and value creation already exist
in discussions pertaining to SD logic. For example, Vargo and Lusch (2006) suggest
that firms take initiatives to provide service for their customers. Moreover, Grönroos
(2006) suggests customers initiate their value-generating process using their own
skills and knowledge. However, this is predominantly masked by firm initiations of
value creation. As Gummesson (2007) suggests, market phenomena are more than
firm initiated marketing phenomena (i.e., B2B and B2C), and that customer initiated
marketing phenomena (i.e., C2C and C2B) should also be taken into account. He
proposes a concept of „balanced centricity‟ suggesting that “in long term
relationships and a well-functioning marketplace all stakeholders have the right to
satisfaction of needs and wants” (p. 24). Moreover, value creation takes place in a
network of activities involving not just the firm and the end consumer but multiple
stakeholders, such as employees, shareholders, citizens, and society” (p. 24). In the
same vein, Vargo and Lusch (2011) propose an actor-to-actor (A2A) orientation
which is a further iteration of FP9. Based on the A2A orientation, value creation
becomes a complex exercise (Vargo, 2009) in complex value networks where value
is always co-created by all actors through resource integration and service provision
(Vargo & Lusch, 2011).
Thus, to account for value creation phenomena that are complex and co-creative, this
thesis proposes a unified concept, namely „value initiation‟ to clarify complex
interactions among actors. This reflects that all types of actors can be both providers
and beneficiaries of value creation activities in service-ecosystems (Vargo, 2009).
This thesis suggests that in the view of A2A-oriented and network-based value
systems, „value initiation‟ reflects actors‟ initiative efforts made towards desired
outcomes. It focuses on desired outcomes (cf., outcome-process driven) and helps to
interpret the value creation relationship between actors (e.g., who initiates value
creation and why?) within a value system. In other words, value creation is seen as
service-for-service through initiation. „Value initiation‟ is an essential concept in the
view of the A2A orientation because it focuses on identifying key actors involved in
the process of value creation in A2A value creation phenomena. By highlighting the
starting point of value creation, it moves away from confusing terms like value co-
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creator, which are caught in conventional dyad marketing relationships (i.e., B2B,
B2C, C2C, and C2B).
Value Initiator
The term „value initiator‟ is proposed to capture the notion that firms, customers and
other actors (e.g., government) can be service providers and users of each other‟s
services, in efforts toward achieving desired outcomes. This term is useful to SD
logic because it highlights the fact that in conventional marketing literature, firms are
assumed to be the ones who initiate the value creation process. In turn, it reflects the
notion that (1) customers‟ roles as service providers, and customers‟ provision of
services are for the benefit of self as well as for the benefit of others, and (2) the fact
that firms provide services not only for the benefit of others, but for their own good
as well (Gummesson, 2007; Vargo, 2009).
Further support for value initiation and value initiator
It is recognised that the concepts of change in customers‟ desired value (i.e.,
customer value change), and initiators of change in customers‟ desired value, were
proposed by Flint and Woodruff (2001). This was the first marketing literature to
provide the foundation for conceptualising value initiation and value initiators, and
underpins the continuous nature of value co-creation.
According to Flint and Woodruff (2001), customer value change is related to
customer received value and customer desired value. Customer received value refers
to the value customers actually experience from using a service and is similar to
value-in-use. Customer desired value refers to the value customers want to receive
from service providers. Importantly, customer desired value and customer received
value are dynamic (Flint & Woodruff, 2001), and Flint and Woodruff suggest this
dynamic nature gives room to customer value change. This change is driven by
tension derived from the inconsistency between received and desired value (Flint &
Woodruff, 2001). Based on the foregoing discussion, it is likely that this tension also
derives from asymmetric outcomes between firms and customers, and that it will
always exist. As such, customer value change can be considered as an on-going
rather than a fixed concept.
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It is postulated that there are different ways to reduce this tension. It can come from
either initiative efforts made by firms (Flint & Woodruff, 2001), for example with
the provision of better service, or from initiative efforts made by customers (Flint,
Woodruff, & Gardial, 1997), for example through changing suppliers. Furthermore,
if consumers‟ desired outcomes strongly deviate from what firms can deliver or
facilitate, they may choose to make their own effort with other consumers to close
the gap between received value and desired value. As a result, it is argued here that
the easing of tension not only comes from firm initiated efforts but also from
consumer initiated efforts. Thus, customer desired value changes can be driven by
„nonmarketer controlled forces‟ (Flint & Woodruff, 2001).
Flint and Woodruff (2001) point out that there can be a gap between desired and
received value, and that there is a distinctive role for actors within the value
networks who make efforts to close the gap between desired and received value.
They also suggest that competitive advantage can be obtained if the future state of
knowable initiators of change, who cause customer value change, is better
understood (Flint & Woodruff, 2001). In other words, firms desired outcomes (i.e.,
competitive advantages) can be achieved through collaboration with customers who
are initiators of customer value change. As illustrated in Figure 2.2, the current SD
logic has not fully addressed customer value change. Figure 2.2 depicts the current
focus on value in use which is based on the service-for-service value co-creation
relationship. It does not fully explain “how and why consumers voluntarily
participate in value co-creation?” It does not appear to capture experiences derived
during resource integration or to better understand how and why, and whose
experiences are fed back to value creation processes for betterment outcomes.
Figure 2.2 Service-for-Service Co-Creation Relationship and the Gap
Service ProviderCo-create
Value-in-useService User
Customervalue change
New Topic
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Currently, Flint and Woodruff‟s (2001) work focuses on service – customer
interaction in a B2B context. This thesis suggests that the relevance of their work is
not limited to B2B contexts but can be extended to the context of A2A. Thus,
through an A2A lens, it can be suggested that it is useful to conceptualise „value
initiation‟ as a value creation phenomenon consisting of complex and co-creative
interactions of all actors, and „value initiators‟ as actors who make initiative efforts
to close gaps between received and desired value.
Figure 2.3 shows value co-creation phenomena are on-going interactions between
service providers. It depicts value co-creation as an experience-for-experience
relationship, and presents a new concept, value-in-experience. Its underlying
implications for service-for-service interactions and initiation are line with the notion
of everyone is a co-creator of value (Vargo & Lusch, 2008).
Figure 2.3 Experience-for-Experience Co-Creation Relationship
In short, the initiation and value initiator concepts proposed above, support SD
logic‟s actor-to-actor orientation (Vargo & Lusch, 2011), perceiving value creation
through a network lens. They illustrate a focus on nodes (value initiator) as well as
on links (value creation through initiation) in value networks.
Co-createValue-in-experience
Service ProviderService Provider
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2.5 Value-In-Experience as an Effort-Based Meaning of Value Creation
As presented in Section 2.2.5, the meaning of value creation resonates with co-
creation and underpins the firm-customer relationship through a lens of service-for-
service exchange. Currently, the meaning of value creation is value-in-use, and by
extension, value-in-context (Vargo & Lusch, 2008). This thinking is derived from
the FP6 and FP10 that states the customer is always a co-creator of value based on
the premise that until an offering is used there is no value, and that
phenomenologically, consumer experiences and perceptions are essential to
determining that value. It is argued here that the conceptualisation that the customer
is always a co-creator of value, and the firm is a facilitator of that value implies that
SD logic does not fully account for efforts made by customers who initiate value co-
creation processes, either with other customers or with firms. It is also argued that
currently value-in-use is evaluation-based where value is always determined by
consumers. This does not reflect a co-creative, effort-based view where value
creation is a joint function of integration efforts made by all actors (Vargo & Lusch,
2011).
As a result, value could be conceptualised to include both efforts made in value co-
creation through interaction and evaluation of meaning. It is proposed that value-in-
experience should identify value as a function of value co-creation efforts made by
all actors, including efforts of evaluation. It is suggested here that the term value-in-
experience is more aligned with effort-based value creation. This thesis argues that
value-in-experience is needed to truly reflect (1) a marketing fulfilment mindset
(Grönroos, 2009), and (2) an effort-based meaning of value creation in a value co-
creation process.
Firstly, value-in-experience represents an effort-based meaning of value creation that
is essential to SD logic because it is aligned with a marketing fulfilment mindset
(Grönroos, 2009). Grönroos (2009) argues that marketing is not about marketing a
promise of value but about value fulfilment. This view can be extended to suggest
that the meaning of value co-creation is not only based on the value determination
mindset of making a promise and evaluating that promise (Vargo & Lusch, 2006),
but it should also be associated with fulfilment and efforts made to fulfil the desired
outcomes. It is argued here that the meaning of value creation should imply or reflect
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co-creation efforts made together to fulfil the experience between firms, customers,
and value network partners towards desired betterment outcomes.
Secondly, value-in-experience is grounded in the notion that consumer value is an
interactive relativistic preference experience (Holbrook, 1999) and that value is
embedded in individuals‟ personalised experiences (Payne, et al., 2008). However,
the definition of value-in-experience proposed here goes beyond its current
evaluation based focus (Arnould & Thompson, 2005; Holbrook, 2006; Woodruff &
Flint, 2006) which is an effective, contextual, non utilitarian meaning of an
evaluation outcome of a customer (Payne, et al., 2008). Instead, Prahalad and
Ramaswamy (2004) suggest that there is a move away from those goods and services
centric models to more recent models where value is embedded in experiences. They
also identify that a move to an experience-centric view of co-creation, creates new
and exciting opportunities (Prahalad & Ramaswamy, 2004). It is suggested that SD
logic should go further to adopt an experience centric co-creation view. That is,
value is not derived from the consumption of goods and services, but is embedded in
the actual personalised experiences created through engagement and involvement
(Prahalad, 2004).
This effort-based meaning of value creation is termed value-in-experience and the
following discussion pursues this view further.
Conceptualising Value-in-experience
Value-in-experience is defined here as an effort-based value. The meaning of effort
refers to the provision of experiences derived from resource integration. These
experiences are drawn from individual or collective efforts made to integrate operant
and operand resources in a given context to create new experiences or solutions.
Such relational interactions enable the creation of better value on a continuous basis.
For example, there are more and more non reciprocal sharing phenomena happening
in firm dominant service provision e.g., Facebook and Google. Consumers‟ operand
and operant resources are lift when firms share their experiences.
In the B2B context, Flint and Woodruff (2001) propose that the concept of customer
desired value refers to “the value that customers want to receive from
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products/services and their providers” (p. 322). Customer desired value is different
from customer received value, and personal values because (1) it is broader than
merely desired attributes of service, (2) it is beyond what customers actually
experience through specific product customer interactions, and (3) it is dynamic and
occurs in customers‟ use situations and use occasions (Flint & Woodruff, 2001, p.
323). Personal values, however, are relatively stable and reflect “ultimate end-states
of existence desired by individuals (Flint & Woodruff, 2001). By definition, personal
values refer to “the central, core, enduring beliefs that guide customer behaviours
across situations” (Flint & Woodruff, 2001, p. 323).
This thesis proposes that customer received value is similar to value-in-use (Vargo &
Lusch, 2004), and that customer desired value can refer to value-in-context (Vargo &
Lusch, 2008). It is argued that neither value-in-use nor value-in-context explicitly
reflect higher order changes in customer desired value. They suggest that changes in
customers‟ desired values might be caused by specific factors rather than at random,
and that therefore there is a need to understand these changes. In this thesis, value-in-
experience is conceptualised to capture value derived from efforts made by actors,
which is added to customer received value to achieve customer desired value. In
other words, value-in-experience is the currency of value co-creation (i.e., a driver of
value co-creation) to be exchanged or shared in order to close the gap between
„received value‟ and „desired value‟ (Flint & Woodruff, 2001). It is important to note
that these co-creative efforts can be made within a non-reciprocal relationship. For
example, Facebook shares its energy-efficient data centre design with other firms in
the hope that they might share their experiences about how to improve its design in
return, however such a return is neither guaranteed nor reinforced.
2.6 Betterment Centricity and Betterment Outcomes
In relation to the outcome-process driven approach argued in Section 2.2.2 (see
Gap2), SD logic needs to be extended to cover the essence embedded in being „better
off‟. For the purpose of this thesis, the term „betterment‟ is used to reflect this
concept. The term „betterment centricity‟ is used to represent an outcome-process
driven mind-set. This is intended to replace the current process-outcome driven
service centricity mindset with a focus on closing the gap between received and
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desired value. It reflects value initiators‟ efforts to co-create value with the goal of
achieving desired outcomes.
The concept of betterment centricity is resonant with SD logic. For example,
Grönroos suggests that using a service is about becoming „better off‟ (Grönroos &
Ravald, 2011, p. 7), or customer centric companies are „better off‟ (Gummesson,
2008). Moreover, using a service is a way to leverage resources through resource
integration (or sharing) because of the service emphasis on “the application of
improvable operant resources (i.e., knowledge and skills) as the basis for the co-
creation of value” (Vargo & Lusch, 2006, p. 50). Furthermore, SD logic is claimed
to be pro-environment and pro-education, which means it focuses on improvement of
social and economic conditions (Lusch & Vargo, 2006).
It is proposed here that betterment centricity is a more fundamental concept, which is
embedded in „service‟, and is currently masked by a process driven view of SD logic.
It is argued that taking an outcome-process driven view, the concept of betterment
centricity is essential, because it does not merely focus on service as value creation
through resource integration, but it highlights that the provision of service is for the
benefit of another entity as well as self. The concept of betterment centricity
highlights the importance of understanding why actors participate in value co-
creation, an aspect that needs extension, and consequently its influence on value
creation has not been explored.
In addition, betterment centricity is important because it also highlights that SD logic
resembles a solution mind-set (Sawhney, 2006). It reflects actors‟ desires/
willingness to make efforts to fulfil the gap between received and desired value, and
it is about deriving new experiences. Moreover, the concept of betterment centricity
focuses on the solutions and mutual benefit (symmetric outcomes) that can be
achieved through co-creating value without overlooking the fact that actors may
have asymmetric desired outcomes (tensions) when they initiate/engage in a value
co-creation process.
This thesis proposes that betterment outcomes refer to ultimate desired outcomes that
are mutually beneficial, and are achieved through an iteration of efforts made by
value initiators to close the gap between received and desired value. For example,
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they can refer to betterment of life (consumer initiated) or brand equity and
sustainable profitability (firm initiated). Thus, under betterment centricity,
betterment outcomes are mutually beneficial for firms and customers and can be
symmetric or asymmetric within or among service systems.
Finally, it is important to note that the concept of betterment centricity proposed here
is in relation to outcome drivers. It is different from a process-outcome driven
perspective that suggests “the provision of better service is the goal of most
providers …” (Oliver, 2006, p. 122). Instead, betterment centricity refers to a
mindset reflecting the provision of service to enhance service providers‟ and users‟
desired outcomes. It is the fulfilment of desired outcomes that service is valued for,
not the process of rendering value to deliver promises (Grönroos, 2009).
2.7 An Outcome-Process Driven Value Co-Creation Process
According to Vargo and Lusch, value co-creation can be unfolded into value co-
creation and value co-production in terms of value-in-use (Lusch, et al., 2007). As
noted previously, Grönroos and Ravald (2011; 2009) argue that the current notions
of value creation and value co-creation as elaborated in SD logic are “confusing”
because SD logic “[mixes] service co-production with value creation” (p. 11) as well
as its “all-encompassing use of the expression value co-creation” (p. 11). Moreover,
with value co-creation in SD logic, “marketing is a continuous social and economic
process, largely focused on operant resources …” (Lusch & Vargo, 2006, p. 105).
Value co-creation allows entities within or amongst service systems to leverage
limited resources through co-production, collaboration, co-participation and other
value creating processes (Lusch & Vargo, 2006).
This thesis suggests that since value-in-experience is proposed to underpin the
meaning of value creation, value co-creation needs to be refined to reflect this
meaning of value creation. It has been suggested that value co-creation can be
unfolded further into three processes by experiential timing; pre-experience (cf.
value proposition), customer experience (cf. offering), and post-experience (cf. value)
(Tynan & McKechnie, 2009). This thesis proposes that value co-creation can be
divided into value proposition co-production (Vargo & Lusch, 2004), offering co-
consumption or co-participation (Baron & Harris, 2008; Pongsakornrungsilp &
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Schroeder, 2009), and value collaboration (Beckett & Nayak, 2008). In this thesis,
these three types of value co-creation are termed experience co-creation contexts. An
outcome-process driven value co-creation process is presented in Figure 2.4.
Figure 2.4 An Outcome-Process Driven Value Co-Creation Process
Value InitiatorsValue Initiators
Betterment Outcomes
Betterment Outcomes
value proposition co-productionoffering co-consumptionvalue collaboration
Experience Co-creation
Contexts
2.8 Experience Co-Creation Framework
From the discussion above, this thesis proposes a framework: the Experience Co-
Creation (ECo) framework. Figure 2.5 is a combination of Figure 2.3 and Figure 2.4
presented earlier in Section 2.4, and Section 2.7, and represents the ECo framework.
This framework incorporates and expands the lexicon in SD-Logic to include three
new concepts to underpin the co-creation of value, namely value initiation and value
initiator (Section 2.4), value-in-experience (Section 2.5), and betterment centricity
and betterment outcomes (Section 2.6). The ECo framework shows that value
initiators make efforts toward achieving their desired betterment outcomes. Both
firms and consumers can be value initiators (service providers), and are benefactors
as well as beneficiaries who co-create value-in-experience for themselves and/or for
others (Vargo, 2009). In short, the ECo framework is proposed to explain an
experience-for-experience co-creation relationship illustrating that (1) value
initiation is a starting point of the value co-creation process; (2) value-in-experience
is the currency of the service-for-service relationship as a value co-creation process;
(3) value initiators make efforts toward achieving betterment outcomes, and (4) the
Experience Co-Creation Contexts
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value co-creation process consists of value proposition co-production, offering co-
consumption and value collaboration. The ECo framework is presented in Figure 2.5.
Figure 2.5 Experience Co-Creation Framework
Co-createValue-in-experience
Value InitiatorsValue Initiators
Betterment Outcomes
Betterment Outcomes
value proposition co-productionoffering co-consumptionvalue collaboration
Service ProviderService Provider
Experience Co-creation Contexts
Owing to the research scope, this thesis focuses on the consumer initiated value
creation process. Next, two emergent concepts: User Experience Sharing and Co-
Creative Consumers, are derived from the ECo framework. These are described in
Section 2.9 and Section 2.10.
2.9 User Experience Sharing
Initially it was Prahalad and Ramaswamy who started paying attention to customers‟
roles and personalised experiences in value co-creation (Prahalad, 2004; Prahalad &
Ramaswamy, 2000, 2004, 2004). Vargo and Lusch (2006) replaced value co-
production with value co-creation in SD logic and suggested that a value co-creation
mindset is essential to underpin the firm-customer value creation relationship.
However, much of this attention has been limited to firm initiated value co-creation
(e.g., B2B or B2C). Thus, customer initiated value creation has been overlooked (as
identified in GAP3, Section 2.2.3). It is recognised that not every consumer wishes
to make the effort to engage extensively in co-creation processes. MacDonald and
Uncles (2009) suggest that there are consumers who desire value but do not wish to
Experience Co-Creation Contexts
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expend effort to engage in its co-creation. Thus, they may be satisfied with a
standard product, rather than engaging in the effort required for customisation that
potentially leads to greater value for themselves and the firm. There is a need to
better conceptualise and understand those consumers who do engage in consumer
initiated value co-creation behaviour.
Consumers may initiate value co-creation behaviour because of growing non-
reciprocal marketing phenomena (as noted in GAP1, Section 2.2.2). Non-reciprocal
market phenomena have become prominent in today‟s marketing environment,
especially in the online context (e.g., convergent mobile online services). The
Internet empowers consumers by enabling the possibility for dialogue through
virtual networks (Grønmo & Ölander, 1991; Pitt, Berthon, Watson, & Zinkhan, 2002)
that go beyond B2C to include C2C interactions outside the firms sphere of influence
(Hsu, et al., 2007; Lee, et al., 2006; Limpisook, 2009; Macdonald & Uncles, 2007).
It is argued here that the increasing level of non-reciprocal marketing phenomena
(e.g., open innovation and user-generated content; (Ahonen, Antikainen, & Mäkipää,
2007; Di Gangi & Wasko, 2009) highlights the need to conceptualise customer
initiated non-reciprocal value creation behaviour.
2.9.1 Conceptualising User Experience Sharing
User Experience Sharing (UES) can be considered a type of consumer-to-consumer
interaction (Martin & Pranter, 1989; Nicholls, 2010). However, in the context of this
thesis, UES focuses on interaction as consumer value co-creation as suggested by
Grönroos (2006) rather than on consumer encounters as seen in conventional
services marketing (Nicholls, 2010). Consumers often engage in co-creation
behaviour to evaluate and enhance their consumption experiences as co-consumers
(Baron & Harris, 2008). Moreover, they continually build upon these experiences for
further value co-creation.
By definition, experience implies not only emotional evaluation (e.g., the first
experience of snow), but also competence (e.g., knowledge and skill) and active
engagement (e.g., a lesson taught by experience) (thefreedictionary.com). As
Prahalad (2004) suggests, value is embedded in experiences which are a result of co-
creation. Therefore, this thesis adopts a broad definition of experience that is not
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limited to evaluation but also includes competence and engagement efforts made by
the individual. By adopting a broad definition, it accommodates/captures the issue
raised by McDonald and Uncles (2009), regarding making or not making an effort
towards the co-creation of value. Moreover, a broad definition of experience also
qualifies consumer experiences (i.e., knowledge and skill) to be seen as resources
that are essential to value co-creation (Prahalad & Ramaswamy, 2004). Sharing these
experiences through interactions with others demonstrates consumers co-creatively
integrating resources (as discussed in Section 2.2.2), that is, sharing as resource
integration. Extending this thinking, Belk (2009) suggests that sharing is a pro-social
and non-reciprocal behaviour. In online communities, this is particularly pertinent
since sharing or integrating resources is largely undertaken by members to achieve
better outcomes or to enhance wellbeing (e.g., Gruen, Osmonbekov, & Czaplewski,
2007). As a result, the concept of UES is proposed as a consumer initiated, non-
reciprocal value creation behaviour. It reflects value-in-experience (as discussed in
Section 2.5), as an effort-based meaning of value creation. It represents initiative
efforts made by consumers to create value with other consumers in a non-reciprocal
context.
2.9.2 Comparing UES with Customer-to-Customer Know-How Exchange
The concept of customer-to-customer (C2C) know-how exchange proposed by
Gruen, Smonbekov, Czaplewski (2007), can be broadened through developing and
testing the User Experience Sharing concept. C2C know-how exchange captures
customers‟ efforts in co-creating better value in the firm facilitated context. In prior
research, it has been identified and referred to as “value creation through customer-
to-customer exchange [that] occurs when the perceived benefits of a company‟s
offering are increased as a result of customer interactions with one another” (Gruen,
et al., 2007). According to Gruen et al. (2007), a better way to achieve value creation
is to facilitate C2C know-how exchange among the customers of an organisation‟s
offerings. Firms can then enjoy the positive outcomes of the facilitation process.
Importantly, and differing from Gruen‟s proposal, UES focuses on customers‟ life
experience derived from their efforts made (i.e., value-in-experience) beyond their
interactions with offerings (i.e., value-in-use).
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C2C know-how exchange notes that consumers can enhance value through sharing
information based on their knowledge and prior experience. However, based on the
ECo framework, User Experience Sharing can happen in three experience co-
creation contexts, and is not limited to information exchange. These three contexts
were previously identified as value proposition co-production, offering co-
consumption, and value collaboration. Additionally, User Experience Sharing
resonates within concepts that (1) focus on sharing experiences derived from a
consumer‟s knowledge and skills arising from use initiation (Szmigin & Foxall,
1998), (2) emphasise value-in-experience, including new and personalised
experiences, therefore going beyond the knowledge and prior experience associated
with the offering; (3) extend to not only increasing perceived benefits derived from
better uses of value propositions offered by firms (e.g., those functions that may not
be known by users), but more specifically linked with personalised and unexpected
value and experiences created beyond firms‟ value propositions. This thesis argues
that User Experience Sharing is a concept that is broader than C2C know-how
exchange. It is a more suitable candidate to represent the consumers‟ non-reciprocal
value co-creation behaviour, resulting from sharing as the integration of resources
derived from consumers‟ co-created experiences.
2.9.3 Comparing User Experience Sharing to Word-of-Mouth
This thesis positions UES as having a different focus to word-of-mouth (WOM),
thus broadening how researchers can think about this important aspect of consumer
interaction, particularly in the online environment. Kozinets, de Valck, Wojnicki,
and Wilner (2010) review the history of WOM. They suggest that a significant body
of WOM research focuses on how to identify and influence opinion leaders who are
trusted or regarded as credible sources by others. While recognising that WOM is a
type of consumer-to-consumer interactive communication, current research often
focuses on how marketing messages, received through advertising and promotions,
are conveyed from an opinion leader to other consumers. This reflects a linear model
with the focus on whether marketing information is transferred in a more or less
faithful way from the company, through the opinion leader to other consumers, or is
altered through interactions between consumers.
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More recent developments in WOM research focus on co-production in consumer
networks (Kozinets, et al., 2010); a direction that is more resonant with the
fundamental premises of SD logic and which can be enabled by the extensive
diffusion of Internet technology. Marketers now focus on directly influencing active
consumers (one on one) through relationship building, which might include seeding
and „co-producing‟ marketing messages in consumer networks, such as online
communities. This approach recognises that marketing messages are no longer
passed through a linear WOM channel but co-produced in WOM networks. Kozinet
et al.‟s (2010) empirical findings in WOM networks, in this case blogs following
product seeding, showed that WOM can be classified into four types, namely
evaluation, explanation, embracing, and endorsement. Thus, WOM can be viewed
more as a type of evaluation-based behaviour, derived from a co-production of
marketing messages and meanings. To broaden this understanding of WOM, UES is
conceptualised as a type of effort-based, rather than evaluation based, value co-
creation behaviour that is initiated by consumers in a network. It is more directly
derived from their interactions and experiences with other consumers as well as with
the product or service and is outside the control of the marketers, instead of through
product offerings and/or marketing messages being seeded into a network. From the
discussion above, it is argued that while current WOM research recognises the
network world–view, as noted in the literature review, recent WOM developments
continue to focus on marketers‟ efforts to co-produce messages and meanings with
consumers, rather than consumer initiated efforts made in co-creating value through
sharing their own experiences.
From an SD logic perspective, UES reflects the behaviour that consumers undertake
to co-create value through sharing resources (i.e., resource integration). Most
importantly, it drives outcomes derived from consumers‟ initiative efforts (which are
outside the company‟s control or beyond the firms‟ intentions) to improve value-in-
experience and the wellbeing of other online consumers. For example, in a CMOS
community, consumers share their experiences to co-consume or co-produce
applications (APPs) with other consumers to fulfil their personalised needs. From the
discussion above, the first proposition is proposed: User Experience Sharing is a co-
creative effort initiated by consumers to derive value-in-experience. For the purpose
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of this research, this thesis will examine factors that influence consumers to exhibit
this behaviour to answer the first research question:
RQ1: What factors influence consumers to exhibit User Experience Sharing
behaviour?
2.10 Co-Creative Consumers
It is well recognised that while consumers might belong to an online community
related to a firm‟s product or service offering, not every individual actually shares
information. Even among those who do share, not every individual shares
information that can be considered to be truly value co-creating in ways that lead to
betterment outcomes or that helps others to further develop competencies and
knowledge. Thus, as identified by McDonald and Uncles (Macdonald & Uncles,
2009) not every consumer desires to be involved in co-creation, which is in line with
the notion of the value initiator discussed in Section 2.4.
Under the ECo framework, value initiators make initiative efforts to co-create value-
in-experience towards their desired betterment outcomes. As this research focuses on
a consumer initiated value co-creation process, the concept of the Co-Creative
Consumer is proposed to represent those value initiators who are willing and capable
of co-creating value-in-experience through User Experience Sharing in a customer
initiated value co-creation process (i.e., either through interaction with firms (C2B)
or other customers (C2C)). Aligning with SD logic reasoning, Co-Creative
Consumers are those consumers who are capable of applying their competences/
willingness to provide service (i.e., application of competences) for the benefit of
other consumers and themselves in everyday life. For example, an iPhone online
forum member who shares his/ her way of combining two or more Apps to create a
personalised solution for a desired betterment outcome (e.g., book five star
accommodation at a rate less than the listed price for his/ her next overseas trip) may
be considered a Co-Creative Consumer.
Importantly, the Co-Creative Consumer is a broader concept than the prosumer
(Ritzer & Jurgenson, 2010). The term prosumer was first used by Toffler (1980) to
describe people who produce some of their own goods or services for their
consumption even though they could buy them in the marketplace. The notion
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prosumer has been used in SD logic to highlight that consumers are endogenous
members of a value network (Gummesson, 2007; Lusch & Vargo, 2006). As
Gummesson (2007) suggests, “within the service-dominant logic the customer is a
prosumer and co-creator of value” (p. 15). Here, Co-Creative Consumers are those
who perform User Experience Sharing in their everyday life. Therefore, Co-Creative
Consumers not only co-produce but also co-consume or collaborate with firms and
other consumers, and more importantly, do so in a non-reciprocal context. Co-
Creative Consumers who share their user experiences do not seek immediate returns
or benefits but focus on making an effort (i.e., User Experience Sharing) toward co-
creation value-in-experience for (long term) betterment outcomes. The concept of
the Co-Creative Consumer focuses on sharing experiences derived from the use of
offerings regardless of what is provided by firms, self, other consumers, or is co-
created with others, rather than on the production of offerings for other reasons (e.g.,
fun, uniqueness). Finally, value co-creation is not only co-production, but also co-
creation of value (Lusch, et al., 2007). Gummesson (2007) suggests that value co-
creation not only refers to co-production through firm-customer interaction but also
the co-creation of value through customer-to-customer interaction. Thus, from the
discussion above, this thesis argues that the Co-Creative Consumer is a broader
concept than Prosumer.
McDonald and Uncles (2007) identify Consumer Savvy and have developed a scale
to test the characteristics that underpin this concept. The six key characteristics of
Consumer Savvy were identified as 1) technological sophistication, 2) interpersonal
network competency, 3) online network competency, 4) marketing literacy, 5)
consumer self efficacy, and 6) consumer expectations. This newly developed scale
has been shown to be capable of identifying the Consumer Savvy construct and its
characteristics in a cross cultural context (e.g., Garnier & Macdonald, 2009). The
construct and scale has also been used to determine levels of desire to engage in
value co-creation activity. This direction is compatible with earlier discussions about
User Experience Sharing in a value co-creation context, indicating that not every
consumer is likely to engage in value co-creation, regardless of whether it is with the
firm or with other consumers in an online community.
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The work by McDonald and Uncles (2007) regarding consumer savvy forms an
important addition to the co-creation literature by identifying the levels of savviness
that consumers may have in relation to their interactions with a firm, its products and
its marketing messages (e.g., Macdonald & Uncles, 2009). However, a perceived
limitation to the concept of Consumer Savvy is that its focus is still predominantly
on firm/customer interaction in terms of value propositions offered. The
characteristics related to network competencies still retain the notion of seeking
information or help rather than providing information/ service or initiating help in
these networks. Consumer Savvy is thus informative to competencies underpinning
User Experience Sharing but not the Co-Creative Consumer.
The concept of the Co-Creative Consumer, developed in the current research,
reflects consumer engagement in value co-creation not only in the context of value
proposition co-production, but also value collaboration and offering co-consumption
as depicted in the ECo framework.
In summary, it is argued that the concept of Co-Creative Consumer is boarder than
the concept Prosumer because it represents consumers‟ roles as co-creators of value
rather than as co-producers. Additionally, it broadens the work undertaken to
determine Consumer Savvy, by introducing further characteristics that identify the
Co-Creative Consumer who makes the effort to initiate activity that co-creates value
for other consumers in an online community.
From the discussion above, the second proposition is proposed: Co-Creative
Consumer is a consumer value initiator who performs UES to co-create value-in-
experience. For the purpose of this research, two further research questions are raised:
RQ2: Why do Co-Creative Consumers participate in User Experience Sharing as part
of value co-creation behaviour?
RQ3: What are the characteristics of Co-Creative Consumers?
Together, Section 2.9 and Section 2.10 have explored the conceptualisation of two
constructs being examined in the research in this thesis, namely User Experience
Sharing and Co-Creative Consumer.
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2.11 Summary
At the beginning of this chapter, a „zoom-out‟ (Vargo & Lusch, 2011) approach was
adopted to explore how Service-Dominant Logic (SD logic) can be adopted to
inform the overall research question: “How and why do consumers voluntarily
participate in a value co-creation process?” First, SD logic was reviewed, in terms of
service centricity and value co-creation. Second, from the literature review, five gaps
were identified, and an outcome-process driven „SD logic friendly lexicon‟ (Lusch &
Vargo, 2006) and the corresponding framework were presented. This thesis argues
that SD logic has not fully accounted for: Gap1: non-reciprocal marketing
phenomena; Gap 2: customer initiated value-creation process; Gap 3: betterment as
the centre of service (and asymmetric outcomes between actors within and amongst
service systems); Gap 4: effort-based meaning of value creation, and Gap 5:
customers as service providers. As a result, this thesis proposes four concepts: (1)
value initiation and value initiator, (2) value-in-experience, and (3) betterment
centricity and betterment outcomes (4) three experience co-creation contexts.
Consequently, a corresponding framework was also developed, namely the
Experience Co-Creation (ECo) Framework, to accommodate a broader range of
marketing phenomena than are currently accommodated in SD logic (i.e., non-
reciprocal value co-creation: open innovation and user-generated contents).
After zooming out and establishing the outcomes driven ECo framework, this
chapter adopted a „zoom-in‟ approach and focused attention back on the outcome-
process driven, rather than process-outcome driven value co-creation process
grounded within the ECo framework. For the purpose of this thesis, the focus in on
customer initiated value co-creation phenomena. Accordingly, two emergent
concepts were theorised to underpin the integrity of this research, and accordingly
the research questions were derived. Consequently, two emergent concepts, User
Experience Sharing, and Co-Creative Consumer were introduced and discussed in
this chapter. Two research propositions were identified in the literature review; (1)
User Experience Sharing is a co-creative effort initiated by consumers to derive
value-in-experience, and (2) Co-Creative Consumers are consumer value initiators
who perform UES to co-create value-in-experience.
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Finally, three research questions are presented:
RQ1: What factors influence consumers to exhibit User Experience Sharing
behaviour?
RQ2: Why do Co-Creative Consumers participate in User Experience Sharing as part
of value co-creation behaviour?
RQ3: What are the characteristics of Co-Creative Consumers?.
The research scope of this thesis specifically investigates, conceptualises and
empirically examines the efforts consumers make and the role of these consumers in
a process of customer initiated non-reciprocal value co-creation within the proposed
Experience Co-Creation (ECo) framework. These questions can be answered through
research conducted in the consumer initiated value co-creation context (i.e.,
convergent mobile online services (CMOS) related to consumer-to-consumer
interactions within online communities that share information related to using Apple
iPhone applications, known as Apps).
In the next chapter the discussion will focus on presenting the development of two
theoretical models.
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CHAPTER THREE THEORETICAL FRAMEWORKS AND
MODEL CONCEPTUALISATION
3.0 Introduction
In this chapter, two theoretical models are developed to examine the concepts of
User Experience Sharing (UES) and Co-Creative Consumers, and to address the
research questions posed. The first model is grounded in the Theory of Planned
Behaviour (TPB) with the integration of Self-Determination Theory and represents a
User Experience Sharing Behaviour Model (UESBM). The second model is based
on Motivation, Opportunity, and Ability Theory (MOA) and represents a Co-
Creative Consumer Motivation Model (CCMM).
The chapter is organised as follows. Firstly, the first theoretical framework, Theory
of Planned Behaviour, is discussed in Section 3.1 followed by the discussion of the
theory, self-determination presented in Section 3.2. Then, the second theoretical
framework, the MOA framework, is described in Section 3.3. Constructs in the two
models are identified and discussed together with their hypothesised relationships in
Section 3.4 and Section 3.5. Each theoretical model is also presented at the end of
the corresponding sections. A summary of the chapter will be presented in Section
3.6.
3.1 Theory of Planned Behaviour
For the purpose of this study, the Theory of Planned Behaviour (TPB) is used as the
theoretical framework to test the proposed User Experience Sharing behaviour in the
online community context. Proposed by Ajzen (1991), TBA is an extension of the
Theory of Reasoned Action (TRA), and has become one of the renowned conceptual
frameworks used in behavioural studies (Ajzen, 2001; Armitage & Conner, 2001).
Armitage and Conner (2001) conducted a meta-analysis, and their findings support
the application of TPB to predict intentions and behaviour. Under TPB, an
intentional behaviour is guided by three kinds of beliefs: behavioural beliefs,
normative beliefs, and control beliefs. According to Ajzen (2002, p. 665),
behavioural beliefs refer to “beliefs about the likely consequences or other attributes
of the behaviour”, reflecting an individual‟s favourable or non-favourable attitude
towards performing the behaviour. Normative beliefs refer to “the normative
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expectations of other people” and reflect social pressure from particularly important
others. Control beliefs refer to “the presence of factors that may further or hinder the
performance of the behaviour” and refer to the level of difficulty perceived by an
individual to perform the behaviour. In aggregate, these three factors give rise to an
intention to exhibit or not exhibit a behaviour. With given opportunity, sufficient
intentions will lead to the actual behaviour. Figure 3.1 depicts a TPB model.
Figure 3.1 Theory of Planned Behaviour
Attitude toward the behaviour
Subjective Norm
Perceived Behavioural
Control
Intention Behaviour
Source: Ajzen (1991)
Notably, Perceived Behavioural Control (PBC) is a key element in TPB. According
to Ajzen (1991), PBC represents a non-motivational aspect influencing intentions
and actual behaviour. It accounts for expected constraints on required opportunities
and resources (e.g., time, money, skills, and cooperation of others). PBC is an
essential predictor not only for its differentiation between TPB and TRA, but
importantly, for its influences on both intentions and actual behaviour (Ajzen, 1991;
Ajzen, 2001, 2002). PBC has been found to be a valid independent predictor of
intentions and behaviour in a variety of research domains (Armitage & Conner,
2001). Ajzen (2002) suggests that while intentions may serve as an immediate
antecedent of actual behaviour, PBC may also directly influence actual behaviour.
This is because volitional control of the behaviour may be limited in reality, and
therefore PBC serves as a proxy of actual (i.e., volitional) control to explain
behaviours that were not under an individual‟s full volitional control. In this case,
PBC provides an explanation of when intentions fail to predict behaviour (Ajzen,
1991; Madden, Ellen, & Ajzen, 1992). As a result, TPB provides a unique and useful
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measurement of rational behaviours that its predecessor, TRA, could not.
Additionally, because PBC reflects an individual‟s judgement on potential
limitations of actual (i.e., volitional) control over the behaviour, Madden, Ellen et al.
(1992), suggest that the relationship between PBC and intentions may vary subject to
the behaviour and the situation.
TPB is considered appropriate for testing UES for the following four reasons: (1)
User Experience Sharing is an intentional behaviour which refers to efforts made
towards achieving desired betterment outcomes; (2) PBC may be useful to examine
competencies which are essential to value co-creation according to SD logic; (3)
TPB has been used extensively in online consumer behaviour studies (Chen, Chen,
& Kinshuk, 2009). Cheung, Zhu et al.(2003) conducted an extant literature review of
114 articles, and found that TPB is one of the most applied theories in the study of
online consumer behaviour. The final reason TPB is used to test UES is (4) TPB has
been used as a valid framework to test sharing behaviour in the organisational
context, namely knowledge sharing (Chen, et al., 2009; Chennamaneni, 2007;
Minbaeva & Pedersen, 2010). Minbaeva and Pedersen (2010) adopt TPB and
compare individual knowledge sharing behaviour in two competing firms. Their
findings indicate that the use of rewards relates negatively to attitudes toward
knowledge sharing, the use of reciprocal schemes relates positively to subjective
norms, and the use of communication mechanisms relates positively to perceived
behavioural control. Chen et al. (2009) integrate social network ties with TPB to test
knowledge sharing behaviour in virtual learning communities. They find that
attitudes toward knowledge sharing, subjective norms, web-specific self-efficacy and
social network ties are positively related to both knowledge sharing intentions and
actual behaviour.
A further variable that has been connected with TPB is that of autonomous
motivation. This can be found within Self-Determination Theory, which is discussed
in the next section.
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3.2 Self-Determination Theory
Self-Determination Theory (SDT) is proposed by Deci and Ryan (1985; 2000), and
concerns autonomous motivation and controlled motivation. Autonomous motivation
refers to engaging in an activity volitionally, and controlled motivation refers to
engaging in an activity as a result of pressure that can come from outside sources
which are both intentional and in contrast to „amotivation‟, which refers to a lack of
intention and motivation (Gagné, 2009; Gagné & Deci, 2005). Gagné (2009),
specifies that autonomous motivation is associated more positively than controlled
motivation with positive outcomes, and proposes incorporating autonomous
motivation with TPB to account for not only the level or amount of knowledge
sharing, but also the quality of knowledge sharing. There are two reasons to employ
autonomous motivation: (1) UES is a voluntary behaviour, and (2) it is proposed in
this thesis that under the Experience Co-Creation (ECo) framework, consumers
participate in UES for betterment and for desired betterment outcomes. For the
purpose of this study, SDT is incorporated with TPB to develop the proposed User
Experience Sharing Behaviour Model.
3.3 Motivation, Opportunity, and Ability Framework
The motivation, opportunity, and ability (MOA) framework is used in this thesis to
develop the Co-Creative Consumer Motivation Model. The theory was originally
proposed by Maclnnis, Moorman and Jaworski (1991) to understand the influences
on communication effectiveness regarding the processing of brand information from
advertisements. The three key components of the framework are motivation,
opportunity, and ability. In Maclnnis, Moorman and Jaworski‟s study (1991),
motivation refers to “consumers' desire or readiness to process brand information in
an ad.” Opportunity refers to “the extent to which distractions or limited exposure
time affect consumers' attention to brand information in an ad.” Ability refers to
“consumers' skills or proficiencies in interpreting brand information in an ad.” The
authors proposed that the MOA components would relate positively to the level of
consumers‟ brand information processing, and in turn affect outcomes of consumers‟
brand attitude and brand learning and memory.
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Two studies have applied the MOA framework to test C2C know-how exchange as
an information source for value creation in online and offline contexts (Gruen,
Osmonbekov, & Czaplewski, 2006; Gruen, et al., 2007). Both tested how the three
components in the framework influence the outcomes (i.e., the overall value of the
firm‟s offering and loyalty intentions.). The results indicated that the MOA
framework is valid for examining C2C knowledge exchanges. UES similarly refers
to a type of value co-creation behaviour, and thus the MOA framework is also
appropriate for investigating why consumers take initiative efforts (e.g., in User
Experience Sharing to co-create value with others).
Next, two theoretical models, User Experience Sharing Behaviour Models (UESBM)
and Co-Creative Consumer Motivation Model (CCMM), grounded in the theories
discussed above will be introduced respectively in Section 3.4 and Section 3.5.
3.4 User Experience Sharing Behaviour Model
The User Experience Sharing Behaviour Model (UESBM) was conceptualised to
underpin the notion that UES is a volitional behaviour of consumers who are willing
and capable of sharing user experiences with others. There are seven constructs in
total in the UESBM. The five constructs are associated with TPB: (1) Attitudes
toward UES, (2) Subjective Norm, (3) Consumer Competence representing PBC, (4)
Intention to Engage in User Experience Sharing, and (5) UES behaviour are
employed in the UESBM. Additionally, two constructs reflecting „autonomous
motivation‟ (Deci & Ryan, 2000): Enjoyment in Helping Others and Consumer
Empowerment are incorporated in the UESBM. They are employed to strengthen the
testing of volitional aspects of UES behaviour, as conceptualised by Gagné (2009).
In particular, autonomous motivation is a type of intrinsic motivation. It refers to
volitional engagement in an activity either because it is fun, enjoyable or personally
meaningful to one‟s volitional value system (Deci & Ryan, 2000; Gagné, 2009).
Gagné (2009) suggests that previous studies have indicated that autonomous
motivation has a positive influence on enduring volitional behaviours such as
volunteering and recycling behaviours. Füller, Mühlbacher and Jawecki (2009),
suggest that both empowerment and enjoyment have a strong impact on the
consumers‟ intentions to continually participate in virtual co-creation tasks (i.e.,
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future Internet-based new product development projects). Thus, Consumer
Empowerment and Enjoyment in Helping Others are used here as autonomous
motivations underpinning UES as a voluntary behaviour.
Next, constructs of the UESBM are discussed, and corresponding hypotheses are
presented.
3.4.1 Attitudes toward User Experience Sharing
Attitudes toward User Experience Sharing refer to the degree to which one evaluates
the behaviour favourably or unfavourably based on an individual‟s evaluation of
engaging in User Experience Sharing (Ajzen, 1991; Gagné, 2009). Attitude towards
the behaviour is based on an individual‟s evaluation of engaging in behaviour of
interest (Ajzen, 1991). If an individual is in favour of the behaviour, it is more likely
to give rise to intentions and the chance of performing the behaviour (Armitage &
Conner, 2001). Retained from its predecessor, TRA, attitude has been recognised as
a good indicator to predict intentions of performing a social behaviour (Ajzen,
Fishbein, & Heilbroner, 1980). For example, Kuo and Young (2008) conducted a
survey with teachers of a Taiwanese virtual professional community to investigate a
knowledge sharing model. The results suggested that attitudes toward knowledge
sharing positively and significantly influenced knowledge sharing behaviour. The
researchers also conducted a longitudinal study to evaluate and compare the
performances of the three key components within the TRA and TPB framework.
They concluded that attitudes toward knowledge sharing positively and strongly
influenced intention to share knowledge in all proposed models. Chen et al. (2009)
used student convenience samples to test an integrated TPB model and reported a
strong association between attitudes toward knowledge sharing and knowledge
sharing intention. Based on the discussion above, a positive relationship is expected
between attitudes and intentions to share knowledge online. Thus, hypothesis U1 is
developed.
Hypothesis U1. Attitudes toward UES relate positively to Intention to Engage in
User Experience Sharing.
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3.4.2 Subjective Norm
A Subjective Norm (SN) reflects an individual‟s belief in the approval (or
disapproval) of engaging in the behaviour of interest from important referents, either
individuals or groups (Ajzen, 1991; Madden, et al., 1992). Armitage and Conner
(2001), conducted a meta-analysis of TPB, and their findings indicated that SN,
retained from its predecessor TRA, was the weakest TPB component relating to
intention. They pointed out that single-item measures may be the reason for the weak
relationship. Nevertheless several empirical studies have provided evidence to
support the theory that SN is a key component of knowledge sharing behaviours
(Chen, et al., 2009; Chennamaneni, 2007; Kuo & Young, 2008; Minbaeva &
Pedersen, 2010). For example, Kuo and Young (2008) tested TRA, TPB and revised
TPB, and found that SN positively influences intention. Chen et al. (2009) tested
factors influencing knowledge sharing in virtual learning communities and reported a
positive and significant relationship between SN and intention. Thus, hypothesis U2
is developed.
Hypothesis U2. Subjective Norm relates positively to Intention to Engage in User
Experience Sharing.
3.4.3 Consumer Competence
The concept of competence is similar to operant resources which is essential to SD
logic. The main reason to adopt TPB rather than TRA as a theoretical framework to
examine UES behaviour is because the theory includes a competence element,
namely PBC (Gagné, 2009). Because TPB is used as a theoretical framework to
theorise and empirically test UES as value co-creation behaviour, PBC is represented
by a concept more aligned with value co-creation, namely „consumer competence‟
that is measured by an adapted consumer savvy scale (Macdonald & Uncles, 2007).
In line with SD logic, consumer competence represents consumers‟ operant physical
resources referring to physical skills (Arnould, et al., 2006) and social operant
resources referring to “networks of relationships with others” (Arnould, et al., 2006,
p. 93). It reflects the capability of consumers to configure their operant resources to
employ available operand resources in order to achieve their life projects and goals
(Arnould, et al., 2006). A consumer competence related study was conducted by
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Macdonald and Uncles (2007), and consequently a multi-dimensional construct,
Consumer Savvy, was proposed, reflecting the connectivity and empowerment of a
consumer. A cross-cultural study conducted by Garnier and Macdonald (2009)
provided further validation of this construct. These researchers proposed a more
parsimonious scale and reported that three dimensions, Technological Sophistication,
Online Network Competency, and Expectations Dimensions, functioned well in a
cross-cultural study. They further suggested that the parsimonious scale will provide
benefit to researchers who intend to reduce survey length. Importantly, they point out
the Consumer Savvy scale is SD logic consistent and would be useful to assess
consumer competence in a networked, global marketplace. Macdonald and Uncles
(2009) investigated the relationship between consumer savvy and value co-creation
and found that consumer savvy is highly correlated with co-creation activities.
Because UES is a type of value co-creation behaviour, two types of competencies,
Technological Sophistication (TS) representing consumers‟ operant physical
resources and Network Competence (NC) representing consumers‟ social operant
resources, are drawn from the research on Consumer Savvy and are incorporated to
reflect an overall consumer competence of UES as discussed below.
3.4.3.1 Technological Sophistication
Technology Sophistication (TS) reflects specific knowledge (competence) of savvy
consumers. TS refers to consumer ability to adopt and use complex and convergent
technologies in their everyday lives (Macdonald & Uncles, 2007). Macdonald and
Uncles (2007), suggest that consumers with high TS are more engaged, informed,
and active in the online marketplace. Notably, they also found that individuals with
higher TS levels are more likely to engage in co-creation behaviour (Macdonald &
Uncles, 2009).
Complex and convergent technologies make possible multiple uses, and
personalisation of service offerings (Gill, 2008). While this may trigger „use
initiation‟ (Foxall, 1994, 1995), it also demands more cognitive resources for better
use (Page & Uncles, 2004). As argued, one of the reasons for consumers to co-create
is a lack of resources, including cognitive resources. According to Alba and
Hutchinson (1987), increasing consumer knowledge means reducing cognitive
efforts and increasing automaticity. Consumer knowledge refers to familiarity and
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expertise including: (1) “the number of product- related experiences that have been
accumulated by the consumer”; and, (2) “the ability to perform product-related tasks
successfully” (Alba & Hutchinson, 1987, p. 411). TS can be seen as consumer
knowledge, and therefore consumers who have higher TS scores may be more likely
to share their use initiation and personalisation experiences with other consumers in
an online community (through co-creation behaviours to enhance consumption
value). Thus they may not only intend to share their experiences, but would actually
be sharing them.
3.4.3.2 Network Competence
Network competence reflects the importance of social ties in consumer-to-consumer
(C2C) interactions. There are two types of network competences: 1) Interpersonal
Network Competencies; and, 2) Online Network Competencies (Macdonald &
Uncles, 2007). First, Interpersonal Network Competence (NW) refers to the general
ability of consumers to utilise their personal network and strong ties to enhance
effectiveness in relation to service consumption and engagement in markets
(Macdonald & Uncles, 2007). Second, Online Network Competence (NO) refers to
consumers‟ ability to utilise their virtual online networks and weak ties to enhance
effectiveness in relation to service consumption and engagement in markets
(Macdonald & Uncles, 2007). Macdonald and Uncles (2007, 2009) suggest that
consumers may benefit from their ability to harness their interpersonal and online
networks, including through: (1) easier access to collective knowledge to make
informed choices; (2) encountering new ideas and perspectives through virtual
networks which influence their perceptions and behaviours; and, (3) becoming
empowered through cooperation with other consumers in the virtual community.
Technological sophistication and network competency together can enhance
information transparency, and therefore empower consumers in the marketplace
(Macdonald & Uncles, 2007). Consumers are more likely to seek information within
the social network to which they belong (Yu & Singh, 2003). A recent study
(Goldenberg, Han, Lehmann, & Hong, 2009), explores the role of hubs in diffusion
and adoption. The findings suggest that hubs are a type of people who have an
exceptionally large number of social ties in the diffusion process, in a large network,
and with multiple adoptions. There are two types of hubs; innovative hubs and
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follower hubs. Consumers as hubs, although not necessarily innovative, are more
likely to be early adopters in the adoption/ diffusion process (Goldenberg, et al.,
2009). Goldenberg et al. (2009) point out that people who have a large number of
ties to other people have a strong influence on diffusion processes in their social
network. In an organisational context, Chen et al. (2009) employed the TPB
framework to propose a model presenting factors influencing knowledge sharing
behaviour. They concluded that social network ties positively and significantly
influence knowledge sharing intentions. Thus, it is argued here that consumers who
are capable of maintaining a larger number of social ties are more likely to engage in
UES. From the discussion above, hypotheses U3 and U4 are developed.
Hypothesis U3. Consumer Competence relates positively to Intention to Engage in
User Experience Sharing.
Hypothesis U4. Consumer Competence relates positively to User Experience
Sharing.
3.4.4 Intention to Engage in User Experience Sharing
An individual‟s intention is a central factor in TPB, reflecting how much effort they
might exert and how willing they may be to try to perform a given behaviour (Ajzen,
1991). Ajzen (1991) found that intention accounts for significant variance in actual
behaviour in condition to an individual having volitional control to decide to perform
or not to perform a given behaviour. In a meta-analytic review, Armitage and Conner
(2001) suggest that intention is a better predictor of actual behaviour than other key
components in TPB. Thus, the following hypothesis U5 is stated.
Hypothesis U5. Intention to engage in User Experience Sharing relates positively to
User Experience Sharing.
3.4.5 Enjoyment in Helping Others
Similar to Evangelism in word-of-mouth (WOM) (Subramani & Rajagopalan, 2003),
enjoyment has been suggested as a type of autonomous motivation (Sheldon & Elliot,
1998). Previously, it has been used to underpin the volitional perspective of the
behaviour motivated by genuine interest (Sørebø, Halvari, Gulli, & Kristiansen,
2009). For the purposes of this thesis, the Enjoyment in Helping Others construct is
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used as autonomous motivation because it has been reported to have a significant
impact on knowledge sharing behaviour (Kankanhalli, Tan, & Wei, 2005; Lee, et al.,
2006; Wasko & Faraj, 2005; Yu, Lu, & Liu, 2010). According to Kankanhalli, Tan
and Wei (2005), Enjoyment in Helping Others refers to a state of intrinsic enjoyment
from helping others without expecting anything in return, and this meaning is in line
with Altruism. Lee, Cheung et al. (2006) explored reasons why customers perform
knowledge sharing in web-based discussion boards using an online questionnaire
(i.e., open questions) to collect qualitative data, and found that the enjoyment of
helping others is the most common reason for participants (87.5%) to participate in
knowledge sharing. Yu, Lu and Liu (2010) conducted an online survey investigating
factors that facilitate voluntary knowledge sharing in online communities, and also
indicated that enjoyment derived from helping others has a positive and significant
impact on weblog knowledge sharing behaviour. Notably, TPB has been used by
Chou and Chang (2008) for examining the impact of enjoying helping indirectly on
knowledge creation through attitude. Their findings show a positive but weak
association. To determine whether this construct has a direct impact on intentions
and behaviour, the following hypotheses U6a and U6b are developed.
Hypothesis U6a. Enjoyment in Helping Others relates positively to Intention to
Engage in User Experience Sharing.
Hypothesis U6b. Enjoyment in Helping Others relates positively to User Experience
Sharing.
3.4.6 Consumer Empowerment
Consumer Empowerment has been referred to a result of consumers‟ subjective
perceptions of increasing control (Wathieu, et al., 2002). This thesis adopts a more
recent definition of consumer empowerment which refers to a positive subjective
state as a result of a mental comparison of a consumer‟s abilities relative to existing
or previous abilities to fulfil their needs and desired outcomes (Hunter, Garnefeld,
Kucuk, Gau, & Viswanathan, 2008). Rogers, Chamberlin, Ellison and Crean (1997)
suggest that empowerment is realised through three factors: (1) self-esteem-self-
efficacy as well as optimism and control over the future; (2) actual power; (3)
righteous anger and community activism. They summarise the literature regarding
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psychological empowerment and identify the definitions of empowerment as follows:
(1) a combination of innate desires, willingness and a sense of personal competence
to take action in the public domain (Zimmerman & Rappaport, 1988); (2) the action
taken by powerless individuals to become empowered (McLean, 1995); (3) a process
of internal restructuring to take control over and influence one‟s livelihood, social
and organisational structure (Segal, Silverman, & Temkin, 1995); and (4) a process
of development, facilitation and sanction to enable individuals to become
autonomous (Staples, 1990). In the context of consumer-to-consumer value co-
creation, consumer empowerment is likely to be related to community activism and
the perception of the ability to influence one‟s livelihood and social structure.
It is suggested that the empowerment of consumers, and of individual effort has
become hard to ignore in marketing (Beckett & Nayak, 2008; Peppers & Rogers,
1993), especially in terms of SD logic (Sweeney, 2007). Various sources contribute
to inevitably increasing consumer empowerment in today‟s market (Denegri-Knott,
Zwick, & Schroeder, 2006). For example, the Internet empowers consumers because
it allows consumers to obtain information faster and to make more distant social
connections, which contributes to the improvement of transparency of information
(Harrison, Waite, & Hunter, 2006; Howells, 2005; Kucuk, 2009; Pires, Stanton, &
Rita, 2006; Shaw, Newholm, & Dickinson, 2006; Wathieu, et al., 2002). Literature
also suggests consumers are empowered in a firm-customer value co-creation
relationship because firms are more willing to co-create with consumers (Kambil,
Friesen, & Sundaram, 1999; Payne, et al., 2008) in return for opportunities to obtain
competitive advantage (Lusch, et al., 2007; Prahalad & Ramaswamy, 2004). Self
service, leading to need for personalisation may well arouse a sense of consumer
empowerment (Grönroos, 2007).
As noted, UES is a type of initiative effort made by consumers in a value co-creation
process. Today‟s consumers share a more proactive role in the value co-creation
relationship as they are more empowered, due to contributions from various
consumer empowerment sources. As a result they are more competent, capable of,
and willing to help each other. As such, it is proposed here that empowered
consumers will actively engage in UES. On the other hand, a mastery goal (i.e., the
betterment of life) is about improvement and personal development and argues that it
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will encourage information sharing (Marijn Poortvliet, Janssen, Van Yperen, & Van
de Vliert, 2007). Rogers et al. (1997) find that an increasing sense of empowerment
comes from the prosperity of quality of life instead of a high level of involvement. It
is argued in this thesis that consumers who share their user experiences are
motivated by their sense of empowerment to take action for the betterment of life in
general. In a TPB theoretical framework this means that Consumer Empowerment
can be tested as a factor influencing both Intention to Engage in UES and UES
behaviour. Thus, hypotheses U7a and U7b are developed.
Hypothesis U7a. Consumer Empowerment relates positively to Intention to Engage
in User Experience Sharing.
Hypothesis U7b. Consumer Empowerment relates positively to User Experience
Sharing.
In the discussion above, each construct of the UESBM is described with the
hypotheses mapped out to show the relationships to be tested. The UESBM model is
presented in Figure 3.2. Table 3.1 summarises the hypotheses for the UESBM.
Figure 3.2 User Experience Sharing Behaviour Model (UESBM)
Attitudes toward UES
Subjective Norm
Intention to Engage in UES
User Experience
Sharing
HU1HU1
HU2HU2
HU5HU5
Consumer Competence
HU3HU3
HU4HU4
Autonomous Motivation
HU7bHU7b
HU6bHU6b
HU7aHU7a
HU6aHU6a
Enjoyment in Helping Others
Consumer Empowerment
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Table 3.1 Hypotheses for User Experience Sharing Behaviour Model
HU1 Attitudes toward UES relate positively to intention to engage in UES.
HU2 Subjective Norm relates positively to Intention to engage in UES.
HU3 Consumer Competence relates positively to intention to engage in UES.
HU4 Consumer Competence relates positively to User Experience Sharing.
HU5 Intention to engage in knowledge sharing relates positively to User Experience
Sharing.
HU6a Enjoyment in helping others relates positively to intention to engage in UES.
HU6b Hypothesis 6b. Enjoyment in helping others relates positively to User Experience
Sharing.
HU7a Consumer Empowerment relates positively to intention to engage in UES.
HU7b Consumer Empowerment relates positively to User Experience Sharing.
3.5 Co-Creative Consumer Motivation Model
In the previous section, the UESBM was conceptualised to show that UES is
volitional behaviour of consumers who are willing and capable of sharing user
experiences with others. In this section, a further model grounded in the Motivation,
Opportunity, Ability (MOA) framework (Maclnnis, et al., 1991) is conceptualised to
identify the characteristics of and motivations that drive Co-Creative Consumers
(those who perform value co-creation focused UES). The model has been named the
Co-Creative Consumer Motivation Model (CCMM).
The structure of the CCMM covers two domains. First, it employs factors reflecting
co-creation perspectives of the MOA framework to further underpin UES as
consumers‟ value co-creation behaviour. Second, individual characteristics are
incorporated to examine the characteristics of the Co-Creative Consumer. In addition,
this complementary model will also help to further understand the emergent UES
behaviour.
The MOA inspired constructs to be used in this new theoretical framework are:
Consumer Citizenship (i.e., representing co-creation motivation), Newness (i.e.,
representing co-creation opportunity), and Relating Needs (i.e., representing co-
creation ability). These MOA components reflect an SD logic mindset. Additionally,
four components are incorporated to examine the personal characteristics of the Co-
Creative Consumer, as antecedent constructs.
In the following sections, details of each CCMM construct will be discussed.
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3.5.1 Opportunity to Co-Create Value – Newness
Opportunity is one of the key components in the MOA framework proposed by
Maclnnis, Moorman and Jaworski (1991). The interpretation of Opportunity varies
depending on the research context. Originally, the concept referred to opportunities
for processing information which is measured by the disruption of cognitive
responses to brand information in an advertisement (Maclnnis, et al., 1991).
The term, Newness, is used here as co-creative opportunity in the CCMM. In the
B2B context, “co-creation opportunities are strategic options for creating value
(Payne, et al., 2008, p. 88)”. Gruen et al. (2006), interpret Opportunity as a situation
that is conducive to, or lacks impediments to, achieving a desired outcome. Gountas
and Mavondo (2005), interpret Opportunity as referring to the availability of time
and favourable social or business conditions. In terms of C2C value co-creation,
Opportunity refers to Newness, which occurs when desired experiences are
actualised (through efforts made by consumers) and become available to consumers
for sharing; for example value derived from innovative and personalised uses of
service offerings. Andrew and Smith (1996) use the concept to measure meaningful
novelty in terms of creativity and solutions to everyday (business) problems. Thus
the experiences of using mobile online services may be perceived by consumers as
not original at all or completely new to them. Thus hypothesis S1 is developed.
Hypothesis S1. Newness relates positively to Value Oriented User Experience
Sharing.
3.5.2 Motivation for Co-Creation Value – Consumer Citizenship
The term, Consumer Citizenship, is used here as co-creative motivation in the
CCMM. Consumer citizenship studies are in their infancy. Growing interest in
consumer marketing research indicates that consumer citizenship influences
consumer behaviour in ways that redefine the relationship between consumers and
service providers, especially in terms of communications and dialogues (e.g., blogs
and eWOM) (Dimitrova & Atanasova, 2009; Kaye, 2006). The concept of
citizenship has been adapted in the contexts of organisations; studies show that the
organisation‟s citizenship behaviour is positively associated with employees‟
feelings of psychological ownership of the company (Van Dyne & Pierce, 2004).
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Moreover, Bolino and Turnley (2005) suggest that in the organisational context
citizenship behaviour is associated with personal initiative, and altruism.
The notion of consumer citizenship is adapted from Boyte and Skelton‟s definition
(2004) and refers to the ongoing contribution of consumer citizens‟ motives to
provide marketplace solutions for themselves and others through cultivating their
skills and values in everyday community contexts. A „consumer citizen‟ is someone
who has a sense of responsibility when they engage in any marketing or
consumption phenomenon as a consumer (Maignan & Ferrell, 2001; Thoresen,
2002). Consumer citizenship may influence co-creative dialogues (i.e., information
exchanges) to enhance experiences (Jaworski & Kohli, 2006) in the context of a
consumer-to-consumer setting. In other words, consumer citizens make efforts to co-
create with other consumers beyond actions such as expressing their voices (Griffin
& Hauser, 1993), or voting (Shaw, et al., 2006).
For the purpose of the construct used in the model, Consumer Citizenship is defined
as consumers‟ motives to contribute and collaborate with others in communities,
through resource sharing; for example, sharing of time and experiences. It is
suggested that in this Co-Creative Consumer Motivation Model, consumer
citizenship reflects the co-creation motivation of the Co-Creative Consumer. It
captures the co-creative nature of Co-Creative Consumers who are not only more
active in pursuing their own needs, but also show passion and are prepared to share
their experiences with others who have similar interests. Moreover, they understand
that there are other consumer citizens who will also share the same view.
Here it is argued that consumer citizens believe that non-reciprocal sharing will have
a collective benefit to the community and that they and others will benefit from their
initiatives in sharing their experiences. Thus, it is proposed that consumers who have
a high level of consumer citizenship would be more likely, not only to perform UES,
but to do so with the idea of benefiting other consumers in mind. Thus hypothesis S2
is developed.
Hypothesis S2. Consumer Citizenship relates positively to Value Oriented User
Experience Sharing.
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3.5.3 Ability to Co-Create Value – Relating Needs
Relating Needs is used here as co-creative ability in the CCMM. Grönroos (2006;
2009) suggests that in the process of generating value, consumers apply their skills
and knowledge to integrate resources available to them. Ballantyne and Varey (2006)
suggest that learning together over time may result in better relationship quality.
These views are further extended by suggesting that User Experience Sharing, a
value co-creation activity, is about consumers sharing experience and learning
together over time. It is argued here that if consumers in a social network are capable
of sharing good quality of use experiences (value-in-experience based experiences),
they will have an on-going value co-creation relationship with other social and
economic actors who share experiences within the community or in that value
network. In turn, on-going value creation activities, such as User Experience Sharing,
will be beneficial to all parties and useful for sustaining further value-creating
activities (Ballantyne & Varey, 2006). SD logic posits that competencies such as
skills and knowledge are the fundamental elements that support value co-creation
(Vargo and Lusch, 2004). Relating Needs is proposed as a value co-creation based
consumer competence.
The term, Relating Needs, refers to consumers‟ ability to integrate their physical,
social and cultural operant resources (Arnould, et al., 2006) for the benefit of self or
of others. It is related to the concept of „value co-creation enablers‟ including
“knowing through knowledge renewal (knowledge generation and application),
relating through relationship development, and communicating through dialogue and
other forms of communicative interaction (Ballantyne & Varey, 2006, p. 337)”. As
consumers spend time in shared participation in activities, observation, and
discussion with others close to them (i.e., friends and online community members),
they are more likely to learn about each other (Miller, 1990) and rely on relationship
involvement when anticipating each other‟s preferences (Gershoff & Johar, 2006). In
the online world, acquaintances that share weak ties (e.g., Twitter followers and
Facebook friends) may know each other better than those in the offline world who
share strong ties (e.g., family and friends). Gershoff and Johar (2006), say that
accepting a recommendation can be similar to accepting a gift and that helps to
enhance a relationship.
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In further support of the Relating Needs construct, Nuttavuthisit (2010), explains
how and why consumers co-create and suggests four interrelated categories of
consumers‟ co-creative practices, including; (1) participation-for-self, (2) creation-
for-self, (3) participation-for-others, and, (4) creation-for-others. These four practices
help to better understand consumers‟ interactions and involvement in a consumer co-
creative process. Relating Needs is associated with the concept „marketplace
metacognition‟, which refers to:
“everyday individuals' thinking about market-related thinking. This includes
people's beliefs about their own and others' mental states and processes and
their beliefs about other people's beliefs on those topics as these beliefs
pertain to the specific domain of marketplace cooperation and manipulation”
(Wright, 2002, p. 677).
It is about “people's beliefs about their own mental states and the mental states,
strategies, and intentions of others as these pertain directly to the social domain of
marketplace interactions” (Wright, 2002, p. 677).
From the discussion above, it is suggested here that Relating Needs as a type of
consumer competence is distinct from other consumer competences (e.g., consumer
savvy) because it takes both self and others' needs into account. Consumers who are
capable of relating their needs to self and others, (known as Relating Needs) are
likely to share personalised knowledge and their own experiences that derive both
self-oriented and other-oriented values (Holbrook, 1999), and in turn are more likely
to lead to on-going value co-creation relationships (i.e., perform on-going User
Experience Sharing within a community). Thus, it is suggested that to be able to
participate in on-going value co-creation (i.e., UES), customers should be competent
at both Relating Needs of Self and Relating Needs of Others.
3.5.3.1 Relating Needs of Self
Relating needs of self refers to an individual‟s ability to personalise and to
understand their personal needs. Recently, more personalised features, products and
services have been offered to customers, especially through the Internet and for
CMOS users. In turn, such capabilities stimulate users‟ demand for further
personalisation (Oulasvirta & Blom, 2008). It is about tailoring products and services
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either for a group of users or individuals to better fit the user (Göker & Myrhaug,
2002). The definitions of personalisation are varied and depend on the applied
context (Vesanen, 2007). For example, according to Blom and Monk (2003),
personalisation is defined as “the process that changes the functionality, interface,
information content, or distinctiveness of a system to increase its personal relevance
to the individual” (p. 193). Personalisation can also be interpreted as: (1) a process,
(2) the attribute of personal relevance, (3) the attribute of change, (4) either
consensus or uniqueness. In terms of technology-based personalisation,
Personalisation Consortium (2005) cited in (Vesanen, 2007, p. 410) defines it as:
“Personalization is the use of technology and customer information to tailor
electronic commerce interactions between a business and each individual
customer. Using information either previously obtained or provided in real-
time about the customer, the exchange between the parties is altered to fit that
customer‟s stated needs as well as needs perceived by the business based on
the available customer information”.
It is suggested that personalisation enhances consumer value when the benefits of
personalisation exceed costs (Simonson, 2005; Vesanen, 2007). If consumers want to
enhance value (for self), they will have a greater need for personalisation of their
product or service offerings. Consumers with a need for personalisation or who
better understand their personalised needs, also show their concern for the relevance
of offerings to their daily life instead of merely accepting whatever offerings are
provided. In other words, they develop the need for personalisation and become
competent in relating needs of self. Therefore, it is argued that these consumers,
whose use patterns are driven by the need for personalisation, are more likely to
participate in value co-creation (i.e., User Experience Sharing).
3.5.3.2 Relating Needs of Others
Relating Needs of Others refers to an individual‟s ability to understand and associate
others‟ needs to one‟s own experiences in order to provide solutions to the benefit of
others. It is argued here that Relating Needs of Others is an essential competence if
consumers play a role of service providers.
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Relevance is the key and service providers often rely on customers‟ feedback to
provide insights to appropriate consumers‟ needs in the cycle of product
development (Carroll, Howard, Vetere, Peck, & Murphy, 2002). Customer
orientation is applied to address the importance of anticipating customers‟ needs in
the context of service encounters and delivery (Donavan, Brown, & Mowen, 2004).
It is argued that no one knows what customers want and need better than those
consumers who actually use the services themselves. If those customers who share
their experience not only understand their needs and relevant solutions but are also
capable of relating these needs and solutions to the benefit of others, it would
certainly enhance value-in-experiences (i.e., towards achieving betterment of life).
This thesis suggests that if individuals believe they are competent in relating to the
needs of others, then they are more likely to share their user experiences.
From the discussion above, it is hypothesised here that Relating Needs is a co-
creative competence that enables consumers to participate in on-going value co-
creation (i.e., UES). Customers should be competent at both Relating Needs of Self
and Relating Needs of Others. Thus the following hypotheses S3 are developed.
Hypothesis S3. Relating Needs relates positively to Value Oriented User Experience
Sharing.
Consumer Characteristics
In the following section, four consumer characteristics are incorporated in the Co-
Creative Consumer Motivation Model as the antecedents of MOA factors. There are
two justifications for the inclusion of personal characteristics as antecedents of
motivation and ability constructs. Firstly, Maclnnis, Moorman and Jaworski (1991),
show that pre-exposure MOA levels can be influenced by consumer characteristics
or situational characteristics; secondly, Gountas and Mavondo (2005), found that
personal characteristics influence a behaviour indirectly through the MOA
components. Personal characteristics can include either personality or traits.
Personality refers to an individual‟s patterns of “feeling, thinking, and behaving”
(John, Robins, & Pervin, 2008, p. 548, ), whereas traits are “consistent patterns of
behaviour” (John, et al., 2008, p. 11,). They are “a series of adjectives or short
phrases” (Mowen and Minor, 2001), used to describe an individual‟s predispositions
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that “differ from another in a relatively permanent and consistent way” (Hilgard et
al., 1975), cited in Hirunyawipada and Paswan (2006, p. 184). In order to craft the
characteristics of Co-Creative Consumer and better understand a particular group of
people, shared characteristics associated with a given behaviour, using a combination
of relevant personal characteristics/traits should be examined to understand their
impact on behaviour (Lastovicka & Joachimsthaler, 1988; Mowen & Minor, 2001).
For the purposes of this research, the following four characteristics have been
selected: (1) Use Innovativeness (2) Mavenism (3) Personal initiative (4)
Communality. They are discussed as follows.
3.5.4 Use Innovativeness
In this model, the term Use Innovativeness is specified as a consumer characteristic.
It refers to consumers‟ tendencies to create innovative solutions in their everyday
lives. Use Innovativeness is proposed by Hirschman (1980) and refers to the
deployment of an already adopted product or service to solve new consumption
problems. A similar concept, use-initiation, was originally proposed by Foxall (1994)
and refers to a consumer who initiates novel functions for an existing product
(Szmigin & Foxall, 1998). Foxall suggests that the concept use-initiation
accommodates a range of alternative applications including not only the radically
inventive changes but also more mundane alternative functions. It matches the idea
that convergent mobile online services can be used to create alternative or
personalised solutions in consumers‟ every day routines. Similar to Szmigin and
Foxall‟s view (1998), use-initiation and Use Innovativeness are used interchangeably
here. In this thesis, the term, Use Innovativeness is used instead of use-initiation to
reflect the personal characteristic.
Use innovative consumers are those who demonstrate innovative behaviours that use
a service in ways not originally intended. For example, something the designer did
not think about, as suggested in Carroll (2004), in relation to mobile phone services
when consumers adapt and modify their use of an innovation and continue to do so
after the innovation is produced (Carroll, Howard, Vetere, Peck, & Murphy, 2001).
These creative use behaviours can involve either modification “…of tools in order to
ensure that they are useful in the context of their everyday activities, and that the
ways in which they use the tools redefines the activities” (Issroff, Scanlon, & Jones,
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2007, p. 19), or behaviour which relates to “the deployment of an already adopted
product or service to solve new consumption problems” (Hirschman, 1980, p. 288).
According to Shih and Ventakesh (2004), use innovativeness (as defined by Price &
Ridgeway, 1983), is different from innate innovativeness. Roehrich (2004) suggests
that use innovativeness has two expressions: (a) using a product in a different way,
or (b) knowing all the different uses of a specific product. An individual who is use
innovative is more likely to positively respond to multiple uses that cover a range of
alternative applications, from radically inventive changes, to more mundane
alternative functions (Foxall, 1994). Use Innovativeness also implies a characteristic
pertaining to a person who is equipped with knowledge and expertise of a specific
product. For the purposes of the research, the construct Use Innovativeness will
characterise Co-Creative Consumers who are stimulated by proactively seeking and
actualising ways to fulfil their personal needs in their day-to-day routines. Therefore,
the following hypotheses are stated:
Hypothesis S4. Use Innovativeness relates positively to Relating Needs.
Hypothesis S4a. Use Innovativeness is a characteristic of Co-Creative Consumers.
3.5.5 Mavenism
Mavenism is a type of consumer characteristic which refers to the consumer
tendency to become especially involved in the marketplace (Goldsmith, Clark, &
Goldsmith, 2006). The term, Mavenism originated from „Market Maven‟ literature
and is used here as one of the consumer characteristics incorporated in the CCMM.
The concept Market Maven was originally proposed by Feick and Price (1987) to
characterise an influencer with general marketplace rather than product specific
expertise (cf., opinion leader (Chan & Misra, 1990)). It is a measurement related to
marketplace behaviours and consumer characteristics (Feick & Price, 1987). By
definition, a Market Maven refers to a diffuser of marketplace information (Feick &
Price, 1987). They are people who have broader knowledge about “many kinds of
products, places to shop and other facets of markets, and initiate discussion with
consumers and respond to requests from consumers for market information” (Feick
and Price 1987, p. 85).
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According to Williams and Slama (1995), the term Market Maven also refers to a
particular type of consumer group who has an important influence on other
consumers. Clark, Goldsmith, and Goldsmith (2008) point out that several studies
show that Mavenism: (1) is positively related to a consumer‟s personality in terms of
openness to experience (Mooradian, 1996); (2) has a positive relationship with
consumer innovativeness and opinion leadership (Goldsmith, Flynn, & Goldsmith,
2003); (3) represents a strong need to share information to help others (Walsh,
Gwinner, & Swanson, 2004); (4) is positively related to attraction to technology
(Geissler & Edison, 2005); (5) is positively influenced by tendency to conform and
consumer need for uniqueness (Clark & Goldsmith, 2005); (6) relates to both
creative choice counter-conformity and status consumption (Goldsmith, Clark, &
Goldsmith, 2006); (7) is positively related to innovativeness and negatively related
to resistance to change (Andrews & Benedicktus, 2006).
Importantly, Clark et al. (2008), suggest that marketing researchers and practitioners
should go beyond demographics and behaviours, and study Mavenism to identify the
psychological characteristics of consumers. They argue that like varying levels of
consumer innovativeness, consumers may also have different tendencies toward
Market Mavenism. In terms of interactions between service providers and consumers,
Clark et al. (2008) suggests that marketing managers and companies can better
communicate with consumers, and consumers can better receive their marketing
messages, if managers learn about Mavenism. He further suggests that Market
Mavenism is a psychological construct associated with motivations and personalities
(Clark, et al., 2008).
It is argued here that instead of being characterised as motivated by the status of
being an expert in a specific product domain (opinion leader), or the novelty of a
specific product (early adopter), Co-Creative Consumers are motivated by their
desire for betterment outcomes. Thus, their motivations are related to sharing
information that will make others better off. Like Market Mavens, they are no longer
communicating information about particular products or their sellers (Westbrook,
1987 cited in Steffes & Burgee, 2009, p. 880) or the messengers who deliver
marketing messages cultivated by marketers. Therefore, the construct of Mavenism
is included to highlight the characteristics of Co-Creative Consumers. They are those
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individuals who can apply general knowledge and experience with markets in their
everyday lives instead of applying product specific knowledge and expertise (cf.,
opinion leader).
This thesis makes the claim that Co-Creative Consumers will be those who are
equipped with the qualities of Mavenism, but are different to Market Mavens
because they share their own user experiences rather than general marketplace
information. Although there is no current study suggesting a relationship between
Mavenism and Relating Needs, previous research has indicated that Market Mavens
have a mediation effect between market helping behaviour and its predictors, e.g.,
general altruism and market place involvement. It is therefore proposed that
Mavenism is a characteristic of the Co-Creative Consumer. Thus the following
hypotheses are specified:
Hypothesis S5. Mavenism relates positively to Relating Needs.
Hypothesis S5a. Mavenism is a characteristic of Co-Creative Consumers.
3.5.6 Personal Initiative
Personal Initiative was introduced into the management literature by Frese, Kring,
Soose, and Zempel (1996). Personal Initiative refers to “a [behaviour] syndrome
resulting in an individual taking an active and self-starting approach to work and
going beyond what is formally required in a given job” (Frese, et al., 1996, p. 38).
The concept was first used to underpin how active individuals influence
organisational effectiveness. Frese et al. (1996), further describe personal initiative
as being outcome driven, proactive, long-term focused, goal-directed and action-
oriented.
In a management context, Frese et al. (1996) suggest that individuals may take action
to redefine tasks to achieve a goal not specifically listed in their job description. This
is similar to the case in marketing where customers may select or adjust service
offerings according to a given context in order to achieve better outcomes. In this
case, it could be argued that these types of customers actively create value through
such actions. Therefore, it is suggested that within the view of SD logic, personal
initiative can be inferred to characterise the proactive aspect of the Co-Creative
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Consumer, that is, the likelihood of them initiating interactions rather than simply
interacting with others‟ initiatives (e.g., the firm). The personal initiative concept has
been tested (e.g., Fay & Frese, 2001; Frese, Garst, & Fay, 2007), but only in the
management/organisational context.
It is noted here that Personal Initiative is different from Organisation Citizenship
Behaviour (OCB) because by definition, OCB implies social and passive
connotations, whereas Personal Initiative does not. However, both Personal Initiative
and OCB can indirectly influence organisational effectiveness (Frese, et al., 1996).
Importantly, Allen, Facteau, & Facteau (2004) found that Personal Initiative is
positively correlated with OCB, thus in this research it can be inferred that Personal
Initiative has a positive relationship with consumer citizenship in the Co-Creative
Consumer Motivation Model, and consequently two hypotheses are put forward.
Hypothesis S6. Personal Initiative relates positively to Consumer Citizenship.
Hypothesis S6a. Personal Initiative is a characteristic of Co-Creative Consumers.
3.5.7 Communality
Communality refers to the consumer tendency to give benefits in response to needs
or to demonstrate a general concern for the other person (Clark & Mills 1993).
Communality was originally proposed by Clark and Mills (1979) to understand
communal relationships that are distinguished from exchange relationships (Clark &
Mills, 1979; Clark & Mils, 1993; Clark, Oullette, Powell, & Milberg, 1987).
According to Clark and Mills (1979, p. 12), “Communal relationships, in which the
giving of a benefit in response to a need for the benefit is appropriate, are
distinguished from exchange relationships, in which the giving of a benefit in
response to the receipt of a benefit is appropriate”.
Communality was later adapted to account for commercial based service
relationships, namely service communality (Goodwin, 1996). Service communality
refers to “the degree to which a service relationship resembles a friendship, and [is
labelled] as a communal [behaviour] [which] is associated with production of
communality in service contexts” (Goodwin, 1996, p. 389). Additionally,
communality will affect the way consumers interpret behaviours of service providers
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and fellow consumers (Goodwin, 1996). Thus, interpretation of a positive
behavioural motive may be misinterpreted as negative depending on the communal
relationship (Goodwin, 1996). As a result, Goodwin argues that communal
relationships will influence the responses of consumers and providers to each other's
behaviour. She points out that communal relationships (social ties) are contrary to
exchange relationships (transactions) because they imply a general concern for the
needs of others rather than reciprocal benefits. Additionally, communal and
exchange relationships can be seen as a continuum array rather than a dichotomy
(Goodwin, 1996). For example, a reciprocal business relationship between a firm and
a customer can be either an exchange or a communal relationship depending on the
dynamics of the relationship. Because communality implies taking into account
individuals‟ desires of paying attention to others‟ needs, it is distinct from altruism
and helping (Goodwin, 1996).
As suggested in GAP5, consumers can be service providers. Therefore, to underpin
the characteristics of the Co-Creative Consumer, the concept of communality is used
as a personal characteristic that refers to how a customer is sensitive to, or responds
to, the importance of taking the needs of others and their own needs into account
during interactions.
The norm of communality is associated with “the desire to give and receive benefits
based on concern for the needs of others” (Clark, et al., 1987, p. 401). Goodwin
(1996), further suggests “the degree of communality will affect perceptions of social
[behaviours], including conversation and offers of help” (Goodwin, 1996, p. 388).
Therefore, it is argued here that communality will have positive influences on
consumer citizenship, which underpins the motivation to co-create value in the
CCMM model. Thus, the following hypotheses are stated:
Hypothesis S7: Communality relates positively to Consumer Citizenship.
Hypothesis S7a: Communality is a characteristic of Co-Creative Consumers.
In the discussion above, the constructs and hypotheses underpinning the Co-Creative
Consumer model are presented. Accordingly, a depiction of the Co-Creative
Consumer Motivation Model (CCMM) is depicted in Figure 3.3. Table 3.2
summarises the hypotheses for the CCMM.
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Figure 3.3 Co-Creative Consumer Motivation Model (CCMM)
Personal Characteristics
MOA
HS1HS1
Newness (Opportunity to co-create value)
HS4HS4
HS5HS5
HS6HS6
HS7HS7 HS2
HS2
HS3HS3
Consumer Citizenship
(Motivation to co-create value)
Value OrientedUser Experience Sharing
Relating Needs (Ability to
co-create value)
Personal Initiative
Communality
Use Innovativeness
Mavenism
Table 3.2 Hypotheses for the Co-Creative Consumer Motivation Model
HS1 Newness relates positively to Value Oriented User Experience Sharing.
HS2 Consumer Citizenship relates positively to Value Oriented User Experience Sharing.
HS3 Relating Needs relates positively to Value Oriented User Experience Sharing.
HS4 Use Innovativeness relates positively to Relating Needs.
HS4a Use Innovativeness is a characteristic of Co-Creative Consumers.
HS5 Mavenism relates positively to Relating Needs.
HS5a Mavenism is a characteristic of Co-Creative Consumers.
HS6 Personal Initiative relates positively to Consumer Citizenship.
HS6a Personal Initiative is a characteristic of Co-Creative Consumers.
HS7 Communality relates positively to Consumer Citizenship.
HS7a Communality is a characteristic of Co-Creative Consumers.
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3.6 Conclusion
This chapter presents two conceptual models that will be tested in this thesis. These
models are: 1) User Experience Sharing Behaviour Model (UESBM), grounded in
the theory of planned behaviour; and, 2) Co-Creative Consumer Motivation Model
(CCMM), grounded in the theory of motivation, opportunity and ability. The models
were developed to answer the research questions underpinning the two emergent
concepts of: (1) User Experience Sharing; and, (2) Co-Creative Consumers. The
constructs contained in each model were discussed from within the relevant literature
and hypotheses were put forward to test the relationships identified. The next chapter
will discuss the methodology for the studies that were undertaken.
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CHAPTER FOUR METHODOLOGY
4.0 Introduction
In this chapter, the overall research design is presented to illustrate the methods used
to address the research questions. There are two objectives in this research design.
Firstly, it sets out to examine the hypotheses, and to confirm the proposed conceptual
models, User Experience Sharing Behaviour Model (UESBM) and Co-Creative
Consumer Motivation Model (CCMM). Secondly, the results from the development
of these models will be used to produce a typology reflecting the characteristics of
Co-Creative Consumers. The chapter is organised as follows: Firstly, Philosophical
Orientation is detailed in Section 4.1. Then, Research Design is presented in Section
4.2. Research Method is explained in Section 4.3. Next, Measurements are illustrated
in Section 4.4. Online Questionnaire Design is explained in Section 4.5. Sampling is
in Section 4.6, followed by Implementation of Sampling Method in Section 4.7.
Finally, Data Analysis Instruments, Ethical Consideration, Limitation and
Delimitations are presented in Sections 4.8, 4.9 and 4.10. In Section 4.11, a
Conclusion is provided.
4.1 Philosophical Orientation
This thesis will provide preliminary studies generating empirical evidence to
underpin Service-Dominant logic (SD logic); positivist orthodoxy (Hughes, 1990), is
used where empirical and logical knowledge is emphasised. By definition,
positivism refers to where “the external world itself determines absolutely the one
and only correct view that can be taken of it, independent of the process and
situations of viewing” (Kirk & Miller, 1986, p. 14). Viewed through a positivism
lens, knowledge is objective and determined by the relationships between human
beings and their environment. As a result, social phenomena can be understood by
searching for regularities and causal relationships. As positivism is the philosophical
paradigm adopted in this study, a model building and model testing approach is used,
and a quantitative survey method is chosen to investigate and answer the research
questions. The methodology adopts nomothetic principles which are common in the
natural sciences and focuses on hypotheses testing and theoretical generalisation by
obtaining empirical evidence (Burrell & Morgan, 1979).
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4.2 Research Design
Research design is derived with consideration to ensure the reliability and validity of
the research outcomes. This is achieved throughout the design employed for model
development (see Chapter 3), and model operationalisation, including sampling,
measurement and data collection described in this chapter. This research has
reviewed the SD logic literature. A „zoom-out‟ approach was adopted to refine SD
logic accommodating non-reciprocal marketing phenomena. As a result, an SD logic
consistent theoretical framework was proposed. Next, a „zoom-in‟ approach was
taken to examine an outcome-oriented value co-creation process. Two theoretical
concepts and corresponding models were conceptualised to shed light on consumer
initiated value co-creation. Two studies have been designed to examine the proposed
models. The first study was designed to calibrate the proposed models and the
second study is a replication study to strengthen the validity and the generalisability
of the models. The results are set to underpin the proposed emergent consumers'
behaviour and role, namely User Experience Sharing and the Co-Creative Consumer.
In terms of the method, a single method using a quantitative online survey was
chosen for data collection. The empirical studies were conducted in the context of
Convergent Mobile Online Services (CMOS). Population sampling frame refers to
CMOS users who participate in online communities. In terms of the research context,
Convergent Mobile Online Services (CMOS) (e.g., iPhone and iPhone Applications),
represents a growing number of non-reciprocal marketing phenomena (i.e., open
innovations and user generated content). As today‟s consumers are empowered by
the Internet (Pitt, et al., 2002), consumers are commonly co-creating value (i.e., User
Experience Sharing) within online communities (e.g., online gaming, uploading self-
made videos, publishing personalised solutions to fulfil needs of daily routines, and
publishing articles and reviews based on experiences). Expert reviews and pilot
studies were conducted in the measurement and survey development processes to
enhance the research validity and reliability. Finally, the collected data was used to
generate operationalised items that supported the models and measured the
relationship between constructs within theoretical models using Confirmatory Factor
Analysis and Structural Equation Modelling. Additionally, the K-means Cluster
Method was used to produce a typology of Co-Creative Consumers.
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The following sections illustrate issues related to the research method, including
sampling, survey and online questionnaire designs, data collection procedures and
analysis methods. Finally, the limitations of the research methodology are
acknowledged.
4.3 Research Method
A quantitative online survey method was used to collect data. The single
questionnaire contains two sets of data for examining the models developed in
Chapter 3. This is a single method research project. The survey method is adapted
and guided by the questionnaire development process proposed by Hair et al. (2007),
that accommodates a survey with multiple objectives. The adapted survey
development process is presented in Figure 4.1.
Figure 4.1 The Survey Development Process
Step 1 Search theoretical framework to underpin research questions
Step 3 Determine the appropriate research method
Step 4 Select and refine measurement scale and item
Step 5 Design, configure and evaluate online questionnaire
Step 6 Obtain ethical approval and web administrators‟ permission
Step 7 Implement the survey and collect Data
Step 2 Define constructs and build hypotheses
Adapted from (Hair, Bush, & Ortinau, 2003, p. 456)
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4.4 Measurement
The first six steps of a general construct development and scale measurement process
(Hair, et al., 2003), were adopted to ensure the validity and reliability of each
construct.
The six steps are presented in Table 4.1.
Table 4.1 A General Construct Development/ Scale Measurement Process
Theoretically identify and
define the construct
Determine dimensionality
of construct
Define construct
Create initial pool of attribute
items
Determine theory,
secondary data and
qualitative research
Select items from the
literature
Assess and select a reduced
set of items
Perform structural analysis
and qualitative judgments
Expert panel review
Construct initial measurement
and pre-test
Conduct pilot study, collect
data from pre-test sample
Pilot study
Do appropriate statistical data
analysis
Conduct construct validity
and scale reliability tests
Reliability test
Refine and purify scale
measurements
Eliminate irrelevant
attribute items
Path analysis,
Measurement analysis
Source: (Hair, et al., 2003, p. 423)
4.4.1 Items Pool and Expert Panel
Sets of suitable items were derived from the existing literature and scales. In general,
potential scale items were considered that had a sound Cronbach Alpha‟s of .7 and
above. The definitions of the constructs were given to the panel together with the
instructions on how to proceed. The pool of items was reviewed by a panel of five
academics with up-to-date marketing knowledge. The panel was asked to give
comments and feedback, particularly with regard to any unsuitable or ambiguous
items. The panel was also asked to give suggestions about any suitable existing items
to measure the constructs. Any disagreements were discussed by the candidate and
his supervisors to reach an agreement regarding retaining or dropping the disputed
items. As a result, items were refined according to the panel‟s feedback relating to
which constructs they believed the relevant items measured and their dimensions.
The pilot studies were conducted to further investigate the items retained.
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4.4.2 Measurements – User Experience Sharing
As User Experience Sharing (UES) is an emergent concept, the measures of UES are
adapted from knowledge sharing literature. Depending on the objectives and
contexts of past research, different measures of knowledge sharing behaviour have
been applied. Chiu et al. (2006) tested not only quantity of knowledge sharing but
also knowledge quality. They used a single item to measure quantity of knowledge
sharing, i.e., average volume of knowledge sharing per month. They measured
knowledge quality in terms of relevance, timeliness, accuracy, understandability, and
reliability, etc. (e.g., knowledge shared by members in the BlueShop virtual
community is relevant to the topic). Chennamaneni (2007) measured knowledge
sharing behaviour by the frequency of different types of work knowledge shared
with co-workers, e.g., factual knowledge from work, business knowledge about
customers, products, suppliers and competitors, internal reports and documents,
work experiences, know-how or tricks of the trade, expertise from training or
education, and know-why knowledge from work. Limpisook (2009) examined
knowledge sharing behaviour by looking at who the sharing was between using
items that are distinguished by whom sharing is with, termed Collaboration if shared
with community members, and termed Co-production if shared with service
providers. Minbaeva and Pedersen (2010) measured knowledge sharing behaviour by
the extent of knowledge actually gained or used, e.g., To what extent have you
gained knowledge from colleagues in your own department?.
Items for measuring User Experience Sharing (UES) cover two domains: 1) how
frequently user experiences are shared with firms and other consumers; and 2) what
types of user experiences are shared.
For the UESBM Model, User Experience Sharing is measured by frequency of User
Experience Sharing with Other Consumers (UESC), and User Experience Sharing
with firms (UESF). In total, five items were assessed, using a Five Point Likert Scale
from 1 (Never) to 5 (Most frequently).
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The three items for the UESC included:
1. How often have you shared your experiences of using mobile online services
with other people either online, or through word of mouth in the past six
months?
2. How often have you actively asked friends or online acquaintances for their
experiences of using mobile online services in the past six months?
3. How often have you given suggestions to friends or online acquaintances
based on your experiences of using mobile online services in the past six
months?
The two items for the UESF included:
1. How often have you contributed comments, reviews, recommendations or
ratings based on your experiences of using mobile online services in the past
six months?
2. How often have you given constructive feedback based on your experiences
of using mobile online services to service providers in the past six months?
For the CCMM, the second set of items for measuring UES have a focus on value
(i.e., Value Oriented UES). As defined, Co-Creative Consumers are value initiators
who actively participate in value creation through User Experiences Sharing. Three
forms of value creation suggested by Flint and Woodruff (2001; 2006) were adopted,
including desired value, received value and personal value. Three items were
assessed using a Five Point Likert Scale from 1 (Never) to 5 (Most frequently).
The three items used in the survey included:
To what extent are you currently sharing your experiences of using mobile online
services
1. … in a way not originally intended by the service provider.
2. … that are new, fun, useful, or interesting to you.
3. … that work for you personally.
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4.4.3 Measurements – User Experience Sharing Behaviour Model
4.4.3.1 Attitudes toward User Experience Sharing
Attitudes toward User Experience Sharing refer to the degree to which one evaluates
the behaviour favourably or unfavourably based on an individual‟s evaluation of
engaging in User Experience Sharing behaviour (Ajzen, 1991; Gagné, 2009). Eight
attitudinal items were chosen in line with Ajzen‟s (2002) instructions. As a result, an
8-item, 5-point Semantic Differential Scale is used as follows: For me, sharing my
experiences of using mobile online services with other people at least once in the upcoming
six months would be:
(a) Difficult|||Easy, (b) Unimportant|||Important, (c) Unsatisfying|||Satisfying, (d)
Useless|||Useful, (e) Harmful|||Beneficial, (f) Unpleasant|||Pleasant, (g) Bad|||Good, and (h)
Worthless|||Valuable.
4.4.3.2 Subjective Norm
A Subjective Norm (SN) reflects an individual‟s belief in the approval (or
disapproval) of engaging in the behaviour of interest from important referents, either
individuals or groups (Ajzen, 1991; Madden, et al., 1992). Four items were used to
measure subjective norm following Ajzen‟s instruction (2002). These items were
assessed using a Five Point Likert Scale from 1 (Strongly Disagree) to 5 (Strongly
Agree) and include:
1. People I interact with often in online communities are important to me.
2. Most people who visit the same online communities that I do expect that I should
share information and experiences.
3. Most people who visit the same online communities that I do expect that I should
share relevant information and experiences if it will help other visitors.
4. Most people who visit the same online communities that I do expect that I should keep
others informed about new information and experiences.
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4.4.3.3 Consumer Competence
For measurement, a recently developed Consumer Savvy scale focusing on
consumers‟ abilities in value co-creation was adapted to measure Consumer
Competence representing perceived behaviour control. As Macdonald and Uncles
(2007, 2009) suggest, consumer competency is a multi dimensional factor, and for
value co-creation, consumer expertise and social ties are essential. Three dimensions
of consumer competency, Technological Sophistication, Interpersonal Networks, and
Online Networks, were adapted from the Consumer Savvy Scale (Macdonald &
Uncles, 2007) to measure consumers‟ beliefs about how competent they are at
performing UES in terms of consumer expertise, and online and offline social
networking ties. As defined by Macdonald and Uncles (2007), each dimension can
be explained as follows: (1) Technological Sophistication (TS) relates to “comfort
and leadership in adopting new technologies” (2) Interpersonal Network (NW)
relates to “interpersonal connectedness” (3) Online Network (ON) relates to
“interacting with others online to search for product information; calling for
assistance in making product choices; and the hedonic value of sharing product
opinions with other consumers online”.
In their study, as discussed in Section 3.4.3, Macdonald and Uncles (2007) findings
support the validation of these three dimensions. The reported Cronbach‟s Alpha for
TS is 0.75, and for ON is 0.88. Because there are only two items in the measurement
of NW, they report a correlation of 0.55 instead. These items were adapted here to fit
the research context and were assessed using a Five Point Likert Scale from 1
(Strongly Disagree) to 5 (Strongly Agree).
The items used include
(1) TS (Three Items):
1. Other people come to me for advice on new mobile online services.
2. In general, I am first among my circle of friends to acquire new mobile
online services when they appear.
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3. I can usually figure out new mobile online services without help from others.
(2) ON (Five Items):
1. I often visit websites to find out about the latest mobile online services that
will be coming out.
2. I'll often search for blogs and review websites that can help me when I'm
looking for mobile online services recommendations.
3. I'll often seek the opinions of others by posting queries about mobile online
services on online community websites.
4. I enjoy sharing points of view about mobile online services with online
acquaintances via online community websites.
5. My best contacts for information about new mobile online services often
include people online that I've never met face-to-face.
(3) NW (Two Items):
1. I always know someone to call if I want to find out about the best mobile
online services.
2. I have a useful network of contacts who can give me up-to-date information
on the latest mobile online service innovations.
4.4.3.4 Intention to Engage in User Experience Sharing
An individual‟s intention refers to how much effort they might exert and how willing
they may be to try to perform a given behaviour (Ajzen, 1991). Four items were
assessed using a Five Point Likert Scale from 1 (Strongly Disagree) to 5 (Strongly
Agree). These items are used to measure intention to engage in User Experience
Sharing following Ajzen‟s instruction (2002), including:
1. I will most likely contribute comments reviews recommendations or ratings
to an online community in the upcoming six months.
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2. I intend to share with other people my experiences of using mobile online
services either online or by word of mouth in the upcoming six months.
3. I will try to share with other people my experiences of using mobile online
services either online or by word of mouth in the upcoming six months.
4. I plan to share with other people my experiences of using mobile online
services either online or by word of mouth in the forthcoming six months.
4.4.3.5 Consumer Empowerment
In this thesis, items derived from the Underlying Dimensions of Community
Activism and Autonomy of Consumer Empowerment scale (Rogers, et al., 1997) are
used to test how the factor of empowerment influences UES as value co-creation
activities. There are a total of 28 items in the original scale. The Cronbach‟s Alpha is
0.86. Five items were assessed using a Five Point Likert Scale from 1 (Strongly
Disagree) to 5 (Strongly Agree). These items that reflect the community activism
and autonomy aspect are adapted including:
1. In the online communities in which I engage I think that people have a right
to make their own decisions, even if they are bad ones.
2. People should share their experiences the way they want.
3. People working together can have an effect on the online community.
4. People have more power if they join together as a group.
5. Working with others can help to change things for the better.
4.4.3.6 Enjoyment in Helping Others
Four items were adapted from the Perceived Enjoyment in Helping Others scales
(Kankanhalli, et al., 2005). The reported Cronbach‟s Alpha is 0.96. These items
include:
1. I enjoy sharing my experiences of using mobile online services with friends
or online acquaintances.
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2. I enjoy helping friends or online acquaintances by sharing my experiences of
using mobile online services.
3. It feels good to help friends or online acquaintances solve their mobile online
services related problems.
4. Sharing my experiences of using mobile online services with friends or online
acquaintances gives me pleasure.
These items were assessed using a Five Point Likert Scale from 1 (Strongly Disagree)
to 5 (Strongly Agree).
4.4.4 Measurements – Co-Creative Consumer Motivation Model
4.4.4.1 Opportunity - Newness
The measurement scale, Opportunity, termed Newness here, is adapted from the
Marketing Program Creativity scale (Andrews & Smith, 1996). Marketing program
creativity is defined as “the extent to which the actions taken to market a product …
represent a meaningful difference from marketing practices in the product category”
(Andrews & Smith, 1996, p. 179). Andrew and Smith (1996) use the concept to
measure meaningful novelty in terms of creativity and solutions to everyday
(business) problems. The reported Cronbach‟s Alpha is 0.91.
After adaptation, a 5-item, 5-point Semantic Differential Scale is used as follows.
The experiences of using mobile online services that I usually share are
“Not original at all|||Completely original”; “Not new to me at all|||Completely new to me”;
“Not personalised at all|||Completely Personalised”; “Not unique at all|||Completely
unique”; and, “Not different at all|||Completely different”.
4.4.4.2 Consumer Citizenship
Four items were adapted from a set of interview questions developed by Constant et
al. (1996), and were originally used to measure organisational motivation (i.e.,
information providers‟ reasons for replying). This concept was later tested by
Lakhani and Von Hippel (2003). Both studies used an interview questionnaire
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technique, therefore no Cronbach‟s Alpha was reported in either study (Constant, et
al., 1996; Lakhani & Von Hippel, 2003). Nevertheless, these questions received high
scores from the interviewees. Because this scale is the only one found that can reflect
the consumer citizenship concept, it is used in this study. These items include:
1. I consider myself a good online community citizen who is willing to help
others.
2. I believe my experiences of using mobile online services are valuable to the
online communities to which I belong.
3. I feel I am responsible for responding to other users’ questions or replies
about mobile online services.
4. Because I expect other users of my online community to share their
experiences of using mobile online services with me or each other, it’s only
fair to share mine with them.
These items were assessed using a Five Point Likert Scale from 1 (Strongly Disagree)
to 5 (Strongly Agree).
4.4.4.3 Relating Needs
There are two sub scales used to measure relating needs including relating needs of
self, and relating needs of others.
Relating Needs of Self
This measurement is derived from a sub-scale of the Consumers‟ Need for
Uniqueness scale, namely Creative Choice proposed by Ruvio, Shoham and Brencic
(2008). Cronbach‟s Alpha is above 0.9 in the study. The scale is adapted to measure
customers‟ ability to accommodate their personalised needs for the benefit of self. In
total, four items are used:
1. I often use mobile online services in such ways that I create personalised
routines that are different from others.
2. I often research the suitability, rather than the popularity, of a mobile online
service because I enjoy having a service that fits my personal needs.
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3. I actively seek to improvise my personalised routines by using a range of
mobile online services.
4. Being able to spot mobile online services that suit my needs assists me in
establishing my personalised routines.
These items were assessed using a Five Point Likert Scale from 1 (Strongly Disagree)
to 5 (Strongly Agree).
Relating Needs of Others
This construct is extracted from a sub-scale of the Customer Orientation (CO) scale
(Donavan, et al., 2004), namely, „need to read the customer‟s needs‟. It was
originally a four-dimensional scale including the items: (1) need to pamper the
customer; (2) need to read the customer„s needs; (3) need for personal relationship;
and, (4) need to deliver the service required. It is used to measure “employees‟
tendency or predisposition to meet customer needs in an on-the-job context
(Donavan, et al., 2004). In this thesis, to reflect that Co-Creative Consumers can be
service providers to others, the construct, „need to read the customer‟s needs‟, is
chosen to measure relating needs of others. Composite Reliability of the construct
(CO) is .88. The Cronbach‟s Alpha for this sub dimension construct is not reported.
Three items are used. These items include:
1. I naturally read and relate to other users’ needs about using mobile online
services.
2. I generally know what mobile online services other users need from their
questions, even questions that can be vague.
3. I am able to anticipate the needs of other users about using mobile online
services.
These items were assessed using a Five Point Likert Scale from 1 (Strongly Disagree)
to 5 (Strongly Agree).
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4.4.4.4 Use Innovativeness
The use innovativeness scale is used to test consumers‟ tendency to use an existing
service in a novel and innovative manner. The items are adapted from the use
innovativeness scale proposed by Price and Ridgeway (1983). It is a multi-
dimensional measurement with a total of 44 items in the original scale. The reported
Cronbach‟s Alpha is 0.91. Girardi (2005), recently validated the use initiation scale.
The findings suggest the use innovativeness scale is uni-dimensional, consisting of 9
items. The reported Cronbach‟s Alpha is 0.79. This study takes into consideration
the findings of both studies, and as a result, ten items are chosen. These items
include:
1. Knowing new ways of using a mobile online service gives me almost as much
pleasure as knowing the usefulness of a mobile online service.
2. I’m very creative when using a mobile online service in a way that is
different from what the developer intended.
3. I’m very interested in exploring new uses of a mobile online service and what
makes it work for me.
4. I do not enjoy a mobile online service unless it has multiple uses.
5. I use mobile online services in more ways than most of my friends.
6. I often begin using a mobile online service for a particular situation, but end
up using it for different situations.
7. A mobile online service's value is directly related to the number of ways it
can be used.
8. It’s always possible to better use a mobile online service by upgrading it.
9. After using mobile online services on my mobile device, I try to keep track of
new upgrades or better alternatives that come out in the market.
10. I enjoy expanding and adding mobile online services on to my mobile devices
that I will use on a continuing basis.
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These items were assessed using a Five Point Likert Scale from 1 (Strongly Disagree)
to 5 (Strongly Agree).
4.4.4.5 Mavenism
Six items were adapted from Geissler and Edison (2005) to measure Mavenism.
Cronbach‟s Alpha is above 0.93 in the their study using a 5 point Likert Scale (cf.,
0.82 in the original study (Feick & Price, 1987)). These items include:
1. I like introducing technologies to my friends.
2. I like helping people by providing them with information about how to use a
technology.
3. People ask me for information about technologies.
4. If someone asked how to get the best use out of several types of technologies,
I could tell them what to do.
5. My friends think of me as a good source of information when it comes to
technologies.
6. I know about lot of different technologies and I like sharing this information.
These items were assessed using a Five Point Likert Scale from 1 (Strongly Disagree)
to 5 (Strongly Agree).
4.4.4.6 Personal Initiative
Seven items were adapted from Frese‟s (1997) interview questions to measure
personal initiative. Personal Initiative has been adopted as a factor that indirectly
influences rewarded suggestions (Frese, Teng, & Wijnen, 1999). Cronbach‟s Alpha
is 0.87 in the study by Frese et al. (1999). These items include:
1. I actively seek to solve problems.
2. Whenever something goes wrong, I search for a solution immediately.
3. Whenever there is a chance to get actively involved, I take it.
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4. I take the initiative immediately, even when others don’t.
5. I use opportunities quickly in order to attain my goals.
6. I often do more than I am asked to do.
7. I am particularly good at putting my ideas into practice.
These items were assessed using a Five Point Likert Scale from 1 (Strongly Disagree)
to 5 (Strongly Agree).
4.4.4.7 Communality
Five items are adapted from the Communality Scale (Clark, Oullette, Powell, &
Milberg, 1987). Mathwick (2002) tests a 7-item Communality Scale in the online
context to inform the characteristics of online consumers. The reported Cronbach‟s
Alpha is 0.95 measured with a 7-point Likert Scale. These items include:
1. When making a decision, I take other people’s needs into account.
2. I believe people should go out of their way to be helpful.
3. I expect people I know to be responsive to my needs.
4. I go out of my way to help other people.
5. I turn to others I know for help when I have a need.
These items were assessed using a Five Point Likert Scale from 1 (Strongly Disagree)
to 5 (Strongly Agree).
4.4.5 Pilot Study
A pilot study is used to detect variation, meaning, task difficulty, respondent interest
and attention, pretesting the questionnaire (e.g., flow of the questionnaire, skip
patterns, and time length) (Aaker, Kumar, & Day, 2005). Aaker et al. (2005), suggest
15 participants for a short and straightforward questionnaire and 25 participants for a
long and complex questionnaire may be needed. To ensure that the measurement
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scales were adapted appropriately to the context, two sets of initial questionnaires
were pre-tested on two pilot groups. The pre-test questionnaires were conducted to
examine the instruments for content validity. The initial pilot study was conducted
using MBA students. A total of 20 questionnaires were collected. The follow up pilot
study was conducted using 15 university research master and PhD students who
reported using mobile online services. Both surveys were paper based. Comments
and suggestions from respondents were used to improve the content and the structure
of the questions before the survey was conducted. Based on the findings of the two
pilot studies, the items that best identified the dimensions were refined and used in
the final survey.
4.5 Online Questionnaire Designs
A web-based online survey has the advantages of being interactive, convenient, and
accessible. Data safety is also enhanced because it is stored in a regularly backed-up
and secured server. Firstly, through a web interface, participants usually answer
questions manually via a mouse, keyboard or touch screen. Some visual facilitation
can be incorporated to encourage participants to complete the survey (e.g., progress
bar, percentage of completion, or current page number and total page number ratio)
and inform participants of their progress. In addition, multiple web addresses can be
assigned to the same survey, which allows administrators to control and monitor data
collected from different sampling sources. Instead of sending out a whole survey, a
hyperlink can be embedded on a web page that allows participants to access the
survey. Interactive screening questions can be placed in the survey to filter out
unsuitable participants at the beginning. Finally, data is easier to backup and store in
a secure server (e.g., a university server). In this section, online questionnaire design
is discussed including (1) survey instrument, (2) justifications of using web-based
online surveys, (3) online questionnaire design, and (4) research procedure/
implementing online questionnaire.
4.5.1 Survey Instrument
The web survey was developed using Key Survey software provided by the
Queensland University of Technology. The web survey was designed using HTML
and Java language, but most survey design functions were pre-configured with
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intuitive customisation settings. The questions and basic configuration were set up
with the assistance of Key Survey IT specialists. Tailored configurations were made
to maintain and monitor the questionnaire by the researcher. The data were stored in
a university server and backed up on a PC hard drive, onsite in the university
premises.
4.5.2 Justifications for Using Web-based Online Surveys
In this research, a web survey method was chosen, a self-selection method was used,
and online community members and visitors were the sampling targets. To address
the issue of the lack of sampling frames, it is common to attach a hyperlink to the
webpage (Fielding, Lee, & Blank, 2008). Due to resource constraints (limited sites,
cost and time), a single questionnaire is used to collect the data for testing two
theoretical models. In addition to this, there are two key reasons to conduct a single
questionnaire:
(1) Comparison of cross models. A single questionnaire design allowed the
researcher to test UES as a behaviour in general and to investigate the motivations of
those who perform the behaviour. This was done through a value co-creation lens, so
the characteristics of the participants could be determined. It also allowed
comparison of the two models.
(2) Comparison of cross samples. Each frame population had its theoretical
implications (i.e., Prosumer and Innovator). Use of a single questionnaire made it
easy for the researcher to conduct comparisons across data.
Because of the research context (i.e., convergent mobile online services (CMOS),
this research study used a web-based survey where respondents (iPhone user) could
access questions through a web browser either from a PC or a mobile device. In this
research, the targeted participants were CMOS users; they had a broadband
connection at the premises where they accessed the survey or 3G access on their
mobile phones. Web surveys can take advantage of this and offer greater
accessibility as the survey can be distributed across various devices (Fielding, et al.,
2008).
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A web-based online survey method was used instead of the email list sampling
method. A web-based online survey is broader than an Internet survey and refers to a
survey that uses any ICT network (e.g., Intranet, 3G, SMS) to support and mediate
the survey process (Fielding, et al., 2008). In addition, web-based online surveys can
be used in various sampling methods where E-mail surveys cannot be used, such as
with probability based Intercept surveys (pop-up), or non-probability based
unrestricted self selection surveys (Fielding, et al., 2008).
Other key reasons for using an online web survey are outlined: Firstly, the online
questionnaire is effective when the sampling pool consists of visitors and members
of online community forums. Secondly, visitors and online community members are
able to see the posting with the web questionnaire hyperlink attached. There is no
discrimination regarding accessing the questionnaire between members and visitors.
Thirdly, it is cost effective, without compromising the quality of the data. As visitors
and members of online communities participate and interact with each other online,
online questionnaires are the most effective way to reach them.
4.5.3 Considerations of Online Questionnaire Design
The four most important issues considered in the survey instrument development
process were uniformity, usability, security and anonymity (Fielding, et al., 2008).
These four design aspects are discussed as follows:
Uniformity
It is suggested that lack of uniformity has an impact on measurement errors (Fielding,
et al., 2008). These results in this thesis suggest that the risks of any uniformity
issues were minimised and implies a possible reduction in the concerns of
measurement errors. A potential problem regarding uniformity was that potential
participants may use different browsers and that therefore the presentation of the
questionnaire (data collection instrument), such as font, width, length, effects could
vary. Different screen sizes of devices and input methods also challenged the
usability. To overcome these issues two actions were taken. First, before rolling out
the survey, the researcher and Key Survey IT support staff tested the questionnaire
on a range of commonly used browsers, including Internet Explorer, Safari, Chrome,
Firefox, Opera, Dolphin browser, and Opera mini across PCs, laptops, and smart
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phones. Secondly, the questionnaire was pre-tested by volunteer users. While the
browsing experiences were different, all testing results were consistent which
suggested that there were no major issues in terms of uniformity.
Usability
Usability refers to the ease of use of the survey instrument. The data collection
instrument is an online questionnaire facilitated by Key Survey software. It is the
official survey software provided by the Queensland University of Technology for
conducting survey studies.
As mentioned earlier, the advantage of the online survey is that the instrument can be
accessed using multiple technologies. This advantage also has drawbacks. While
online surveys can be accessed via PCs, handsets and other mobile devices, Internet
speeds may vary. There was a possibility that if the participants used mobile devices,
Internet connections could have been interrupted, resulting in incomplete surveys. To
address this issue, on the information sheet supplied prior to potential participants
accessing the survey, participants were advised to conduct the survey on a computer,
rather than their mobile phone or other mobile device.
In addition, considering the long length of the questionnaire, Arial 12-point font was
used in the survey, as this setting is reported to enhance reading speed compared to
other font styles and font sizes (Bernard, Lida, Riley, Hackler, & Janzen, 2002).
Paging instead of scrolling techniques were used to enhance the survey experience
(Peytchev, Couper, McCabe, & Crawford, 2006). Paging helps the researcher to
control the order of the questions presented, since with scrolling, participants may
not complete the questions in the listed order (Dillman, 2007). The questionnaire
survey was broken into 12 pages. Page indicators were set in place to inform and
encourage participants to complete the questionnaire.
From the final data collection result, (1) there was no feedback from the participants
to suggest that there were difficulties accessing the questionnaire, (2) there were no
incomplete surveys. The reasons may be that Key Survey software was web browser
based and was designed with minimum graphics, and therefore had minimal
demands on Internet speed. Also, many CMOS users have 3G or a broadband
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connection for their devices, meaning that it is unlikely that results would be
compromised by Internet speed or the device used.
Security
All hyperlinks were shown with the university domain. The advantage of using a
university domain based hyperlink is that as the survey is from a credible source it
can ease potential participants‟ concerns about security (e.g., spam). It is expected
that this improved the response rate. A plain language straight forward information
sheet with researchers‟ details is also likely to have helped. There was no password
control in place because it would have added an unnecessarily burden on potential
participants, possibly reducing response rates (Crawford, 2002). Although incentives
used in the research may cause concerns regarding out-of-sample submission, the
hyperlink was posted within selected forums, and therefore the potential participants
were most likely to be visitors and members of the web forums. In addition, Key
Survey provided customisation settings and security to enhance data reliability, e.g.,
participants had to answer at least one question in each set of questions before
moving to the next page). The survey configuration was also set to prevent possible
multiple submissions, e.g., participants could not enter the survey if Key Survey
software detected a response coming from the same IP address).
Anonymity
In the information sheet, information regarding the anonymity and the security of the
data were emphasised. Participants‟ personal information was collected for the
purpose of a prize draw using a separate survey and database to ensure the
anonymity of the participants in the research. Reflecting on the research context and
the language of the questions, the questionnaire was low in sensitivity and therefore
less likely to raise privacy concerns that could have threatened the measurement
validity of the instrument.
4.5.4 Implementing the Online Questionnaire
The questions were arranged and placed in a number of sections using the guidelines
suggested by Hair et al. (2007). In terms of operationalisation, the first page of the
online questionnaire showed the content and sought informed consent. A suggestion
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had been made to survey participants on the information sheet at the beginning of the
web survey to encourage them to access the web browser on a PC. The respondents
had to tick an “Agree” box to continue the survey. Beginning on the second page,
there were up to three screening questions depending on the sampling techniques
applied (i.e., judgemental or convenience). Participants who were not suitable could
not continue to answer the questionnaire and they were redirected to a „Thank you‟
page. A copy of the online questionnaire can be found in Appendix C.
4.6 Sampling
In this research, the target population was online communities and the sampling
frame were CMOS users who participate in online communities. Non-probability
judgemental sampling and convenience sampling techniques were adopted (Malhotra,
et al., 2004). As there were two studies in this research, two sets of data were
collected according to the chosen frame population. The first set of data was used to
calibrate and re-specify the two proposed models. The second dataset was collected
to further confirm the model. Datasets were also used to perform cluster analyses to
underpin the characteristics of Co-Creative Consumers in both studies. The sample
size for each study was 326 in the first study and 296 in the second study. A large
sample size for both studies was required in order to perform Structural Equation
Modelling analyses.
4.6.1 Population and Sampling Frame
Population refers to the entire group of interest that the researcher ultimately intends
to draw conclusions about (Fielding, et al., 2008). This research project is set to
underpin UES behaviour and investigate motivations regarding consumer-to-
consumer value co-creation (i.e., Value Oriented UES) within online communities.
Dialogues are considered as a type of value co-creation (Ballantyne & Varey, 2006).
They are most commonly observed in online communities. Online communities (e.g.,
online forums) are important knowledge bases and can be launched by service
providers or be operated by community members who share the same interests and
passions (e.g., Faraj & Wasko, 2001; Wu & Sukoco, 2010). Therefore, online
communities constitute the study population in this thesis.
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In this research, non-probability judgement and convenience sampling techniques
were used to recruit participants. The first step was based on the principal
researcher‟s judgement to select a sampling frame. The sampling frame chosen were
CMOS users who participate in online communities. In general, two key concerns
about using Internet-based surveys are (1) the lack of a sampling frame, and (2)
online users do not include offline users, therefore the results cannot generalise to the
public (Fielding, et al., 2008). It is less of an issue to this research because (1) the
target population are online communities (2) consumers should always have Internet
access in order to use CMOS. Thus, the data is representative and reflective of the
population.
4.6.2 Sampling Procedures
Non-probability judgemental and convenience sampling techniques were used in this
research. Like other non-probability sample techniques, the results may not fully
support statistical inference. As a preliminary study, non-probability samples can be
insightful in defining ranges of alternatives and collecting other sorts of non-
inferential data (Fielding, et al., 2008).
Additionally, before the data collection, an attempt was made in terms of collecting
probability samples. The attempt involved contacting administrators to obtain
complete email lists of selected online forums. Due to privacy concerns, this was
rejected by most forum administers. One web administrator did initially agree to
send a hyperlink to members but did not follow through.
4.6.3 Numbers of Sampling Cases
Items to measure the variables in the conceptual model were developed using results
found in the literature review. For this study, the Sampling Error Formula (Fink &
Kosecoff, 2005) is applied to set the required sample number to support the
reliability of the study. Using this formula, three variables are considered. Applying
the proportion of the sample (5 point scale, 20/80), the tolerated sampling error ( =
0.05), and the identified confidence interval (95%), the result of the suggested ideal
sample size is around 300.
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4.7 Implementation of Sampling Method
4.7.1 Data Collection
The sample in Study One was drawn from a PC Do-It-Yourself (DIY) online
community, Overclockers Australia Forums. Main topics discussed on this forum are
related to PC hardware, Software and Gaming …etc. It is claimed to be „Australia‟s
busiest PC hardware community/ forum”. The discussions related to iPhone and
Apps and therefore it was a community more likely in which to recruit CMOS users.
The sample in Study Two was collected mainly from Apple product online
communities, including MacTalk.com.au, MacRumors Forums, ilounge.com, and
mybuzz.com.au. A small portion of samples are iPhone users recruited from
Facebook and offline. Apple is the manufacturer of iPhone, and iPhone is an
innovative platform that accommodates CMOS (i.e., Apps). Therefore, iPhone users
are more likely to be CMOS users. These online forums were hosted in regions
where iPhone 3G and 3G networks are available. The online forums were selected
with considerations regarding the community size and reputation based on (1)
numbers of threads and posts, and (2) numbers of members. Both members and
visitors can access all forums. There is no restriction to reading forum posts on these
forums. The importance of choosing forums with non-discriminative reading access
was that the data better reflected the target population which included users who
were more engaged in online communities (i.e., posting), and also those who were
less involved in online communities (i.e., reading). Table 4.2 is provided to show the
size and reputation of these online forums.
Table 4.2 Numbers of Posts and Members in the Participant Online Communities
Access date
17/11/2010
Threads Posts Member
OCAU Forums 574,570 9,591,253 115,693 Study 1
Sampling
Source
MacTalk
Forums
89,724 1,038,777 36,961 Study 2
Sampling
Sources MacRumors
Forums
1,000,023 11,156,719 512,976
ilounge Forums 236,238 1,354,289 200,787
Sources: from the corresponding forums
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4.7.2 Recruitment
There are several ways to recruit online participants. For example, recruitment can
involve sending email invitations, posting a web link on the website, web banners,
posting web links on social networking sites, forums and blogs, and sending an SMS
with a hyperlink, and so forth. In this study‟s survey, all the participants could access
the embedded web link attached to the post that redirected potential participants to
the web survey. Therefore, the samples consisted of visitors and members who
accessed the post through the forum of the online community. In this research,
participants had to read the post on the forum to access the web survey, and therefore
it fitted the sampling target definition as “online community members and visitors”.
For an unrestricted self-selection survey method the survey has to be accessible in a
public domain in which everyone can potentially participate. A web-link was
embedded in threads and posted by the moderators on each online community forum
where both members and visitors could click the link to access the survey
questionnaire. Each initial thread post was placed in each selected online community
by the administrator or with the permission of the administrator of the forums. It was
up to the potential participants to opt in and participate in the survey. The survey link
was posted for a months‟ duration in order to allow sufficient time for most visitors
and members to access it.
There are very limited online iPhone communities that could qualify as sample sites.
With consideration of time constraints and cost, a single questionnaire simplified the
data collection procedures allowing the researcher to collect all required independent
data at the same time. This method also minimised potential multiple entries from
the same participants.
4.7.3 Characteristics of Samples
While the sampling frame is CMOS users who participate in online communities, the
collected data in both studies may provide more meaningful and informative data to
answer research questions because these samples may reflect theoretically
recognised consumer profiles, namely Prosumer (Toffler, 1980) and Innovator
(Foxall, 1994).
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The data collected in Study One may reflect the characteristics of a theoretically
recognised consumer profile, namely Prosumer (Toffler, 1980). The data collected in
Study Two are likely to be iPhone (Apps) users because they were mainly collected
from Apple product forums. As iPhone is considered to be an innovative platform
for Apps, iPhone users are likely to use Apps. CMOS (e.g., Apps) is considered a
type of innovative service offering and can be used in multiple ways by consumers.
Therefore, iPhone users who use Apps may reflect the characteristics of a
theoretically recognised consumer profile, namely Innovator (Foxall, 1994).
In this study, Prosumer is considered to be co-producer which describes consumers
who play both roles of co-producer and consumer in a consumption process (Toffler,
1980). It is in line with SD logic that co-production reflects the blurred firm-
customer distinction (Gummesson, 2007). An innovator can refer to consumers who
are the first to adopt an innovation (Rogers, 2003). According to Foxall (1994),
innovators are broad categorisers. They are more likely to try new products and use
them more actively to find a solution. They are more likely to risk errors and costs to
take advantage of potential positive chances, e.g., accepting the risk of buying an
unsatisfactory item. They also think in abstract and therefore tend to ask more
questions, search widely for information and investigate more relationships. The
innovative and solution-oriented characteristics of innovators are also in line with
SD logic.
4.7.4 Cost, Survey Solicitation and Survey Access Control
The length of the online survey was not considered problematic in terms of cost
since the Key Survey service was used (provided by Queensland University of
Technology). The length of the survey however, may have had an impact on the
response rate and data reliability. Cost is a concern when it comes to survey
solicitation. Most researchers who use online surveys prefer them for the reason that
they are cheaper than telephone or mail surveys. However, it is often argued that data
quality can sometimes be poorer with these types of survey. The researcher has
worked in the area of E-marketing, and is experienced with issues that may occur
when utilising web surveys. This may ease concerns about this issue.
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4.7.5 Survey Incentives
A lottery approach refers to an approach that uses a significant reward to increase the
response rate (Hair, et al., 2003). An incentive is something of relatively significant
value, and participants have an equal chance of obtaining it. It is common to offer an
incentive to encourage a higher response rate. This research required a large sample
size, so in order to maximise the number of respondents, a lottery approach (i.e., a
prize draw) was undertaken. Approval for this was sought when ethical approval was
submitted. In addition, separated online questionnaires were used to ensure
participants‟ anonymity.
4.8 Statistical Analysis Method
Structural Equation Modelling (SEM) and K-means cluster analysis were chosen to
analyse the data collected. Statistical calculations using SPSS and AMOS enabled
further analyses. SPSS is used to administer and analyse the collected quantitative
data (e.g., internal reliability test and K-means cluster analysis) (Hair, et al., 2007).
AMOS, on the other hand, is a Structural Equation Modelling (SEM) computer
package employed for confirmatory factor analysis and structural analysis (Hair, et
al., 2007). SEM was used to investigate impacts and relationships between testing
variables of the User Experience Sharing Behaviour Model and Co-Creative
Consumer Motivation Model, and K-means cluster analysis was used to produce a
typology of Co-Creative Consumers.
4.9 Ethical Consideration
This program of research was conducted according to the National Statement on
Ethical Conduct in Research Involving Humans, developed by the National Health
and Medical Research Council (NHMRC), and the Queensland University of
Technology guidelines. As the research involves surveying humans, a Level 2
Ethical Clearance application was prepared for ethical clearance for each study. To
ensure that this research was free of coercion, discrimination and exploitation
(Aguinis & Henle, 2001), participation in this research was entirely voluntary and
participants could withdraw at any time. Informed consent was obtained from
participants in each of the studies and confidentiality was maintained by removing
P a g e | 119
identifying features from the data collected. The results from each of the studies
were kept secure in accordance with Queensland University of Technology standards.
4.10 Limitations and Delimitations
There are three notable limitations to the method.
(1) Considering the cost and time constraints, the non-probability sampling method
was chosen. The limitations of non-probability sampling are its impact on data
quality and that statistical results used to represent the whole population may be
weak. The method might limit the generalisability of results. Because this research is
an exploratory study, the main research purpose is to test the emergent concepts
rather than make generalisations.
(2) The nature of Internet surveys may weaken the legitimacy of using probability
sampling because probability samples in Internet surveys are highly affected by the
problem of non-coverage and sampling frame problems (Fielding, et al., 2008). The
issues are related to the fact that 1) the Internet may not be available to all members
of the general population; 2) if email is used to invite participants to access the web
survey, there is no email directory of the general population of Internet users that can
be used as a sample frame. Despite the efforts made to adopt probability sampling,
non-probability judgemental and convenience sampling techniques were adopted.
Because the target population was online communities, concerns about Internet
based surveys resulting in the lack of a sampling frame were less of an issue.
(3) The long length of the questionnaire may have had an impact on the reliability of
the survey results. The researcher conducted and maintained the design and
implementation of the online survey to help to enhance the quality of data.
(4) The results show more than 95% of participants were male. This is not a
deliberate result. According to (Fielding, et al., 2008), the types of self selected
participants may be affected by different recruitment methods. A more intuitive
explanation could be that the discussion on the web forum could have been more
high-tech oriented, and therefore the demographic of participants are more likely to
be male.
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4.11 Conclusion
In this chapter, a two-study single method of research was identified. For each study,
data was collected using a single online web-based survey. The data was used to test
two theoretical models and produce the typology of Co-Creative Consumers. The
next two chapters discuss the results from Study One and Study Two.
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CHAPTER FIVE STUDY ONE RESULTS
5.0 Introduction
The previous chapter presented the research methodology for the research program.
The purpose of this chapter is to report the results from testing the proposed
hypothetical relationships stated in the two theoretical models developed in Chapter
Three.
The chapter is organised as follows. First, the results for the preliminary analysis of
the data and descriptive statistics of the sample are presented. Second, the results for
the reliability analysis for each of the constructs are reported. Third, the results of the
Confirmatory Factor Analysis (CFA) are provided as the first part of the two-stage
model estimation process in Structural Equation Modelling. Fourth, the results of full
SEM analysis for each model are presented. Finally, the summary of the chapter is
provided. All construct items (retained/ deleted) can be found in Appendix B.
5.1 Sample Characteristics
It will be recalled that the data for this study were collected from a PC DIY online
community, Overclockers.com.au. The Study One sample consisted of respondents
aged between 18 – 65 years old. The sample comprised 302 males and 19 females.
The majority of respondents have achieved a 12-year high school qualification
(91.4%) and all respondents are resident in Australia. Table 5.1 shows the sample
characteristics in terms of gender, age, education and their residence.
Table 5.1 Sample Characteristics of Respondents
Study 1 N = 326 Total Number Percentage %
Gender Total 321 98.5%
male 302 92.6%
Female 19 5.8%
Age Total 324 99.4%
18 - 25 170 52.1%
26 - 35 115 35.3%
36 - 45 27 8.3%
46 - 55 11 3.4%
56 - 65 1 0.3%
Above 65 0 0.0%
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Education Total 326 100%
Less than 10 years
schooling
8 2.5%
10 years to 11 years of
schooling
17 5.2%
12 years of schooling 61 18.7%
Basic vocational
qualification
3 0.9%
Skilled vocational
qualification
22 6.7%
Diploma or Associate
diploma
37 11.3%
Undergraduate degree
(Bachelors)
130 39.9%
Postgraduate
certificate/diploma
21 6.4%
Coursework Masters 6 1.8%
Research Masters 0 0.0%
PhD or ABD 8 2.5%
Professional qualification 10 3.1%
others 3 0.9%
Residence Total 326 100%
Australia 326 100%
5.2 Data Preparation and Preliminary Analysis
The data collected through the online survey were automatically collated into an
Excel database when participants clicked the submit button, resulting in no entry
errors. This database was converted into SPSS 17.0 for preliminary analysis. There is
a low percentage of missing values. A high level of randomness is termed missing
completely at random (MCAR) (Hair, et al., 2007). According the MCAR test, the
data is missing at random (MAR). A Model-Based procedure, the EM algorithm
(Dempster, Laird, & Rubin, 1977), is used to compute incomplete MAR data. The
remedy to repair missing at random (MAR) data is to reduce the bias and therefore
enhance the quality of the data for generalisability (Hair, et al., 2007). Outlier and
normality were checked using AMOS 17.0. The Mahalanobis D2 results indicated
that many cases are multivariate outlier. To reflect the true data, the outlier cases
were kept. Normality is also checked and indicated that data were non-normal.
After the preliminary analysis process, AMOS 17.0 was used to conduct SEM
analysis. To test the proposed models, a two-stage model estimation process of
Structural Equation Modelling was performed based on the Maximum Likelihood
(ML) estimation method (Anderson & Gerbing, 1988; Byrne, 2006). First, the results
of both confirmatory measurement model and structure model tests in sequence in
the following sections. The results of User Experience Sharing Behaviour Model
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(UESBM) are first reported followed by the results of the Co-Creative Consumer
Motivation Model (CCMM).
5.3 Test of Measurement Model for User Experience Sharing Behaviour Model
As the first part of the two-stage model estimation process of Structural Equation
Modelling, Confirmatory Factor Analysis (CFA) was performed. In this section, the
CFA analytical result of each construct was presented. Each measurement model
specifies the hypothesised relationships between the latent variable and manifest
indicators (Hair, Black, Babin, Anderson, & Tatham, 2006). CFA is able to test the
relationships between the manifest indicators and latent variables, correlations
between pairs of latent variables, and correlations between the errors of manifest
indicators (Polit and Tatano 2008). Each of the key constructs in the UESBM will be
subject to testing. Each corresponding measurement model will be presented in this
section. The key constructs are outlined as follows: (1) User Experience Sharing
(UESC and UESF), (2) Attitudes toward User Experience Sharing (ATT), (3)
Subjective Norm (SN), (4) Consumer Competency (COMP), (5) Intention to engage
in User Experience Sharing (INT), (6) Enjoyment in Helping Others (EIHO) and (7)
Consumer Empowerment (EMP).
Assessment of Model Fit
The Chi-square test has been criticised for its sensitivity to sample sizes and
deviations from normality (Bagozzi, 1981). To address this concern, five Goodness
of Fit indices were used to assess model fit: the Chi-square X2 test, CMIN/DF, CFI,
RMSEA and SRMR (Hair, et al., 2006). The thresholds for each fit index are listed
in Table 5.2.
Table 5.2 Fit Indices
Chi-square CMIN/DF CFI RMSEA SRMR
P ≥ .05 ≤ 3 ≥ .95 Good Fit:
≤ .05
Acceptable Fit:
≤ .08
Good Fit:
≤ .05
Acceptable Fit:
≤ .08
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Model Re-specification
For model re-specification, the three rules that were applied are explained as follows:
1) The estimated loadings should generally be .7 or higher (Hair, et al., 2007); 2)
Standardised residuals which are less than 2.58 are considered satisfactory (Byrne,
2006); 3) Modifications indices of 4 or more suggest that the fit could be improved
(Byrne, 2006). Importantly, each re-specification decision was justified according to
theoretical considerations.
5.3.1 Measurement Model for User Experience Sharing
Initial estimation of the measurement model indicated the one-dimensional model
was a poor fit of the model to the data across both samples. The CMIN/DF was well
above the acceptable ratio which is at or below 3. The other fit indices also indicated
the poor fit with the CFI below the threshold value of ≥ .95, and the RMSEA and
SRMR above the upper threshold value of ≤ .08.
Using the factor test in AMOS, the eigenvalue suggests a possible two-dimensional
construct containing five indicators. The eigenvalue greater than .80 was accepted
because the construct was new and face validity also suggested a two-dimensional
construct is appropriate. Therefore, a further test using two-factor dimensional was
conducted. The CMIN/DF value was slightly above 3 at 3.262, and the Chi-square
X2 test was significant (P=0.011). Considering the large sample size (n=326), the
significant results are acceptable. RMSEA was also slightly higher than the
suggested .08 threshold at .083. However, the model was supported by the CFI, and
SRMR. The CFA results for User Experience Sharing are presented in Table 5.3.
Table 5.3 User Experience Sharing Model Fit
Two factors
UESC & UESF
X2 DF p CMIN/
DF
CFI RMS
EA
SRMR
Original 149.3 5 .000 29.857 .831 .298 0.961
Final 13 4 .011 3.262 .989 .083 .0254
5.3.2 Measurement Model for Attitudes toward User Experience Sharing
The initial examination indicated that the measurement model was a poor fit of the
model to the data. The CMIN/DF was above the acceptable ratio which is at or
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below 3. The other fit indices also indicated the poor fit with the CFI below the
threshold value of ≥ .95, and the RMSEA above the upper threshold value of ≤ .08.
However, SRMR was below the upper threshold .08 but above stricter threshold .05.
As a result, a re-specification was conducted. From this point, it becomes an
exploration instead of a confirmation process. After the re-specification, ATT2, 3
and 4 were removed using the criteria of SRV and M.I. After the re-specification, all
other indices were satisfied. As further re-specification will result in just
identification as well as the concern of over specification, no further re-specification
was conducted. The CFA results for Attitudes toward User Experience Sharing are
presented in Table 5.4.
Table 5.4 Attitudes toward User Experience Sharing Model Fit
ATT 1, 5, 6, 7 & 8 X2 DF p CMIN/
DF
CFI RMS
EA
SRMR
Original 188.4 20 .000 9.421 .882 .161 .0667
Final 11.5 5 .043 2.297 .992 .063 .0206
5.3.3 Measurement Model for Subjective Norm
The initial examination indicated that the measurement model was a good fit of the
model to the data as all indices were satisfied. The CMIN/DF was above the
acceptable ratio which is at or below 3. The other fit indices indicated the good fit
with the CFI above the threshold value of ≥ .95, and the SRMR below the lower
threshold value of ≤ .05. However, RMSEA was above the lower threshold .05. No
further re-specification was conducted for the concern of over specification. The
CFA results for Subjective Norm are presented in Table 5.5.
Table 5.5 Subjective Norm Model Fit
SN 1, 2, 3 and 4 X2 DF p CMIN/
DF
CFI RMS
EA
SRMR
Original 4.5 2 .103 2.272 .995 .063 .0178
5.3.4 Measurement Model for Consumer Competence
The original construct indicates the three-dimensional model was a poor fit of the
model. The CMIN/DF was above the acceptable ratio which is at or below 3. The
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other fit indices also indicated the poor fit with the CFI below the threshold value of
≥ .95, and the RMSEA above the upper threshold value of ≤ .08.
As a result, a re-specification was conducted. From this point, it becomes an
exploration instead of a confirmation process. After the re-specification NO3 and
NO4 were removed using the criteria of SRV and M.I. As a result, the CMIN/DF
was below 2. All other indices were satisfied. The CFA results for Consumer
Competence are presented in Table 5.6.
Table 5.6 Consumer Competence Model Fit
TS 1, 2, 3, NO 1, 2
and 5, and NW 1, 2
X2 DF p CMIN/
DF
CFI RMS
EA
SRMR
Original 176.2 32 .000 5.507 .879 .118 .0574
Final 25.9 17 .077 1.521 .989 .040 .0263
5.3.5 Measurement Model for Intention to Engage in User Experience Sharing
The original construct indicates the one-dimensional model was an acceptable fit of
the model to the data. The other fit indices indicated a good fit with the CFI above
the threshold value of ≥ .95, and the SRMR below the lower threshold value of ≤ .05.
However, the CMIN/DF was above the acceptable ratio which is at or below 3 as
well as RMSEA were above the upper threshold .08. There was no further re-
specification to avoid over re-specification. In addition, any re-specification will
result in just identification where measurement examination cannot be performed.
The CFA results for Intention to Engage in User Experience Sharing are presented in
Table 5.7.
Table 5.7 Intention to Engage in User Experience Sharing Model Fit
INT 1, 2, 3 and 4 X2 DF p CMIN/
DF
CFI RMS
EA
SRMR
Original 12.3 2 .002 6.145 .988 .126 .0219
5.3.6 Measurement Model for Enjoyment in Helping Others
The original construct indicates a one-dimensional model. The CMIN/DF was above
the acceptable ratio which is at or below 3. According to other fit indices, only
SRMR at .0395 was below the threshold and all other indices do not meet the criteria.
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The measurement model was a poor fit. Any re-specification will result in just
identification where measurement examination cannot be performed. There was no
re-specification conducted. The CFA results for Enjoyment in Helping Others are
presented in Table 5.8.
Table 5.8 Enjoyment in Helping Others Model Fit
EIHO 1, 2, 3 and 4 X2 DF p CMIN/
DF
CFI RMS
EA
SRMR
Original 50.7 2 .000 25.362 .937 .274 .0395
5.3.7 Measurement Model for Consumer Empowerment
The original construct indicates the one-dimensional model was a poor fit for the
model to the data. The CMIN/DF was above the acceptable ratio which is at or
below 3. The other fit indices also indicated a poor fit with the CFI below the
threshold value of ≥ .95, and the RMSEA above the upper threshold value of ≤ .08.
As a result, a re-specification was conducted. From this point, it becomes an
exploration instead of a confirmation process. After the re-specification, EMP2 was
removed using the criteria of SRV and M.I. CMIN/DF was still above 3. To avoid
the issue of over specification, no further re-specification was conducted. Despite the
higher CMIN/DF (5.901) and RMSEA (.123), all other indices supported the re-
specified measurement model of the construct. The CFA results for Consumer
Empowerment are presented in Table 5.9.
Table 5.9 Consumer Empowerment Model Fit
(EMP1, 3, 4 and 5) X2 DF p CMIN/
DF
CFI RMS
EA
SRMR
Original 68.1 5 .000 13.625 .910 .197 .0631
Final 11.8 2 .003 5.901 .981 .123 .0310
5.4 User Experience Sharing Behaviour Full Measurement Model
The re-specified constructs above were used to conduct full measurement analysis.
The results indicate the measurement model has an acceptable fit as fit indices were
satisfactory if using high thresholds. However, X2 1047.6 was quite large although
the CMIN/DF met the acceptable ratio which is at or below 3. This is because there
are several constructs that were just-identified and could not perform CFA. After
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further specification was conducted, ATT1, SN1, NO5, INT1, EIHO3, and EMP1
were removed using the criteria of SRV and M.I. The full measurement model was
significantly improved. The Results are presented in Table 5.10. The UESBM full
measurement is presented in Figure 5.1.
Table 5.10 UESBM Full Measurement Model
X2 DF p CMIN/
DF
CFI RMS
EA
SRMR
Using Re-specified
Constructs
1047.6 496 .000 2.112 .912 .058 .0654
Further Re-specified 556.7 319 .000 1.745 .955 .048 .0446
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Figure 5.1 UESBM Full Measurement Model
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5.5 Reliability and Validity Analysis for UESBM
The internal reliability analysis was conducted as the initial step of the measurement
specification (Hair, et al., 2006). Convergent and Discrimination validity tests were
also conducted before conducting the structure model test (Anderson & Gerbing,
1988; Bagozzi & Yi, 1988). The results should exceed the threshold values for
Cronbach's Alpha, Average Variance Extracted and Composite Reliability which are
0.7, 0.5 and 0.6 respectively (Bagozzi, 1981; Hair, et al., 2006). The values of
Cronbach's Alpha, Average Variance Extracted and Composite Reliability are
reported in Table 5.11. They provide information about how well the sets of multiple
indicators capture the constructs of interest (Bagozzi & Yi, 1988; Steenkamp &
Baumgartner, 2000). Table 5.11 illustrates the results of Cronbach's Alpha, Average
Variance Extracted and Composite Reliability.
Table 5.11 Reliability of Measures for UESBM
Reliability of Measures for UESBM model
Measure Individual
Item
Reliability
Cronbach's
Alpha
Composite
Reliability
Average
Variance
Extract
ATT 0.89 0.89 0.68
ATT5 0.784
ATT6 0.867
ATT7 0.826
ATT8 0.809
SN 0.87 0.87 0.69
SN2 0.767
SN3 0.892
SN4 0.833
INT 0.92 0.92 0.80
INT2 0.888
INT3 0.933
INT4 0.856
COMP 0.65 0.77 0.54
TS 0.906 0.74
TS1 0.821
TS2 0.712
TS3 0.578
NO 0.734 0.82
NO1 0.919
NO2 0.755
NW 0.521 0.73
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NW1 0.724
NW2 0.792
EIHO 0.86 0.86 0.67
EIHO1 0.893
EIHO2 0.824
EIHO4 0.736
EMP 0.84 0.84 0.64
EMP3 0.734
EMP4 0.812
EMP5 0.846
UESC 0.87 0.87 0.69
UESC1 0.800
UESC2 0.811
UESC3 0.871
UESF 0.83 0.85 0.75
UESF1 0.990
UESF2 0.719
Internal Reliability Test Results
User Experience Sharing was operationalised using two factors, with UESC
containing three items and UESF containing two items. The scale reliability results
were good with a Cronbach alpha of .87 for UESC and of .83 for UESF. ATT was
operationalised using four items. The scale reliability for the construct was .89. SN
was operationalised using three items. The scale reliability for the construct was
good with a Cronbach alpha of .87. COMP is a three-factor higher order construct
with a total ten items adapted from the consumer savvy scale (Macdonald & Uncles,
2007). The three factors were Technological Sophistication (TS) using three items,
Interpersonal Network Competency (NW) using two items, and Online Network
Competency (NO) using two items. Cronbach alphas of all three sub-constructs were
above the recommended theoretical threshold (> .70). However, the Cronbach alpha
is lower than 0.7 for the higher order construct. INT was operationalised using three
items. The scale reliability for the construct was .92. Higher alphas were expected
because similar vocabulary, as suggested by the original author of Theory of Planned
Behaviour, was used. EIHO was operationalised using three items. The tests resulted
in the same Cronbach alpha of .86. Finally, EMP was operationalised using three
items. The scale reliability for the construct was .84. In sum, except CMOP, all other
constructs satisfied the theoretical threshold (>.7) and were mostly above .8.
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5.6 User Experience Sharing Behaviour Full Structure Equation Model
A model development approach was adopted. In Study One, the data was used to
calibrate the model. The final model had a good fit. X2 was very close to and
CMIN/DF was the same as the results in the full measurement model. All fit indices
indicated a good fit to the dataset. CMIN/DF was under 2. CFI was .95 above the
required threshold. RMESA and SRMR were also under the recommended threshold
at .048 and .046. According to the fit indices presented in Table 5.12, the UESBM
was accepted.
Table 5.12 UESBM Model Fits
Full SEM Models X2 DF p CMIN/
DF
CFI RMS
EA
SRMR
UESBM 563.6 323 .000 1.745 .954 .048 .0461
Results of UESBM
In this model, User Experience Sharing behaviour is represented by User Experience
Sharing with Other Consumers and User Experience Sharing with Firms. Notably,
consumer empowerment had no significant impact on intention to engage in UES (β
= - .05, p = .316) and the actual User Experience Sharing either with Other
Consumers (β = - .07, p= .224). It had a weak negative impact on User Experience
Sharing with firms (β = - .015, p= .015). Enjoyment in Helping Others and
Consumer Competence were the two most significant constructs influencing
intention to engage in UES and the actual User Experience Sharing. Nevertheless,
Consumer Competence had no significant impact on User Experience Sharing with
Firms (β = .09, p= .329). In particular, Enjoyment in Helping Others had a higher
impact on intention to engage in UES and the actual User Experience Sharing than
all other constructs in the model. In terms of original Theory Planned Behaviour
constructs, Attitude (β = .16, p= .008) had a positive impact on Intention and
Subjective Norm had no significant impact on Intention (β= .08, p=.142). Intention
had no significant impact on User Experience Sharing with Other Consumers (β
= .12, p=.117) and a positive significant impact on User Experience Sharing with
Firms (β = .16, p= .048). Figure 5.2 depicts the full SEM model results.
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Figure 5.2 User Experience Sharing Behaviour Full SEM Model
Attitudes toward UES
Subjective Norm
Consumer Competence
Intention to Engage in UES
User Experience Sharing with Other
Consumers
User Experience Sharing with Firms
ns
.16*
Consumer Empowerment
Enjoyment in Helping Others
ns.35***
- .15*.33***
ns
.30***
.16**
ns
.37*** ns
.30**
Notes: * p=<0.05, **p=<0.01, ***p=<0.001, and ns (not significant)
P a g e | 134
5.7 Test of Hypotheses for User Experience Sharing Behaviour Model
According to the SEM, the model is sustained. The tests of the hypotheses are
reported in Table 5.13. These findings are discussed in more detail in Chapter Six
where they will be compared with the hypotheses tests with the confirmatory
UESBM.
Table 5.13 Hypotheses Testing for UESBM
HU1 Attitudes toward UES relate positively to intention to engage in
UES.
Supported
HU2 Subjective Norm relates positively to Intention to engage in UES. Not
Supported
HU3 Consumer Competence relates positively to intention to engage in
UES.
Supported
HU4 Consumer Competence relates positively to User Experience
Sharing.
Partially
Supported
HU5 Intention to engage in knowledge sharing relates positively to User
Experience Sharing.
Partially
Supported
HU6a Enjoyment in helping others relates positively to intention to
engage in UES.
Supported
HU6b Hypothesis 6b. Enjoyment in helping others relates positively to
User Experience Sharing.
Supported
HU7a Consumer Empowerment relates positively to intention to engage
in UES.
Not
Supported
HU7b Consumer Empowerment relates positively to User Experience
Sharing.
Not
Supported
Co-Creative Consumer Motivation Model
5.8 Test of Measurement for Co-Creative Consumer Motivation Model
In the CCMM, the key constructs includes: (1) Value Oriented User Experience
Sharing Behaviour (UES) (2) Opportunities - Newness (NEW), (3) Consumer
Citizenship (CIT), (4) Relating Needs (REL), (5) Use Innovativeness (UI), (6)
Mavenism (MAV), (7) Personal initiative (PIN) and (8) Communality (COMU). The
same procedures presented from 5.3 to 5.6 were applied here, Confirmatory Factor
Analysis (CFA) was performed. Each of the key constructs in the proposed model
will be subject to testing. Each corresponding measurement model will be presented
in this section.
P a g e | 135
In total, five Fit indices were used to assess model fit, including the Chi-square X2
test, CMIN/DF, CFI, RMSEA and SRMR. The thresholds for each fit index are the
same as listed in Section 5.3.
5.8.1 Measurement Model for User Experience Sharing
Due to the constraint of just identification, the measurement analysis for UES was
not applicable. The construct was later tested in the full measurement model.
5.8.2 Measurement Model for Newness
The original construct indicates a one-dimensional model. All indices indicated a
very good fit of the measurement model across both samples. The CFA results for
Newness are presented in Table 5.14.
Table 5.14 Newness Model Fit
New 1, 2, 3, 4 & 5 X2 DF p CMIN/
DF
CFI RMS
EA
SRMR
Original 5.6 5 .349 1.116 .999 .019 .0175
5.8.3 Measurement Model for Consumer Citizenship
The original construct indicates a one-dimensional model. The CMIN/DF was above
the acceptable ratio which is at or below 3. RMSEA was above the upper threshold.
Nevertheless, the CFI was above the threshold value of ≥ .95, and the SRMR below
the lower threshold value of ≤ .05. Any re-specification will result in just
identification where measurement examination cannot be performed. Therefore, the
measurement model was accepted without re-specification. The CFA results for
Consumer Citizenship are presented in Table 5.15.
Table 5.15 Consumer Citizenship Model Fit
CIT 1, 2, 3 and 4 X2 DF p CMIN/
DF
CFI RMS
EA
SRMR
Original 19.2 2 .000 9.608 .956 .163 .0385
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5.8.4 Measurement Model for Relating Needs
Using the factor test in AMOS, the eigenvalue suggests a possible two-dimensional
construct containing eight indicators. After the initial estimation of the measurement
model, the two-dimensional model was accepted without re-specification. The
CMIN/DF was below the acceptable ratio which is at or below 3. The other fit
indices also indicated the good fit with the CFI above the threshold value of ≥ .95,
the SRMR below their lower threshold value of ≤ .05, and the RMSEA below the
upper threshold value of ≤ .08. The CFA results for Relating Needs are presented in
Table 5.16.
Table 5.16 Relating Needs Model Fit
REL X2 DF p CMIN/
DF
CFI RMS
EA
SRMR
Original 25.7 13 .019 1.973 .987 .055 .0354
5.8.5 Measurement Model for Use Innovativeness
The initial examination indicated that the measurement model was a poor fit of the
model to the data. The CMIN/DF was above the acceptable ratio which is at or
below 3. The other fit indices also indicated the poor fit with the CFI below the
threshold value of ≥ .95, the SRMR and the RMSEA above the upper threshold .08.
As a result, a re-specification was conducted. From this point, it becomes an
exploration instead of a confirmation process. With the considerations of over
specification, UI 4, 7, 8, 9 and 10 were removed using the criteria of SRV and M.I.
After the re-specification, all indices were satisfied which indicated a good fit of the
re-specified measurement model. The CFI was above .95, and both RMSEA and
SRMR were below the lower threshold .05. The CFA results for Use Innovativeness
are presented in Table 5.17.
Table 5.17 User Innovativeness Model Fit
UI1,2,3,5 & 6 X2 DF p CMIN/
DF
CFI RMS
EA
SRMR
Original 245.9 35 .000 7.025 .841 .136 .0820
Final 7.1 5 .214 2.429 .996 .036 .0203
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5.8.6 Measurement Model for Mavenism
The initial examination indicated that the measurement model was a poor fit of the
model to the data. Only the SRMR was below the lower threshold .05. The
CMIN/DF was above the acceptable ratio which is at or below 3. The other fit
indices also indicated the poor fit with the CFI below the threshold value of ≥ .95,
and the RMSEA above the upper threshold .08. As a result, a re-specification was
conducted. From this point, it becomes an exploration instead of a confirmation
process. With the considerations of over specification, MAV1 and 2 were removed
using the criteria of SRV and M.I.
After the re-specification, all indices were satisfied which indicated a acceptable fit
of the re-specified measurement model. The CFI (1.00) met the thresholds, and both
RMSEA and SRMR were under the lower threshold .05. The CFA results for
Mavenism are presented in Table 5.18.
Table 5.18 Mavenism Model Fit
MAV 3, 4, 5 and 6 X2 DF p CMIN/
DF
CFI RMS
EA
SRMR
Original 106.1 9 .000 11.792 .929 .182 .0468
Final 2.0 2 .374 .982 1.000 .000 .0077
5.8.7 Measurement Model for Personal Initiative
The initial examination indicated that the measurement model was a poor fit of the
model to the data. Only the SRMR was below the upper threshold .08. The
CMIN/DF was above the acceptable ratio which is at or below 3. The other fit
indices also indicated a poor fit with the CFI below the threshold value of ≥ .95, and
the RMSEA above the upper threshold .08. As a result, a re-specification was
conducted. From this point, it becomes an exploration instead of a confirmation
process. With the considerations of over specification, PIN1, 2 and 7 were removed
using the criteria of SRV and M.I.
After the re-specification, all indices were satisfied which indicated an acceptable fit
of the re-specified measurement model. The CFI (1.00) was above the thresholds,
P a g e | 138
and both RMSEA and SRMR were under the lower threshold .05. The CFA results
for Personal Initiative are presented in Table 5.19.
Table 5.19 Personal Initiative Model Fit
PIN3, 4, 5 and 6 X2 DF p CMIN/
DF
CFI RMS
EA
SRMR
Original 95.7 14 .000 6.835 .896 .134 .0593
Final 0.2 2 .909 .095 1.000 .000 .0044
5.8.8 Measurement Model for Communality
The initial examination indicated that the measurement model was a very good fit of
the model to the data despite the RMSEA was slightly above the lower threshold .05
but well below the upper threshold .08. The other fit indices indicated the good fit
with the CFI above the threshold value of ≥ .95, and the SRMR below the
threshold .05. As a result, no further re-specification was conducted. The CFA
results for Communality are presented in Table 5.20.
Table 5.20 Communality Model Fit
COMU 1, 2, 3, 4, 5 X2 DF p CMIN/
DF
CFI RMS
EA
SRMR
Original 9.5 5 .090 1.903 .984 .053 .0315
P a g e | 139
5.9 Full Measurement Model for Co-Creative Consumer Motivation Model
The re-specified constructs above were used to conduct full measurement analysis.
The results indicate the measurement model has an acceptable fit as fit indices were
satisfactory if using high thresholds. However, X2 1088.8 was quite large although
the CMIN/DF met the acceptable ratio which is at or below 3. In turn, a re-
specification was conducted. From this point, it becomes an exploration instead of a
confirmation process. After the re-specification, New1and 2, CIT1, RELS1, UI2,
MAV6, PIN6 and COMU3 and 5 were removed using the criteria of SRV and M.I.
The full measurement model was significantly improved. The Results are presented
in the tables below. For comparison, the same procedure was conducting to test
Relating Needs as a low order construct. The results are presented in Table 5.21 and
Table 5.22, and the CCMM full measurement models are also depicted below in
Figure 5.3 and 5.4.
Table 5.21 Full Measurement Model using Higher Order REL
CCMM HO X2 DF p CMIN/
DF
CFI RMS
EA
SRM
R
Using Re-specified
Constructs
1088.8 564 .000 1.931 .907 .054 .0617
Re-specified in the
measurement model
566 320 .000 1.769 .942 .049 0.487
Table 5.22 Full Measurement Model using Lower Order RELS and RELO
CCMM LO X2 DF p CMIN/
DF
CFI RMS
EA
SRMR
Using Re-specified
Constructs
1079.9 558 .000 1.935 .907 .054 .0610
Re-specified in the
measurement model
556.2 314 .000 1.771 .943 .049 .0475
P a g e | 140
Figure 5.3 CCMM Higher Order Full Measurement Model
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Figure 5.4 CCMM Lower Order Full Measurement Model
P a g e | 142
5.10 Reliability and Validity Analysis for Co-Creative Consumer Motivation
Model
The internal reliability analysis was conducted as the initial step of the measurement
specification (Black et al. 2006). Convergent and Discrimination validity tests were
also conducted before conducting the structure model test (Anderson & Gerbing,
1988; Bagozzi & Yi, 1988). The results should exceed the threshold values for
Cronbach's Alpha, Average Variance Extracted and Composite Reliability which are
0.7, 0.5 and 0.6 respectively (Bagozzi, 1981; Hair, et al., 2006). The values of
Cronbach's Alpha, Average Variance Extracted and Composite Reliability are
reported in Table 5.23. They provide information about how well the sets of multiple
indicators capture the constructs of interest (Bagozzi & Yi, 1988; Steenkamp &
Baumgartner, 2000). The following Table 5.23 provides the results of reliability of
measures for CCMM.
Table 5.23 Reliability of Measures for CCMM
Reliability of Measures for CCMM model
Measure Individual
Item
Reliability
Cronbach's
Alpha
Composite
Reliability
Average
Variance
Extract
NEW 0.82 0.83 0.61
NEW3 0.681
NEW4 0.840
NEW5 0.820
CIT 0.80 0.80 0.57
CIT2 0.729
CIT3 0.815
CIT4 0.727
RELS 0.80 0.81 0.59
RELS2 0.616
RELS3 0.830
RELS4 0.835
RELO 0.82 0.82 0.61
RELO1 0.717
RELO2 0.825
RELO3 0.799
UI 0.76 0.77 0.45
UI1 0.774
UI3 0.781
UI5 0.655
UI6 0.615
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MAV 0.89 0.89 0.74
MAV3 0.580
MAV4 0.806
MAV5 0.674
PIN 0.80 0.78 0.55
PIN3 0.832
PIN4 0.867
PIN5 0.876
COMU 0.72 0.73 0.47
COMU1 0.586
COMU2 0.708
COMU4 0.757
UES 0.81 0.90 0.63
UES1 0.577
UES2 0.921
UES3 0.847
Internal Reliability Test Results
The internal reliability test for each of the key constructs is described as follows.
UES was operationalised using three items. The scale reliability for the construct
was good with a Cronbach alpha of .81. NEW was operationalised using three items.
The scale reliability for the construct was good with a Cronbach alpha of .82. CIT
was operationalised using three items. The scale reliability for the construct was also
adequate with a Cronbach alpha of .80. REL is proposed as a two-factor construct.
Two factors were Relating Needs of Self (RELS) using three items and Relating
Needs of Others (RELO) using three items. First, the scale reliability for the sub-
construct, RELS, was good with a Cronbach alpha of .80. Second, the scale
reliability for the sub-construct, RELO, was .82. Cronbach alphas of both sub-
constructs were similar, and well above the recommended theoretical threshold
(> .70). UI was operationalised using four items. The scale reliability for the
construct was with a Cronbach alpha of .76. MAV was operationalised using three
items. The scale reliability for the construct was .89. PIN was operationalised using
three items. The scale reliability for the construct .80. COMU was operationalised
using three items. The scale reliability for the construct was .72. In sum, all final
items of the key constructs satisfied the theoretical threshold cut off point .70
recommended by Nunnally (1978).
P a g e | 144
5.11 Co-Creative Consumer Motivation Full Structural Equation Model
A model development approach was adopted. In this study, the data is being used to
calibrate the model. The final (lower order) model has a good fit. CMIN/DF was
under 2. X2 and CMIN/DF were slightly higher than the result in the full
measurement model. CFI (.939) was slightly below the stricter threshold. SRMR
(.518) was also slightly above the stricter threshold. RMESA was under the
recommended threshold at .049. All fit indices indicated a good fit to the dataset and
the CCMM (lower order) model was accepted. Despite being higher order CCMM
had a slightly low X2. The lower order CCMM provides more information. Also, the
path loading from Use Innovativeness to Relating Needs is extremely high in the
higher order CCMM which may distort the result of other paths (e.g., REL to CIT or
REL to UES). This result shown in Figure 5.6 also indicated Relating Needs may be
under-identification due to only two sub-constructs RELS and RELO.
Table 5.24 CCMM Full SEM Model
CCMM SEM X2 DF p CMIN/
DF
CFI RMS
EA
SRMR
Lower Order 588.5 332 .000 1.773 .939 .049 .0518
Higher Order 586.3 333 .000 1.761 .940 .048 .0523
Results of CCMM
In the CCMM, User Experience Sharing behaviour is represented by Value Oriented
User Experience Sharing. Amongst co-creation MOA factors, Consumer Citizenship
(Motivation) and Relating Needs of Self (Ability) have positive and significant
impacts on User Experience Sharing. The path loading of Consumer Citizenship to
User Experience Sharing was (β =.24, p=.002). The path loading of Relating Needs
of Self to UES was (β =.21, p=.013). Relating Needs to Others has no significant
impact on UES at (β =.15, p= .070). Newness has no significant impact on UES (β
=.07, p= .243). Notably, Use Innovativeness had a positive and significant impact on
all co-creation MOA factors. UI had a very strong impact on Relating Needs of Self
(β =.72, p<0.001) and Relating Needs of Others (β =.73, p<0.001), on Consumer
Citizenship (β =.58, p<0.001) and on Newness (β =.42, p<0.001). UI to CIT and UI
to NEW were two new paths identified in the model development. In terms of
personal characteristics, Mavenism has a positive impact on RELS (β =.15, p=.005)
P a g e | 145
but no significant impact on RELO (β =.09, p=.135). Personal Initiative and
Communality both had no significant impact on Consumer Citizenship (β =.06, p
=.515, and β =.07, p=.453 respectively) when considering the strong impact on UI. A
lower order CCMM full SEM model is presented in Figure 5.5. For comparison, a
higher order CCMM full SEM model is presented in Figure 5.6.
Figure 5.5 CCMM Lower Order Full SEM Model
Notes: * p=<0.05, **p=<0.01, ***p=<0.001, and ns (not significant)
Newness
Consumer Citizenship
Relating Needs of Self
User Experience
Sharing
Personal Initiative
Use Innovativeness
Communality
Mavenism
ns
.24**
ns
ns
.72***
.15**
.58***
.42***
Relating Needs of Others
.21*
ns
.73***
ns
P a g e | 146
Figure 5.6 CCMM Higher Order Full SEM Model
Notes: * p=<0.05, **p=<0.01, ***p=<0.001, and ns (not significant)
Newness
Consumer Citizenship
User Experience
Sharing
Personal Initiative
Use Innovativeness
Communality
Mavenism
ns
ns
ns
ns
.42***
Relating Needs
.45***
.95***
ns
.56***
P a g e | 147
5.12 Test of Hypotheses for Co-Creative Consumer Motivation Model
According to the SEM, the CCMM model is sustained and all constructs are
positively correlated with User Experience Sharing. The tests of the hypotheses are
reported in Table 5.25 as follows.
Table 5.25 Test of Hypotheses for CCMM
CCMM Hypothesis Results
HS1 Newness relates positively to Value Oriented User
Experience Sharing.
Not
Supported
HS2 Consumer Citizenship relates positively to Value Oriented
User Experience Sharing.
Supported
HS3 Relating Needs relates positively to Value Oriented User
Experience Sharing.
Partially
Supported
HS4 Use Innovativeness relates positively to Relating Needs. Supported
HS5 Mavenism is relates positively to Relating Needs. Partially
Supported
HS6 Personal Initiative relates positively to Consumer
Citizenship.
Not
Supported
HS7 Communality relates positively to Consumer Citizenship. Not
Supported
New
Path
Use Innovativeness relates positively to Consumer
Citizenship.
New
Finding
New
Path
Use Innovativeness relates positively to Newness. New
Finding
5.13 Summary
This chapter illustrated the results conducted from the data analyses using CFA and
SEM. Next, in Chapter 6, the results of a replica study will be presented.
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CHAPTER SIX STUDY TWO RESULTS
6.0 Introduction
The previous chapter presented the results from Study One. This chapter reports the
results from Study Two. Taking a model development approach, Study Two is a
replica study to confirm the User Experience Sharing Behaviour Model and the Co-
Creative Consumer Motivation Model developed in Study One. The chapter is
organised as follows. First, the results of the preliminary analysis of the data and
descriptive statistics of the sample are presented. Second, the results of the reliability
analysis for each of the constructs are reported. Third, the results of full SEM
analysis and K-means cluster analysis are reported. Fourth, the tests of the
hypotheses are illustrated. Finally, the conclusion of the chapter is provided.
6.1 Study Two Sample Characteristics
The sample in Study Two was collected mainly from Apple product online
communities, including MacTalk.com.au, MacRumors Forums, ilounge.com, and
mybuzz.com.au. A small portion of samples are iPhone users recruited from
Facebook and offline. The Study Two sample consisted of respondents aged over 18
years old. There was a large male sample of 251 compared to a small female sample
of 40. The majority of respondents achieved a 12-year high school qualification
(95.3%) and a majority of respondents live in Australia (97) and the USA (142).
Table 6.1 shows the sample characteristics in terms of gender, age, education and
residence.
Table 6.1 Sample Characteristics of Respondents
Study 2 N = 294 Total Number Percentage %
Gender Total 291 99.0%
male 251 85.4%
Female 40 13.6%
Age Total 294 100%
18 - 25 89 30.3%
26 - 35 81 27.6%
36 - 45 80 27.2%
46 - 55 33 11.2%
56 - 65 10 3.4%
Above 65 1 0.3%
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Education Total 294 100%
Less than 10 years
schooling
0 0.0%
10 years to 11 years of
schooling
11 3.7%
12 years of schooling 23 7.8%
Basic vocational
qualification
6 2.0%
Skilled vocational
qualification
10 3.4%
Diploma or Associate
diploma
29 9.9%
Undergraduate degree
(Bachelors)
99 33.7%
Postgraduate
certificate/diploma
29 9.9%
Coursework Masters 32 10.9%
Research Masters 14 4.8%
PhD or ABD 24 8.2%
Professional qualification 14 4.8%
others 3 1.0%
Residence Total 294 100%
Australia 97 33.0%
UK 24 8.2%
USA 142 48.3%
Others 31 10.5%
6.2 Data Preparation and Preliminary Analysis
The data collected through the online survey were automatically collated into an
Excel database when participants clicked the submit button, resulting in no entry
errors. This database was converted into SPSS 17.0 for preliminary analysis. There is
a low percentage of missing values. According the MCAR test, the data is missing at
random (MAR). The EM algorithm (Dempster, et al., 1977) is used to compute
incomplete MAR data. Outlier and normality was checked using AMOS 17.0. The
Mahalanobis D2 results indicated that many cases are multivariate outlier. To reflect
the true data, the outlier cases were kept. Normality is also checked and show that
data were non-normal. After the preliminary analysis process, AMOS 17.0 was used
to conduct SEM analysis. CFA were conducted with the same results (items of each
construct retained) as shown in Chapter 5. As the second data set is used to confirm
the proposed models, only the results of Reliability and Validity Analysis and the
structure model tests are presented in sequence in the following sections. The results
of User Experience Sharing Behaviour Model (UESBM) are first reported followed
by the results of the Co-Creative Consumer Motivation Model (CCMM). This
chapter also presents the results of the data analyses conducted using K-means
Cluster Analyses.
P a g e | 150
6.3 Reliability and Validity Analysis for User Experience Sharing Behaviour
Model
The internal reliability analysis was conducted as the initial step of the measurement
specification (Hair, et al., 2006). Convergent and Discrimination validity tests were
also conducted before conducting a structure model test (Anderson & Gerbing, 1988;
Bagozzi & Yi, 1988). The results should exceed the threshold values for Cronbach's
Alpha, Average Variance Extracted and Composite Reliability which are 0.7, 0.5 and
0.6 respectively (Bagozzi, 1981; Hair, et al., 2006). The values of Cronbach's Alpha,
Average Variance Extracted and Composite Reliability are reported in Table 6.2.
They provide information about how well the sets of multiple indicators capture the
constructs of interest (Bagozzi & Yi, 1988; Steenkamp & Baumgartner, 2000). Table
6.2 illustrates the results of Cronbach's Alpha, Average Variance Extracted and
Composite Reliability.
Table 6.2 Reliability of Measures for UESBM
Reliability of Measures for model
Measure Individual
Item
Reliability
Cronbach's
Alpha
Composite
Reliability
Average
Variance
Extract
ATT 0.91 0.92 0.73
ATT5 0.822
ATT6 0.878
ATT7 0.918
ATT8 0.796
SN 0.83 0.83 0.62
SN2 0.773
SN3 0.784
SN4 0.811
INT 0.94 0.94 0.84
INT2 0.906
INT3 0.932
INT4 0.916
COMP 0.63 0.74 0.50
TS 0.855 0.79
TS1 0.881
TS2 0.771
TS3 0.592
NO 0.786 0.86
NO1 0.939
NO2 0.811
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NW 0.418 0.76
NW1 0.644
NW2 0.946
EIHO 0.86 0.86 0.68
EIHO1 0.838
EIHO2 0.858
EIHO4 0.771
EMP 0.81 0.82 0.60
EMP3 0.778
EMP4 0.814
EMP5 0.728
UESC 0.89 0.89 0.74
UESC1 0.846
UESC2 0.809
UESC3 0.921
UESF 0.82 0.84 0.72
UESF1 0.940
UESF2 0.746
Internal Reliability Analysis
User Experience Sharing was operationalised using two factors, with UESC
containing three items and UESF containing two items. The scale reliability results
were good with a Cronbach alpha of .89 for UESC and of .82 for UESF. They are
consistent with Study One results (.87 and .83). ATT was operationalised using four
items. The scale reliability for the construct was relatively high with a Cronbach
alpha of .91. The final result is slightly higher than the final result in Study One
results (.89). SN was operationalised using three items. The scale reliability for the
construct was good with a Cronbach alpha of .83. It is slightly lower than Study One
results (.87). COMP is a three-factor higher order construct with the total ten items
adapted from the consumer savvy scale (Macdonald & Uncles, 2007). Three factors
were Technological sophistication (TS) using three items, Interpersonal Network
Competency (NW) using two items, and Online Network Competency (NO) using
two items. First, the scale reliability for the sub-construct, TS, was adequate with a
Cronbach alpha of .79. Second, the scale reliability for the sub-construct, NW, was
reasonable with a Cronbach alpha of .76. Third, the scale reliability for the sub-
construct, NO, was satisfactory with a Cronbach alpha of .86. All three sub-
constructs were above the recommended theoretical threshold (> .70). They are
consistent with Study One results (.74, .73 and .82). INT was operationalised using
P a g e | 152
three items. The scale reliability for the construct was relatively high with a
Cronbach alpha of .94. As the similar wordings suggested by the original author of
Theory of Planned Behaviour were used, the higher alphas are expected. The final
result is slightly higher than the Study One results (.92). EIHO was operationalised
using three items. The tests with both samples resulted in the same Cronbach alpha
of .86. Finally, EMP was operationalised using three items. The scale reliability for
the construct was adequate with a Cronbach alpha of .81. The final result is slightly
lower than the Study One result (.84). In sum, except COMP, all items of the key
constructs satisfied the theoretical threshold (>.7) and were mostly above .80.
6.4 User Experience Sharing Behaviour Full Structure Equation Model
A model development approach was adopted. In Study Two, the data was used to
replicate the model and to test the stability of the model. The final model had a good
fit. All fit indices indicated a good fit to the dataset. CMIN/DF was under 2. The CFI
was .955 above the required threshold. RMESA and SRMR were also under the
recommended threshold at .050 and .048. Compared to the model in Study One, a
similar result was obtained. The X2 difference between Study One and Study Two
was only 3. The fit indices in both studies shown in Table 6.3 indicated a good fit to
the datasets which suggests that the calibrated UESBM is accepted and confirmed.
Table 6.3 UESBM Model Fits
Full SEM Models X2 DF p CMIN/
DF
CFI RMS
EA
SRM
R
UESBM 560.6 323 .000 1.736 .955 .050 .0478
Study 1 Results 563.6 323 .000 1.745 .954 .048 .0461
Results of the User Experience Sharing Behaviour Model
In this model, User Experience Sharing behaviour is represented by User Experience
Sharing with Other Consumers and User Experience Sharing with Firms. Again,
consumer empowerment had no significant impact on intention to engage in UES (β
= - .03, p=.613) and the actual User Experience Sharing either with Other
Consumers (β =- .00, p=.966) or with firms (β =- .01, p=.844). Enjoyment in Helping
Others had a significant impact on User Experience Sharing with Other Consumers
(β =.36, p<0.001) but no impact on User Experience Sharing with Firms (β =.16,
P a g e | 153
p=.081). Consumer Competence had a strong and significant impact on intention to
engage in UES (β =.58, p<0.001). Consumer Competence had a moderate significant
impact on both User Experience Sharing with Other Consumers and Firms (β =.35,
p<0.01, and β =.37, p<0.01). Notably, Intention had no significant impact on both
User Experience Sharing with Other Consumers (β = .05, p=.622) and with firms (β
= .13, p=.269). In terms of other original Theory of Planned Behaviour constructs,
both Attitude (β = .08, p=.195) and Subjective Norm (β = .07, p=.176) had no
significant impact on Intention. A UESBM full SEM model is presented in Figure
6.1.
Figure 6.1 User Experience Sharing Behaviour Full SEM Model
Attitudes toward UES
Subjective Norm
Consumer Competence
Intention to Engage in UES
User Experience Sharing with Other
Consumers
User Experience Sharing with Firms
ns
ns
Consumer Empowerment
Enjoyment in Helping Others
ns.36***
nsns
.37**
.58***
ns
ns
.24** ns
.35**
Notes: * p=<0.05, **p=<0.01, ***p=<0.001, and ns (not significant)
6.5 Test of Hypotheses for User Experience Sharing Behaviour Model
According to the SEM, the model is confirmed. The tests of the hypotheses shown in
Table 6.4 are reported as follows.
Hypothesis U1 posits that Attitudes toward UES (ATT) relate positively to intention
to engage in UES (INT). In Study One, the results showed that hypothesis U1 was
supported, but it was not supported in Study Two. In Study One, as hypothesised,
P a g e | 154
ATT is significantly correlated with INT (β = .16, p<0.01). However, the hypothesis
was not supported (β = .08, ns) in Study Two.
Hypothesis U2 posits that Subjective Norm relates positively to Intention to engage
in UES. The results showed that hypothesis U2 was not supported in either Study
One (β= .08, ns) or Study Two (β = .07, ns).
Hypothesis U3 posits that Consumer Competence relates positively to intention to
engage in UES. The results showed that hypothesis U3 was supported in both Study
One (β = .30, p<0.001) and Study Two (β = .58, p<0.001).
Hypothesis U4 posits that Consumer Competence relates positively to User
Experience Sharing. The results showed that hypothesis U4 was supported in Study
Two and partially supported in Study One. Consumer Competence is significantly
and positively related to both UESC (β = .35, p<0.01) and UESF (β = .37, p<0.01) in
Study Two. Consumer Competence is significantly and positively related to UESC
(β = .30, p<0.01), but had no significant impact on UESF (β = .09, ns) in Study One.
Hypothesis U5 posits that Intention to engage in knowledge sharing relates
positively to User Experience Sharing. The results showed that hypothesis U5 was
partially supported in Study One and was not supported in Study Two. In Study One,
the results showed that INT is significantly and positively related to UESF (β = .16,
p<0.05), but had no significant impact on UESC (β = .12, ns). In Study Two, the
results showed that INT had no significant impact on either UESC (β = .05, ns) or
UESF (β = .13, ns).
Hypothesis U6a posits that Enjoyment in helping others relates positively to
intention to engage in UES. The results showed that hypothesis U6a was supported
in both Study One (β = .37, p<0.001) and Study Two (β = .24, p<0.01).
Hypothesis U6b posits that Enjoyment in helping others relates positively to User
Experience Sharing. The results showed that hypothesis U6b was supported in Study
One and was partially supported in Study Two. In Study One, the results showed that
EIHO had a significant impact on both UESC (β = .35, p<0.001) and UESF (β = .33,
p<0.001). In Study Two, the results showed that EIHO was significantly and
P a g e | 155
positively related to UESC (β = .36, p<0.001), but it had no significant impact on
UESF (β = .16, ns).
Hypothesis U7a posits that Consumer Empowerment relates positively to intention
to engage in UES. The results showed that hypothesis U7a was not supported in
either Study One (β = -.05, ns) or Study Two (β = -.03, ns).
Hypothesis U7b posits that Consumer Empowerment relates positively to User
Experience Sharing. The results showed that hypothesis U7b was not supported in
either Study One or Study Two. In Study One, EMP had no significant impact on
UESC (β = -.07, ns). However, in contrast to the hypothesis, EMP had a significant
and negative impact on UESF (β = -.15, p<0.05). In Study Two, EMP had no
significant impacts on either UESC (β = .00, ns) or UESF (β = -.01, ns).
The results of hypotheses testing for UESBM are presented in Table 6.4.
Table 6.4 Hypotheses Testing for UESBM
UESBM Hypothesis Study One
Results
Study Two
Results
HU1 Attitudes toward UES relate positively to intention
to engage in UES.
Supported Not
Supported
HU2 Subjective Norm relates positively to Intention to
engage in UES.
Not
Supported
Not
Supported
HU3 Consumer Competence relates positively to
intention to engage in UES.
Supported Supported
HU4 Consumer Competence relates positively to User
Experience Sharing.
Partially
Supported
Supported
HU5 Intention to engage in knowledge sharing relates
positively to User Experience Sharing.
Partially
Supported
Not
Supported
H6Ua Enjoyment in helping others relates positively to
intention to engage in UES.
Supported Supported
H6Ub Hypothesis 6b. Enjoyment in helping others
relates positively to User Experience Sharing.
Supported Partially
Supported
H7Ua Consumer Empowerment relates positively to
intention to engage in UES.
Not
Supported
Not
Supported
H7Ub Consumer Empowerment relates positively to
User Experience Sharing.
Not
Supported
Not
Supported
P a g e | 156
Co-Creative Consumer Motivation Model
6.6 Reliability and Validity Analysis for Co-Creative Consumer Motivation
Model
An internal reliability analysis was conducted as the initial step of the measurement
specification (Hair, et al., 2006). Convergent and Discrimination validity tests were
also conducted before conducting the structure model test (Anderson & Gerbing,
1988; Bagozzi & Yi, 1988). The results should exceed the threshold values for
Cronbach's Alpha, Average Variance Extracted and Composite Reliability which are
0.7, 0.5 and 0.6 respectively (Bagozzi, 1981; Hair, et al., 2006). The values of
Cronbach's Alpha, Average Variance Extracted and Composite Reliability are
reported in Table 6.5. They provide information about how well the sets of multiple
indicators capture the constructs of interest (Bagozzi & Yi, 1988; Steenkamp &
Baumgartner, 2000).
Table 6.5 Reliability of Measures for CCMM
Reliability of Measures for model
Measure Individual
Item
Reliability
Cronbach's
Alpha
Composite
Reliability
Average
Variance
Extract
NEW 0.83 0.84 0.64
NEW3 0.683
NEW4 0.890
NEW5 0.813
CIT 0.73 0.74 0.49
CIT2 0.644
CIT3 0.754
CIT4 0.688
RELS 0.82 0.83 0.62
RELS2 0.655
RELS3 0.849
RELS4 0.838
RELO 0.85 0.86 0.67
RELO1 0.671
RELO2 0.873
RELO3 0.892
UI 0.76 0.76 0.45
UI1 0.653
UI3 0.555
UI5 0.700
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UI6 0.748
MAV 0.92 0.92 0.80
MAV3 0.870
MAV4 0.862
MAV5 0.946
PIN 0.85 0.86 0.66
PIN3 0.817
PIN4 0.897
PIN5 0.723
COMU 0.78 0.79 0.56
COMU1 0.645
COMU2 0.827
COMU4 0.752
UES 0.81 0.91 0.64
UES1 0.534
UES2 0.937
UES3 0.878
Internal Reliability Test Results
The internal reliability tests for each of the key construct is described as follows.
UES was operationalised using three items. The scale reliability for the construct
was good with a Cronbach alpha of .81. NEW was operationalised using three items.
The scale reliability for the construct was good with a Cronbach alpha of .83. In both
reliability tests, alphas were well over the theoretical threshold (>.7). The final result
is consistent with the Study One result (.82). CIT was operationalised using three
items. The scale reliability for the construct was also adequate with a Cronbach alpha
of .73. The result is lower than the Study One result (.80) but still above the
recommended theoretical threshold (> .70). REL is proposed as a two-factor
construct. The two factors both used three items. First, the scale reliability for the
sub-construct, RELS, was good with a Cronbach alpha of .82. Second, the scale
reliability for the sub-construct, RELO, was good with a Cronbach alpha of .85.
Cronbach alphas of both sub-constructs were similar, and well above the
recommended theoretical threshold (> .70). The results are consistent with the Study
One results which are above (> .80). UI was operationalised using four items. The
scale reliability for the construct was good with a Cronbach alpha of .76. The result
was the same as with Study One result (.76). MAV was operationalised using three
items. The scale reliability for the construct was relatively high with a Cronbach
alpha of .92. The result is slightly higher than the Study One result (.89). PIN was
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operationalised using three items. The scale reliability for the construct was high and
vigorous with a Cronbach alpha of.85. The result is higher than the Study One result
(.80). Finally, COMU was operationalised using five items. The scale reliability for
the construct was relatively low with a Cronbach alpha of .78 which is higher than
the result of Study One (.72). In sum, all final items of the key constructs satisfied
the theoretical threshold (>.7).
6.7 Co-Creative Consumer Motivation Full Structure Equation Model
A model development approach was adopted. In Study Two, the data was used to
replicate and confirm the model. The final model had a better fit than the model in
Study One. According to fit indices, the results indicated a good fit to the dataset.
CMIN/DF was way under 2. The CFI was .95 above the required threshold. RMESA
was also under the recommended threshold at .046. SRMR was slightly higher at
close to 0.6. Based on the analytic results shown in Table 6.6, the CCMM was
accepted and confirmed.
Table 6.6 CCMM Full SEM Model
CCMM SEM X2 DF p CMIN/
DF
CFI RMS
EA
SRM
R
Lower Order 535.1 332 .000 1.612 .952 .046 .0591
Study 1 Results 588.5 332 .000 1.773 .939 .049 .0518
Results of CCMM
In the CCMM, User Experience Sharing behaviour is represented by Value Oriented
User Experience Sharing. Amongst co-creation MOA factors, Newness, Consumer
Citizenship and Relating Needs of Others had a positive and significant impact on
User Experience Sharing (β =.20, p=.003, β =.18, p=.024, and β =.19, p=.018
respectively). Relating Needs of Self had no impact on UES (β =.11, p=.196).
Use Innovativeness again had a positive and significant impact on all co-creation
MOA factors although it was not as strong as it was in Study One. Nevertheless, UI
still had a very strong impact on Relating Needs of Self (β =.67, p<0.001) and
Relating Needs of Others (β =.63, p<0.001), on Consumer Citizenship (β =.35,
p<0.001) and on Newness (β =.39, p<0.001). The two new paths identified in Study
P a g e | 159
One (i.e., UI to CIT and UI to NEW) were confirmed by this dataset. In terms of
personal characteristics, Mavenism had a positive impact on RELS (β =.18, p=.008)
and on RELO (β =.18, p=.007). Personal Initiative (β =.17, p=.025) had a positive
impact on Consumer Citizenship. Notably, Communality (β =.34, p<0.001) had a
positive and much stronger impact on Consumer Citizenship even considering the
strong impact on UI. In Study Two, all personal characteristics had a significant
impact on their corresponding co-creation MOA factors. A lower order CCMM full
SEM model is presented in Figure 6.2.
Figure 6.2 CCMM Lower Order Full SEM Model
Notes: * p=<0.05, **p=<0.01, ***p=<0.001, and ns (not significant)
Newness
Consumer Citizenship
Relating Needs of Self
User Experience
Sharing
Personal Initiative
Use Innovativeness
Communality
Mavenism
.20**
.18*
.17*
.34***
.67***
.18**
.35***
.39***
Relating Needs of Others
ns
.19*
.63***
.18**
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6.8 K-means Cluster Analysis
Cluster analysis is used to explore a natural structure among the observations based
on a multivariate profile (Hair, et al., 2007). Because the researcher's definition of
the variate is critical to the cluster analysis (Hair, et al., 2007), the factors selected
are those tested and confirmed (hypotheses supported or partially supported) in the
CCMM. The final decision was subject to the researcher‟s judgement as there was no
objective cluster analysis procedure to determine the number of clusters (Hair, et al.,
2007). In this thesis, the K-means Cluster Method was conducted using SPSS 17.0.
Five clusters were produced based on the researcher's decision with the
considerations of interpretability and parsimony (Chaturvedi, Carroll, Green, &
Rotondo, 1997; Srivastava, Alpert, & Shocker, 1984). Notably, cluster analysis
always produces clusters and has no statistical basis upon which to draw statistical
inferences from a sample to a population (Hair, et al., 2007). To address this concern,
the two data sets used in Study One and Study Two were tested to validate the
cluster results. The results are presented as follows:
The results of K-means Cluster Analysis using the Study One Dataset
Cluster One showed this type of participant is high in all aspects and is distinct from
all other clusters. In particular, they are high in PI which is different from other
clusters. In total 44 participants belong to this cluster.
Cluster Two showed that this type of participant was not only high in Mavenism and
Communality but also high in UES. In total 110 participants belong to Cluster Two.
It accommodates the highest number of participants.
Cluster Three showed that this type of participant was high in Mavenism and
Communality but low in UES. In total 78 participants belong to this cluster.
Cluster Four showed that this type of participant was above average in all aspects. In
total 60 participants belong to this cluster.
Cluster Five showed that this type of participant had the lowest score in all aspects
compared to other clusters. In total 34 participants belong to this cluster. It
accommodates the lowest number of participants.
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The results of K-means Cluster Analysis using the Study Two Dataset
One outlier was deleted from the data. The results show that there are five clusters.
Cluster One showed this type of participant was high in all aspects and was distinct
from all other clusters. In particular, they have the highest level of Mavenism. In
total 70 participants belong to this cluster.
Cluster Two showed that this type of participant was also high in Mavenism and
high in UES which is different from Cluster Three. All other aspects were above
average and relatively high in two aspects of Relating Needs compared to other
clusters. In total 102 participants belong to this cluster. It accommodates the largest
number of participants.
Cluster Three showed that this type of participant was very high in Mavenism (4.24)
but was very low (2.18) in UES. All other aspects were above average and relatively
high in two aspects of Relating Needs compared to other clusters. In total 52
participants belong to Cluster Three.
Cluster Four showed that this type of participant was above average in general
including UES, but they had low scores in two aspects of relating needs. In total 43
participants belong to this cluster.
Cluster Five showed that this type of participant was very low in UES (1.77), and the
results were mixed in all other aspects. They are quite high in pro-social personal
characteristics (i.e., Personal Initiative and Communality). However, they were also
very low in two aspects in relating needs like Cluster Four, and very low in Use
Innovativeness. In total 26 participants belong to this cluster. It accommodates the
least number of participants.
In general, five clusters in Study Two demonstrated similar patterns to five clusters
obtained in Study One. Firstly, there is one distinct cluster with highest scores in
every aspect. Secondly, there are two clusters high in Mavenism in particular with
one very high in UES and the other very low in UES.
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Further comparison and explanation will be discussed in Chapter 7. The comparison
table of the results using the two data sets are shown in Table 6.7. The consistent
results indicated that there was a distinct cluster that scored high in every aspect.
Table 6.7 Co-Creative Consumer Cluster Results
Each first row shows the cluster results from the Study One Dataset.
Cluster UES CIT RELS RELO UI MAV PIN COMU N
One 3.98 4.38 4.52 4.55 4.48 4.79 4.70 4.52 44
3.94 4.18 4.44 4.35 4.28 4.85 4.41 4.48 70
Two 3.94 3.41 3.91 3.75 3.86 4.49 3.71 3.96 110
3.76 3.57 3.77 3.47 3.61 4.27 3.50 3.88 102
Three 2.26 3.27 3.59 3.47 3.63 4.30 3.64 4.01 78
2.18 3.26 3.67 3.40 3.39 4.24 3.49 3.65 52
Four 3.33 3.33 3.23 3.20 3.29 3.71 3.39 3.43 60
3.20 3.26 2.83 2.97 3.03 3.02 3.00 3.69 43
Five 2.01 2.31 2.70 2.69 2.58 3.58 2.88 3.30 34
1.77 2.64 2.91 2.17 2.61 3.69 3.48 3.79 26
(CIT: Consumer Citizenship; RELS: Relating Needs of Self; RELO: Relating Needs
of Others; UI: Use Innovativeness; MAV: Mavenism; PIN: Personal Initiative;
COMU: Communality)
6.9 Test of Hypotheses for Co-Creative Consumer Motivation Model
According to SEM, the CCMM model was confirmed. According to K-means cluster
analysis, five clusters were identified and confirmed. A clear cluster of Co-creative
Consumer was identified. The tests of the hypotheses are reported as follows.
Hypothesis S1 posits that Newness related positively to Value Oriented User
Experience Sharing. The result showed that hypothesis S1 was supported in Study
Two but not supported in Study One. In Study Two, as hypothesised, NEW was
P a g e | 163
significantly and positively correlated with UES (β = .20, p<0.01). However, NEW
had no significant impact on UES (β = .07, ns) in Study One.
Hypothesis S2 posits that Consumer Citizenship related positively to Value Oriented
User Experience Sharing. The results show that hypothesis S2 was supported in both
Study One (β= .24, p<0.05) and Study Two (β = .18, p<0.05).
Hypothesis S3 posits that Relating Needs related positively to Value Oriented User
Experience Sharing. A low order construct solution was supported in both studies.
The results showed that hypothesis S3 was partially supported in both Study One and
Study Two. In Study One, RELS was significantly and positively correlated with
UES (β = .21, p<0.05) while RELO had no significant impact on UES (β = .15,
ns). In Study Two, RELO was significantly and positively correlated with UES (β
= .19, p<0.05) while RELS had no significant impact on UES (β = .11, ns).
Hypothesis S4 posits that Use Innovativeness related positively to Relating Needs.
The results showed that hypothesis S4 was supported in both Study One and Study
Two. UI was significantly and positively related to both RELS (β = .72, p<0.001)
and RELO (β = .73, p<0.001) in Study One. UI also had significant and positive
impacts on both RELS (β = .67, p<0.001) and RELO (β = .63, p<0.001) in Study
Two.
Hypothesis S4a posits that Use Innovativeness is a characteristic of Co-Creative
Consumers. The results showed that hypothesis S4a was supported. A high level of
Use Innovativeness was found as one of the personal characteristics of Co-Creative
Consumers.
Hypothesis S5 posits that Mavenism related positively to Relating Needs. The results
showed that hypothesis S5 was supported in Study Two and was partially supported
in Study One. In Study Two, the results showed that Mavenism was significantly and
positively related to both RELS (β = .18, p<0.01) and RELO (β = .18, p<0.01). In
Study One, the results showed that Mavenism was significantly and positively
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related to RELS (β = .15, p<0.01) but it had no significant impact on RELO (β
= .09, ns).
Hypothesis S5a posits that Mavenism is a characteristic of Co-Creative Consumers.
The results showed that hypothesis S5a was supported. A high level of Mavenism
was found as one of the personal characteristics of Co-Creative Consumers.
Hypothesis S6 posits that Personal Initiative related positively to Consumer
Citizenship. The results showed that hypothesis S6 was supported in Study Two but
was not supported in Study One. In Study Two, the results showed that PIN was
significantly and positively related to CIT (β = .17, p<0.05). In Study One, the
results showed that PIN had no significant impact on CIT (β = .06, ns).
Hypothesis S6a posits that Personal Initiative is a characteristic of Co-Creative
Consumers. The results showed that hypothesis S6a was supported. A high level of
Personal Initiative was found as one of the personal characteristics of Co-Creative
Consumers.
Hypothesis S7 posits that Communality related positively to Consumer Citizenship.
The results showed that hypothesis S7 was supported in Study Two but was not
supported in Study One. In Study Two, the results showed that COMU was
significantly and positively related to CIT (β = .34, p<0.001). In Study One, the
results showed that COMU had no significant impact on CIT (β = .07, ns).
Hypothesis S7a posits that Communality is a characteristic of Co-Creative
Consumers. The results showed that hypothesis S7a was supported. A high level of
Communality was found as one of the personal characteristics of Co-Creative
Consumers
Two extra paths were identified in Study One and the consistent results were shown
in Study Two. The first new finding suggested that Use Innovativeness was
positively related to Consumer Citizenship in both Study One (β = .58, p<0.001)
and Study Two (β = .35, p<0.001). The Second new finding suggested that Use
P a g e | 165
Innovativeness was positively related to Newness in both Study One (β = .42,
p<0.001) and Study Two (β = .39, p<0.001).
The results of hypotheses testing for CCMM are presented in Table 6.8.
Table 6.8 Test of Hypotheses for CCMM
CCMM Hypothesis Study One
Results
Study Two
Results
HS1 Newness relates positively to Value Oriented User
Experience Sharing.
Not
Supported
Supported
HS2 Consumer Citizenship relates positively to Value
Oriented User Experience Sharing.
Supported Supported
HS3 Relating Needs relates positively to Value Oriented
User Experience Sharing.
Partially
Supported
Partially
supported
HS4 Use Innovativeness relates positively to Relating
Needs.
Supported Supported
HS4a Use Innovativeness is a characteristic of Co-Creative
Consumers.
Supported
HS5 Mavenism relates positively to Relating Needs. Partially
Supported
Supported
HS5a Mavenism is a characteristic of Co-Creative
Consumers.
Supported
HS6 Personal Initiative relates positively to Consumer
Citizenship.
Not
Supported
Supported
HS6a Personal Initiative is a characteristic of Co-Creative
Consumers.
Supported
HS7 Communality relates positively to Consumer
Citizenship.
Not
Supported
Supported
HS7a Communality is a characteristic of Co-Creative
Consumers.
Supported
New
Path
Use Innovativeness relates positively to Consumer
Citizenship.
New
Finding
Confirmed
New
Path
Use Innovativeness relates positively to Newness. New
Finding
Confirmed
6.10 Conclusion
This chapter illustrates the results of the data analyses conducted using SEM and K-
means Cluster Analyses. The results confirmed two theoretical models, UESBM and
CCMM. Two new relationships between Use Innovativeness and Newness and
between Use Innovativeness and Citizenship were confirmed in CCMM. The
clustering results showed five consistent clusters and a distinct group of participants
P a g e | 166
who scored high in every aspect. In Chapter 7, the discussions on these findings and
a conclusion of the research will be presented.
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CHAPTER SEVEN DISCUSSION AND CONCLUSION
7.0 Introduction
The previous chapter presented the analysis and results for Study Two. This chapter
discusses the research findings, theoretical contributions and managerial implications,
limitations and future research directions of the current project. The chapter is
organised as follows. A recap of this thesis is provided in Section 7.1. A discussion
of SEM results for the UESBM and the CCMM is described in Section 7.2 and 7.3,
and a discussion of cluster analysis results is provided in Section 7.4. A reflection of
conceptual findings is outlined in Section 7.5. The contributions to theory and
managerial implications are in Section 7.6 and 7.7. Discussions on limitations and
delimitations are described in Section 7.8. The research directions and
recommendations for future study are covered in Section 7.9. Finally, a conclusion is
presented in Section 7.10.
7.1 Overview of Findings
In this thesis, a „zoom-out‟ (Vargo & Lusch, 2011) approach was adopted to explore
how Service-Dominant Logic (SD logic) can be adopted to inform the overall
research question: “How and why do consumers voluntarily participate in a value co-
creation process?” In Chapter Two, a review of SD logic based on its 2008
foundational premises was conducted. From the literature review, two themes,
service centricity and value co-creation emerged, and in total five gaps were
identified. This thesis highlighted the needs that SD logic can be extended to: (1)
non-reciprocal marketing phenomena; (2) customer initiated value-creation
processes; (3) betterment centricity as the essence of service (and asymmetric
outcomes between actors within and amongst service systems); (4) effort-based
meaning of value creation; and (5) customers as service providers. The proposed
ECo framework accommodates an extended lexicon complementary to SD logic as
follows: (1) value initiation and value initiator; (2) value-in-experience; (3)
betterment centricity and betterment outcomes; and (4) three experience co-creation
contexts. The Experience Co-Creation (ECo) Framework was designed to
accommodate broader marketing phenomena (i.e., non-reciprocal open innovation
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and user-generated content (UGC)). After zooming out and establishing the ECo
framework, this study took a zoom-in approach and placed attention back on a value
co-creation process that is outcome-process driven, rather than process-outcome
driven.
Owing to the scope of the current research, this thesis focuses specifically on non-
reciprocal value co-creation phenomena initiated by consumers. Two emergent
concepts: User Experience Sharing and Co-Creative Consumers have been proposed
grounded in the ECo framework. User Experience Sharing refers to consumers‟
initiative efforts made to co-create value with either other consumers or with firms.
The term, Co-Creative Consumer, refers to value initiators who perform User
Experience Sharing. Together, these two theorised concepts shed light on the
following two propositions: (1) User Experience Sharing derives value-in-experience
as consumers make initiative efforts to participate in value co-creation, and (2) Co-
Creative Consumers are value initiators who perform UES. Three research questions
were identified underpinning the scope of this research:
RQ1: What factors influence consumers to exhibit User Experience Sharing
behaviour?
RQ2: Why do Co-Creative Consumers participate in User Experience Sharing as part
of value co-creation behaviour?
RQ3: What are the characteristics of Co-Creative Consumers?
To answer these research questions, two theoretical models, the User Experience
Sharing Behaviour Model (UESBM) grounded in the Theory of Planned Behaviour
framework, and the Co-Creative Consumer Motivation Model (CCMM) grounded in
the Motivation, Opportunity, Ability framework were theorised. The models use SD
logic consistent constructs and draw upon multiple streams of literature including
consumer education, consumer psychology and consumer behaviour, and
organisational psychology and organisational behaviour. These constructs include
User Experience Sharing with Other Consumers (UESC), User Experience Sharing
with Firms (UESF), Enjoyment in Helping Others (EIHO), Consumer Empowerment
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(EMP), Consumer Competence (COMP), and Intention to Engage in User
Experience Sharing (INT), Attitudes toward User Experience Sharing (ATT) and
Subjective Norm (SN) in the UESBM, and User Experience Sharing (UES),
Consumer Citizenship (CIT), Relating Needs of Self (RELS) and Relating Needs of
Others (RELO), Newness (NEW), Mavenism (MAV), Use Innovativeness (UI),
Personal Initiative (PIN) and Communality (COMU) in the CCMM. Many of these
constructs are relatively new to marketing and require further empirical evidence for
support. In general, the findings shed light on “How and why consumers voluntarily
participate in the value co-creation process?”, and characteristics of Co-Creative
Consumers who actively engage in UES.
Two studies were conducted to underpin corresponding research questions. Study
One was conducted to calibrate and re-specify the proposed models. Study Two was
a replica study to confirm the proposed models. In Study One, data were collected
from a PC DIY online community. In Study Two, a majority of data were collected
from an Apple product online community. Considering the nature of the forums, the
Study One data may reflect some characteristics of Prosumers and the Study Two
data may reflect some characteristics of Innovators. The results drawn from two
independent samples (N = 326 and N = 294) provide empirical support for the
overall structure theorised in the research models shown in Chapter Three.
The results in both models showed that Enjoyment in Helping Others and Consumer
Competence in the UESBM, and Consumer Citizenship and Relating Needs in
CCMM have significant impacts on UES. The consistent results appeared in both
Study One and Study Two. These findings give encouraging empirical evidence to
support SD logic (Vargo & Lusch, 2008).
The findings related to each of the constructs with respect to their hypotheses are
explained in detail below.
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7.2 User Experience Sharing Behaviour Model
UESBM was developed to answer the first and second research questions:
RQ1: What factors influence consumers to exhibit User Experience Sharing
behaviour?
RQ2: Why do Co-Creative Consumers participate in User Experience Sharing as part
of value co-creation behaviour?
7.2.1 Enjoyment in Helping Others (EIHO)
EIHO is a type of autonomous motivation grounded in Self-Determined Theory. The
results showed that EIHO had a significant positive effect on INT. More importantly,
EIHO had a positive and significant impact on UESC. It also had a strong impact on
UESF in Study One but no significant impact on UESF in Study Two. In general, the
results support the hypothesis U6a and partially support the hypothesis U6b. While
its significant impact on UESC is similar to findings in the Knowledge Sharing
literature (Lee, et al., 2006; Yu, et al., 2010), the results here show that consumers
are more likely to share their user experiences with other consumers than with firms.
Notably, while EIHO in particular measured the likelihood of enjoyment in helping
friends and online acquaintances rather than helping firms, it appears to have a
strong impact on UESF in Study One. Nevertheless, EIHO has no significant impact
on UESF in Study Two. One of the explanations is to consider the characteristics of
participants in the two studies (see Section 4.7.3). Because participants were
predominantly iPhone users, this may be explained by participants‟ gratitude toward
Apple which is renowned for gaining high loyalty and satisfaction from its
customers. In this case, similar to having long-term relationships with friends and
online acquaintances, more competent consumers who have a long-term relationship
with the firm and are likely to become working consumers (Cova & Dalli, 2009)
who play a similar role to an employee. As a result, the prosumer-like participants in
Study One who may be more confident and highly competent are more likely to co-
produce with firms.
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Finally, this finding suggests that consumers voluntarily share their experiences with
other consumers. It supports that theory that User Experience Sharing behaviour is to
be considered as a consumer initiated value co-creation behaviour and that
consumers can be service providers. This construct also addresses Gap 1 as
identified in the literature review. Its significant impact on UESC suggests that UES
is likely to be a consumer-to-consumer non-reciprocal value co-creation
phenomenon.
7.2.2 Consumer Empowerment (EMP)
EMP is the other autonomous motivation in the UESBM. This thesis hypothesised
positive relationships between EMP and INT, and EMP and the actual UES
behaviour. The results do not support the proposed hypotheses, U7a and U7b. There
is no significant relationship found between EMP and Intention. Similar findings
were found between EMP and UESC. Additionally, EMP had a weak negative
impact on UESF in Study One but there is no significant impact on UESF in Study
Two.
A likely explanation is that notably, after re-specification, the semantic meaning of
EMP reflects empowerment derived from co-creation or working together rather than
working alone. While Technological Sophistication, and Network Competency can
enhance information transparency, and therefore empower individuals in the
marketplace (Macdonald & Uncles, 2007), the impact of co-creative empowerment
may come from consumers‟ beliefs in their ability to harness their interpersonal and
online networks and become empowered through cooperation with other consumers
in the virtual community (Macdonald & Uncles, 2007, 2009). Hence the
responsiveness to co-creative empowerment which comes from working together
(i.e., sharing their user experiences) may be contingent to their beliefs on being
competent to co-create with firms and co-create with other consumers. In other
words, the sense of co-creative empowerment alone does not lead to responsiveness
to the empowerment unless consumers are confident they are capable of co-creating
value (i.e., User Experience Sharing). Therefore, the insignificant result may indicate
that Consumer Competence takes power over Consumer Empowerment in the model.
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On the other hand, the negative impact on UESF in Study One suggests that
competent consumers who are responsive to co-creative empowerment are likely to
co-create value with other consumers instead of with firms. In this case, consumers
who sense empowerment from learning from others may want to keep the
experiences to themselves and not share them with a firm, similar to when a firm
wants to keep know-how to itself for its own competitive advantage. Here,
consumers may be motivated to share user experiences in a reciprocal instead of
non-reciprocal relationship. In future research it would be interesting to see if there is
any evidence showing that firms that share with their consumers are more likely to
have their consumers share with them in return.
Finally, the finding from a recent online co-creation new product development study
(FüLler, et al., 2009), the empowerment factor, Experienced Empowerment, has a
positive and significant impact on Intention of future participation (in online co-
creation projects). However, two measurement items are semantically different from
EMP (i.e., Experienced Empowerment: “I had the feeling of active participation at
new product development”, and “This project gave me the feeling that I am taken
seriously”. From their finding it can be inferred that a sense of empowerment may
occur after participants actually engage in UES. Thus it is suggested here that a
longitudinal study may help to further explore the impact of EMP on both INT and
UES.
7.2.3 Consumer Competence (COMP)
The results supported the hypothesis U3 in both studies. Hypothesis U4 is supported
in Study Two and partially supported in Study One. In general, Consumer
Competence (COMP) had strong positive effects on INT, and UESC and UESF. The
results support Macdonald and Uncles‟ (2009) findings that consumer savvy is
related to desire for co-creation, which refers to UES in this thesis.
Notably, in Study Two, COMP had a much stronger impact on INT and UESF
compared to the same paths in Study One. The result in Study Two was almost
double that of Study One from COMP to INT. Additionally, COMP had no
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significant impact on UESF in Study One and a significant positive impact on UESF
in Study Two.
One explanation may be that there are more prosumer-like participants in Study One.
The high loading on Technological sophistication implies that they are highly
capable of improvising solutions without the help of firms, and therefore they are
less likely to share with firms as a result of their competence. In turn, the Study One
results show COMP has a positive significant impact on UESC but not on UESF.
This result implies that these highly competent participants are inclined to share their
user experiences with other consumers and are much less likely to share with firms.
This is consistent with the discussion in Section 7.2.2. The fact that participants in
Study Two are more actively looking for information online (the higher loading on
Online Network) may explain why they are more likely to share their user
experiences with both other consumers and firms. They may be more likely to obtain
their knowledge and build relationships with both other consumers and firms to
enhance their own competence.
7.2.4 Theory of Planned Behaviour Factors
The results indicate that ATT and NOR had either no or only a weak impact on INT.
INT had either no or only a weak impact on UESC and on UESF. Hypothesis U1
was supported in Study One but not in Study Two. U2 was not supported in either
study. Hypothesis U5 was partially supported in Study One but not supported in
Study Two. A likely explanation is that EIHO and COMP are better predictors of
INT and UES behaviour. These findings support SD logic suggesting autonomous
and competent consumers are likely to co-create value.
From the discussions above, overall findings show that UES is a type of C2C
interaction aligning with SD logic and therefore can potentially lead to consumer
initiated value co creation.
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7.3 Co-Creative Consumer Motivation Model
CCMM was developed to answer the second and third research questions:
RQ2: Why do Co-Creative Consumers participate in User Experience Sharing as part
of value co-creation behaviour?
RQ3: What are the characteristics of Co-Creative Consumers?
7.3.1 Co-Creation Opportunity – Newness (NEW)
The result supported the hypothesis S1 in Study Two but not in Study One. Newness
(NEW) refers to co-creation opportunity. In Study One, NEW had no significant
impact on UES as measured by three types of value related shared experiences. In
Study Two, NEW had a moderate positive impact on UES. A possible explanation
for the lack of significance of NEW in Study One may be the more significant
collective impacts from Consumer Citizenship, Relating Needs of Others and
Relating Needs of Self. In other words, Study One participants are more likely to
share their user experiences based on the relevance of their experiences to others
rather than to share experiences simply because they are unique or novel. Moreover,
a lack of confidence regarding their new experiences may be the reason for the
mixed results between two studies. A future study may incorporate „consumer self-
confidence‟ which is regarded as a driver for consumers to seek assistance when
faced with complex or uncertain decisions (Bearden, Hardesty, & Rose, 2001).
7.3.2 Co-Creation Motivation – Consumer Citizenship (CIT)
The results supported the hypothesis S2. Consumer Citizenship refers to consumers‟
motives to provide solutions based on their experiences through contributing and
collaborating with others in communities as resource sharing. The result shows that
Consumer Citizenship has a moderate positive impact on UES in both studies. The
concept of Consumer Citizenship is still in its infancy, nevertheless with growing
consumer engagement in online communities, Consumer Citizenship is becoming
more and more prominent between consumers who are online citizens. Thus,
consumers may feel more responsible to make efforts in co-creating value for
themselves and for others. It is expected that in certain contexts, consumer
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citizenship will have a more significant impact on UES (e.g., environmental
sustainability or global warming interest groups in „political marketing‟ (Lock &
Harris, 1996)).
Consumer Citizenship is a key concept that resonates within the ECo framework
(betterment centricity) that consumers are willing to take responsibility to provide
solutions to self and for others through value co-creation. The results support SD
logic that consumers are no longer a passive entity and it further supports the concept
that service provision is more than a reciprocal action mainly masked by money.
Also it can be extended to argue that the reaction to consumers‟ dissatisfaction goes
further than boycotting or voicing their concerns. Consumers will work together to
take the role of service providers and deliver value-in-experience for themselves and
others. Importantly, Consumer Citizenship corresponds with an Actor-to-Actor
worldview under SD logic that every actor in this thesis can be called a value
initiator to produce value-in-experience for themselves and others.
It would be interesting to see if consumers motivated by their consumer citizenship
are more likely to have a sense of responsibility associated with value initiation and
therefore are more willing to share their user experience in terms of provision of
solution (in this case, they would be more solution oriented, instead of having a more
negative active reaction, such as boycott and negative WOM).
7.3.3 Co-Creation Ability – Relating Needs (REL)
The hypothesis theorising Relating Needs (REL) as a higher-order construct with
two higher-order factors, RELS and RELO, was not supported. The results using a
higher-order construct, REL, generated a Heywood Case (Hair, et al., 2006) in Study
Two but not in Study One. And a low order construct solution is supported in both
studies. The results are suggestive of two lower-order constructs, Relating Needs of
Self (RELS) and Relating Needs of Others (RELO). Since REL is an emergent
concept, a likely explanation is that the higher-order construct, REL, may be
empirically under-justified. A future study may be conducted to further explore
possible higher-order factors to stabilise Relating Needs as a higher-order construct.
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The higher-order solution is depicted in Figure 5.6. Nevertheless, a lower-order
solution does provide more information as explained below.
As a result of the discussion above, a lower-order solution was accepted. Notably,
RELS had a moderate impact on UES while RELO had no significant impact on
UES in Study One. In contrast, RELS had no significant impact on UES and RELO
had a moderate impact on UES in Study Two. A possible explanation is that the
shared experiences of Study One participants are more relevant to others with or
without intentionally taking others‟ needs into account. Participants in Study One
may be more likely to be use innovative and be very specific with their own needs
(i.e., high in UI and RELS). These are similar to the characteristics of lead users
(Von Hippel, 1986), whose needs are leading-edge and representative of other
consumers‟ future needs. Participants in Study Two on the other hand will be more
likely to share their user experiences when there is an opportunity, and if they can
relate their user experiences to others. Consistent with the previous discussions, the
characteristics of two datasets are reflected in the diverged results regarding impacts
of RELO and RELS on UES.
The findings partially support that RELS and RELO were both positively and
significantly related to UES. These findings provide empirical evidence for SD
logic‟s claim that competence as an operant resource is essential to value co-creation.
More importantly, the results imply that consumers can be service providers for
themselves or others.
7.3.4 Use Innovativeness (UI)
The results suggested the hypothesis S4 was supported. However, unexpectedly the
results indicate that Use Innovativeness has a strong positive impact on all co-
creation factors (i.e., RELS and RELO, CIT, and NEW). As a result, there are two
new significant relationships identified: Use Innovativeness to Consumer Citizenship
and Use Innovativeness to Newness.
In particular, UI has a consistent significant positive impact on both RELS and
RELO. A likely explanation may be drawn from the lead user literature.
“Lead user” was first introduced by Von Hippel (1986). It refers to those users who
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present strong needs that are ahead of the market but are likely to be generalised in
the marketplace in the future. The concept, lead user, was proposed to solve the issue
that marketers are struggling with finding potential users who can solve problems
and anticipate their needs without the stimulation of real-world use experiences of a
product or a service (Von Hippel, 1986). Firms recruit lead users to gain insights into
developing value propositions and this may be an indirect way of value co-creation
(Lusch, et al., 2007).
Research shows that lead users are highly innovative and most likely to know how to
fulfil their needs (Diehl & Schrader, 2009; e.g., Hienerth, Pötz, & von Hippel, 2007;
Schreier & Prugl, 2008). Schreier and Prugl (2008) tested consumers‟ “lead userness”
and found that they are likely to be more knowledgeable and more experienced in a
domain-specific context, and they are likely to be innovative. Diehl and Schrader
(2009) suggest that lead users are more likely to actively initiate inventions or fulfil
their own needs based on their prior experience, knowledge and motivation. Diehl
and Schrader (2009) extended the original conceptualization of lead users and
claimed that they will also score highly on other perspectives, including new needs,
opinion leadership, dissatisfaction with existing products, use experience, know-how
concerning materials and technologies, and involvement. Thus lead users are likely
to be highly innovative and able to integrate available resources to fulfil their own
needs. This may explain why UI has such a high impact on RELS.
UI was also found to have an equally high impact on Relating Needs of Others. This
finding may highlight the difference between Co-Creative Consumers and Lead
Users. Most importantly, “lead users” are conceptualised as those who initiate new
needs and are optimistic about benefits that can be provided through an invention
beyond what current offerings can afford (Von Hippel, 1986). Co-Creative
Consumers on the other hand focus on taking initiatives to co-create value (i.e., UES)
through understanding their own needs and taking others‟ needs into account for the
benefit of self and others.
Notably, there were two new relationships identified. The results suggest that UI has
positive and significant impacts on the other two co-creation factors (i.e., CIT and
NEW) in both studies. A likely explanation for the relationship between UI and CIT
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is that CIT reflects a sense of responsibility to provide solutions for the benefit of
others. Therefore, consumers with high use-innovativeness are more likely to
improvise solutions (i.e., value) either for themselves or others. On the other hand,
NEW refers to co-creation opportunity that reflects consumers‟ likelihood to share
when they encounter user experiences. The final results suggested these
opportunities reflected unique, different or personalised experiences. A possible
explanation is that consumers with high use-innovativeness have more opportunities
to gain these experiences.
7.3.5 Mavenism (MAV)
The hypothesis, S5, is partially supported in Study One and supported in Study Two.
The results in both studies show that MAV has a weak positive impact on RELS. It
has a weak positive impact on RELO in Study Two but has no significant impact on
RELO in Study One. The reason MAV has a weak impact on RELS and RELO may
be because it refers to “a propensity of initiating discussion with consumers and
responding to requests from consumers for market information” (Feick & Price,
1987, p. 85) rather than specifically exploring and discovering needs of self and
others.
7.3.6 Personal Initiative and Communality (PIN and COMU)
The result supports the hypothesis, S6 in Study Two but not in Study One. PIN and
COMU are associated with pro-social behaviour (Frese, et al., 1996; Goodwin, 1996).
PIN has a weak positive impact on CIT and COMU has a moderate impact on CIT in
Study Two. However, neither PIN nor COMU have a significant impact on CIT in
Study One. A likely explanation may be that Study Two participants‟ propensity to
be pro-social is more likely to have a higher impact on CIT.
The reason that communality had a moderate impact on CIT in Study Two but no
significant impact on CIT in Study One may be that Study Two participants, who are
more likely to take others‟ needs into account, will be more likely to develop CIT
that focuses more on others‟ needs rather than reciprocal benefits (Goodwin, 1996).
On the other hand, Study One prosumer-like participants in a PC DIY community,
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may already have high communality and therefore the propensity of communality
has less of an impact on CIT.
From the discussions above, the results suggest that CCMM is a pioneering
consumer initiated value co-creation model that generates supporting empirical
evidence and extends the understanding of SD logic. The significant relationships
between UI and MOA factors as well as the significant impacts of MOA factors on
UES clearly indicate CCMM capture factors that influence the direct value co-
creation phenomena.
7.4 Co-Creative Consumer Clusters
A K-means cluster analysis technique was adopted to generate clusters in order to
answer the third research question: What are the characteristics of a Co-Creative
Consumer?
As discussed in 7.3.4, the Co-Creative Consumer is different from a Lead User
because Co-Creative Consumers are capable of relating needs of others alongside
needs of self, and of being highly use-innovative. By the definition and the
hypotheses, Co-Creative Consumers will be the cluster that scores the highest in
Value Oriented User Experience Sharing and should score highly in all consumer
characteristics.
A consistent clustering pattern was found when the clustering results from Study
One and Study Two datasets were compared. According to the pattern, the five
clusters are identified as: (1) UXer, (2) Maven Type A, (3) Maven Type B, (4)
Tentatives, and (5) Newbies. When compared to the other four types, the results
show clearly that the UXer who shares three types of experiences most frequently
scores the highest in all consumer characteristics. As a result, this cluster indicates
the existence of the most active Co-Creative Consumers and reflects the
characteristics of Co-Creative Consumers. A discussion of each of five clusters and
the patterns follows.
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Cluster Analysis Result Interpretations
Type One: UXer
The first classification type is the UXer. UXers can be seen as highly co-creative.
These participants have the highest scores in every category including the highest
level of use-innovative tendency, a characteristic that is also seen in Lead Users
(Schreier & Prugl, 2008) and the highest level of Mavenism, which can also be seen
in Type Two and Type Three. Notably, the UXer shows the highest level of
consumer citizenship and are most competent in terms of relating needs of self and
of others among the five clusters. UXers most actively share their valuable
experiences with others. The findings align with the theoretical argument that the
UXer is an emergent consumer profile that is distinct from Lead Users, a co-
producer of innovations (Von Hippel, 1986) and the Market Maven, a diffuser in the
marketplace (Feick & Price, 1987). Importantly, the UXer is likely to be a value
initiator in a value/ experience co-creation process. For example, these participants
may be those who post the first solutions or who are the first to answer others‟
requests in an online forum.
Type Two: Maven Type A (Maven who actively engage UES)
The second classification type is Maven Type A. The results show that although the
participants in this cluster score highly in UES, the scores of all aspects are below
four, except in Mavenism. Maven Type A has lower scores in all aspects when
compared to the UXer, including Relating Needs of Self, Relating Needs of Others
and User Innovativeness.
A likely explanation is that Maven Type A has broader marketplace knowledge and
is enthusiastic in sharing the experiences which are valuable to them. Although the
experiences they share are not wholly based on the marketing messages pushed by
firms, these experiences mostly draw upon value propositions proposed by firms that
are not as well known by other consumers (e.g., less popular but quality APPs), or
experiences learned from other consumers. It is possible that the experiences they
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share may be less solution oriented, less relevant and less innovative when compared
to UXers. For example, Maven Type As may be more likely to write reviews of
service offerings to show how marketing claims differ based on their experiences,
but less likely to address how these offerings can be used in alternative contexts.
Thus they are likely to be those who reply to an original post.
Thus, Maven Type A can be people who convey marketing messages, performing
eWOM. They also rate highly in Communality, which indicates that their sharing
behaviour is driven by helping others. They will be those people that companies
currently indentify as playing the customer service role or function for the service
provider without pay, as they also rate quite highly in relating needs. Maven Type A
also passes on screened marketing messages or information available in the market
(those they think are valuable to them and people they relate to).
Type Three: Maven Type B (Maven who doesn‟t engage in UES)
The third type represents Maven Type B. Notably, this type of consumer is similar to
Maven Type A in sharing a high score in Mavenism. However, they do not actively
participate in UES. The results show the participants in this cluster obtain low UES
scores, well below the average. A likely explanation is that Maven Type B has
broader marketplace knowledge but may not be users and therefore have few
experiences to share.
Type Four: Tentatives (Non Maven who share moderate UES)
The fourth type is Tentatives. Participants who are Tentatives obtain average scores
in all respects. An explanation may be that Tentatives do not have broad marketplace
knowledge, but they are willing and attempt to share their user experiences.
Tentatives represent those who may give ratings but are not likely to write reviews to
elaborate the reasons for their rating. If these participants do post, their posts in the
forum may contain a mix of marketing messages intended by firms and personal
experiences. It is also possible that Tentatives may simply elaborate their emotional
opinions or express their agreement or disagreement with other threads or posts in
online forms.
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Type Five: Newbies (Rarely Share and low in every aspect except Mavenism)
The fifth type is Newbies. Participants who are Newbies score low on every aspect,
except for moderate inclines in Mavenism, that may be explained by the nature of
the online forum as the sampling frame. As the results showed, participants in this
cluster did not actively share their user experiences, participants may have been
motivated to complete the survey because of the incentive scheme. Also, Newbies
may be those who often observe and learn from others rather than share their own
experiences.
Additionally, the lower number of participants in this cluster indicates that the
reward was not the reason people voluntarily participated in sharing their user
experiences. This is consistent with the literature in SDT and knowledge sharing.
Autonomous motivation is more likely to have a strong impact on pro-social
behaviour and to be associated with positive outcomes (Gagné & Deci, 2005).
7.5 Reflection on Conceptual Findings
7.5.1 ECo Framework
The results for User Experience Sharing and Co-Creative Consumers underpin the
use of the ECo framework in the consumer-to-consumer context. Consumers can be
value initiators who make an effort to co-create value with each other. Experiences
shared are based on the efforts made during everyday routines (e.g., newness, and
different types of values shared). The results also suggest however, that UES is
driven by non-reciprocal motivation factors such as enjoyment in helping others and
consumer citizenship.
7.5.2 Betterment Centricity
A full discussion regarding the implications of betterment outcomes is beyond the
scope of this study, but the initial results imply that consumers are more likely to
create solutions for themselves and others through UES to obtain their desired
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betterment outcome. The effects of asymmetric outcomes and symmetric outcomes
between cooperating parties are not discussed.
In future work, it would be interesting to use asymmetric or symmetric outcomes as
control variables to better understand whether non-reciprocal value co-creation
phenomena work the same or differently under these controlled conditions. People
who have mutual interests may work together but they may also have conflicts of
interest. For example, Google provided Android operating system (OS) for mobile
manufactures which reduced their OS development costs, but these mobile
manufacturers customised the Android OS, often not sharing customisation codes,
and turning these customisations into their own competitive advantage. This limited
the openness of communication between customers who used the same Android OS
but different mobile handsets. On the other hand, actors who have asymmetric
desired outcomes may share common goals that encourage them to cooperate and
make co-created outcomes, and achieve their own desired outcomes (e.g., in regard
to developers of Apps and Apple, Apple designs the tool for developers to create
Apps, and developers and Apple can both benefit from the cooperation).
7.6 Contribution to Theory
This research offers both theoretical insights and empirical evidence to better
understand relational value co-creation. It is a pioneering study providing empirical
evidence dedicated to developing SD logic based theories. By using SD logic as a
lens and focusing on consumer initiated, non-reciprocal marketing phenomena, this
study makes several theoretical contributions.
Firstly, this thesis contributes to current theory by adapting a recently developed
consumer savvy scale to measure Consumer Competence, which is incorporated into
the TPB based model. Perceived Behaviour Control was represented by Consumer
Competence to reflect an SD logic mindset. The findings are consistent with the
suggestion made by Macdonald and Uncles (2009), that Consumer Competence as
measured by the adapted Consumer Savvy Scale is an SD logic consistent construct.
The results support the claim that consumers are more active and empowered
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because their competences in terms of expertise and network connectivity enable
them to co-create value for themselves and others through User Experience Sharing.
Secondly, this thesis makes a contribution towards incorporating the concept of
consumer citizenship as an SD logic consistent construct that represents active
consumers‟ motivations leading to performing Value Oriented UES. The results
show that consumer citizenship has a positive and significant impact on Value
Oriented UES. As consumer citizenship reflects a consumers‟ active role in terms of
taking responsibility to co-create value, this sense of responsibility in providing a
solution and deriving value as experience (value-in-experience), is an important
concept that supports the theorisation of value-in-experience as an effort based
meaning of value under the ECo framework.
Thirdly, this thesis makes another contribution by theorising Relating Needs, which
is proposed as a core competence of Value Oriented UES. Relating Needs gives the
theoretical contribution to further inform academia on the competences of direct
value co-creation. Due to an empirical data error, the hypothesis of relating needs as
a higher order construct needs further examination and in this study, two lower order
constructs are presented in the final model.
Fourthly, this thesis also makes a contribution to inform the debate on the consumer
role in value co creation as value creator or co-creator and the results support the
proposition of value initiation and value initiator.
The results suggest that use innovativeness is mediated by MOA factors. While a
process of indirect value co creation is likely to pay more attention on the
engagement of consumers with a high level of use innovativeness (i.e., lead users),
the finding of Co-Creative Consumers supports the view that consumers who possess
a high level of consumer citizenship and have an ability to relate the needs of self
and others are more likely to perform direct value co-creation. In turn, Co-Creative
Consumers are more likely to feel the responsibility of value initiation and become
value initiators. The results support the concepts of value initiation, and value
initiator, which can be used to clarify the concepts of value co-creator, and value co-
creation.
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The fifth major contribution of this research to theory is the conceptualisation of the
Experience Co-Creation (ECo) Framework. The framework is embedded with an
„SD logic friendly lexicon‟ (Lusch & Vargo, 2006), reflecting five gaps identified
based on the review of the ten foundational premises of SD logic (Vargo & Lusch,
2008). The conceptualisation of the ECo framework presents a new opportunity for
extensions for SD logic to further accommodate consumer initiated, non-reciprocal,
value co-creation marketing phenomena. This research also provides preliminary
empirical support for the ECo framework in a consumer research context. The ECo
framework informs the most recent Actor-to-Actor orientation and network-world-
view emerging from consolidated works of SD logic (Alter, 2010; Gummesson, et al.,
2010; Lusch, Vargo, & Tanniru, 2010; Vargo & Lusch, 2011). Most importantly, it
offers an initiation-driven, effort-based and betterment-centric mindset
complementing to the continuous evolution of SD logic.
The sixth contribution of this research is the conceptualisation of User Experience
Sharing that represents emergent consumer initiated value co-creation behaviour
under the ECo framework. SD logic creates a new avenue for re-examining current
marketing theory and developing new marketing theory (Gummesson, et al., 2010)
including consumer behaviour research. The conceptualisation of User Experience
Sharing provides theoretical grounds and empirical evidence underpinning consumer
value co-creation behaviour informed by consumer-to-consumer interaction (Libai et
al., 2010; Nicholls, 2010; Nuttavuthisit, 2010), but distinct from word-of-mouth and
knowledge-sharing. Previous attempts to investigate consumer-to-customer value co-
creation have been found in the literature, for example, intentional social action
(Bagozzi, 2000; Bagozzi & Dholakia, 2002), customer-to-customer knowledge
exchange (Gruen, et al., 2006; Gruen, Osmonbekov, & Czaplewski, 2005; Gruen, et
al., 2007) and consumer engagement behaviour (Van Doorn et al., 2010). Distinctly,
the conceptualisation of User Experience Sharing entails consumer value initiation in
three experience co-creation contexts, including: value proposition co-production,
offering co-consumption, and value collaboration.
The seventh contribution of the research is the conceptualisation of the Co-Creative
Consumer that represents an emerging value-co-creation oriented consumer profile.
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The conceptualisation of the Co-Creative Consumer provides theoretical grounds
and empirical evidence underpinning SD logic consistent characteristics of
consumers. The results indicated that Co-Creative Consumers inherit characteristics
of Market Mavens, Prosumers and Lead Users.
The eighth contribution of the research is the presentation of two theoretical models
to answer, “how and why consumers voluntarily participate in a value co-creation
process?” The Use Experience Sharing Behaviour Model and the Co-Creative
Consumers Model are grounded in the Theory of Planned Behaviour (TPB) and the
Motivation, Opportunity, Ability (MOA) frameworks respectively. The empirical
evidence not only supports User Experience Sharing and Co-Creative Consumers,
but also confirms that TPB and MOA frameworks are compatible theories with SD
logic.
The ninth contribution of the research is that this research is the first single study to
incorporate and empirically examine SD logic consistent constructs into TPB and
MOA frameworks (i.e., Consumer Empowerment, Consumer Competence, Relating
Needs and Consumer Citizenship). The results add new knowledge and predicate
research directions for future studies.
The tenth contribution of the research is that it is one of the few pieces of research
dedicated to providing both further extensions and empirical support for SD logic. It
also incorporates Convergent Mobile Online Services (CMOS) as the research
context to reflect the complexity of service systems accommodating both reciprocal
and non-reciprocal value co-creation marketing phenomena.
7.7 Implications for Marketing Practice
This research has practical implications for marketing managers who intend to
develop and implement a customer engagement management strategy to establish a
co-creative relationship with their customers through consumer initiated online
communities.
In terms of customer engagement management, the findings in this thesis suggest
that managers need to become facilitators and embrace consumer initiated online
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communities as a type of customer engagement platform. The results show that
managers need to share resources in a non reciprocal manner to encourage customer
engagement (i.e., User Experience Sharing with Firms). Managers need to avoid
seeing and exploiting consumers as resources.
To enable firm-customer value co-creation, the results in this thesis indicate that
firms who want to co-create value with consumers should place their focus on
facilitating consumers‟ fulfilment of needs rather than exploitation of harnessing
consumers‟ use innovativeness. Managers should facilitate Co-Creative Consumers‟
engagement through creating channels and opportunities for nurturing and
communicating value initiation opportunities. For example, they could provide
resources to support independent forums and provide information relating to
outcomes of aggregated data sourced from insights gathered from Co-Creative
Consumers. In many cases, consumers share their experiences with service providers
in a non-reciprocal nature (i.e., with no immediate rewards). Nevertheless, these
consumers do so with the intention that while service providers can carry these
experiences to future projects for their own competitive advantages, it will
eventually benefit customers‟ betterment of life. This thesis also suggests that service
providers should share the cumulative insights learnt from engaged consumers as a
way of nurturing a long-term value co-creation relationship.
The results in the User Experience Sharing Behaviour Model suggest that firms who
want to increase customer engagement need to be aware of the different
characteristics of consumers as well as their competences. Firms should nurture
relationships with competent consumers, as their motivation to share user
experiences with firms comes from their enjoyment in helping others who they
consider to be friends or with whom they have an on-going relationship. To nurture
an on-going relationship, firms should share the aggregated experiences of engaged
consumers who actively contribute in an online community. For less competent
consumers, firms should facilitate them to improve their competences in terms of
expertise and social networks by encouraging and sponsoring a user initiated forum
space where less competent consumers can learn and make connections with other
competent consumers.
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The results in the Co-Creative Consumer Motivation Model show that managers who
want to co-create value with consumers need to look beyond use innovativeness and
pay attention to two types of competences, Relating Needs of Self and Relating
Needs of Others, which are specifically associated with value co-creation. These
competencies qualify consumers to play a role of „working consumers‟ in the area of
Research and Development (R&D) and customer service. By identifying and
utilising these competences, firms will be able to incorporate these competences as
resources to form new competitive advantages.
Notably, the impact of these competences may vary depending on the general
competences associated with user experience sharing, including expertise and social
networks. For competent consumers, firms should facilitate and encourage these
consumers to share their experiences associated with personalised and new solutions,
for example innovative uses and convergent uses that accommodate personal needs.
For less competent consumers, firms should facilitate and encourage these
consumers to share experiences associated with their insights on scenario based
experiences, for example, how these services are used in different circumstances and
contexts.
The findings in Section 6.8 provide an analytical tool to identify Co-Creative
Consumers. Co-Creative Consumers are those who actively engage in consumer
initiated value co-creation. The findings show that Co-Creative Consumers are
motivated by their sense of responsibility and ownership of their solution provisions
drawn from their life experiences. Managers can also use the identified typologies to
develop their customer engagement strategies focusing on collaboration with Co-
Creative Consumers to 1) fulfil their desired value which can be used to better value
propositions; and, 2) help other consumers to increase received value of a service
offering.
The results in User Experience Sharing Behaviour Model show that co-creative
empowerment has a negative impact on co-creation with firms. The findings show
that consumers who are competent in value creation themselves intend to share such
experiences with other consumers. Nevertheless, managers can overcome this if they
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foster an on-going relationship similar to a weak-tie relationship in an online
community.
7.8 Limitations and Delimitations
The limitations and delimitations are discussed as follows.
Firstly, the sampling frame in this research are CMOS users who participate in
online communities. As the data was collected from online forums, these results are
subject to the limitation that all users who are members of the online community are
potentially more likely to share, compared to those who do not use online
communities. Additionally, the results are more likely to focus on sharing use
innovation and personal use experiences through dialogues, rather than other forms
of value co-creation that are not based on firms‟ offerings such as sharing software
codes and statistical formulas, etc. Nevertheless, dialogue is one of the key forms of
value co-creation. UES in this thesis is about dialogue-based collaboration and co-
production, and co-consumption phenomena in the context of CMOS.
Secondly, this research is focused on consumer-to-consumer value co-creation
within the ECo framework. The A2A relationship in the service economy can be
more complex. However, this study has been undertaken to better understand the
gaps identified in the literature review (i.e., C2C non-reciprocal value co-creation
practice). In future studies, it is recommended that the ECo framework be used to
explore other A2A relationships (e.g., offering co-consumption between business
partners in a value network, such as with the Android OS system).
Thirdly, the findings are limited by the scope of the research including costs and
time. In future studies, offline communities and other online communities (e.g.,
brand communities, online gaming communities, non-profit communities, open
innovation communities, social networking communities, and second life, etc.) can
be used to enhance the generalisability of the two proposed theoretical models.
Fourthly, samples were male dominated in both studies. This may be because in the
high-tech world, males are most active and therefore dominant in samples.
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Fifthly, in Study Two, participants were from the UK, USA and Australia.
Nevertheless, online communities may be culturally less diverse and considering
how culture and technology are diffused in these countries, they might share a
similar online culture in general.
Finally, due to survey length constraints, in some cases, existing concepts were
measured using a part of the full scale (e.g., Consumer Empowerment Scale,
Consumer Savvy Scale), and in other cases, new concepts were measured by inferred
scales borrowed from other disciplines (e.g., Consumer Citizenship and Relating
Needs). Consequently, some constructs may have been subject to under-
identification and just-identification. To capture the complexity of value co-creation
practices, it is suggested that further exploration of these constructs is necessary.
7.9 Directions for Future Study
SD logic has raised broader discussions in marketing research. The rich conceptual
insights provide many opportunities for future study. Drawn from the results,
possible directions for future studies are presented as follows:
Firstly, the results show that Use Innovativeness is highly correlated to Relating
Needs of Self and Relating Needs of Others. Consumers who perform UES to co-
create with others may focus on either relating needs of self or relating needs of
others depending on the general competence in terms of the degree of expertise and
network connectivity. In terms of future study, relating needs will require further
examination to form its own scale, This concept is theorised based on an SD logic
mindset, and it can be used to better understand consumers‟ active roles and
competence as resources in a direct value co-creation process. It also implies a
solution orientation where consumers look for new experiences based on needs
instead of prior experiences, which often focus on associated problems.
Secondly, the findings suggest that Consumer Competence acts as a self-
empowerment factor that takes power from the Consumer Empowerment construct.
Nevertheless, the findings also indicate the reasons that co-creative empowerment
has no significant impact on UES with other consumers and has a negative mitigated
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impact on UES with firms, depends on how responsive they are to co-creative
empowerment. Their responsiveness of co-creative empowerment may be better
measured by a longitudinal study or case studies as consumers may not be aware of
co-creative empowerment until they have experience co-creating value with others
through UES. In addition, another method (i.e., experiment) may also be used in a
future study to test the link between awareness and responsiveness of co-creative
empowerment, because the results indicate that the responsiveness of co-creative
empowerment may be contingent with consumers‟ belief of their competences in
terms of expertise and network connectivity in order to co-create value with others.
Thirdly, the UESBM and CCMM models can be extended by adding SD logic
consistent outcome variables reflecting betterment centricity (e.g., customers‟
gratification instead of satisfaction or loyalty).
Fourthly, the results indicate that network competence is one of the key drivers that
encourage consumers to share their user experiences with others. Therefore, the
researcher may employ social networking analysis (SNA) to gain a more specific
understanding of consumers‟ actual online social ties and structures.
Fifthly, as mentioned in Section 7.8, there is a need to further investigate the
proposed models using full scales of the concepts tested in this research. It is also
possible to develop new scales to reflect these emerging concepts. For example, (1)
examining relation norm or sharing norm; (2) employing a full consumer
empowerment scale to test how value co-creation transforms consumer
empowerment beyond the sense of sovereignty in the UESBM.
Sixthly, case studies or other qualitative study methods may be used to further
explore effort-based value concepts, namely value-in-experience and also further
empirical research in different research contexts is needed to underpin the ECo
framework, such as environmental sustainability and global warming interests
groups.
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Finally, as mentioned in Section 7.3.1, a future study may incorporate „consumer
self-confidence‟ (Bearden, et al., 2001) as a consumer characteristic in the Co-
Creative Consumer Motivation Model.
7.10 Conclusion
This thesis is devoted to the provision of theoretical insights and empirical evidence
not only to underpin SD logic but also to provide a complementary mindset to
further enhance SD logic. While research in consumer marketing is predominately
considered to be in the realm of the exchange paradigm, SD logic has provided a
new mindset for revamping marketing theory. The current research goes further, and
departs from the ten SD logic foundational premises and arrives at an ECo
framework, reconciling an extended lexicon of SD logic. This framework reflects a
betterment centric experience co-creation relationships and processes. It looks
beyond the dyadic relationship of firms as service providers and consumers as
service users. It has a focus on the economic and social actors who share a
congruence of interests and make efforts to strive for betterment through value co-
creation.
This thesis extends the concept of sharing (Belk, 2009), which is significant to non-
reciprocal consumer market phenomena, with value derived from user experience,
and it proposes user experience sharing as an emergent value co-creation behaviour.
It shows that consumers who participate in online communities do co-create value of
their own through User Experience Sharing. The results show that consumers share
not only those experiences that are new and interesting to themselves but also those
that are personalised, and not necessarily intended by firms. These effort-based
experiences (i.e., value-in-experience) are seen as the currency of value co-creation
desired by value initiators to leverage their desired betterment outcomes. That is,
these desired betterment outcomes steer the direction regarding what efforts should
be made and how resources should be integrated in a value co-creation process. In
addition, value initiation also represents a starting point for value co-creation,
because the delivery of value is not an end but a reflective opportunity for betterment.
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Conventional marketing research has only limited discussion of consumers as value
creators, and studies considering active consumers focus on consumers being value
facilitators in the processes where service providers' marketing efforts are made.
This thesis conceptualises the Co-Creative Consumer as a value initiator who makes
efforts to co-create value with other value initiators. The findings indicate Co-
Creative Consumers have a distinct consumer profile, different from Market Mavens,
Lead Users and Prosumers.
In summary, this thesis provides a fresh view to marketing theory in terms of the
provision of an extended lexicon of SD logic and the ECo framework. This research
also provides empirical evidence to support the ECo framework in a consumer
marketing context. It is expected that this synthesised outcome-process driven
framework will resonate with a betterment centric logic, and will provide a new
avenue for future research. It is also important to note that the notion of betterment
centricity does not compete with that of service centricity in SD logic, but is a further
iteration of the essence of a solution-mindset in the service economy/system. The
thesis can be summed up as follows:
Just as service centricity reflects service-for-service through interaction, betterment
centricity abides by the view that experience-for-experience through initiation for
betterment is a mindset for service economy.
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APPENDIX A - GLOSSARY OF TERMS
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Terms used in Chapter Two
Betterment Centricity: Betterment Centricity reflects actors‟ desires/ willingness to
make efforts to fulfil the gap between received and desired value, and it is about
deriving new experiences. It focuses on the solutions and mutual benefit (symmetric
outcomes) that can be achieved through co-creating value without overlooking the
fact that actors may have asymmetric desired outcomes (tensions) when they
initiate/engage in a value co-creation process.
Betterment Outcomes: Betterment outcomes refer to ultimate desired outcomes that
are mutually beneficial, and are achieved through an iteration of efforts made by
value initiators to close the gap between received and desired value. For example,
they can refer to betterment of life (consumer initiated) or brand equity and
sustainable profitability (firm initiated). Thus, under betterment centricity,
betterment outcomes are mutually beneficial for firms and customers and can be
symmetric or asymmetric within or among service systems.
Convergent Mobile Online Services (CMOS): CMOS refers to online services that
are offered to mobile phone users.
Experience Co-Creation Contexts: Experience Co-Creation Contexts capture the
meaning of value co-creation as value-in-experience through a lens of experiential
timing, including pre-experience, customer experience, and post-experience (Tynan
& McKechnie, 2009). As a result, three experience co-creation contexts refer to
value propositions of co-production (pre-experience) (Vargo & Lusch, 2004),
offering co-consumption or co-participation (customer experience) (Baron & Harris,
2008; Pongsakornrungsilp & Schroeder, 2009), and value collaboration (post-
experience) (Beckett & Nayak, 2008).
Experience Co-Creation (ECo) Framework: The ECo framework is proposed to
explain an outcome-process driven value co-creation illustrating that (1) value
initiation is a starting point of the value co-creation process; (2) value-in-experience
is the currency of the service-for-service relationship as a value co-creation process;
(3) value initiators make efforts toward achieving betterment outcomes, and (4) the
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value co-creation process consists of value proposition co-production, offering co-
consumption and value collaboration.
Co-Creative Consumers: The concept of the Co-Creative Consumer is proposed to
represent those value initiators who are willing and capable of co-creating value-in-
experience through User Experience Sharing in a customer initiated value co-
creation process (i.e., either through interaction with firms (C2B) or other customers
(C2C)). Aligning with SD logic reasoning, Co-Creative Consumers are those
consumers who are capable of applying their competences/ willingness to provide
service (i.e., application of competences) for the benefit of other consumers and
themselves in everyday life.
User Experience Sharing: User Experience Sharing is a co-creative effort initiated
by consumers to derive value-in-experience. It can be considered a type of
consumer-to-consumer interaction (Martin & Pranter, 1989; Nicholls, 2010).
However, in the context of this thesis, UES focuses on interaction as consumer value
co-creation as suggested by (Grönroos, 2006) rather than on consumer encounters as
seen in conventional services marketing (Nicholls, 2010). It is more directly derived
from their interactions and experiences with other consumers as well as with the
product or service and is outside the control of the marketers, instead of through
product offerings and/or marketing messages being seeded into a network.
User Experience Sharing resonates within concepts that (1) focus on sharing
experiences derived from a consumer‟s knowledge and skills arising from use
initiation (Szmigin & Foxall, 1998), (2) emphasise value-in-experience, including
new and personalised experiences, therefore going beyond the knowledge and prior
experience associated with the offering; (3) extend to not only increasing perceived
benefits derived from better uses of value propositions offered by firms (e.g., those
functions that may not be known by users), but more specifically linked with
personalised and unexpected value and experiences created beyond firms‟ value
propositions.
Value Initiation: „Value initiation‟ reflects actors‟ initiative efforts made towards
desired outcomes. It draws a focus on desired outcomes (c.f. outcome-process driven)
and helps to interpret a value creation relationship between actors (e.g., who initiates
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value creation and why?) within a value system. In other words, value creation is as
service-for-service through initiation.
Value initiator: The term „value initiator‟ is proposed to capture the notion that
firms, customers and other actors (e.g., government) can be service providers and
users of each other‟s services, in efforts toward achieving desired outcomes.
Value-in-experience: Value-in-experience refers to value derived from efforts made
to fulfil the gap between customer desired value and customer received value. It is
proposed here that value-in-experience as an effort-based value is the currency of
value co-creation (i.e., a driver of value co-creation) that leads to closing the gap
between received and desired value. Value-in-experience, including new and
personalised experiences, therefore going beyond the knowledge and prior
experience associated with the offering.
Terms used in Chapter Three
UESBM refers to User Experience Sharing Behaviour Model which is grounded in
the Theory of Planned Behaviour framework with Self-Determination Theory.
UESC refers to User Experience Sharing with Other Consumers. The items measure
the frequency of user experience sharing (with other consumers) exhibited by a
consumer.
UESF refers to User Experience Sharing with Firms. The items measure the
frequency of user experience sharing (with service providers) exhibited by a
consumer.
EIHO refers to Enjoyment in Helping Others which is a state of intrinsic enjoyment
from helping others without expecting anything in return. This meaning is in line
with Altruism.
EMP refers to Consumer Empowerment which is a positive subjective state as a
result of a mental comparison of a consumer‟s abilities relative to existing or
previous abilities to fulfil their needs and desired outcomes.
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COMP refers to Consumer Competence which represents consumers‟ operant
physical resources and social operant resources. It reflects the capability of
consumers to configure their operant resources to employ available operand
resources in order to achieve their life projects and goals.
TS refers to Technological Sophistication which is related to comfort and leadership
in adopting new technologies.
NW refers to Interpersonal Network which is related to interpersonal connectedness.
ON refers to Online Network which is related to interacting with others online to
search for product information; calling for assistance in making product choices; and
the hedonic value of sharing product opinions with other consumers online.
INT refers to Intention to Engage in User Experience Sharing which reflects how
much effort a consumer might exert and how willing a consumer may be to try to
perform User Experience Sharing behaviour.
ATT refers to Attitudes toward User Experience Sharing which is the degree to
which one evaluates the behaviour favourably or unfavourably based on an
individual‟s evaluation of engaging in User Experience Sharing behaviour.
SN refers to Subjective Norm which reflects an individual‟s belief in the approval
(or disapproval) of engaging in the behaviour of interest from important referents,
either individuals or groups.
CCMM refers to Co-Creative Consumer Motivation Model grounded in the
Motivation, Opportunity, Ability framework. The models use SD logic consistent
constructs and draw upon multiple streams of literature including consumer
education, consumer psychology and consumer behaviour, and organisational
psychology and organisational behaviour.
CIT refers to Consumer Citizenship which is the ongoing contribution of consumer
citizens‟ motives to provide marketplace solutions for themselves and others through
cultivating their skills and values in everyday community contexts.
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REL refers to Relating Needs which is related to consumers‟ ability to integrate their
physical, social and cultural operant resources for the benefit of self or of others.
RELS refers to Relating Needs of Self which represents an individual‟s ability to
personalise and to understand their personal needs.
RELO refers to Relating Needs of Others which represent an individual‟s ability to
understand and associate others‟ needs to one‟s own experiences in order to provide
solutions to the benefit of others.
NEW refers to Newness as an opportunity occurs when desired experiences are
actualised (through efforts made by consumers) and become available to consumers
for sharing.
MAV refers to Mavenism which is a type of consumer characteristics which refers to
the consumer tendency to become especially involved in the marketplace.
UI refers to Use Innovativeness which is the consumer tendency to create innovative
solutions in their everyday lives.
PIN refers to Personal Initiative which is the tendency to take an active and self-
starting approach to work and go beyond what is formally required in a given job.
COMU refers to Communality which is the tendency to give benefits in response to
needs or to demonstrate a general concern for the other person.
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APPENDIX B – LIST OF ITEMS AND SOURCES DERIVED
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Survey items for the User Experience Sharing Behaviour Model
Note: Bold depicts the retained items.
User Experience Sharing with Other Consumers (UESC)
1. How often have you shared your experiences of using mobile online services with
other people either online, or through word of mouth in the past six months?
2. How often have you actively asked friends or online acquaintances for their
experiences of using mobile online services in the past six months?
3. How often have you given suggestions to friends or online acquaintances based
on your experiences of using mobile online services in the past six months?
User Experience Sharing with Firms (UESF)
1. How often have you contributed comments, reviews, recommendations or ratings
based on your experiences of using mobile online services in the past six months?
2. How often have you given constructive feedback based on your experiences of
using mobile online services to service providers in the past six months?
Attitudes toward User Experience Sharing (Eight Items)
For me, sharing my experiences of using mobile online services with other people at least
once in the upcoming six months would be:
(a) Difficult|||Easy, (b) Unimportant|||Important, (c) Unsatisfying|||Satisfying, (d)
Useless|||Useful, (e) Harmful|||Beneficial, (f) Unpleasant|||Pleasant, (g) Bad|||Good, and (h)
Worthless|||Valuable.
Subjective Norm
1. People I interact with often in online communities are important to me.
2. Most people who visit the same online communities that I do expect that I should
share information and experiences.
3. Most people who visit the same online communities that I do expect that I should
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share relevant information and experiences if it will help other visitors.
4. Most people who visit the same online communities that I do expect that I should
keep others informed about new information and experiences.
Intention to Engage in User Experience Sharing
1. I will most likely contribute comments reviews recommendations or ratings to an
online community in the upcoming six months.
2. I intend to share with other people my experiences of using mobile online services
either online or by word of mouth in the upcoming six months.
3. I will try to share with other people my experiences of using mobile online services
either online or by word of mouth in the upcoming six months.
4. I plan to share with other people my experiences of using mobile online services
either online or by word of mouth in the forthcoming six months.
Consumer Competence
Technological Sophistication (TS)
1. Other people come to me for advice on new mobile online services.
2. In general, I am first among my circle of friends to acquire new mobile online
services when they appear.
3. I can usually figure out new mobile online services without help from others.
Online Network (ON)
1. I often visit websites to find out about the latest mobile online services that will be
coming out.
2. I'll often search for blogs and review websites that can help me when I'm looking
for mobile online services recommendations.
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3. I'll often seek the opinions of others by posting queries about mobile online services
on online community websites.
4. I enjoy sharing points of view about mobile online services with online
acquaintances via online community websites.
5. My best contacts for information about new mobile online services often include
people online that I've never met face-to-face.
Interpersonal Network (NW)
1. I always know someone to call if I want to find out about the best mobile online
services.
2. I have a useful network of contacts who can give me up-to-date information on
the latest mobile online service innovations.
Original items (Macdonald & Uncles, 2007)
Technological Sophistication - Innovative Expertise
1. Other people come to me for advice on new technologies.
2. In general, I am first among my circle of friends to acquire new technology
when it appears.
3. I can usually figure out new high-tech products and services without help
from others.
Online Network Competency
1. I often check-out chatrooms and bulletin boards to find out about the latest
products that are coming.
2. I'll often see if there is an online community that can help me when I'm
looking for a product recommendation.
3. I'll often seek the opinions of other customers by posting a query about a
product on an online bulletin board or chat room.
4. I enjoy sharing points of view with online acquaintances via bulletin boards
and chatrooms.
5. My best contacts for new product information often include people online
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that I've never met face-to-face.
Interpersonal Network Competency
1. I always know someone to call if I want to find out about the best product or
service.
2. I have a useful network of contacts who can give me up-to-date product
information on the latest innovations.
Consumer Empowerment
1. In the online communities in which I engage I think that people have a right to make
their own decisions, even if they are bad ones.
2. People should share their experiences the way they want.
3. People working together can have an effect on the online community.
4. People have more power if they join together as a group.
5. Working with others can help to change things for the better.
Original items (Rogers, et al., 1997)
1. People have a right to make their own decisions, even if they are bad ones
2. People should try to live their lives the way they want to
3. People working together can have an effect on their community
4. People have more power if they join together as a group
5. Working with others in my community can help to change things for the
better
Enjoyment in Helping Others
1. I enjoy sharing my experiences of using mobile online services with friends or
online acquaintances.
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2. I enjoy helping friends or online acquaintances by sharing my experiences of
using mobile online services.
3. It feels good to help friends or online acquaintances solve their mobile online
services related problems.
4. Sharing my experiences of using mobile online services with friends or online
acquaintances gives me pleasure.
Original items: (Kankanhalli, et al., 2005)
1. Enjoy sharing my knowledge with others through EKRs.
2. Enjoy helping others by sharing my knowledge through EKRs.
3. It feels good to help someone else by sharing my knowledge through EKRs.
4. Sharing my knowledge with others through EKRs gives me pleasure.
Survey Items for the Co-Creative Consumer Motivation Model
User Experience Sharing
To what extent are you currently sharing your experiences of using mobile online
services
1. … in a way not originally intended by the service provider.
2. … that are new, fun, useful, or interesting to you.
3. … that work for you personally.
Newness (Five Items)
The experiences of using mobile online services that I usually share are
“Not original at all|||Completely original”; “Not new to me at all|||Completely new to me”;
“Not personalised at all|||Completely Personalised”; “Not unique at all|||Completely
unique”; and, “Not different at all|||Completely different”.
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Original items (Andrews & Smith, 1996)
Compared to what your competitors where doing last year, your product‟s most recent
marketing program is:
Dull --- Exciting; Fresh --- Routine; Conventional --- Unconventional; Novel --- Predictable;
Usual --- Unusual; Unique --- Ordinary; Commonplace --- Original.
Consumer Citizenship
1. I consider myself a good online community citizen who is willing to help others.
2. I believe my experiences of using mobile online services are valuable to the online
communities to which I belong.
3. I feel I am responsible for responding to other users’ questions or replies about
mobile online services.
4. Because I expect other users of my online community to share their experiences of
using mobile online services with me or each other, it’s only fair to share mine
with them.
Original Items (Constant, et al., 1996; Lakhani & Von Hippel, 2003)
1. Being a good company citizen
2. The problem is important to the company
3. It is part of my job to answer questions like this one
4. I expect others to help me, so it is only fair to help them
Relating Needs
Relating Needs of Self
1. I often use mobile online services in such ways that I create personalised routines
that are different from others.
2. I often research the suitability, rather than the popularity, of a mobile online
service because I enjoy having a service that fits my personal needs.
P a g e | 207
3. I actively seek to improvise my personalised routines by using a range of mobile
online services.
4. Being able to spot mobile online services that suit my needs assists me in
establishing my personalised routines.
Original items (Ruvio, et al., 2008)
1. I often combine possessions in such a way that I create a personal image that
cannot be duplicated.
2. I often try to find a more interesting version of run-of-the-mill products
because I enjoy being original.
3. I actively seek to develop my personal uniqueness by buying special products
or brands.
4. Having an eye for products that are interesting and unusual assists me in
establishing a distinctive image.
Relating Needs of Others
1. I naturally read and relate to other users’ needs about using mobile online
services.
2. I generally know what mobile online services other users need from their
questions, even questions that can be vague.
3. I am able to anticipate the needs of other users about using mobile online services.
Original items (Donavan, et al., 2004)
1. I naturally read the customer to identify his/her needs.
2. I generally know what service customers want before they ask.
3. I enjoy anticipating the needs of service customers.
P a g e | 208
Use Innovativeness
1. Knowing new ways of using a mobile online service gives me almost as much
pleasure as knowing the usefulness of a mobile online service.
2. I’m very creative when using a mobile online service in a way that is different from
what the developer intended.
3. I’m very interested in exploring new uses of a mobile online service and what
makes it work for me.
4. I do not enjoy a mobile online service unless it has multiple uses.
5. I use mobile online services in more ways than most of my friends.
6. I often begin using a mobile online service for a particular situation, but end up
using it for different situations.
7. A mobile online service's value is directly related to the number of ways it can be
used.
8. It’s always possible to better use a mobile online service by upgrading it.
9. After using mobile online services on my mobile device, I try to keep track of new
upgrades or better alternatives that come out in the market.
10. I enjoy expanding and adding mobile online services on to my mobile devices that I
will use on a continuing basis.
Original items (Price & Ridgeway, 1983)
1. Knowing how a product works offers almost as much pleasure as knowing
that the product works very well.
2. I‟m very creative when using products.
3. I‟m very interested in appearance of products and what makes them tick.
P a g e | 209
4. I do not enjoy a product unless I can use it to its fullest capacity.
5. I use products in more ways than most people.
6. I often buy a food item for a particular recipe but end up using it for
something else.
7. A product‟s value is directly related to the ways it can be used.
8. It‟s always impossible to improve on a project by adding new features.
9. After purchase of a product, I try to keep track of new accessories that come
out in the market.
10. I enjoy expanding and adding on to projects in which that I‟m involved on a
continuing basis.
Mavenism
1. I like introducing technologies to my friends.
2. I like helping people by providing them with information about how to use a
technology.
3. People ask me for information about technologies.
4. If someone asked how to get the best use out of several types of technologies, I
could tell them what to do.
5. My friends think of me as a good source of information when it comes to
technologies.
6. I know about lot of different technologies and I like sharing this information.
Original items (Geissler & Edison, 2005)
1. I like introducing new brands and products to my friends.
2. I like helping people by providing them with information about many kinds
of products.
3. People ask me for information about products, places to shop or sales.
P a g e | 210
4. If someone asked where to get the best buy on several types of products, I
could tell them where to shop.
5. My friends think of me as a good source of information when it comes to
new products or sales.
6. I know a lot of different products, stores and sales and I like sharing this
information.
Personal Initiative
1. I actively seek to solve problems.
2. Whenever something goes wrong, I search for a solution immediately.
3. Whenever there is a chance to get actively involved, I take it.
4. I take the initiative immediately, even when others don’t.
5. I use opportunities quickly in order to attain my goals.
6. I often do more than I am asked to do.
7. I am particularly good at putting my ideas into practice.
Original items (Frese, et al., 1997)
1. I actively attack problems.
2. Whenever something goes wrong, I search for a solution immediately.
3. Whenever there is a chance to get actively involved, I take it.
4. I take initiative immediately even when others don‟t.
5. I use opportunities quickly in order to attain my goals.
6. Usually I do more than I am asked to do.
7. I am particularly good at realizing ideas.
P a g e | 211
Communality
1. When making a decision, I take other people’s needs into account.
2. I believe people should go out of their way to be helpful.
3. I expect people I know to be responsive to my needs.
4. I go out of my way to help other people.
5. I turn to others I know for help when I have a need.
Original items (Clark, et al., 1987)
1. When making a decision, I take other people‟s needs and feelings into
account.
2. I believe people should go out of their way to be helpful.
3. I expect people I know to be responsive to my needs and feelings.
4. I often go out of my way to help another person.
5. When I have a need, I turn to others I know for help.
P a g e | 212
APPENDIX C – USER EXPERIENCE SHARING
QUESTIONNAIRE
User Experiences Sharing Survey
Research Team ContactsTom Chen, PhD Candidate Phone:(07) 3138 5190 Email: [email protected] Professor Judy Drennan, Principal Supervisor Phone: (07) 3138 5308 Email: j [email protected]
Description
Page J213
1\o'CI"X •Y 01 tn• real ','>f
Faculty of Business
This project is being undertaken as a component of the PhD project for Tom Chen. The purpose of the study is to examine how individuals find new ways to use their mobile phones and why they share these experiences with each other.
Participation Participation in this survey is voluntary. If you do agree to participate, you can withdraw at any point up until when you submit the survey without comment or penalty. The survey will be conducted online: the time and place are chosen at participants' convenience.
Expected benefits Participants may choose to enter the prize draw after they complete the survey. In addition, the results may provide insights into how users can enhance the value of mobile online services through sharing user experiences with others.
Risks There are no foreseen risks associated with your participation in this project.
Confidentiality All responses are confidential, and results will only be published in aggregate and for research purposes.
The survey will be collated and only the research team will have access to the data. The survey will not be associated with your name or email address. Your participation will remain anonymous. The information collected is confidential and will not be disclosed to third parties without your consent, except to meet government, legal or other regulatory authority requirements. They will only be used for research, academic and instructional purposes.
Consent to Participate Please click "Next" at the end of the consent section to confirm your agreement to participate.
Questions I further information about the project You may contact the researchers listed above about any matter or concerns regarding the project.
Concerns I complaints regarding the conduct of the project OUT is committed to researcher integrity and the ethical conduct of research projects. However, if you do have any concerns or complaints about the ethical conduct of the project you may contact the QUT Research Ethics Officer on 3138 2340 or [email protected]. The Research Ethics Officer is not connected with the research project and can facilitate a resolution to your concern in an impartial manner.
Page 1 of 17
Pa ge 1214
Welcome! Please note: You may complete this survey on your Smart phone, but it is not optimised for mobile browsers. We recommend that you complete this survey on a computer. If the text in your browser is too small for you to read, press and hold "CTRL" key, then use"+" or"-" to adjust the text size.
lt will take approximately 10 minutes to complete this survey. There is an indicator on each page outlining your progress. Please note that every question on the page needs to be answered before you can proceed to the next page. On the last page of the survey, make sure you click "Submit" to complete the survey. Once you complete the survey, if you would like to participate in the prize draw and win an Apple iPad click "Close" on the Thank You page (Australia, UK, USA residents only).
There are no right or wrong answers. Please answer each individual question carefully. When you are ready, click "Next" to start the survey.
Are you a member of an online community? An online community is a virtual community that exists online, and whose members can interact with others, e.g. Facebook, Twitter, Youtube, Linkedln, online forums, online interest groups, blogs, Bulletin Board Systems (BBS), etc.
Please pick one of the answe!S below.
0 Yes
0 No
Do you use Apps or any online service via a browser on your Smartphone? E.g. iPhone Apps, Email, Skype, mobile banking, Google Maps, Twitter, Facebook, MySpace, Linkedln ...
Please pick one of the answe!S below.
0 Yes
0 No
Do you use any online service via a browser on your computer? E.g. Email, Internet banking, Facebook ...
Please pick one of the answe!S below.
0 Yes
0 No
Page 2 of 17
P age 1215
Question 1
Please marlc the corresponding circle -only one per line. p 1J
(12 times or
(1-3 times) (4-6 times) (7-11 times) more)
Seldom
11 Never RarelY. " 11 Often RegularlY.
How often have you shared
your experiences of using
mobile on line services with
other people either on line,
or through word of mouth In
the past six months? 0 0 0 0 0
How often have you actiVely ,,
11 asked friends or on line
acquaintances for their
experiences of using mobile
onllne services In the past
six months? 0 0 0 0 0
How often have you given
suggestions to friends or
onllne acquaintances based
on your experiences of
using mobile online services
In the past six months? 0 0 0 0 0
How often have you li contributed comments,
reviews, recommendations
or ratings based on your
experiences of using mobile
onllne services In the past
six months? 0 0 'I 0 0 0
How often have you given
constructive feedback
based on your experiences
of using mobile online
services to service
providers in the past six
months? 0 0 0 0 0
Page 3 of 17
Page 121_6
Question 2 To what extent are you currently sharing your experiences of using mobile on line services ...
Please mark the corresponding circle - only one per line.
in a way not originally
intended by the service
provider? 11
tliat are new, fun, useful, or Interesting to Y.OU? .,
that work for you
personally?
Question 3
Never
0
0
0
RarelY:
0
0
0
In the online communities in which I "engage", I think that ...
Please mark the corresponding circle - only one per line.
people have a right to make
their own decisions, even if
they are bad ones.
If
people should share their 1 experiences the way they ,j
1)11want. I
people working together can
have an effect on the online
community.
people have more power If they join together as a group. 11
working with others can
help to change things for
the better.
Strongly
Disagree il Disagree
0 0
0 0
0 0
0 0
0 0
I~
1!
...
Seldom Often Regularly
0 0 0
0 0 0
0 0 0
1r Neutral ti Agree •• Strongly Agree
0 0 0 IJ
0 0 0
0 0 0
0 0 0
0 0 0
Page 4 of 17
P age 1217
Question 4
Please marf( the corresponding circle - only one per line. i"
!I
u
j Strongly
Disagree Dis~gree Neutral AQree StronQIY Agree
I consider myself a good online community citizen who is willing to help others. 0 0 0 0 0
I believe my experiences of using mobile onllne services are valuable to the onllne communities to which I
!1. Jl ll belong. 0 0 0 0 0
I feel I am responsible for responding to other users' questions or replies about mobile on line services. 0 0 0 0 0
! 11
Because I expect other users of my onllne community to share their experiences of using mobile onllne services with me or
Jl each other, Ifs only fair to share mine with them. 0 0 0 .lt 0 Q
Page 5 of 17
Pa ge 1218
Question 5
Please mark the corresponding circle -only one per fine.
ff
Strongly
Disagree Disagree Jl Neutral Agree Strongly Agree
I enjoy sharing my experiences of using mobile
on line services with friends
or online acquaintances. 0 0 0 0 0 ,_. !'
I enjoy helping frienas or
onllne acquaintances by sharing my experiences of using mobile online
~ l services. 0 0 0 0 0
lt feels good to help friends
or online acquaintances solve their mobile on line
services related problems. 0 0 0 0 0
Sharing my experiences of ll 11 using mobile onllne services
with friends or onllne
li acquaintances gives me ~ pleasure. 0 0
" 0 0 0
Question 6 The experiences of using mobile on line services that I usually share are ...
Please mark the corresponding circle - only one per fine.
'> -._. Jl 1 2 3 4 5
Not original at
alii! I Completely original 0 0 0 0 0 ll
Not new to me at aiiiJICompletel}t new to me 0 0 0 11 0 0
Not personalised at
aiiJIICompletely personalised 0 0 0 0 0
I~
1! !! Not unique at !i aiJIIICon:'ipJet«;!ly_ unigue 0 0 ,. 0 0 11 0
Not different at
aiiiiJCompletely different 0 0 0 0 0
Page 6 of 17
P age 1219
Question 7 For me, sharing my experiences of using mobile online services with other people at least once in the upcoming six months would be ...
Please mark the co" espondlng circle -only one per line.
11 1
Difficult! I! Easy 0
UnimP-Qrtantlll!mportant 11 0
UnsatisfyingiiiSatisfying 0
UseiesslJIUseful 0
Harmful Ill Beneficial 0
Un~leasan~(IPieasant ll 0
BadiiiGood 0
WorthlessJJJValuafile ll 0
Question 8
Please mark the co"esponding circle- only one per line.
People I interact with often in online communities are important to me.
J!
Most people who visit the 1r same onllne communities that I do expect that I should share info.rmatlon and experiences.
Most people who visit the same online communities that I do expect that I should share relevant information and experiences if it will help other visitors.
Most people who visit the ~l same onllne communities that I do expect that I should keep others Informed about new informatlon and experiences.
Stmngly
DisaQree
0
0
0
0
2 11
0
~I 0 ,,
0
ll 0 .11
0
ll 0
0
11 0
Disagree
0 11
I~
0 IL
0
0
If .,
11 3 4 5
0 0 0
0 'I 0 11 0
0 0 0
0 ll 0 0
0 0 0
0 0 0
0 0 0
0 11 0 0
11 Neutral StrOIJ9!Y Agree
0 0 0
0 0 0
0 0 0
0 0 0
Page 7 of 17
P a $ e 1220
Question 9
Please marl< the corresponding circle - only one per line.
11
Strongly !f 11
Disagree Disagree Neutral Agree Strongly Agree
I will most likely contribute comments, reviews, recommendations or ratings to an online community in the upcoming six months. 0 0 0 0 0
11
·,· " I Intend to share with other people my experiences of using mobile onllne services, either onllne or by word of mouth In the upcomlng six months. 0 ~I 0 0 0 0
I will try to share with other people my experiences of using mobile online services, either online or by word of mouth in the upcoming six months. 0 0 0 0 0
I' I~ !; I plan to share wtth other
geople my experiences of I, using mobile onllne 11
services, either onllne or by word of mouth In the
Ji forthcoming six months. 11 0 0 0 0 il 0
Page 8 of 17
P age 1221
Question 10
Please mark the cc"esponding circle - only one per line.
" 11
il Strongly
Disagree ,, Disagree Neutral Agree Strongl~ Agree
Other people come to me for advice on new mobile online services. 0 0 0 0 0
In general, I am first among my circle of friends to acquire new mobile onllne services when they appear. 0 0 11 0 0 0
I can usually figure out new mobile online services without help from others. 0 0 0 0 0
I always know someone to call If I want to find out about the best mobile onllne services. 0 0 0 Jl 0 0
I have a useful network of contacts who can give me up-to-date information on the latest mobile on line service innovations. 0 0 0 0 0
I often visit websltes to find
I! out about the latest mobile onllne services that will be
comi11gout. 0 Jt 0 li 0 0 j) 0
I'll often search for blogs and review websites that can help me when I'm looking for mobile online services recommendations. 0 0 0 0 0
,: ! 111 often seek the opinions of others by posting queries about mobile onllne services on onllne community websltes. il 0 0 0 0 0
I enjoy sharing points of view about mobile on line services with online acquaintances via on line community websites. 0 0 0 0 0
Page 9 of · 17
Pa ge I ~22
11
I. !: My best contacts for Information about new mobile onllne services often
11 ;l Include people onllne that I've never met face-to-face. 0 0 0 0 0
I naturally read and relate to other users' needs about using mobile online services. 0 0 0 0 0
I,
I generally know what mobile onllne services other users need frOm their questions, even questions that can be vague. 0 0 0 0 0
I am able to anticipate the needs of other users about using mobile online services. 0 0 0 0 0
Page 10 of 17
Page !223
Question 11 In general, ...
Please mark the corresponding circle - only one per line. I
Strongly ·u
Disagree Dlsagree Neutral .Agree StronglY' Agree
I actively seek to solve problems. 0 0 0 0 0
whenever something goes wrong, I search for a
11 solution Immediately:. jp 0 0 0 0 0
whenever there is a chance to get actively involved, I take it. 0 0 0 0 0
I take the Initiative
ii Immediately, even when others don't. 0 0 0 0 11 a I use opportunities quickly in order to attain my goals. 0 0 0 0 0
'!" I often do more than I am asked to do. 0 0 0 0 !~ 0
I am particularly good at putting my ideas into practice. 0 0 0 0 0
when making a decision, I 11
take other ReQple's needs I ·Into account. il 0 0 0 0 0
I believe people should go out of their way to be helpful. 0 0 0 0 0
i! I expect people I know to be rel?,P.Q.nsive to ·ll}y_ needs. 0 0 0 Jl 0 0
I go out of my way to help other people. 0 0 0 0 0
il
1! 11
,. I turn to others I know for help when U1ave a n~j!d. 0 0 0 0 iL 0
Page 11 of 17
Question 12
Please mi!rlc the cc"esponding circle • only one per line.
'! Strongly
1! 11
Disagree ii Disagree Neutral Agree StronglY- Agree
Knowing new ways of using
a mobile online service
gives me almost as much
pleasure as knowing the
usefulness of a mobile
on line service. 0 0 0 0 0 .,,
i! I'm very creative when
using a mobile onllne
service In a way that Is
different from what the
develoP.er Intended.. 0 0 0 ;I 0 0
I'm very interested in
exploring new uses of a
mobile online service and
what makes it work for me. 0 0 0 0 0 "
,!, I do not enjoy a mobile
onllne selVice unless it has
multiple uses. 0 d 0 0 0 :~ 0
I use mobile online services
in more ways than most of
my friends. 0 0 0 0 0
I often begin using a mobile 11
onllne service for a
particular situation, but end
up using 1t for different
situations. 0 0 0 0 0
A mobile on line service's
value is directly related to
the number of ways it can
be used. 0 0 0 0 0
Ifs always posslbl~ to better
use a mobile onllne service
by upgrading lt. 0 11 0 0 0 ll 0
After use mobile online
services on my mobile
device, I try to keep track of
new upgrades or better
alternatives that come out in
the market. 0 0 0 0 0
Page 12 of 17
I enjoy expanding and adding mobile onllne services on to my mobile devices In which I will use on a continuing basis.
Question 13
0
Please mark the co"esponding circle - only one per line.
~ Strongly
Disagree
I like introducing technologies to my friends. 0
!like helping peoP-le by providing them with Information abotit how to use a technol<>gy. 0
People ask me for information about technologies. 0
If someone asked how to get the best use on several types of technologies, I could tell them what to do. 0
My friends think of me as a good source of information · when it comes to technologies. 0
I know a lot of different technologies and ! like sharing this information. 0
0
Disaaree
0
I!
0
0
0
0
0
P age 1225
0 0 0
lf
11 Neutral Agree " Strongly Ag~
0 0 0 ~r
0 i 0 0
0 0 0
1f
0 0 ;I 0
0 0 0
0 :i 0 0
Page 13 of 17
Question 14
Please mark the co"esponding circle - only one per line.
Sfror:~gly
11 Strongly Agree ll Disagree Disagree Neutral Agree
I often use mobile online services in such ways that I create personalised routines that are different from others. 0 0 0 0 0
I often research the 11
suitability, rather than the 11 'I
popularity, of a mobile onllne service because I enjoy having a servl.ce that
jj ll flts my P.:!i!rsonal needs. 0 0 11 0 0 0
I actively seek to improvise my personalised routines by using a range of mobile on line services. 0 0 0 0 0
'I Being able to spot mobile onllne services that suit my needs assists me In establishing my
11 personalised routines. 0 0 0 0 0
Page 14 of 17
Pag e J227
Question 15
Please mark the corresponding circle • only one per line.
Strongly j ii 11
Disagree Disagree Neutral Agree Strongly Agree
I like to have the
responsibility of handling a
situation that requires a lot
of thinking. 0 0 0 0 0 " u
I really enjoy a task that
lnvorves coming up with
new solutions to problems. 0 0 0 jl 0 0
Learning new solutions
doesn't exCite me very
much. 0 0 0 0 0 ,, I usually end up deliberating
about solutions even when
they do not affect me
~rsonally. 0 0 0 0 0
Question 16
Gender
Please pick one of the answers below.
0 Male
0 Female
Age Group
Please pick one of the answers below.
0 18- 25
0 26-35
0 36-45
0 46-55
0 56 .65
0 Above 65
Page 15 of 17
Page 1228
Level of Education
Please pick one of the answets below.
0 Less than 1 0 years schooling
0 1 0 Y.ears to 11 }':ears af sehooling
0 12 years of schooling
0 Basic vocational (!ualification
0 Skilled vocational qualification
0 Diploma or Associate diRioma
0 Undergraduate degree (Bachelors)
0 PostQraduate certificate/diploma
0 Coursework Masters
0 Research Masters
0 PhD or ABO
0 Rrofessional (!Ualification
0 Other
Are you currently living in?
Please pick one of the answets below.
0 Australia
0 UK
0 USA
0 Other
If you like to receive a managerial report of the results, please add your email address in this text box.
Please use the blank space to write your answers.
Page 16 of 17
Page 1229
If you have any comments or questions regarding this survey, please add in this text box.
Please write your answer in the space below.
CRICOS No. 00213J
Page 17 of 17
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