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BRANDED MARKETING EVENTS: THE INFLUENCE OF EVENT

EXPERIENCE ON CUSTOMER ENGAGEMENT

A thesis submitted in fulfilment

of the requirement for the degree of

DOCTOR OF PHILOSOPHY

By

Teagan Lynette Altschwager, B.Com. (Hons)

School of Marketing and Management

Adelaide Business School

University of Adelaide

November 2014

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ABSTRACT

This thesis investigates the role of branded marketing events (BMEs) in facilitating

customer engagement. As business environments become more dynamic and interactive,

customers are seeking participation through unique experiences with brands (Vivek,

Beatty, and Morgan 2012), and hence customer engagement has emerged as an important

concept in academe. Previous research has demonstrated that customer engagement is

highly impactful in enhancing customer-brand relationships (Brodie, Hollebeek, Jurić, and

Ilić 2011a), however, there has been little research exploring the antecedents that facilitate

customer engagement. This thesis proposes that BMEs can be used as strategic tools to

facilitate engagement with an event, with engagement transferred to the brand and

ultimately resulting in enhanced behavioural intention of loyalty.

A quantitative online survey was conducted in the South Australian wine industry to

investigate how experiential components of a BME contribute to both customer event

engagement and customer brand engagement. The impact of BME experiences on

behavioural intention of loyalty, and the moderation effect of experiential needs are

examined through structural equation modelling.

Results indicate that customer event engagement has a mediating effect on the relationship

between BME experiences and customer brand engagement. Sensorial, relational and

pragmatic experiences are found to only impact customer event engagement, while

cognitive experience has a direct impact on customer brand engagement. This highlights

that the heightened state of engagement can transfer between focal objects; from the event

to the brand. This provides further insight into the BME’s impact on customer brand

engagement and behavioural intention of loyalty. In addition, support is found for the

inclusion of a social dimension of customer brand engagement, and partial support for a

social dimension of customer event engagement. Therefore, results of this thesis suggest

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that BME experiences facilitate customer engagement and subsequent behavioural

intention of loyalty.

The moderating influences of the individual’s experiential needs, namely need for

cognition, need for affect, and novelty-seeking needs are also examined. There is evidence

that attendees with a strong need for cognition engage more strongly with relational BME

experiences, while attendees with low need for cognition engage more strongly with

sensorial BME experiences. However, few moderating effects are identified overall.

This research empirically demonstrates the strong and positive relationship between BMEs

and customer engagement, and advocates the use of BMEs as an effective brand-building

activity. This thesis contributes to the knowledge of customer engagement through

identifying engagement transfer between two focal engagement objects, and provides

support for the inclusion of a social engagement dimension. The findings provide support

for the BME activities that managers undertake with the intention of facilitating customer

engagement and providing brand-related outcomes through such endeavours.

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TABLE OF CONTENTS

ABSTRACT ............................................................................................................................ I

TABLE OF CONTENTS ..................................................................................................... III

LIST OF FIGURES ........................................................................................................... VII

LIST OF TABLES ............................................................................................................ VIII

DECLARATION .................................................................................................................. X

PUBLICATIONS ................................................................................................................. XI

ACKNOWLEDGMENTS ................................................................................................. XII

KEY TERMS, DEFINITIONS AND ABBREVIATIONS .............................................. XIV

CHAPTER 1: INTRODUCTION .................................................................................... 1

1.1 Background to the Research ........................................................................................ 1

1.2 Research Problem and Propositions ............................................................................ 2

1.3 Justification for the Research ....................................................................................... 3

1.4 Research Context ......................................................................................................... 5

1.5 Research Method ......................................................................................................... 6

1.6 Delimitation and Scope of the Thesis .......................................................................... 7

1.7 Outline of the Thesis .................................................................................................... 9

1.8 Chapter 1 Summary ................................................................................................... 10

CHAPTER 2: LITERATURE REVIEW ....................................................................... 11

2.1 Chapter 2 Introduction ............................................................................................... 11

2.2 Customer Engagement ............................................................................................... 14

2.2.1 Theoretical Foundations of Customer Engagement ............................................ 14

2.2.2 Customer Engagement Conceptualisation .......................................................... 15

2.2.2.1 Different Perspectives of Customer Engagement ........................................ 18

2.2.2.2 Definition of Customer Engagement ........................................................... 19

2.2.2.3 Dimensions of Customer Engagement ........................................................ 20

2.2.2.4 What Customer Engagement is not: Related Concepts ............................... 22

2.2.2.5 Antecedents and Outcomes of Customer Engagement ................................ 26

2.3 Branded Marketing Events ........................................................................................ 28

2.3.1 Marketing Events ................................................................................................ 28

2.3.1.1 Defining Marketing Events .......................................................................... 30

2.3.2 Conceptualisation of Marketing Events .............................................................. 32

2.3.2.1 Branded Marketing Events - a Definition .................................................... 33

2.3.2.2 Investigating a Broader Conceptualisation of BMEs: Customer Experience ................................................................................................................................. 35

2.3.3 Customer Experience .......................................................................................... 36

2.3.4 Components of Experience within a BME ......................................................... 37

2.3.5 Outcomes of BMEs experiences ......................................................................... 39

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2.4 Customer Engagement and BMEs: A Conceptual Framework ................................. 41

2.4.1.1 The role of Social Engagement within Customer Engagement ................... 44

2.4.2 Relationships between Experiential Components of a BME and Customer Engagement ................................................................................................................. 47

2.4.2.1 Cognitive Experience ................................................................................... 50

2.4.2.2 Emotional Experience .................................................................................. 52

2.4.2.3 Sensorial Experience .................................................................................... 53

2.4.2.4 Pragmatic Experience .................................................................................. 55

2.4.2.5 Relational Experience .................................................................................. 56

2.4.3 The Interplay between Customer Engagement Objects ...................................... 59

2.4.3.1 Customer Engagement to Behavioural Intention of Loyalty ....................... 62

2.5 Experiential Needs ..................................................................................................... 66

2.5.1 Conceptualising Experiential Needs ................................................................... 66

2.6 Hypotheses Summary ................................................................................................ 74

2.7 Conceptual Framework .............................................................................................. 76

2.8 Chapter 2 Summary ................................................................................................... 78

CHAPTER 3: RESEARCH METHOD ......................................................................... 79

3.1 Chapter 3 Introduction ............................................................................................... 79

3.2 Research Design ........................................................................................................ 80

3.3 Unit of analysis .......................................................................................................... 81

3.4 Data Collection Method ............................................................................................. 82

3.4.1 Measurement Instrument .................................................................................... 82

3.4.2 Operationalistion of the Theoretical Constructs ................................................. 83

3.4.3 Measurement Scales ........................................................................................... 84

3.4.4 Questionnaire Design .......................................................................................... 92

3.4.4.1 Scaling ......................................................................................................... 93

3.4.4.2 Questionnaire Content ................................................................................. 94

3.4.4.3 Questionnaire Structure and Sequencing ..................................................... 94

3.4.5 Ethics and Information Confidentiality .............................................................. 97

3.4.6 Data Coding and Editing ..................................................................................... 97

3.5 Pre-Test: University of Adelaide Orientation Week .................................................. 98

3.5.1 Overview ............................................................................................................. 98

3.5.2 Subjects ............................................................................................................... 98

3.5.3 Sample and Respondent Profile .......................................................................... 99

3.5.4 Data Collection Procedure ................................................................................ 100

3.5.5 Pre-test Data Analysis ....................................................................................... 100

3.6 Main Study: South Australian Wine Industry .......................................................... 103

3.6.1 Overview ........................................................................................................... 103

3.6.2 Subjects ............................................................................................................. 103

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3.6.3 Selection of Participating Wineries .................................................................. 103

3.6.4 Selection of Individual Respondents ................................................................ 104

3.6.5 Respondent Profiles .......................................................................................... 105

3.6.6 Data Collection Procedure ................................................................................ 106

3.7 Preliminary Analysis ................................................................................................ 108

3.7.1 Data Cleaning ................................................................................................... 108

3.7.2 Non-Response Bias ........................................................................................... 109

3.7.3 Construct Validity ............................................................................................. 111

3.7.3.1 Convergent Validity ................................................................................... 112

3.7.3.2 Discriminant Validity and Reliability Testing ........................................... 126

3.7.4 Testing for Common Method Bias ................................................................... 131

3.8 Chapter 3 Summary ................................................................................................. 132

CHAPTER 4: RESULTS ............................................................................................. 133

4.1 Chapter 4 Introduction ............................................................................................. 133

4.2 Social Engagement as an Independent Engagement Dimension ............................. 134

4.2.1 Convergent Validity of Social Engagement Dimensions ................................. 134

4.2.2 Discriminant Validity and Reliability Testing of Social Event Engagement ... 137

4.2.3 Discriminant Validity and Reliability Testing of Social Brand Engagement ... 140

4.2.4 Discriminant Validity of Social Constructs ...................................................... 143

4.2.5 Structural Model of Customer Event Engagement ........................................... 146

4.2.6 Structural Model of Customer Brand Engagement ........................................... 149

4.2.7 Discussion of Hypothesis 1............................................................................... 151

4.3 Path Model Analysis using Structural Equation Modelling .................................... 153

4.3.1 Path Model Analysis ......................................................................................... 153

4.3.2 Calculation of Composite Variables ................................................................. 154

4.4 Evaluating Path Models ........................................................................................... 158

4.4.1 Model Specification .......................................................................................... 158

4.4.2 Model Identification ......................................................................................... 158

4.4.3 Model Estimation .............................................................................................. 159

4.4.4 Model Re-specification ..................................................................................... 161




4.5 The Moderation Effect of Experiential Needs ......................................................... 176

4.5.1 Method for Multi-group Analysis ..................................................................... 176

4.5.2 Need for Cognition ........................................................................................... 178

4.5.3 Need for Affect ................................................................................................. 180

4.5.4 Novelty-Seeking Needs .................................................................................... 183

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4.6 Chapter 4 Summary ................................................................................................. 189

CHAPTER 5: DISCUSSION AND CONCLUSION .................................................. 191

5.1 Chapter 5 Introduction ............................................................................................. 191

5.2 Summary of Findings ............................................................................................... 192

5.2.1 The Role of Social Engagement ....................................................................... 192

5.2.2 Experiential Components of A BME that Facilitate Customer Engagement ... 193

5.2.3 Engagement Transfer from Event to Brand ...................................................... 195

5.2.4 The Impact of Customer Engagement on Behavioural Intention of Loyalty ... 196

5.2.5 How the Individual’s Experiential Needs Moderate Event Engagement ......... 197

5.2.6 Updated Study Framework ............................................................................... 198

5.3 Contributions to the Academic Discipline ............................................................... 199

5.4 Managerial Implications .......................................................................................... 203

5.5 Limitations of the Research ..................................................................................... 205

5.6 Directions for Future Research ................................................................................ 207

5.7 Concluding Thoughts ............................................................................................... 210

APPENDICES ................................................................................................................... 212

REFERENCES .................................................................................................................. 220

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LIST OF FIGURES

Figure 1-1: Theoretical Framework ....................................................................................... 5 Figure 2-1: Conceptual Framework ..................................................................................... 76 Figure 3-1: Measurement Model - Cognitive Experience ................................................. 114 Figure 3-2: Measurement Model - Emotional Experience ................................................ 115 Figure 3-3: Measurement Model - Sensorial Experience .................................................. 116 Figure 3-4: Measurement Model - Pragmatic Experience ................................................. 116 Figure 3-5: Measurement Model - Relational Experience ................................................. 117 Figure 3-6: Measurement Model - Event Attention ........................................................... 117 Figure 3-7: Measurement Model - Brand Attention .......................................................... 118 Figure 3-8: Measurement Model - Event Identification .................................................... 119 Figure 3-9: Measurement Model - Brand Identification .................................................... 120 Figure 3-10: Measurement Model - Event Enthusiasm ..................................................... 120 Figure 3-11: Measurement Model - Brand Enthusiasm ..................................................... 121 Figure 3-12: Measurement Model - Event Absorption ...................................................... 121 Figure 3-13: Measurement Model - Brand Absorption ..................................................... 122 Figure 3-14: Measurement Model - Event Interaction ...................................................... 122 Figure 3-15: Measurement Model - Brand Interaction ...................................................... 123 Figure 3-16: Measurement Model - Behavioural Intention of Loyalty ............................. 123 Figure 3-17: Measurement Model - Novelty-Seeking ....................................................... 124 Figure 3-18: Measurement Model - Need for Affect ......................................................... 124 Figure 3-19: Measurement Model - Need for Cognition ................................................... 125 Figure 4-1: Measurement Model – Social Event Engagement .......................................... 135 Figure 4-2: Measurement Model - Social Brand Engagement .......................................... 136 Figure 4-3: Measurement Model - Event Engagement ...................................................... 137 Figure 4-4: Measurement Model - Brand Engagement ..................................................... 140 Figure 4-5: Measurement Model - Social Constructs ........................................................ 144 Figure 4-6: Measurement Model - Customer Event Engagement ..................................... 147 Figure 4-7: Measurement Model - Customer Brand Engagement ..................................... 150 Figure 4-8: Identified Path Model ..................................................................................... 160 Figure 4-9: Re-Specified Path Model ................................................................................ 164 Figure 4-10: Path for Low Need for Cognition ................................................................. 178 Figure 4-11: Path Model for High Need for Cognition ..................................................... 179 Figure 4-12: Path Model for Low Need for Affect ............................................................ 181 Figure 4-13: Path Model for High Need for Affect ........................................................... 181 Figure 4-14: Path Model for Low Novelty-Seeking Needs ............................................... 183 Figure 4-15: Path Model for High Novelty-Seeking Needs .............................................. 184 Figure 5-1: Updated Study Framework ............................................................................. 199

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LIST OF TABLES

Table 2-1: Overview of Customer Engagement Literature ................................................. 16 Table 2-2 Antecedents and Outcomes of Customer Engagement ....................................... 27 Table 2-3: Key Features of Marketing Events ..................................................................... 28 Table 2-4: Summary of Marketing Event Definitions ........................................................ 30 Table 2-5: Experiential Components within a BME ........................................................... 38 Table 2-6: Summary of Hypotheses .................................................................................... 74 Table 3-1: Measurement of Constructs ................................................................................ 90 Table 3-2: O-Week Events Profile ....................................................................................... 99 Table 3-3: Winery Participants .......................................................................................... 104 Table 3-4: Respondent Profile for Number of Responses and Age ................................... 105 Table 3-5: Summary of Data Collection Procedures ......................................................... 107 Table 3-6: Testing for Non-Response Bias ........................................................................ 110 Table 3-7: Summary of Indices Used to Assess Model Fit ............................................... 113 Table 3-8: Goodness of Fit Indices for Cognitive Experience .......................................... 114 Table 3-9: Goodness of Fit Indices for Emotional Experience ......................................... 115 Table 3-10: Goodness of Fit Indices for Sensorial Experience ......................................... 116 Table 3-11: Goodness of Fit Indices for Pragmatic Experience ........................................ 116 Table 3-12: Goodness of Fit Indices for Relational Experience ........................................ 117 Table 3-13: Goodness of Fit Indices for Event Attention .................................................. 117 Table 3-14: Goodness of Fit Indices for Brand Attention ................................................. 118 Table 3-15: Goodness of Fit Indices for Event Identification ........................................... 119 Table 3-16: Goodness of Fit Indices for Brand Identification ........................................... 120 Table 3-17: Goodness of Fit Indices for Event Enthusiasm .............................................. 120 Table 3-18: Goodness of Fit Indices for Brand Enthusiasm .............................................. 121 Table 3-19: Goodness of Fit Indices for Event Absorption ............................................... 121 Table 3-20: Goodness of Fit Indices for Brand Absorption .............................................. 122 Table 3-21: Goodness of Fit Indices for Event Interaction ............................................... 122 Table 3-22: Goodness of Fit Indices for Brand Interaction ............................................... 123 Table 3-23: Goodness of Fit Indices for Behavioural Intention of Loyalty ...................... 123 Table 3-24: Goodness of Fit Indices for Novelty-Seeking ................................................ 124 Table 3-25: Goodness of Fit Indices for Need for Affect .................................................. 124 Table 3-26: Goodness of Fit Indices for Need for Cognition ............................................ 125 Table 3-27: Reliability and Validity Indices ...................................................................... 127 Table 3-28: Reliability and Validity of Measurement Model ............................................ 129 Table 3-29: Common Method Bias - Goodness of Fit Indices .......................................... 131 Table 4-1: Social Engagement Items Included and Excluded From Model ...................... 134 Table 4-2: Goodness of Fit Indices - Social Event Engagement ....................................... 135 Table 4-3: Goodness of Fit Indices - Social Brand Engagement ....................................... 136

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Table 4-4: Goodness of Fit Indices - Event Engagement .................................................. 137 Table 4-5: Reliability and Validity – Event Engagement .................................................. 139 Table 4-6: Goodness of Fit Indices - Brand Engagement .................................................. 141 Table 4-7: Reliability and Validity – Brand Engagement ................................................. 142 Table 4-8: Goodness of Fit Indices - Social Constructs .................................................... 144 Table 4-9: Reliability and Validity – Social Constructs .................................................... 145 Table 4-10: Goodness of Fit Indices – Event Engagement ............................................... 148 Table 4-11: Goodness of Fit Indices – Brand Engagement ............................................... 150 Table 4-12: Summary of Hypothesis 1 .............................................................................. 151 Table 4-13: Factor Loadings and Error Variances for Composite Variables .................... 157 Table 4-14: Goodness of Fit Indices for Identified Path Model ........................................ 160 Table 4-15: Regression Weights – Original Path Model ................................................... 161 Table 4-16: Goodness of Fit Indices for Re-Specified Path Model ................................... 164 Table 4-17: Regression Weights: - Re-Specified Path Model ........................................... 165 Table 4-18: Summary of Hypothesis 2 .............................................................................. 166 Table 4-19: Summary of Hypothesis 3 .............................................................................. 172 Table 4-20: Summary of Hypothesis 4 .............................................................................. 173 Table 4-21: Experiential Needs Groups - Value Classification ......................................... 177 Table 4-22: Nested Model Comparisons and Goodness of Fit Indices - Need For Cognition ...... 179 Table 4-23: Need for Cognition ......................................................................................... 180 Table 4-24: Nested Model Comparisons and Goodness of Fit Indices - Need for Affect ........... 182 Table 4-25: Need for Affect ............................................................................................... 182 Table 4-26: Nested Model Comparisons and Goodness of Fit Indices - Novelty-Seeking Needs .... 184 Table 4-27: Novelty-Seeking Needs .................................................................................. 185 Table 4-28: Summary of Hypothesis 5 .............................................................................. 186

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DECLARATION

I certify that this work contains no material which has been accepted

for the award of any other degree or diploma in my name, in any

university or other tertiary institution and, to the best of my

knowledge and belief, contains no material previously published or

written by another person, except where due reference has been made

in the text. In addition, I certify that no part of this work will, in the

future, be used in a submission in my name, for any other degree or

diploma in any university or other tertiary institution without the prior

approval of the University of Adelaide and where applicable, any

partner institution responsible for the joint-award of this degree.

I give consent to this copy of my thesis when deposited in the

University Library, being made available for loan and photocopying,

subject to the provisions of the Copyright Act 1968.

The author acknowledges that copyright of published works

contained within this thesis resides with the copyright holder(s) of

those works.

I also give permission for the digital version of my thesis to be made

available on the web, via the University’s digital research repository,

the Library Search and also through web search engines, unless

permission has been granted by the University to restrict access for a

period of time.

Signed: ___________________________________

Date: November 28, 2014

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PUBLICATIONS

The following publications are based upon the research presented in this thesis, and may

contain results and materials presented herein.

Altschwager, T., Goodman, S., Conduit, J., Habel, C. “Branded Marketing Events: a Proposed ‘Experiential Needs’ based Conceptual Framework” (forthcoming) Event Management: an International Journal (accepted May 2014)

Altschwager, T., Conduit, J., Bouzdine-Chameeva, T., Goodman, S. “A comparison of Wine Event Experiences in France and Australia” (under review) Journal of Travel Research

Altschwager, T., Conduit, J., Goodman, S. (2014) “Dinner or Music: Which Events Enhance Customer Brand Engagement?” Australian and New Zealand Marketing Academy Conference, Brisbane Australia

Altschwager, T., Conduit, J., Bouzdine-Chameeva, T., Goodman, S. (2014) “Customer Engagement: a Comparison between Australian and French Wine Events” International Conference of the Academy of Wine Business Research, Geisenheim, Germany * Best paper award

Altschwager, T., Conduit, J., Goodman, S. (2014) “Wine events: a way to engage customers?” Wine and Viticulture Journal (forthcoming November-December issue)

Altschwager, T., Conduit, J., and Goodman, S. (2013) “Facilitating Engagement by Aligning Brand Marketing Events and Customer Experimental Needs” Australian and New Zealand Marketing Academy Conference, Auckland New Zealand

Altschwager, T., Conduit, J., Goodman, S. (2013) “Branded Marketing Events: Facilitating Customer Engagement” International Conference of the Academy of Wine Business Research, St Catharines Canada

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ACKNOWLEDGMENTS

My PhD journey would not have been possible without the support of many people.

First, I wish to thank my supervisors, Dr. Steve Goodman and Dr. Jodie Conduit for their

support throughout my PhD. Steve’s assistance with approaching industry partners,

research partners, which led to invaluable collaborations with Professor Tatiana Bouzdine-

Chameeva, was greatly appreciated.

Jodie, where do I even start! Thank you for everything. I feel truly honoured to be your

first PhD student to completion; you are an exceptional supervisor and a wonderful person.

I can never thank you enough for all of your guidance throughout this process.

The people I’ve met throughout this PhD have become my dear friends - thank you all for

being such wonderful support. Zubair Ali Shahid, Rebecca Dolan, Joanne Ho, Hande

Akman and Ervin Sim, your encouragement and friendship have meant the world to me.

Special thanks must also be given to Cibo, for being my second home.

I acknowledge the support of the University of Adelaide, which provided the scholarship

and funding that enabled me to complete my research and attend conferences. I also

acknowledge Ray Adam for his valuable help in proof-reading the abstract, introduction,

literature review and discussion chapters of this thesis.

Last, but by no means least, thank you to my beautiful family. Thank you for believing in

me, even at times when I didn’t believe in myself. To Grace, Sonya, Ruby and Arch for

being my support crew. And finally, to Michael. You are brilliant, and I could not have

done this without you.

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For Grace

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KEY TERMS, DEFINITIONS AND ABBREVIATIONS

The definitions of selected terms are listed to provide clarity and to set certain

terminologies for the context in which they were utilised in this thesis;

Associative network theory: theory that customers retain information about events in

memory; through a process of ‘spreading activation’ certain sets of event-related

information can trigger thoughts about related information, in this case linked

information about the host brand (Smith 2004).

Behavioural intention of loyalty (BIL): word-of-mouth and purchase intention (Zeithaml,

Berry, and Parasuraman 1996).

Branded marketing events (BMEs) : a brand-initiated experience that serves as a

platform for customers to interact with the brand and other actors (definition in this

thesis, page 35).

Customer engagement: “a psychological state that occurs by virtue of interactive, co-

creative customer experiences with a focal agent/object (e.g., a brand) in focal

service relationships” (Brodie et al. 2011a, pg 260). Focal objects investigated in

this thesis are; the event (referred to as customer event engagement) and the brand

(referred to as customer brand engagement).

Customer experience: a customer-centric concept, and encompasses all interactions and

experiences between a customer and brand (Gentile, Spiller, and Noci 2007),

including those outside of regular consumption activity.

Engagement dimensions: This thesis follows a five-dimensional view of customer

engagement; attention, enthusiasm, interaction, identification and absorption (So,

King, and Sparks 2012). (Definitions of each engagement dimension are provided

on pages 22 to 24).

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Event experience: The broader construct of brand experience is considered to encapsulate

event experiences (Brakus, Schmitt, and Zarantonello 2009). Brand experience

includes numerous brand-related stimuli, including branding, communications, as

well as the environments and situations in which the brand is experienced,

including events (Brakus et al. 2009). This thesis focuses on brand-related stimuli

from a BME; therefore, the researcher refers to this as event experience instead of

brand experience.

Experiential components of a BME: the components of a BME utilised in this thesis are

cognitive, emotional, sensorial, pragmatic and relational (Gentile et al. 2007)

Experiential needs: the need that an individual seeks to fulfil through experiences

Experiential needs investigated in this thesis are need for cognition, need for affect

and novelty-seeking needs (definitions of each type of experiential need are

provided on pages 69 to 72).

Optimum stimulation level (OSL) theory: theory that individuals seek out stimulation

from particular environments in order to achieve satisfaction (Steenkamp and

Baumgartner 1992).

Service dominant (S-D) logic: describes the shift in marketing over the past several

decades to a new marketing philosophy that considers “the exchange of intangibles,

specialized skills and knowledge, and processes (doing things for and with)”, with a

view to develop a more comprehensive and inclusive perspective of marketing

thought (Vargo and Lusch 2004, pg 3).

Social engagement: the customer’s heightened level of interest regarding the focus of

engagement (i.e. the event or the brand) based on personal exchanges with other

actors (definition in this thesis, page 46). Focal objects investigated in this thesis

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are; the event (referred to as social event engagement) and the brand (referred to as

social brand engagement).

Social exchange theory: argues that customers engage in activities that provide emotional

rewards including social approval and human contact (Abdul-Ghani, Hyde, and

Marshall 2011).

Theory of consumption values: states that various consumption values perceived by the

customer are focal in explaining consumer choice with regards to purchase (or not

purchase) as well as brand selection (Sheth, Newman, and Gross 1991).

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Introduction Chapter

CHAPTER 1: INTRODUCTION

1.1 Background to the Research

In recent years, business environments have become more dynamic and interactive, with

customers seeking participation through unique experiences with the offerings and

activities of the organisation (Vivek et al. 2012). Customer engagement has emerged as an

important construct that facilitates customer-brand interaction and relationships (Brodie et

al. 2011a), customer loyalty (Bowden 2009) and contributes to a firm’s financial value

(Bijmolt, Leeflang, Block, Eisenbeiss, Hardie, Lemmens, and Saffert 2010; Kumar, Aksoy,

Donkers, Venkatesan, Wiesel, and Tillmanns 2010). As academic interest in customer

engagement continues to grow, research is broadening to explore various methods of

facilitating engagement, both customer- and brand-initiated (Vivek et al. 2012). However,

despite the interest in customer engagement there have been few contributions that focus

on the strategic drivers that facilitate customer engagement.

The focus of this thesis is to investigate branded marketing events (BMEs); a brand-

initiated experience that serves as a platform for customers to interact with the brand and

other actors. Founded in marketing events and customer experience literature, a BME is

interactive in nature, unique to the individual, highly experiential and essentially brings the

brand to life (Wohlfeil and Whelan 2006). The characteristics of these events are

conducive to engendering a psychological state of customer engagement with the brand

(Brodie, Ilic, Juric, and Hollebeek 2011b), and are expected to enhance behavioural

intention of loyalty toward the brand (So et al. 2012).

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1.2 Research Problem and Propositions

The central purpose of this thesis is to explore how BME experiences facilitate customer

engagement. The primary research problem addressed in this thesis is:

How do BME experiences impact customer engagement, and what impact does

this have on behavioural intention of loyalty? How does the individual’s

experiential needs moderate a BME’s impact on customer engagement?

This research problem is further articulated in this thesis through the examination of

customer engagement, marketing events and customer experience literature. It is argued

that conceptually, customers engage with the event itself and through this engagement with

the event their engagement transfers to the brand. An individual’s experiential needs

moderate this process in that the fulfilment of experiential needs strengthens the

relationship between BME experiential components and customer event engagement. In

developing the conceptual framework (Figure 1-1, and is discussed in Chapter 2), five

research questions are identified. These research questions are established in Chapter 2 and

frame the development of hypotheses which are empirically investigated in Chapter 4. The

five research questions addressed in this thesis are:

SUMMARY OF RESEARCH QUESTIONS: 1. What is the role of social engagement within the overall customer engagement construct?

2. How do the experiential components of a BME facilitate customer engagement?

3. What is the relationship between the engagement with two focal objects; customer event

engagement and customer brand engagement?

4. What impact does customer engagement have on behavioural intention of loyalty?

5. Does an individual's experiential needs moderate the relationship between BME experiences and

customer event engagement?

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1.3 Justification for the Research

Service-dominant (S-D) logic has changed the way marketing researchers think and

approach interactions with customers (Vargo and Lusch 2004). Customers are no longer

satisfied with passive communication with brands; they want to interact, customise, and

drive their own brand experiences (Vivek et al. 2012). It is the brand’s duty to provide a

platform for interaction and customer engagement to occur. A branded marketing event is

an effective means of facilitating customer engagement as it is completely interactive and

subjective in nature, whereby the perceived value is determined by the individual. Previous

marketing event studies have investigated event effectiveness (Weihe, Mau, and Silberer

2006; Whelan and Wohlfeil 2006); however, research in this area is yet to investigate

ability of events to facilitate customer engagement.

This thesis contributes to the overall understanding of customer engagement and the

interplay between engagement objects (the event and the brand). A general lack of

empirical quantitative enquiry into customer engagement is observed in Table 2-1 (Chapter

2). Further quantitative research, including this thesis, is required to contribute to the

empirical justification of customer engagement operationalisation and its brand-related

outcomes. Research in customer engagement, as a relatively new body of literature, is

starting to build with regards to understanding the various antecedents and outcomes of

customer engagement (Fehrer, Woratschek, and Germelmann 2013); however, research

does not yet investigate the strategic use of events to drive customer engagement.

This thesis makes several key contributions to theory and literature. First, it contributes to

the understanding of facilitating customer engagement through the effective platform of

BMEs. Various components of a BME experience are identified from customer experience

literature (Gentile et al. 2007), and used to investigate the relationship between BME

experience and customer engagement. These relationships are supported by social

exchange theory (Möller 2013; Saks 2006), as resources are contributed by the brand and 3 | P a g e


the customer for mutual benefit; the brand provides a platform (BMEs) through which

unique and memorable experiences occur, and the customer in turn contributes through

their engagement with the event and with the brand. Social exchange theory also supports

the existence of a social dimension of customer engagement (Abdul-Ghani et al. 2011),

which is also explored in this thesis.

Second, this thesis explores the interplay between two engagement objects; customer event

engagement and customer brand engagement. Using associative network theory (Smith

2004), this thesis postulates that customer engagement experienced with the event can also

replicate onto the associated brand, thus facilitating customer brand engagement. Extant

literature on customer engagement to date does not explore multiple focal engagement

objects simultaneously. However, this relationship is important to understand as it is

becoming more common for brands to initiate experiences with customers that extend

beyond normal service interactions (for example, BMEs); in this situation it is unclear

whether the brand receives any benefit for undertaking such interactions.

S-D logic recognises that value is uniquely created and determined by the individual

(Vargo and Lusch 2008). Therefore, an understanding of the individuals’ needs within the

scope of BMEs is important to gauge a comprehensive understanding of how customer

engagement is facilitated during BMEs. Specifically, the moderation of experiential needs

in the relationship between BME experiential components and customer event engagement

is examined. Optimum stimulation level theory (Steenkamp and Baumgartner 1992) guides

the hypotheses presented in this thesis, arguing that the relationship between customer

event engagement and BME experiences is enhanced when the individual’s experiential

needs are satisfied during the BME. Customer engagement literature recognises that the

individuals’ needs can moderate the level of customer engagement facilitated (Brodie et al.

2011a), but currently has not explored this moderation effect.

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The theoretical framework in Figure 1-1 highlights the focal constructs of interest and

presents them together to depict their relationships. A more detailed explanation and

theoretical justification for each of the hypothesised relationships is discussed in Chapter 2

and is presented in a conceptual framework, Figure 2-1.

FIGURE 1-1: THEORETICAL FRAMEWORK

1.4 Research Context

The research context of this thesis is wine-related BMEs held in the South Australian wine

industry. The Australian wine industry is dominated by a small number of large wine

brands, with over two thousand small wineries competing for the remaining market

(Winetitles 2013). Customer engagement through event experiences is therefore an

important strategy for wine brands to differentiate and create closer connections with their

customers.

Wine marketing studies recognise the impact of events and customer experience in the

wine industry (Hoffman, Beverland, and Rasmussen 2001; Pikkemaat, Peters, Boksberger,

and Secco 2009). Wine brands already host events and implement other activities to create

customer experience and engage customers (Barth 2007). However, the wine industry

context receives little attention in customer engagement literature (Hollebeek 2010).

Research has indicated that the individual’s hedonic attitudes tend to impact their

attendance of special events more so than utilitarian drivers (Gursoy, Spangenberg, and

Rutherford 2006). Wine consumption is considered a primarily hedonic experience

5 | P a g e


(O'Neill and Charters 2000), related with leisurely activity and lifestyle (Jingxue,

Morrison, Cai, and Linton 2008) and therefore is deemed an appropriate context in which

to conduct the study for this thesis.

Research on similar hedonic experiences (e.g. in tourism) have started to recognise and

adopt customer engagement strategies (So, King, Sparks, and Wang 2014). Therefore, the

wine industry provides a context in which a diverse range of events are available for

investigation in this thesis, where unique and memorable customer experiences are

anticipated, and where the individual’s experiential needs are expected to moderate the

impact of these experiences on customer engagement.

1.5 Research Method

This section provides an overview of the research method adopted in this thesis. A detailed

description and justification of the procedures is discussed in Chapter 3.

A deductive, quantitative research approach is taken in this thesis to investigate causal

relationships between theoretically developed constructs. An online questionnaire is

developed and pre-tested in the University sector and the main study is conducted in the

South Australian wine industry. The researcher attended many of the events to seek the

participation of event attendees; willing participants provided their email address and were

sent the online questionnaire. For a small number of events the participating wineries

emailed the survey link to attendees on the researcher’s behalf.

Existing scales are selected to capture each of the constructs within the conceptual model,

and minor modifications made to wording when required to ensure their applicability to the

context. Items are assessed in the pre-test analysis for construct validity and reliability;

poor-fitting items are excluded from the main study to shorten the survey length.

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Data analysis is conducted using SPSS 21 and AMOS 21, and structural equation

modelling (SEM) employed. Each latent construct and associated measured variables are

tested for construct validity and reliability using various measurement models before

structural models and path models are assessed. Composite measures are calculated to

enable complex models to be investigated with sample size constraints. Multi-group

analysis is conducted to identify the effects of moderators on each of the paths within the

model.

1.6 Delimitation and Scope of the Thesis

The managerial implications, limitations and future directions topics are discussed in

Chapter 5, and attest that the relationships identified in this thesis cannot be generalised

beyond the scope of this thesis. Further examination of the relationships among the key

constructs is recommended in various industry settings.

The scope of this thesis is limited to wine-related BMEs held in the South Australian wine

industry. The findings of this thesis are relevant for related fields, particularly where the

host brand or industry is primarily hedonic. However, further research is required to

extrapolate these relationships in the context of unrelated fields, for example for utilitarian

brands and products.

Data collection for this thesis was limited to South Australia. A broader national study

would have captured a greater variety of wine regions. However, while wine regions in

Australia carry some importance, the customer has been found to associate predominantly

with the individual wine brand (Rasmussen and Lockshin 1999). Therefore, data collection in

the main South Australian wine regions are not believed to be of detriment to the

generalisability of the findings in reflecting the broader Australian population.

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In addition, the location-based boundaries imposed on this research mean that cultural

influences cannot be identified. This is particularly relevant to the wine industry, where

consumer wine culture is anticipated to impact customer behaviours, outcomes and

perceptions related to the wine industry (Overby, Gardial, and Woodruff 2004). Therefore,

research replicating these relationships is advised in the specific country of interest to

account for cultural differences, particularly in ‘old world’ wine countries (e.g. France) as

Australia is considered a ‘new world’ wine country (O'Neill, Palmer, and Charters 2002).

Furthermore, this thesis specifically investigates customer experience and engagement

within the platform of the event, and does not account for the various experiences and

interactions between the customer and brand beyond the BME. There is confusion in the

use of the term ‘experience’; experience can describe knowledge or expertise in retrospect

(for example I have experience in this topic) whereas an experience refers to living

through, undertaking or facing a specific event (Palmer 2010). The parameters of ‘the

experience’ in this thesis reflect the duration of the event; however, it is recognised that a

customer’s overall ‘experience’ (from a cumulative perspective) with a brand can extend

beyond this one event experience and cannot be controlled.

Finally, although other notions such as customer orientation, customer management and

relationship marketing are relevant and often drawn on in discussing customer

engagement, they are emergent from the perspective of Goods-Dominant logic; S-D logic

has progressed these ideas with a greater emphasis on the customer’s central role in value

creation (Vargo and Lusch 2008). The various theoretical frameworks grounding customer

engagement is a likely cause of the varying perspectives that researchers in the area have

on the customer engagement construct; in particular the various definitions of customer

engagement and perspectives of customer engagement as either a behaviour or a

psychological mindset. Therefore, this thesis has set a demarcation of the research area and

follows the S-D logic perspective throughout.

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1.7 Outline of the Thesis

The structure of this thesis follows the five chapter approach in Perry (1998); each chapter

is briefly outlined below.

CHAPTER 1 provides an introduction and background to this thesis. This chapter briefly

describes the research problem and subsequent propositions, justification for the research,

and outlines the scope and delimitations of this thesis.

CHAPTER 2 reviews the literature regarding customer engagement, marketing events and

customer experience, and outlines the theoretical underpinning of the relevant research

propositions and hypotheses. The emergence of customer engagement and its theoretical

foundation in S-D logic is discussed. A review of marketing events and customer

experience literature is undertaken to demonstrate the applicability of BMEs in facilitating

customer engagement and to outline the experiential components of a BME. The

behavioural intention of loyalty toward the brand is discussed and its outcomes from

customer event engagement and customer brand engagement explored. Finally, this chapter

discusses the moderator variables that potentially influence the relationships between the

experiential components of BMEs and customer event engagement. Chapter 2 concludes

with a summary and justification of hypotheses and a conceptual framework that is

empirically tested in the following chapters.

CHAPTER 3 describes the research method used to establish the relationships among the

key constructs. Details concerning sample size, data collection procedures, and

questionnaire design are presented and justified. This chapter has a focus on the

measurement constructs, and provides information regarding the operationalisation of the

constructs. The pre-test data analysis is described and changes to the final questionnaire are

identified. This chapter concludes with an examination of the construct validity and

reliability of the measures used in the main study.

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CHAPTER 4 addresses the main propositions and hypotheses of this thesis. Social

customer engagement constructs are examined with reference to the event and the brand,

and are tested for their applicability as an additional independent dimension of customer

engagement. Path model analysis investigates the influence of the BME experiential

component antecedents to customer engagement, the relationship between customer event

engagement and customer brand engagement, and the outcome of behavioural intention of

loyalty. Finally, this chapter demonstrates the multi-group analysis used to investigate the

moderation of experiential needs in the relationship between the experiential components

of a BME and customer event engagement.

CHAPTER 5 integrates the key findings from the literature review and results chapters. It

identifies the contributions to academic knowledge and managerial implications. This

chapter concludes with the study limitations and directions for future research.

1.8 Chapter 1 Summary

This chapter laid the foundations for this thesis. It introduced the research problem,

research questions and hypotheses. Then the research was justified, the method was briefly

described and justified, the thesis was outlined, and the delimitations and scope were

given. On these foundations, the thesis can proceed with a detailed description of the

research. The next chapter presents a summary of extant literature, mainly in the research

areas of customer experience, marketing events and customer experience.

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Literature Review Chapter

CHAPTER 2: LITERATURE REVIEW

2.1 Chapter 2 Introduction

Engagement refers to a psychological mindset that occurs through interactive experiences

between engagement subjects and objects (Brodie et al. 2011a; Hollebeek 2011a).

Engagement is a term commonly used in industry and academe, and it is investigated in

various research areas including sociology, political science, psychology, and

organisational behaviour (Brodie et al. 2011a). However, this concept has only recently

been adopted in the marketing discipline (Vivek et al. 2012). “Customer Engagement” as a

concept has emerged as a popular research area due to the changing perspective of

customer-company relationships, as evidenced by the shift first to relationship marketing,

and more recently to service-dominant (S-D) logic. Focal to the S-D logic perspective is

the notion that marketing is customer-centric; this extends beyond customer orientation to

include collaboration, learning, and adapting to each customer and their dynamic needs

(Vargo and Lusch 2004). This perspective provides insights about the customer not

previously recognised, namely that there are far greater outcomes for companies who do

not just communicate ‘one-way’ to customers, but instead communicate interactively with

customers and recognise that those customers uniquely perceive value (Vargo and Lusch

2008).

For the past decade, the concept of customer engagement has been a key research priority

of the Marketing Science Institute; first appearing in the 2006-2008 Research Priorities to

establish a greater understanding of engagement (MSI 2006), it was again listed in 2010-

2012 to encourage further conceptual development (MSI 2010). The 2014-2016 report

places “the understanding of customers and customer experience” as a Tier 1 Research

Priority, calling for further conceptual development, measurement, and a broader

investigation of the various marketing activities that may create engagement (MSI 2014).

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Customer engagement has also strongly emerged as a concept of practitioner interest and

this is reflected in the abundance of engagement articles in Harvard Business Review (e.g.

Koehn 2011; Wang 2012), the Gallup Business Journal (e.g. O'Boyle and Fleming 2014;

Sorenson and Adkins 2014) and the Economist (e.g. Voyles 2007), as well as industry

conferences (e.g. the Annual Summit on Customer Engagement 2014). In recent years,

business environments have become more dynamic and interactive, with customers

seeking participation through unique experiences with the offerings and activities of the

organisation (Vivek et al. 2012).

This literature review focuses on the conceptual domain of customer engagement and

demonstrates the ability of customer experience to facilitate customer engagement.

Research to date has predominantly focused on creating a common understanding of the

definition of customer engagement, dimensions that capture the construct, and how to

distinguish customer engagement from related concepts, particularly involvement (Brodie

et al. 2011b). As common conceptualisations emerge, new research needs to shift its focus

to empirical enquiry and further understanding of how customer engagement is facilitated

through different platforms and in different contexts. This thesis explores customer

engagement from a strategic standpoint, identifies the brand-provided resources within an

event experience and investigates which experiences customers choose to engage with.

Therefore, the literature on customer experience and marketing events is consulted to

examine in detail the components of experience that facilitate customer engagement.

Current literature considers customer engagement with a focal object, but there is little

acknowledgement of the multiple factors within a service system with which a customer

engages. This thesis considers customer engagement with both the event and the brand,

and argues that the focal direction of the engagement can project from the event to the

brand using associative network theory. In addition, this thesis contributes to the debate of

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whether social engagement is an independent dimension of customer engagement with

reference to social exchange theory.

Finally, with the understanding that customers uniquely create and interpret value, this

thesis investigates the role that an individual’s experiential needs play in the facilitation of

customer engagement within an event experience. The moderating effect of the consumers’

experiential needs are based on MacInnis and Jaworski’s (1989) categorisation of

consumer needs, as well as related theories including exploratory consumer behaviour.

Customers attending an event are likely to possess varying levels of cognitive needs, a

desire for novelty-seeking or excitement, and/or a need for affect. These needs are likely to

influence how the event is perceived and whether customer engagement is facilitated.

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2.2 Customer Engagement

Engagement is a multidisciplinary concept reflecting a variety of contexts including

employee engagement (Kahn 1990; Saks 2006), student engagement (Kahu 2013; Skinner,

Wellborn, and Connell 1990) and community engagement (Algesheimer, Dholakia, and

Herrmann 2005; Keener 1999). While there are some consistencies in engagement

conceptualisation across the various academic disciplines, for example the existence of

cognitive, emotional and behavioural dimensions of engagement (Kahn 1990; Kahu 2013;

Saks 2006), there are also considerable differences such as focal subjects (‘who’ is

engaging) and objects (with ‘what’ is the subject engaging) (Hollebeek 2011a). An

overview of engagement conceptualisations and studies in the academic disciplines of

sociology, political science, psychology, educational psychology, and organisational

behaviour can be found in Brodie et al. (2011a). While research is gaining momentum in

this area, customer engagement within marketing academe is still a relatively recent

concept (Abdul-Ghani et al. 2011).

2.2.1 Theoretical Foundations of Customer Engagement

The literature on customer engagement in marketing has emerged from the current focus

on service-dominant (S-D) logic. Vargo and Lusch’s (2004, pg 2) seminal paper on S-D

logic describes the shift in marketing over the past several decades from a goods-based

view to a new marketing philosophy that considers “the exchange of intangibles,

specialized skills and knowledge, and processes (doing things for and with)”, with a view

to develop a more comprehensive and inclusive perspective of marketing thought. This

reorientation has implications for how marketers perceive and approach the customer,

exchange processes and markets (Vargo and Lusch 2004). Compared to the more narrow

focus of the ‘goods dominant’ perspective, in which one-way, mass communication was

considered an effective way to ‘market to’ customers (Vargo and Lusch 2004), S-D logic

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considers a more inclusive perspective, with emphasis on the interactive nature of

experiences and co-creative environments (Brodie et al. 2011b). From this perspective, the

brand does not merely provide value, but instead value is unique to each individual and

created with the consumer (Vargo and Lusch 2004).

The S-D logic provides a number of insights relevant to the understanding of customer

engagement. First, customers are co-creators of value (Vargo and Lusch 2014). They do

not passively receive information and value from organisations, but instead create value

that is unique and determined individually (Vargo and Lusch 2014). Therefore, interaction

is a prevalent and necessary construct in customer-company relationships, as customer

interaction will allow them to create value. As a result, companies recognise that rather

than a focus on delivering value, they must focus on providing a platform and resources for

the customer to interact and create value (Vargo and Lusch 2008). The event experience is

the resource provided by the brand that customers draw from to facilitate engagement. This

thesis takes the perspective of S-D logic and considers customer engagement facilitated

during provider-initiated events through this theoretical lens.

2.2.2 Customer Engagement Conceptualisation

Research on customer engagement emphasises its conceptual infancy with regards to

theoretical development (Brodie et al. 2011b) and encourages researchers to focus on the

development of conceptual understanding and identifying the characteristics of the

engagement construct (MSI 2010). While it is not the primary objective of this thesis to

contribute to overall construct definition and development, the fact that the literature on

customer engagement remains focused on the conceptual boundaries of the construct

necessitates a comprehensive overview to establish the theoretical position of this thesis

before introducing contextual elements of the research. Table 2-1 provides a summary of

definitions of customer engagement and related engagement subjects from the literature.

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TABLE 2-1: OVERVIEW OF CUSTOMER ENGAGEMENT LITERATURE

Reference Definition Perspective Dimensions Method

(Higgins and Scholer 2009, pg 102)

“Engagement is a state of being involved, occupied, fully absorbed, or engrossed in something—sustained attention”

Psychological Not stated Conceptual

(Bijmolt et al. 2010, pg 341)

“The behavioral manifestation from a customer toward a brand or a firm which goes beyond purchase behavior”

Behavioural Word of Mouth, Co-creation, Complaining Behaviour

Conceptual

(Hollebeek 2010, pg 3)

“the level of a consumer’s cognitive, emotional and behaviourally‐based motivation in brand interactions”

Psychological Cognitive, Emotional, Behavioural

Conceptual

(Mollen and Wilson 2010, pg 12)

“a cognitive and affective commitment to an active relationship with the brand as personified by the website or other computer-mediated entities designed to communicate brand value”

Psychological Cognitive, Affective

Conceptual

(van Doorn, Lemon, Mittal, Nass, Pick, Pirner, and Verhoef 2010, pg 254)

“a customer’s behavioural manifestations that have a brand or firm focus, beyond purchase, resulting from motivational drivers”

Behavioural Valence, Form/modality, Scope, Nature of impact, Customer goals

Conceptual

(Abdul-Ghani et al. 2011, pg 1060).

“a consumer’s ongoing attention to an object of consumption such as a website or brand”

Psychological Utilitarian, Hedonic, Social

Empirical Qualitative

(Brodie et al. 2011a, pg 260)

“A psychological state that occurs by virtue of interactive, co-creative customer experiences with a focal agent/object (e.g., a brand) in focal service relationships”


Conceptual

(Brodie et al. 2011b, pg 3)

“Consumer engagement in a virtual brand community involves specific interactive experiences between consumers and the brand, and/or other members of the community. Consumer engagement is a context-dependent, psychological state characterized by fluctuating intensity levels that occur within dynamic, iterative engagement processes”



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Reference Definition Perspective Dimensions Method

(Hollebeek 2011b, pg 555)

“the level of a customer’s cognitive, emotional and behavioral investment in specific brand interactions”



(Hollebeek 2011a, pg 790)

“the level of an individual customer’s motivational, brand-related and context-dependent state of mind characterised by specific levels of cognitive, emotional and behavioural activity in direct brand interactions”


Conceptual

(Gambetti, Graffigna, and Biraghi 2012, pg 659)

“A dynamic and process-based concept evolving in intensity on the basis of the brand capability of increasingly intercepting consumers’ desires and expectations using all possible physical and virtual touchpoints between brand and consumers. CBE appears as an overarching marketing concept encapsulating different consumer decision-making dimensions, from brand preference to brand purchase”

Psychological Experiential, Social


(So et al. 2012) Refers to Brodie et al. (2011a) customer engagement definition

Psychological Identification, Attention, Enthusiasm, Absorption, Interaction

Empirical Quantitative

(Vivek et al. 2012, pg 127)

“the intensity of an individual’s participation in and connection with an organization’s offerings and/ or organizational activities, which either the customer or the organization initiate”

Psychological Cognitive, Emotional, Behavioural, Social


(Calder, Isaac, and Malthouse 2013, pg 4)

“a psychological state that occurs by virtue of interactive, co-creative customer experiences with a focal agent/object (e.g. a brand) … under a specific set of context-dependent conditions … and exists as a dynamic, iterative process”

Psychological Social, Intrinsic enjoyment, Utilitarian, Identity, Civic


(Hollebeek, Glynn, and Brodie 2014, pg 1)

“A consumer's positively valenced brand-related cognitive, emotional and behavioral activity during or related to focal consumer/brand interactions”


Empirical Qualitative and Quantitative

(Taheri, Jafari, and O'Gorman 2014, pg 321)

“involvement with and commitment to a consumption experience”



(So et al. 2014, pg 2)

“A customer’s personal connection to a brand as manifested in cognitive, affective, and behavioural responses outside of the purchase”

Psychological Identification, Attention, Enthusiasm, Absorption, Interaction


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2.2.2.1 Different Perspectives of Customer Engagement

The overview of customer engagement and other relevant engagement subject studies

listed in Table 2-1 shows an inconsistency in the conceptualisation of engagement,

particularly with reference to distinguishing engagement from involvement (Higgins and

Scholer 2009) or attention (Abdul-Ghani et al. 2011). This necessitates an emphasis

regarding the definition and conceptualisation of customer engagement in order to clarify

its meaning in this thesis.

Two perspectives of customer engagement conceptualisation have emerged from recent

studies and are highlighted in Table 2-1; customer engagement as a behaviour (Bijmolt et

al. 2010; van Doorn et al. 2010; Verhoef, Reinartz, and Krafft 2010), and customer

engagement as a psychological mindset. The latter is multidimensional in nature and

includes a behavioural dimension (Brodie et al. 2011a; Calder et al. 2013; Gambetti et al.

2012; Hollebeek 2011a; So et al. 2012; Vivek et al. 2012). While the behavioural

dimension is pivotal to the overall customer engagement construct and is the most easily

observable manifestation of engagement for researchers, this dimension in isolation does

not entirely explain whether the customer is truly engaged (So et al. 2012). The

behavioural dimension of customer engagement is only one element of engagement and

does not explain the intention or motivation causing the behaviour (So et al. 2012), making

engagement indistinguishable from constructs such as participation (Brodie et al. 2011a).

The notion of customer engagement as a psychological mindset considered from a

multidimensional perspective allows this thesis to capture the complexity of the construct

(So et al. 2012) and therefore is utilised to ensure a comprehensive depiction of customer

engagement.

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2.2.2.2 Definition of Customer Engagement

This thesis follows the definition provided in Brodie et al.’s (2011a, pg 260) seminal

customer engagement paper, in which customer engagement is defined as “a psychological

state that occurs by virtue of interactive, co-creative customer experiences with a focal

agent/object (e.g., a brand) in focal service relationships”. This particular

conceptualisation is adopted in this thesis as it clearly identifies the interactive nature of

experiences, which distinguishes it from related concepts, including involvement, and

places an emphasis on the customer’s central role in the creation of the experience to

facilitate engagement (Brodie et al. 2011a). In addition, this definition follows the

perspective of customer engagement as a multidimensional psychological mindset (Brodie

et al. 2011a), the approach adopted in this thesis.

A key element of the customer engagement definition is that engagement emerges “from

two-way interactions between relevant engagement subject(s) and object(s)” (Hollebeek

2011a, pg 787). The engagement subject refers to the person who facilitates the

engagement, i.e. customers, while the engagement object identifies to what the person’s

engagement is directed, i.e. the brand (Hollebeek 2011a). Customer engagement has been

described with regards to various engagement objects, for example media, advertising,

entertainment or brands (Abdul-Ghani et al. 2011; Vivek et al. 2012). This thesis extends

current literature as it considers how customer engagement is facilitated with an event and

the associated brand hosting the event (from here referred to as the host brand). This

contribution is further discussed in section 2.4.3.

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2.2.2.3 Dimensions of Customer Engagement

When considering customer engagement from a psychological mindset perspective, it has

been generally conceptualised to incorporate three dimensions; cognitive, emotional and

behavioural engagement (Brodie et al. 2011a; Hollebeek 2011a; Taheri et al. 2014). So, et

al. (2012; 2014) extend this view and propose a five-dimensional conceptualisation;

attention, enthusiasm, interaction, identification and absorption. These elements capture

the commonly accepted tri-dimensional perspective of engagement with the attention

(cognitive), enthusiasm (emotional), and interaction (behavioural) elements, however it

extends this conceptualisation with an additional two dimensions; identification and

absorption. This thesis implements the broader five-dimension conceptualisation of

customer engagement provided by So et al. (2012; 2014) as it is consistent with, and

extends, the discussion of customer engagement. The context in which the So et al. (2012)

measure has been utilised, engagement with tourism brands is closely aligned with the

context of this thesis.

Attention represents a “consumer’s attentiveness and focus on the brand” (So et al. 2012,

pg 6). This definition is consistent with cognitive engagement, or ‘immersion’, which is the

extent of a consumer’s “brand-related concentration in particular brand interactions”

(Hollebeek 2011b, pg 566) as well as ‘vigour’ or the willingness to invest effort into an

activity (Salanova, Agut, and Peiró 2005). It represents the concentration or cognitive

resources a consumer commits in their interactions with the event or brand (Hollebeek

2011b). Customers with high levels of attention or cognitive engagement have a strong

focus on information related to the event and brand (So et al. 2012).

Enthusiasm “represents an individual’s strong level of excitement and interest regarding

the focus of engagement, such as a brand” (So et al. 2012, pg 5; Vivek et al. 2012). This

definition is consistent with emotional engagement, using the terms ‘passion’ and positive

affection to reflect the extent of a consumer’s “positive brand-related affect in particular

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brand interactions” (Hollebeek 2011b, pg 567). Customers with strong enthusiasm

experience great excitement and emotional connection to the event and brand (So et al.

2012).

Interaction represents the “behavioral manifestation of a consumer’s relationship with the

brand beyond traditional consumptive behavior” (So et al. 2012, pg 7). This is consistent

with behavioural engagement, or ‘activation’, and reflects the extent of a consumer’s

“energy, effort and/or time spent on a brand in particular brand interactions” (Hollebeek

2011b, pg 569). Interaction or behavioural engagement encompasses the active

participation in event or brand-related activities (Mollen and Wilson 2010; So et al. 2012).

Identification is introduced by So et al. (2012), and while they acknowledge that it is

absent from customer engagement research to date, they draw from employee engagement

to argue its applicability to the customer engagement space. Grounded in Social Identity

Theory, identification explains the relationship between customers and specific brands; if

an association with the brand can provide the consumer with a means of conveying self-

expression or self-definition, this will enhance the relationship between the consumer and

the brand (So et al. 2012). Identification in this context is defined as “an individual’s

perceived oneness with or belongingness to an organization, and at the brand level,

identification occurs when the consumer sees his or her self-image as overlapping the

brand’s image” (So et al. 2012, pg 7). This construct is also consistent with Sprott, Czellar

& Spangenberg’s (2009) brand engagement in self-concept construct. Customers with high

levels of identification interact in an event and with a brand, as doing so enhances their

self-image or provides a means of self-expression.

Absorption is a “pleasant state in which the customer is fully concentrated, happy, and

deeply engrossed while playing his role, and an absorbed customer interacting with the

brand or other customers perceives time as passing quickly” (So et al. 2012, pg 6). The

term is often associated with the concept of flow, an optimal experience, and is described

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using terms such as engrossment, intrinsic enjoyment, or effortless concentration

(Csikzentmihaly 1990). The concept of flow is also discussed in the marketing events

literature (Drengner, Gaus, and Jahn 2008), and is often associated with emotional

elements of the experience. As this thesis investigates customer engagement during events,

the inclusion of absorption as an engagement dimension is appropriate for this context.

Absorption is considered in this thesis as an extremely high level of enthusiasm or

emotional engagement, containing the additional characteristics of engrossment in the

experience and losing sense of time (So et al. 2012; Vivek et al. 2012).

2.2.2.4 What Customer Engagement is not: Related Concepts

Important to the conceptualisation of customer engagement is to establish its unique

qualities that distinguish it from related concepts. This has been strongly emphasised in

previous research, with a particular focus on differentiating engagement from involvement

(Brodie et al. 2011b). This need has arisen from various misconceptions of engagement.

For example, Abdul-Ghani et al. (2011) demonstrate confusion of involvement and

engagement, using the term involvement as the cognitive motivation towards a product

category, versus engagement as the affective or emotional associations with a market

offering. This perspective is inconsistent with other engagement research, which argues

that the engagement construct includes cognitive, emotional and behavioural elements

(Brodie et al. 2011a). Therefore, this literature review provides an overview of the

conceptual differences to distinguish customer engagement from a number of related

concepts. First, customer engagement is differentiated from related but clearly distinct

constructs including involvement, brand experience and satisfaction. Second, overlapping

constructs which contribute to the understanding of engagement but are not exhaustive,

including participation, interactivity, commitment, flow, identification and loyalty are

addressed.

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The difference between involvement and engagement is argued extensively throughout

customer engagement literature (Bowden 2009; Brodie et al. 2011b; Brodie et al. 2011a;

Mollen and Wilson 2010). The primary characteristic of engagement distinguishing it from

involvement is the emphasis on interaction and therefore the inclusion of a behavioural

dimension of engagement (Brodie et al. 2011b; Hollebeek 2010; Hollebeek 2011a).

Customer engagement is more extensive than involvement; while involvement considers

the relevance or interest a consumer may possess with regards to a brand or other focal

object, engagement requires interaction between the engagement object and subject

(Brodie et al. 2011b).

Commitment is often described as an emotional attachment associated with attitude; “a

customer is considered to be committed when his or her values, self-image, and attitudes

are strongly linked to a specific choice alternative” (Bowden 2009, pg 70). While

commitment encompasses the ‘psychological state’ of engagement, it does not capture the

interactive or actionable/behavioural dimension of engagement. It is also a resultant

concept, and has been recognised as an outcome of engagement (Brodie et al. 2011b).

Brand experience is an internal and behavioural response from an individual resulting

from brand-related stimuli (Brakus et al. 2009). Brand experience does not presume a

motivational state, which distinguishes it from customer engagement (Hollebeek 2011a); it

can include experiences in which the consumer shows little interest or connection with the

brand (Brakus et al. 2009). This thesis takes the perspective that a brand experience is a

context through which customer engagement can be facilitated, but it does not capture the

psychological state that encompasses customer engagement.

Satisfaction is another construct that is often confused with engagement; it is however

distinguishable in that satisfaction is an evaluation process (Calder et al. 2013).

Engagement captures the active interactions and heightened psychological state within a

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particular moment; satisfaction is considered an evaluative or reflective outcome of that

moment (Calder et al. 2013).

Loyalty is a commitment to an organisation exhibited through consistent repeat purchases

despite adverse situational influences or efforts from competitors (Oliver 1999). Loyalty is

considered an outcome that is partially driven or resulting from engagement, and reflects

an enduring outcome rather than a heightened and momentary psychological state

(Bowden 2009; Hollebeek 2011a).

The next series of concepts are considered to partially represent engagement or have

overlapping qualities, however are not exhaustive of engagement. These concepts are

useful in contributing to the overall understanding of engagement, however customer

engagement is considered to be a broader and more encapsulating construct that recognises

and considers the complex and multifaceted nature of the experience.

Flow has been previously described as a distinct construct to engagement (Mollen and

Wilson 2010), however the five-dimensional perspective of customer engagement adopted

and empirically supported by So et al. (2012) incorporates the dimension of ‘absorption’,

which captures a psychological state similar to the notion of flow. While Mollen and

Wilson (2010) claim that flow is passive, and therefore distinct from engagement, it is

argued in this thesis that a state of flow is a highly active construct, to such an extent that

customers lose sense of everything else outside of that experience. Discussion of a flow

state uses words including ‘engrossed’, and a state of ‘optimal experience’ (So et al. 2012).

Customers in a state of flow display complete concentration, a feeling that the activity they

are participating in is all-encompassing; it is a highly enjoyable psychological state in

which the consumer feels engrossed in the activity causing them to lose sense of time,

however still feel in control of the activity (Drengner et al. 2008). This thesis takes the

perspective that flow is an active consumer psychological state and hence contributes to

the overall customer engagement construct. While the concept of flow is a heightened state

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and is associated with emotional elements of the experience (Drengner et al. 2008), it is not

an absolute indicator of customer engagement. It can, however, be included as a key

element of the construct.

While the previous concepts encapsulate the psychological aspects of engagement without

reference to active participation, the constructs of interactivity and participation

demonstrate this overlap in reverse, capturing the behavioural manifestations without

consideration of the purpose or intent behind those actions. Mollen and Wilson (2010, pg

10) argue that “engagement differs from simple interactivity because it must include

creative, purposeful activity”. Interactivity has therefore been considered an antecedent to

engagement (Hollebeek 2011a), or one dimension of the engagement construct (So et al.

2012). The perspective taken in this thesis is that interactivity is one dimension of

customer engagement; interaction is a focal element of engagement, as evidenced by the

consistent reference to interaction in customer engagement definitions (Brodie et al. 2011a;

Calder et al. 2013; Hollebeek et al. 2014; So et al. 2012). ‘Interaction’ is commonly used

as the distinguishing characteristic between engagement and other related concepts,

including involvement (Brodie et al. 2011b; Hollebeek 2010; Hollebeek 2011a). However,

customer engagement is a multidimensional construct (Brodie et al. 2011a; So et al. 2012)

and must therefore consider interaction as one dimension to be utilised in combination with

other dimensions to gain a comprehensive view of engagement.

Participation is a similar construct to interactivity and is defined as “the degree to which

customers produce and deliver service” (Brodie et al. 2011a, pg 261). Both definitions

imply action between the customer and the company, but do not capture the intention or

motivation driving these actions, and hence do not encapsulate the full notion of customer

engagement.

In summary, numerous variables have been confused with customer engagement due to the

relatively underdeveloped literature investigating it. Many of these concepts have now

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been distinguished from customer engagement, but careful delineation is still required from

researchers to ensure accurate and consistent understanding. One cause of confusion is the

misconception of customer engagement relative to its antecedents and outcomes. Common

antecedents and outcomes identified in customer engagement literature are now

highlighted.

2.2.2.5 Antecedents and Outcomes of Customer Engagement

As research on customer engagement expands, an emphasis on further conceptual

development including the investigation of the various antecedents that create engagement

is required (MSI 2014). Therefore, it is necessary to understand the various antecedents

and outcomes of customer engagement identified in extant literature, and contribute to the

understanding of engagement by investigating currently unexplored variables that are

likely to drive customer engagement.

Numerous antecedents and outcomes of customer engagement have been proposed in

previous research. Fehrer et al. (2013) provide an overview of the various antecedents and

outcomes through a systematic review of customer engagement literature. A summary of

antecedents and outcomes of customer engagement are shown in Table 2-2. Constructs are

categorised into three main groups; (i) identified antecedents of customer engagement

(identification, identity, hedonism), (ii) identified outcomes of customer engagement

(loyalty, customer value, word of mouth, product innovation), and (iii) constructs that have

been considered as either antecedents or outcomes, depending on the study context

(participation, satisfaction, trust, involvement, commitment and interaction) (Fehrer et al.

2013). This overview highlights that there is ambiguity in the customer engagement

literature with regards to whether constructs are considered antecedents or outcomes. In

addition, the overview demonstrates a narrow focus of constructs that largely capture

‘personal states of being’; very few papers investigate the strategic facilitation of customer

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engagement. This is an important connection to make in customer engagement research, as

new platforms or activities that facilitate customer engagement require further exploration.

TABLE 2-2: ANTECEDENTS AND OUTCOMES OF CUSTOMER ENGAGEMENT

Antecedents

Cus

tom

er E

ngag

emen

t

Outcomes

Identification Loyalty

Identity Customer value

Hedonism Word of mouth

Product innovation

Satisfaction Satisfaction

Trust Trust

Commitment Commitment

Involvement Involvement

Interaction Interaction

Table based on Fehrer et al. (2013)

Few studies have investigated customer experience as an antecedent of customer

engagement. So et al. (2012) consider brand experience as an outcome of customer

engagement; however, these authors adopt a different perspective of the term experience.

Experience can be described as knowledge or expertise in retrospect (for example, I have

experience in this topic) whereas ‘an experience’ refers to living through, undertaking or

facing a specific event (Palmer 2010). This thesis investigates ‘an experience’, specifically

a provider-initiated event in which the components of experiences are resources provided

by the organisation with which customers can interact, create their own unique value, and

facilitate engagement. A key contribution of this thesis is the investigation of customer

experience created through an engagement platform of BMEs and to identify that this

experience drives customer engagement. The next section explores the literature areas of

marketing events and customer experience to further understand how events drive

customer engagement.

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2.3 Branded Marketing Events

2.3.1 Marketing Events

A marketing event is an innovative tool for creating a customer experience, which has

recently received increased attention from researchers (Drengner et al. 2008; Wood 2009).

Marketing events seek to elicit active interaction between the consumer and the brand

using an experiential approach (Wood 2009). Adopting this view and working to facilitate

positive customer experiences, an environment is created that is conducive to

communicating high volumes of marketing content or messages with the objective of

eliciting favourable consumer responses (Schmitt 1999). Marketing events elicit active

engagement between the customer and the organisation due to their interactive and

experiential nature, and are argued to have a far greater effectiveness than traditional

marketing (Holbrook and Hirschman 1982). Wohlfeil and Whelan (2006) identify four key

features of a marketing event, outlined in Table 2-3.

TABLE 2-3: KEY FEATURES OF MARKETING EVENTS

Experience-orientation As a marketing event is personally experienced by those who attend, the ‘media experience’ is a lot stronger than only passively receiving information

Interactivity Participants can interact both with other participants, as well as brand representatives

Self-initiation Marketing events have the intention of influencing customers on an emotional level, and thus can affect the emotional associations the consumer has with the brand

Dramaturgy An event acts as a ‘dramatization’ of the company’s brand image; it brings the brand image to life

Source: (Wohlfeil and Whelan 2006, pp 645-646)

The key features of marketing events, in particular interactivity and self-initiation parallel

central elements of S-D logic and support the proposition that a marketing event can elicit

customer engagement, as the individual drives active experiences (Brodie et al. 2011a). It

is commonly understood in this literature space that the consumer drives the event

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experience and has control over whether they chose to interact during an event and the

nature of that interaction (Close, Finney, Lacey, and Sneath 2006). Organisations provide

the event platform to initiate active customer engagement, with the objective of creating

value, developing an emotional connection and encouraging loyalty (Crowther 2011).

Despite the recognition of ‘customer-initiated experiences’ echoed in marketing events

studies, little research in this area explicitly refers to the customer engagement literature. A

number of marketing events papers incorporate the word engagement in the title (e.g.

Close et al. 2006; Whelan and Wohlfeil 2006); however these articles do not define or

conceptualise the engagement construct. It is the intent of this thesis to further develop the

marketing events literature and bridge the gap in knowledge between event experience and


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2.3.1.1 Defining Marketing Events

Table 2-4 provides a summary of definitions provided in the literature of marketing events.

While the applicability of marketing events within customer engagement literature is

evident, there is still a disconnect in terms of the language used or emphasis given to

particular elements of the marketing event experience.

TABLE 2-4: SUMMARY OF MARKETING EVENT DEFINITIONS

Reference Definition

(Gupta 2003) “occurrences designed to communicate particular messages to target audiences”

(Sneath, Finney, and Close 2005, pg 374)

“A variety of activities including ‘the marketing of events and marketing with events’. The marketing of an event is not related to sponsorship, whereas marketing with events entails the promotion of sponsors through the sponsorship vehicle”

(Close et al. 2006)

“the practice of promoting the interests of an organization and its brands by associating the organization with a specific activity”

(Weihe et al. 2006, pg 202)

“Marketing-events are used as a channel to communicate a brand and as a platform for a unique presentation of a brand”

(Whelan and Wohlfeil 2006, pg 327)

“Brand-related hyperrealities whereby the brand message is turned into a ‘real-lived’ multisensual brand experience, resulting in a strengthened emotional attachment to the brand. Event-marketing also facilitates voluntary dialogue and interaction between highly targeted participants”

(Drengner et al. 2008, pg 138)

“a communication tool whose purpose is to disseminate a company’s marketing messages by involving the target groups in experiential activities”

(Getz 2008, pg 404)

“a spatial-temporal phenomenon, and each is unique because of interactions among the setting, people, and management systems – including design elements and the program”

(Wood 2009, pg 248)

“any event that helps market a product/service, idea place or person; any event that communicates with a target audience; any event which has the potential to communicate”

(Crowther 2010, pg 371)

“A grouping that comprises a wide and rich variety of event types, termed ‘marketing event platforms’.... Each individual occasion is expressed as an ‘episode’, with organisations likely to engage in a number of 'marketing event episodes' over a given time period to achieve different objectives”

(Leischnig, Schwertfeger, and Geigenmueller 2011, pg 621)

“A communication instrument whose purpose is to promote the interests of a company and its brands by associating the company with a specific activity. Events are characterized by three aspects: (1) events are typically offered on a discrete or intermittent basis; (2) events allow companies face-to-face contact with their target audience by actively engaging customers with the company and the brand; (3) events are primarily based on entertainment and thus creative exciting and pleasant experiences”

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Three points of interest regarding marketing event definitions emerge from Table 2-4.

First, there is confusion in the literature between marketing events and sponsorship (Sneath

et al. 2005). While sponsorship is often considered to be a type of marketing event, their

inclusion is debated on the basis that these events exist for some other purpose but are used

later for marketing, and sponsorship agreements generally lack control over event

operations (Wood 2009). Second, these definitions indicate the high level of interaction

that occurs through the platform of marketing events (Getz 2008; Whelan and Wohlfeil

2006). As a result, each event is unique due to the interactions of the customers with each

other and with the event (Getz 2008). Marketing events therefore have the capacity to

facilitate customer engagement, as interaction and unique experience are central elements

of customer engagement (Brodie et al. 2011a). Third, a dated lexicon is generally used in

marketing event definitions reflecting a goods-dominant logic as opposed to S-D logic. For

example, terms including a communication tool/instrument (Drengner et al. 2008;

Leischnig et al. 2011) that promotes/communicates to customers (Close et al. 2006; Gupta

2003) imply one-way communication to customers, which is conflict to the unique

interactions emphasised in S-D logic (Vargo and Lusch 2004).

In the next section, these points are used to discuss the conceptualisation and redefinition

of a branded marketing event.

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2.3.2 Conceptualisation of Marketing Events

There is considerable debate among scholars regarding the conceptualisation and definition

of marketing events (Close et al. 2006; Drengner et al. 2008; Wohlfeil and Whelan 2006;

Wood 2009). A sponsorship agreement entitles the sponsoring brand to associate with an

event (Drengner et al. 2008); the sponsorship event is not created for the purpose of

communicating brand information or facilitation of customer-brand interaction. Due to this

lack of emphasis and the focus on the event itself, not the sponsor, customers at

sponsorship events may not interact with the brand in the event space (Drengner et al.

2008). In addition, within a sponsorship agreement the sponsoring brand generally lacks

control over event operations and distribution of brand-related information (Drengner et al.

2008; Mau, Weihe, and Silberer 2006). Multiple brands can sponsor the same event to the

detriment of each sponsor as the event becomes cluttered with conflicting brand messages

(Wood 2009). This results in a reduced ability for the event to translate to brand-related

outcomes for the sponsoring brand.

Despite similarities to sponsorship events, marketing events are created specifically for the

purpose of marketing a brand (Wood 2009). This is a major benefit of a marketing event,

as the brand is the central focus and the event can be tailored to emphasise brand-related

information and encourage customer-brand interaction (Wood 2009). The host brand of a

marketing event maintains control over the marketing dialogue and event operations. The

differing attributes and subsequent brand outcomes are demonstrated in Mau et al. (2006),

who conclude that sponsored events and marketing events are not only different activities,

but that marketing events have the ability to be more effective in influencing customer

attitudes. The literature is clear that sponsorship and marketing events are separate

activities; sponsorship should not be considered within the definition of marketing events

(Wood 2009).

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2.3.2.1 Branded Marketing Events - a Definition

The term branded marketing event is introduced in this thesis and defined as follows:

A branded marketing event (BME) is a brand-initiated experience that serves as a

platform for customers to interact with the brand and other actors.

The explicit purpose of a BME is to create a unique brand-related experience with the

customer. The term ‘branded marketing event’ more clearly positions an event as a

branding activity; it is brand-centric, with the intention of eliciting brand-related outcomes

such as customer brand engagement. This definition builds on marketing events literature

(Drengner et al. 2008; Whelan and Wohlfeil 2006) but also captures the nature of dynamic

interactions, and hence recognises the principles of S-D logic (Vargo and Lusch 2008) and

customer engagement (Brodie et al. 2011a).

Where marketing events were previously discussed as a “communication tool whose

purpose is to disseminate a company’s marketing messages by involving the target groups

in experiential activities” (Drengner et al. 2008, pg 138, emphasis added), the definition

proposed in this thesis removes words that imply a Goods-Dominant logic; e.g.

communication tool (see definitions from Gupta 2003; Leischnig et al. 2011; Weihe et al.

2006 in Table 2-4), promote or disseminate (see Close et al. 2006; Drengner et al. 2008;

Leischnig et al. 2011 in Table 2-4), and involving (see Drengner et al. 2008 Table 2-4).

The emphasis on BMEs as a platform for customer-initiated experiences creates a stronger

alignment of the proposed definition to the S-D logic (Vargo and Lusch 2008). The

proposed definition also maintains a strong reference to interactions within the experience.

Interaction is recognised in marketing events definitions (see Getz 2008; Whelan and

Wohlfeil 2006 in Table 2-4) and is a central characteristic of customer engagement (Brodie

et al. 2011a).

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The broader construct of brand experience is considered to encapsulate event experiences

(Brakus et al. 2009). Brand experience includes numerous brand-related stimuli, including

branding, communications, and the environments and situations in which the brand is

experienced, including events (Brakus et al. 2009). This thesis focuses on brand-related

stimuli from a BME; therefore, the researcher refers to this as event experience instead of

brand experience.

The proposed definition identifies that BMEs are a platform through which the brand and

customer can interact. This platform contains multiple touch points where the customer can

interact with the brand, specific event activities and/or other customers attending the event.

While this thesis does not examine customer engagement with each of these individual

touch points, it is recognised that overall customer event engagement is an aggregate of

numerous touch points.

Finally, as the term ‘branded marketing event’ is used in this thesis, it is acknowledged

that extensive literature exists around brands and branding. A brand is defined as “an

identifiable product, service, person or place augmented in such a way that the buyer or

user perceives relevant unique added values which match their needs more closely” (De

Chernatony and Dall’Olmo Riley 1998, pg 424). This research domain is broad in scope,

with various approaches including brand equity (Keller and Lehmann 2006), brand value

(Kamakura and Russell 1993), brand performance (Harris and De Chernatony 2001), brand

salience (Romaniuk and Sharp 2004) and brand perceptions (Romaniuk and Sharp 2003).

There are often conflicting perspectives within this body of literature; for example Sharp

and Sharp (1997) argue that brand loyalty has minimal impact on repeat purchase, while

Chaudhuri and Holbrook (2001) emphasise the considerable brand impacts resulting from

brand loyalty.

However, this literature area tends towards a goods-dominant logic perspective, in that

companies develop a brand proposition and communicate this to customers; this is

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considered a dated and narrow-focused approach (Vargo and Lusch 2004). Researchers are

encouraged to ‘break free from the industrial age paradigm of branding’ and consider an

expanded view of brand-customer relationships, where brands connect with and are shaped

by customers (Christodoulides 2008). This thesis adopts this S-D logic perspective. It

recognises that customers do not passively receive information, but instead have an

individualised perception of ‘value’, including a unique and individually determined

perception of a brand (Vargo and Lusch 2014). Therefore, while the branding literature

body is acknowledged, it is not a central focus of this thesis. Instead, this thesis builds from

customer engagement, marketing events and customer experience literature, where direct

applicability to S-D logic is apparent.

2.3.2.2 Investigating a Broader Conceptualisation of BMEs: Customer Experience

Marketing events literature has taken a narrow approach in its identification of different

event types. Studies have typically highlighted the ability of events to have entertainment

or educational value (see Leischnig et al. 2011 Table 2-4). This dichotomy is based on the

notion that events target attendees on an emotional level, while at the same time engage

and interact with the consumer, creating the ability to strongly communicate brand-related

information (Drengner et al. 2008). Empirically, studies have taken a focus predominantly

on entertainment events, however researchers have identified the need for various ‘types’

of events to be considered (Leischnig et al. 2011; Packer and Ballantyne 2004; Whelan and

Wohlfeil 2006). This thesis consults customer experience literature to inform a broader

range of event types that may facilitate customer engagement.

Many marketing events studies refer to the customer experience literature in developing

their understanding of event experiences and types (Crowther 2010; Leischnig et al. 2011;

Whelan and Wohlfeil 2006; Wohlfeil and Whelan 2006; Wood 2009). For example,

Whelan and Wohlfeil (2006) describe opportunities to gain customers’ attention through 35 | P a g e


marketing events that recognise the importance of customer experience. As marketing

events are highly experiential in nature, it is paramount that BMEs are informed from

customer experience in order to ensure their effectiveness (Crowther 2010). This thesis

explores the broader conceptualisation offered in customer experience literature to

establish a more complete and exhaustive view of BME experiences.

2.3.3 Customer Experience

The emergence of customer experience has seen increased popularity as researchers and

practitioners seek alternative media that recognise consumers’ needs for novelty and

individualism (Schmitt 1999). Customer experience is a customer-centric concept, and

encompasses all interactions and experiences between a customer and a brand (Gentile et

al. 2007), including those outside of regular consumption activity. This concept is a

depiction of the view of experience taken in this thesis, as it takes a customer-centric

approach and captures the broad set of experiences that BMEs contain.

There is some confusion around the use of ‘experience’ as a verb or as a noun (Palmer

2010). This thesis adopts the perspective of experience as a noun; “a process of undergoing

and living through an event” (Palmer 2010, pg 197). This perspective aligns with Pine and

Gilmore’s (1998) popular conceptualisation of experience; a memorable event that a brand

creates using their goods and services as central elements of that experience to engage

customers. This conceptualisation also makes the clear connection between events and

customer experience. It is widely recognised that an event falls within the plethora of

customer experiences (Gentile et al. 2007; Oh, Fiore, and Jeoung 2007; Schmitt 1999;

Yuan and Wu 2008), and as such, customer experience measures are used to capture a

BME experience. BMEs are conceptualised in this thesis as the platform in which customer

engagement occurs, and event experiences occur within this platform through various

customer interactions.

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2.3.4 Components of Experience within a BME

Customer experience has been referred to as encompassing all interactions and experiences

between a customer and a brand (Gentile et al. 2007) including those outside of regular

consumption activity. This conceptualisation indicates that customer experience is a very

broad concept, capturing a wide diversity of interactions, and therefore requires a method

of classifying this diversity and simplifying an otherwise complex construct. While ‘BME

experiences’ are identified as a specific type or subset of experience to be explored in this

thesis, the diversity of experiences remains. As identified in the previous discussion of

marketing events, events are provided by the host brand and are tailored to suit the brand’s

objectives (Wood 2009), demonstrating the highly unique nature of events. Therefore,

identifying specific experiential components of a BME is important in gaining a better

understanding of how BMEs facilitate customer engagement.

Customer experience studies have commonly developed typologies of experiential

components that capture the totality of the experience. The experiential components

utilised in this thesis are Cognitive, Emotional, Sensorial, Pragmatic and Relational

(Gentile et al. 2007) and reflect the diversity and unique nature of experiences.

There are many commonly recognised dimensions of a customer experience, including the

sensorial, emotional and cognitive experience components (Brakus et al. 2009; Chang and

Chieng 2006; Gentile et al. 2007; Sahin, Zehir, and Kitapçı 2011; Schmitt 1999; Tynan and

McKechnie 2009; Yuan and Wu 2008). Additional experiential elements, including

pragmatic, lifestyle and relational aspects of the experience are also often proposed and

evaluated in academic studies (Chang and Chieng 2006; Sahin et al. 2011; Tynan and

McKechnie 2009). The conceptualisation of Gentile et al. (2007) takes the broadest

perspective of these studies and encompasses all of the commonly identified experiential

components proposed in this literature space; Cognitive, Emotional, Sensorial, Pragmatic,

Relational and Lifestyle. This perspective of experience is considered robust in terms of

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covering the social/relational elements (Chang and Chieng 2006; Schmitt 1999; Tynan and

McKechnie 2009) as well as the behavioural or ‘pragmatic’ components (Brakus et al.

2009; Chang and Chieng 2006; Sahin et al. 2011; Schmitt 1999). Given the diverse nature

of BMEs due to the varying objectives of the host brand and the unique interactions

created during events (Wood 2009), the components are considered applicable across

various types of experiences and therefore they are utilised within the context of BMEs in

this thesis.

Gentile et al. (2007) also include a ‘lifestyle’ component of experience, which is not

present in many studies (Brakus et al. 2009; Schmitt 1999; Yuan and Wu 2008) and is not

listed explicitly in the study by Chang and Chieng (2006), but was included as a survey

item within their measurement of pragmatic experience. Due to the ambiguity of the

lifestyle component, commonly excluded or embedded within other experiential

components in previous studies, it has not been incorporated in this thesis. Table 2-5

outlines the definitions of each experiential component.

TABLE 2-5: EXPERIENTIAL COMPONENTS WITHIN A BME

Sensorial Experiences that aim to provide positive sensory stimulation, addressing sight, hearing, touch, taste and/or smell

Emotional Experiences that evoke an affective response or relation (with a company, brand or products), by targeting moods, feelings and/or emotions

Cognitive Experiences that stimulate thought or conscious mental processes

Pragmatic Experiences that involve physical action – “the practical act of doing something”

Relational Experiences that provide social context and relationships with others

Source: Definitions adapted from Gentile et al. (2007)

An additional reason for utilising this conceptualisation of experiential components is that

Gentile et al. (2007) apply a conceptual lens consistent with the S-D logic perspective

taken in this thesis. Gentile et al. (2007) recognise that customers actively create their

experience, rather than passively receive the experience from a company. BMEs may

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comprise one, several or all of these components (Gentile et al. 2007) and in providing the

platform through which customers undertake these experiences, BMEs can facilitate


2.3.5 Outcomes of BMEs experiences

Events are described as a ‘hyperreality’, a highly engaging and memorable experience that

is shaped to communicate a particular message about the brand (Whelan and Wohlfeil

2006). Events have the ability to build strong customer relationships and create an

association between the brand and the qualities of the event (Wood 2009). BMEs can

provide numerous benefits for brands; they can enhance awareness and familiarity of the

brand, create strong, positive brand images, influence consumer attitudes, and create

emotional brand attachment (Whelan and Wohlfeil 2006). Previous marketing events

studies have identified numerous outcome variables, most commonly event satisfaction

(Leischnig et al. 2011), influencing brand image (Drengner et al. 2008), creating positive

brand opinion (Close et al. 2006) and influencing customer attitudes (Martensen,

Gronholdt, Bendtsen, and Jensen 2007; Sneath et al. 2005). In addition, marketing events

can result in enhanced attitudes towards the brand (Leischnig et al. 2011; Weihe et al.

2006) and purchase intention (Close et al. 2006; Martensen et al. 2007; Whelan and

Wohlfeil 2006). However, customer engagement as an outcome of a BME experience has

not received explicit attention.

It is likely that customer engagement was facilitated during the interactions and

experiences of these events, and contributes to the relationships identified in these previous

studies (e.g. events leading to purchase intention) without specific inclusion in their

research. Introducing customer engagement into this framework can therefore provide a

more comprehensive view of how BMEs facilitate engagement. In addition, customer

engagement can provide insight into why certain BMEs lead to brand-related outcomes 39 | P a g e


while others do not; customer engagement must be facilitated in order for brand-related

outcomes to occur, which implies that engagement is a mediating variable within this

relationship.

This thesis identifies the pivotal relationship between BME experience and customer

engagement. Due to the highly personalised and interactive experience that both the

customer and the host brand uniquely create, this marketing approach has the ability to

create strong connections and facilitate engagement (Crowther 2010). Therefore, this thesis

posits that various components of experience can facilitate customer engagement. Brands

provide the resources that drive various experiences to occur through the BME platform;

the customer then contributes their own resources as they interact and create value through

this unique experience. It is therefore recognised in this thesis that BMEs are a suitable

platform in which to facilitate customer engagement; utilising the concepts from the

literature bodies of marketing events and customer experience informs further development

and understanding of how customer engagement is driven through the context of BMEs.

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2.4 Customer Engagement and BMEs: A Conceptual Framework

The central purpose of this thesis is to explore how BME experiences facilitate customer

engagement. Therefore, the following section draws from marketing event, customer

experience and customer engagement literature to outline the sources of similarity between

the constructs, and provide insight into how various BME experiences drive customer

engagement. The complementarity of these constructs is assessed with reference to various

principles of the S-D logic; specifically, the common perception taken in these literature

bodies that customers are drivers of their own unique experience (Calder et al. 2013; Close

et al. 2006) and their common emphasis on interaction (Brodie et al. 2011a; Whelan and

Wohlfeil 2006). Although S-D logic has been discussed as the theoretical underpinning to

customer engagement (Brodie et al. 2011a), the following discussion highlights its

relevance to the customer experience and marketing event literature and hence provide a

framework for understanding the relationships between BMEs and customer engagement.

Customer engagement research commonly refers to experiences as an element of

facilitating engagement (Brodie and Hollebeek 2011; Gambetti et al. 2012; Mollen and

Wilson 2010). Vivek et al. (2012) introduce a classification of customer engagement foci,

where provider-initiated activities, including events, are identified as one method of

facilitating engagement. This trend is mirrored in the customer experience literature, as

experiences with a brand are described as unique and personal, and can result in a

motivational state of engagement (Calder et al. 2013; Gentile et al. 2007).

Marketing events literature commonly refers to the ability of events to create unique

experiences, and uses customer experience literature to inform this element of events

(Crowther 2010; Leischnig et al. 2011; Whelan and Wohlfeil 2006; Wohlfeil and Whelan

2006; Wood 2009). Marketing events studies have also used the term engagement,

however do not conceptualise or explore engagement (Close et al. 2006; Whelan and

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Wohlfeil 2006). This thesis further integrates these constructs and subsequently informs a

strategic approach of using BME experiences to drive customer engagement.

The complementarity of marketing events, customer experience and customer engagement

is evident through their applicability to S-D logic. First, S-D logic reiterates that customers

are the drivers of value creation (Vargo and Lusch 2008) and the company only provides

value propositions or platforms through which customers interact and create their own

value. This message is echoed in customer experience literature; companies provide the

context for the experience to occur that enables the customer to create their own unique

experiences (Gentile et al. 2007; Zomerdijk and Voss 2010). Customer experience

literature also recognises that events are highly subjective in nature (Brakus et al. 2009)

and therefore the individual perceives and determines the value in the experience. Research

in marketing events has also made the connection with S-D logic (Crowther 2010;

Crowther and Donlan 2011), particularly emphasising that customers drive their own

unique experiences (Wohlfeil and Whelan 2006). A central element of customer

engagement is the interaction that occurs to create a heightened psychological state, and

thus is inherently subjective to the individual (Brodie et al. 2011a). A BME is therefore

considered an effective means of facilitating customer engagement, as it is interactive and

subjective in nature, whereby the individual determines and perceives value. This

experience, personal and unique to the individual, leads to engagement (Gentile et al.

2007). A BME should elicit strong customer brand engagement, the mechanics of which

are the focus of this thesis.

Second, S-D logic recognises that customers are not passive in their contact with firms;

rather they create value through extensive interaction to shape their brand experiences

(Vargo and Lusch 2004). Marketing events literature has primarily overlooked the active

participation of customers in the communication of the marketing message (Drengner et al.

2008). However, it is this aspect of the experience that makes BMEs a highly effective

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means of eliciting customer engagement (Brodie et al. 2011a; Vargo and Lusch 2004).

Participants interact extensively with other participants and brand representatives during an

event experience (Wohlfeil and Whelan 2006). S-D logic is used in customer experience

literature to explain the interactions occurring during an experience (Crowther 2010).

Customer experience is argued to occur through interaction, and relies on the consumer

driving and uniquely creating their desired experience (Tynan and McKechnie 2009).

Interaction is a focal element of customer engagement, and is the primary quality

distinguishing it from related concepts such as involvement (Brodie et al. 2011a;

Hollebeek 2011a). Therefore, the interactive elements of a BME create an environment

conducive to customer engagement (Vargo and Lusch 2004; Vivek et al. 2012; Wohlfeil

and Whelan 2006). Specifically, the BME is the platform through which customer

engagement is facilitated as customers interact and create their own unique and valuable

experiences (Zomerdijk and Voss 2010). Through high levels of interaction within this

platform, customers create a BME experience that is of most value to them, and therefore

gain the most value from the experience (Prahalad and Ramaswamy 2004).

In summary, discussion in the literature of marketing events, customer experience and

customer engagement have commonalities with reference to their applicability to S-D

logic. Studies that comprehensively bring these literature bodies together are scarce.

Therefore, this thesis investigates BMEs as a brand-initiated engagement platform, which

encompasses activities beyond the normal offering of the organisation. This thesis

contributes to the knowledge of customer engagement through investigating how BMEs,

comprised of various experiential components, facilitate customer engagement.

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2.4.1.1 The role of Social Engagement within Customer Engagement

Social engagement refers to a dimension of engagement based on personal exchanges with

other actors; however, its presence and conceptualisation within the overall customer

engagement construct is often debated in the customer engagement literature (Calder,

Malthouse, and Schaedel 2009; Gambetti et al. 2012; Sawhney, Verona, and Prandelli

2005; Vivek et al. 2012). While the three dimensional perspective (cognitive, emotional,

and behavioural) of customer engagement is widely accepted (Hollebeek 2011b), various

customer engagement studies have included a social dimension of engagement (Vivek et

al. 2012), social-interactive engagement (Calder et al. 2009), or social elements of

engagement (Gambetti et al. 2012; Sawhney et al. 2005). Others have a strong social focus

throughout their discussion of customer engagement (Abdul-Ghani et al. 2011;

Algesheimer et al. 2005), but do not explicitly indicate social engagement as an

independent engagement dimension (Brodie et al. 2011b). This thesis argues that the

impact of social influences within the BME experience is substantial, and includes social

engagement as a dimension of the customer engagement construct.

Social exchange theory argues that customers engage in activities that provide emotional

rewards including social approval and human contact (Abdul-Ghani et al. 2011).

Customers interactively establish value with organisations and, given the opportunity, will

engage in practices to create value (Schau, Muñiz Jr, and Arnould 2009). Practices dictate

what is necessary for engaging social actors in a meaningful way within a particular setting

(Schau et al. 2009). Organisations should encourage customers to interact in order to drive

engagement with the brand (Schau et al. 2009). Therefore, including a social dimension of

engagement as separate and unique to the other dimensions of engagement is an important

development, as it captures the heightened psychological state of the customer during their

unique and meaningful interactions with other actors either in context of, or directly

towards, the brand.

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A definition of social engagement is the customer’s heightened level of interest regarding

the focus of engagement (i.e. the event or the brand) based on personal exchanges with

other actors. In this regard social engagement is an important addition as it takes a holistic

perspective and captures interactions beyond the control of the brand, but which also

contribute to the overall facilitation of customer engagement (Verhoef, Lemon,

Parasuraman, Roggeveen, Tsiros, and Schlesinger 2009). The inclusion of a social

dimension of engagement broadens the perspective of interactions from customer-brand to

include customer-customer in the context of brands (Kozinets 2014).

The definition of social engagement constructed for this thesis is consistent with So et al.’s

(2012) definitions of customer engagement dimensions (see section 2.2.2.3). A comparison

to So et al.’s (2012) enthusiasm definition is used identify the similarity in structure;

enthusiasm “represents an individual’s strong level of excitement and interest regarding the

focus of engagement, such as a brand” (So et al. 2012, pg 5). The social engagement

definition follows the same structure of identifying the engagement subject (the customer),

the engagement state (heightened level of interest), the engagement object (regarding the

focus of engagement i.e. the event or the brand) and an outline of the social nature of the

engagement (based on personal exchanges with other actors). A recent conceptual paper by

Kozinets (2014, pg 10) is the first to provide an in-depth conceptualisation and definition

for social brand engagement; “meaningful connection, creation and communication

between one consumer and one or more other consumers, using brands”. The Kozinets

(2014) definition is consistent with the social engagement definition constructed for this

thesis. The next section discusses customer social engagement with reference to the event

and the brand.

Research Question: What is the role of social engagement within the overall customer engagement construct?

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Social event engagement is defined as the customer’s heightened level of interest

regarding the event based on personal exchanges with other customers. This form of

engagement occurs when the customer has a personal exchange with other customers

within the context of, or with reference to, the event.

Customer engagement literature has conceptually acknowledged that social engagement

can occur with a provider-initiated activity or event (Kozinets 2014; Vivek et al. 2012). A

range of service encounters, including BMEs, are experienced either intentionally with

others, or in the presence of other customers (Tombs and McColl-Kennedy 2010; Zhang,

Beatty, and Mothersbaugh 2010). This has become considerably more important given the

current marketing trend of brands creating memorable experiences for their customers

(Zhang et al. 2010). Customers are constantly interacting both with brand representatives

and other customers in attendance of the event (Drengner et al. 2008). Therefore, whether a

person attends an event with others (friends, family) or interacts directly or indirectly with

others attendees unknown to the consumer but present at the event, personal exchanges are

abundant. The personal exchanges pertaining to the event can contribute to the customer’s

heightened psychological state with reference to the event, and hence build their level of

customer event engagement. As a result of these insights, the following hypothesis is

proposed;

Hypothesis 1a: Social event engagement is a dimension of customer event

engagement.

Social brand engagement is defined as the customer’s heightened level of interest

regarding the brand based on personal exchanges with other customers. This form of

engagement occurs when the customer has a personal exchange with other customers about

or with reference to the brand. This conversation builds the customer’s interest in the brand

due to the brand-related information exchanged between the customers. The host brand is

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not directly in control of this social exchange, however can offer opportunities for

customers to interact (i.e. during a BME) and hence facilitate social brand engagement.

A number of the studies with a focus on social engagement are set in an online context

(e.g. Calder et al. 2009), which is considered to have a high level of customer-to-customer

as well as customer-to brand interactions within the virtual space (Abdul-Ghani et al. 2011;

2011b). This level of social interaction is equally applicable to BMEs, as they are

fundamentally a social activity (Kozinets 2014). The interactions with other customers

within the same experience can have a considerable impact on either enhancing or

damaging that customer’s experience with the associated brand (Zhang et al. 2010).

Therefore, social brand engagement is an important consideration within a BME due to the

large opportunity for personal exchanges between customers to occur, and for the brand-

related discussion within this exchange to contribute to the customer brand engagement

construct. Therefore, the following hypothesis is proposed:

Hypothesis 1b: Social brand engagement is a dimension of customer brand

engagement.

2.4.2 Relationships between Experiential Components of a BME and Customer

Engagement

The marketing events literature provides a sound argument and theoretical justification for

events to facilitate customer engagement through their mutual applicability to S-D logic.

However, little research has embraced the engagement literature to provide an

understanding of how marketing events engage customers. A BME is an effective means of

creating meaningful experiences as it is interactive and subjective in nature, leading to

customer engagement (Brodie et al. 2011a; Calder et al. 2013).

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While social exchange theory (Möller 2013; Saks 2006) was discussed in the previous

section (2.4.1.1) in the context social engagement, it can also be used to explain the

relationship between BME experiences and customer engagement on a broader level. This

theory explores reciprocity between the brand and the customer, in which both parties

actively contribute to the relationship in order to receive mutual benefits or avoid potential

risks (Cropanzano and Mitchell 2005; Möller 2013). While social exchange theory has

been previously discussed in the context of employee engagement (Saks 2006), its

applicability extends to customer engagement insofar as it highlights the contribution of

resources from both the brand and the customer.

Stronger engagement results from both parties contributing resources, interacting and

abiding by the implied ‘rules of exchange’ (Saks 2006). The actions and reactions from

both parties over time are a process of building a mutually beneficial relationship, for

example increased customer trust and commitment (Cropanzano and Mitchell 2005). The

conclusion drawn from this theory is that extensive contribution from the consumer (i.e.

their engagement) and the brand (in this context the provision of a BME) will result in

mutually beneficial outcomes.

The brand resources within this exchange are the provision of various components of

experience through the BME platform. Marketing events studies have identified categories

of events; however, as previously discussed this categorisation is relatively narrow in its

focus. As a result, customer experience literature is examined to find a more

comprehensive conceptualisation of experience. This thesis investigates five experiential

components; Cognitive, Emotional, Sensorial, Pragmatic, and Relational (Gentile et al.

2007).

Research Question: How do the experiential components of a BME facilitate customer engagement?

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The following section identifies the ability for each experiential component to contribute to

customer engagement. Each experiential component is discussed, and the resulting

customer event engagement and customer brand engagement outcomes are proposed. The

connections are proposed by identifying the brand-provided resources within the exchange

(BME experiential component) and the logical corresponding resources provided by the

customer (dimensions of customer engagement) (Saks 2006).

The hypotheses identify the general relationship anticipated between the experiential

component, customer event engagement and customer brand engagement. It is

acknowledged that specific experiential components may contribute to individual customer

engagement dimensions (e.g. attention, absorption, immersion) as opposed to customer

engagement in a general sense; however, this is beyond the scope of this thesis. Therefore,

customer engagement outcomes are considered from an overall perspective in this thesis,

not on particular engagement dimensions, as each should contribute to and enhance each

other and result in a general level of customer engagement (Brodie et al. 2011a). Future

research should investigate the more particular relationships concerning the dimensions of

engagement, and this is discussed in Chapter 5.

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2.4.2.1 Cognitive Experience

A cognitive experience is one that requires the participant to actively think, or aims to

stimulate thought or conscious mental processes in a particular area of interest or

knowledge (Gentile et al. 2007). In the context of the wine industry a wine education event

is an example of a strong cognitive experience. For a cognitive experience, the brand-

provided resources encompass information designed to make the customer think and

possess intellectual appeal; cognitive experiences therefore appeal to customers through

stimulating intrigue (Schmitt 1999). For example, wine education sessions involve

teaching the attendee about various topics including the winery’s history, blends or the

process of wine production.

In order for customer engagement to occur, the customer must also provide resources

within the BME and contribute to the exchange (Saks 2006). Customers are anticipated to

elicit event attention, displaying attentiveness during the event (So et al. 2012; Tynan and

McKechnie 2009) and a heightened level of concentration in the event interaction

(Hollebeek 2011b) in response to the information and cognitive stimulation provided

during the BME. Customer event engagement therefore occurs when the customer elicits a

willingness to invest mental effort into the cognitive experience (Salanova et al. 2005).

Learning through a cognitive experience requires active participation of the customer (Pine

and Gilmore 1998), for example thinking through ideas and asking questions during a wine

education session or participating in demonstrations that reflect a discussion topic such as

the fermentation process (Charters and Ali-Knight 2000; So et al. 2012). Customers could

therefore engage through event interaction, actively participating in the event experience

by discussing topics with winemakers or other customers, or participating in

demonstrations (So et al. 2012).

In addition, customers could respond to the brand-provided resources during cognitive

BME experiences with event enthusiasm (So et al. 2012). If the customer possesses a

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strong interest in wine, they would find the experience of learning about wine enjoyable

(Packer and Ballantyne 2004), eliciting a heightened level of affect in response to the

information provided during the BME (Hollebeek 2011b).

The brand-provided resources in a cognitive experience also have the capacity to facilitate

customer brand engagement if the resources within the BME experience are brand-centric.

Wine education sessions are likely to focus on brand-related information, for example the

discussion is likely to be about the wine brand’s varietals or how their particular wine is

produced (Charters and Ali-Knight 2000).

Cognitive experiences that involve thinking and mental processes directly related to the

brand (e.g. discussing the different processes of producing wine, different varietals) change

the customer’s perception of the brand and its products (Yuan and Wu 2008). Education

events are described as eliciting customer interaction, however the customer’s focus is not

necessarily on the event but rather the content shared during the event (Pine and Gilmore

1998). Customers can also respond to a cognitive experience with enhanced identification

with reference to the brand (So et al. 2012); the customer feels that the brand is a means of

self-expression (Sprott et al. 2009). For example, a wine connoisseur, having experienced a

cognitive event and learning more about a particular wine brand, would feel that their

knowledge related to that wine brand contributes to their wine lifestyle, hence causing

them to feel strong brand identification (So et al. 2012).

Therefore the following hypotheses are proposed;

Hypothesis 2a: Cognitive event experience contributes to customer event engagement

Hypothesis 2b: Cognitive event experience contributes to customer brand engagement

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2.4.2.2 Emotional Experience

An emotional experience is one that evokes an affective response and targets moods,

feelings and/or emotions (Gentile et al. 2007). An example of an emotional experience in

the wine industry is a winery picnic, where attendees are encouraged to relax and enjoy

live music. For an emotional experience, the brand-provided resources include the source

of entertainment designed to generate customer enjoyment (Tynan and McKechnie 2009)

and provide emotional value (Yuan and Wu 2008). Emotional experiences therefore appeal

to the customer’s emotions by stimulating their excitement, joy and interest in the activity

(Schmitt 1999; So et al. 2012). For example, winery picnics or music events are run to

elicit relaxation, leisure and enjoyment (Jingxue et al. 2008).

The anticipated customer resources contributed to this exchange include event enthusiasm,

displaying positive affect during the event (Hollebeek 2011b) and a heightened level of

excitement and interest regarding the event interaction in response to the source of

entertainment provided during the BME (So et al. 2012; Vivek et al. 2012). Customer

event engagement therefore occurs when the customer elicits enthusiasm and willingness

to further interact in the event activities (So et al. 2012). Depending on the intensity of the

experience, the customer can also elicit event absorption due to the strong emotional

qualities the event provides (Drengner et al. 2008; So et al. 2012). For example, during a

music event at a winery, the customer may feel such excitement and enthrallment in the

music that they experience a state of flow, becoming completely engrossed in the

experience and lose sense of time (Csikzentmihaly 1990; Vivek et al. 2012).

The brand-provided resources in an emotional experience also have the capacity to

facilitate customer brand engagement if the resources within the BME experience are

brand-centric. Winery picnic events can have an emphasis on the brand, for example

serving the brand’s wines and providing tastings during the event. Emotional experiences

can also reflect or embody the image of the brand (Drengner et al. 2008), leading to

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customer brand engagement; for example, a music event at a winery could emphasise the

brand’s youthful image by showcasing new bands with a younger following, or project an

image of elegance or sophistication by playing jazz or opera. If the brand’s image is

evident in the emotional experience, the customer’s heightened interactions during the

BME can create a closer connection to the brand (Wohlfeil and Whelan 2006) and event

enthusiasm (So et al. 2012). Customers can also respond to an emotional experience with

enhanced identification with reference to the brand (So et al. 2012) if the customer feels

that the brand’s image is consistent with their own self-image.


Hypothesis 2c: Emotional event experience contributes to customer event engagement

Hypothesis 2d: Emotional event experience contributes to customer brand engagement

2.4.2.3 Sensorial Experience

A sensorial experience is one that provides positive sensory stimulation, addressing sight,

hearing, touch, taste and/or smell (Gentile et al. 2007). A wine industry example of a

sensorial experience is a wine tasting or wine and food pairing event.

For a sensorial experience, the brand-provided resources encompass sources of sight,

sound, scent, taste, and touch (Yuan and Wu 2008) designed to provide sensory meaning

and stimulation (Gentile et al. 2007; Schmitt 1999). The customer-provided resources in

this exchange include event interaction, displaying participation in event activities (Mollen

and Wilson 2010) and a heightened level of energy toward the event interaction in

response to the sensorial elements provided during the BME (Hollebeek 2011b). The focal

element of a sensorial experience is sensory stimulation (Gentile et al. 2007); therefore the

experience inherently requires active participation from the customer (they must taste,

touch, smell something).

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In addition, sensorial experiences appeal to customers through aesthetics or excitement

(Schmitt 1999) stimulating event enthusiasm (So et al. 2012). For example, wine

consumption is strongly related to leisure activity and aesthetic consumption (Charters and

Pettigrew 2005), in particular wine and food which trigger the human senses of taste

(Gentile et al. 2007). Event enthusiasm is facilitated by a sensorial experience when the

customer elicits feelings of pleasure, happiness, or a positive mood towards the event

(Hollebeek 2011b).

The brand-provided resources in a sensorial experience also have the capacity to facilitate


For example, customers pay attention to brand-related information during a wine tasting

event (So et al. 2012), as tasting the wines or pairing wines with food provides sensory-

related information (e.g. what varietals of the brand’s wine the customer enjoys, or the type

of food that matches with particular wine products). Sensorial experience is therefore

posited to contribute to customer brand engagement as the customer gives their attention in

order to acquire new brand knowledge through learning wine tastes and smells, or

recognising the taste of appropriate food and wine pairings (Schmitt 1999). For the wine

connoisseur, the sensorial experience becomes a means through which customers learn

about the brand and gain knowledge in an area of interest to them (Charters and Ali-Knight

2000).


Hypothesis 2e: Sensorial event experience contributes to customer event engagement

Hypothesis 2f: Sensorial event experience contributes to customer brand engagement

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2.4.2.4 Pragmatic Experience

A pragmatic experience requires physical behaviours or actions from the customer (Gentile

et al. 2007). This is likened to ‘escapist experiences’ conceptualised by Pine and Gilmore

(1998), and involves a high level of customer immersion in the activity. In the context of

the wine industry a grape-stomp or a wine-blending event is an example of a pragmatic

experience.

For a pragmatic experience, the brand-provided resources encompass physical activities

designed to stimulate active customer participation (Mollen and Wilson 2010). For

example, wine-blending events involve extensive customer participation in the wine

production processes. The customer-provided resources in this exchange are anticipated to

include event interaction (Pine and Gilmore 1998), displaying considerable effort and

energy elicited during the event (Hollebeek 2011b) and a heightened level of behaviour in

the event interaction in response to the physical elements provided during the pragmatic

BME experience (So et al. 2012). Customer event engagement therefore occurs when the

customer elicits a willingness to participate and elicit energy into the pragmatic experience

(So et al. 2012).

Customers could also respond to the brand-provided resources during pragmatic BME

experiences with event attention (Pine and Gilmore 1998; So et al. 2012). If the customer

has a strong wine involvement, they would find the experience of participating in wine-

making engaging and elicit a heightened level of interest and focus in order to attain new

brand-related information (Hollebeek 2011b), eliciting a heightened level of event

attention in response to the physical activity provided during the BME (So et al. 2012).

In addition, customers could elicit a heightened level of excitement and interest in response

to the pragmatic experience (Vivek et al. 2012) if they experience pleasure or novelty in

participating in a pragmatic experience. For example, customers participating in a grape-

stomp or creating their own wine blend find great enjoyment, excitement, and novelty in

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the experience, resulting in a heightened state of positive affect and interest in the BME

(Hollebeek 2011b; Vivek et al. 2012). A highly unique, novel or exciting pragmatic BME

experience could also elicit event absorption in which the customer experiences a

heightened state of flow, engrossment and complete concentration and happiness during

the activity (Csikzentmihaly 1990; So et al. 2012).

The brand-provided resources in a pragmatic experience also have the capacity to facilitate


A wine-blending event is brand-centric, as the customer participates in the production

process of making their own unique wine blend based on the existing varietals on offer at

the winery. Pragmatic experience is therefore posited to contribute to customer brand

engagement as the customer gives their attention (So et al. 2012) in order to acquire new

brand knowledge through learning about the wine product process and blending of wine

varietals (Schmitt 1999).


Hypothesis 2g: Pragmatic event experience contributes to customer event engagement

Hypothesis 2h: Pragmatic event experience contributes to customer brand engagement

2.4.2.5 Relational Experience

A relational experience is one that emphasises the social context and relationships with

others (Gentile et al. 2007). Events are typically public with many people in attendance,

and so the entire experience occurs within a social context (Zhang et al. 2010). Wine

dinner events or meeting the winemaker are examples of relational BME experiences in the

wine industry.

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For a relational experience, the brand-provided resources encompass activities designed to

be experienced together with other people (Gentile et al. 2007); relational experiences

therefore appeal to customers through social event engagement, a heightened state of

interest regarding the event based on these personal exchanges with other customers

(discussed in section 2.4.1.1) (Kozinets 2014; Vivek et al. 2012). For example, wine dinner

events involve large groups of people, either known or unknown to each other,

participating in a food and wine degustation; the customers are seated together, and

encouraged to mingle and socially interact during the dinner. These interactions can induce

a heightened sense of connectedness with other customers in the context of the event

(Kozinets 2014), providing social value (Tynan and McKechnie 2009).

In addition, customers could respond to the brand-provided resources during relational

BME experiences with event enthusiasm (So et al. 2012). Interactions with winemakers or

other attendees during a relational experience are intended to be enjoyable, exciting

experiences due to the aesthetics and leisure associated with wine activities (Jingxue et al.

2008). Therefore, the customer would elicit a heightened state of excitement and emotional

connection to the event (So et al. 2012) in response to an experience that connects the

customer to a broader social context (Schmitt 1999).

The brand-provided resources in a relational experience also have the capacity to facilitate


Wine dinner events and ‘meet the winemaker’ events are likely to include brand-related

information, for example the winemaker talking about their experiences working at the

winery (Charters and Ali-Knight 2000). Therefore, while the brand-provided resources are

the activities that connect people (Schmitt 1999), the exchanges that occur during the

relational experience are cognitive in nature and specific to the brand (Yuan and Wu

2008). The customer therefore provides their focus and concentration to brand-related

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information relayed by the winemaker or other attendees, creating a heightened state of

brand attention (So et al. 2012).

In addition, a relational experience can also provide a means of affirming the customer’s

identity and sense of belongingness as the experience connects the customers to

likeminded others in a social group (e.g. the ‘wine’ lifestyle) (Gentile et al. 2007). For

example, a wine dinner places the customer in a situation with other likeminded customers;

their shared interest in the wine brand reinforces the customer’s self-image and need to be

positively perceived by others (Schmitt 1999; So et al. 2012). Therefore, the customer

responds to the relational experience with a heightened sense of self-image and connection

toward the brand (So et al. 2012), as the brand is a focal element of the experience.

Therefore, the following hypotheses are proposed;

Hypothesis 2i: Relational event experience contributes to customer event engagement

Hypothesis 2j: Relational event experience contributes to customer brand engagement

While the connections between the various components of event experience are proposed

to contribute to customer event engagement and customer brand engagement, it remains

unclear what relationship exists between the two customer engagement constructs. The

following section investigates the interplay between the two engagement objects.

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2.4.3 The Interplay between Customer Engagement Objects

Organisations host BMEs to achieve brand-related outcomes; to create a closer connection

with their customers and interact in a unique way to create value (Wood 2009). While it is

established that provider-initiated activities are a means of facilitating customer

engagement (Vivek et al. 2012), a BME experience is beyond the normal interactions with

a brand. It is therefore important to investigate if and how the connection is made between

the event experience and the host brand, as this impacts whether organisations receive any

benefit in hosting BMEs.

Customer engagement recognises that either the customer or the provider is the initiator of

engagement (Vivek et al. 2012) and highlights the need for an interaction between a focal

object and the customer (Brodie et al. 2011a; Hollebeek et al. 2014). In this regard,

customer event engagement occurs from the interactions during the BME (Vivek et al.

2012). Although Vivek et al. (2012) recognise that providers may initiate activities or

events to engage customers with the event, they do not explain how the nature of

interaction with the event facilitates customer brand engagement.

The literature on customer engagement identifies that an interaction must occur between

the ‘engagement subject’ (e.g. the customer) and an ‘engagement object’ (e.g. a brand)

(Hollebeek 2011a), however, extant studies do not explore the relationship between

multiple engagement objects. Brodie et al. (2011b) identifies that customers can engage

with numerous engagement objects but these objects were in reference to ‘themes’ of

discussion with members of an online community. These multiple objects were not

described as having a causal relationship, but rather as specific ‘topics of interest’ in which

a community member may engage. Brodie et al. (2011b) also mentioned a possible

relationship between the online community engagement objects (themes), however this

was not explored.

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It is proposed in this thesis that the engagement subject, the customer, will interact and

create value during an event experience and therefore will elicit customer event

engagement. However, with an understanding that ‘brand experience’ encompasses a broad

range of brand-related stimuli, including environments in which the brand is present (e.g.

events) (Brakus et al. 2009), it is also posited that a relationship exists between customer

event engagement and customer brand engagement. The relationship between customer

event engagement and customer brand engagement is not explored in the customer

engagement literature, making it a main contribution of this thesis.

There are a number of marketing events studies that investigate brand-related outcomes

resulting from events (Crowther 2011; Martensen et al. 2007; Weihe et al. 2006; Whelan

and Wohlfeil 2006). Marketing events are expected to create customer engagement with

the brand due to the high level of brand information and brand-related experiences within

the event (Whelan and Wohlfeil 2006). In addition, positive brand outcomes arise when the

event experience accurately depicts brand personality or desired brand images and values

(Crowther 2011). Therefore, a relationship between BMEs and host brand outcomes is

recognised in marketing events literature that is not explained in customer engagement

literature. This thesis contributes to the engagement literature by exploring customer event

engagement and its relationship with, and ability to further facilitate, customer brand

engagement.

Associative network theory (ANT) is the underpinning of this phenomenon. ANT is

founded in psychology from similar theoretical domains including ‘spreading activation

theory in memory’ (Anderson 1983), and ‘semantic processing’ (Collins and Loftus 1975).

Research Question: What is the relationship between the engagement with two focal objects; customer event engagement and customer brand engagement?

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ANT provides an understanding of how memory operates and specifically the mental

process of connecting pieces of information in memory (Smith 2004). When two pieces of

information are received simultaneously they can be mentally matched-together and

produce transfer; the associations of the first piece of information are replicated with the

second (Smith 2004). Memory contains ‘nodes’, or individual pieces of information, that

are triggered or called to mind through a process of activation (Smith 2004). When a

person has an experience that triggers multiple nodes simultaneously, connections can be

formed in memory which causes information of one concept to activate information of

another; this is referred to as ‘spreading activation’ (Smith 2004).

ANT has been used to understand various phenomena in the field of marketing; for

example celebrity endorsement, brand extensions (Keller and Aaker 1992) and sponsorship

(Smith 2004). In a sponsorship context, customers retain information about events in

memory; through a process of ‘spreading activation’ certain sets of event-related

information can trigger thoughts about related information, in this case linked information

about the host brand (Smith 2004). Particularly within sponsorship literature, ANT is

described with reference to the concept of brand image transfer. Brand image transfer

describes a process whereby customers initially have specific associations towards an

event. When a brand is presented with this event and a perceived connection between the

two is established, the associations with the event can become linked and projected onto

the brand (Gwinner 1997; Gwinner and Eaton 1999). Brand image transfer is commonly

used in marketing events literature to describe common associations or attitudes placed

upon an event and host brand (Martensen et al. 2007).

This thesis extends ANT into the context of BMEs and customer engagement. A recent

sponsorship paper has taken an initial step in bringing ANT into the customer engagement

domain, finding that more interactive or engaging brands benefit from enhanced brand

recall compared to passive brands (Pokrywczynski and Brinker 2014). A particularly

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strong connection is anticipated for BMEs as these events are branded and tailored

specifically to relate to the host brand. As BMEs are proposed to facilitate high levels of

customer engagement, the benefit to the brand in hosting a BME is expected to increase.

This thesis further extends ANT into customer engagement literature and proposes that

spreading activation can also occur between engagement objects; from event engagement

to brand engagement. The customer first engages with the event and due to the strong

connection between the event and the brand, this state of engagement can also project onto

the brand. This relationship is yet to be investigated in customer engagement literature, and

hence is a contribution of this thesis. Therefore, the following hypothesis is proposed:

Hypothesis 3: There is a positive relationship between customer event engagement

and customer brand engagement

2.4.3.1 Customer Engagement to Behavioural Intention of Loyalty

Research on customer engagement has investigated various outcomes, including

satisfaction, loyalty, commitment and trust (Brodie et al. 2011b), however, relatively less

attention has been given to purchase intention outcomes; for example ‘brand usage intent’

(Hollebeek et al. 2014) and behavioural intention of loyalty (So et al. 2012). Given that

organising a BME is a considerable investment for the host brand, it is important to

determine the brand-related outcomes. Particularly for engagement activities that do not

necessarily stimulate an immediate monetary outcome for the brand, such as a BME, it is

important to investigate the anticipated brand-related outcomes resulting from customer

engagement. Evidence of brand benefits would further support BMEs as an antecedent of

customer engagement and an effective brand-building activity.

This thesis investigates behavioural intention of loyalty (BIL) toward the brand as an

indication of consumption behaviour (Zeithaml et al. 1996). Originally investigated as an

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outcome of service quality (Zeithaml et al. 1996), the BIL construct has been widely

utilised to reflect the outcomes resulting from relationship marketing (Hennig-Thurau,

Gwinner, and Gremler 2002) as well as engagement (So et al. 2012). Zeithaml et al. (1996)

conceptualise four categories of BIL; word-of-mouth, purchase intention, price sensitivity

and complaining behaviour. Service quality must surpass a certain satisfaction threshold in

order to impact BIL (Zeithaml et al. 1996); this is consistent with the idea of engagement

and BMEs in that extraordinary experiences or a heightened psychological state are

required to have a strong brand impact.

This thesis employs only two of the BIL categories proposed in Zeithaml et al. (1996);

word-of-mouth and purchase intention. The decision to adopt only two dimensions was

based on a number of considerations. First, results from Zeithaml et al.’s (1996) study

indicated ‘loyalty’ as the largest BIL factor, encompassing favourable behavioural

intention items including positive word of mouth/willingness to recommend, reporting the

brand as their first choice to buy and do business with in the future. Second, word-of-

mouth and purchase intention are already identified outcomes in customer engagement,

marketing events and customer experience literature; employing consistent outcome

variables in this thesis provides empirical support for these existing assertions in the

literature. Finally, as BMEs extend beyond normal customer-brand interactions (Vivek et

al. 2012) and do not necessarily involve a monetary transaction, it was debated whether the

constructs of price sensitivity and complaining behaviour maintained strong applicability

in this context.

The theory of consumption values (Sheth et al. 1991) provides a general framework to

explain consumption behaviour; the theory states that various consumption values

perceived by the customer are focal in explaining consumer choice with regards to

purchase (or not purchase) as well as brand selection (Sheth et al. 1991). This theory is

consistent with S-D logic and customer engagement in that uniquely created and

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individually perceived value is focal to the interactions between customers and brands

(Brodie et al. 2011a; Vargo and Lusch 2004). This theory has been applied to understand

experiences, and supports the link between customer engagement and brand-related

outcomes (Vivek et al. 2012); therefore, it provides insight into the relationship between

customer engagement (with the event and the brand) and behavioural intention of loyalty

investigated in this thesis.

The BIL dimensions of word-of-mouth and purchase intention have specifically been

utilised in So et al. (2012), however with reference to a different engagement object

(tourism brands). This thesis extends the research on BIL resulting from customer

engagement as it explores the impact from both an event and brand perspective. These

individual relationships are discussed in the following section.

The main objective of a company in hosting a marketing event is to lead to brand-related

outcomes, for example increased brand purchase intention (Crowther 2010; Drengner et al.

2008; Leischnig et al. 2011; Martensen et al. 2007) and word of mouth (Crowther 2011;

Gupta 2003; Wood 2009). Similarly, customer experiences have been found to impact on

loyalty intentions and customer satisfaction (Klaus and Maklan 2013) as well as word of

mouth (Grewal, Levy, and Kumar 2009) and purchase intentions (Palmer 2010). The

relationship between customer event engagement and BIL is consistent with the extant

literature as it captures brand word-of-mouth and purchase intention (Zeithaml et al. 1996).

A BME experience that facilitates customer event engagement can have positive outcomes

for the brand because the unique customer-brand interactions during the BME allow the

customer to construct relevant meanings about the brand, leading to loyalty (Crowther and

Donlan 2011). In summary, these studies support the presence of a direct relationship

Research Question: What impact does customer engagement have on behavioural intention of loyalty?

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between customer event engagement and behavioural intention of loyalty toward the brand.

Therefore the following hypothesis is proposed:

Hypothesis 4a: There is a positive relationship between customer event engagement

and behavioural intention of loyalty

The notion that customer brand engagement enhances a customer’s predisposition towards

a brand and hence increases behavioural intention of loyalty has been espoused in recent

literature (Bowden 2009; Hollebeek 2011a). The heightened psychological state and

interactions that occur between customer and the brand is thought to predispose the

customer to future purchases (So et al. 2012). This relationship is also supported is

customer experience literature; the attitudes formed from a brand experience are expected

to predict brand purchase intention (Zarantonello and Schmitt 2010). Despite these

previous assertions that customer brand engagement facilitates behavioural intention of

loyalty (So et al. 2012), there is little empirical examination of this relationship. Therefore

the following hypothesis is proposed:

Hypothesis 4b: There is a positive relationship between customer brand engagement

and behavioural intention of loyalty

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2.5 Experiential Needs

BMEs can facilitate customer engagement as they are unique customer-driven experiences,

creating significant customer value (Brodie et al. 2011a; Calder et al. 2013). Consistent

with this view, this thesis explores how individuals with varying experiential needs engage

with the event through different BME experiential components (cognitive, emotional,

sensorial, pragmatic and relational). It is expected that the fulfilment of experiential needs

will strengthen the relationship between BME experiential components and customer event

engagement.

2.5.1 Conceptualising Experiential Needs

Consumer needs are defined as requirements for something essential or desirable that is

lacking, and are categorised as utilitarian, means-to-an-end based needs, and expressive,

based on internal aspirations to fulfil a social or aesthetic need (MacInnis and Jaworski

1989). Within the category of expressive needs are experiential needs (MacInnis and

Jaworski 1989), the need that an individual seeks to fulfil through experiences based

broadly on their need for sensory or cognitive stimulation. People possessing a need for

sensory stimulation seek experiences that are novel, exciting and entertaining. They seek

variety, risk taking and adventure (Baumgartner and Steenkamp 1996; Orth and Bourrain

2005). Consumers with cognitive stimulation needs find motivation in information-seeking

or curiosity; these people seek experiences that aid them in acquiring or enhancing their

knowledge in a particular area of interest (Baumgartner and Steenkamp 1996; Orth and

Bourrain 2005). MacInnis and Jaworski’s (1989) experiential needs have conceptual

similarity to exploratory consumer behaviour, which suggests that individuals engage in

activities for intrinsic pleasure gained from a unique experience rather than for extrinsic

outcomes (Baumgartner and Steenkamp 1996). These behaviours are motivated by a desire

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for experiences that provide excitement, novelty, variety, or satisfy curiosity (Baumgartner

and Steenkamp 1996).

The influence of experiential needs is explained with optimum stimulation level (OSL)

theory; individuals seek out stimulation from particular environments in order to achieve

satisfaction (Steenkamp and Baumgartner 1992). Individuals differ in their perceived level

of ‘ideal’ stimulation, and will engage in exploratory behaviour in order to achieve their

ideal level of stimulation (Orth and Bourrain 2005; Steenkamp and Baumgartner 1992).

The role of experiential needs within this theory is in the delineation of the types of

stimulation and level of stimulation sought by the individual, as this will determine the

extent to which the individual engages in exploratory behaviour (Steenkamp and

Baumgartner 1992). Therefore, the individual’s experiential needs are an important factor

in explaining behaviour as it moderates the level of engagement facilitated in particular

environments (Steenkamp and Baumgartner 1992).

OSL theory is beneficial in the understanding of individual variations of facilitated

customer event engagement from particular BME experiences (Steenkamp and

Baumgartner 1992). The experiential needs of the individual have a moderating effect as

they influence the perceived relevance and attention given to certain stimuli, in this case

BME experiences (MacInnis and Jaworski 1989). The specific experiential needs

investigated in this thesis include need for cognition, need for affect and novelty-seeking

needs. These experiential needs were considered relevant to this thesis as each reflects key

motivations of customers identified in marketing events literature (Crompton and McKay

1997; Csikszentmihalyi 2000; Leischnig et al. 2011; Whelan and Wohlfeil 2006; Wohlfeil

and Whelan 2006). In addition, these experiential needs were consistently identified in

various consumer needs studies (Calder et al. 2009; MacInnis and Jaworski 1989; Orth and

Bourrain 2005; Steenkamp and Baumgartner 1992; Wilson 1997). It is expected that each

of these constructs influences the types of BMEs in which customer’s find value, and

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hence moderates the ability for event experiences to facilitate customer engagement. The

impact of consumer needs on customer engagement has not been empirically tested,

making this another contribution of this thesis.

While the potential moderating effect of a customer’s needs on customer engagement has

been noted in previous customer engagement research, little is known about the value of

this influence (Hollebeek 2011a). Individual-specific variables, for example the customer’s

need for cognition, are identified as potential moderators of customer engagement, as this

reflects the central themes of customer engagement being contextual in nature and driven

by the individual (Brodie et al. 2011a). As the experience during a BME is customer-

driven (Wohlfeil and Whelan 2006), it follows that their personal interests or needs will

influence their propensity to interact and engage with the various experiential components

of BMEs. It is expected that individuals who possess a strong experiential need (for

cognition, affect, or novelty-seeking) are more likely to elicit event engagement from

particular experiential components that align with or fulfil those needs (Higgins and

Scholer 2009). A greater understanding of the role of the individual’s experiential needs

will provide insight into why some BMEs are more effective at building customer

engagement with some groups of customers than with others (Crompton and McKay

1997).

Experiential needs delineate the various experiences individuals seek (Laurent and

Kapferer 1985; MacInnis and Jaworski 1989; Park and Young 1986). The experiential

needs of the individual impacts the perceived relevance and attention given to certain

experiences (MacInnis and Jaworski 1989), and therefore moderates the strength of the

relationship between particular BME experiences and customer event engagement

Research Question: Does an individual's experiential needs moderate the relationship between BME experiences and customer event engagement?

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(Steenkamp and Baumgartner 1992). The moderating effect of experiential needs has not

been investigated in customer engagement literature, and therefore is a contribution of this

thesis.

The broad framing of the following moderation hypotheses has been used because the

literature at this stage does not offer insight into particular moderator effects. Without a

clear theoretical foundation for such hypotheses, it was decided that an exploratory

approach be taken for this particular research question.

Need for cognition is broadly described as “the desire to be informed” (Wilson 1997, pg

553). Individuals with a high need for cognition find learning and acquiring new

knowledge enjoyable, and find great benefit in experiences that satisfy their curiosity about

topics of interest (Calder et al. 2009). Therefore, individuals who have a high need for

cognition are anticipated to engage in curiosity motivated behaviours (Steenkamp and

Baumgartner 1992), and find greater relevance in BME experiences that satisfy their need

for further learning, self-education or general curiosity (Calder et al. 2009). Following the

idea that ‘thinking is fun’ (Hallahan 2009), these individuals are more likely to interact

during cognitive BME experiences that are thought provoking, informative or educational,

which will facilitate customer engagement during the event. Need for cognition is

highlighted as a potential moderator of customer engagement, however has not been

investigated empirically (Brodie et al. 2011a).

Individuals with a high need for cognition are expected to elicit a stronger relationship

between cognitive experiences and customer event engagement. A cognitive experience

requires the participant to think and sparks interest through exchanging information and

knowledge (Gentile et al. 2007); individuals with a high need for cognition have a drive to

be informed, learn and acquire new knowledge (Calder et al. 2009), and therefore a

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cognitive experience is expected to satisfy their need for cognition (Packer and Ballantyne

2004).

Individuals with a high need for cognition could also facilitate a stronger level of customer

event engagement from pragmatic or relational BME experiences; for example, a relational

experience involving a wine-maker could involve sharing of information, or a pragmatic

experience such as the customer creating their own wine blend could teach them about

wine production. The individual’s need for learning and acquiring new knowledge is

satisfied from the information they receive through these relational and pragmatic

experiences (Calder et al. 2009), thus strengthening the relationship between these BME

experiences and customer event engagement.

Individuals with a low need for cognition are expected to display a weaker relationship

between cognitive BME experience and customer event engagement. These individuals do

not have a desire to learn and acquire new knowledge, and therefore will not elicit the

same level of interest or perceived the same relevance in experiences requiring them to

think, learn and exchange information (Gentile et al. 2007), and therefore the relationship

between cognitive experience and customer event engagement is reduced.


Hypothesis 5a: An individual’s need for cognition from an experience will moderate

the relationship between the BME experience and customer event engagement

Need for affect refers to an individual’s motivation to “approach or avoid situations and

activities that are emotion inducing for themselves and others” (Maio and Esses 2001, pg

585). People who possess a strong need for affect actively seek emotional experiences and

stimuli in various aspects of their lives (Sojka and Giese 1997). Therefore, customers

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attending a BME who have a high need for affect are expected to engage to a greater extent

in emotionally-driven experiences that provide entertainment, escape, aesthetic enjoyment

and/or emotional release (Calder et al. 2009).

Individuals with a high need for affect are anticipated to have a stronger relationship

between emotional experiences and customer event engagement. A central focus of

emotional experiences is evoking an affective response or positive mood in the individual

(Gentile et al. 2007), for example a winery picnic. For an individual with a high need for

affect, this type of event would fulfil their need for an emotionally-driven experience

providing entertainment, enjoyment and escape (Calder et al. 2009; Maio and Esses 2001)

and therefore facilitate a stronger relationship between emotional BME experience and

customer event engagement.

Individuals with a high need for affect could also exhibit a stronger relationship between

sensorial experiences and customer event engagement. A sensorial experience provides

sensory stimulation, for example wine and food pairing, and wine is often considered a

form of aesthetic consumption (Charters and Pettigrew 2005). This experience could fulfil

the individual’s high need for affect through providing aesthetic enjoyment, positive mood

and entertainment (Sojka and Giese 1997), therefore strengthening the relationship

between sensorial experience and customer event engagement.

Individuals with a low need for affect are expected to demonstrate a weaker relationship

between emotional BME experience and customer event engagement. These individuals do

not actively seek emotional experiences (Sojka and Giese 1997), and while they may find

an emotional experience pleasant, it does not specifically fulfil any desired need they

possess. Therefore, an emotional experience would have less ability to elicit a heightened

state as the customer does not perceive unique value from the experience (Brodie et al.

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2011a), and the relationship between emotional experience and customer event

engagement would be weaker for individuals with low need for affect.


Hypothesis 5b: An individual’s need for affect from an experience will moderate the

relationship between the BME experience and customer event engagement

Novelty-seeking is “the desire of the individual to seek out novel stimuli” (Hirschman

1980). People with a high need for novelty-seeking have a desire for experiences that

provide a change from routine, and include excitement, surprise and adventure (Lee and

Crompton 1992). They are variety seekers (Steenkamp and Baumgartner 1992) and

consider new experiences as a means of escape or to alleviate boredom (Lee and Crompton

1992). Therefore customers with a high novelty-seeking need are anticipated to find

enjoyment in any BME experience that is different to their usual experiences in everyday

life, providing variety and/or novelty.

Individuals with a high novelty-seeking need are anticipated to display a stronger

relationship between pragmatic and sensorial experiences and customer event engagement.

Pragmatic experiences involve physical activities or actions, and are likened to escapist

experiences (Gentile et al. 2007; Pine and Gilmore 1998), while sensorial experiences

provide sensory stimulation (Gentile et al. 2007). These experiences (for example a grape

stomp, or a wine and food pairing) are expected to involve activities that extend beyond the

individual’s normal day-to-day lives, and therefore fulfil the need for variety, novelty and

change from routine sought by individuals with a high novelty-seeking need (Lee and

Crompton 1992).

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These individuals will perceive a high level of value and fulfilment in pragmatic and

sensorial experiences (Steenkamp and Baumgartner 1992), and therefore strengthen the

relationships between pragmatic and sensorial experiences and customer event

engagement.

Individuals with low novelty-seeking needs are expected to elicit a weaker relationship

between pragmatic and sensorial experiences and customer event engagement. These

individuals are referred to as ‘novelty avoiding’ (Lee and Crompton 1992), and prefer

familiar or planned experiences. Therefore, pragmatic and sensorial BME components

which contain unfamiliar experiences extending beyond the individual’s normal activities

may be perceived by novelty avoiders as undesirable (Lee and Crompton 1992) or lacking

any perceived value. Therefore, a weaker relationship occurs between pragmatic and

sensorial experience and customer event engagement for individuals with low novelty-

seeking needs.


Hypothesis 5c: An individual’s novelty-seeking needs from an experience will moderate

the relationship between the BME experience and customer event engagement

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2.6 Hypotheses Summary

In summary, this thesis explores how experiential components of BMEs facilitate customer

engagement with the event and with the brand, and investigates the behavioural intention

of loyalty that result. The moderating effect of the individual’s experiential needs in the

relationship between BME experiential components and customer event engagement is

also investigated.

The hypotheses presented in this chapter are summarised in the following Table 2-6:

TABLE 2-6: SUMMARY OF HYPOTHESES

H# Hypothesis

1a Social event engagement is a dimension of customer event engagement

1b Social brand engagement is a dimension of customer brand engagement

2a Cognitive event experience contributes to customer event engagement

2b Cognitive event experience contributes to customer brand engagement

2c Emotional event experience contributes to customer event engagement

2d Emotional event experience contributes to customer brand engagement

2e Sensorial event experience contributes to customer event engagement

2f Sensorial event experience contributes to customer brand engagement

2g Pragmatic event experience contributes to customer event engagement

2h Pragmatic event experience contributes to customer brand engagement

2i Relational event experience contributes to customer event engagement

2j Relational event experience contributes to customer brand engagement

3 There is a positive relationship between customer event engagement and customer brand engagement

4a There is a positive relationship between customer event engagement and behavioural intention of loyalty

4b There is a positive relationship between customer brand engagement and behavioural intention of loyalty

5a An individual’s need for cognition from an experience will moderate the relationship between the BME experience and customer event engagement

5b An individual’s need for affect from an experience will moderate the relationship between the BME experience and customer event engagement

5c An individual’s novelty-seeking needs from an experience will moderate the relationship between the BME experience and customer event engagement

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These hypotheses capture how BME experiences facilitate customer event engagement and

customer brand engagement; the role of social engagement within the broader customer

engagement construct; the interplay between engagement objects (the event and the brand);

the behavioural intention of loyalty outcomes resulting from customer engagement at

BMEs; and the moderation effects of experiential needs (need for cognition, need for affect

and novelty-seeking needs) on the relationship between BME experiences and customer

event engagement. These relationships are presented in the following conceptual

framework.

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2.7 Conceptual Framework

The hypotheses are summarised in a conceptual framework (Figure 2-1). This illustrates

the ability for a BME, comprised of various experiential components, to facilitate customer

engagement with the event and with the brand. The individual’s experiential needs are

proposed to moderate the process of facilitating customer engagement, as fulfilment of

experiential needs is expected strengthen the relationship between BME experiential

components and customer event engagement. Customer event engagement is anticipated to

project onto the host brand, and lead to increased behavioural intention of loyalty.

FIGURE 2-1: CONCEPTUAL FRAMEWORK

There are three main theoretical contributions to this thesis. First, social exchange theory is

used to identify the resources provided by the organisation (i.e. the experiential

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components of the BME platform) and the reciprocated heightened psychological state of

engagement elicited by the customer as a result. This relationship has received little

academic attention, and contributes to knowledge by predicting the ability of a BME to

facilitate customer engagement. Second, the expected relationship between engagement

objects, namely the event and the brand, is explored. Associative network theory is used to

inform the interplay between engagement objects, specifically that engagement with the

event will be projected onto the brand. Third, it is posited that an individual’s experiential

needs will moderate the relationship between BME experiences and customer event

engagement. Optimum stimulation level theory provides insight into the various types of

stimulation individuals seek from particular environments, suggesting that the relationship

between BME experiences and customer event engagement is strengthened when an

individual’s experiential needs are fulfilled.

In addition, this thesis explores the role of a social engagement dimension within the

broader construct of customer engagement, which has been the focus of significant debate

in customer engagement research to date. The findings of this study will enable

practitioners to strategically design BMEs to more effectively engage their customers.

Managers can tailor their events to facilitate specific engagement outcomes and may

provide particular experiences that fulfil customer needs sought from an event.

Finally, this thesis contributes to customer engagement literature as it confirms and extends

previous research positing that customer engagement leads to BIL (So et al. 2012). This

relationship is supported by the theory of consumption values (Sheth et al. 1991), and

extends current knowledge through investigating the impact of the customer engagement

of two focal objects, the event and the brand, on BIL.

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This chapter provided an overview of extant literature to inform this thesis and identified

contributions of the study. First, customer engagement was introduced as the central

concept, with theoretical grounding in service-dominant logic. A conceptual understanding

and viewpoint of the researcher was provided regarding customer engagement

perspectives, definition of the construct, dimensions of customer engagement, related

concepts, antecedents and outcomes.

Branded marketing events, based on marketing events and customer experience literature,

was explained as the context and platform through which this thesis will investigate

customer engagement. As a method of facilitating customer engagement, it is important to

have an understanding of how organisations create a platform for customers to engage with

the organisation.

It was then posited that initial engagement with the BME would also trigger engagement

with the host brand. From this interplay between engagement objects it is expected that the

customer will elicit increased behavioural intention of loyalty.

Finally, the individual’s experiential needs were explored as a moderator in facilitating

customer engagement. It is anticipated that a customer is more willing to engage with

events that fulfil their need for cognition, need for affect and novelty-seeking.

Hypotheses were introduced and a conceptual framework outlined to explain the direction

of this thesis. The next chapter will explicate the data collection procedures and research

design approach taken in this thesis.

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Research Method Chapter

CHAPTER 3: RESEARCH METHOD


This chapter outlines the methodological approach used to collect data and test the

hypotheses presented in this thesis. First, the research design and unit of analysis adopted

is outlined. A description of the data collection method follows, with a focus on the

measurement instrument, and questionnaire design. Important considerations regarding the

operationalisation of constructs and measurement scales are discussed. Next, the pre-test

study including sample, data collection methods and procedures, and pre-test data analysis

are described. The main study follows, with an outline of participating winery and

individual respondent selection, respondent profiles and data collection methods.

Following data cleaning, the analyses undertaken to determine the reliability and validity

of the measures are presented.

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3.2 Research Design

A deductive research approach was taken to provide empirical evidence for proposed

relationships and causality between constructs (Neuman 2006). The research questions

established in the literature review were a result of identified gaps in theory; more

specifically gaps linking the constructs of BME experiential components, customer event

engagement, customer brand engagement, behavioural intention of loyalty, and moderation

effects of experiential needs. Therefore the approach of this thesis was to examine causal

relationships between constructs (Neuman 2006).

This thesis adopted a quantitative research approach, implementing a cross-sectional study

to obtain data at one point in time (post-event) by individuals who participated only once

in the study (Neuman 2006). A questionnaire was developed and distributed in two study

stages. Existing measures were used to represent each of the constructs, with minor

adaptation to suit the research contexts. A pre-test was conducted in the University sector.

This preliminary study served as a pilot study, and was used to conduct confirmatory factor

analysis and statistical testing of constructs. The questionnaire was modified on the basis

of these findings before the commencement of the next study. The main study was

conducted in the South Australian wine sector, from the McLaren Vale, Adelaide Hills and

Barossa Valley wine regions.

This thesis employs causal research utilising structural equation modelling (from here

referred to as SEM) to verify predictions with the data. SEM is a widely used and accepted

analysis technique of complete models (Kline 2011) in a variety of disciplines, and

particularly for those researching in the social sciences (Hooper, Coughlan, and Mullen

2008). SEM is also a widely used technique in leading marketing journals (Martínez-

López, Gázquez-Abad, and Sousa 2013). SEM takes a confirmatory approach to testing a

range of structural relationships simultaneously and, unlike other multivariate methods, can

estimate and correct for measurement error (Byrne 2001). In addition, this thesis includes 80 | P a g e


latent (unobservable) and measured variables; SEM has the ability to incorporate both

types of variables (Byrne 2001).

SEM analysis is an effective tool for theory testing and developing marketing models

(Steenkamp and Baumgartner 2000). This approach was chosen because engagement has

only recently been adopted in marketing literature (Vivek et al. 2012). Research on

customer engagement generally lacks empirical quantitative enquiry (see Table 2-1 in

Chapter 2) (Brodie et al. 2011b). As common conceptualisations of customer engagement

emerge, research must focus on empirically measuring the impact of customer engagement

and exploring a wider range of potential antecedents and outcomes to gain a

comprehensive understanding of the construct. Therefore, this thesis conducts quantitative

research to investigate customer engagement, and contributes to the empirical justification

of its operationalisation, antecedents (experiential components of BMEs) and outcomes

(behavioural intention of loyalty).

3.3 Unit of analysis

As this thesis endeavours to understand the impact of event experiences on the individual

customer, the unit of analysis is the individual who attended the event. This distinction is

key in framing the entire thesis with regards to preferred respondents, sample size, and

frame of reference taken in the survey design (Neuman 2006). This unit of analysis is also

consistent with the theoretical underpinning of this thesis; the S-D logic, as it regards

customer-brand experiences as interactive and individually driven and interpreted (Vargo

and Lusch 2008). In addition, it is recognised that each experiential component of the BME

is not mutually exclusive; one event may include a number of different experiential

components, and again this perception is derived from the individual (Gentile et al. 2007).

Therefore, in conducting this thesis, it was paramount that the perceived experience and

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3.4 Data Collection Method

3.4.1 Measurement Instrument

This thesis used self-administered questionnaires, predominantly through online surveys

administered using Qualtrics software. An online survey was deemed the most appropriate

for this thesis for a number of reasons. First, online surveys are a more time and cost

efficient data collection method (Denissen, Neumann, and Zalk 2010); once the survey is

developed, it is easy to distribute to a large number of people. Furthermore, large samples

can be obtained in a short amount of time, and with little manual work needed from the

researcher (Denissen et al. 2010). This was particularly important for this thesis as both the

pre-test and main study were conducted at various events. An online data collection

method enabled easy replication of the survey for different events, timely delivery of the

survey to respondents immediately following the event, and the elimination of transcription

errors, all of which save time in data preparation for analysis (Fricker Jr and Schonlau

2010).

Common limitations of online surveys, for example the perception of the survey being

‘spam’ leading to low response rate and problems with sample coverage (Denissen et al.

2010; Fricker Jr and Schonlau 2010; Vicente and Reis), is mitigated by the researcher

attending the majority of the events to obtain emails addresses from attendees. The

researcher was given the opportunity to explain the nature of the study, ask for consent

from the respondents, and provide information regarding survey distribution and incentives

to participate. This also ensured that surveys were only being sent to relevant respondents;

those who attended the specific events.

Self-administered questionnaires were sent to respondents immediately following the

event; the data collection period was two weeks following the event, which allowed for

follow-up reminder emails to those who had not started the survey, and those who had only

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partially completed the survey. The decision to apply a self-administered questionnaire

design after the event experience was made for a number of reasons. The surveys were

completed at the respondent’s convenience (Neuman 2006) and therefore did not interrupt

their event experience. This was also at the request of the host brands, who wanted

minimal disruption to attendees during the event. In addition, this method ensured the

researcher did not influence the results through social desirability bias (Neuman 2006).

Similar approaches of making contact with participants during an event and requesting

they complete the questionnaire post-event are common in a number of marketing events

studies (e.g. Crompton and McKay 1997; Lee, Sandler, and Shani 1997).

3.4.2 Operationalistion of the Theoretical Constructs

This section introduces the measures used to operationalise each construct from the

literature. Existing measures were used for all constructs; often there were a variety of

alternative measures within each body of literature, therefore the most appropriate and

comprehensive measurement scale was selected. Minor modifications were made to

existing scales to create linguistic style consistency and ensure their applicability to the

new research context (Brakus et al. 2009), while still maintaining their original meaning. A

number of existing scales, for example experiential components, had been previously

designed for studies that focused on the customer’s experience with a product (Gentile et

al. 2007) or with reference to experiential product-centric brands (Brakus et al. 2009).

However, as this thesis explored experience and engagement at events they were adapted

to reflect this characteristic.

The survey was adapted for two different contexts; a pre-test held in the University sector

(a student-sample) followed by the main study held in the South Australian Wine sector.

Student samples are often argued to lack generalisability; however, when they encompass

an applicable population of interest or share a theoretically relevant commonality student

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samples are considered appropriate (Randall and Gibson 1990). The focus of this thesis

was to capture the experiences and perceptions of event attendees, and as the student

sample had all attended a University event, they were deemed an appropriate study sample.

3.4.3 Measurement Scales

The main constructs of importance for this survey were experiential components; event

engagement; brand engagement; behavioural intention of loyalty; and experiential needs

(need for cognition, need for affect and novelty-seeking needs). Theoretical constructs

were operationalised for this questionnaire using established measures from literature

(Brakus et al. 2009; Calder et al. 2009; Chang and Chieng 2006; Hallahan 2009; Lee and

Crompton 1992; Maio and Esses 2001; So et al. 2012; Sojka and Giese 1997; Sweeney and

Soutar 2001).

An objective indication of experiential components was not of concern, rather it was

important to capture the attendee’s individual perception of the event experience to

determine whether engagement was achieved, and whether the type of experience aligned

with that individual’s experiential needs. A close examination of the literature suggests that

the main components of an experience are cognitive, emotional, sensory, pragmatic and

relational (Gentile et al. 2007). Many studies used various sub-sets and combinations of

these components, commonly reflecting the sensorial, emotional and cognitive components

of experience (Brakus et al. 2009; Chang and Chieng 2006; Gentile et al. 2007; Sahin et al.

2011; Schmitt 1999; Tynan and McKechnie 2009; Yuan and Wu 2008). However, it was

determined that Gentile et al.’s (2007) conceptualisation was robust and comprehensive,

with attention also given to social/relational elements (Chang and Chieng 2006; Schmitt

1999; Tynan and McKechnie 2009) as well as behavioural or ‘pragmatic’ components

(Brakus et al. 2009; Chang and Chieng 2006; Sahin et al. 2011; Schmitt 1999).

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While Gentile et al.’s (2007) conceptualisation of experiential components was

implemented in this thesis, their study context was highly product-centric and their

measurement items were difficult to replicate in the context of this thesis. Chang and

Chieng’s (2006) measures were used instead, as their study followed a similar

conceptualisation of experiential components to Gentile et al. (2007) and was conducted in

coffee stores, hence their items were easier to apply to the context of this thesis with only

minor rewording (from ‘coffee store’ to ‘event experience’). Chang and Chieng’s (2006)

experience measure only includes three items per experiential component. Three items

were reported as having item to total coefficient values below 0.5 in one study context,

which suggests that these items did not significantly contribute to the reliability of the

construct (Chang and Chieng 2006). Each of the experience measures were therefore

supplemented with additional items to account for any item quality issues, as a minimum

of three items per construct are required to run a congeneric measurement model (Hair,

Black, Babin, and Anderson 2012). The cognitive, sensorial, emotional and pragmatic

experiences were supplemented with items from Brakus et al. (2009), and relational

experience was supplemented with items from Sweeney and Soutar (2001).

Customer engagement is an emergent literature area; research to date has focused

predominantly on conceptual development (Brodie et al. 2011a). Measures capturing

elements of customer engagement are limited, for example ‘brand engagement in self-

concept’ (Sprott et al. 2009) and Calder, Isaac, and Malthouse’s (2013) measures for

engagement. Neither of these measures reflect the commonly accepted dimensions of

customer engagement (Brodie et al. 2011a) and is not consistent with the conceptualisation

of engagement taken in this thesis.

The five dimension conceptualisation of customer engagement from So et al. (2012) and

their subsequent measures were found most applicable to this thesis; these measures

capture the commonly accepted three dimensions of customer engagement (Brodie et al.

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2011a), while extending this view to investigate a broader and more comprehensive idea of

customer engagement. In addition, these measures were used in a hospitality and tourism

context of service encounters (So et al. 2012); therefore the measures were easily

replicable to fit the context of this thesis.

A major contribution of this research is the investigation of engagement from both an event

and brand perspective, to explore the relationship between two engagement objects in the

one study. Gwinner and Eaton’s (1999) study on brand image transfer explored this

process by replicating the same set of items, first phrased to describe the particular events

and then reworded to describe the brand. Image transfer was confirmed when very similar

responses were indicated for event image and brand image (Gwinner and Eaton 1999).

Drengner et al. (2008) used the same technique, replicating the same items to identify

image transfer from the event to the brand. Therefore, for this thesis the same engagement

measures were used twice; first to reflect engagement during an event, and then reworded

to capture engagement with the brand. This required careful consideration of the rewording

of items so that the ‘event engagement’ items consistently referred to the ‘event’ or implied

engagement within the event experience, while the ‘brand engagement’ items were clearly

distinguished to capture engagement occurring with the brand (Brakus et al. 2009).

Respondent instructions were also included at the beginning of the customer event

engagement and customer brand engagement items to ensure that participants understood

and differentiated between the repeated questions (Hair, Lukas, Miller, Bush, and Ortinau

2008).

There is significant debate within the engagement literature of the existence and

conceptualisation of social engagement; some discuss social engagement as a separate

dimension (Calder et al. 2009; Vivek et al. 2012), while others maintain that social

engagement is a subset within affective engagement (Brodie et al. 2011a). Measurement

items from Calder et al. (2009) were included to capture social event engagement and

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social brand engagement. While social engagement has been introduced in other literature

areas, for example social psychology (Achterberg, Pot, Kerkstra, Ooms, Muller, and Ribbe

2003; Glass, De Leon, Bassuk, and Berkman 2006; Huo, Binning, and Molina 2009),

Calder et al. (2009) investigated customer engagement arising from experiences, and was

therefore utilised in this thesis. Calder et al. (2009) provide a different conceptualisation of

customer engagement which includes a social-interactive engagement element;

‘community’ and ‘participation and socialising’ are identified as the two dimensions of

social-interactive engagement (Calder et al. 2009). The majority of items for community

and participation and socialising were used in this thesis; however, three items were highly

specific to the online context investigated in Calder et al.’s (2009, pg 325) study and were

not applicable to the BME context, for example, “I often feel guilty about the amount of

time I spend on this site socializing”.

The ‘behavioural intention of loyalty’ measure (So et al. 2012), encompassing word of

mouth and purchase intention was utilised in this thesis; these four key items implemented

in So et al.’s (2012) study is based on Zeithaml et al. (1996), an extensively cited and

replicated measure. The shortened version of this measurement scale from So et al. (2012)

was considered appropriate for this thesis due to the conceptual relevance of the included

constructs (word of mouth and purchase intention) with regards to customer engagement

literature; the additional constructs captured in Zeithaml et al.’s (1996) scale (price

sensitivity and complaining behaviour) were not consistent with expected customer

engagement outcomes (Fehrer et al. 2013) and hence were not included in this thesis.

The individual’s experiential needs were reported using well-established and highly

replicated measures, mainly from psychology literature. A consolidated version of the need

for cognition scale (Cacioppo, Petty, and Kao 1984) from Hallahan (2009) was used in this

thesis.

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Hallahan’s (2009) study investigated need for cognition as a moderator between the level

of thinking and attention a customer gives to information in advertising. The role of need

for cognition in Hallahan’s (2009) study is consistent with how the construct is considered

in this thesis; need for cognition is an individual differences variable (in this thesis,

experiential need) which moderates the amount of thinking (in this thesis, event attention)

a customer elicits towards particular information (in this thesis, cognitive BME

experience). Hallahan’s (2009) results indicated that, of the completed need for cognition

scale, one factor consisting of nine items emerged as the predominant factor influencing

the customer’s level of thinking and attention of advertising information; those items were

therefore implemented in this thesis.

Elements of the novelty-seeking scale from Lee and Crompton (1992) were implemented

as the paper was conducted in a similar study context (tourism) and has been shown to be

robust. This paper investigated novelty from multiple dimensions; thrill, change from

routine, boredom alleviation and surprise (Lee and Crompton 1992). However, to reduce

the 21 item scale, only the change of routine dimension was implemented as these items

were perceived to have the most applicability to the context of this thesis. In addition, only

four of the change of routine items (of nine) were used, as the remaining items were not

easily transferable to this study context (for example ‘I want to experience customs and

cultures different from those in my own environment on vacation’; ‘I like to travel to

adventurous places’), and also reported comparatively lower factor score weights

compared to the items implemented (Lee and Crompton 1992).

Finally, the individual’s need for affect was reported using measures from Sojka and Giese

(1997) and Maio and Esses (2001). There are varying perspectives and numerous scales to

measure affect (Sojka and Giese 1997); for this thesis items were selected that were

perceived to address situations or experiences where need for affect influenced the

individual’s perceptions (e.g. when I recall a situation, I usually recall the emotional

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aspects of the situation). Items with less applicability to the context of this thesis were not

included in the questionnaire (e.g. I’m good at empathising with other people’s problems; I

enjoy trying to explain my feelings – even if it’s only to myself) (Sojka and Giese 1997).

The four selected items were supplemented with an additional two items from Maio and

Esses (2001) that also made reference to emotional experiences or situations (I feel that I

need to experience strong emotions regularly; I approach situations in which I expect to

experience strong emotions).

In summary, the previous discussion highlights the process taken to select robust measures

to represent each of the constructs identified in this thesis, while also attempting to shorten

the survey length to avoid confusion or frustration among the participants (Hair et al.

2012). Each of the constructs and their related measures are described in the following

Table 3-1. Some measurement items were slightly modified to suit the context of the study;

this is a common method to achieve strong relevance and applicability of the measures

(e.g. Algesheimer et al. 2005; Hightower, Brady, and Baker 2002).

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TABLE 3-1: MEASUREMENT OF CONSTRUCTS Scale (Reference) Item Final Measure (modified for this thesis) Cognitive Experience (Chang and Chieng 2006)

EXP_COG1 This event tried to intrigue me EXP_COG2 This event tried to stimulate my curiosity EXP_COG3 This event appealed to my creative thinking

Emotional Experience (items 1, 2 and 3 from Chang and Chieng 2006) (items 4, 5 and 6 from Brakus et al. 2009)

EXP_EMO1 This event tried to put me in a certain mood EXP_EMO2 This event tried to be emotional EXP_EMO3 This event tried to arouse feelings in me EXP_EMO4 This event induced feelings and sentiments EXP_EMO5 I had strong emotions at this event EXP_EMO6* This event was an emotional event

Sensorial Experience (Chang and Chieng 2006)

EXP_SEN1 This event was focused on creating a sensory experience EXP_SEN2 This event tried to excite my senses EXP_SEN3 This event provided sensory enjoyment

Pragmatic Experience (items 1, 2, and 3 from Chang and Chieng 2006) (items 4, 5 and 6 from Brakus et al. 2009)

EXP_PRAG1* This event tried to remind me of activities I can do EXP_PRAG2* This event got me to think about my behaviour EXP_PRAG3* This event made me think about my lifestyle EXP_PRAG4 I engaged in physical actions and behaviours when I attended

this event EXP_PRAG5 This event was action oriented EXP_PRAG6 This event involved physical experiences

Relational Experience (Sweeney and Soutar 2001)

EXP_REL1* Attending this event helped me to feel accepted EXP_REL2 Attending this event improved the way I am perceived EXP_REL3 Attending this event made a good impression on other people EXP_REL4 Attending this event gave me social approval EXP_REL5 Attending this event created a favourable perception of me

among other people EXP_REL6* This event had a positive social image

Event Attention (So et al. 2012)

ATT_EVENT1* I liked learning about this event ATT_EVENT2 I paid a lot of attention at this event ATT_EVENT3 Anything related to this event grabbed my attention ATT_EVENT4 I concentrated a lot during this event

Event Identification (So et al. 2012)

ID_EVENT1 When someone criticises this event, it feels like a personal insult ID_EVENT2 When I talk about this event, I usually say ‘we’ rather than

‘they’ ID_EVENT3 This event’s successes are my successes ID_EVENT4 When someone praises this event, it feels like a personal

compliment Event Enthusiasm (So et al. 2012)

ENTH_EVENT1* I was enthusiastic about this event ENTH_EVENT2 I was heavily into this event ENTH_EVENT3 I was passionate about this event ENTH_EVENT4 I felt excited about this event ENTH_EVENT5 I loved this event

Event Absorption (So et al. 2012)

AB_EVENT1* When I was taking part in this event, I forgot everything else around me

AB_EVENT2 Time flew when I was taking part in this event AB_EVENT3* When I was taking part in this event, I got carried away AB_EVENT4* When I was taking part in this event, it was difficult to detach

myself AB_EVENT5 When I was taking part in this event, I was immersed AB_EVENT6 When I was taking part in this event intensely, I felt happy

Event Interaction (So et al. 2012)

INT_EVENT1 I liked getting involved in discussions at this event INT_EVENT2 I enjoyed interacting with like-minded others at this event INT_EVENT3 I liked actively participating in discussions at this event INT_EVENT4 I thoroughly enjoyed exchanging ideas with other people during

this event INT_EVENT5* I frequently participated in activities during this event

* item was removed during construct analysis and pre-testing

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Scale (Reference) Item Final Measure (modified for this thesis) Social Event Engagement (Calder et al. 2009)

SOC_EVENT1* This event did a good job of getting its attendees to contribute or provide feedback

SOC_EVENT2* I liked meeting other people who attended this event SOC_EVENT3 I’ve gotten interested in things I otherwise wouldn’t have

because of other attendees at this event SOC_EVENT4 I was as interested in input from other attendees as I was in

information provided by organisers during this event SOC_EVENT5 A big reason I liked this event is what I got from other attendees SOC_EVENT6* I did quite a bit of socialising at this event SOC_EVENT7* I contributed to conversations at this event

Brand Attention (So et al. 2012)

ATT_BRAND1* I like learning about X Winery ATT_BRAND2 I pay a lot of attention to anything about X Winery ATT_BRAND3 Anything related to X Winery grabs my attention ATT_BRAND4 I concentrate a lot on X Winery

Brand Identification (So et al. 2012)

ID_BRAND1 When someone criticises X Winery, it feels like a personal insult ID_BRAND2 When I talk about X Winery, I usually say ‘we’ rather than

‘they’ ID_BRAND3 X Winery’s successes are my successes ID_BRAND4 When someone praises X Winery, it feels like a personal

compliment Brand Enthusiasm (So et al. 2012)

ENTH_BRAND1* I am enthusiastic about X Winery ENTH_BRAND2 I am heavily into X Winery ENTH_BRAND3 I am passionate about X Winery ENTH_BRAND4 I feel excited about X Winery ENTH_BRAND5 I love X Winery

Brand Absorption (So et al. 2012)

AB_BRAND1* When I am interacting with X Winery, I forget everything else around me

AB_BRAND2 Time flies when I am interacting with X Winery AB_BRAND3* When I am interacting with X Winery, I get carried away AB_BRAND4 When interacting with X Winery, it is difficult to detach myself AB_BRAND5 In my interaction with X Winery, I am immersed AB_BRAND6 When interacting with X Winery intensely, I feel happy

Brand Interaction (So et al. 2012)

INT_BRAND1 I like to get involved in discussions about X Winery INT_BRAND2 I enjoy interacting with like-minded others about X Winery INT_BRAND3 I like actively participating in discussions about X Winery INT_BRAND4 I thoroughly enjoy exchanging ideas with other people about X

Winery INT_BRAND5* I frequently participate in activities related to X Winery

Social Brand Engagement (Calder et al. 2009)

SOC_BRAND1* X Winery does a good job of getting people to contribute or provide feedback

SOC_BRAND2* I like meeting other people who enjoy X SOC_BRAND3 I’ve gotten interested in things I otherwise wouldn’t have

because of other X Winery consumers SOC_BRAND4 I’m as interested in what others think about X Winery as I am in

more formal information about X SOC_BRAND5 A big reason I like X Winery is what I get from talking to others

about the wine SOC_BRAND6* I do quite a bit of socialising that relates to X Winery SOC_BRAND7* I contribute to conversations about X Winery

Behavioural intention of loyalty (So et al. 2012)

BIL_BRAND1 I would say positive things about X Winery to other people BIL_BRAND2 I would recommend X Winery to someone who seeks my advice BIL_BRAND3 I would encourage friends and relatives to purchase X Wines BIL_BRAND4 I would purchase X wines in the future

* item was removed during construct analysis and pre-testing

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Scale (Reference) Item Final Measure (modified for this thesis) Novelty-seeking needs (Lee and Crompton 1992)

NEED_NOV1 I like to find myself at destinations where I can explore new things

NEED_NOV2 I want to experience new and different things NEED_NOV3 I enjoy the change of environment which allows me to experience

something new NEED_NOV4* My ideal experience involves looking at things I have not seen

before Need for affect (items 1, 2, 3 and 4 from Sojka and Giese 1997) (items 5 and 6 from Maio and Esses 2001)

NEED_AFF1* I'm more of a "feeler" than a "thinker" NEED_AFF2* When I recall a situation, I usually recall the emotional aspects of

the situation NEED_AFF3* I prefer a task that is emotional and important to a task that is

intellectual and important NEED_AFF4 Emotion excites me NEED_AFF5 I feel that I need to experience strong emotions regularly NEED_AFF6 I approach situations in which I expect to experience strong

emotions Need for cognition (Hallahan 2009)

R_NEED_COG1* Thinking is not my idea of fun R_NEED_COG2 I would rather do something that requires little thought than

something that is sure to challenge my thinking abilities R_NEED_COG3 I try to anticipate and avoid situations where there is a likely

chance I will have to think in depth about something R_NEED_COG4 I only think as hard as I have to R_NEED_COG5 Learning new ways to think doesn't excite me very much R_NEED_COG6* It’s enough for me that something gets the job done: I don’t care

how or why it works R_NEED_COG7 I prefer to think about small, daily projects to long-term ones R_NEED_COG8 I like tasks that require little thought once I have learned them R_NEED_COG9* I feel relief rather than satisfaction after completing a task that

required a lot of mental effort * item was removed during construct analysis and pre-testing

3.4.4 Questionnaire Design

This section outlines the format of the questionnaire and the theoretical basis for its

development. The questionnaire is included in Appendix A-1. The questions were designed

to be easily understood by participants without assistance from the researcher. For this

reason, several measurement items were slightly modified to enhance understanding in the

context in which they were being completed. Detailed explanations and examples were

also included to accompany the questions and ensure understanding from the participants.

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3.4.4.1 Scaling

All constructs were measured using likert type scales, with seven response options. Likert

style questions are relatively easy to construct and administer and are readily understood

by respondents, making them particularly suitable for a self-administered questionnaire

(Hair et al. 2008). All established measures utilised in this thesis had been previously

implemented using a likert scale structure (Brakus et al. 2009; Chang and Chieng 2006;

Hallahan 2009; Lee and Crompton 1992; Maio and Esses 2001; So et al. 2012; Sojka and

Giese 1997; Sweeney and Soutar 2001).

Seven point response formats are commonly used in well-developed measures as to ensure

sufficient scale variance, which is particularly important for conducting SEM (Noar 2003).

Scales that extend beyond seven points will provide little benefit for analysis or scale

variance (Noar 2003). A seven point scale was also common in the established measures

implemented in this thesis (Brakus et al. 2009; So et al. 2012; Sweeney and Soutar 2001).

Therefore, all constructs in this thesis were measured using a seven point likert scale

ranging from (1) strongly disagree, (4) neither agree nor disagree, to (7) strongly agree.

The inclusion of a neutral response choice in scale development is often debated (Hair et

al. 2008; Neuman 2006). A forced-choice scale, one that does not have a neutral response

option, may result in lower-quality data as some respondents may lack knowledge or

experience of a given topic and are unable to accurately respond to the question (Hair et al.

2008). However, a free-choice scale, one that includes a neutral response option, may

provide an easy option for respondents who are indecisive or do not want to reveal their

true feelings (Hair et al. 2008). Although there are arguments for and against providing an

odd number of response options (Neuman 2006), this thesis provided a neutral midpoint (4

– neither agree nor disagree) to allow for those who were genuinely undecided, as opposed

to forcing an opinion.

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3.4.4.2 Questionnaire Content

The questionnaire was designed to capture the perceived experiences of the participant

during the BME and its ability to facilitate customer event engagement and customer brand

engagement. The questionnaire also created a profile of the respondent’s experiential needs

with regards to cognition, affect, and novelty-seeking. There were no qualifying questions

throughout the questionnaire; all respondents were asked to complete all sections.

Respondent instructions were provided extensively throughout to ensure the respondent

had a high level of understanding (Hair et al. 2008). This is particularly important for

online surveys as they are self-administered and provide no way for respondents to ask

questions or clarify the requirements of the survey (Hair et al. 2008). The sequence in

which these concepts were presented to the respondents is outlined in the following

section.

3.4.4.3 Questionnaire Structure and Sequencing

Introduction – The introduction screen included a brief outline of the research project and

a summary of questionnaire content (Hair et al. 2008), and a description of the opportunity

to win an incentive to increase the respondent’s motivation to complete the survey

(Denissen et al. 2010; Hair et al. 2008). Participants were instructed that questions pertain

to one specific event, not numerous events they may have attended. Included in the

introduction were explicit directions instructing respondents to answer all questions even if

some appeared similar or abstract. This was emphasised, as multi-item measures were used

for each construct; repetition may cause confusion for the participant (Hair et al. 2008). A

force-response logic was used on all questions with the online medium, to ensure

respondents did not skip over particular items. Screen breaks were also placed in the

questionnaire to limit the number of questions per screen; similar-sounding questions were

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not on the same page, reducing the level of confusion for the participant (Toepoel, Das,

and Soest 2009).

Event experiences – measures representing each of the five components of experience

were presented first to establish the perceived type of BME experience encountered by the

respondent. Specific instructions preceded each section, and examples of ‘experience’

types were given to ensure items were understood. For example, the cognitive experience

items were introduced by explaining that this type of experience includes any components

of the event that made the participant think, intrigued them, or made them want to seek

further information.

Customer event engagement – items for each of the five engagement dimensions

(attention, absorption, enthusiasm, interaction, identification) were then presented to

capture the respondent’s level of engagement during the event experience. It was reiterated

throughout this section that the items related to the event in question, not about the

participant’s perceptions of this style of event in general, or previous events held by the

brand. The respondent instructions indicated that the questions referred to their interactions

and behaviours during the event, and were asked to answer the questions only about the

event in question.

Customer brand engagement - This section was sequenced to follow event engagement

measures as both originated from the same measure and therefore had very similar

wording. It was important to present the event-related questions first to establish event

engagement before investigating any engagement with the brand. In this section the

questions were framed towards the brand as opposed to the event experience – respondents

were notified that the questions would appear similar but that it was part of the design.

Behavioural intentions of loyalty – measures representing the respondent’s behavioural

intention of loyalty, encompassing word of mouth and brand purchase intention were

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presented in this section. These items were the final brand-specific questions of the survey,

and were placed after the customer brand engagement measures while the reported

recollections of the brand were still in the participant’s mind and therefore easy to answer.

Experiential needs – measures capturing the respondent’s levels of need for cognition,

need for affect and need for novelty were included to determine the respondent’s levels of

experiential needs. This section required participants to answer questions directly related to

their own personal needs and predispositions to particular kinds of activities/experiences. It

was considered appropriate to have these questions follow the event and brand constructs

as to not distract the respondent from thinking about their event experience. These

questions are also very specific to the individual, and more personal and self-reflective in

nature; therefore these items were placed towards the end of the survey to indicate a

‘transition phase’ (Hair et al. 2008). This communicated to the respondent that the nature

of the questions were about to change from brand focused to more individual-specific

information (Hair et al. 2008).

Demographics – questions of age and nationality were included at the end of the

questionnaire. This section was included last as personal information can often be

considered threatening or uncomfortable by respondents and creates a perception of non-

anonymity (Hair et al. 2008). Events that ran on multiple days also included a question

asking them to specify the specific date/event they attended. Participants could choose if

they wanted to enter the prize draw by leaving their name and email address at the end of

the questionnaire; this was placed at the end of the survey to ensure only respondents who

completed the survey could enter the draw.

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3.4.5 Ethics and Information Confidentiality

This thesis had ethics approval granted by the University of Adelaide Human Research

Ethics Committee (Appendix A-2). Participants were assured confidentiality of their

responses and personal information in the introduction to the survey. The nature and

purpose of the research was expressed to participants before asking for their consent to

participate; it was emphasised that the study was undertaken by a PhD candidate at

University of Adelaide to assure participants that the research was not a commercial

venture, nor would their information be given to any third party. The participants were

advised that their information (email address) would only be used to the purpose of

contacting them with the survey and to notify them if they won the completion incentive.

3.4.6 Data Coding and Editing

The data received was prepared through Qualtrics online survey software – question items

were automatically coded, and a response ID assigned to each participant. These codes

were later modified for readability. Non-responses were automatically coded in SPSS as a

full stop (Pallant 2010). A number of items were negatively worded in the original survey;

these variables were reverse-coded using SPSS21 before data analysis commenced.

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3.5 Pre-Test: University of Adelaide Orientation Week

3.5.1 Overview

The main objective of the pre-test was to determine the length of time taken to complete

the survey online and to run preliminary factor analysis to assess the validity of the

selected measures. In particular, experiential components were measured using items from

Chang and Chieng (2006) and Brakus et al. (2009); factor analysis would identify

unnecessary items that could be excluded from the main study. The pre-test was conducted

in the University sector, the details of which are described in this section.

3.5.2 Subjects

The University of Adelaide Orientation Week (from here referred to as ‘O-Week’) was

considered an appropriate platform from which to run a pre-test of the study and validate

the measurement instrument. Students attended a wide variety of events including

information sessions, University support lectures, social events, barbeques, which allowed

the researcher to investigate a range of experiences.

University of Adelaide students who attended an event during O-Week was determined as

the sampling frame as it allowed a large number of individuals attending a range of

different O-Week events to be surveyed. These students were from various disciplines,

were commencing or continuing students, and studying at an undergraduate or

postgraduate level. Respondents from a number of different events were approached (see

Table 3-2). Equivalent questionnaires were distributed to all respondents; participants were

asked to indicate the event they attended at the beginning of the questionnaire.

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3.5.3 Sample and Respondent Profile

A purposive or judgment sampling approach was used, whereby the researcher uses

subjective information, in this case location/attendance of an event, to identify the sample

for inclusion in the study (Neuman 2006). The researcher attended preliminary lectures,

information sessions, and the Student barbeque event and distributed fliers that outlined the

study and contained the online survey URL. The qualifying dimension relevant to survey

participants was attendance to an O-Week event, and these participants were approached

with survey fliers during an event, thus already achieving that qualifier.

The researcher attended 10 events held at O-Week which ran over five days, and obtained

a total of 223 responses. A limitation of this pre-test is the likelihood of students attending

more than one event, and this distorting their responses. To mitigate this, the participant

was instructed at the beginning of the survey to identify one event they had attended and to

answer all survey questions with reference to that event. They were reminded of this

throughout the survey. Also, respondents were asked to indicate the total number of O-

Week events they had attended. The following Table 3-2 indicates the types of events

attended by students, and the number of responses specifically on each event type.

TABLE 3-2: O-WEEK EVENTS PROFILE

Event Number of Respondents % of Total Responses

Adelaide University Union activities 7 3

Tours 10 5

Hub Day Out barbeque* 90 40

Welcome Sessions (faculty/school) 12 5

Doing Uni information session 9 4

Marketing introduction lecture* 25 11

Information /help sessions 8 4

Reality Bites 36 16

O'meet 3 2

Trial Lectures 23 10

Total 223 100%

* indicates events in which surveys were distributed in person

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3.5.4 Data Collection Procedure

Data was collected both online (after the event) and with a paper survey (during the event).

Both approaches have been implemented in previous event studies, e.g. post-event

(Crompton and McKay 1997; Lee et al. 1997) and during the event (Close et al. 2006;

Leischnig et al. 2011).

Online surveys were preferred due to increased convenience for the participant who could

complete the survey in their own time (Neuman 2006), and easy replication of the survey

for different events (Fricker Jr and Schonlau 2010). In addition, this data collection

procedure was often at the request of the O-Week organisers, as there was available little

time in the sessions to complete the questionnaire.

Self-complete paper surveys were also distributed to students to complete during the Hub

Day Out barbeque and at the end of the marketing introduction session (see Table 3-2).

The barbeque was an informal event running for two hours where students had enough

time to participate in the survey; the marketing introduction session finished ten minutes

early and willing participants were asked to stay and complete the survey sheet before

leaving the lecture.

The questionnaire was expected to take approximately fifteen minutes to complete online,

and an incentive of one iPad Mini was provided to encourage participation (Denissen et al.

2010; Hair et al. 2008). All participants who completed the questionnaire went into the

draw to win the prize.

3.5.5 Pre-test Data Analysis

A major finding of the pre-test was that the survey was too long. It is recommended that

online surveys take no longer than 15 minutes, as lengthier surveys may result in a

decreased completion rate and compromise response validity (Rea and Parker 2012).

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However, Qualtrics survey software reported a duration trimmed mean of 31 minutes for

participants to complete the online survey (a trimmed mean factors in respondents who had

left and re-entered the survey). Approximately 64 participants exited the survey part way

through, an approximate completion rate of 78% (223 completed responses from 287).

Therefore, serious consideration was given to removing unnecessary items during

preliminary analysis.

Factor Analysis was conducted to establish validity and reliability of the measures included

in the pre-test survey. The pre-test included multiple measures for each experiential

component to ensure each construct was adequately captured; measures from Chang and

Chieng (2006) and Brakus et al. (2009) were used to investigate cognitive, emotional,

sensorial and pragmatic experience, while measures from Chang and Chieng (2006) and

Sweeney and Soutar (2001) explored relational experience (as Brakus et al. 2009 did not

measure relational experience).

Testing of constructs indicated that the additional items from Brakus et al. (2009) enhanced

the reliability of the emotional and pragmatic experiential constructs, and therefore all

items were included in the main study (see Appendix A-3). However, the Brakus et al.

(2009) measures did not enhance the reliability of the cognitive and sensorial measures,

and therefore only the Chang and Chieng (2006) items were included in the main study.

The relational experience items from Sweeney and Soutar (2001) achieved strong

reliability; inclusion of the two items from Chang and Chieng (2006) did not increase the

reliability of the construct and were therefore removed from the main study. A list of the

items changes in the pre-study versus the main study, and a summary of reliability values

are provided in Appendix A-3.

As previously discussed in Chapter 2, the conceptualisation of engagement presented by

So et al. (2012) identifies a five dimension construct; however, this thesis had originally

followed a three dimension conceptualisation, consistent with extant literature on customer

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engagement (Brodie et al. 2011a). The pre-test survey only included items that aligned

with the three predominant dimensions of engagement; So et al.’s (2012) attention and

enthusiasm measures were used in the pre-test to capture cognitive and emotional

dimensions of engagement, while participation measures (Chan, Yim, and Lam 2010) were

used to investigate behavioural engagement. However, upon further reflection and

exploration of the customer engagement literature, the researcher decided that the

expanded five dimension view of customer engagement had great applicability to the event

context, and provided an additional element to the study; to question and investigate the

dimensionality of customer engagement. This five dimension framework still included the

commonly used three dimensions of engagement, with an additional two elements; this

meant that the dimensionality of engagement could be compared in further research. The

researcher also decided that for completeness of replication of So et al.’s (2012)

dimensions of engagement, the participation measures would be replaced with So et al.’s

(2012) interaction measures. In brief, the researcher recognised these oversights after the

pre-test, and decided that the benefit of making these changes to the main study

outweighed the limitations of having a consistent survey in the pre-test and main study.

Calder et al.’s (2009) social engagement measures, and the need for cognition, novelty-

seeking and need for affect measures all achieved reliability and remained in the survey for

the main study.

Finally, word of mouth was identified in customer engagement literature as a potential

outcome of engagement (Fehrer et al. 2013; Vivek et al. 2012); three word of mouth items

from So et al.’s (2012) behavioural intention of loyalty construct was used in the pre-test.

The fourth item in the BIL measure, purchase intention, was omitted as it did not logically

fit the context of the pre-test; i.e. ‘I would purchase the University of Adelaide in the

future’. However, for completeness of measure replication, the purchase intention item was

included in the main study (‘I would purchase wine X in the future’).

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3.6 Main Study: South Australian Wine Industry

3.6.1 Overview

The main study of this thesis was conducted at wine-related events in the South Australian

wine industry. Ten events from six wineries were used to collect data, with 274 complete

responses obtained. The objective of the main study was to assess the proposed

relationships and hypotheses explicated in Chapter 2. The details of the main study,

including the identification and selection of participating wineries and events, individual

respondent selection and profile, and data collection procedure are described in the

following section.

3.6.2 Subjects

The target population of the main study was Australian wine customers; the study subjects

were recent attendees of selected wine events held in the main South Australian wine

regions surrounding Adelaide; McLaren Vale, the Adelaide Hills and the Barossa Valley.

A focus on individual attendees allowed data to reflect the individual’s perspective of the

event experience, which is consistent with the theoretical underpinning of S-D logic

followed in this thesis (as previously discussed in section 3.3).

3.6.3 Selection of Participating Wineries

A purposive sampling technique (Neuman 2006) was used to identify appropriate wineries

to take part in this research. Wineries that had recently conducted or were about to conduct

a relevant BME for their customers were sought. Research was conducted online to

identify wine events held in the wine regions surrounding Adelaide within the data

collection period (June to December 2013). Event information was obtained from winery

websites and wine region tourism websites (e.g. http://mclarenvale.info,

http://www.barossa.com, http://www.adelaidehillswine.com.au).

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http://mclarenvale.info/

http://www.barossa.com/

http://www.adelaidehillswine.com.au/


Wineries were approached across a range of winery sizes and a known range of events.

The researcher contacted the marketing manager or director of each winery (via email) and

explained the nature of the study, and the participation requirements and outcomes for the

winery. Participating wineries were given a report on the nature of customer engagement

and perceptions of the experience specific to their event. Six of the thirteen approached

wineries agreed to take part in the study.

Respondents from ten different wine events (from six wineries) were contacted, providing

a broad range of particular types of event experiences. To examine the major constructs of

this thesis, it was important that the participating wineries were hosting their own BMEs

for customers. These events needed to be distinguished from joint events, sponsored

events, or community based events, to ensure emphasis was placed on the individual wine

brand during the event (Wood 2009). It was also important that the organisations included

in the study covered the comprehensive range of experiential components conceptualised

in the study (i.e. cognitive, emotional, sensorial, pragmatic and relational; Gentile et al.

2007). The participating wineries and events are outlined in Table 3-3.

TABLE 3-3: WINERY PARTICIPANTS

Wine brand Events held Location Winery size*

Brand A 3 Concerts at Winery Adelaide hills 500-999

Brand B Lunch and Dinner with the winemaker events McLaren Vale 250-499

Brand C Picnic at the winery (& live music) Barossa 100-249

Brand D Silent Auction with food and wine Currency Creek 20-49

Brand E Dinner with the winemakers McLaren Vale 2500-4999

Brand F New wine launch (with lunch) McLaren Vale 500-999

*winery size by tonnage crushed (Winetitles 2013)

3.6.4 Selection of Individual Respondents

A purposive sampling approach was used to identify individual respondents (Neuman

2006). The researcher attended various wine events run by the participating wine brands

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and approached all attendees to ask if they would be willing to participate in the study.

Willing participants provided their email to the researcher, with a link to the online survey

provided the following day. A self-administered survey minimised the impact of the

researcher on the respondent, for example social desirability bias (Neuman 2006).

The qualifying dimension relevant to survey participants was that the participant had

attended a branded-wine event; as these participants were approached during a given event,

this qualifier was already met. For multi-day events, participants were asked to identify the

particular event date they had attended at the beginning of the questionnaire, and were

instructed to answer all questions with reference to that specific event (not previous wine

events they may have attended).

3.6.5 Respondent Profiles

The following Table 3-4 outlines the characteristics of individual respondents from each

event compared to the characteristics of the overall sample, based on number of responses

and age distribution. Country of residence was also investigated, however only 13

responses from the total response set of 274 resided in an interactional country (Austria 1;

China 1; Ireland 1; New Zealand 1; United Kingdom 8; United States 1).

TABLE 3-4: RESPONDENT PROFILE FOR NUMBER OF RESPONSES AND AGE

Event Winery n

Age distribution Wine Involvement Consumption Frequency

18-33 34-49 50+ M SD Var 1* 2* 3* 4* 5* Concert M Brand A 50 21 22 7 5.26 1.06 1.13 9 23 7 6 5 Concert J Brand A 50 28 19 3 5.62 1.17 1.37 6 19 16 7 2 Concert T Brand A 12 0 10 2 5.44 0.92 0.85 3 6 1 2 0 Dinner C Brand B 17 3 6 8 5.55 1.38 1.91 6 7 2 1 1 Lunch P Brand B 58 8 13 37 5.51 1.18 1.40 24 26 6 1 1 Lunch T Brand B 13 3 2 8 5.42 1.03 1.05 2 10 0 1 0 Picnic W Brand C 26 6 15 5 5.15 0.94 0.88 0 13 8 4 1 Auction C Brand D 20 2 7 11 3.79 1.43 2.06 1 6 3 4 6 Dinner B Brand E 26 1 10 15 5.85 0.86 0.74 12 12 0 2 0 Lunch H Brand F 2 0 0 2 6.07 0.76 0.58 1 1 0 0 0

Total 274 72 104 98 5.36 1.21 1.46 64 123 43 28 16 * Consumption frequency values: 1 = almost everyday

2 = 2-3 times a week 3 = once a week

4 = 2-3 times per month 5 = once or less per month

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All age brackets were adequately represented (see Table 3-4), with minor variations in

respondent age for certain events; e.g. winery concerts. This may reflect the target market

of the concert’s performer or the nature of the event itself.

An additional characteristic of relevance to this context is wine involvement and wine

consumption frequency. Table 3-4 outlines wine involvement means and standard

deviations from respondents from each event, as well as for the overall sample.

3.6.6 Data Collection Procedure

Attendees were approached during the event to seek their participation in the study. If they

agreed to participate, they were asked to provide their email so a survey link could be sent

to them after the event. An incentive of a chance to win a wine-related prize was provided

to increase participation rate (Denissen et al. 2010; Hair et al. 2008). The incentive was

negotiated with the winery, and was a wine-brand related prize; for example a bottle of

Shiraz Cabernet (for Auction C) and a two pack of La Biondina and il Briconne

Sangiovese (Lunch P).

The survey was emailed to participants within a day of the wine event. A second reminder

email was distributed a week later to those who had not yet participated, and a final email

was distributed a few days later indicating that the survey would close by the end of the

week. The survey included wine brand logos and event photos in order to present a

professional image, and to promote the collaboration of the winery. Online surveys were

selected as an appropriate form of questionnaire administration due to it being less

intrusive than asking attendees to participate during the event. The participating wineries

insisted that attendees be disturbed as little as possible during the event; as well as this,

participation rate was expected to be considerably higher if the participant did not have to

complete the survey during the event. In addition, this protocol was followed to ensure the

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researcher did not influence the results through social desirability bias (Neuman 2006).

The data collection period was the two weeks immediately after the event.

In a small number of cases the wineries handled distribution of surveys on the researcher’s

behalf to avoid any negative customer perceptions resulting from their email information

being given to a third party. Therefore, the procedures undertaken in the collection of the

completed questionnaires varied slightly. This may have impacted on the relative response

rate of the respective events, but not on the nature of the responses; as indicated in Table 3-

5, the response rates for events in which the researcher was present (between 44% and

60%) were considerably higher than the events in which the researcher was absent

(between 11% and 40%). An approximate number of attendees are also listed in Table 3-5;

the researcher did not have access to the specific number of attendees of all events,

however could deduce an approximate value from email lists or a count of attendees at one

point during an event. Due to the public, non-ticketed nature of some events, the total

number of attendees was not known even to the host.

TABLE 3-5: SUMMARY OF DATA COLLECTION PROCEDURES Brand Event Approximate

number of attendees

Researcher present

Incentive Number of Respondents

Response Rate

Brand A Concert M at Winery 265 No No 50 20%

Brand A Concert J at Winery 294 No No 50 17%

Brand A Concert T at Winery 79 No No 12 16%

Brand B Lunch C with the winemakers

50 Yes Yes 17 53%

Brand B Dinner P with the winemakers

150 Yes Yes 58 60%

Brand B Lunch T with the winemakers

80 Yes Yes 13 44%

Brand C Picnic W at the winery (& live music)

70 Yes No 26 55%

Brand D Silent Auction C with food and wine

100 Yes yes 20 54%

Brand E Dinner B with the winemakers

240 No Yes 26 11%

Brand F New wine launch H (with lunch)

30 No No 2 40%

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3.7 Preliminary Analysis

3.7.1 Data Cleaning

A number of data cleaning and quality control methods were conducted to identify

potentially random or inattentive responses to ensure the quality of the data included in

analysis (Meade and Craig 2012). This is a particularly important process for online

surveys due to factors including anonymity and lack of environmental control with

unknown distractions and divided attention influencing the respondent (Meade and Craig

2012).

First, all incomplete data was identified. The researcher excluded responses with more than

10% of items missing (Hair et al. 2012). None of the incomplete responses met the

minimum missing values rule, with a total of 86 incomplete responses deleted. All of the

remaining responses had complete data.

Survey duration was then examined, as a considerably short response time can indicate

lack of thought and attention given to survey items, while a considerably long response

time can indicate inattention or distractions experienced by the respondent (Meade and

Craig 2012). Responses falling in the 15% (less than 10 minutes) and 85% (39.5 minutes

and greater) percentiles were flagged for further quality control testing.

Data was then assessed for response patterns or responses with minimal variance, with 20+

responses in a row flagged for further quality tests; only three responses were flagged

based on this criterion (Malhotra 2009; Meade and Craig 2012).

An additional quality control technique is to include self-reported survey attention or

interest questions, which provides respondents with the opportunity to provide feedback on

their boredom or decreased attention by the end of the survey (Meade and Craig 2012).

While this approach was not taken in this survey, there was a free response comments

section at the end of each survey; responses that included comments were checked for

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evidence of respondents’ frustrations, reported boredom or difficulties with the

questionnaire.

As a result of data quality testing, three responses were deleted as the researcher could

conclusively state that these responses were of poor quality:

Respondent A – high number of repeated responses (response = 4, neutral position on the

seven-point likert scale), and fell within the 15% percentile on survey duration.

Respondent B – very high number of repeated responses (all responses either 7 or 1,

endpoints of the seven-point likert scale).

Respondent C – commented that they may have misinterpreted the questions.

3.7.2 Non-Response Bias

Non-response bias testing was conducted to ensure there were no considerable differences

in responses between early and late respondents (Armstrong and Overton 1977). The early

respondents group included participants who completed the survey within a day of the

initial email invitation (n=117, 43% of respondents); the late respondents group included

those who completed the survey after receiving two reminder emails (n=30, 11% of

respondents). An independent sample t-test was conducted to assess the difference between

early and late respondents, and Levene’s test for equality of variances was observed to

indicate whether equal variances were assumed or not assumed, and reported accordingly

(Coakes, Steed, and Ong 2010). Relational experience was the only construct indicating a

significant difference between early and late respondents (see Table 3-6), indicating that a

problem of non-response bias was unlikely.

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TABLE 3-6: TESTING FOR NON-RESPONSE BIAS

Construct Group Statistics Independent Samples Test

Response Group Mean Sig (2-tailed) Cognitive Experience Early 4.77 0.80 Late 4.70 Emotional Experience

Early 5.11 0.09 Late 4.68 Sensory Experience

Early 5.60 0.98 Late 5.59 Pragmatic Experience

Early 4.30 0.58 Late 4.14 Relational Experience

Early 4.10 0.02 Late 3.52 Event Attention

Early 4.98 0.62 Late 4.87 Event Identification

Early 3.38 0.23 Late 3.01 Event Enthusiasm

Early 5.26 0.32 Late 5.02 Event Absorption

Early 5.14 0.14 Late 4.77 Event Interaction

Early 5.13 0.29 Late 5.37 Social Event Engagement

Early 3.74 0.53 Late 3.56 Brand Attention

Early 5.03 0.67 Late 5.14 Brand Identification

Early 2.94 0.28 Late 2.61 Brand Enthusiasm

Early 4.36 0.62 Late 4.51 Brand Absorption

Early 3.94 0.15 Late 4.35 Brand Interaction

Early 4.45 0.26 Late 4.73 Social Brand Engagement

Early 3.46 0.50 Late 3.64 BIL

Early 6.01 0.93 Late 5.99 Novelty-seeking

Early 6.00 0.07 Late 6.31 Need for Affect

Early 4.29 0.16 Late 4.65 Need for Cognition

Early 5.34 0.37 Late 5.61

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3.7.3 Construct Validity

This thesis employs SEM, a multivariate technique that simultaneously assesses numerous

dependence relationships (Hair et al. 2012). This technique is valuable for this thesis

because measured variables are used to observe latent constructs, and because customer

engagement is considered a dependent variable resulting from various BME experiences

and simultaneously an independent variable in a subsequent dependence relationship with

behavioural intention of loyalty. SEM analysis allows the testing of all of these

relationships in one technique (Hair et al. 2012).

A latent construct refers to a construct that cannot be directly measured, but rather is

represented by multiple measured variables (questionnaire items) (Hair et al. 2012). Latent

constructs are beneficial are they are a more comprehensive approach of exploring a

complex construct; a number of measures are used to reflect the latent construct, and are

then tested for their contribution to that concept (construct validity) and only that concept

(discriminant validity) (Hair et al. 2012). In addition, SEM can estimate and account for

measurement error, which is the degree to which measured variables do not describe the

latent construct (Hair et al. 2012).

The first step of SEM is to define individual constructs through the investigation of

construct validity, which is the assessment of measurement variables and the extent to

which they represent the intended latent construct (Hair et al. 2012). This process assures

the quality of each construct implemented in the measurement model and subsequent path

diagram analysis (Hair et al. 2012). Construct validity is assessed through convergent

validity and discriminant validity testing (Hair et al. 2012).

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3.7.3.1 Convergent Validity

One-factor congeneric measurement models were tested using AMOS 21 prior to the

evaluation of a comprehensive measurement model. The purpose of this test is to assess

convergent validity; that the measured variables predicted to contribute to each latent

construct share a high level of common variance (Hair et al. 2012). In addition, one-factor

congeneric measurement models produce factor score weights which are necessary to

calculate composite measures (Rowe 2002); the justification and process of calculating

composite measures for path model analysis is discussed in Chapter 4.

It is recommended that a range of fit indices are considered for the analysis of models, to

account for any effects based on data non-normality, sample size, or model complexity

(Hair et al. 2012; Lei and Lomax 2005). There are a wide variety of fit indices available for

reporting, but as a general guide the range of indices selected should include; χ² value and

associated df; one absolute fit index (GFI, RMSEA); one goodness-of-fit index (GFI, CFI,

TLI); one incremental fit index (NFI, CRI, TLI); and one badness-of-fit index (RMSEA)

(Hair et al. 2012).

The only statistically based measure of model fit is the Chi-Square (Hair et al. 2012). If the

required non-significance is met (p-value > 0.05), it indicates that the proposed theory fits

reality (Hair et al. 2012). However, chi-square and its significance value are reported with

the knowledge that this value becomes less meaningful for more complex models with a

large number of observed variables tested (Hair et al. 2012). The Normed Chi-Square

reflects the Chi-Square adjusted by the degrees of freedom; the acceptable levels shown in

Table 3-7 include values between 1 and 3, with values below 1 representing an overfit of

the model and values over 3 indicating poor model fit (Hair et al. 2012).

Goodness-of-fit index (GFI) was one of the first fit indices to attempt to have less

sensitivity to sample size, with values greater than 0.90 supporting model fit (Hair et al.

2012). Normed Fit Index (NFI) is an incremental fit index, and reflects a ratio of the

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difference in chi-square of the model versus the null model (Hair et al. 2012). Values

nearing 1 indicate model fit. The Tucker-Lewis Index (TLI) compares the chi-square of the

specified model to the null model (Hair et al. 2012). In addition, TLI is not normed which

means that values can exceed 1 or fall below 0; a TLI value near 1 suggests good model fit

(Hair et al. 2012). Comparative Fit Index (CFI) is a similar index, however is normed and

therefore ranges between 0 and 1; values above 0.90 supporting model fit (Hair et al.

2012).

The Root Mean-Square Error of Approximation (RMSEA) is a badness-of-fit index, and is

commonly reported with chi-square as it attempts to correct the shortfalls associated with

chi-square, namely sample size and model complexity (Hair et al. 2012). A low RMSEA

value indicates model fit; < 0.05 indicates best fit, however 0.05-0.08 is acceptable (Hair et

al. 2012).

In summary, this thesis reports the principal goodness-of-fit index (χ²/df), Goodness-of-fit

index (GFI), Root mean square error of approximation (RMSEA) and Normed Fit Index

(NFI), Tucker Lewis Index (TLI) and Comparative Fit Index (CFI) (Hair et al. 2012;

Hooper et al. 2008; Martínez-López et al. 2013). Each construct model in this thesis was

tested against these fit indices and their related cut-off values as shown in Table 3-7:

TABLE 3-7: SUMMARY OF INDICES USED TO ASSESS MODEL FIT Name Abbreviation Type Acceptable level

Chi-Square χ² Model fit p> 0.05

Normed Chi-Square χ²/df Absolute Fit Model Parsimony

1.0 < χ²/df > 3.0

Goodness-of-Fit GFI Absolute fit GFI > 0.90

Normed Fit Index NFI Incremental Fit NFI > 0.95

Tucker-Lewis Index TLI Incremental Fit TLI > 0.95

Comparative Fit Index CFI Incremental Fit CFI > 0.95

Root Mean-Square Error of Approximation

RMSEA Absolute Fit <0.05, 0.05–0.08 acceptable

Sources: (Hair et al. 2012; Hooper et al. 2008; Kline 2011; Martínez-López et al. 2013)

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The following Figures 3-1 to 3-19 report the one-factor congeneric measurement models

and their corresponding fit indices for each construct investigated in this thesis. Factor

loadings between each measured variable and their latent variables were also observed,

with values above .07 indicating ideal convergent validity (Kline 2011) and values above

0.50 indicating acceptable convergent validity (Hair et al. 2012).

FIGURE 3-1: MEASUREMENT MODEL - COGNITIVE EXPERIENCE

TABLE 3-8: GOODNESS OF FIT INDICES FOR COGNITIVE EXPERIENCE χ² df χ²/df p GFI NFI TLI CFI RMSEA

0.82 1 0.82 .37 0.99 0.99 1.00 1.00 0.00

The one-factor congeneric measurement model for cognitive experience achieved

satisfactory goodness-of-fit with respect to the fit indices described in Table 3-7. Items 1

and 2 met the ideal threshold value of >0.70 supporting convergent validity of the model

(Kline 2011). Item 3 (COG_EXP3=.68) achieved an acceptable factor loading of above

0.50 (Hair et al. 2012). While item 3 did not reach the ideal threshold value, its inclusion

provided an additional theoretical nuance to the construct and was therefore kept in the

model.

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FIGURE 3-2: MEASUREMENT MODEL - EMOTIONAL EXPERIENCE

TABLE 3-9: GOODNESS OF FIT INDICES FOR EMOTIONAL EXPERIENCE χ² df χ²/df p GFI NFI TLI CFI RMSEA

7.50 4 1.88 0.11 0.99 0.99 0.99 0.99 0.06

The one-factor congeneric measurement model for emotional experience achieved

satisfactory goodness-of-fit with respect to the fit indices described in Table 3-7. Four

variables achieved the ideal factor loadings threshold of > 0.70, indicating convergent

validity (Kline 2011). Item 5 (EXP_EMO5 = 0.68) achieved an acceptable factor loading

of above 0.50 (Hair et al. 2012). While item 5 did not reach the ideal threshold value, it

was maintained in the model due to its conceptual relevance.

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FIGURE 3-3: MEASUREMENT MODEL - SENSORIAL EXPERIENCE

TABLE 3-10: GOODNESS OF FIT INDICES FOR SENSORIAL EXPERIENCE χ² df χ²/df p GFI NFI TLI CFI RMSEA

3.30 1 3.30 0.07 0.99 0.99 0.99 0.99 0.09

The one-factor congeneric measurement model for sensorial experience achieved

satisfactory goodness-of-fit with respect to the fit indices described in Table 3-7. All

variables achieved factor loadings > 0.70, indicating convergent validity (Kline 2011).

FIGURE 3-4: MEASUREMENT MODEL - PRAGMATIC EXPERIENCE

TABLE 3-11: GOODNESS OF FIT INDICES FOR PRAGMATIC EXPERIENCE χ² df χ²/df p GFI NFI TLI CFI RMSEA

0.74 1 0.74 0.39 0.99 0.99 1.00 1.00 0.00

The one-factor congeneric measurement model for pragmatic experience achieved



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FIGURE 3-5: MEASUREMENT MODEL - RELATIONAL EXPERIENCE

TABLE 3-12: GOODNESS OF FIT INDICES FOR RELATIONAL EXPERIENCE χ² df χ²/df p GFI NFI TLI CFI RMSEA

4.21 2 2.11 0.12 0.99 0.99 0.99 0.99 0.06

The one-factor congeneric measurement model for relational experience achieved



FIGURE 3-6: MEASUREMENT MODEL - EVENT ATTENTION

TABLE 3-13: GOODNESS OF FIT INDICES FOR EVENT ATTENTION χ² df χ²/df p GFI NFI TLI CFI RMSEA

1.93 1 1.93 0.17 0.99 0.99 0.99 0.99 0.06

The one-factor congeneric measurement model for event attention achieved satisfactory

goodness-of-fit with respect to the fit indices described in Table 3-7. All variables achieved

factor loadings > 0.70, indicating convergent validity (Kline 2011).

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FIGURE 3-7: MEASUREMENT MODEL - BRAND ATTENTION

TABLE 3-14: GOODNESS OF FIT INDICES FOR BRAND ATTENTION χ² df χ²/df p GFI NFI TLI CFI RMSEA

0.68 1 0.68 0.41 0.99 0.99 1.00 1.00 0.00

The one-factor congeneric measurement model for brand attention achieved satisfactory



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FIGURE 3-8: MEASUREMENT MODEL - EVENT IDENTIFICATION

TABLE 3-15: GOODNESS OF FIT INDICES FOR EVENT IDENTIFICATION χ² df χ²/df p GFI NFI TLI CFI RMSEA

4.35 2 2.18 0.11 0.99 0.99 0.99 0.99 0.07

The one-factor congeneric measurement model for event identification achieved


variables achieved ideal factor loadings of > 0.70, indicating convergent validity (Kline

2011) with the exception of item 2 (ID_EVENT2= 0.66) which still achieved an acceptable

factor loading of > 0.50 (Hair et al. 2012). Item 5 also remained in the model because it

provided an additional theoretical nuance to the construct.

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FIGURE 3-9: MEASUREMENT MODEL - BRAND IDENTIFICATION

TABLE 3-16: GOODNESS OF FIT INDICES FOR BRAND IDENTIFICATION χ² df χ²/df p GFI NFI TLI CFI RMSEA

0.97 1 0.97 0.32 0.99 0.99 1.00 1.00 0.00

The one-factor congeneric measurement model for brand identification achieved


variables achieved factor loadings > 0.70, indicating convergent validity (Kline 2011)

FIGURE 3-10: MEASUREMENT MODEL - EVENT ENTHUSIASM

TABLE 3-17: GOODNESS OF FIT INDICES FOR EVENT ENTHUSIASM χ² df χ²/df p GFI NFI TLI CFI RMSEA

0.91 1 0.91 0.34 0.99 0.99 1.00 1.00 0.00

The one-factor congeneric measurement model for event enthusiasm achieved satisfactory


factor loadings > 0.70, indicating convergent validity (Kline 2011). 120 | P a g e


FIGURE 3-11: MEASUREMENT MODEL - BRAND ENTHUSIASM

TABLE 3-18: GOODNESS OF FIT INDICES FOR BRAND ENTHUSIASM χ² df χ²/df p GFI NFI TLI CFI RMSEA

2.66 1 2.66 0.10 0.99 0.99 0.99 0.99 0.08

The one-factor congeneric measurement model for brand enthusiasm achieved satisfactory



FIGURE 3-12: MEASUREMENT MODEL - EVENT ABSORPTION

TABLE 3-19: GOODNESS OF FIT INDICES FOR EVENT ABSORPTION χ² df χ²/df p GFI NFI TLI CFI RMSEA

1.21 1 1.21 0.27 0.99 0.99 0.99 0.99 0.03

The one-factor congeneric measurement model for event absorption achieved satisfactory



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FIGURE 3-13: MEASUREMENT MODEL - BRAND ABSORPTION

TABLE 3-20: GOODNESS OF FIT INDICES FOR BRAND ABSORPTION χ² df χ²/df p GFI NFI TLI CFI RMSEA

2.20 1 2.20 0.14 0.99 0.99 0.99 0.99 0.07

The one-factor congeneric measurement model for brand absorption achieved satisfactory



FIGURE 3-14: MEASUREMENT MODEL - EVENT INTERACTION

TABLE 3-21: GOODNESS OF FIT INDICES FOR EVENT INTERACTION χ² df χ²/df p GFI NFI TLI* CFI RMSEA

.037 1 .037 .848 1.00 1.00 1.01 1.00 .00

The one-factor congeneric measurement model for event interaction achieved satisfactory



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FIGURE 3-15: MEASUREMENT MODEL - BRAND INTERACTION

TABLE 3-22: GOODNESS OF FIT INDICES FOR BRAND INTERACTION χ² df χ²/df p GFI NFI TLI CFI RMSEA

0.47 1 0.47 0.49 0.99 1.00 1.00 1.00 0.00

The one-factor congeneric measurement model for brand interaction achieved satisfactory



FIGURE 3-16: MEASUREMENT MODEL - BEHAVIOURAL INTENTION OF LOYALTY

TABLE 3-23: GOODNESS OF FIT INDICES FOR BEHAVIOURAL INTENTION OF LOYALTY χ² df χ²/df p GFI NFI TLI CFI RMSEA

0.87 1 0.87 0.35 0.99 0.99 1.00 1.00 .00

The one-factor congeneric measurement model for behavioural intention of loyalty

achieved satisfactory goodness-of-fit with respect to the fit indices described in Table 3-7.

All variables achieved factor loadings > 0.70, indicating convergent validity (Kline 2011). 123 | P a g e


FIGURE 3-17: MEASUREMENT MODEL - NOVELTY-SEEKING

TABLE 3-24: GOODNESS OF FIT INDICES FOR NOVELTY-SEEKING χ² df χ²/df p GFI NFI TLI CFI RMSEA

0.91 1 0.91 0.34 0.99 0.99 1.00 1.00 0.00

The one-factor congeneric measurement model for novelty-seeking achieved satisfactory



FIGURE 3-18: MEASUREMENT MODEL - NEED FOR AFFECT

TABLE 3-25: GOODNESS OF FIT INDICES FOR NEED FOR AFFECT χ² df χ²/df p GFI NFI TLI CFI RMSEA

2.92 1 2.92 0.09 0.99 0.99 0.99 0.99 0.08

The one-factor congeneric measurement model for need for affect achieved satisfactory



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FIGURE 3-19: MEASUREMENT MODEL - NEED FOR COGNITION

TABLE 3-26: GOODNESS OF FIT INDICES FOR NEED FOR COGNITION χ² df χ²/df p GFI NFI TLI CFI RMSEA

13.4 9 1.49 0.15 0.98 0.99 0.99 0.99 0.04

The one-factor congeneric measurement model for need for cognition achieved satisfactory



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3.7.3.2 Discriminant Validity and Reliability Testing

Following the assessment of one-factor congeneric measurement models, an overall

measurement model was analysed. This measurement model comprising all latent

constructs and their respective measured variables enables discriminant validity testing and

confirms (along with convergent validity) construct validity (Hair et al. 2012).

Measurement model testing is the first of the two-step SEM process, in which a

comprehensive confirmatory factor analysis (CFA) is conducted to evaluate measurement

model fit and construct validity (Hair et al. 2012). The second step is assessment of the

structural model, in which hypotheses are tested and significance of relationships are

assessed (Hair et al. 2012). This second step is taken only after CFA has confirmed

construct validity and is described in Chapter 4; the first step is crucial in assuring the

quality of the measures used to calculate the structural model outcomes (Hair et al. 2012).

Discriminant validity ensures that the measured variables used to capture a particular latent

construct are contributing distinctly to that construct, and tests the extent to which each

construct correlates with other constructs; it measures whether a construct is truly distinct

from others (Hair et al. 2012). The average variance extracted (AVE) estimate is used to

measure discriminant validity, and should achieve a greater value than the squared

correlation estimate (HSC) which would indicate that the latent construct explains the

variance in its associated measured variables more than other constructs in the model (Hair

et al. 2012).

In addition, reliability is investigated as it is a necessary element of validity testing; it

assesses the extent to which measured variables are internally consistent (Hair et al. 2012)

and free from random measurement error (Kline 2011). Cronbach’s coefficient alpha is the

most widely used measurement of reliability, however is criticised as construct weights are

constrained to be equal and therefore underestimates reliability (Peterson and Kim 2013).

The construct reliability measure is often used with SEM and allows construct weights to

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vary (Peterson and Kim 2013) and therefore is also included to determine reliability (Hair

et al. 2012). The key validity and reliability indices and analysis thresholds are summarised

in the following Table 3-27:

TABLE 3-27: RELIABILITY AND VALIDITY INDICES

Indicator Threshold Reference

Construct reliability > 0.7 (Fornell and Larcker 1981; Hair et al. 2012)

Cronbach’s alpha >0.7 (De Vaus 2002)

Average Variance Extracted

> 0.5 to achieve convergent validity Must exceed the square of the correlations between constructs (HSC) to achieve discriminant validity

(Fornell and Larcker 1981; Hair et al. 2012)

The results of the overall measurement model are presented in Table 3-28. Results indicate

Cronbach’s alphas of at least 0.80 (De Vaus 2002) and high construct reliability scores all

exceeding the threshold of 0.7 (Fornell and Larcker 1981). Convergent validity is

confirmed with all average variance extracted values exceeding 0.5 (Hair et al. 2012) and

discriminant validity is examined with all average variance extracted scores exceeding the

square of the correlations between constructs (Hair et al. 2012).

The event absorption construct was the only variable to not achieve discriminant validity

(Table 3-28), as it was found to have high correlation with event enthusiasm. However, the

event absorption construct achieved reliability and convergent validity (De Vaus 2002;

Hair et al. 2012). Conceptually, event absorption (likened to flow) and event enthusiasm

(emotional engagement) have been identified as having similarities with their reference

and applicability to emotional experience (Drengner et al. 2008). Enthusiasm refers to a

heightened level of excitement and interest (So et al. 2012; Vivek et al. 2012), while

absorption is a heightened state of complete concentration, intrinsic enjoyment and deep

engrossment (Csikzentmihaly 1990; So et al. 2012). While the constructs share common

traits of happiness and positive emotion, the two remain distinct constructs; absorption is

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an extremely high level of enthusiasm, containing the additional characteristics of

engrossment in the experience and losing sense of time (So et al. 2012; Vivek et al. 2012).

Marketing events are identified as highly experience-oriented, interactive, emotional, and a

dramaturgy of the brand (Wohlfeil and Whelan 2006); these characteristics highlight the

applicability of both enthusiasm and absorption to be facilitated during BMEs. Therefore,

as event absorption and event enthusiasm are conceptually related but distinct and are both

applicable to BMEs, it is argued that each remain in the model as separate constructs.

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TABLE 3-28: RELIABILITY AND VALIDITY OF MEASUREMENT MODEL

Scale Item L C CA CR AVE HSC

Cognitive Experience EXP_COG1 0.88 0.78 0.85 0.86 0.67 0.32 EXP_COG2 0.87 0.76 EXP_COG3 0.69 0.48

Emotional Experience

EXP_EMO1 0.74 0.55 0.89 0.89 0.62 0.47 EXP_EMO2 0.79 0.63 EXP_EMO3 0.87 0.76 EXP_EMO4 0.80 0.64 EXP_EMO5 0.73 0.53

Sensorial Experience EXP_SEN1 0.92 0.84 0.94 0.94 0.83 0.47 EXP_SEN2 0.95 0.90 EXP_SEN3 0.87 0.75

Pragmatic Experience EXP_PRAG4 0.80 0.65 0.84 0.84 0.64 0.27 EXP_PRAG5 0.81 0.65 EXP_PRAG6 0.79 0.62

Relational Experience

EXP_REL2 0.87 0.75 0.96 0.96 0.86 0.19 EXP_REL3 0.93 0.87 EXP_REL4 0.97 0.94 EXP_REL5 0.93 0.86

Event Attention ATT_EVENT2 0.80 0.64 0.84 0.84 0.64 0.60 ATT_EVENT3 0.84 0.71 ATT_EVENT4 0.76 0.57

Event Identification

ID_EVENT1 0.77 0.60 0.88 0.89 0.67 0.23 ID_EVENT2 0.66 0.44 ID_EVENT3 0.90 0.80

ID_EVENT4 0.92 0.84

Event Enthusiasm

ENTH_EVENT2 0.91 0.83 0.91 0.92 0.74 0.71 ENTH_EVENT3 0.90 0.81 ENTH_EVENT4 0.84 0.70 ENTH_EVENT5 0.78 0.61

Event Absorption

AB_EVENT2 0.75 0.57 0.84 0.84 0.64 0.71 AB_EVENT5 0.78 0.61

AB_EVENT6 0.86 0.74

Event Interaction

INT_EVENT1 0.87 0.76 0.95 0.95 0.82 0.38 INT_EVENT2 0.87 0.76 INT_EVENT3 0.96 0.91 INT_EVENT4 0.93 0.86

Social Event Engagement

SOC_EVENT3 0.76 0.57 0.85 0.85 0.65 0.38 SOC_EVENT4 0.85 0.71

SOC_EVENT5 0.81 0.66

L = loadings C = correlations

CA = cronbach’s alpha CR = construct reliability

AVE = average variance extracted HSC = highest squared correlation

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Scale Item L C CA CR VE HSC

Brand Attention

ATT_BRAND2 0.94 0.87 0.94 0.94 0.85 0.64 ATT_BRAND3 0.94 0.89

ATT_BRAND4 0.88 0.77

Brand Identification

ID_BRAND1 0.85 0.72 0.92 0.92 0.75 0.49 ID_BRAND2 0.78 0.61 ID_BRAND3 0.88 0.78

ID_BRAND4 0.94 0.88

Brand Enthusiasm

ENTH_BRAND2 0.95 0.91 0.96 0.96 0.86 0.64 ENTH_BRAND3 0.96 0.93 ENTH_BRAND4 0.93 0.87

ENTH_BRAND5 0.86 0.73

Brand Absorption

AB_BRAND2 0.90 0.8 0.90 0.91 0.76 0.63 AB_BRAND5 0.88 0.77

AB_BRAND6 0.85 0.71

Brand Interaction

INT_BRAND1 0.89 0.80 0.97 0.97 0.87 0.59 INT_BRAND2 0.95 0.91 INT_BRAND3 0.97 0.94

INT_BRAND4 0.93 0.86

Social Brand Engagement

SOC_BRAND3 0.85 0.72 0.88 0.88 0.70 0.44 SOC_BRAND4 0.85 0.72

SOC_BRAND5 0.82 0.67

Novelty-seeking

NEED_NOV1 0.90 0.81 0.95 0.95 0.86 0.28 NEED_NOV2 0.93 0.86

NEED_NOV3 0.95 0.91

Need for Affect

NEED_AFF4 0.85 0.73 0.91 0.91 0.78 0.16 NEED_AFF5 0.88 0.77

NEED_AFF6 0.91 0.83

Cognitive Needs

R_NEED_COG2 0.80 0.63 0.91 0.91 0.63 0.13 R_NEED_COG3 0.87 0.75 R_NEED_COG4 0.82 0.67 R_NEED_COG5 0.79 0.63 R_NEED_COG7 0.74 0.55

R_NEED_COG8 0.76 0.57

Behavioural Intention of Loyalty

BIL_BRAND1 .951 .905 0.97 0.96 0.87 0.42 BIL_BRAND2 .988 .976

BIL_BRAND3 .911 .830

BIL_BRAND4 .871 .759



VE = average variance extracted HSC = highest squared correlation

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3.7.4 Testing for Common Method Bias

The final test run to confirm quality of the construct was to check for common method

bias. This method considers biases respondents have towards answering questions with

relation to various factors, including social desirability bias, scale formats, and item

context effects (e.g. scale length or context-inducted mood) (Podsakoff, MacKenzie, Lee,

and Podsakoff 2003). All final items in the study were tested using the Harman’s single-

factor technique, to check that variance cannot be account for by a single general factor

(Podsakoff et al. 2003). Results indicated extremely poor fit for when all survey items were

considered part of one general factor, confirming that this survey does not have problems

with common method bias (Podsakoff et al. 2003).

TABLE 3-29: COMMON METHOD BIAS - GOODNESS OF FIT INDICES χ² df χ²/df p GFI NFI TLI CFI RMSEA

19197.01 3485 5.51 0.00 0.26 0.28 0.31 0.32 0.13

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This chapter described the process undertaken to collect data for this thesis. A deductive,

quantitative research design was employed in this thesis to investigate causal relationships

through SEM. The unit of analysis was the individual; specifically, the event attendee.

A pre-test in the University sector revealed that the initial survey was too long and

assessed the selected measurement items. A number of event experience items were

removed, and customer engagement and behavioural intention of loyalty items were

replaced as a result of the preliminary analysis.

The main study was conducted in the South Australian wine industry and included six

participating wineries hosting ten wine-related BMEs. Respondents were primarily

approached during each event and invited to participate in the study, providing their email

address for the online survey to be sent to them after the event.

Preliminary analysis was also described in this chapter. First, a number of data cleaning

and quality control tests were conducted, resulting in three responses being removed from

the sample collected for the main data analysis. One-factor congeneric measurement

models were run to assess the model fit of each construct. Reliability and validity was

confirmed for the majority of constructs.

The next chapter describes the main data analysis conducted in this thesis, and investigates

the proposed thesis hypotheses identified in Chapter 2.

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Results Chapter

CHAPTER 4: RESULTS


This chapter outlines each step of data analysis to address the research questions described

in Chapter 2. Data was analysed with SPSS21 and AMOS21 applying structural equation

modelling (SEM). The first section investigates the proposition that social engagement is a

dimension of customer engagement.

Section two introduces the identified path model reflecting the conceptual model and

hypothesised relationships for this thesis. The section begins with a discussion of

composite variables, their applicability to path model analysis and the process of

composite variable calculation. The steps for SEM analysis are then discussed which

includes model specification, identification, estimation and re-specification. Hypotheses

regarding the impact of components of BME experience on customer event engagement

and customer brand engagement, the relationship between the two customer engagement

constructs, and the outcome of behavioural intention of loyalty are then discussed with

reference to the final re-specified model.

Section three utilises multi-group analysis to investigate the moderation effect of

experiential needs. The model was tested comparing ‘low’ and ‘high’ groups of 1) need for

cognition, 2) need for affect and 3) novelty-seeking needs. An exploratory approach was

taken in this analysis step, as the investigation of moderating variables is scarce in

customer engagement literature. While results are described and briefly discussed in this

chapter, a detailed discussion of findings and their theoretical and managerial implications

is provided in Chapter 5.

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Results Chapter

4.2 Social Engagement as an Independent Engagement Dimension

In Chapter 3, So et al.’s (2012) five-dimension conceptualisation of customer engagement

was tested for statistical fit from both a brand and event perspective. However, social

engagement has been conceptualised diversely in customer engagement studies; as a social

dimension of engagement (Vivek et al. 2012), social-interactive engagement (Calder et al.

2009), social elements of engagement (Gambetti et al. 2012; Sawhney et al. 2005), or a

strong focus throughout their discussion (Abdul-Ghani et al. 2011; Algesheimer et al.

2005); however, there is no consistency in the literature on the presence or role of social

engagement. Therefore, this thesis aims to provide some clarity to this debate and

investigates social engagement as an independent dimension of customer engagement.

4.2.1 Convergent Validity of Social Engagement Dimensions

The original social engagement construct utilised in this thesis consisted of seven items

from Calder et al. (2009), however the social event engagement and social brand

engagement models were reduced to three items for the purpose of parsimony.

TABLE 4-1: SOCIAL ENGAGEMENT ITEMS INCLUDED AND EXCLUDED FROM MODEL

Item no: Included Excluded

SOC_EVENT1 This event did a good job of getting its attendees to contribute or provide feedback

SOC_EVENT2 I liked meeting other people who attended this event

SOC_EVENT3 I’ve gotten interested in things I otherwise wouldn’t have because of other attendees at this event

SOC_EVENT4 I was as interested in input from other attendees as I was in information provided by organisers during this event

SOC_EVENT5 A big reason I liked this event is what I got from other attendees

SOC_EVENT6 I did quite a bit of socialising at this event

SOC_EVENT7 I contributed to conversations at this event

*the same items were replicated for social brand engagement; substitute the word ‘event’ for ‘brand’

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Results Chapter

The three included items reflect the interactions the customer has with other actors with

respect to the event or brand; in particular the information and value received from other

attendees. In comparison, the excluded items had a common focus on the individual’s

reported contribution to social interactions. The included items share a common trait of

emphasising the customer’s level of interest and value from social reactions, whereas the

excluded items focus on the nature of the interaction. While the excluded items referred to

social interactions, they do not refer to a heightened state of interest.

The process of reaching the final model involved running the original model with all seven

items and identifying those reporting low factor loading values (Kline 2011). The

following Figures 4-1 and 4-2 report the final one-factor congeneric measurement models

for social event engagement and social brand engagement.

FIGURE 4-1: MEASUREMENT MODEL – SOCIAL EVENT ENGAGEMENT

TABLE 4-2: GOODNESS OF FIT INDICES - SOCIAL EVENT ENGAGEMENT χ² df χ²/df p GFI NFI TLI CFI RMSEA

3.2 1 3.2 0.07 0.99 0.99 0.98 0.99 0.09

The social event engagement congeneric model achieved acceptable fit with the data,

although χ²/df > 3 extends beyond the threshold value required and RMSEA is above the

<0.08 (Hair et al. 2012). This model was deemed acceptable as factor loadings for each

indicator were above 0.70 which indicates convergent validity (Kline 2011). As this model

only included three indicators, it is a just-identified model; therefore, an equality constraint

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Results Chapter

was imposed on the error terms of SOC_EVENT3 and SOC_EVENT4 in order to

sufficiently identify the model (Kline 2011).

The assertions regarding these final items were further supported as the social brand

engagement model implemented the same three items to achieve model fit (Figure 4-2 and

Table 4-3). The items capture the impact of social interactions regarding the brand in

representing social brand engagement.

FIGURE 4-2: MEASUREMENT MODEL - SOCIAL BRAND ENGAGEMENT

TABLE 4-3: GOODNESS OF FIT INDICES - SOCIAL BRAND ENGAGEMENT χ² df χ²/df p GFI NFI TLI CFI RMSEA

0.77 1 0.77 0.38 0.99 0.99 1.00 1.00 0.00

The social brand engagement congeneric model achieved fit with the data, although χ²/df

<1 suggests model overfit (Hair et al. 2012). Factor loadings for each measured variable

were above 0.70 confirming convergent validity (Kline 2011). This model is a just-

identified model, therefore an equality constraint was imposed on the error terms of

SOC_BRAND3 and SOC_BRAND4 to identify the model (Kline 2011).

In summary, the one-factor congeneric measurement models indicated that social event

engagement and social brand engagement achieved convergent validity. The next section

describes the discriminant validity and reliability testing of customer event engagement

and customer brand engagement with the inclusion of their respective social engagement

dimensions.

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Results Chapter

4.2.2 Discriminant Validity and Reliability Testing of Social Event Engagement

Following the testing of one-factor congeneric models for social event engagement and

social brand engagement, the social event engagement construct was included in a

confirmatory factor analysis model to investigate the discriminant validity of the construct.

FIGURE 4-3: MEASUREMENT MODEL - EVENT ENGAGEMENT

TABLE 4-4: GOODNESS OF FIT INDICES - EVENT ENGAGEMENT

χ² df χ²/df p GFI NFI TLI CFI RMSEA

411.87 174 2.37 0.00 0.87 0.91 0.94 0.95 0.07

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Results Chapter

The event engagement measurement model (Figure 4-3 and Table 4-4) achieved

satisfactory fit with the data. A number of fit indices were below the desired threshold

values (p<0.05, GFI<0.90, NFI<0.95, TLI<0.94), however when model complexity

increases the original GOF thresholds become unrealistic (Hair et al. 2012). All factor

loadings met the ideal threshold value of 0.70 (Table 4-3) supporting convergent validity

of the model (Kline 2011) with the exception of ID_EVENT2 = 0.66 which still achieved

an acceptable factor loading of above 0.50 (Hair et al. 2012).

The social event engagement construct demonstrated sound reliability and discriminant

validity (Table 4-5). Cronbach’s alpha and construct reliability threshold values were

achieved for all event engagement dimensions, indicating internal consistency (CA > 0.80

and CR > 0.7). Convergent validity was confirmed (AVE > 0.5) and discriminant validity

was achieved as the average variance extracted (AVE) exceeded the highest squared

correlation (HSC), demonstrating that social event engagement is a robust construct, and

distinct from the other customer event engagement dimensions (Hair et al. 2012). The

event absorption construct AVE value did not exceed HSC; however, as discussed in

Chapter 3 (section 3.7.3.2), event absorption and event enthusiasm have similarities with

their mutual reference to emotional drivers of engagement (Drengner et al. 2008).

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Results Chapter

TABLE 4-5: RELIABILITY AND VALIDITY – EVENT ENGAGEMENT Scale Item L C CA CR AVE HSC

Event Attention

ATT_EVENT2 0.81 0.66 0.84 0.84 0.64 0.59

ATT_EVENT3 0.82 0.68

ATT_EVENT4 0.78 0.60

Event Identification

ID_EVENT1 0.77 0.59 0.88 0.89 0.67 0.23

ID_EVENT2 0.66 0.44

ID_EVENT3 0.90 0.81

ID_EVENT4 0.92 0.84

Event Enthusiasm

ENTH_EVENT2 0.92 0.85 0.91 0.92 0.73 0.68

ENTH_EVENT3 0.91 0.82



Event Absorption

AB_EVENT2 0.74 0.55 0.84 0.84 0.64 0.68

AB_EVENT5 0.85 0.72

AB_EVENT6 0.81 0.66

Event Interaction

INT_EVENT1 0.87 0.76 0.95 0.95 0.82 0.37

INT_EVENT2 0.87 0.76




SOC_EVENT3 0.74 0.55 0.85 0.85 0.65 0.37






In summary, the social event engagement construct achieved satisfactory model fit, both as

a stand-alone construct as evidenced in the one-factor congeneric measurement model, and

within the broader measurement model of event engagement. Construct validity and

reliability were achieved with the exception of event absorption; however, this construct

remained in the model due to the conceptual recognition that it is closely related and yet

distinct from event enthusiasm (discussion in section 3.7.3.2).

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Results Chapter

4.2.3 Discriminant Validity and Reliability Testing of Social Brand Engagement

The tests for discriminant validity and reliability were replicated for the social brand

engagement construct. A measurement model of brand engagement was analysed to ensure

social brand engagement was a discriminant and reliable construct (Hair et al. 2012).

FIGURE 4-4: MEASUREMENT MODEL - BRAND ENGAGEMENT

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Results Chapter

TABLE 4-6: GOODNESS OF FIT INDICES - BRAND ENGAGEMENT χ² df χ²/df p GFI NFI TLI CFI RMSEA

340.18 172 1.98 0.00 0.90 0.95 0.97 0.97 0.06

The brand engagement measurement model (Figure 4-4) achieved reasonable fit with the

data. While the significance value was not achieved (p <0.05), it is recognised that the

significance value becomes less indicative of model fit when model complexity increases,

particularly for a smaller sample size (Hair et al. 2012). The remaining fit indices suggest

model fit and all factor loadings were greater than 0.70, indicating convergent validity

(Kline 2011).

The results of this model provide initial support for social brand engagement as an

independent dimension of brand engagement. Additional testing from this model examined

the discriminant validity and reliability of the constructs, and is outlined in Table 4-7.

The results from the brand engagement measurement model (Table 4-7) indicate that social

brand engagement achieves discriminant validity and reliability as an independent

dimension of the brand engagement construct; cronbach’s alpha is above 0.70 (De Vaus

2002) indicating reliability of social brand engagement, and a construct reliability (CR)

value above 0.7 indicating internal consistency (Hair et al. 2012). Convergent validity is

confirmed with the average variance extracted (AVE) exceeding 0.5 and discriminant

validity was achieved as the AVE score exceeded the square of the correlations between

constructs (HSC) (Hair et al. 2012).

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Results Chapter

TABLE 4-7: RELIABILITY AND VALIDITY – BRAND ENGAGEMENT Scale Item L C CA CR AVE HSC

Brand Attention

ATT_BRAND2 0.93 0.87 0.94 0.94 0.85 0.63



Brand Identification

ID_BRAND1 0.84 0.71 0.92 0.92 0.74 0.43

ID_BRAND2 0.76 0.57

ID_BRAND3 0.88 0.77

ID_BRAND4 0.95 0.90

Brand Enthusiasm

ENTH_BRAND2 0.96 0.92 0.96 0.96 0.85 0.63




Brand Absorption

AB_BRAND2 0.89 0.8 0.90 0.91 0.76 0.62

AB_BRAND5 0.87 0.75

AB_BRAND6 0.86 0.73

Brand Interaction

INT_BRAND1 0.88 0.77 0.97 0.96 0.87 0.59





SOC_BRAND3 0.84 0.71 0.88 0.88 0.70 0.44






In summary, the social brand engagement construct achieved good model fit, both as a

stand-along construct as evidenced in the one-factor congeneric measurement model, and

within the broader measurement model of brand engagement. Construct validity and

reliability were achieved. Therefore, the social brand engagement construct is a worthwhile

addition to the brand engagement construct and is discriminant from other brand

engagement dimensions. The final test for discriminant validity and reliability was

conducted with social event engagement, social brand engagement and relational

experience components as they share a common focus on social elements.

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4.2.4 Discriminant Validity of Social Constructs

Various social constructs were utilised in this thesis; each is conceptually unique and

distinct, however share a common focus on social elements. Therefore, it was important to

demonstrate the empirical uniqueness of the relational experience, social event engagement

and social brand engagement constructs.

A relational experience is one that emphasises the social context and relationships with

others (Gentile et al. 2007).

Social event engagement is the customer’s heightened level of interest regarding the event

based on personal exchanges with other customers, and occurs when the customer has a

personal exchange with other customers about or with reference to the event.

Social brand engagement is the customer’s heightened level of interest regarding the brand

based on personal exchanges with other customers, and occurs when the customer has a

personal exchange with other customers about or with reference to the brand.

Conceptually these constructs differ as relational experience reflects the ‘nature’ of the

experience in which social interactions are abundant; it does not encompass any motivation

or psychological state derived from that experience. In contrast, social engagement

encompasses the heightened psychological state of the customer based on personal

exchanges with others, which can either reflect on the event or the brand.

A measurement model (Figure 4-5) containing the relational experience, social event

engagement and social brand engagement constructs was assessed for discriminant

validity.

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FIGURE 4-5: MEASUREMENT MODEL - SOCIAL CONSTRUCTS

TABLE 4-8: GOODNESS OF FIT INDICES - SOCIAL CONSTRUCTS

χ² df χ²/df p GFI NFI TLI CFI RMSEA

89.80 32 2.81 0.00 0.94 0.96 0.96 0.97 0.08

The social constructs model achieved fit with the data. Significance was not achieved;

however, model fit was still concluded as significance value becomes less indicative of

model fit of complex models, particularly with a smaller sample size (Hair et al. 2012). In

addition, standardised factor loadings for each indicator were above 0.70 confirming

convergent validity (Kline 2011).

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TABLE 4-9: RELIABILITY AND VALIDITY – SOCIAL CONSTRUCTS Scale Item L C CA CR AVE HSC

Relational Experience

EXP_REL2 0.87 0.75 0.96 0.96 0.86 0.17

EXP_REL3 0.93 0.87

EXP_REL4 0.97 0.94

EXP_REL5 0.93 0.86


SOC_EVENT3 0.77 0.60 0.85 0.85 0.65 0.27




SOC_BRAND3 0.90 0.81 0.88 0.88 0.70 0.27






Table 4-9 highlights that social brand engagement, social event engagement and relational

experience are empirically distinct constructs. The social brand engagement and social

event engagement constructs, although having a covariance of 0.52 (Figure 4-5) achieved

discriminant validity (AVE > HSC) (Hair et al. 2012). Furthermore, although social brand

engagement and social event engagement latent constructs indicated strong covariance

with relational experience (0.31 and 0.41 respectively) discriminant validity was also

achieved (AVE > HSC) (Hair et al. 2012).

Reliability and internal consistency was achieved for each construct (CA > 0.80 and CR >

0.7 respectively), and convergent validity (AVE > 0.5) (Hair et al. 2012). These results

indicate that social event engagement, social brand engagement and relational experience

have achieved construct validity. Support is provided for each construct as empirically and

conceptually distinct; the following structural models and path models include these

constructs with the knowledge that each is accurate and distinct.

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4.2.5 Structural Model of Customer Event Engagement

Measurement models and structural models are similar with regards to the latent constructs

and measured variables included the analysis, however measurement models identify

covariances between latent constructs and assess discriminant validity and reliability (Hair

et al. 2012). A structural model instead includes paths from each latent variable to a

higher-order latent construct, which allows the model to estimate the strength and

significance of the impact each latent variable (e.g. social engagement) has on the higher-

order construct (e.g. customer engagement) (Hair et al. 2012).

The purpose of running these models was solely to assess how well a six dimension model

of customer engagement (event and brand) including social engagement fitted the data;

therefore, a confirmatory modelling strategy was employed (Hair et al. 2012). This strategy

is the most direct utilisation of SEM in which the conceptual model, founded in the

relevant literature, is assessed for model fit without investigation of competing models

(Hair et al. 2012).

A structural model of event engagement dimensions including attention, enthusiasm,

absorption, identification, interaction and social event engagement leading to a higher

order latent construct of customer event engagement was assessed. The findings of this

structural model would provide support that social event engagement is an important

dimension that significantly contributes to the higher-order construct of customer event

engagement.

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FIGURE 4-6: MEASUREMENT MODEL - CUSTOMER EVENT ENGAGEMENT

* Covariance between z25 and z35 = .57 not shown on diagram.

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The event engagement structural model (Figure 4-6 and Table 4-10) revealed questionable

fit with the data. Due to the complexity of the model and the relatively small sample size, it

is unrealistic to expect fit indices to reach their original thresholds (Hair et al. 2012).

However, low standardised factor loadings were found for event interaction (0.36) and

social event engagement (0.31) which are less than commonly accepted levels of 0.7 or

0.50 to confirm convergent validity (Hair et al. 2012; Kline 2011). Event identification

(0.51) was also lower than the ideal 0.70 value, however was greater than 0.5 and therefore

acceptable (Hair et al. 2012).

To achieve reasonable model fit, an error covariance was placed between event interaction

and social event engagement. While it is recognised that event interaction and social event

engagement have common traits, they are conceptually distinct constructs. Interaction

encompasses the energy or effort the customer exerts in order to actively participate in

event activities (So et al. 2012). Social event engagement is the customer’s heightened

level of interest regarding the event based on personal exchanges with other customers, and

occurs when the customer has a personal exchange with other customers with reference to

the event.

While the error covariance may suggest that the social event engagement and event

interaction constructs are distinct from the other customer event engagement dimensions,

the two constructs were maintained in further analysis for a number of reasons. First, the

purpose of hypothesis 1 was to explore whether social engagement can be considered an

element of customer engagement; the results provide partial support for this hypothesis.

Second, the social event engagement construct achieved discriminant validity, reliability,

and convergent validity as reported in sections 4.2.1 and 4.2.2. Third, support is found for

TABLE 4-10: GOODNESS OF FIT INDICES – EVENT ENGAGEMENT χ² df χ²/df p GFI NFI TLI CFI RMSEA

463.07 182 2.54 0.00 0.85 0.90 0.93 0.94 0.08

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the inclusion of social brand engagement (discussed in section 4.2.6); social event

engagement and event interactions should remain for the purpose of complete replication

of the customer engagement measures with regards to the brand and the event. It is

recognised that this is a limitation of the research, and is discussed in Chapter 5.

4.2.6 Structural Model of Customer Brand Engagement

The structural model process was replicated for brand engagement in which the dimensions

of attention, enthusiasm, absorption, identification, interaction and social brand

engagement were assessed for their relationship with the higher-order latent construct of

customer brand engagement.

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FIGURE 4-7: MEASUREMENT MODEL - CUSTOMER BRAND ENGAGEMENT

TABLE 4-11: GOODNESS OF FIT INDICES – BRAND ENGAGEMENT χ² df χ²/df p GFI NFI TLI CFI RMSEA

441.75 183 2.41 0.00 0.87 0.93 0.96 0.96 0.07

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The brand engagement structural model (Figure 4-7 and Table 4-11) achieved acceptable

fit with the data. Standardised factor loadings for each indicator were above 0.70

confirming convergent validity (Kline 2011) with the exception of brand identification

(0.64) which achieved an acceptable (>0.50) although not ideal value (Hair et al. 2012).

The findings of the structural model support the proposition that social brand engagement

is a significant dimension of customer brand engagement, with a standardised factor

loading of 0.76 (Figure 4-7). The personal exchanges between customers have a strong

impact on the brand, as brand-related discussion can impact the overall interest the

customer has in the brand. Social brand engagement is therefore an important dimension

that significantly contributes to the higher-order construct of customer brand engagement.

4.2.7 Discussion of Hypothesis 1

TABLE 4-12: SUMMARY OF HYPOTHESIS 1 H# Hypothesis Supported/ Not Supported

1a Social event engagement is a dimension of customer event engagement

Partially Supported

1b Social brand engagement is a dimension of customer brand engagement

Supported

H1a: Social event engagement is a dimension of customer event engagement

Convergent validity, discriminant validity and reliability of each of the customer event

engagement dimensions were confirmed; attention, enthusiasm, absorption, identification,

interaction and social event engagement. These results support social event engagement as

distinct from the other dimensions of customer event engagement. However, the structural

model of customer event engagement only achieved satisfactory fit. A covariance was

placed on the error terms of social engagement and interaction dimensions in the event

engagement construct model. The social event engagement and event interaction constructs

remained in the model despite their potential distinction from the other customer event

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engagement dimensions. This structure of customer engagement has been used by Calder

et al. (2009), who identify two broad engagement constructs; personal engagement and

social-interactive engagement elements (Calder et al. 2009). This finding is discussed

further in Chapter 5, directions for future research. Therefore, H1a was partially

supported.

H1b: Social brand engagement is a dimension of customer brand engagement

A measurement model confirmed the discriminant validity and reliability of each of the

customer brand engagement dimensions; attention, enthusiasm, absorption, identification,

interaction and social brand engagement. The findings confirm that social brand

engagement holds as a unique dimensions and not a subset of an existing element of brand

engagement. The second-step involved structural model testing, in which social brand

engagement was found to significantly contribute to the higher-order construct of customer

brand engagement. This structural model achieved fit, and therefore H1b was supported.

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4.3 Path Model Analysis using Structural Equation Modelling

4.3.1 Path Model Analysis

Path analysis refers to a SEM approach that estimates the strength and significance of

relationship between constructs, assessed through the strength of paths illustrated in the

path diagram (Hair et al. 2012). A path diagram is a visual representation of the complete

conceptual model and includes the complete set of hypothesised relationships among the

included constructs (Hair et al. 2012).

Path model analysis was used to investigate hypotheses H2, H3 and H4;

H2a-j: Cognitive, emotional, sensorial, pragmatic and relational event experiences contribute to

customer event engagement and customer brand engagement

H3: There is a positive relationship between customer event engagement and customer brand

engagement

H4a-b:There is a positive relationship between customer event engagement (and customer brand

engagement) and behavioural intention of loyalty

Each of these hypotheses are assessed using the complete path model as this allows the

nature of the relationships among the antecedents (BME experiential components), event

engagement, brand engagement and behavioural intention of loyalty to be explored

simultaneously and their combined effects considered (Hair et al. 2012). In this regard,

path analysis is a comprehensive method that captures the relationships among

independent variables and considers the direct and indirect effects on the dependent

variables (Kline 2011). The relationships between experiential components and customer

engagement (H2a-j), in particular, benefit from path model analysis as each experiential

component is assessed for its contribution to event engagement and brand engagement, and

test the relationship between event engagement and brand engagement. Overall, this

represents two relationships between experience and brand engagement; directly and

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indirectly through event engagement. The latter is referred to as an indirect effect (Kline

2011).

SEM requires a large sample size to ensure statistical stability. A rule of thumb is that the

ratio of sample size to the number of model parameters should be at least 5:1, preferably

10:1 (Hair et al. 2012; Kline 2011). An even greater ratio is required in situations where

data does not conform to assumptions of multivariate normality (Hair et al. 2012), as is

common in research practice (Byrne 2001). It is recommended that sample sizes of above

200 be implemented to ensure accuracy (Hair et al. 2012). The achieved sample size of

274, although an acceptable size for simple models (e.g. one-factor congeneric

measurement models), was not deemed sufficient for the analysis of the proposed complex

models if latent and observed variables were included (Rowe 2002). Therefore, composite

variables were calculated based on the results of the one-factor congeneric measurement

model, and the path model constructed using these composite measures.

4.3.2 Calculation of Composite Variables

Composite variables have commonly been calculated as a means of data reduction (Rowe

2002), and enable a more accurate evaluation of complex models despite a limited sample

size. The use of composite variables includes firstly creating the variables using factor

score weights through AMOS 21 (Rowe 2002). Second, the factor loading and error

variance value for each composite variable is computed to remove additional complexity

from the overall model, hence providing greater stability and accuracy of the path model

results. The resulting composite variables and their respective factor loadings and error

variances are implemented in the path analysis model.

Factor score weights were derived from each one-factor congeneric measurement model

and were used to calculate the composite variables (Rowe 2002) once each construct had

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satisfied construct validity and reliability. The values estimated from a single one-factor

congeneric measurement model are likely to be more stable than values desired from an

overall measurement model as the model is far less complex; this is particularly important

when using a relatively small sample size. This ensures reliability and validity of the

composite variables (Rowe 2002). Fitting a one-factor congeneric measurement model

allows for differences in the degree to which each individual measure contributes to the

overall composite scale, thus providing a more realistic representation of the data (Rowe

2002). In addition, fitting a one-factor congeneric measurement model takes into account

the measurement error associated with the measurement of the indicator variables.

The factor score weights were transferred into EXCEL 2010 and used to calculate a sum of

weights for each construct. The factor score weight for each item were divided by the sum

of weights calculated for the respective construct to produce a proportionally weighted

scale score for each item (Rowe 2002). The final composite scores were then computed in

SPSS 21.

Path models can investigate the relationships amongst the latent variables underlying these

composite scales rather than the original observed variables. An extra step was also taken

to further reduce the amount of paths to be estimated, hence decreasing the complexity of

the model and creating greater stability in the path model results; this involved computing

the factor loadings and error variances for each composite variable and including this

information in the path model (Politis 2001). This approach is beneficial as the structural

parameter estimates are more stable; instead of using a large number of raw indicator

variables to measure the latent constructs in the full model, a much smaller number of

composite indicators are computed. Each latent variable was therefore measured by a

single composite variable in which the composite scale variance, standard deviation and

reliability were used to fix the composite variable factor loading and measurement error

variance (Politis 2001). These values were calculated from the standard deviation of the

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composite variable and the reliability of the composite variable, which is calculated using

coefficient H (Hancock and Mueller 2001; Mueller and Hancock 2008).

Cronbach’s alpha is criticised as being an under-estimate of the reliability for congeneric

measures. Conversely, coefficient H is a ‘maximised’ reliability indicator and is considered

a better estimate of composite reliability if one-factor congeneric measurement models

have been used to develop the composite variable (Mueller and Hancock 2008). Therefore,

coefficient H values were calculated for each composite variable as an indicator of

composite reliability.

The final step, reported in Table 4-13, is calculating the factor loading (λ = sx*√ rx) and

error variance (Ɵ = sx2 [1-rx]) values for each composite variable (Politis 2001). The

resultant values are built into the path model to account for the known amount of error

associated with the measurement of each latent variable (Politis 2001).

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TABLE 4-13: FACTOR LOADINGS AND ERROR VARIANCES FOR COMPOSITE VARIABLES Name of Latent Variable Standard

Deviation of Composite (sx)

Reliability of Composite (rx)

Factor Loading (λ) (sx*√ rx)

Error Variance (Ɵ) (sx

2 [1-rx])

Cognitive experience 1.23 0.89 1.16 0.17

Emotional experience 1.20 0.91 1.15 0.13

Sensory experience 1.27 0.94 1.23 0.09

Pragmatic experience 1.36 0.84 1.25 0.30

Relational experience 1.37 0.97 1.34 0.06

Event attention 1.26 0.85 1.16 0.24

Event identification 1.52 0.92 1.46 0.18

Event enthusiasm 1.30 0.94 1.25 0.11

Event absorption 1.22 0.85 1.12 0.22

Event interaction 1.26 0.97 1.24 0.06

Social event engagement 1.40 0.85 1.29 0.30

Brand attention 1.35 0.95 1.32 0.09

Brand identification 1.50 0.96 1.46 0.10

Brand enthusiasm 1.53 0.98 1.51 0.06

Brand absorption 1.42 0.91 1.36 0.18

Brand interaction 1.22 0.98 1.21 0.04

Social brand engagement 1.28 0.88 1.21 0.19

Behavioural intention of loyalty 1.12 0.98 1.11 0.02

Novelty-seeking 0.86 0.95 0.84 0.04

Need for affect 1.29 0.91 1.23 0.14

Need for cognition 1.20 0.92 1.15 0.12

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4.4 Evaluating Path Models

The process of path model analysis follows the following basic steps of SEM; specify the

model, evaluate model identification, estimate the model and re-specify the model (Kline

2011). These steps are common and followed in most analyses (Kline 2011). This thesis

describes each step in the following section.

4.4.1 Model Specification

Model specification involves the diagrammatic representation of proposed relationships

between constructs of interest which enables testing of hypotheses (Kline 2011). The

specified model utilised in this thesis is theory-driven and reflects the conceptual model

introduced in Chapter 2. It is important that the model is grounded in theory because SEM

is a confirmatory technique; the program cannot suggest path relationships but rather

assesses the accuracy of predicted relationships against the data (Hair et al. 2012).

Therefore, theoretical relationships established in the literature are used to specify

relationships between constructs and establish causation (Hair et al. 2012).

4.4.2 Model Identification

Model identification refers to the ability for the program to allow a unique estimate of all

model parameters; if the requirements of identification are not met, the model is ‘not

identified’ and analysis cannot be conducted or output is meaningless (Kline 2011). Two

requirements must be met in order for the path model to be identified; first, the number of

observations must equal or be greater than the number of free model parameters; second,

all latent variables must have an assigned scale (Kline 2011). The specified model created

in this thesis met the requirements of model identification.

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4.4.3 Model Estimation

Model estimation includes evaluating model fit and interpreting the parameter estimates

(Kline 2011). As previously discussed in Chapter 3, a variety of fit indices were utilised in

this thesis to assess how well the data fit the theoretical model; the principal goodness-of-

fit index (χ²/df), Goodness-of-fit index (GFI), Root mean square error of approximation

(RMSEA), Normed Fit Index (NFI), Tucker Lewis Index (TLI) and Comparative Fit Index

(CFI) (Hair et al. 2012). The fit indices and their respective threshold values are outlined in

Table 3-7.

The estimation technique utilised throughout this thesis is maximum likelihood estimation

as it is a flexible approach, has proven robust even when the data does not meet normality

assumptions, and therefore is the most widely used approach and the default estimation

technique in most SEM programs including AMOS21 (Hair et al. 2012).

Parameter estimates are then examined to assess each of the relationships proposed in the

model. Parameter estimates must be statistically significant and in the predicted direction;

standardised loading estimates are reported in Table 4-15 (Hair et al. 2012).

Figure 4-8 shows the identified path model, consisting of the composite variables

representing the five experiential components, event engagement, brand engagement and

behavioural intention of loyalty.

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FIGURE 4-8: IDENTIFIED PATH MODEL

TABLE 4-14: GOODNESS OF FIT INDICES FOR IDENTIFIED PATH MODEL χ² df χ²/df p GFI NFI TLI CFI RMSEA

541.00 118 4.60 0.00 0.80 0.81 0.80 0.84 0.12

Results from the identified path model indicate poor fit with the data (χ²/df =4.60, p=0.00,

GFI=0.80, NFI=0.81, TLI=0.80, CFI =0.84, RMSEA =0.12), with no fit indices reaching

their respective thresholds as outlined in Table 3-7. It is very common for specified models

to not achieve fit (Kline 2011); a poor fitting model indicates that some hypotheses

reflected by the paths may not have empirical support, or a relationship exists between

constructs or error variables that have not yet been accounted for in the model. Parameter

estimates are observed to identify insignificant and problematic paths contributing to poor

model fit.

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TABLE 4-15: REGRESSION WEIGHTS – ORIGINAL PATH MODEL Estimate S.E. C.R. p

EVENT_ENGAGEMENTEMOTIONAL_EXP .155 .073 2.115 .034

EVENT_ENGAGEMENTSENSORIAL_EXP .229 .066 3.488 ***

EVENT_ENGAGEMENTCOGNITIVE_EXP .052 .061 .851 .395

EVENT_ENGAGEMENTRELATIONAL_EXP .254 .050 5.062 ***

EVENT_ENGAGEMENTPRAGMATIC_EXP .223 .060 3.736 ***

BRAND_ENGAGEMENTCOGNITIVE_EXP .328 .079 4.132 ***

BRAND_ENGAGEMENTEVENT_ENGAGEMENT .991 .137 7.238 ***

BRAND_ENGAGEMENTEMOTIONAL_EXP -.181 .094 -1.930 .054

BRAND_ENGAGEMENTSENSORIAL_EXP .017 .087 .199 .842

BRAND_ENGAGEMENTPRAGMATIC_EXP -.268 .081 -3.293 ***

BRAND_ENGAGEMENTRELATIONAL_EXP -.065 .069 -.935 .350

BEH_INT_LOYALTY BRAND_ENGAGEMENT .532 .067 7.916 ***

BEH_INT_LOYALTY EVENT_ENGAGEMENT .120 .083 1.441 .149

*** indicates p-value significantly different from zero at the 0.001 level (two-tailed)

Regression weights output (Table 4-15) shows a number of insignificant paths; cognitive

and emotional experiences did not have significant relationships with event engagement;

emotional, sensorial and relational experiences did not have significant relationships with

brand engagement; finally, the relationship between event engagement and behavioural

intention of loyalty was also insignificant. This led to model re-specification, which is

described in the following section.

4.4.4 Model Re-specification

Model re-specification is the process of adding or deleting paths in order to achieve a more

parsimonious model (Hair et al. 2012; Kline 2011). However, manipulations to the model

should not occur without justification; re-specification should adhere to the same principles

followed in model specification (Kline 2011). The re-specified model must also achieve

the aforementioned requirements of model identification (Kline 2011).

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First, insignificant paths were eliminated (Hair et al. 2012). A number of insignificant

paths between emotional, sensorial and relational experience leading to brand engagement

were removed. This is conceptually justified as components of BME experience engage

customers initially with the event, which then translates into brand engagement through the

process of engagement transfer. An insignificant path between emotional experience and

event engagement was also removed; therefore, the emotional experience construct was

removed entirely as no paths (hypothesised relationships) remained. This finding is

unexpected as the emotional elements of an event is strongly emphasised in marketing

events literature (Leischnig et al. 2011; Packer and Ballantyne 2004; Whelan and Wohlfeil

2006). Conceptual justification for the removal of this construct is in detailed the following

section 4.4.5.

In addition, the path between cognitive experience and event engagement was removed;

the remaining significant path indicated a direct relationship between cognitive experience

and brand engagement. Events with a strong cognitive experience are likely to be highly

brand-centric, with discussion and information based on the brand itself. Further

justification is given in section 4.4.5.

Finally, the insignificant path between event engagement and behavioural intention of

loyalty was removed. This finding supports the notion of engagement transfer, as it

demonstrates how brand outcomes do not occur directly from event engagement; brand

engagement must be facilitated through its relationship with event engagement in order for

behavioural intention of loyalty to result.

Following the elimination of insignificant paths, modification indices (MI) were identified

in AMOS 21 (Hair et al. 2012). Modification indices estimate the level of model

improvement achieved if an additional path was entered into the model, with values of 4.0

or greater suggesting significant model improvement (Hair et al. 2012). Expected

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parameter changes are also consulted as it indicates the estimated positive or negative

change for the parameter in the model (Byrne 2001).

A modification made to the model was to place covariances on the error terms for each

event and brand engagement counterpart. The nature of the measurement items for event

and brand engagement was described in Chapter 3; the same items were replicated for both

engagement objects with rewording to reflect either ‘event’ or ‘brand’. This technique has

been implemented in previous studies (Drengner et al. 2008; Gwinner and Eaton 1999),

with similar responses giving support of image transfer. However, repeated measures can

experience issues of auto-correlation error and therefore error covariances were placed

between each event and brand engagement dimension to account for this error (Kline

2011); i.e. between event attention and brand attention; event and brand identification;

event and brand enthusiasm; event and brand absorption; event and brand interaction;

event and brand social engagement.

The re-specified model, accounting for each of the identified modifications, is now

discussed.

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FIGURE 4-9: RE-SPECIFIED PATH MODEL

* Covariances between e6 and e12 = .24; e7 and e13 = .61; e8 and e14 = .17; e9 and e15 = .14; e10 and e16 = .24; e11 and e17 = .27 not shown on diagram.

TABLE 4-16: GOODNESS OF FIT INDICES FOR RE-SPECIFIED PATH MODEL χ² df χ²/df p GFI NFI TLI CFI RMSEA

268.45 104 2.58 0.00 0.89 0.90 0.91 0.93 0.08

Reasonable model fit is established for the re-specified path model (χ²/df =2.58, p=0.00,

GFI=0.89, NFI=0.90, TLI=0.91, CFI =0.93, RMSEA =0.08), based on the threshold values

of fit indices. Although the p-value was not significant and a number of fit indices only

came close to their threshold values, the values obtained were deemed sufficient due to the

complexity of the model which can weaken the overall fit and therefore cause the original

fit thresholds to be unattainable (Hair et al. 2012). In addition, through assessment of

parameter estimates (Table 4-17) it is found that all included paths achieved significance.

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In brief, the conceptual model was re-specified based on statistical and theoretical

considerations with the aim of achieving a more parsimonious model. Insignificant paths

were removed and covariances were placed between a number of error terms.

Rationalisation of each of these modifications was provided and led to a re-specified model

which achieved reasonable model fit.

The following section details the implications of the path model findings for hypotheses 2,

3 and 4 introduced in Chapter 2.

TABLE 4-17: REGRESSION WEIGHTS: - RE-SPECIFIED PATH MODEL

Estimate S.E. C.R. p

EVENT_ENG SENSORIAL_EXPERIENCE .330 .055 5.964 ***

EVENT_ENG PRAGMATIC_EXPERIENCE .282 .059 4.808 ***

EVENT_ENG RELATIONAL_EXPERIENCE .259 .050 5.195 ***

BRAND_ENG EVENT_ENGAGEMENT .844 .103 8.175 ***

BRAND_ENG COGNITIVE_EXPERIENCE .297 .070 4.238 ***

BRAND_ENG PRAGMATIC_EXPERIENCE -.279 .079 -3.512 ***

BEH_INT_LOYALTY BRAND_ENGAGEMENT .604 .048 12.534 ***

*** indicates p-value significantly different from zero at the 0.001 level (two-tailed)

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The set of hypotheses 2a-2j address the research question of whether experiential

components of a BME facilitate customer event engagement and customer brand

engagement. It was proposed that due to the nature of BMEs with regards to their high

level of interaction, and the unique and customer-driven experience created, that BMEs

could facilitate customer engagement (Crowther and Donlan 2011). Support of these

hypotheses would advocate the use of BMEs as a strategic driver of customer engagement.

The re-specified path model (Figure 4-9) indicated significant relationships between

sensorial, pragmatic and relational BME experiences and event engagement, while

cognitive experience directly impacted brand engagement. Pragmatic experience had a

direct negative relationship with customer brand engagement, but this will be argued to be

due to a suppressor effect. The hypotheses and associated outcome obtained from data

analysis are outlined in Table 4-18. Each hypothesis is then briefly addressed in the

following paragraphs. Emphasis is given to results which do not support the hypotheses

developed in Chapter 2, while supported hypotheses have already been described and will

be the focus of discussion in Chapter 5.

TABLE 4-18: SUMMARY OF HYPOTHESIS 2

H# Hypothesis Supported/Not Supported

2a Cognitive event experience contributes to customer event engagement Not supported

2b Cognitive event experience contributes to customer brand engagement Supported

2c Emotional event experience contributes to customer event engagement Not Supported

2d Emotional event experience contributes to customer brand engagement Not Supported

2e Sensorial event experience contributes to customer event engagement Supported

2f Sensorial event experience contributes to customer brand engagement Not Supported

2g Pragmatic event experience contributes to customer event engagement Supported

2h Pragmatic event experience contributes to customer brand engagement Not Supported

2i Relational event experience contributes to customer event engagement Supported

2j Relational event experience contributes to customer brand engagement Not Supported

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H2a: Cognitive event experience contributes to customer event engagement

The results revealed an insignificant relationship between cognitive experience and event

engagement. Cognitive experiences include education or information sessions in which the

attendee is provided with brand information to increase their brand-related knowledge in

an area of interest (Gentile et al. 2007). Education events are described as eliciting

customer interaction, however the customer’s focus is not necessarily on the event but

rather the content shared during the event (Pine and Gilmore 1998).The experience sparks

attention and interest towards the brand specifically, and not with the event activity. The

event is brand-centric, with discussions and information focused specifically on the brand;

therefore, the focal object of engagement is the brand, not the event. Consequently, H2a

was not supported.

H2b: Cognitive event experience contributes to customer brand engagement

A significant direct relationship was found between cognitive experience and brand

engagement. This was the only significant direct relationship between a BME experience

and brand engagement; the other BME experiences impacted on event engagement, and

therefore indirectly influenced brand engagement. As previously discussed, the brand-

centric nature of a cognitive experience provides the rationale for a strong direct impact on

brand engagement (Pine and Gilmore 1998). Cognitive experiences involve thinking and

mental processes regarding the brand specifically, which impacts the customer’s

perception of the brand (Yuan and Wu 2008). Therefore the cognitive experience affects

engagement toward the brand, as opposed to being transferred from the event through to

the brand. H2b was supported.

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H2c: Emotional event experience contributes to customer event engagement

The results showed that the relationship between emotional experience and event

engagement was insignificant. This finding is unexpected as the emotional elements of an

event is strongly emphasised in marketing events literature (Leischnig et al. 2011; Packer

and Ballantyne 2004; Whelan and Wohlfeil 2006). However, this finding is explained as

emotional experiences may create pleasant experiences or feelings of excitement but not

necessarily evoke the level of interaction or psychological state with regards to the event

required to achieve engagement (Pine and Gilmore 1998); customers can enjoy an

emotional BME experience while remaining passive in that experience. Therefore, H2c

was not supported.

H2d: Emotional event experience contributes to customer brand engagement

The relationship between emotional experience and brand engagement was insignificant,

H2d was not supported; this finding led to the removal of the emotional experience

construct from the re-specified model as neither of the hypotheses regarding emotional

experience were supported. The brand-provided resources in an emotional experience

include the source of entertainment designed to generate customer enjoyment (Tynan and

McKechnie 2009). However, this experience may not provide sufficient emotional value

(Yuan and Wu 2008) that would encourage customers to contribute to the exchange with

their engagement. This is an important finding of this thesis, and is discussed with

reference to managerial implications in Chapter 5.

H2e: Sensorial event experience contributes to customer event engagement

The parameter estimate highlighting the relationship between sensorial experience and

event engagement was significant, leading to the support of H2e. The brand-provided

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resources in a sensorial experience, including sources of sight, sound, scent, taste, and

touch (Yuan and Wu 2008) provide sensory meaning and stimulation (Gentile et al. 2007;

Schmitt 1999), and facilitate customer event engagement.

H2f: Sensorial event experience contributes to customer brand engagement

The relationship between sensorial experience and brand engagement was insignificant,

emphasising that sensorial experiences only have an indirect impact on brand engagement

through the event engagement construct. H2f was not supported. The focal element of a

sensorial experience is sensory stimulation (Gentile et al. 2007); therefore the experience

inherently requires active participation from the customer in the BME activity. Customer

engagement occurs with the event as the focus of the participation is on the event activity,

not the brand.

H2g: Pragmatic event experience contributes to customer event engagement

The results showed that pragmatic experience had a significant relationship with event

engagement, giving support to H2g. A pragmatic experience encompasses physical

activities designed to stimulate active customer participation (Mollen and Wilson 2010),

and drives customer event engagement.

H2h: Pragmatic event experience contributes to customer brand engagement

Although a significant relationship was indicated between pragmatic experience and brand

engagement, the parameter estimate reported a strong negative relationship. This finding

contradicts the hypothesised relationship established from literature, and is in conflict with

the other paths identified in the model, for example pragmatic experience has a negative

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effect on brand engagement, however brand engagement maintains a significant and

positive relationship with BIL.

It is argued that this construct has experienced a suppression effect (Kline 2011).

Suppressor variables are relatively common in SEM, however are often met with problems

of interpretation by researchers (Maassen and Bakker 2001). Although statistically the p-

value is significant (>0.05), a suppressor variable does not have a relationship with the

dependent variable, but instead has correlations with one or more independent variables.

The commonalities between the suppressor and other independent variables are irrelevant

to the identified dependent variable (Maassen and Bakker 2001). Therefore, the suppressor

variable (pragmatic experience) enhances the predictive power of the related independent

variables (other experiential component constructs); however, as the suppressor variable

and other independent variables are positively correlated with regards to an aspect

irrelevant to the dependent variable (brand engagement), the relationship in the path model

between the suppressor (pragmatic experience) and the dependent variable (brand

engagement) becomes negative.

Conceptually, this phenomenon illustrates that pragmatic experience has relationships with

the other components of experience; cognitive, sensorial and relational. Together these

constructs have strong predictive power on ‘something’ other than brand engagement; this

could reflect their combined impact on event engagement, or it could refer to something

not captured in the path model. As identified in the conceptual discussion of pragmatic

experience (Section 2.4.2.4, Chapter 2), pragmatic experiences can vary greatly and

include cognitive or emotional elements, depending on the activity (Pine and Gilmore

1998). Therefore, the customer may not perceive the experience as purely ‘pragmatic’, but

rather as pragmatic and emotional (e.g. a grape stomp) or pragmatic and cognitive (e.g.

creating your own wine blend). The combined effects of these perceived experiences

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contribute to the path model but do not reflect a relationship between pragmatic experience

and brand engagement, hence the suppression effect resulting in a negative path estimate.

This path was maintained in the model as it achieved significance and therefore has

predictive power, however as a suppressor variable this relationship should not be

interpreted as pragmatic experiences having a negative impact on brand engagement

(Maassen and Bakker 2001). Instead, it is recognised that the pragmatic experience

construct contributes to the other independent variables (BME experiences) and together

explain relationships in the model. Therefore, H2h is not supported.

H2i: Relational event experience contributes to customer event engagement

The relationship between relational experience and event engagement was significant, and

therefore H2i was supported. The interactions during a relational event induce a heightened

sense of connectedness with other customers in the context of the event (Kozinets 2014),

providing social value (Tynan and McKechnie 2009).

H2j: Relational event experience contributes to customer brand engagement

The results did not support the relationship between relational experience and brand

engagement. Relational experiences only contribute to brand engagement indirectly

through event engagement which reported a significant relationship. Therefore, H2j was

not supported.

For a relational experience, the brand-provided resources encompass activities designed to

be experienced together with other people (Gentile et al. 2007). Therefore, because the

other attendees and relational activity in which they interact are focal to the experience,

relational experience facilitates customer event engagement, not customer brand

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Overall, the findings are in support of BME experiences facilitating customer event

engagement. The sensorial, pragmatic and relational experiences during a BME facilitate a

heightened psychological state in the customer, resulting in engagement with the event;

however, these experiences do not have a significant relationship with customer brand

engagement. Cognitive experience facilitates customer brand engagement, but does not

have a significant relationship with customer event engagement. This finding reflects the

highly brand-centric nature of cognitive experiences. The next section discusses hypothesis

3; the relationship between customer event engagement and customer brand engagement.


The following section addresses the research question of the relationship between two

focal engagement objects; specifically does customer event engagement further facilitate

customer brand engagement. The re-specified path model (Figure 4-9) indicated a

significant relationship between the event engagement and brand engagement constructs,

supporting hypothesis 3.


H# Hypothesis Supported/ Not Supported

3 There is a positive relationship between customer event engagement and customer brand engagement Supported

H3: There is a positive relationship between customer event engagement and

customer brand engagement

A strong and significant relationship was evident between customer event engagement and

customer brand engagement, and H3 was supported. The customer interacts and creates

value during an event experience and therefore elicits customer event engagement. Then,

due to the strong connection between the event and the brand, this state of engagement also

projects onto the brand (Smith 2004).

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Additionally, the results support a notion of engagement transfer. It was found that BME

experiences had a significant relationship with customer event engagement, however,

largely not with customer brand engagement (with the exception of cognitive experience).

It could therefore be argued that customer engagement does not generally occur directly

with the brand, but rather customer event engagement is facilitated as a result of the BME

experience, which is then transferred onto customer brand engagement.


The following discussion provides insight into the research question on outcomes of brand

engagement; namely, whether brand engagement leads to increased behavioural intention

of loyalty. The re-specified path model (Figure 4-9) indicated a significant relationship

between brand engagement and brand behavioural intention of loyalty. The relationship

between event engagement and behavioural intention of loyalty was insignificant.

TABLE 4-20: SUMMARY OF HYPOTHESIS 4 H# Hypothesis Supported/ Not Supported

4a There is a positive relationship between customer event engagement and behavioural intention of loyalty Not supported

4b There is a positive relationship between customer brand engagement and behavioural intention of loyalty Supported

H4a: There is a positive relationship between customer event engagement and

behavioural intention of loyalty

The direct relationship between event engagement and behavioural intention of loyalty was

not significant, and therefore H4a was not supported. Although BME experiences

generally had a relationship with customer event engagement, not customer brand

engagement, the customer event engagement construct did not contribute to behavioural

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intention of loyalty. Marketing event research that take an associative network theory

perspective advocate that brand-related outcomes are a direct result of brand attitudes, not

event attitudes (Martensen et al. 2007). These brand attitudes are the drivers of brand-

related outcomes (Martensen et al. 2007).

H4b: There is a positive relationship between customer brand engagement and

behavioural intention of loyalty

The re-specified path model showed a strong and significant relationship between brand

engagement and behavioural intention of loyalty, in support of H4b. The heightened

psychological state that occurs between customer and the brand impacts the customers

future purchase intentions and word of mouth, two key dimensions of BIL (Sheth et al.

1991; So et al. 2012).This supports the notion that customer brand engagement must be

facilitated in order for brand-outcomes to occur, as customer brand engagement is the only

significant and direct impact on behavioural intention of loyalty.

These findings provide support for a notion of engagement transfer. BME experiences

generally have a relationship with event engagement, not brand engagement. However,

event engagement does not directly contribute to behavioural intention of loyalty, which

indicates that an additional construct (brand engagement) must provide a mediation effect

between event engagement (an outcome of BME experiences) and behavioural intention of

loyalty toward the brand. This relationship is consistent with the process of spreading

activation within associative network theory (Smith 2004). Customer event engagement is

first facilitated, which is then projected onto customer brand engagement. The results

justify the inclusion of both customer event engagement and customer brand engagement

constructs; BME experiences generally result in customer event engagement (Vivek et al.

2012), while only customer brand engagement results in behavioural intention of loyalty

(Zarantonello and Schmitt 2010). A significant relationship exists between event and brand 174 | P a g e

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engagement (Smith 2004). Therefore, strong support is found for the transfer of the

engagement effect from the focal object of the event to the brand as the focal object.

Following model re-specification, multi-group path analysis was conducted to test whether

model parameters vary between high and low experiential needs samples. The results are

outlined in the following section.

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4.5 The Moderation Effect of Experiential Needs

4.5.1 Method for Multi-group Analysis

The previous analysis focused on the thesis sample in its entirety, which included

respondents who are likely to exhibit different experiential needs. Chapter 2 identified the

potential for an individual’s experiential needs to moderate the extent to which particular

experiential components effect event engagement (MacInnis and Jaworski 1989;

Steenkamp and Baumgartner 1992 ; Wilson 1997). This research question of moderation is

investigated in this section.

This thesis utilised multi-group analysis to consider moderation effects. This particular

analysis technique allowed the calculation of moderation in the complete path model and

the investigation of its effects on individual paths, providing a holistic view of the

moderation impact (Kline 2011). Multi-group analysis was deemed valuable to identify

whether the final model replicated well for each sub-sample, or whether different impacts

were found. Using the group analysis feature in AMOS 21, parameters were constrained

and the model-re-estimated. Nested model comparisons tests (Chi-Square difference test)

assessed whether values of the model parameters varied across groups (Kline 2011;

Vandenberg and Lance 2000). Nested models involved the estimation and comparison of

two different models. First, a baseline model was calculated by simultaneously estimating

the final generic path model across both groups (Byrne 2001). Structural regression

weights were then constrained and set equal across the groups, followed by a re-estimation

of the model. To show the existence of moderators, the analysis must show that the

equality constraint is not reasonable, and that the two parameters significantly differ from

each other (Byrne 2001). Comparison of models was conducted using chi-square change

and significance values (Byrne 2001), with a p-value < .05 indicating that the constrained

model has significantly worse fit, and therefore the unconstrained model can be assumed as

correct.

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High and low groups were created by calculating the mean value of each construct,

splitting the sample into high and low groups, and removing the mean value to two decimal

places. These values are outlined in Table 4-21.

TABLE 4-21: EXPERIENTIAL NEEDS GROUPS - VALUE CLASSIFICATION Cognition 5.37 n Affect 4.26 n Novelty 6.05 n

Lower group (<) 5.36 127 Lower group (<) 4.25 129 Lower group (<) 6.04 163

higher group (>) 5.38 146 higher group (>) 4.27 143 higher group (>) 6.06 111

The high and low groups for each experiential need were then categorised within the path

model, which allowed the output to reflect the entire sample, the ‘low’ needs group and the

‘high’ needs group. The results for each experiential need are shown on a replicated path

model; one indicating the path estimates and relationships present for the high needs group

and the other reflecting the results from the low needs group.

Due to the complexity of the model, and the limited sample size per group, it was deemed

appropriate to further create composite measures for both brand engagement and event

engagement as a means of data reduction (Rowe 2002). This would allow more accurate

observation of differences in structural weights (i.e. paths within the model).

The results of the chi-square difference test (∆χ²) were then presented, measuring

invariance of the unconstrained and constrained models (Vandenberg and Lance 2000).

This test observed the change in goodness-of-fit when cross-group constraints were

imposed upon the model (Cheung and Rensvold 2002). In addition, the critical ratios for

differences between parameters was reported as this clearly indicates the specific

relationships of significant difference between high needs and low needs groups.

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4.5.2 Need for Cognition

The following path models demonstrate the differences in standardised estimates when the

path model is calculated using only the low need for cognition group (Figure 4-10) and the

high need for cognition group (Figure 4-11).

FIGURE 4-10: PATH FOR LOW NEED FOR COGNITION

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FIGURE 4-11: PATH MODEL FOR HIGH NEED FOR COGNITION

The chi-square difference test (∆χ²) (Vandenberg and Lance 2000) indicated that the

unconstrained and constrained models were significantly different (p=0.01) and the

equality constraint is not reasonable; therefore, high and low need for cognition groups

differ from each other.

TABLE 4-22: NESTED MODEL COMPARISONS AND GOODNESS OF FIT INDICES - NEED FOR COGNITION

χ² ∆χ² df ∆ df χ²/df p GFI NFI TLI CFI RMSEA

Unconstrained Model 30.82 - 16 - 1.93 0.01 0.97 0.96 0.95 0.98 0.06

Structural Weights Equal Model 50.60 19.73 23 7 2.20 0.00 0.95 0.93 0.93 0.96 0.07

Significance of nested model comparison, assuming unconstrained model to be correct: p = 0.01

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TABLE 4-23: NEED FOR COGNITION Low needs High needs Critical ratios a

BILBRAND_ENGAGEMENT 0.74 0.71 -0.91

BRAND_ENGPRAG_EXP -0.28 -0.28 0.04

EVENT_ENGSENS_EXP 0.55 0.20 -2.80*

EVENT_ENGPRAG_EXP 0.19 0.37 1.31

EVENT_ENGREL_EXP 0.08 0.42 3.24*

BRAND_ENGEVENT_ENG 0.79 0.91 1.02

BRAND_ENGCOG_EXP 0.23 0.16 -0.60 a Critical Ratios for Differences between Parameters (Unconstrained) * significant difference (>1.96)

An examination of the individual hypothesised relationships (Table 4-23) showed that the

relationship between sensorial experience and event engagement was significantly stronger

for individuals with low need for cognition (0.55) than high need for cognition (0.20). In

addition, the relationship between relational experience and event engagement was

significantly stronger for individuals with high need for cognition (0.42) than low need for

cognition (0.08). The remaining five relationships did not achieve a significant critical ratio

value (<1.96), indicating that high and low need for cognition groups do not differ in their

engagement resulting from pragmatic and cognitive experiences. Conceptual support for

these findings is provided in the discussion of hypotheses section.

4.5.3 Need for Affect

The multi-group path analysis was then replicated to investigate the moderation effect of

need for affect. The path models were then tested for differences in standardised estimates

between the low need for affect group (Figure 4-12) and the high need for affect group

(Figure 4-13).

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FIGURE 4-12: PATH MODEL FOR LOW NEED FOR AFFECT

FIGURE 4-13: PATH MODEL FOR HIGH NEED FOR AFFECT

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The chi-square difference test (∆χ²) (Vandenberg and Lance 2000) indicated that the

unconstrained and constrained models were not significantly different (p=0.67) and the

equality constraint is reasonable; therefore, high and low need for affect groups do not

differ from each other.

TABLE 4-25: NEED FOR AFFECT Low needs High needs Critical ratios a

BIL BRAND_ENGAGEMENT 0.70 0.72 0.412

BRAND ENG PRAG_EXP -0.35 -0.22 0.949

EVENT_ENG SENS_EXP 0.31 0.47 0.743

EVENT_ENG PRAG_EXP 0.32 0.17 -0.947

EVENT_ENG REL_EXP 0.37 0.20 -1.35

BRAND_ENGEVENT_ENG 0.82 0.84 -0.452

BRAND_ENG COG_EXP 0.23 0.18 -0.812 a Critical Ratios for Differences between Parameters (Unconstrained) * significant (>1.96)

An examination of the individual hypothesised relationships confirmed that there were no

significant path differences for high need for affect versus low need for affect groups, as all

critical ratio values were below 1.96. Therefore, there is no difference between individuals

with high and low need for affect with regards to the influence of BME experiences on

event engagement. Implications of this result are considered in the discussion of

hypotheses section.

TABLE 4-24: NESTED MODEL COMPARISONS AND GOODNESS OF FIT INDICES - NEED FOR AFFECT





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4.5.4 Novelty-Seeking Needs

The final multi-group path analysis tested moderation by novelty-seeking needs. The

following path models outline the differences in standardised estimates between the low

novelty-seeking needs group (Figure 4-14) and the high novelty-seeking needs group

(Figure 4-15).

FIGURE 4-14: PATH MODEL FOR LOW NOVELTY-SEEKING NEEDS

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FIGURE 4-15: PATH MODEL FOR HIGH NOVELTY-SEEKING NEEDS

The chi-square difference test (∆χ²) (Vandenberg and Lance 2000) revealed that the

unconstrained and constrained models were not significantly different (p=0.16) and the

equality constraint is reasonable; therefore, high and low novelty-seeking needs groups do

not differ from each other.

TABLE 4-26: NESTED MODEL COMPARISONS AND GOODNESS OF FIT INDICES - NOVELTY-SEEKING NEEDS





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TABLE 4-27: NOVELTY-SEEKING NEEDS Low needs High needs Critical ratios a

BIL BRAND_ENG 0.73 0.69 -1.36

BRAND_ENG PRAG_EXP -0.30 -0.25 0.38

EVENT_ENG SENS_EXP 0.37 0.27 -0.38

EVENT_ENG PRAG_EXP 0.29 0.31 0.04

EVENT_ENG REL_EXP 0.18 0.40 2.02

BRAND_ENGEVENT_ENG 0.80 0.90 1.46

BRAND_ENG COG_EXP 0.22 0.16 -0.45 a Critical Ratios for Differences between Parameters (Unconstrained) * Significance (>1.96)

This finding of invariance was further confirmed from the individual hypothesised

relationships outlined in Table 4-27; no significant path differences were present for high

novelty-seeking needs versus low novelty-seeking needs groups. The discussion of

hypotheses section describes this outcome in greater detail.

In summary, there was little evidence to suggest that the individual’s experiential needs

moderated the relationship between BME experiential components and customer event

engagement. Significant difference was found for need for cognition; however, the

moderation only impacted two relationships. The next section provides a discussion of

hypotheses.

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H# Hypothesis Supported/ Not Supported

5a An individual’s need for cognition from an experience will moderate the relationship between the BME experience and customer event engagement Partially Supported

5b An individual’s need for affect from an experience will moderate the relationship between the BME experience and customer event engagement Not Supported

5c An individual’s novelty-seeking needs from an experience will moderate the relationship between the BME experience and customer event engagement Not Supported

An exploratory approach was taken to investigate the moderation effect of experiential

needs in the relationship between BME experiences and customer event engagement. The

current literature does not offer insight into the effect of individual needs in the

hypothesised relationships, and so an overall moderation effect was explored. Multi-group

analysis was employed to test for moderating effects between high and low experiential

needs groups based on need for cognition, need for affect and novelty-seeking needs. The

overall moderation of the model (chi-square difference test) and the identification of

individual relationships were assessed.

H5a: An individual’s need for cognition from an experience will moderate the


Partial supported was found for a moderating effect of the individual’s need for cognition

on the relationships between BME experiences and customer event engagement. While the

chi-square difference test indicated model variance, only two paths were significantly

impacted by need for cognition. Therefore, H5a was partially supported.

Sensorial experience had a stronger impact on event engagement for individuals with low

need for cognition, indicating that individuals with a desire to be informed did not engage

strongly with events providing sensory stimulation (Wilson 1997). Sensorial experience

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did not fulfil the need for information and knowledge sought from the individual, and

therefore event engagement was not achieved (Gentile et al. 2007).

Relational experience had a stronger impact on event engagement for individuals with high

need for cognition, indicating that individuals found relevance and fulfilment of cognitive

needs from experiences with a focus on social interaction (Calder et al. 2009). Relational

experience could involve discussions with the winemaker or other knowledgeable

individuals (Charters and Ali-Knight 2000), and these interactions could provide insight or

knowledge and therefore fulfil the individual’s need for information.

H5b: An individual’s need for affect from an experience will moderate the


H5c: An individual’s novelty-seeking needs from an experience will moderate the


Results from the multi-group analysis did not reveal a significant moderating effect of the

individual’s need for affect nor novelty-seeking needs in the relationships between BME

experiences and customer event engagement. Therefore, H5b and H5c were not supported.

While the results may accurately reflect that no moderation effect exists for need for affect

or novelty-seeking needs, these findings could also indicate a limitation of the study. The

influence of the individual’s experiential needs could occur during their decision making

process of whether to attend the event. Therefore, individuals attending BMEs are more

likely to already find interest in the activity. Further discussion of this finding is reported in

Chapter 5.

The effects of experiential needs could have occurred during the individual’s decision

making process of whether to attend the event, therefore limiting the attendees (and survey

respondents) to those who already anticipated a fulfilment of their needs through 187 | P a g e

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attendance of that particular event. According to optimum stimulation level (OSL) theory,

individuals seek out stimulation from particular environments in order to achieve

satisfaction; individuals engage in exploratory behaviour to achieve their ideal level of

stimulation (Steenkamp and Baumgartner 1992). Therefore, individuals in attendance of an

event would have sought that particular experience as they believed it would fulfil their

experiential needs and achieve their desired level of stimulation. This explanation provides

support for the impact of experiential needs, albeit not captured within the parameters of

this thesis. This limitation also provides an avenue for future research, and is discussed in

Chapter 5.

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The results of the quantitative research for this thesis were detailed in this chapter, and

were outlined in three sections. First, reliability and validity testing was run to investigate

the robustness of a social dimension of engagement (Hypotheses 1a and 1b). It was

concluded that the social brand engagement was a unique and independent dimension

within the customer brand engagement model, and was therefore included for the

remaining analysis. Social event engagement was also implemented throughout the

analysis, despite some weaknesses observed in the customer event engagement structural

model.

In section two, path model analysis was conducted which captured the hypothesised

relationships of interest in this thesis. The impact of BME experiential components on

customer engagement with the event and the brand (Hypotheses 2a-j), the existence of

engagement transfer reflected in the relationship between customer event engagement and

customer brand engagement (Hypothesis 3), and the behavioural intention of loyalty

toward the brand resulting from customer engagement with the brand (Hypotheses 4a and

4b) were all investigated.

The justification for the calculation of composite variables was made, and the process of

path model analysis was outlined. With the aim of achieving a higher level of parsimony,

the specified model was re-specified based on empirical and theoretical considerations.

The re-specified model achieved sound model fit, and goodness of fit indices and

individual paths were presented. The findings indicated support for BME experiences

leading to customer event engagement, with the exception of cognitive experience which

had a direct relationship with brand engagement. There was support for the existence of the

notion of engagement transfer. A significant relationship was found between event

engagement and brand engagement, BME experiences mainly led to event engagement and

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behavioural intention of loyalty. Therefore, because customer event engagement mediates

the relationship between event experience and customer brand engagement, it is argued

that the focus of the engagement transfers from the event to the brand.

Finally, a multi-group analysis was conducted to compare high and low experiential needs

groups based on need for cognition, need for affect and novelty-seeking needs. The results

indicated that generally a moderation effect was not present. Need for cognition was found

to have a partial moderation effect, with only two relationships impacted by moderation.

The following Chapter 5 is the discussion and conclusion of this thesis. The findings and

their implications for theory and practice are discussed, as well as managerial implications,

limitations and directions for future research.

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Discussion and Conclusion Chapter

CHAPTER 5: DISCUSSION AND CONCLUSION


The primary objective of this thesis was to explore the role of branded marketing event

(BME) experiences in the facilitation of customer engagement. It was proposed that the

sensorial, emotional, cognitive, pragmatic and relational components of a BME experience

would facilitate customer event engagement and customer brand engagement. Experiential

needs (need for cognition, need for affect and novelty-seeking needs) were posited to

moderate the extent to which BME experiences facilitate customer event engagement. It

was also proposed that the BME experience would directly and indirectly impact customer

brand engagement through customer event engagement. Finally, behavioural intention of

loyalty (BIL) was hypothesised as being the result of customer engagement. A conceptual

model was developed which drew from the literature on customer engagement, marketing

events and customer experience. This conceptual model was tested empirically and support

was found for the majority of the hypotheses, however some distinct and interesting

divergent results were also found. The analysis for five key research questions and

associated hypotheses were presented in Chapter 4.

This chapter identifies and summarises the main findings and conclusions of this thesis.

The theoretical contributions to academic knowledge arising from this thesis are

highlighted. The practical applications of these results are then outlined in a discussion of

the managerial implications. Finally, the chapter concludes with the limitations of the

research and directions for future research.

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5.2 Summary of Findings

5.2.1 The Role of Social Engagement

The findings in chapter 4 provide partial support for a social dimension within customer

event engagement (H1a), and support for a social dimension within customer brand

engagement (H1b). The inclusion of a social dimension of engagement as advocated in

Vivek et al. (2012) and Calder et al. (2009) is consistent with the results of this thesis.

Social brand engagement fits within the customer brand engagement measurement model,

holds as a distinct construct and not a subset of another engagement dimension, and

significantly contributes to the higher order construct of total customer brand engagement.

Social brand engagement has gained traction in recent customer engagement research, as

scholars are recognising the importance of an expanded view of customer engagement

(Kozinets 2014).

Social event engagement, however, is only partially supported as a dimension of customer

event engagement. The structural model for customer event engagement reveals a

covariance between social event engagement and event interaction constructs. Social and

interactive engagement have a strong connection as social engagement inherently contains

interactions with others (Calder et al. 2009; Kozinets 2014). Therefore, social event

engagement is an important inclusion of customer event engagement due to the high level

of customer-to-customer interactions during a BME (Wohlfeil and Whelan 2006).

Calder et al.’s (2009) conceptualisation of engagement identifies personal engagement and

social-interactive engagement elements (Calder et al. 2009). These elements comprise

various dimensions, for example social-interactive engagement includes ‘community’ and

‘participation and socialising’ dimensions (Calder et al. 2009). Although this

conceptualisation is not widely adopted in customer engagement literature to date, the

results from this thesis are consistent with Calder et al. (2009), and is an avenue for future

research.

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5.2.2 Experiential Components of A BME that Facilitate Customer Engagement

Customer experience and marketing event literature advocate the ability for various

experiences to contribute to either the event (Drengner et al. 2008; Pine and Gilmore 1998)

or the brand (Brakus et al. 2009; Whelan and Wohlfeil 2006); therefore, hypotheses were

developed to capture the impact that each experiential component had on both customer

event engagement and customer brand engagement. The findings indicate that sensorial,

pragmatic and relational components of experience contribute to customer event

engagement (H2e, H2g and H2i) but not directly to customer brand engagement (H2f, H2h

and H2j). In addition, the findings reveal that cognitive experiences do not have a

significant impact on customer event engagement (H2a), but rather have a strong direct

relationship with customer brand engagement (H2b).

The cognitive component of a BME experiences encompasses learning, cognitive

processing and experiences providing mental stimulation for the participant (Gentile et al.

2007). BMEs are a brand-initiated activity, and therefore it is expected that a cognitive

experience would relate directly to the brand (Pine and Gilmore 1998). A common

example of a cognitive BME experience is a wine education session. Within this

experience, attendees are provided information about the wine brand including the

different wine varietals on offer and appropriate wine and food pairing. Therefore, it is

plausible that a cognitive BME experience would not necessarily facilitate customer event

engagement; i.e. encouraging feelings of wanting to learn more about the event,

contributing to discussions and paying attention to information regarding the event, but

instead would facilitate customer brand engagement (Pine and Gilmore 1998). Attendees

of a cognitive BME experience gain a higher propensity to seek brand information, learn

more about the brand, and facilitate discussions regarding the brand, hence exhibiting

customer brand engagement (Hollebeek 2011b; Salanova et al. 2005; So et al. 2012).

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Findings indicate that the emotional component of experience does not facilitate

engagement with the event or the brand. This is an unexpected and important finding as the

emotional nature of event experience is a strong focus of marketing event literature

(Leischnig et al. 2011; Packer and Ballantyne 2004; Whelan and Wohlfeil 2006). While

emotional experiences create pleasant experiences or feelings of excitement, the intensity

or value from this experience is not enough to facilitate customer engagement with the

event or brand (Pine and Gilmore 1998). From a social exchange theory perspective, the

resources contributed by the brand are not perceived as enough value to warrant the

customer’s contribution of their engagement (Cropanzano and Mitchell 2005).

Results of this thesis show that the sensorial, pragmatic and relational experiential

components of BMEs facilitate customer event engagement. A sensorial experience

provides sensory meaning and stimulation for customers (Schmitt 1999), for example a

wine and food pairing event, resulting in the customer’s participation and heightened

interaction in event activities (Mollen and Wilson 2010). Focal to a sensory experience is

sensory stimulation (Gentile et al. 2007), which inherently requires customer interaction

with the activity; for example tasting the wine and food and identifying wine fragrances.

Wine has a strong connection with aesthetic consumption (Charters and Pettigrew 2005),

and therefore wine events with a sensorial focus were predicted heighten the customer’s

excitement and event enthusiasm through aesthetics (Schmitt 1999; So et al. 2012).

A pragmatic experience requiring physical behaviours or actions from the customer

(Gentile et al. 2007) is also expected to stimulate customer event engagement through the

active customer participation inherent in the experience (Mollen and Wilson 2010). A

wine-blending event requires the customer to participate in the wine production process;

their engagement is apparent from their considerable interaction effort elicited toward the

activity (Hollebeek 2011b), and their heightened level of attention given to the activity

(Pine and Gilmore 1998).

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A relational experience, for example wine dinner events or meeting the winemaker, is

designed to be experienced with other people (Gentile et al. 2007). Relational experiences

therefore appeal to customers through social event engagement and event enthusiasm

(Kozinets 2014; Vivek et al. 2012), and facilitate customer event engagement.

5.2.3 Engagement Transfer from Event to Brand

This thesis supports the existence of a mediated relationship between BME experiences

and customer brand engagement through customer event engagement (H3). The findings

are consistent with associative network theory in that event related information is projected

onto the brand (Smith 2004). The findings demonstrate that the engagement experienced

with reference to the event is also replicated onto the brand, suggesting that event

engagement transferred to brand engagement.

The results of this thesis suggest that overall customer event engagement has a strong

mediating effect, with BME experiences facilitating customer brand engagement

predominantly through customer event engagement. The impact of sensorial, pragmatic

and relational experiential components on customer brand engagement is fully mediated

through customer event engagement, while cognitive experience has a direct relationship

with customer brand engagement (H2b). The researcher considers this a process of

‘engagement transfer’, where the psychological state facilitated towards the event has a

flow on effect and facilitates engagement with the host brand.

Finally, the notion of engagement transfer is further relevant, because although customer

brand engagement has a significant relationship with BIL (H4b), there is not a significant

direct relationship between customer event engagement and BIL (H4b). Therefore, for BIL

to occur, the BME must facilitate customer brand engagement. BME experiences have a

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strong mediating effect on customer brand engagement only through customer event

engagement, highlighting the importance of engagement transfer in this process.

5.2.4 The Impact of Customer Engagement on Behavioural Intention of Loyalty

There are mixed views and a lack of clarity in the marketing event and engagement

literature regarding whether BIL results directly from customer event engagement

(Crowther 2010; Drengner et al. 2008; Leischnig et al. 2011), or customer brand

engagement (Bowden 2009; Hollebeek 2011a). Customer engagement literature

predominantly focuses on the brand as the focal object of the engagement, leading to

brand-related outcomes (e.g. Gambetti et al. 2012; Hollebeek et al. 2014; So et al. 2012;

Wirtz, Den Ambtman, Bloemer, Horváth, Ramaseshan, Van De Klundert, Canli, and

Kandampully 2013). However, these studies are not conducted in the context of BMEs and

do not investigate the interplay between two engagement objects. An expanded view of

associative network theory provides insight into the relationships between two engagement

objects, and their brand-related outcomes (Smith 2004). Associative network theory

suggests that a direct relationship exists between the brand-related associations and BIL

outcomes (Smith 2004). This means that the associations the customer has with the event

are not the direct cause of BIL; these associations must replicate onto the brand, and it is

the brand associations originating from the event experience that have an effect on BIL

(Smith 2004). Marketing event research that takes a brand image transfer perspective also

advocates that brand-related outcomes are a direct result of brand attitudes, not event

attitudes (Martensen et al. 2007). Through brand image transfer (Gwinner and Eaton 1999)

the event attitudes are transferred onto the brand. These brand attitudes are the drivers of

brand-related outcomes (Martensen et al. 2007).

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5.2.5 How the Individual’s Experiential Needs Moderate Event Engagement

Findings of the multi-group analysis reveal that only need for cognition (H5a) has a

significant moderating influence between BME experience and customer event

engagement. Individuals with high need for cognition find relational experiences more

impactful in facilitating customer event engagement; this moderation effect is justified

because the opportunity to discuss and share information with likeminded others can fulfil

the individual’s need for cognition (Calder et al. 2009; Steenkamp and Baumgartner 1992).

The individual’s knowledge is reinforced or highlighted through their sharing of wine

knowledge with others. Relational experiences provide these individuals with a platform

for showcasing their knowledge to others, sharing opinions and ideas about wine, and

learning more about wine from other knowledgeable individuals, hence encouraging

customer event engagement.

Individuals with high need for cognition are less likely to facilitate event engagement

during sensorial BME experiences; sensorial experiences provide sensory stimulation,

which does not fulfil the individual’s desire to be informed or gain information and

knowledge on an area of interest (Gentile et al. 2007; Wilson 1997). While an individual

with high need for cognition would still find pleasure in a wine-related sensorial

experience as it is consistent with their wine lifestyle (Charters and Ali-Knight 2000), their

level of engagement is likely to be weaker than if they had experienced an event that

satisfied their need for learning and general curiosity (Calder et al. 2009).

These moderation effects are consistent with optimum stimulation level (OSL) theory

which has been used to explain exploratory consumer behaviour (Steenkamp and

Baumgartner 1992). OSL theory states that customers actively seek out environments that

provide their desired level of stimulation; the level of stimulation and type of stimulation is

derived from the customer’s inherent needs (Steenkamp and Baumgartner 1992). The

individual’s needs influence the perceived relevance of event experience and can result in

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heightened engagement when the experience fulfils their needs (MacInnis and Jaworski

1989).

The impact of cognitive and pragmatic BME experiences on event engagement does not

significantly differ for individuals with high need for cognition versus those with low need

for cognition. It was suggested in Chapter 4 that limitations of the research may have

impacted these findings, and are discussed in the limitations of the research section. There

is little evidence to suggest that the individual’s need for affect (H5b) or novelty-seeking

needs (H5c) moderate any of the relationships between BME experiences and customer

event engagement.

5.2.6 Updated Study Framework

The findings from Chapter 4 led to an updated study framework as outlined in Figure 5-1.

A number of modifications have been included in the study framework, highlighting key

findings of this thesis.

First, the updated framework captures the sensorial, relational and pragmatic BME

experiential components leading to customer event engagement (H2e, H2g and H2i), and

cognitive experience leading directly to customer brand engagement (H2b). Emotional

experience has been removed from the framework entirely. This indicates that experiential

components may have a different impact on customer engagement and subsequent BIL

depending on the focal object of engagement. Sensorial, relational and pragmatic BME

experiences require customer engagement with the event as the focal object; customer

event engagement will then replicate onto the brand and contribute to BIL. Conversely,

cognitive BME experiences require direct customer engagement with the brand in order to

lead to BIL outcomes. This particular finding has important managerial implications,

suggesting that a BME with a strong cognitive focus will have strong direct brand

implications in terms of facilitating engagement and BIL outcomes.

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The updated study framework also captures the process of engagement transfer from

customer event engagement to customer brand engagement (H3), and the outcome of BIL

resulting from customer brand engagement (H4b). While conceptual arguments could be

established from the literature (Section 2.4.3.1, Chapter 2) for customer event engagement

and customer brand engagement to both directly impact BIL, the results of this thesis

favour the notion of engagement transfer. The relationship between customer event

engagement and BIL was fully mediated through customer brand engagement; a significant

direct relationship was not found.

FIGURE 5-1: UPDATED STUDY FRAMEWORK

5.3 Contributions to the Academic Discipline

The main contribution of this thesis is the establishment of an empirical relationship

between BME experiences, customer event engagement and customer brand engagement.

An association between BMEs and customer engagement is discussed in previous literature

with little empirical support (Calder et al. 2009; Vivek et al. 2012). This thesis

demonstrates that the sensorial, pragmatic and relational components of BME experiences

facilitate customer event engagement, and that cognitive experiences facilitate customer

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brand engagement. The sensorial, pragmatic and relational components of a BME

experience indirectly facilitate customer brand engagement, fully mediated through

customer event engagement. This establishes an empirical association between BME

experiences and customer engagement on both an event and brand level, which is

supported by social exchange theory (Cropanzano and Mitchell 2005).

This thesis provides quantitative evidence to contribute to the empirical justification of

customer engagement operationalisation and its brand-related outcomes, namely BIL. This

thesis undertook empirical quantitative enquiry on the customer engagement construct, as

the nature of customer engagement research is still heavily conceptual (discussed in Table

2-1, Chapter 2) (Brodie et al. 2011b). This thesis implements the measures of engagement

provided by So et al. (2012), and extends the construct with the inclusion of a social

engagement dimension. Support is found for the operationalisation of the customer brand

engagement measurement model in the context of BMEs.

Establishing this connection between BME experiences and customer engagement

provides further support for the integration of the bodies of literature pertaining to

marketing events, customer experience and customer engagement, all grounded in S-D

logic. This thesis empirically examines BMEs as comprising various customer experience

components; sensorial, emotional, cognitive, pragmatic and relational (Gentile et al. 2007).

Various studies in customer experience have examined different experiential components;

however, they are often inconsistent with regards to the dimensionality of customer

experience (Brakus et al. 2009; Chang and Chieng 2006; Gentile et al. 2007; Sahin et al.

2011; Schmitt 1999; Tynan and McKechnie 2009; Yuan and Wu 2008). In addition, often

research focused on the customer’s experience with a product (Gentile et al. 2007) or

experiential product-centric brands (Brakus et al. 2009). Never before has this

conceptualisation of experiential components been used to investigate drivers of customer

engagement, and therefore is a central contribution of this thesis. The measures from

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Chang and Chieng (2006) were implemented in this thesis, and extend the applicability of

this scale to customer engagement and events literature.

Previous research in customer engagement has primarily focused on the brand as the focal

object of the engagement (e.g. Fehrer et al. 2013; Gambetti et al. 2012; Hollebeek et al.

2014; So et al. 2012; Wirtz et al. 2013). Although Vivek et al. (2012) classify various foci

of customer engagement and propose that customers engage with provider-initiated

activities (i.e. BMEs), customer event engagement has not been examined empirically.

This thesis was the first to examine customer engagement with two focal objects in one

study, and investigate the relationship between engagement objects (Brodie et al. 2011b).

Customer event engagement and customer brand engagement were both explored as

outcomes of a BME experience. The interplay between customer event engagement and

customer brand engagement was also explored.

The identification of engagement transfer from customer event engagement to customer

brand engagement provides support for associative network theory (Smith 2004) in

explaining how customer engagement is facilitated through BME experiences. This thesis

is the first to extend associative network theory in the area of customer engagement and

advocates the investigation of multiple engagement objects and their interplay in reaching

brand outcomes.

This thesis extends the knowledge of the relationship between customer engagement and

BIL; while BIL has been identified as an outcome of engagement (So et al. 2012), this

thesis is the first to explore BIL as an outcome of customer event engagement and

customer brand engagement. Confusion exists in the marketing event and customer

engagement literature regarding whether brand-related outcomes result from event

engagement or brand engagement (Bowden 2009; Crowther 2010; Drengner et al. 2008;

Hollebeek 2011a; Leischnig et al. 2011). This thesis provides clarity on this issue by

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engagement on BIL. The results suggest that customer event engagement does not have a

direct relationship with BIL, but instead contributes to customer brand engagement.

Customer brand engagement has a direct and significant relationship with BIL.

This thesis provides empirical evidence to support the inclusion of a social dimension

within customer brand engagement, and partial support for social engagement as part of the

customer event engagement construct. There is considerable debate in customer

engagement literature regarding the presence and role of a social element of engagement

(Calder et al. 2009; Gambetti et al. 2012; Sawhney et al. 2005; Vivek et al. 2012). This

finding of this thesis are consistent with social exchange theory (Abdul-Ghani et al. 2011)

and demonstrates that customers can achieve a heightened psychological state of social

connection and human contact with reference to the brand (and similarly, the event).

The antecedent of BME experiences contributing to customer engagement, and outcomes

of customer engagement were also empirically investigated. Therefore, the nomological

network of customer engagement was further identified (Brodie et al. 2011a). Further

support was found for customer brand engagement leading to BIL (So et al. 2012). This

thesis further contributed to the understanding of outcomes of customer engagement as it

investigates the impact of both customer event engagement and customer brand

engagement on BIL.

The conceptualisation and outcomes of customer engagement have been the central focus

of customer engagement literature to date (Brodie et al. 2011b). This thesis is the first

study to examine the antecedent of BME experiences contributing to customer

engagement, and the role of moderating variables impacting this relationship.

The findings from this thesis have broader application to related disciplines given the

multidisciplinary nature of engagement including sociology, political science, psychology,

educational psychology, and organisational behaviour (Brodie et al. 2011a). Student

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of how experiences facilitate engagement, the relationship between multiple engagement

objects, and further insights provided in this thesis. In addition, the insights on event

experience would have great value in retail, service and tourism industries, where special

events and memorable consumer experiences play a key role in differentiation.

5.4 Managerial Implications

As the respondents of this thesis were drawn from attendees of South Australian winery-

hosted events, the results will have use for managers in similar settings. While implications

can be drawn for managers in different environmental settings, further investigation should

occur before the results are generalised.

For managers and event organisers, a notable finding to emerge from this thesis is the

importance of structuring BMEs to facilitate customer engagement for the event and the

brand. The findings show that relational, pragmatic and sensorial experiences have a direct

relationship with event engagement, while cognitive experience has a direct relationship

with brand engagement. This means that practitioners should consider designing BMEs

with a cognitive focus to engage customers with the brand specifically. Wine education

seminars with a direct focus on the wine brand (rather than a ‘generic’ wine education

session) will have a direct impact on customer brand engagement, and result in BIL.

However, managers and event organisers are advised that if a cognitive experience is

implemented, emphasis on the brand is pivotal. Cognitive experience does not contribute to

customer event engagement, and therefore the event must contain brand-related

information and stimulate customer interest to acquire brand-related knowledge in order to

achieve customer brand engagement.

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Alternatively, practitioners can implement events focusing on relational, pragmatic and/or

sensorial experiences, and these BMEs should focus on the event experience as the focal

engagement object, not the brand. Meet the wine maker events (relational), wine-blending

sessions (pragmatic) or wine and food pairing (sensorial) should be designed to allow

attendees to interact, become excited and feel socially or emotionally connected with the

event experience. As customer event engagement has a strong relationship with customer

brand engagement, it is inferred that these experiential components also have an indirect

impact on BIL. Therefore, the relational, pragmatic and sensorial experiences should aim

to facilitate engagement with the event specifically, because through engagement transfer,

this event engagement will also impact brand engagement and subsequent behavioural

intention of loyalty.

All event experiences should have some reference or focus on the brand, as it is brand

engagement that leads to behavioural intention of loyalty toward the brand. The fact that

only customer brand engagement and not customer event engagement leads to BIL

reiterates the need for managers to have a branded marketing event mindset. It is through

engagement transfer from event to brand that brand-related outcomes occur; therefore, the

brand must have central focus when planning events.

In addition, as experiential needs do not have a major impact on the types of experiences

leading to customer event engagement, managers are advised to plan BMEs that include a

combination of sensorial, pragmatic and relational experiences as customers generally

exhibit customer event engagement as a result.

Emotional experience was the only experiential component that did not have a significant

relationship with customer engagement. This finding is particularly relevant for managers,

as many marketing event studies emphasise the emotional elements of the experience as

having an impact on brand outcomes (Leischnig et al. 2011). While emotional experiences

create pleasant experiences or feelings of excitement, the intensity or value from this

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experience is not enough to facilitate customer engagement with the event or brand (Pine

and Gilmore 1998). Creating an emotional experience is a common strategy for many

event organisers, and is particularly emphasised in the wine industry, as wine lifestyle is

often associated with leisure, hedonism and aesthetic consumption (Charters and Pettigrew

2005; O'Neill and Charters 2000). It is recommended that marketing managers should not

invest on predominantly emotional experiences as they are not found to have a significant

relationship with customer engagement. If an emotional experience approach is taken by

the brand, it is recommended that this style of experience is implemented in combination

with other experiential components (e.g. cognitive, pragmatic, sensorial, and/or relational),

as these BME components have a significant impact on customer engagement. This finding

is based on respondents from a range of wine-events, and therefore has generalisability

within the wine industry. However, replication of the study is required to determine

whether this finding applies to different contexts or products/services.

5.5 Limitations of the Research

This section addresses some of the limitations of this thesis. From these limitations,

opportunities for further research are identified and examined.

The results of this thesis do not examine the change in BIL as an outcome of the BME

experience, but rather establish associations between the two constructs. A pre- and post-

event survey would have provided more insight into the level of BIL felt by the customer

before experiencing the BME as well as after. In addition, a longitudinal research design

would have provided a more comprehensive view of the development of customer

engagement pre- and post-event, and captured the impact of multiple moments of

engagement over time (Brodie et al. 2011a). It has been suggested that customer

engagement is cyclical, and that reciprocal effects between antecedents and outcomes

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could be present (Fehrer et al. 2013; Hollebeek et al. 2014). However, this was not

captured in this thesis.

In addition, it is recognised that the individual’s experiential needs could impact their

decision to attend a BME, which could explain the limited impact experiential needs had

on the relationship between BME experiences and customer event engagement. It is

probable that those who attended (and who participate in the survey) were limited to

attendees who already found interest in the activity. This provides an explanation for

experiential needs not demonstrating a moderating effect through multi-group analysis.

The individual’s experiential needs would have impacted their decision to attend the event,

and therefore the respondents captured in this thesis study would more generally find value

or fulfilment of their needs with the event they have chosen to attend.

A number of method limitations are present in this thesis. First, there is a lack of

consistency between the pre-tested items and those used in the main study. Upon further

reflection and exploration of the customer engagement literature, the researcher decided

that So et al.’s (2012) expanded five dimension view of customer engagement had great

applicability to the event context, and allowed the investigation of the dimensionality of

customer engagement. The researcher also decided that for completeness of replication of

So et al.’s (2012) dimensions of engagement, the participation measures would be replaced

with So et al.’s (2012) interaction measures. The researcher recognised these oversights

after the pre-test, however decided that the insights gained from changing a number of the

items in the main study would outweigh the limitations of having a consistent survey in the

pre-test and main study. Second, a relatively small sample size and participation of a small

number of South Australian wineries meant that event type or brand bias could not be

examined individually. A larger scale study with a greater diversity of events and larger

response rates for each individual event is required in order to control for any biases that

may influence the results.

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It was acknowledged in Chapter 2 that specific experiential components may contribute to

individual customer engagement dimensions (e.g. attention, absorption, immersion) as

opposed to customer engagement in a general sense. Instead, customer engagement

outcomes were considered from an overall perspective with support from customer

engagement literature that each engagement dimension should contribute to and enhance

the others, and result in a general level of customer engagement (Brodie et al. 2011a). This

is a limitation of this thesis, as the relationships between BME experiential components

were not investigated with reference to each customer engagement dimension, and

therefore do not provide a complete understanding of how customer engagement is

facilitated.

Furthermore, this thesis considers the impact of each experiential on customer event

engagement and customer brand engagement; however, it is also acknowledged that an

event can include multiple or all experiential components, and this was not accounted for

in the analysis. ‘Complex’ experiences, containing multiple experiential components, could

facilitate a different level of customer engagement than experiences reflecting a single

experiential component (Gentile et al. 2007; Pine and Gilmore 1998); however, it was not

explored in this thesis.

5.6 Directions for Future Research

This section highlights areas for future research. The discussion focuses on opportunities

that emerge from the limitations of this thesis and future research directions identified from

Chapter 2 and 3.

In examining the role of social engagement within customer event engagement and

customer brand engagement, this thesis took the perspective that social engagement would

have equal applicability for both engagement objects. However, there is evidence in this

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thesis to suggest that social engagement has a different effect within customer event

engagement versus customer brand engagement. In particular, the social event engagement

and event interaction elements had a strong connection that indicated they may be distinct

from the other customer engagement dimensions. In the BME context, which is inherently

social, respondents may find less disparity between a heightened state encompassing the

participation in activities (interaction) and a heightened state of connectedness with others

as part of their engagement (social). Future research should further investigate different

perspectives on the dimensionality of engagement; two dimensions of engagement (Calder

et al. 2009), three dimensions of engagement (Brodie et al. 2011a) or five dimensions of

engagement (So et al. 2012).

As identified in the limitations of the research, a single survey implemented shortly after a

BME has limited ability to capture drivers to attend the BME, identify pre-event customer

brand engagement or BIL, or examine the extended effects of customer brand engagement

after the event. Different research/survey methods could provide a more comprehensive

view of the impact of customer engagement. Two such examples include pre- and post-

event surveys and longitudinal research. A longitudinal approach could explore the

endurance of customer engagement over time. Previous research has recognised the

potential for customer engagement to have enduring qualities, as well as the ability over

time to exhibit varying levels of engagement intensity (Brodie et al. 2011b). However,

little research to date has explored in detail the customer engagement construct over time.

Future research featuring a longitudinal design should investigate the enduring brand-

related outcomes sustained from a BME experience.

In addition, future research could implement an experimental design to more exhaustively

capture varying experiential needs and test the moderating impact on customer engagement

when these individuals are exposed to experiences that do not satisfy their experiential

needs. Similar manipulations could explore a more exhaustive combination of single or

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multiple experiential components to further investigate their impact on customer event

engagement and customer brand engagement.

Qualitative research approaches implemented instead of, or in addition to, a quantitative

research approach provide a different direction for future research. In situ approaches such

as a diary study would provide insight into the unique, personal and momentary

experiences of BME attendees. Interviews or focus groups could further investigate the

impact of various experiential components, the perceived level of customer event

engagement and customer brand engagement facilitated, as well as exploring the

experiential needs of the individual that may drive attendance to a BME. A qualitative

approach provides the researcher with the opportunity to discover additional factors

impacting an individual’s BME experience that may have otherwise gone unnoticed or not

captured in a survey. For example, an attendee may feel a sense of engagement with an

additional object other than the event or the brand (perhaps with the service staff, the wine

region, or the band/musician playing during the BME).

Another avenue for future research is further exploration of the different elements of

customer engagement to identify their individual impact on BIL and similar brand-related

outcomes. The concept of engagement intensity, and the ability for individual engagement

dimension to contribute to overall engagement intensity is acknowledged (Brodie et al.

2011b) but not investigated. The interplay between engagement dimensions has the ability

to generate various levels of engagement intensity, and single engagement dimensions may

have the ability to influence the other engagement dimensions (Brodie et al. 2011b). For

example, emotional engagement may facilitate enhanced levels of cognitive and/or

behavioural engagement (Brodie et al. 2011b). In addition, future research could integrate

BME experiential components within this investigation to determine which components of

experience lead to which dimensions of customer engagement and subsequently result in

BIL or related brand-outcomes. The individual’s experience and perception of experiential

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components are unique, and so the same event may be perceived as including different

components of experience and facilitating different dimensions of engagement. An added

complexity to this process is the ability of events to comprise a number of different

experience components, and thus encourage a variety of event engagement dimensions to

unfold.

Finally, future research needs to extend into different contexts in which customer

engagement may occur. This thesis focused on the wine industry; an offline and hedonic

context. Similar studies should investigate utilitarian contexts, different industries and

various products/services to demonstrate applicability and generalisability of the customer

engagement construct. For example, trade-show and industry events are a common form of

business-to-business interactions (Herbig, O'Hara, and Palumbo 1994); however,

engagement is not well understood outside of the typical customer-brand or customer-

customer interactions.

5.7 Concluding Thoughts

As a result of this thesis there is further knowledge of how brands can strategically

facilitate customer engagement. Greater insight into the nature of customer engagement,

namely its dimensions (social engagement), antecedents (BME experience) and moderators

(experiential needs) has been achieved.

Incorporating the research areas of customer engagement, marketing events and customer

experience, consistent in their applicability to S-D logic (Vargo and Lusch 2014), has

allowed a more strategic investigation of customer engagement. The findings from this

thesis have provided a framework for understanding the experiential components of BMEs

(Gentile et al. 2007) and their impact on customer event engagement, customer brand

engagement and BIL (So et al. 2012). This thesis provides support for social exchange

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theory (Cropanzano and Mitchell 2005; Saks 2006) as a predictor of the resources

contributed in the form of BME experiences from the brand and customer engagement

contributed by the individual in explaining the reciprocal interactions leading to mutual

outcomes for the customer and the brand.

The process of engagement transfer is a central contribution of this thesis, justifying how a

BME, an activity extending beyond the normal customer-brand interactions (Vivek et al.

2012), has the capacity to lead to BIL for the host brand. Engagement facilitated with the

event, which facilitates engagement with the brand, demonstrates that BMEs are a unique

brand-building activity founded in associative network theory (Smith 2004).

While customer engagement literature has for a short time reached an understanding of

customer engagement conceptualisation, this thesis extends these ideas through

quantitative empirical enquiry and explores under-researched antecedents, outcomes and

moderators of the customer engagement process. The development of effective BME

experiences requires a thorough investigation of customer experiences, and the individual’s

experiential needs that influence their ability or willingness to engage with the event.

Continual development regarding the dimensions, platforms and antecedents that facilitate

customer engagement is essential for the development of customer engagement research as

a prominent and impactful research area of marketing, and ensuring its broad applicability

and managerial benefits.

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APPENDICES

APPENDIX A-1: QUESTIONNAIRE

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APPENDIX A-2: ETHICS APPROVAL

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APPENDIX A-3: ADDITITONAL ANALYSIS FROM PRE-TEST

GOODNESS OF FIT INDICES FOR ALL ITEMS – PRE- TEST Construct χ² df χ²/df GFI NFI CFI RMSEA Cognitive experience 3.31 1 3.31 0.99 0.99 0.99 0.10 Emotional experience 11.80 6 1.97 0.98 0.97 0.99 0.07 Sensorial experience 1.62 1 1.62 0.99 0.99 0.99 0.05 Pragmatic experience 0.68 1 0.68 0.99 0.99 1.00 0.00 Relational experience 6.31 7 0.90 0.99 0.99 1.00 0.00 Cognitive event engagement 2.71 2 1.35 0.99 0.99 0.99 0.04 Emotional event engagement 1.15 1 1.15 0.99 0.99 1.00 0.03 Event participation 6.85 3 2.28 0.99 0.99 0.99 0.08 Social event engagement 11.46 11 1.04 0.99 0.99 0.99 0.01 Cognitive brand engagement 0.85 1 0.85 0.99 0.99 1.00 0.00 Emotional brand engagement 1.64 1 1.64 0.99 0.99 0.99 0.05 Brand participation 3.83 3 1.28 0.99 0.99 0.99 0.04 Social brand engagement 15.37 11 1.40 0.98 0.98 0.99 0.04 Need for cognition 34.53 24 1.44 0.97 0.96 0.99 0.04 Need for affect 9.74 6 1.62 0.99 0.99 0.99 0.05 Novelty-seeking 1.04 1 1.04 0.99 0.99 1.00 0.01 Word of mouth 0.74 1 0.74 0.99 0.99 1.00 0.00

SUMMARY OF ITEM CHANGES IN PRE-TEST VERSUS MAIN STUDY Pre-test Main Study Cognitive Experience Chang and Chieng (2006)

This event tried to intrigue me This event tried to intrigue me This event tried to stimulate my curiosity This event tried to stimulate my curiosity This event appealed to my creative thinking This event appealed to my creative thinking

Brakus et al. (2009)

I engaged in a lot of thinking when I attended this event

-

This event did not make me think - This event stimulated my curiosity and problem solving

-

Reliability: The 3 Chang and Chieng (2006) items received a Cronbach’s alpha of 0.81. When the 3 Brakus et al. (2009) items were added to the reliability test, Cronbach’s alpha was 0.82. Therefore, Chang and Chieng’s (2006) items were used in the main study to achieve parsimony. Sensorial Experience Chang and Chieng (2006)

This event was focused on creating a sensory experience

This event was focused on creating a sensory experience

This event did not try to engage my senses - This event tried to excite my senses This event tried to excite my senses This event provided sensory enjoyment This event provided sensory enjoyment

Brakus et al. (2009)

This event made a strong impression on my visual sense or other senses

-

I found this event interesting in a sensory way

-

This event did not appeal to my senses - Reliability: The 4 Chang and Chieng (2006) items received a Cronbach’s alpha of 0.85. Strong reliability was already achieved with the 4 Chang and Chieng (2006) items, therefore there was little benefit in including the Brakus et al. (2009) items. The 4 Chang and Chieng (2006) items were then assessed through a one-factor congeneric measurement model; poor inter-item correlation was found for item 2, and the model achieved fit when this item was removed. Therefore the main study included items 1, 3, and 4 from Chang and Chieng (2006).

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Relational Experience Chang and Chieng (2006)

This event offered me a sense of group belonging

-

I could relate to other people through this event

-

Sweeney and Soutar (2001)

Attending this event helped me to feel accepted

Attending this event helped me to feel accepted

Attending this event improved the way I am perceived

Attending this event improved the way I am perceived

Attending this event made a good impression on other people

Attending this event made a good impression on other people

Attending this event gave me social approval

Attending this event gave me social approval

Attending this event created a favourable perception of me among other people

Attending this event created a favourable perception of me among other people

This event had a positive social image This event had a positive social image Reliability: The 6 Sweeney and Soutar (2001) items received a Cronbach’s alpha of 0.91, while the Chang and Chieng (2006) items received a Cronbach’s alpha of 0.79. In the interest of parsimony only the 6 Sweeney and Soutar (2001) items were used in the main study. Pragmatic Experience – no changes from pre-test to main study Emotional Experience – no changes from pre-test to main study PARTICIPATION MEASURES USED IN PRE-TEST Chan, Yim, and Lam (2010)

I spent a lot of time sharing information about my needs and opinions with organisers during this event I put a lot of effort into expressing my personal needs to organisers during this event I provided suggestions to organisers for improving the event I had a high level of participation in this event I was very much involved in deciding how this event should be provided

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