Concert Attendee Behaviour: The Influence of Motivations ...

Concert Attendee Behaviour: The Influence of Motivations, Fan

Identification and Product Involvement

By

ALICIA KULCZYNSKI

B.A. (Communications), B.Sc. (Forensics), University of Newcastle, Australia

A thesis submitted in fulfilment of the requirements for the degree of Doctor of Philosophy

Newcastle Business School

Faculty of Business and Law

UNIVERSITY OF NEWCASTLE

April 2014

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STATEMENT OF AUTHORSHIP

This thesis contains no material that has been accepted for the award of any other degree or diploma in any university or other institution. To the best of my knowledge, the thesis contains no material previously published or written by another person, except where due reference has been made in the text. Selected findings from the thesis have been presented at conferences and published in referred proceedings and journals.1I give consent to the final version of my thesis being made available worldwide when deposited in the University’s Digital Repository, subject to the provisions of the Copyright Act 1968.

Signed: ………………………………………………………….. Date: …………………………………

1 The following article and presentations have been based on the research reported in this thesis.

Refereed Journal Article

[1] Perkins A. (2012), 'How devoted are you? An examination of online music fan behaviour', Annals of Leisure Research, 15(4), pp. 354-365.

Refereed Conference Papers

[1] Perkins A. (2012), ‘Exploring motivations for popular music concert attendance’, Proceedings of the Australian and New Zealand Marketing Academy Conference – Sharing the Cup of Knowledge', 3-5 Dec, Canterbury, NZ.

[2] Perkins A. (2010), ’Identification in popular music: A netnographic exploration of online fan communities’, Proceedings of the Australian and New Zealand Marketing Academy Conference - 'Doing More with Less', 29 Nov - 1 Dec, Adelaide, Australia.

Best Paper Award

[1] Identification in popular music: A netnographic exploration of online fan communities Tourism, Sports, Arts and Heritage Marketing track ANZMAC 2010, University of Canterbury, Christchurch, New Zealand

Note: ‘Perkins’ is Alicia Kulczynski’s maiden name (Married 30th November 2013)

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ACKNOWLEDGEMENTS On the accomplishment of this thesis I would like acknowledge my appreciation to

those that have helped me throughout the research process.

I am forever indebted to my closest friend Dr Stacey Baxter, for her guidance as a co-

supervisor, and also her continued support as a friend. It is only a true friend, who

can have the patience to be a sounding board both during, and out of work hours,

for four, long, uninterrupted years. And although she probably won’t read this (those

who know Stacey will know why), I could not have done this without her.

Special thanks go to my supervisor, Professor Alison Dean for her invaluable advice

and editing expertise. I will always be grateful for what I have learned from Alison

and the guidance and support she has provided for building the early stages of my

academic career.

I need to thank my husband, Michal Kulczynski, for still wanting to marry me at the

end of last year, after enduring many a day of waiting on me, as I hollered for

sustenance from behind my computer. He has provided nothing but love, patience

and endless support throughout this journey.

My thanks are extended to all those in the Newcastle Business School whom have

‘popped in to my office’ and offered me guidance and encouragement. I would also

like to thank my family and friends for their continued interest and reassurance, and

for not asking me too many times, when I was due to finish.

Finally, I would like to thank all others that have made this research possible. I owe

many thanks to those that have participated in the studies, and to the University of

Newcastle who provided funding for the project; without this financial assistance the

project would not have been possible.

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TABLE OF CONTENTS

STATEMENT OF AUTHORSHIP ....................................................................................... ii

ACKNOWLEDGEMENTS ................................................................................................. iii

TABLE OF CONTENTS ..................................................................................................... iv

LIST OF TABLES ............................................................................................................ viii

LIST OF FIGURES ............................................................................................................. x

LIST OF APPENDICES ..................................................................................................... xi

ABSTRACT ...................................................................................................................... xii

CHAPTER1 ......................................................................................................................... 1

Introduction...................................................................................................................... 1

1.1 Background ................................................................................................................... 2

1.2 Popular Music and Concert Attendance ...................................................................... 5

1.3 Social Identity ............................................................................................................... 6

1.3.1 Fan Identification ........................................................................................... 7

1.3.2 Fan Identification in Music ............................................................................ 8

1.4 Product Involvement .................................................................................................... 11

1.5 Motivations .................................................................................................................. 15

1.5.1 Motivations and Fan Identification .............................................................. 17

1.6 Research Questions ...................................................................................................... 17

1.7 Proposed Conceptual Framework ............................................................................... 19

1.8 Structure of thesis ....................................................................................................... 20

1.8.1 Overview of Studies ...................................................................................... 24

1.9 Significance of the Research ....................................................................................... 25

1.9.1 Theoretical Contribution ............................................................................. 25

1.9.2 Practical Contribution .................................................................................. 27

1.10 Chapter Conclusion .................................................................................................... 28

CHAPTER 2 ...................................................................................................................... 29

Study 1 - A Netnographic Analysis of Online Fan Behaviour ........................................ 29

2.1 Introduction ................................................................................................................ 29

2.2 Aim of Study 1 .............................................................................................................. 29

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2.3 Levels of Fan Identification ........................................................................................ 30

2.4 Research Design ........................................................................................................... 33

2.4.1 Rationale for using Netnography .................................................................. 33

2.5 Procedure ..................................................................................................................... 35

2.6 Results .......................................................................................................................... 37

2.6.1 Casual Fan ...................................................................................................... 37

2.6.2 Loyal Fan ....................................................................................................... 38

2.6.3 Diehard Fan .................................................................................................. 40

2.6.4 Dysfunctional Fan ......................................................................................... 41

2.7 Discussion ................................................................................................................... 42

2.8 Limitations .................................................................................................................. 44

2.9 Implications for Study 2 and Study 3 ......................................................................... 46

CHAPTER 3 ...................................................................................................................... 48

Study 2 - An Exploration of Consumer Motivations, Fan Identification and Product Involvement in Concerts ................................................................................................ 48

3.1 Introduction ................................................................................................................ 48

3.2 Aim of Study 2 ............................................................................................................. 48

3.3 Research Design ........................................................................................................... 51

3.3.1 Rationale for using Focus Groups ................................................................ 52

3.4 Method ......................................................................................................................... 53

3.5.1 Conducting the Focus Groups ..................................................................... 54

3.5.2 Analysis of Focus Group Transcripts ........................................................... 57

3.5 Results ......................................................................................................................... 58

3.6.1 Motivations for Popular Music Concert Attendance .................................. 58

3.6.2 Fan Identification ......................................................................................... 67

3.6.3 Product Involvement .................................................................................... 72

3.6.4 Potential Relationships between Product Involvement and Fan Identification ................................................................................................ 74

3.6.5 Summary of Motivations across Fan Identification and Product Involvement .................................................................................................. 77

3.6 Discussion .................................................................................................................... 81

3.7 Limitations .................................................................................................................. 84

3.8 Implications for Study 3 .............................................................................................. 85

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CHAPTER 4 ......................................................................................................................86

Study 3 - Testing Relationships between Fan Identification, Product Involvement and Motivations ..............................................................................................................86

4.1 Introduction ................................................................................................................ 86

4.2 Aim of Study 3 ............................................................................................................. 86

4.2.1 Development of Hypotheses ........................................................................ 87

4.2.2 Conceptual Model ........................................................................................ 93

4.3 Method ........................................................................................................................ 95

4.3.1 Sample .......................................................................................................... 96

4.3.2 Measures ....................................................................................................... 98

Product Involvement .................................................................................................. 98

Fan Identification ........................................................................................................ 101

Motivations (Mediator) ............................................................................................. 103

Dependent Variables .................................................................................................. 105

4.3.3 Data Preparation ......................................................................................... 106

4.3.4 Method of Analysis ...................................................................................... 107

4.4 Results ........................................................................................................................ 109

4.4.1 Product Involvement ................................................................................... 109

4.4.2 Fan Identification ......................................................................................... 131

4.4.3 Motivations .................................................................................................. 134

4.4.4 Structural Model ......................................................................................... 144

Concert Attendance ................................................................................................... 144

Amount willing to pay for tickets .............................................................................. 152

Willingness to Travel ................................................................................................. 157

4.4.5 Difference Tests ........................................................................................... 162

4.5 Results of Hypothesis Tests ....................................................................................... 162

4.6 Discussion of Results ................................................................................................. 164

4.6.1 Fan Identification ........................................................................................ 165

4.6.2 Product Involvement ................................................................................... 168

4.6.3 Motivations .................................................................................................. 172

4.6.4 Mediating Effects ......................................................................................... 174

4.6.5 Differences .................................................................................................... 181

4.7 Summary ..................................................................................................................... 181

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CHAPTER 5 .................................................................................................................... 184

Discussion & Conclusion .............................................................................................. 184

5.1 Introduction ............................................................................................................... 184

5.2 Concluding Remarks .................................................................................................. 185

5.2.1 Motivations for Popular Music Concert Attendance ................................. 186

5.2.2 Concert Attendance .................................................................................... 187

5.2.3 Amount Willing to Pay ................................................................................ 191

5.2.4 Willingness to Travel .................................................................................. 192

5.3 Implications ................................................................................................................ 193

5.3.1 Theoretical Contributions ........................................................................... 193

5.3.2 Practical Implications.................................................................................. 195

5.4 Limitations and Directions for Future Research ..................................................... 200

5.5 Conclusion ................................................................................................................. 203

APPENDICES ................................................................................................................. 206

REFERENCES ................................................................................................................. 260

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LIST OF TABLES

Table 2.1 Rock Fan Typology Levels proposed by Beaven and Laws (2007)

Page 32

Table 2.2 Discussion topics categorised into Beaven and Laws (2007) Rock Fan Typology

Page 36

Table 3.1 Motivations for Popular Music Concert Attendance Page 59

Table 3.2 Summary of Motivations across Levels and Types of Involvement

Page 79

Table 3.3 Product Involvement and Fan Identification Matrix 4

Table 4.1 Respondent Profile Page 97

Table 4.2 The Consumer Involvement Profile (CIP): The five facets of Product Involvement

Page 99

Table 4.3 Modified Conversational English CIP Scale by Rodgers and Schneider (1993)

Page 101

Table 4.4 Reysen and Branscombe's (2010) Fanship Scale Page 102

Table 4.5 Concert Attendee Motivation Scale (CAMS) Items Page 104

Table 4.6 Standards of Interpretation used during Statistical Analyses

Page 108

Table 4.7 Product Involvement: Comparison of CFA Models - Factor Loadings, AVE Estimates, Construct Reliability and Criterion Validity

Page 110

Table 4.8 5-factor Vs 4-factor Vs 3-factor Product Involvement Models: Comparison of Fit Indices

Page 110

Table 4.9 Discriminant Validity of 5-factor Product Involvement Model: AVE Estimates and Squared Correlations

Page 113

Table 4.10 Fit Indices: Four Factor Product Involvement Model Page 116


Page 117

Table 4.12 Fit Indices: Three Factor Product Involvement Model Page 119

Table 4.13 Original Vs Modified 3-factor Product Involvement Model: Comparison of Fit Indices

Page 120


Page 121

Table 4.15 Final Product Involvement Measurement Model: Items, Factor Loadings, AVE Estimates and Reliability

Page 123

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Table 4.16 Product Involvement: Sign Facet Items with INTR1 Page 123

Table 4.17 Product Involvement: Original Pleasure Facet with INTR2

Page 126

Table 4.18 Product Involvement: Original Risk Importance Facet Page 127

Table 4.19 Product Involvement: Fit Comparison between First and Second Order Measurement Models

Page 130

Table 4.20 Fan Identification: Comparison of Fit Indices between 9-item and 8-item Model

Page 132

Table 4.21 Fan Identification: Evaluation of Measurement Model - Factor Loadings, AVE Estimates, Construct Reliability and Criterion Validity

Page 133

Table 4.22 Fit Indices: Motivations (CAMS) Page 137

Table 4.23 Motivations: Evaluation of Measurement Model - Factor Loadings, AVE Estimates, Construct Reliability and Criterion Validity

Page 139

Table 4.24 Motivations: Fit Comparisons between Original 10-factor CAMS and Final 9-factor CAMS

Page 140

Table 4.25 Motivations: Discriminant Validity of 9-factor CAMS - AVE Estimates and Squared Correlations

Page 140

Table 4.26 Motivations: Fit Comparisons between First and Second Order Models

Page 144

Table 4.27 Average Number of Popular Music Concerts: Structural Model Results

Page 147

Table 4.28 Number of Artist Specific Concerts: Structural Model Results

Page 148

Table 4.29 Number of Artist Specific Concerts: Mediating effects of Motivations

Page 150

Table 4.30 Number of Artist Specific Concerts: Mediating effects of separate Motivations on the relationship between Product Involvement and Number of Artist Specific Concerts

Page 151

Table 4.31 Fit Indices: Amount Willing to Pay Page 152

Table 4.32 Amount Willing to Pay: Structural Model Results Page 154

Table 4.33 Amount Willing to Pay: Mediating Effects of Motivations

Page 155

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Table 4.34 Amount Willing to Pay: Mediating effects of Separate Motivations on the relationship between Fan Identification and Amount Willing to Pay

Page 156

Table 4.35 Amount Willing to Pay: Mediation effects of Separate Motivations on the relationship between Product Involvement and Amount Willing to Pay

Page 156

Table 4.36 Fit Indices: Willingness to Travel Page 157

Table 4.37 Willingness to Travel: Structural Model Results Page 159

Table 4.38 Willingness to Travel: Mediating Effects of Motivations Page 160

Table 4.39 Willingness to Travel: Mediating effects of Separate Motivations on the relationship between Fan Identification and Willingness to Travel

Page 161

Table 4.40 Willingness to Travel: Mediating effects of Separate Motivations on the relationship between Product Involvement and Willingness to Travel

Page 161

Table 4.41 Hypotheses 1-12 and Summary of Results Page 163

Table 4.42 Hypotheses 13-19 and Summary of Results Page 164

Table 4.43 Correlations between Fan Identification and Motivations Page 167

Table 4.44 Correlations between Product Involvement and Fan Identification

Page 170

Table 4.45 Motivations Positively Influence the Dependent Variables

Page 174

Table 4.46 Mediating Effects of Motivations Page 180

LIST OF FIGURES

Figure 1.1 Preliminary Conceptual Model Page 20

Figure 1.2 Overview of Chapters Page 23

Figure 4.1 Concert Attendee Behaviour: Conceptual Model Page 94

Figure 4.2 Product Involvement: First Order Measurement Model Page 129

Figure 4.3 Product Involvement: Second Order Measurement Model Page 130

Figure 4.4 Motivations: First Order Measurement Model Page 142

Figure 4.5 Motivations: Second Order Measurement Model Page 143

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Figure 4.6 Concert Attendance: Structural Model Results Page 146

Figure 4.7 Amount Willing to Pay: Structural Model Results Page 153

Figure 4.8 Willingness to Travel: Structural Model Results Page 158

LIST OF APPENDICES

Appendix A Study 2: Participant Information Sheet Page 206

Appendix B Study 2: Focus Group Consent Form Page 209

Appendix C Study 2: Focus Group Moderator's Guide Page 210

Appendix D Study 2: Focus Group Handouts Page 214

Appendix E Study 3 Participant Information Sheet Page 217

Appendix F Study 3: Questionnaire Page 220

Appendix G English Translations of the CIP Scale Page 231

Appendix H Proposed Unique Motivations for Popular Music

Concert Attendance

Page 232

Appendix I Study 3: Data Cleaning and Re-specification Activities Page 233

Appendix J Study 3: Product Involvement Normality Testing Page 234

Appendix K Study 3: Fan Identification Normality Testing and EFA Page 236

Appendix L Study 3: Motivations Normality Testing and EFA Page 239

Appendix M Study 3: Product Involvement Models Page 249

Appendix N Study 3: Motivations Models Page 251

Appendix O Study 3: Final Structural Models Page 253

Appendix P Study 3: Structural Model Specification Activities Page 256

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ABSTRACT

The ability to draw consumers to live music performances is vital to the success of

both distinct musical acts, and the perpetuation of the music industry as a whole.

Analysis of popular music concert attendees, however, is sparse.

Therefore, this project investigates the behaviour of concert attendees by

considering consumers’ motivations for attendance, level of fan identification and

involvement in popular music concerts. The investigation comprises three studies

which examine the influence of these consumer behaviour variables on popular

music concert attendee behaviour, measured by: the average number of popular

music concerts a consumer will attend per year, the number of concerts a consumer

will attend for a particular artist, the amount consumers are willing to pay for

popular music concert tickets and the distance consumers were willing to travel to

popular music concerts.

With limited attention given to popular music concerts in the marketing literature, a

netnographic analysis was employed in Study 1 and focus groups conducted in Study

2, in order to gain a deeper understanding of fan behaviour in a popular music

context. These studies explore how popular music fans differ in relation to their

attachment to popular music artists, their level of involvement with popular music

performances and the internal drivers for their behaviour. The findings reveal nine

motivations that drive popular music concert attendance including hero worship,

aesthetics, nostalgia, social interaction, uninhibited behaviour, physical

attractiveness, escape, status enhancement and physical skills. The results also

indicate that fan identification and product involvement are likely to be important

determinants of concert attendee behaviour.

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Utilising findings from Study 1 and Study 2, and in combination with the literature,

hypotheses were developed and a conceptual model proposed in order to test the

influence of fan identification, product involvement and motivations for attendance

on popular music concert attendee behaviour (i.e. number of popular music concerts

per year, number of concerts for a specific artist, amount willing to pay and

willingness to travel) in Study 3. Data were collected from a randomised sample of

Australian consumers who had attended a popular music concert within the last six

months prior to data collection (n=502). Measures were developed (where

appropriate), and refined using exploratory and confirmatory factor analyses and

their psychometric properties assessed. Hypotheses were tested using covariance

based structural equation modelling in AMOS and other multivariate statistical tests

in SPSS.

Major findings relating to the four aspects of concert attendee behaviour, tested in

the structural model, reveal that:

1) The number of popular music concerts consumers attend on average, per year

depends ultimately on an individual’s level of interest in popular music

concerts (product involvement);

2) The number of concerts an individual will attend for any given artist will

directly depend on their level of attachment to that artist, that is, fan

identification (fans with higher levels of attachment will go to see the same

artist more), and motivations for attendance, specifically physical

attractiveness;

3) The amount consumers are willing to pay for popular music concerts will

primarily depend on an individual’s motivation for attending a specific

popular music concert; specifically individuals motivated by aesthetics and

physical skill will pay more for concerts; and

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4) A consumer’s willingness to travel to popular music concerts will be related to

their level of attachment to an artist (fan identification) and, more

importantly, motivations for attendance. Individuals motivated by aesthetics,

hero worship and uninhibited behaviour will travel further to concerts.

This project provides a model for the prediction and explanation of concert attendee

behaviour in a popular music context. Contrary to existing studies on popular music

in marketing, this research offers a quantitative perspective on fan identification and

demonstrates the application of the product involvement scale for a hedonic service.

Development of a scale for measuring motivations for popular music concert

attendance – the Concert Attendee Motivation Scale (CAMS) also provides

academics with a valid and reliable construct for measuring motivations for popular

music concert attendance.

Traditionally popular music marketers have had to rely solely on the promotion of a

specific artist and the music genre in order to attract consumers to live music

performances. Findings from this research suggest that communication of popular

music concerts utilising fan identification, product involvement and motivations will

influence concert attendee behaviour. In order to remain relevant and meaningful to

existing and new markets, marketers should consider consumer behaviour variables

such motivations, fan identification and product involvement in all aspects of

marketing, including the design of product offerings, communication campaigns,

merchandising and branding (including sponsorship).

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CHAPTER1

Introduction

Hedonic consumptive experiences such as popular music concert attendance

represent a significant aspect of cultural events in many countries, though studies

regarding popular music tend to focus on recorded music and neglect live

performances (Cloonan, 2010, Duffett, 2012). The ability to draw consumers to live

music performances is vital to the success of both distinct musical acts, and the

perpetuation of the music industry as a whole. Individuals attend concerts for many

different reasons, and consumption behaviour in relation to popular music concerts

is varied. Concert attendees range from those that exhibit ‘ordinary audience

behaviour’ (Cavicchi, 1998), attending concerts for pure pleasure and enjoyment and

possessing no significant connection to the performer, to the ‘Dysfunctional fan’

(Beaven and Laws, 2007) who will disrupt their life and take advantage of any

opportunity to encounter their favourite artist. The notion of fandom and the

tendency for individuals to form attachments to music celebrities, actors and

athletes (Soukup, 2006) has been well established in the popular culture literature

(e.g. Gray, Sandvoss and Harrington, 2007; Sandvoss, 2005; Hills, 2002; Harris and

Alexander, 1998), however, “audience analysis research exploring the market for live

music concerts and festivals is extremely sparse" (Oakes, 2010, p. 165).

This thesis draws from three theoretical areas of consumer behaviour, namely,

motivations, fan identification and product involvement in order to explain

consumer behaviour in relation to popular music concert attendance. The first

chapter of this thesis provides the background for the topic and introduces the

research problem to be addressed. The discussion will first provide justification for

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the research topic by explaining the importance of popular music concerts in today’s

music industry. It will then consider the role and importance of the three specific

consumer behaviour variables that will be used to explain popular music concert

attendance (motivations, fan identification and product involvement). Throughout

the discussion, major concepts are defined and the relationships between variables

are considered. Chapter 1 concludes with a conceptual model that shows how the

research questions will be addressed in the three studies that comprise this thesis.

The methodology for each study will be introduced, followed by a brief description

and mapping of the subsequent chapters.

1.1 Background

In reference to arts marketing, questions continually arise around the notion of

attendance and determining how to effectively attract larger audiences (Bernstein,

2007). Consumer needs, interests, attitudes and preferences strongly affect

attendance (and non-attendance), and whilst marketers may be able to influence

some of these aspects, a true understanding of the consumer and how providers can

create more value by offering products that are better able to meet consumers’ needs

is required (Caru and Cova, 2006).

Consumers are willing to spend more money on experiences as opposed to material

things (Van Boven et al, 2000). In light of this consumer research specifically

focusing on experiential aspects of the consumption experience has been given

special attention in the literature and is termed, hedonic consumption (Lacher,

1989). Hedonic consumption experiences are said to be subjectively based and are

regarded as “involving a steady flow of fantasies, feelings and fun” (Holbrook and

Hirschman, 1982, p. 132). This seminal definition came about as, traditionally,

consumer research related to hedonic consumption had focused on tangible

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products such as beer, and not how consumers “perceive and experience products”

such as movies and rock concerts (Hirshman and Holbrook, 1982). To date, however,

little research involving music concerts has been conducted within marketing and

consumer behaviour (O'Reilly, 2004).

The global popular music concert business is a billion dollar industry for ticket sales

alone and provides many opportunities for marketers to build strong brand

identities and create long lasting relationships with fans via sponsorship, licensed

merchandise and more (O’Reilly, 2004). The continuing popularity of live music has

been found to be a significant contributor to the popular music scene, where concert

attendance has been considered the most important sector of the music business for

many artists (Waddell, 2009).

The music industry, however, is continually struggling with the impact of digital

recordings on music sales (Rushe, 2010), and, the importance of concerts for

musicians to remain highly profitable, is ever more pertinent (Rushe, 2010). In

February 2011, The Australian Recording Industry Association released music

wholesale sales figures indicating an increasing trend in digital sales, with digital

tracks and digital albums increasing by 47% and 45% respectively from 2009-2010

alone. This meant a continuing decline in sales of physical product (including CD

singles and albums, vinyl, cassettes and music video/DVD), with CD album sales

experiencing the smallest decline, down 21% in dollar value (ARIA, 2011). As digital

sales continue to grow and artists lose revenue in the sales of physical product,

illegal consumption of music also poses a concern and challenge for the music

industry (IFPI, 2012), Figures from the Australian Bureau of Statistics (ABS) show

that Australian households will now spend more than double on music concert fees

and charges (an average of $1.89/week), than pre-recorded compact discs and

records ($0.92/week) (ABS, 2011a).

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As a result of the decline in physical product, touring remains the biggest source of

income for top artists (Billboard, 2012), however, as western economies continue to

face financial challenges, promoters struggle with attendance and turn to strategies

such as ticket discounting and co-billing acts in order to increase audience numbers

(Jones, 2011). Of all arts and cultural events held in Australia, including: art galleries,

museums, classical music concerts, popular music concerts, theatre performances,

dance performances, musicals and operas, and other performing arts, popular music

concerts have the highest attendance rate (ABS, 2011a). According to results released

by the ABS almost one third of the Australian population had attended a popular

music concert in the 12-month period from 2009-2010 (ABS, 2011b), with more than

one-third (40%) attending popular music concerts more than twice (ABS, 2011b).

However, despite the size and nature of the music industry there exists little

research in reference to popular music concert attendance, and audience analysis in

reference to the market for live music concerts and motivations for attendance are

extremely sparse (Oakes, 2010).

The popular music concert industry provides strong links with popular culture,

where financial rewards are possible from an awareness of how popular music fans

form relationships with music artists, bands or brands (O’Reilly, 2004). However,

consumers also receive benefits from marketing exchanges that extend beyond the

primary economic benefits of purchasing products (Arnett, German and Hunt,

2003). Hedonic activities that include culture and the arts, such as popular music

concerts, provide ways for people to connect with others, feel socially included, and

promote positive community identities (ABS, 2011b). What drives people to attend

(or prevents attendance) is a function of “customer’s needs, interests, attitudes, and

preferences” (Bernstein, 2007, p. 16). Whilst the foremost motivation for concert

attendance may be entertainment and to see a performer live, other benefits that

consumers derive from attendance including social, prestige and identity

enhancement benefits, are often deemed just as important in explaining consumer

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behaviour (Reed et al, 2012). Despite this, marketing of popular music concerts has

traditionally focused on the promotion of genre styles and artists (Shuker, 2008). It

appears that understanding the identity enhancement benefits and internal

motivations for attendance may be crucial to understanding what drives consumers

to attend popular music concerts.

1.2 Popular Music and Concert Attendance

Popular music refers to all styles of music that are part of the everyday background

of contemporary social life (Adorno, 1990). It is “mass produced, mass marketed, and

is generally treated as a commodity” (Kotarba and Vannini, 2009, p. 9). Popular

music includes genres from rock, pop, rap, dance, metal and country, and is

commercially orientated, where ‘popular’ can be quantified “through sales, charts,

radio airplay, and so forth” (Shuker, 2008, p. 6). Shuker (2008) defines concerts as

complex cultural phenomena “involving a mix of music and economics, ritual and

pleasure, for both performers and their audience” (p. 57), whilst accentuating that

concerts are about “promotion as much as performance” (p. 59).

Historically, concert tours were crucial for introducing English bands into the

American market during the 1960s and for the commercial breakthrough of many

highly recognised artists. In the 1990s concert tours became purely promotional,

aimed at attracting and developing a fan base for artists, and whilst concert tours

continue to be a crucial part of national and international music scenes today, they

have become more critical to the survival of many artists than ever before (Waddell,

Barnet & Berry, 2007). Concerts play an important role in exposing performers and

their music to prospective fans, facilitating purchases, assisting with commercial

breakthrough, image building and creating a following (Shuker, 2008). Today,

concert attendance is considered the most important sector of the music business

for many artists (Waddell, 2009). As the music industry continues to struggle with

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the impact of digital recordings on music sales (Rushe, 2010), the importance of

concerts for musicians to remain highly profitable is ever more pertinent (Rushe,

2010).

As well as the importance of live music concerts for popular music artists and the

music industry as a whole, concert attendance is seen as an activity associated with a

more encompassing phenomenon, ‘fandom’, which is typically applied to popular

music fans who have a varying degree of enthusiasm and commitment to the

following of music, and particular music performers or music genres (Shuker, 2008).

Basic practices associated with fandom include “an idealized connection with a star,

strong feelings of memory and nostalgia, and the use of collecting to develop a sense

of self” (Gray et al., 2007). It is these practices that create significant affective

involvement in popular culture.

1.3 Social Identity

Social identity theory originates from psychology (Hogg et al., 1995) and forms a

theoretical foundation for understanding consumers’ consumption of popular music

concerts. Social identity theory involves the classification of individuals into various

social categories (Tajfel & Turner, 1985). Social classification is determined from an

individual perspective, where people will categorise or attach themselves with

individuals who are similar in respect to their social and personal identities

(Jacobson, 2003). Social identity involves a connection with others and membership

within a social group (Tajfel, 1978; Donavan et al., 2005; Reysen & Branscombe,

2010), whereas a personal identity comprises specific attributes and interests that

imply an individual connection with an object or person (Wann, 1997; Donavan et

al., 2005; Reysen & Branscombe, 2010). For example, in the context of music, an

individual may identify with a music performer or band (personal identity), but also

have a connection with others who identify with the same performer or band (social

identity). Identification has been described as “the perception of oneness with or

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belongingness to a group, involving direct or vicarious experience of its successes

and failures” (Ashforth & Mael, 1989, p. 34). Ashforth and Mael (1989) also propose

that identification with a group is similar to identification with an individual, for

example a solo music artist, or lead singer of a band.

1.3.1 Fan Identification

Fan identification is derived from social identity theory (Fink et al., 2002; Zhang &

Won, 2010), where a positive social identity is achieved through identifying with an

object and connecting with other fans. A commonly applied definition adopted in

the sporting literature describes fan identification as “an orientation of the self in

regard to other objects, including a person or group that results in feelings or

sentiments of close attachment” (Trail et al, 2000, p. 165-166). This attachment

provides a means by which people begin to define themselves (Sutton et al., 1997).

Therefore, a person may identify with some object (band, artist, organisation, team

or other social institution) through personal identity, but their social identity also

gives an individual a sense of belongingness or membership with others who also

identify with the same object (Mael & Ashforth, 1992).

The concept of fan identification, also termed fandom, is not a new one. Fandom has

been defined as a “phenomenon of public performance” (Cavicchi, 1998:5) and has

been applied to hedonic activities and other types of public performance such as

sporting events, dramatic and cinematic productions, recorded music and concerts

(Cavicchi, 1998). The term ‘fan’ is said to apply to ‘any individual who is an

enthusiastic, ardent, and loyal admirer of an interest’ regardless of the object of

fanaticism (Reysen and Branscombe, 2010: 177), and has also been described to have

both a descriptive and prescriptive reference, also denoting a myriad group and

individuals which have varied degrees of enthusiasm toward something (Cavicchi,

1998).

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Highly identified fans attend more events, pay more for tickets, buy sponsors

products and purchase more licensed merchandise (Fink et al, 2002), whilst less

identified fans are seen as the cause of attendance fluctuations (Wann &

Branscombe, 1993). Highly identified fans, therefore, exhibit greater loyalty, more

price tolerance and less performance sensitivity, then less identified fans (Gwinner &

Swanson, 2003).

1.3.2 Fan Identification in Music

Although fan identification literature has predominantly focused on sport fans,

recent research by Reysen and Branscombe (2010) found that sports fans were

similar to fans of other interests, such as sports, music, media and hobbies; and that

past research regarding sport fans is relevant and projectable to these fans. Reysen

and Branscombe (2010) argue that the term ‘fan’ applies to “any individual who is an

enthusiastic, ardent, and loyal admirer of an interest” (p. 177) regardless of the object

of fanaticism, and that all fans engage in a process of identification. This

identification however, will vary depending on the level of attachment with the

object (e.g. band/artist) (Hogg & Terry, 2001; Sutton et al., 1997).

Despite the similarity realised between sport fans and fans of other interests, a lot of

the sport fan literature focuses on fans as a group, and it has been suggested that

team identification has been distorted with the theoretically different concept of a

personal connection with a team. As stated by Reysen and Branscombe (2010),

“researchers have at times blurred the meaning of team identification – using the

term to signify two theoretically different concepts” (p. 177). In light of this, Reysen

and Branscombe (2010) make a distinction between a personal identity and a social

identity (Simon, 2004; Turner, Hogg, Oakes, Reicher & Wetherell, 1987), by defining

identification with an object, or the fan interest itself, as fanship. This is similar to

the definition of ‘team identification’ as defined by Wann (1997) in the sporting

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literature as “the extent that a fan feels psychologically connected to a team” (p. 331),

which really describes an individual’s connection to the team, and not a fan’s

connection to other fans of the team. Due to the often fuzzy application and specific

wording of fan identification measures used in the sporting literature, Reysen and

Branscombe present a new measure of identification, which reflects a personal

connection with any fan interest. It is important to note that this scale was

generated with participants from four categories of fan interests, with one of those

categories representing music fans. Music fans were represented in all three studies

of scale development and represented 29.3, 20, and 17.3 percent of each study. The

fanship scale was determined to be internally consistent and proved to have

predictive ability. Given that this is the only scale developed to be applicable for use

in a music context; this scale has been adopted to measure an individual music fan’s

connection to an artist or band. This study is therefore not concerned with social

identity, that is, it does not measure a music fan’s connection with other music fans.

For the purposes of this study, a fan is defined as an individual with any degree of

attachment or interest in a particular artist or band, that is, any level of fan

identification.

Despite fan identification being predominately researched in a sporting context,

literature exists that explores the notion of ‘fandom’ in popular culture (e.g. Gray,

Sandvoss & Harrington, 2007; Sandvoss, 2005; Hills, 2002; Harris & Alexander, 1998).

This literature covers a wide range of contemporary culture including music

celebrities, actors and athletes (Soukup, 2006). However, much of the ‘fandom’

literature dealing with music celebrities has been purely qualitative (e.g. Fraser &

Brown, 2002; Soukup, 2006), and is “compounded by the contended nature of

fandom itself, and the sometimes disparaging treatment of fandom and fan

behaviours in academic literature” (Beaven & Laws, 2007, pp. 120-121). While Reysen

and Branscombe (2010) acknowledge that identification measures are applicable

across contexts, no research appears to have investigated fan identification from a

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popular music perspective. Nor has the construct been applied to a popular music

context to measure fan levels of identification, and the effects of identification on

behavioural outcomes, such as concert attendance.

Reysen and Branscombe (2010) examined the similarities and differences between

sport fans and non-sport fans in terms of identification with an object of interest

(fanship) and identification with other fans (fandom). The authors discovered the

findings positively correlated with findings from similar studies in sport (e.g. Wann

and Branscombe, 1993) and developed a universal measure of fanship (fan

identification) applicable across contexts. Using this scale, the authors found that

sports fans were generally similar to non-sport fans and they therefore suggest that

past research regarding sports fans may be generalisable to fans in other categories.

However, whilst the scale is reliable, the authors propose that future research is

needed to assess the predictive validity of the scale for fan behaviour in other

interest categories. This research addresses this gap by addressing the authors' call

for future research to test this measure for popular music fans.

Previous studies on fan identification have identified that fans use many different

forms of media including magazines, television, radio, websites and forums to

engage not only with the object of their ‘fandom’ but also with other fans. Of these

media, online media usage has the strongest impact on fan identification, where fans

were found to use such media, e.g. discussion forums, to maintain and enhance their

identification (Phua, 2010). The concept of online fandom has been introduced to

the literature, from soap opera fans (Baym, 2000) to popular music and rock fans

(Baker, 2009; Beaven and Laws, 2007; Kibby, 2000) and the concept of ‘fan cultures’

and ‘fandom’ has been thoroughly considered by Hills (2002). However, there is no

evidence that approaches classifying levels of fans in reference to fan motivations for

attendance and behaviour have been applied empirically.

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1.4 Product Involvement

Bloch and Bruce (1984) draw a distinction between involvement with a leisure

activity and the product used to participate in that activity. A consumer may possess

a high level of involvement with a product, where the product is the focus of interest

to the consumer, or, conversely, a consumer may be highly involved in a leisure

activity, which then leads to an accompanying involvement with a product needed

to perform that activity. When measuring involvement related to the consumption

of popular music concerts, it may be beneficial to discern the product-related

involvement of concert attendance from artist-related involvement, and the

respective influence of these constructs on behaviour (an individual could be

involved in concert attendance because concerts are important to them, or because

the artist performing the concert is important to them). Consequently, in this thesis,

which aims to explore consumer behaviour in reference to attendance at popular

music concerts, two types of involvement are considered: the consumer’s

involvement with concerts and a consumer’s attachment to the artist or band.

Product involvement is defined as the level of involvement an individual possesses

towards the act of concert attendance, whilst the level of attachment to a performing

artist ‘fan identification’, as defined in section 1.3.1 represents and involves a personal

connection with the artist or band (adapted from Reysen & Branscombe, 2010).

Scholars propose various definitions of product involvement. Key approaches

include the description of product involvement as an individual’s interest in or

attachment to a particular product or service (Richins and Bloch, 1986; Te’eni-Harari

and Hornik, 2010). Product involvement is an important construct in analysing

consumer attitudes and behaviour and is of interest to both consumer researchers

and practitioners (Michaelidou and Dibb, 2006). Product Involvement involves the

“customer’s ultimate concern for a purchase/consumption experience” (Bolfing,

1988, p. 50) and describes the level of interest, arousal, or emotional attachment that

a consumer has with a product or service (Rothschild, 1984; Bloch, 1986). Product

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involvement has been demonstrated to influence “the decision-making process

regarding a product, the extent to which consumers will search for information

about the product, the timing in adoption of the product, the manner in which the

consumer’s attitudes and preferences regarding the product are influenced, the

consumer’s perceptions of alternatives in the same product category and brand

loyalty” (Te’eni-Harari and Hornik, 2010, p. 499). In the current study, product

involvement is defined as a consumer’s level of interest in the consumption of

popular music concerts.

A number of possibilities in reference to an individual consumer’s product

involvement with a concert, versus an attachment with the performing artist/s

emerge. An individual consumer could possess:

(a) a high level of involvement with concert attendance and a high level

attachment to the performing artist;

(b) a high level of involvement with concert attendance and a low level of

attachment to the performing artist;

(c) a low level of involvement with concert attendance, but a high level of

attachment to a particular artist or band; or

(d) a low level of involvement with concert attendance and a low level of

attachment to the performing artist.

Depending on their level of product involvement, particular product categories may

be more or less significant “to people’s lives, their sense of identity, and their

relationship with the rest of the world” (Te’eni-Harari and Hornik, 2010). Product

involvement is suggested to be crucial to the purchase decision making process, and

has been demonstrated to influence the extent to which consumers will search for

information about a product and the manner in which the consumer’s attitudes and

preferences regarding the product are influenced (Te’eni-Harari and Hornik, 2010).

Additionally, the more interested consumers are with a product/service, the more

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they are likely to purchase that product/service (Te’eni-Harari and Hornik, 2010). It

may be important to consider the level of interest and significance consumers place

on popular music concerts when considering what drives concert attendee

behaviour.

Types of Product Involvement

There are two types of involvement that have been generally considered in the

literature, situational and enduring involvement, each representing varying states of

arousal and product interest at different points of time (Michaelidou and Dibb,

2006; Richins and Bloch, 1986). Situational involvement describes temporary arousal

and interest and is stimulated by environmental factors in specific situations, such as

need, promotion and purchase (Richins and Bloch, 1986). Enduring involvement, on

the other hand, corresponds to a long-term arousal and interest about a product,

and signifies an ongoing concern with a product that surpasses any situational

influences, and is stable over time (Laurent and Kapferer, 1985; Rothschild, 1979).

Both situational and enduring involvement describe the degree of arousal and

interest a consumer has with a product or service and both affect consumer

behaviour such as information search and attention to product related messages

(Richins and Bloch, 1986). However, the time at which each of these types of

involvement occurs is different and enduring product involvement is essentially an

interest in, or attachment to a product category which is independent of purchase or

other situational factors (Bloch and Bruce, 1984).It is important to distinguish

between situational and enduring involvement in order to ensure that product

involvement is accurately measured. Therefore, further detail regarding the

differences between situational and enduring involvement follows.

Consumers experience situational involvement when something triggers an interest

or concern in relation to the product, e.g. the product is receiving media attention,

or during the purchase process for high-risk products which are accompanied by

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behaviour such as increased information search to inform the high risk purchase

(Richins and Bloch, 1986). This involvement is temporary and will decline after the

media attention has diminished, or after purchase and the novelty of the new

product has worn off. Enduring involvement describes an ongoing level of interest or

arousal for a product, irrespective of the situational involvement aroused by a

purchase situation. It is stimulated by the extent that the product is connected with

an individual’s sense of self and/or the degree of hedonic pleasure or enjoyment

associated with the product (Bloch and Richins, 1983; Kapferer and Laurent, 1985;

Richins and Bloch, 1986).

In this project, product involvement in relation to popular music concerts will be

measured as an enduring consumer characteristic, that is, the level of consumer

interest in the consumption of popular music concerts. Whilst some studies on

involvement look at the product itself as being high or low in involvement, some

authors believe it may be more realistic to look at involvement as a consumer

characteristic as opposed to a product characteristic (e.g. Bolfing, 1988). As

mentioned earlier, involvement is primarily described as the consumer’s interest in

the purchase/consumption experience and, therefore, an individual’s interest and

varying situational needs that essentially create involvement could affect an

individual’s classification of a product and impact how important the

product/service is to the consumer (Bolfing, 1988). These individual characteristics

mean that consumers will also have different usage goals and desire diversely

different product benefits from their consumption experience. This study is

interested in the factors that influence popular music concert attendee behaviour

and how important attending live performances are to the consumer, as opposed to

how involvement in concert attendance differs from other purchase/consumption

experiences. Therefore, this research examines the influence of enduring product

involvement on concert attendee behaviour.

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1.5 Motivations

Motivations are seen as the fundamental reason for behaviour (Mayo & Jarvis, 1981;

Snepenger, 2006). Whilst varied definitions of motivation exist in the literature,

motivation is commonly defined as “an internal factor that arouses, directs, and

integrates a person’s behaviour” (Murray, 1964, p.7). The decision to attend a

popular music concert will be influenced by an individual’s motivation to fulfil a

desired need (Crompton and McKay, 1997). In defining motivations it is important

to distinguish between motivations and motives. The two terms are often used

interchangeably in the literature, and therefore the motivational concept linked with

need and wants is often confused with the concept of motives. As defined above,

motivations are “an internal factor that arouses, directs, and integrates a person’s

behaviour” (Murray, 1964, p. 7), or a desire to fulfil a particular need (Crompton &

McKay, 1997; Mahatoo, 1989). Motives on the other hand are reasons for behaviour,

“derived from or related to the needs” (Mahatoo, 1989, p. 33). Therefore, according

to Mahatoo (1989), motivations generate the “response tendency” (p. 33), and

motives “direct the specific response” (p. 33). Additionally, a single motivation may

be served by a number of motives. For example, in relation to attending a popular

music concert, an individual may be motivated by social interaction, but their

motive for social interaction may be more related to popularity, conformity, or

connecting. These motives could also potentially be satisfied by a particular number

of ways (Mahatoo, 1989), not specifically concert attendance. Therefore a motivation

represents the need, and motives are reasons for behaviour that are derived from

these needs.

Crompton and McKay (1997) suggest that an understanding of consumer

motivations for attendance is important for designing product offerings. Consumers

purchase a service expecting certain benefits from that service in order to satisfy a

particular need. Identifying these needs is a key factor in developing elements of a

concert event and tailoring marketing communications to address these needs.

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Crompton and McKay (1997) found a very close relationship between motivation and

satisfaction, where motivations for attendance occur before the concert and

evaluation of satisfied needs are made after the concert has been attended. Therefore

in order to ensure that consumers are satisfied with popular music performances, it

is necessary to understand first what they seek to gain from popular music concert

attendance.

Existing studies on motivation have yet to include a specific focus on popular music

concerts, though studies on motivation exist in reference to attendance at sporting

events (see Fink, Trail and Anderson, 2002; Wann,1995), jazz festivals (Formica and

Uysal,1996), tourism (Iso-Ahola, 1982; 1983; 1990; Snepenger, King, Marshall &Uysal,

2006), performing arts (Swanson, Davis & Zhao, 2008), music festivals (Bowen &

Daniels, 2005) and festival events in general (Crompton and McKay, 1997; Nicholson

and Pearce, 2001).

A number of reasons can be identified for investing effort into better understanding

the motivations of popular music concert attendees. Firstly, it has been shown that

motivations will differ depending on the type of event attended (Nicholson and

Pearce, 2001), and secondly, motivations are not mutually exclusive (Iso-Ahola, 1983;

1990). Therefore, whilst it is possible that motivations for popular music concert

attendance may be similar to those of other events and activities, it is possible that

unique motivations exist, and additionally, particular combinations of motivations

specific only to popular music concert attendance. Finally, studies related to

motivations for attendance to music festivals have indicated that motivations may be

used to broaden the appeal of music events (Bowen and Daniels, 2005). Therefore,

by identifying how groups of consumers differ in respect to motivations for

attendance, it may be possible to market popular music concerts beyond the

promotion of genre and artist.

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1.5.1 Motivations and Fan Identification

Empirical studies in the sporting literature have found correlations between fan

identification and motivations (Trail et al., 2000; Trail & James, 2001; Wann, 1995), as

well as gender differences in respect to motivations. Fink, Trail and Anderson (2002)

examined the relationship between the motivations: vicarious achievement,

aesthetics, drama, escape, family, acquisition of knowledge, appreciation of physical

skills of the participants, social interaction, and physical attractiveness of the

participants and fan identification. For males and females, the social prestige, self-

esteem and social empowerment of being associated with a successful team

(vicarious achievement) was the most significant motivation for attending sporting

events (product involvement) and explained the most variation in identification with

a team (fan identification). However, the combination of motivations for attendance

differed for males and females. Females appreciated the vicarious achievement,

aesthetics and drama the sport provided, and whilst males were also were motivated

by the vicarious achievement and aesthetics of the sport, acquisition of knowledge

and the social interaction attained at games were also important. Spending time

with family was the only motivation found not to be related to fan identification

(Fink et al., 2002, Wann, 1995). As fan identification is a strong predictor of fan

consumption behaviour (Fink et al., 2002; Madrigal, 1995; Wakefield, 1995; Wann &

Branscombe, 1993), understanding motivations for concert attendance in music

(including motivations for males and females), and the relationship between

motivations and fan identification, may provide valuable knowledge regarding

concert attendee behaviour for music managers and music marketers.

1.6 Research Questions

Studies regarding popular music have tended to focus on recorded music and

neglect live events (Cloonan, 2010; Duffett, 2012), which is simultaneously expected

17 | P a g e

and surprising respectively. It is predictable that scholars would be interested in the

impact of digital recordings on music sales, but it is evident that little attention has

been paid to the importance of ensuring the dynamic service environment of the live

performance is preserved. Live popular music performances have been described

continuously as being “an essential part of popular music’s gestation, creation,

development, and establishment (Kronenburg, 2011), however the live music

industry’s aims remain primarily economic, that is, to fill seats and standing space,

and to sell tickets (Duffett, 2012). The goal of selling tickets has often outweighed the

importance of creating enjoyable fan experiences, with promoters more likely to woo

fans as a consumer group, than aim to please them as a community (Duffett, 2012).

This is contrary to the goal of artists who are more concerned with creating and

maintaining a fan base. Whilst these may seem like very disparate goals it is possible

that the aspirations of both artist and promoter could be simultaneously achieved

through different promotion strategies. The utilisation of behavioural drivers which

incorporate knowledge gained from understanding the influence of motivations, fan

identification and product involvement on popular music concert attendance, may

mean that more tickets can be sold whilst still focusing efforts on maintaining and

creating a fan base. These constructs have also proven to be useful in explaining

consumer behaviour in a number of contexts, but have yet to be applied to a popular

music context specifically.

The three major questions guiding this project are therefore:

1) What are consumers’ motivations for popular music concert attendance?

2) What is the relative influence of motivations, fan identification and

product involvement on popular music concert attendance?

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3) What is the relative influence of motivations, fan identification and

product involvement on the amount consumers are willing to pay for

concert tickets?

1.7 Proposed Conceptual Framework

Based on the theoretical background provided on the constructs: motivations, fan

identification and product involvement; in reference to popular music concert

attendee behaviour, it is proposed that people will have different levels of

involvement with the product (concerts) and also have different levels of attachment

to the artist or band that is performing the concert (fan identification). Product

involvement and fan identification may be important predictors for explaining

consumer behaviour in relation to popular music concert attendance. It is also

possible that one’s motivation for attending popular music concerts will affect

concert attendee behaviour, and motivations for attendance may also influence the

relationship between level of product involvement and concert attendee behaviour,

and fan identification and concert attendee behaviour. The relationships between

these constructs will be important to marketing managers when designing product

offerings and communication aimed at targeting individuals. A preliminary

conceptual model of these relationships is shown in Figure 1.1.

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Figure 1.1: Preliminary Conceptual Model

1.8 Structure of thesis

Despite being able to make speculations regarding motivations, fan identification

and product involvement based on literature, very little is known about how these

variables will operate in a popular music context. Therefore, the first two studies of

this thesis are dedicated to exploring concert attendee behaviour and the constructs

motivations, fan identification and product involvement in reference to popular

music concerts. These studies will provide the foundation for the development of

hypotheses and refinement of the preliminary conceptual model. Each study will

build upon the previous in order to gain a complete understanding of the constructs

before developing and testing a proposed structural model in Study 3. In order to

test the model it was first important to:

1) Gain a full understanding of fan identification and behaviour within a

popular music context;

2) Explore the constructs of motivations, fan identification and product

involvement and their potential influence on concert attendee behaviour;

Gender

Fan Identification

Product

Involvement

Motivation

Concert Attendee Behaviour

20 | P a g e

3) Identify motivations for popular music concert attendance and determine if

they differ to other types of events covered in the literature; and

4) Develop a scale for measuring motivations for popular music concert

attendance.

The project employs a combination of qualitative and quantitative methodologies.

Studies 1 and 2 both utilize a qualitative design in order to explore each of the

constructs in a popular music context and to aid questionnaire development for a

final quantitative study, Study 3. First a netnographic method was adopted for an

initial exploration into fan behaviour. This unobtrusive method allowed the

researcher to develop insight into the topics needed for the development of the

project and to gain valuable information needed to inform subsequent studies,

specifically in relation to the construction of a moderator's guide for focus groups

utilised in Study 2. Study 2 was conducted to generate information and detail needed

to produce hypotheses. Findings from the focus groups also facilitated the

development of the Concert Attendee Motivation Scale (CAMS) by first identifying

motivations specific to popular music concert attendance that had yet to be

discussed in any detail in the literature, and second, generating wording to be

adopted for scale items for the CAMS.

Results of the exploratory research in Study 1 and Study 2 reinforced speculations

regarding the influence of motivations, product involvement and fan identification

on popular music concert attendee behaviour. These keys variables have been

known individually to influence attendance to other types of events (particularly

sporting events); however findings from Study 1 and Study 2 suggest some

differences for popular music concerts, specifically in relation to motivations for

attendance. These findings informed the development of a conceptual model for

concert attendee behaviour and the development of hypotheses to be tested. Study

3, therefore applies a quantitative approach in order to test the hypothesized

relationships between motivations, fan identification and product involvement, and

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their influence on concert attendee behaviour. Concert attendee behaviour was

measured on a number of aspects, including: the average number of popular music

concerts attended per year, number of popular music concerts for a particular artist,

amount willing to pay for concert tickets, and willingness to travel.

This thesis comprises five chapters. A visual illustration giving an overview of

chapters is provided below (see Figure 1.2). Chapter 1 Introduction has provided the

background, overall rationale for the project and advice on how the thesis will

proceed. This chapter also provides a brief overview of the literature that builds the

theoretical foundation for exploring the factors that influence popular music concert

attendance. Chapter 2 Study 1 examines the objectives, methods, procedures and

results of the netnographic study of an online fan community and presents

implications for subsequent studies for this thesis. Chapter 3 Study 2 details the

specifics of the focus groups conducted to explore the relevant constructs in a

popular music context. Again details of the method, procedures and results are

presented, along with a discussion of the implications for the final study. Chapter 4

Study 3 utilises studies 1 and 2 and the extant literature, to develop hypotheses for

testing the relationships proposed in the preliminary conceptual model. This chapter

outlines the methods, procedures and results of the online quantitative study. The

chapter concludes by reporting the hypothesis tests and interpreting the results of

the analysis. Finally, Chapter 5 Conclusions provides a discussion of the results of the

three studies, linking back to the theoretical perspectives outlined in Chapter 1. This

chapter offers a conclusion to the thesis by examining the theoretical implications of

the results for contribution to the body of literature regarding popular music concert

attendance and the constructs under investigation, as well as the practical and

managerial implications for artists and concert promoters. Chapter 5 also identifies

limitations of the overall project and presents directions for future research.

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Figure 1.2: Overview of Chapters

CHAPTER 1

Introduction

• Background

• Theoretical Framework

o Popular Music

o Concerts

o Fan Identification

o Product Involvement

o Motivations

• Research Questions

• Significance of the Research

o Theoretical Contribution

o Practical Contribution

CHAPTER 2

Study 1 –Netnography

• Literature • Research Design • Procedure • Results • Discussion and Implications for Studies 2 & 3

CHAPTER 3

Study 2 – Focus Groups

• Literature • Research Design • Procedure • Results • Discussion and Implications for Study 3

CHAPTER 4

Study 3 – Online Survey

• Research Design • Measures • Development of Hypotheses • Results • Discussion

CHAPTER 5

Conclusion

• Summary

o Concert Attendee Behaviour

o Fan Identification

o Motivations

o Product Involvement

• Contribution to Literature

• Managerial Implications

• Limitations

• Future Research

• Conclusion to Project

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1.8.1 Overview of Studies

Chapter 2: Study 1 - A Netnographic Analysis of Online Fan Behaviour

Study 1 details a netnographic study of an online fan community which aimed to

gain a greater understanding of fan identification and behaviour within a popular

music context. Posts from the discussion forum of one popular music artist –

Metallica, were contextually analysed over a one month period. To aid the analysis, a

rock fan typology derived from a mapping exercise undertaken by Beaven and Laws

(2007) was used to categorise fans into four different fan levels and used to report

the behaviour of fans participating in the online discussion. The results of Study 1

provided a deeper understanding of fan behaviour and highlighted some areas of

research to be addressed in subsequent studies. The study also suggested that the

three constructs (motivations, fan identification and product involvement) play a

key role in influencing fan behaviour in relation to popular music concerts. The

findings from Study 1 highlighted some important implications for the focus groups

to be conducted in Study 2, and more significantly identified the ‘willingness to

travel’ dependent variable that was incorporated into the quantitative survey in

Study 3.

Chapter 3: Study 2 - An Exploration of Consumer Motivations, Fan Identification and

Product Involvement in Concerts

Focus groups were conducted in Study 2 to explore the constructs of motivations,

fan identification and product involvement in a popular music context, and to aid

variable identification and development of items for the Concert Attendee

Motivation Scale (CAMS) to be used in the succeeding quantitative study.

Specifically, ten motivations for popular music concert attendance were identified,

including; nostalgia, aesthetics, escape, physical attraction, status enhancement,

physical skills, social interaction, hero worship and uninhibited behaviour.

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Motivations were found to differ to other types of events discussed in the literature

and participants discussed possible relationships between motivations and fan

identification, and motivations and product involvement. These discussions lead to

the development of additional hypotheses to be tested in Study 3.

Chapter 4: Study 3 - Testing Relationships between Fan Identification, Product

Involvement and Motivations.

Finally, Study 3 was conducted to test the proposed structural model. A

questionnaire was constructed using the literature and findings from Study 1 and

Study 2 to aid development, and a reputable online research company was

commissioned to distribute the questionnaire to Australian consumers of varying

demographics. The relationships between fan identification, product involvement,

motivations and concert attendance (including amount willing to pay and

willingness to travel) were then examined. In total, 19 hypotheses were tested,

including the mediating role of motivations between fan identification and concert

attendance and product involvement and concert attendance relationships.

1.9 Significance of the Research

The findings of this research have significant implications for both theory and

practice, and are therefore beneficial to scholarly work, and also marketing and

music industry professionals, including concert promoters.

1.9.1 Theoretical Contribution

The theoretical contributions of this project are situated in a number of areas

including consumer behaviour, arts marketing, tourism marketing and leisure

marketing. Details are outlined below.

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1) The research provides a theoretical model for the prediction and explanation of

popular music concert attendance, the amount individuals are willing to pay

for popular music concert tickets, and willingness to travel to popular music

events.

2) Fan identification in a popular music context is explored and tested in a

quantitative study. Previously, fan identification has predominately been

explored qualitatively in the fandom literature (Schimmel, Harrington and

Bielby, 2007).

3) The product involvement scale of Laurent and Kapferer (1985) is applied in a

popular music context. Three facets of product involvement; sign value,

pleasure, and risk probability, are found to relate to popular music concerts.

The findings contribute to theory regarding the product involvement

construct, and specifically enhance its understanding by providing results for

another service application. Findings involving the construct will add to theory

regarding the dimensionality of the construct which has been shown to differ

for various products and services.

4) The development and testing of the new Concert Attendee Motivation Scale

(CAMS) provides a valid and reliable construct for measuring motivations for

popular music concert attendance, including details regarding the dimensions

of motivations for popular music concert attendance and item wording.

5) The project demonstrates that consumer motivations for popular music

concert attendance differ to other types of events detailed in the literature.

Motivations found to be significant to popular music concert attendance

include: nostalgia, aesthetics, escape, physical attractiveness of artist, status

enhancement, physical skills of artist, social interaction, hero worship and

uninhibited behaviour.

6) Motivations are found to play an important role in predicting popular music

concert attendance and findings of this project enhance our understanding of

the potential use of motivations in attracting consumers to specific events.

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Specifically, individuals motivated by the physical attractiveness of the artist

will attend more concerts for that artist; individuals motivated by aesthetics

and physical skill will pay more for concerts; and individuals motivated by

aesthetics, hero worship and uninhibited behaviour will travel further to

events.

1.9.2 Practical Contribution

The project has practical implications for music managers and concert marketers

and promoters. Findings of this research may help popular music concert promoters

and artists to achieve marketing goals with balance, typically in relation to the sale

of tickets versus the creation and maintenance of a fan base. Practical implications of

these research findings are detailed below.

1) Overall, this research provides concert promoters a deeper understanding of

what type of popular music consumer is attracted to the live music product,

their motivations for attendance and insight into the role product involvement

and fan identification plays in respect to; frequency of popular music concert

attendance, amount willing to pay for tickets and willingness to travel to

events.

2) These findings provide detail regarding how fans differ in their level of product

involvement, attachment with artists and other fans, and motivations for

attendance. Outcomes related to this research will therefore provide useful

insight for marketers, enabling them to more effectively segment and target all

types of fans, including loyal attendees, occasional ticket buyers and also

potential audiences.

3) From a managerial perspective, comprehension of these findings will allow

music managers and promoters to address the desires of different market

segments efficiently regarding design of product offerings, communication

campaigns and merchandise.

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4) Concert promoters traditionally focus on promoting the music genre and/or

artist (Shuker, 2008). The results of this research, however, indicate that the

consideration of consumers’ motivation for attendance offer new alternatives

for promotional strategies aimed at targeting consumers beyond an emphasis

on genre and the performing artist.

5) Results of this study suggest a reliance on the music itself or a specific artist, to

attract all audiences is unlikely, especially at popular music concerts, where

there is an absence of other activities, diversions and non-musical attractions

that are typically associated with music festivals (Bowen and Daniels, 2005).

Findings of this research therefore, suggest ways for artists and concert

promoters to attract fans with low levels of fan identification and product

involvement.

1.10 Chapter Conclusion

This research proposes that fan identification, product involvement, and motivations

each play an important role in determining attendance at popular music concerts,

and other important variables associated with attendance, such as amount willing to

pay for tickets and willingness to travel. This chapter outlines the purpose of the

research, which is to empirically support this claim by first gaining insight through

qualitative techniques, so that these constructs can be adapted to, and fully

understood from, a popular music perspective, and second, to quantitatively test the

proposed theoretical model. The methodologies to be employed in the three studies

comprising the project and the theoretical and practical significance of the project

are summarised. The next chapter will detail and present the findings of the first

study of this thesis, and will include discussion and implications for subsequent

studies of this project.

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CHAPTER 2

Study 1 - A Netnographic Analysis of Online Fan Behaviour

2.1 Introduction

Chapter 2 examines the methods, procedures and results of the first study of this

thesis, which is a netnographic study conducted to explore fan behaviour in relation

to popular music concert attendance. The chapter first discusses theory to further

understand fan identification and its application to a popular music context. Further

detail regarding the specific methodology is then presented, followed by a discussion

of the results and implications for Study 2 and Study 3.

2.2 Aim of Study 1

The aim of Study 1 is to gain a greater understanding of concert attendee behaviour

in a popular music context. Netnography is used to explore the different levels of fan

identification evident among online concert goers using the public message board of

the rock band Metallica, and analysed with respect to an existing rock fan typology.

As mentioned in Chapter 1, fan identification is proposed to influence individual

motivations at attendance to popular music concerts, as well as popular music

concert attendance directly. However, research in reference to fan identification in a

popular music context, and motivations for popular music concert attendance is

limited, and not yet rich enough to provide a sound conceptual foundation for

investigating the role of these constructs in relation to concert attendee behaviour.

In light of this gap, exploratory research was needed to provide greater insight and

background information in reference to fan motivations and behaviour, and to

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explore how these motivations and behaviour might differ between individuals with

varying levels of fan identification.

2.3 Levels of Fan Identification

The abundance of literature regarding sport fan identification has shown that

individuals, who share similar fan experiences, can possess very disparate levels of

identification (Hogg & Terry, 2001; Sutton et al., 1997). Beaven and Laws (2007)

proposed that the levels of engagement in the fan community and the management

processes required in sport are closely congruent with music, inferring that the use

of the fan identification construct in a music context is justified.

Sutton, McDonald and Milne (1997) suggested three discernible levels of fan

identification; low identification (Social Fans), medium identification (Focused

Fans) and high identification (Vested Fans). These levels were derived on the belief

that not all fans have the “same level of fervour, devotion, and commitment to their

favourite team” (p. 17). Social Fans partake in a passive relationship with the sport,

are low on emotion and are attracted by the entertainment and social value of the

sport. Focused Fans form an association with a sport or team based on “fad, social

factors, team performance, or player personality” (p.17), however, the relationship or

identification may be short term and can be easily affected by poor performance or

changes in the team. Vested Fans are the most loyal and hold the longest

relationship with the sport or team. They are very emotionally involved, and possess

unwavering loyalty even in instances of poor performance (Sutton et al., 1997). In

reference to popular music, a music fan with low identification may go to a concert

because they like that particular genre, but not specifically the band that is playing.

A music fan with medium identification may like the band because they believe they

put on a great live performance or are partial to the lead singer (or other), but may

lose their identification if the band becomes too old and no longer “performed”, or

the lead singer left to follow a solo career, join another band or became deceased. A

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fan with a high level of identification would possess the same qualities as a highly

identified vested sport fan. While logical, this comparison is only intuitive and

requires further investigation.

In response to the absence of research about rock music fans, Beaven and Laws

(2007) undertook a mapping exercise drawing from sport and popular culture

literature, namely Hunt et al (1999) and Thorne and Bruner (2006) to produce a

terminology of different fan levels appropriate to rock fans. The ‘Rock Fan Typology’

(Beaven & Laws, 2007:125) proposed four different fan levels: casual, loyal, die hard

and dysfunctional. Table 2.1 shows how these levels are characterised. The

definitions provided for each of these fan typologies provide information as to the

type of consumption behaviour each fan level may participate in (for example,

concert attendance, recordings, t-shirts and other merchandise), as well as their

individual social behaviours.

Whilst Beaven and Laws (2007) characterised fans at four different levels in their

rock fan typology, when applying this typology to discourse of fan behaviour

discussed on a rock band’s discussion forum, they were unable to identify casual fans

in their research. This framework provides a starting point for a preliminary

exploration of concert attendee behaviour and will be used to categorise the

reported behaviour of concert attendees participating in an online discussion forum

of the popular band, Metallica. The following research questions are used to guide

Study 1:

1. What levels of fan identification are evident among concert goers of the

online fan community?

2. Do these differ in terms of definition or abundance in reference to Beaven

and Laws (2007) proposed levels of rock fan typology?

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3. What concert related behaviours appear to differentiate fans categorized at

different levels of identification?

Table 2.1: Levels of Rock Fan Typology (Beaven and Laws, 2007, pp.126-127)

Casual Fan

A fan for a limited time (coinciding with a chart placing)

Die Hard

Fan

Band is very important to self – identification

May be a regular attendee of a broad range of concerts but may only make a casual decision to attend a specific concert.

Will own all or most recordings, collect merchandise and will be very knowledgeable about band history.

May own a small number of recordings

Will wear t-shirts from previous tour or dress up

Will make changes to lifestyle - will travel and attend more than one gig per tour

Loyal Fan

Uses the band to maintain self-concept and is loyal even if chart placing is low.

Dysfunctional

Fan

Band is primary means of self-identification and is main method of identification to others.

Will attend a focused range of concerts within the band’s sub-genre but prioritise attending band’s local concert

Will maintain a relationship with others in the community, although may seek to be recognised as an expert by them or be competitive or antagonistic to the community.

May identify themselves by wearing a band t-shirt and has many recordings and some merchandise.

Interferes with other aspects of life (following tours at the expense of work/family life)

May seek contact with the band, including stalking behaviour

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2.4 Research Design

Netnography is a technique that has been specifically developed for studying online

communities in a natural and unobtrusive nature as opposed to traditional

qualitative techniques such as focus groups and interviews (Kozinets, 2002).

Netnography as a marketing research tool can provide researchers with an in-depth

understanding of online consumer groups, including behaviour and consumption

patterns, and has been used for a wide range of topics, including identity (Kozinets,

2002; Misra et al, 2008; Kozinets, 2010).

2.4.1 Rationale for using Netnography

Previous studies on fan identification have acknowledged that fans use many

different forms of media including magazines, television, radio, websites and forums

to engage with both the object of their ‘fandom’ and with other fans. Of these,

however, Phua (2010) found online media usage has the strongest impact on fan

identification, where fans were found to use online media, such as discussion forums

to maintain and enhance their identification. Online fan communities are said to be

taking the place of traditional music scenes (Gray, Sandvoss & Harrington, 2007)

with these spaces, along with message boards of popular music artists and bands,

providing a virtual space for these fan communities to express their ‘fandom’,

somewhere they can communicate their fanatical interests and social connections

irrespective of geographical location (Kozinets, 1999). Further, fan communities are

seen to be consumers and producers of a vast array of information (Baker, 2009).

Netnography is a modernized version of ethnography, adapted in light of

technological advances such as the internet, for studying participant discourse in an

online community. The benefits of netnography, as opposed to traditional

qualitative techniques such as focus groups and conventional ethnography, is that it

provides an economical and efficient means for studying specific consumer groups

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(Kozinets, 2002). Netnography is also seen as less intrusive than ethnography, the

data is publicly available and due to the nature of online discussion forums, the

written communication is already inherently transcribed (O’Reilly et al, 2007).

The advantages outlined above, and the tendency for online communities to make

available a large quantity of data, justify the use of netnography and the analysis of

an online discussion forum as an exploratory research tool. As little is known about

the application of fan identification in a popular music context, nor the specifics on

motivations for popular music concert attendance, the netnographic exploration of

an active fan community was deemed appropriate for obtaining detailed insight into

the topics.

The choice of Metallica’s message board for this study was based on chart placing at

the time of the research and additionally on criteria adhered to in the literature

(Kozinets, 2002; Misra et al, 2008). In February 2010, Metallica, were number one at

the box office for U.S concert sales, with an average box office gross of $US1.37

million per city in a week (Chicago Tribune, 2010). Mid-year in 2009, Metallica had

grossed over $US20 million between 1 January and 30 June, selling 330,655 tickets in

a six month period, after touring only nine cities (Pollstar, 2009). These statistics

suggest that Metallica should have a substantial fan base, and an active online

community was discovered on inspection of the band’s official website.

According to Kozinets (2002, p. 63), a preferred online community is one that has:

• A more focused and research question-relevant segment, topic, or group;

• Higher ‘traffic’ of postings;

• Larger numbers of discrete message posters;

• More detailed or descriptively rich data; and

• More between-member interactions of the type required by the research

question.

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In February, 2010, Metallica’s message board had five forums: Anything Metallica,

Tour, March Madness Song Tournament, Death Magnetic and Polling Time. The

content of the ‘Tour’ forum was deemed ‘research question relevant’ to concert goers

(entailing discussion of ‘shows, set lists and anything that relates to Metallica

touring’). The message board is publicly accessible (no need to join or pay money)

and has a large fan base. As of 2 March, 2010, the number of topics in the ‘Tour’

forum was 3,131, with 64,915 replies and at the time of viewing there were a total of

154 active users online. The researcher did not actively participate in the discussion

to avoid influencing interactions (Kozak and Decrop, 2009). Consent was not

required as access was not restricted (for example, by passwords and membership)

and thus the site is deemed ‘public communication’ (Elgesem, 2002; Langer and

Beckman, 2005; Beaven and Laws, 2007 and Kozak and Decrop, 2009).

2.5 Procedure

An exploratory sample of 1524 postings (with 72,124 views) from the Metallica

message board was analysed over a one month period (February 1, 2010 to February

28, 2010). All threads and their related posts were retrieved and downloaded. As a

first pass, threads were either coded as 'primarily social' or 'informational'. As the

social posts would be of interest in this research area, they were further classified as

either on-topic or off-topic (Kozinets, 2002). On-topic threads and posts (113) were

then contextually analysed and categorised into one of the four rock fan typologies

using Beaven and Laws’ (2007) criteria (see Table 2.1).

Evidence of discourse in the discussion that coincided with the criteria in the rock

fan typology was sought to categorise the fans as casual, loyal, diehard or

dysfunctional. The data are reported in Table 2.2. All four levels of the fan typology

were evident in the exploratory sample.

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Table 2.2: Discussion topics categorised into Beaven and Laws’ (2007) rock fan typology.

Casual Fan Missed tickets/haven't seen

Metallica before (2)

Die-Hard Fan

Practice attempts to get tickets (2)

Meet up before show with other fans (6)

New fan/ first Metallica concert (2) Know band/history (12)

Don't care where they get seats (1) Attend multiple shows (2)

There for fun (1) Comment on changing quality of shows (2)

Like live music (2) Think they are Metallica's biggest fan (4)

Seek advice/Info from other fans (5)

Only see band if outdoor concert (8)

Loyal Fan

Become a fan member to get good tickets (1)

Dysfunctional Fan

Competitive/antagonistic behaviour towards other fans (4)

Upload videos from concerts (1) Can't sleep (11 weeks before concert) (1)

Give tour advice to Metallica (25) Changed travel plans (1)

Brag about getting tickets (3) Early Line up (2)

Identify with genre (1) Stalking behaviour/seek contact with band (1)

Personally address the band/band member (19)

Willing to pick up stranger / Willing to go with stranger (2)

Drive/Fly long distances to follow

tour (3)

When dividing the discussion topics; where a post was distinctly congruent with

Beaven and Laws (2007) criteria, supporting discussion and other posts by the same

user were then examined and the posts of the individual were always categorised at

the most extreme fan level. If an individual posted discourse that only related to

criterion specific to casual fan behaviour, then they were included in the ‘casual’

category (and therefore all of their posts were included in the ‘casual’ section of

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Table 2.2). If a participant posted discourse that was relevant to the dysfunctional

criterion set out by Beaven and Laws (2007), then they were regarded as being a

‘dysfunctional’ fan and all other discourse the individual engaged in was positioned

as discourse of behaviour pertaining to a dysfunctional fan. For example, consider

discussion related to ‘bragging about ticket purchases’ which was categorised as

behaviour pertaining to a loyal fan. It is possible that a dysfunctional fan may also

engage in this behaviour, but for those individuals identified as dysfunctional fans

(by matching with at least one criterion of Beaven and Laws (2007) rock fan

typology), there was no corresponding discourse evident in the discussion analysed

to indicate this behaviour. For posts that signified bragging about tickets purchases;

when considering supporting content or other posts by the same individuals

reporting this behaviour, the behaviour did not surpass that of a loyal fan. Coding

continued until all fan discourse was categorized.

2.6 Results

2.6.1 Casual Fan

A total of 21 posts out of the 113 on-topic posts (19%) were identified as discussion

pertaining to a casual fan. A casual fan was identified as being a fan for a limited

time, such as coinciding with a chart placing (Beaven and Laws, 2007). At the time of

analysis, Metallica were on tour for their ‘Death Magnetic’ album. The majority of

discussion apparent at this fan level was associated with the desire to obtain tickets,

see Metallica for the first time and to seek information or advice from other fans.

Cavicchi (1998) suggests that one can only be a fan if an individual places certain

significance on the popular culture and those that attend for pure pleasure and

enjoyment are exhibiting only ordinary audience behaviour. These individuals are

seen to have a temporary role, in that they may listen to an artist’s music and attend

a concert or two, but possess no significant connection to the performer beyond that 37 | P a g e

of enjoying the “superficial elements of rock performance” (Cavicchi, 1998, p. 91).

When categorising the discourse of fans into the ‘casual’ category, those posts that

lacked a significant connection with Metallica and expressed desires of only seeing

the band for pleasure and enjoyment in the leisure activity itself were included.

These fans seemed to make a ‘casual’ decision to attend (Beaven and Laws, 2007), as

they were not bothered with seating allocation and expressed the desire to attend for

fun – drinking and ‘rocking out’.

As one casual fan expresses,

…alls [sic] I know is I'm gonna get hammered drunk and rock out!

Casual Fans also sought to seek other forms of live music entertainment on the night

and surrounding days; an indication of attendance to a broad range of concerts

(fitting with the criteria proposed by Beaven and Laws, 2007). Moreover, some

participants only expressed an interest in seeing the band at outdoor festivals,

indicating attendance for experience and not necessarily a necessity to see Metallica.

I could [sic] care less about seeing them in some hockey or

basketball arena. The energy and atmosphere just isn’t there

unless they play outside.

2.6.2 Loyal Fan

Classification of this fan level was the hardest when it came to determining whether

an individual used the band to maintain their self-concept and whether they owned

t-shirts, recording and merchandise (unless it was explicitly expressed in the post).

One of the criteria proposed by Beaven and Laws (2007) that would categorise a fan

at this level was that these fans would attend a focused range of concerts within the

band’s sub-genre but prioritise attending the band’s local concert. This criterion was

38 | P a g e

used to start categorising the ‘loyal fan’. Where specific evidence was sought in

reference to only attending the local concert and also attendance to other bands in

the sub-genre, further information on motivations and behaviour could then be

established.

These fans attended other rock concerts in the sub-genre like Alice in Chains,

Slipknot and Machine Head. As well as wanting to attend Metallica’s local show, fans

seemed to want to ‘celebrate’ the occasion by making a weekend of shows in the sub-

genre.

I will be there for sure!!! I got floor tickets. I'm hoping Machine

Head does a show at the House of Blues the night before. Also,

have you guys ever heard of a band named Steel Panther? They

look stupid but are funny as hell. They will be doing a show

Friday night. Also there might be something going on at The

Hard Rock Hotel.

These same fans also indicated they became fan club members to obtain good tickets

(and they also brag about getting them). The preponderance of discussion among

loyal fans was dedicated to making contact with the band. Participants personally

addressed the band and specific band members, providing tour advice, advising

where they should travel and with whom they should tour.

Love u guys, you guys kick ass!!!! Oh yeah, Lars.. U are the

baddest ass drummer ever.

Dear Metallica, last time you came to Serbia the show was

awesome but many of your trusting fans weren't there

:banghead: and we'd really, really, love to see you again..

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Discussion was also devoted to thanking the band for their performances, giving

individual band members personal praise and shaming them on broken promises.

Loyal fans contributed to the majority of discussion during the period of data

collection (n=50; 44%).

2.6.3 Diehard Fan

In order to identify a diehard fan, it was easiest to first establish whether the

discourse represented behaviour of a dysfunctional fan. As the post had already been

excluded from the casual and loyal categories, it seemed logical to then ask, is this

behaviour extreme enough to be indicative of someone with an unwavering

dysfunctional attachment?

Discussion from participants classified as diehard fans accounted for 25 percent

(n=28) of total on-topic posts. These fans were knowledgeable about the band and

the band’s history and were able to comment on the changing quality of recordings

and shows. They demanded recognition of this knowledge by acclaiming themselves

as Metallica’s biggest fans (though they were often harassed by dysfunctional fans).

lol biggest fan, pretty much everyone think that they are

Metallicas biggest fan. I am a dedicated fan that worships, and

obsesses over Metallica.. Doesn't mean that I am the biggest fan

Cavicchi (1998) suggests that an individual’s behaviour presents a more realistic

indication of fan level than attitude does, therefore, proclamations or attitudes of

being “Metallica’s biggest fan” without an exhibition of the behaviour associated

with the dysfunctional fan (someone who probably could actually be Metallica’s

biggest fan), was included in the diehard fan category. Diehard fans also sought

contact with other fans - wanting to meet up with strangers with the same level of

identification.

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My friends and I are probably down to meet some other Vegas

Metalliheads. We should start an email list.

Slight adjustments to lifestyle (Beaven and Laws, 2007) were evident with discussion

pertaining to travel to, and attendance at multiple shows, as well as peculiar

activities such as allocating time to perform ‘practice’ ticket purchases for other

cities, so the fan knew what to expect when purchasing their own ticket in their local

city.

2.6.4 Dysfunctional Fan

Dysfunctional fans were the easiest to identify and the least represented in the

discussion forum (n=14; 12 %). Discussion attributed to dysfunctional fans

demonstrated major interferences with other aspects of life (Beaven and Laws,

2007). One fan indicated that they lined up 19 days before a concert date just so they

could be the first there.

Actually this message it's about the line to see metallica's

concert. This concert it's on march 7, and since yesterday (feb

17) we are making line… hope to see a lot of metallica's fans join

us in this unique adventure!!!

A number of dysfunctional fans revealed flying and driving vast distances to attend

concerts (one car trip calculated to be over 1,000 kms, others even travelled to

different countries).

… we are going to drive from Kaliningrad to Moscow for a

Metallicas consert [sic]. We will be driving through Belarus and

we can pick you up anywhere on the way from Lida to Minsk,

take your chance and do not be confused, there is always a way

to reach your goal!

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These fans changed travel plans on concert announcements, were willing to pick up

strangers (met on the discussion board) to accompany them on concert road trips

and indicated not being able to sleep due to excitement, up to eleven weeks before a

show. They sought to make physical contact with the band, investigating itineraries

and which motel the band would be staying at. Competitive and antagonistic

behaviour was also evident among these fans who sought to be experts (Beaven and

Laws, 2007). This was indicated through discussion with others who asked

questions, commented or made factual ‘Metallica’ mistakes.

well DUUUUUUUH of course the tickets were sold out

extremely fast, who did you thenk [sic] was coming??? F-----g

Talia or what?? It was metallica, of course you needed to get

them THE FIRST DAY.

2.7 Discussion

Analyses of posts on the Metallica discussion forum illustrate fan behaviours

consistent with the levels of rock fan typology proposed by Beaven and Laws (2007).

However, whilst Beaven and Laws (2007: 125) identified only ‘serious fans’ (loyal, die

hard, dysfunctional), this study has revealed a substantial number of casual fans

interacting in the online community. Jenkins (1988) suggests that a person becomes

a fan by sharing thoughts and feelings and joining a community of other fans who

share common interests. It therefore seems reasonable that the ‘causal’ fans in this

study are in fact fans, not just spectators or contributors to the discussion. This

supports the definition of fan adopted for this study; that a fan is an individual with

any degree of attachment or interest in a particular artist or band.

Throughout the discussion it is evident that causal fans not only have a different

purpose for interacting within an online fan community, but they also possess very

42 | P a g e

different motivations for attendance to a Metallica concert than fans categorized

with higher levels of identification. Motivations are seen as the fundamental reason

for behaviour (Mayo & Jarvis, 1981; Snepenger, 2006), and the realization that

different fan groups will attend particular events to fulfil different needs has

important implications for marketing strategy and in finding ways to increase

concert attendance. The literature notes that motivations will differ depending on

the type of event attended (Nicholson & Pearce, 2001), and with existing studies yet

to include a specific focus on popular music concerts, more research is warranted.

That is, the results of this study reveal the necessity to further investigate

motivations for attendance, in subsequent studies, if a thorough investigation on

what influences people to attend popular music concerts is to be conducted.

As discussed in the results of Study 1, discourse pertaining to casual fans indicated

that individuals categorized at this level possess very little attachment to the band

and instead are more interested in the overall concert experience. This finding may

suggest a high level of involvement with attending concerts as opposed to a high

level of identification with the artist conducting the show. That is, they are involved

with the ‘product’, with no attachment to the artist, indicating that it may also be

necessary to consider an individual’s level of product involvement and the effect that

it has on popular music concert attendance.

The behaviour categorised for diehard and dysfunctional fans provides evidence that

very little needs to be done in order to get these fans to attend a concert; they are

willing to pay any price and go to great lengths to follow the object of their affection.

In order to continue to increase attendance however, strategies for attracting the

casual and loyal fans need to be adopted. The results of this exploratory study

indicate that this increased attendance may be achieved by considering the

behaviours identified by casual fans, and creating events that appeal to the casual

consumer, such as outdoor concerts and festivals. Promotion of other activities that

43 | P a g e

create ‘fun’ and atmosphere that are associated with many festivals could also have

the potential to attract these fans.

It is evident in the online discussion that loyal fans who possess less dedication than

die hard and dysfunctional fans, only have the tendency to attend concerts whereby

the event is in the local vicinity. They also want to see other bands in the sub-genre

and express the desire to make a ‘weekend event’ when attending a concert. In order

to increase attendance of these fans to concerts, which may be further away, it is

suggested that these events be ‘packaged’ with other events or concerts by artists in

the same sub-genre. Recently there is evidence that artists combine with stronger

(more popular) support acts in order to increase attendance (Jones, 2011). Co-billing

artists so that consumers experience more than one band in a particular genre would

appear to be a strategy that would attract loyal fans required to travel further

distances to a particular concert event, and would also appear to provide more value

for money.

Overall, fans categorised as possessing higher levels of fan identification were willing

to pay more for tickets, attend multiple shows, and travel long distances in order to

attend a concert, including other cities and states, as well as other countries. From

the online discussion, it appears that these fans will take advantage of any

opportunity they get to see their favourite artist, and would be likely to attend

packaged events and festivals.

2.8 Limitations

Limitations of this study can be primarily attributed to the exploratory nature of the

sample. The examination of online fan behaviour involved only one fan group (i.e.

Metallica fans) and qualitative methods were used to analyse the discussion,

meaning that the classification of the discourse of fan behaviours into the four levels

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of the rock fan typology contain some element of subjectivity. In light of these

limitations it is necessary to:

1. Explore motivations for popular music concert attendance in more depth

through other methods so that a broader perspective can be gained; and

2. Adopt a quantitative approach to measure motivations for attendance and

levels of fan identification.

The categorisation of discourse into the fan categories in this study was quite

stringent as only the evidence available in the discourse could be relied on for

categorisation. Whilst the concept of fan identification may not be as concrete as

categorised and fans may indeed move fluidly between categories at different

periods of time, the results do provide information in reference to different fan

levels, and suggest that an individual could possess a different level of commitment

to an artist at any one time. Further exploration and quantitative research will

ensure a greater understanding of how fan identification actually affects concert

attendance.

It is also important to note that, despite the large amount of data, only a one month

period was examined for this study and therefore results do not reflect changes over

time. The data were also collected in a period of a new album release and whilst the

band was actively touring. The collection of data at this point in time may mean that

participants may be stimulated by situational factors, heightening their level of

interest and arousal, and in turn the categorisation of their discourse relating to

their level of identification (Richins and Bloch, 1986). Subsequent studies in this

thesis therefore attempt to eliminate this situational response.

The applicability of the results to offline identity has also not been explored;

meaning fans that choose to engage in online communities may hold different

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characteristics to those who do not participate in online discussion forums. This

aspect of fans was not able to be investigated within the current design.

2.9 Implications for Study 2 and Study 3

The categorisation of concert attendees into different fan levels in this study reveals

that consumers have very different reasons for attending concerts and it would

seem, different drivers for concert related behaviour. Motivations are “an internal

factor that arouses, directs, and integrates a person’s behaviour” (Murray, 1964, p.7)

and are therefore important in understanding the fundamental reasons as to why

consumers attend popular music concerts. Study 2 therefore explores motivations

for popular music concert attendance and attempts to identify how motivations for

popular music concert attendance differ to other types of events identified in the

literature. One of the limitations noted above was that the netnographic exploration

conducted in Study 1 was too narrowly focused and pertained to discourse posted on

the discussion forum of only one performer. Study 2 will examine motivations for

popular music attendance comprehensively and ask participants what motivates

them to attend popular music concerts without consignment to a specific artist or

band. Discussion of motivations for popular music concert attendance will identify

motivations for attending this type of event, which can then be added to existing

measures of motivation established in the literature (and used to test a structural

model in Study 3).

As the results of Study 1 also indicate that motivations for attendance may differ

between fans with different levels of identification this aspect should be explored

further in the next study. Prior research on motivations for attendance to other

events (e.g. sport) has found significant correlations between motivation for

attendance to events and fan identification (e.g. Fink et al., 2002). Motivations for

attendance to sporting events have also been shown to differ between fans with

different levels of identification (Gau et al., 2009). These outcomes can be explored

46 | P a g e

in a popular music context and therefore discussion related to motivations for

concert attendance at different fan identification levels will be explored. This

approach will not only allow a deeper understanding of the potential relationship

between fan identification and motivations for attendance to events in a popular

music context; but will also allow for the generation of hypotheses regarding these

two constructs, to be investigated in Study 3.

In Summary, Study 1 has established that it is possible that popular music ‘fans’ may

attend concerts irrespective of a personal attachment to the artist/band performing.

In particular, casual fans appeared to possess no significant connection to the

performer, but instead were seen to only pursue the pleasure and enjoyment of

concert related behaviour. For this reason, the concept of ‘product involvement’ in

popular music concerts needs to be explored in more detail. It is possible that

popular music fans could be involved in concert attendance because concerts are

important to them and/or because the artist performing the concert is important to

them. Findings from Study 1 also indicate that motivations for attending popular

music concerts, level of fan identification and product involvement may also

influence how far an individual may travel to a specific event. Literature regarding

fan identification studies in other areas have identified that highly identified fans

will attend more events and are willing to pay more for tickets, but little is known

about the impact of these variables on an individual’s willingness to travel to other

cities, states and/or countries to attend popular music concerts. Therefore

motivations for popular music concert attendance, fan identification and product

involvement has been hypothesized to influence willingness to travel as a result of

these findings. In light of this, ‘Willingness to travel’ will now be included as a

dependent variable in the quantitative study of this thesis (Study 3), and another

research question introduced:

What is the relative influence of motivations, fan identification and product

involvement on the distance consumers are willing to travel to concert events?

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CHAPTER 3

Study 2 - An Exploration of Consumer Motivations, Fan Identification and Product Involvement in

Concerts

3.1 Introduction

Chapter 2 outlined the method, procedures and results for the first study of this

thesis, which was a netnographic study conducted to explore fan behaviour with

reference to popular music concert attendance. The results of Study 1 highlight the

need for further exploration into popular music concert attendance, particularly

concerning motivations for attendance, as well as the concept of product

involvement. Chapter 3 examines the methods, procedures and results of the second

study of this thesis, in particular focus groups, which were conducted to explore

motivations, product involvement and fan identification in a popular music context.

The chapter will first provide justification for, and details regarding the

implementation of the focus groups. This will be followed by a discussion of the

results, and implications of the results for Study 3 will be presented.

3.2 Aim of Study 2

The aim of Study 2 is to explore the constructs of motivations, fan identification and

product involvement in a popular music context. The results of the netnographic

study conducted in Study 1 reveal a number of aspects of popular music concert

attendance that warrant further investigation. Firstly, results suggest that fans can

have very disparate motivations for attending popular music concerts. The

revelation that popular music concert attendees differ in their motivations to attend

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just one artist (Metallica) seem to suggest that many internal factors affect an

individual’s decision to attend popular music concerts. As mentioned in Chapter 1,

motivations that drive consumer decisions to attend specific events have been

identified for sporting events, performing arts, jazz festivals, tourism, food festivals

and festivals in general, where motivations have been demonstrated to differ

depending on the type of event attended. Existing studies on motivation however,

have yet to include a specific focus on popular music concerts.

Studies related to different types of events have revealed varied motivations for

attendance. Formica and Uysal (1996) identified five dimensions of motivations for

jazz festival attendance, including, excitement and thrills, socialization,

entertainment, event novelty and family togetherness. Crompton and McKay (1997)

acknowledged six categories of motivations for general festival events (food festivals,

music events, parades, balls and shows). The motivations consisted of cultural

exploration, novelty/regression, recover equilibrium, known group socialization,

external interaction/socialization, and gregariousness. A comparative analysis of

visitor motivations specific to four different events in New Zealand, (namely a food

festival, an air show, a wine, food, and music festival, and a competitive music

festival), also revealed that motivations will differ, depending on the event attended

(Nicholson and Pearce, 2001).The fact that motivations that drive attendance have

been shown to differ between not only disparate, but also similar events, suggests

that a closer examination of motivations for popular music is warranted.

Whilst there are no empirical studies on motivation for attendance at popular music

concerts, Earl (2001) used a subjective personal introspective method to identify

characteristics of live music performances that cannot be offered by recordings. This

research suggests a ‘line of inquiry’ that could be useful in explaining consumer

motivation for attending live music concerts. These characteristics included aspects

that economists would usually ignore such as identity enhancement, experiencing

concert specific music, the pure joy of live performances, sampling without 49 | P a g e

commitment, hero worship, opportunity for uninhibited forms of behaviour and

social interaction (Earl, 2001). Oakes (2010) also considered reasons as to why music

consumers would choose to attend live music performances as opposed to just

listening to CD recordings at home. These included the emotional arousal of

audience participation, the thrill of proximity to a celebrity, status enhancement,

stagecraft and, again, social interaction.

It is also possible that a consumer may possess more than one motivation for going

to see a live popular music concert. Iso-Ahola (1983; 1990), who has published

several works on motivation theory in reference to leisure, recreation and tourism,

proposed that motivations are not mutually exclusive, finding that it is not unlikely

for an individual to possess more than one motivation for attendance at a single

event.

Therefore the first aim of Study 2 is to explore motivations for popular music concert

attendance and in particular, if and how motivations for popular concert attendance

differ from motivations to other types of events. These insights will be beneficial for

gaining a true understanding of consumer behaviour in relation to concert

attendance, and will also help with the generation of hypotheses and identification

of questionnaire items (to be added to existing measures of motivation established

in the literature) for a follow up quantitative study (Study 3).

The results of Study 1 also show that motivations for attendance may differ between

fans with different levels of fan identification. As prior research has demonstrated

correlations between motivations for attendance and fan identification for other

events (Fink et al., 2002; Gau et al., 2009), the second aim of Study 2 is to explore the

potential relationship between motivations for attendance and fan identification, in

reference to popular music concerts, and again to assist with the generation of

hypotheses regarding these two constructs for Study 3.

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Finally, Study 1 showed that individuals attended Metallica concerts that appeared to

possess no significant connections to the actual performer, but instead they

attended for the pleasure and enjoyment of concert related behaviour. This finding

has important implications for studying consumer behaviour in reference to popular

music concert attendance as there may be a need to discern the product-related

involvement of concert attendance from artist-related involvement (Bloch and

Bruce, 1984). Whilst fan identification describes a person’s attachment towards

another person or group (Trail et al., 2000), ‘product involvement’ describes an

individual’s interest in or attachment to a particular product or service (Richins and

Bloch, 1986; Te’eni-Harari and Hornik, 2010). The third aim of Study 2 is therefore to

explore the potential relationship between motivations and product involvement.

The primary research questions for Study 2 are:

1. What motivates someone to attend a popular music concert?

2. Do motivations for popular music concerts attendance differ to motivations

for attendance to other types of events?

3. Do people with different levels of fan identification have different motivations

for attending popular music concerts?

4. Do people with different levels of product involvement have different

motivations for attending popular music concerts?

3.3 Research Design

In this study (Study 2), focus groups were employed to gain a deeper understanding

of the specific motivations for popular music concert attendance and how

motivations for attendance to popular music concerts may differ to other types of

events identified in the literature. In order to enrich the research questions and

hypotheses for this thesis, the focus groups will also seek to gain insight into the role

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product involvement and fan identification play in respect to one’s motivation for

attending a popular music concert.

3.3.1 Rationale for using Focus Groups

Qualitative research provides an in-depth understanding of consumers, where

qualitative research has been described as becoming “almost synonymous with the

focus group” (Calder, 1977, p. 353). Focus groups have many advantages compared to

other qualitative methodologies, such as observation and in-depth interviews. Focus

groups generate stimulation among participants which allows for wider idea

generation and a chain reaction of opinions and attitudes (Malhotra, 2010). Focus

groups are particularly useful when the culture of a specific group is of interest, and

when the degree of consensus on a given topic needs to be explored (Morgan &

Kreuger, 1993).

Focus groups are commonly applied in the “consumer arena” (Cooper & Schindler,

2014, p. 133), and can be used for any situation requiring preliminary insight and

understanding (Malhotra, 2006). Quantitative methods may be good for prediction

and looking at differences and relationships (Burns and Bush, 2010); however, the

research questions for Study 2 require further detail and explanation which focus

group data will provide. Findings from the focus groups will foster understanding in

relation to consumer perceptions, preferences and behaviour concerning popular

music concert attendance (Malhotra, 2006). Focus groups reveal consumer

motivations about products and services and are invaluable to help understand

results from quantitative studies (Burns and Bush, 2010). The information gained

from the focus groups will also be helpful in structuring the consumer online

questionnaire to be conducted in Study 3. It will not only aid in the identification of

variables to be included in the questionnaire, but also guide the generation of

hypotheses to be tested quantitatively (Fern, 1982). Further, focus groups are often

utilised in the first step of measurement scale development and will reveal items to

52 | P a g e

be used in a quantitative survey project (Fern, 1982; Cooper & Schindler, 2014). As

scales for motivations have not specifically been developed in relation to motivations

for popular music concert attendance, the focus groups will provide a means to

identify motivations that may need to be included in that scale, as well as specific

measurement items.

3.4 Method

Participants in the focus groups comprised undergraduate and postgraduate

Australian University students, as well as members of the general public ranging

from 18 years to 32 years. The respondents were sourced by distributing information

sheets to University of Newcastle lecturers and tutors (who were not the researcher

or other individuals associated with the project), who then handed the information

sheets out to their students during class (see Appendix A and Appendix B for

participant information sheet and consent form). Interested participants were asked

to contact the researcher to be involved in the focus groups. Some students handed

information onto other people they knew and therefore, members of the general

public were also represented in the research. Whilst the results of this study are not

intended to be generalised, a higher proportion 18-34 year olds attend popular music

concerts than any other age category in Australia. Results from a survey of

attendance at selected cultural venues and events in Australia conducted by the

Australian Bureau of Statistics indicate that 44.6% of 18-24 year olds and 40.2% of

25-34 year olds attend popular music concerts (ABS, 2010a). Therefore, the age

groups typically associated with higher rates of popular music concert attendance

were reflected in the focus groups.

In accordance with guidelines traditionally followed in the marketing research field,

focus groups were continued until the moderator could anticipate group responses

and no new material was being generated (Calder, 1977). This resulted in a total of

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four focus groups (n=31). Saturation of responses appeared to occur after only the

second focus group which is a little less than the typical three to four focus groups

usually required for the same topic (Malhotra, 2006). But as more participants were

initially recruited, another two focus groups went ahead just to be sure.

The focus groups comprised a one and a half hour discussion with the researcher as

the moderator. All focus groups were audio taped and written transcripts prepared

from the audio. The written transcripts formed the basis of a content analysis

conducted in NVivo. A copy of the moderator’s guide and focus group hand out can

be found in Appendix C and D, respectively.

3.5.1 Conducting the Focus Groups

Introduction and Establishing Rapport

Focus groups were conducted in a relaxed informal atmosphere, and participants

were seated at a round table in one of the university common rooms. Depending on

the time of day the focus group was conducted, all focus group participants were

greeted with food and refreshments on arrival. The sharing of food and refreshments

proved a successful informal icebreaker for respondents to introduce themselves to

each other and for the researcher to establish rapport through preliminary

conversation.

Focus groups began with a brief explanation of the purpose of the focus groups and

how the session was to run. The expected time duration of the discussion was

reiterated, confidentiality addressed and the participants were assured that there

were no right or wrong answers. Before proceeding, permission to audio tape the

discussion was sought and granted. The focus groups began with participants

formally introducing themselves and discussing an icebreaker question regarding

the best music concert they had ever attended.

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Popular Music and Popular Music Concerts

In order to ensure the group were approaching the topic of ‘popular’ music concerts

from the correct perspective (and not associated solely with the pop genre of music),

introductory questions were posed to the group to gain an overall reaction of their

interpretation of popular music concerts. This involved discussion relating to what

words came to mind when they think of popular music and popular music concerts.

General discussion involving reasons for attendance, which would lead onto more

specific questions regarding motivations for attendance, fan identification and

product involvement, were also discussed in this section. Before continuing, all

participants were provided a formal and informal definition of popular music and

popular music concerts to be used for the remainder of discussion. Popular music

was formally defined as any music that is commercially made, mass produced and is

popular with many people, embracing many musical genres including pop music,

rap, hip hop, R&B, punch and rock, to name a few (Shuker, 1998). Specific examples

were then given in a more informal definition of popular music concerts, where it

was explained that a popular music concert involves going to see any band/artist

who is popular among the masses (E.g. Pink, Metallica, Keith Urban, Elton John) at a

stadium, entertainment centre or similar.

Motivations for Popular Music Concert Attendance

In this section of the focus groups, participants were first provided with a definition

of motivations and were asked to give insight on what motivates them to attend a

popular music concert (unaided). Once the group could no longer retrieve

motivations from memory, they were then provided with a handout of motivations

that had been identified for varied events in the literature (aided) - see Appendix D.

Participants were asked to consider the motivations in front of them and discuss

their applicability to popular music concerts, and whether any category on the list of

identified motivations had ever driven them to attend a popular music concert.

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Product Involvement

Moving on from motivations for popular music concert attendance, participants

were asked to consider the concept of product involvement. A definition was

provided and the concept explained, with examples, by the moderator. Once the

group could express a clear understanding of the construct, participants were asked

to consider what their level of product involvement was, in line with what had

motivated them to attend a popular music concert in the past. This section

concluded with discussion pertaining to how individual behaviour may have differed

depending on one’s level of product involvement, that is, their interest or emotional

attachment to popular music concert attendance.

Fan Identification

Discussion concerning fan identification progressed in the same manner as

discussion related to product involvement. A definition was provided and contrasted

with that of product involvement until all participants could express a sufficient

level of understanding. Participants considered their motivations for attendance to

popular music concerts they had attended in the past, and discussion revolved

around how motivations may have differed depending on the level of fan

identification (attachment) the participants had with the respective artist, at the

time of attendance. This section concluded with discussion pertaining to how

individual behaviour may have differed depending on one’s level of fan

identification.

The Potential Relationship between Product Involvement and Fan Identification

In this part of the focus group, product involvement and fan identification were

considered simultaneously in order to gain a greater understanding of the possible

impact of the constructs on popular music concert attendance and to explore any

relationships or patterns that may be perceived between them. Participants were

then provided with a product involvement/fan identification matrix (see Appendix 56 | P a g e

D) and asked to consider each of the four options. That is, motivated them to attend

a concert where they possessed one of the following:

1) A low level of product involvement and a low level of fan identification;

2) A low level of product involvement and a high level of fan identification;

3) A high level of product involvement and a low level of fan identification;

and

4) A high level of product involvement and a high level of fan identification.

Closing

At the conclusion of the focus groups, when participants could no longer add further

information, the main points of the focus group were summarised by the moderator

and the group were offered an opportunity for any final comments. Participants were

thanked for their input, reassured about confidentiality, and given the opportunity

to obtain a copy of the research results.

3.5.2 Analysis of Focus Group Transcripts

Content analysis is deemed an appropriate method of analysis when the data

collected is communication (Malhotra, 2006), and is considered ‘the most widely

used formalised procedure by qualitative researchers in their efforts to create data

structures from focus group discussions” (Hair, Lucas and Miller, 2008, p. 127).

Analysis is typically performed by assigning labels or codes to the data based on

meaningful categorisation by the researcher (Malhotra, 2006). As a first pass,

analysis consisted of reading through each of the focus group transcripts and ‘open

coding’ groups of words and sentences into themes. Each code was stored as an

individual ‘node’ in NVivo for later retrieval. A form of ‘axial coding’ utilised in

grounded theory studies (Malhotra, 2006) was then used to help refine and organise

the themes and ideas resulting from the open coding. During this process, the

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context, frequency of comments and the specificity of responses to the constructs of

interest were considered (Hair et al., 2008). In NVivo, this comprised of creating a

number of tree node structures to organise groups of common ideas and themes.

Once categories were grouped and labelled, they could then be organised into

distinct frameworks relating to motivations, fan identification or product

involvement. These are now discussed in turn and the research questions for the

focus groups are considered for interpretation.

3.5 Results

3.6.1 Motivations for Popular Music Concert Attendance

In reference to motivations for attending popular music concerts, consistent

patterns emerged from the focus groups. Of the 16 motivations for attendance

considered in the focus groups (see Appendix D for full list), nine motivations were

considered as potential motivations for popular music concert attendance. These

included: Escape, Physical Skill of the Artist, Aesthetics, Hero Worship, Uninhibited

Behaviour, Social Interaction, Status Enhancement, Physical Attractiveness of the

Artist and Experience New and Concert Specific Music. In addition, Nostalgia was a

reoccurring motivation for concert attendance identified in the focus groups. A

nostalgic motivation could not be identified previously in the literature for

attendance to events. Vicarious Achievement, Acquisition of Knowledge and Family

motivations associated with sporting attendance (Fink, Trail and Anderson, 2002),

did not appear to be relevant to popular music concerts. Nor was the Joy of Live

Performances or Sampling without Commitment identified in the in Earl's (2001)

introspective study.

The motivations identified as common themes emerging from the focus groups led

to the development of Table 3.1 which summarises the key insights gained about

motivations for popular music concert attendance. Discussion relevant to each

motivation was used in conjunction with descriptions from the literature, to form

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the definitions for motivations for popular music concert attendance. Each of these

will now be discussed in detail.

Table 3.1: Motivations for Popular Music Concert Attendance

Motivation Definition Motivation Definition

Nostalgia To relive a period with happy personal associations, sentimental longing to relive the past, childhood memories. E.g. Roxette, Backstreet Boys, Aqua.

Escape Seeking distraction from everyday life and responsibilities. E.g. Work and kids.

Physical Skill of the Artist

The appreciation of the physical skill of the artist or the well-executed performance of the band.

Aesthetics The artistic admiration of the music and of the artists/bands technical skill. E.g. John Butler.

Hero Worship Being in close proximity to celebrities, form of support and demonstration of dedication to music of artist/band. Can involve touching the artist and crying.

Uninhibited Behaviour

Social behaviour that may be unaccepted in a normal setting such as drinking, moshing, dancing and going crazy.

Social Interaction

To interact and socialise with alike people, to feel part of a group with similar interests.

Physical Attractiveness of the Artist(s)

Watching concerts because of the physical attractiveness or ‘sex appeal’ of an individual artist/band member or band

Status Enhancement

Competitive behaviour, gaining 'bragging rights' and seeking to increase 'fan' status as a consequence of attendance. E.g. More concerts = Bigger fan.

Experience new and concert specific music

Hearing music that has not been released, where attendance is the only means of exposure. Hearing covers, acoustic sets etc. that can only be experienced at concerts.

Nostalgia

Many focus group participants expressed being motivated to attend a particular

concert because they “never would have got to see them as a child” and they were

59 | P a g e

“too young to go to concerts or buy tickets”. These concerts represented artists that

“were pretty cool back in the day” and motivated some respondents to attend just for

a “blast from the past kind of thing”, something that appeared “retro”, and for a

number of participants “took me back to my childhood”.

Attending artists for nostalgic reasons also seemed to counteract negative social

connotations for bands and artists that may not be perceived as “cool” today. Whilst

a number of focus group members expressed attendance at concerts as a means of

status enhancement and a way to increase fan status, a number of participants were

also wary that attendance at concerts by some artists may be seen to “deteriorate it”,

that is, they “might lose a bit a status” for attendance to artists they may have liked

when they were younger. Some bands that were mentioned primarily included pop

groups such as Backstreet Boys, New Kids on the Block, Aqua, Spice Girls and

Girlfriend. By labelling these groups as “pretty cool back in the day” and expressing a

primarily nostalgic motivation for attendance, participants were more comfortable

expressing their level of attachment to these artists.

Aesthetics and Physical Skill of the Artist(s)

A number of focus group participants expressed being motivated to attend concerts

just to admire the inherent beauty of the music, with one participant explaining,

“the idea of just listening to him play, just with an acoustic guitar, I play guitar

myself and I really like acoustic music”. The artistic appreciation for music in general

seemed to be closely linked with an appreciation for the physical skill of an artist or

the well-executed performance of a band. For some participants the motivation to

attend a concert was “very much about appreciating [his] abilities” and “purely for

the technical and the skill”.

Some participants expressed that “sometimes a more powerful performance is just

one person on a stage with like [sic] a guitar”. This opinion was primarily expressed

60 | P a g e

by fans in the focus group that were more motivated by aesthetics and the artistic

appreciation of artists with whom they had a high level of attachment.

Experience New and Concert Specific Music

Another motivation revealed in the discussion was attending concerts for an

opportunity to experience new music and music that can only be heard at concerts.

For some participants, new music referred to “actually seeing bands or music that I

haven’t actually been exposed to” and for others this meant “hearing songs from

their upcoming record that you haven’t heard yet”. For the majority, however, it was

primarily about the opportunity to hear music from a particular artist where

attendance to the concert is the only means of experiencing some aspect of the

artist’s performance. This included hearing music that had not yet been released or

recorded and other unique performances such as hearing ‘cover’ songs, instrumental

riffs, stripped down acoustic versions of songs and improvisations. To sum up, one

participant explained that their motivation for attending some artists was purely to

hear “stuff you can’t normally listen to on a CD”. From the discussion, it appears that

individuals with a high level of fan identification are the ones who seek unreleased

and rare, atypical versions of songs at concerts, where individuals with low levels of

fan identification for a particular artist attend concerts to experience a new artist for

the first time. One fan with a low level of identification, who also expressed having a

high level of interest in concert attendance, explained that they “often like to go to

concerts that are out of my comfort zone”.

Hero Worship

A number of focus group members conveyed that an important aspect and indeed a

motivation for attending some concerts was to provide support to the artist. Some

participants stated that they are a “big fan of going and supporting bands I like” and

that they would “very much go to an individual act to support an artist”.

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When prompted if participants mean ‘support’ to show appreciation for the band or

to support the band financially, respondents indicated that it was a combination of

both types of support that motivated them to attend concerts. Financial support was

particularly important for smaller Australian acts as compared with well-established

global bands. For example one participant said that they “don’t really think, oh yeah,

The Strokes are coming out, better support them, they don’t need money. But

smaller bands... yeah”. The ‘support’ however, also included acts that come from

overseas that may not have a huge following in Australia. Participants attended

concerts to “invest in the future” and “ensure they come back so that I can see them

again”.

Being in the physical proximity of an artist/band was also important to some

participants, with one participant saying they were “absolutely in love and just…and

being in the vicinity, I just want to be near you and my life will be complete”. For

some respondents the physical closeness of their hero was an emotional experience

“I cried for like the first three songs of the set but I didn’t like go and stalk him in the

car parking lot”. One participant classified their sister as possessing a very high level

of fan identification with Jon Bon Jovi. The sister had made travel plans at the last

minute to fly to New York just to see a Bon Jovi concert and the focus group

participant recalls her sister’s recollection of one particular concert where her sibling

reports “touching Jon’s boot”. The participant emulates her excitement, which they

describe to have “heard a million times! That she…touched…Jon’s…boot!”

Other participants agreed that getting in close vicinity to artists they were attached

to, was important to them, but there are varying degrees, with another participant

stating, “I would love to be at the front, but I’m not to the point where I would pass

out, or go to the airport or cry if they gave me a hug”. One of the associated benefits

of getting up close to artists at concerts was the opportunity to receive a ‘piece’ of

the artist. These pieces come in the form of “guitar picks and drum sticks and that

sort of stuff”, including “sweaty stuff that gets thrown out”. For those concert 62 | P a g e

attendees that possessed high levels of fan identification, these were just as

important as the physical proximity, as they would have something from the artist

they could cherish forever.

Social Interaction

A number of social motivations for attendance were revealed in the focus group

discussion. The majority of participants had attended concerts, at times, only for

“support”, because their partner or friends “had no one to go with”. Participants also

mentioned that at a majority of concerts, it was typical to meet up with friends. For

participants who had a high level of fan identification with a particular artist, social

interaction moved beyond a desire to spend time with friends. The attachment for

these fans motivated them to want to interact and socialize with other people with

the same interest as them, even people they did not know personally. At concerts,

those with higher levels of identification expressed the desire to feel “part of a group”

who “liked the same music” they did, with some even describing these events as

“community” like.

Status Enhancement

A common theme that emerged from the focus groups was that participants felt that

attendance at concerts set “a good sort of stage for I think particularly young men to

carve out an identity for themselves”. Respondents felt that concerts were an avenue

for young men (and some women) to “go parading around with their shirt off,

beating your chest…comparing tattoos”. This notion of status enhancement was

emphasised by the need for some participants to “check in’ and put their attendance

at a concert as their ‘status update’ on Facebook.

Part of this form of ‘sharing’ appeared to relate to a concept of ‘coolness’ for having

attended a particular concert. One participant expressed that they “went to Michael

Jackson, and I like the fact that I went to Michael Jackson, I feel there are bragging

63 | P a g e

rights to have gone to that” and they appeared to enjoy the fact that “not many

people can say that”.

Some participants felt that attending concerts was an important part of their status

as a fan and felt that they could not say that they were a fan of an artist if they had

not seen them live. One participant stated that his friends were always stating “You

haven’t seen them live?!” in relation to a band that he liked, and expressed “It was

like I wasn’t as big a fan as them; I had to be able to say guess what, I saw ‘em live”.

Even the number of ‘artist specific’ concerts attended seem to affect the ‘status’ of a

fan: “A friend of mine who I actually met at a concert, we’ve been friends since, he’s

like a really big fan of The Vines and I’ve seen them like five times and he’s seen

them probably 10, and whenever we go, you know someone will say this is the first

time I’ve seen them and I’ll be like I’ve seen them five times and he’s I’ve seen them

10. There is a really big element of you’re not as big of a fan until you’ve seen them

live and even if you have seen them live there is always going to be someone who

saw them the first time they were here or seen them more often”.

Escape

It appears that for a majority of motivations for attendance that fan identification

will play some form of role, but there are participants who very much were

motivated to attend concerts just “to get out, to get out of the house, just for

something to do”. Popular music concerts provide a chance for escape and the need

to find a diversion from work and the normal, unexciting activity of everyday life.

For some participants, attendance is a way “you can forget about that job you got to

go to or…whatever” and an avenue “to get away from the children”.

Participants agreed that “people want to see something different at concerts”. A

chance for entertainment, that is musical performance, “massive, crazy stage shows”,

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theatrics and stagecraft, including “crowds, jumping around and rocking out”, create

the perfect atmosphere for escaping “from the norm” and the “real world”.


A large number of participants conveyed that their sole motivation for attendance to

some concerts was at times just to “go a bit crazy”, with one participant venting

ecstatically, “I love it…Wooooooo!” The opportunity for uninhibited behaviour was

deemed an important aspect of the concert experience, where participants expressed

desires of drinking, dancing and “rocking out”.

Participants also discussed the non-spoken code of mosh pits and how being sweaty

is a part of the experience. One participant explained the ‘hair flick’, where people

get a friend to soak their hair with a bottle of water and they do the “whole head

flick action and it gets everyone! It’s part of the experience (laughs)”. Whilst these

forms of behaviour may seem daunting to some fans who are motivated purely by

the music and their attachment to an artist or band; ‘mosh pit’ like behaviour is

considered a compulsory part of the concert experience, particularly for those with a

high level of product involvement. This high level of product involvement (that is

the level of interest and emotional attachment to attending concerts) appeared to be

something that was created over time. One participant expressed that “the first time

I went into a mosh pit when I was 14 or something, it terrified me, I didn’t actually

understand what it would be, and getting thrown around I was terrified, but then

since it’s really fun, and I love doing it”.

Another behaviour that participants believe allow them to feel uninhibited at

concerts was in relation in what they choose to wear. One participant expressed that

she doesn’t “go around in midriff tops and shorts with my bum hanging out, but I

will be like Oh! I will wear that to a concert but that wouldn’t be appropriate to wear

like [sic] down the street”. Some participants also explained temporary changes to

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their personality and behaviour, with one participant relaying that “you toughen up

a little bit you are not the person you are when you go anywhere else, like I go to a

mosh pit and if someone pushes me I push back”.

Physical Attractiveness

Some participants expressed that they were purely motivated by the physical

attractiveness of an artist or band/band member. One participant stated that she

had “seen The Vines like six times cause Craig [the lead singer] is the hottest thing

ever!” Males even expressed going to see artists like Pink with their partners and

girlfriends, purely because “she’s hot!!” In fact, some male participants expressed this

would be the only reason they went to see an artist (with whom they had a very low

level of fan identification). For some participants however, artists would “have to be

extremelllllly hot” and they would have to be “like right up the very front” for them

to be motivated purely for physical reasons.

Push/Pull Factors

Beyond internal motivations for attendance, participants also brought up a number

of push/pull factors that affected their decision to attend a popular music concert.

One of these was the destination of the concert, not only in relation to the

geographical positioning of the concert, but also the actual venue the concert was to

take place in. For example, participants indicated that they would go to places like

Byron Bay and other places of natural beauty like in Victoria, Queensland and New

South Wales. In relation to destination, a number of participants would prefer to

travel to see a concert, as opposed to seeing an artist in their local city. One

participant expressed that they had “been to ones [concerts] 1000 km but not one

that is 3 km away”. In reference to the actual venue, a number of participants also

mentioned that they had been to concerts at the Opera House, “mostly just to go to

the Opera House”.

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Fans with a low level of identification with bands and artists they have seen, have

been ‘pulled’ towards attendance through “freebies” and promotions like “Buy one,

get one free”. A number of participants recalled a time when they had gained tickets

at a reduced price because a concert had not sold out. Whilst these participants had

not possessed a high enough level of fan identification to attend these concerts at

full price, their level of product involvement was high enough to warrant them

attending the concert at a discounted price.


Low Level of Fan Identification

Some fans in the focus groups with a low level of fan identification to a specific artist

described their reason for attending concerts as getting “dragged along with friends”.

Whilst most of these participants also enjoyed the entertainment and atmosphere

that concerts offered, they often have a very small level of attachment towards the

artist, to the point where some respondents went to concerts of bands they actually

disliked, with friends. One important thing to note, however, is that some

participants with a low level of fan identification that did attend a concert only

because their friends liked the artist, actually ended up enjoying the show and liking

the artist themselves. One participant explained that:

“I was just like oh my god I can’t believe I have to sit through this, but

they put on like such a good show and were so revved up… I went in I

hate this band and I can’t believe I’m here and yeah to someone who

like [sic] I really appreciated what they do because they put so much

into their live shows”.

Some participants had been to concerts of artists, never having heard of them prior

to attendance, and now have “absolutely been following them ever since”. This

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finding suggests that just getting people to a concert can have a big impact on the

level of identification a person ultimately has with an artist/band. Finding ways to

increase attendance to artists/bands, particularly attracting those with low levels of

fan identification, therefore may have important implications for future loyalty.

Fans with lower levels of identification differed to fans with higher levels of

identification in their need for the artist to talk and tell stories during a

performance. One participant explained their experience of seeing a band talk too

much, “they just kept talking and talking too much, and I was like oh god, when is

this going to end…It was like they were telling stories and not really singing and

kinda playing guitar and kinda not playing guitar, we were like sing a song!”. Fans

with higher levels of identification actually found this essential to their enjoyment of

a show with some even expressing it is like “we are friends!” and they get to meet the

person “through their performance”.

Some other reasons for consumers to attend popular music concerts, when they have

a low level of identification with the artist, were revealed in the focus groups. These

included social interaction and “the escape idea, just for a night out”. Some

participants had also felt the need to attend past concerts, to artists with whom they

have a low level of attachment, just to “fit in with a group” and not be the only

person not to go and see them.

In relation to behaviours fans with low levels of identification expressed, spending

time at the bar and the beer garden during concerts, were evident. Respondents who

expressed having a low level of identification at a particular concert also expressed

feeling a type of antagonistic behaviour from other fans with higher levels of

identification. One respondent explained that they had gone to see a band because

they liked a couple of their songs on the radio, but didn’t know all the lyrics to the

songs. This participant wasn’t “singing along” and they explained that “there was a

guy that knows every single lyric to all the songs and he would look at me and I

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wouldn’t be singing along and he would look at me to say like I am not even a fan,

you don’t know the words like I do!”

A majority of the low identification focus group respondents had attended concerts,

not for the headlining act, but instead to see the support act. The implication of this

behaviour was that, a number of participants, who had a low level of attachment to

the headlining act, actually left the concert with a more favourable attitude to that

headlining act. Some participants also began ‘following’ the headlining acts of these

concerts they attended.

In summary, those participants who self-identified as having attended a concert with

a low level of identification with the artist appeared to mainly attend for escape and

social interaction. Fans with low levels of identification would attend concerts to fit

in with their friends, but were likely to spend a lot of their time socialising as

opposed to being engrossed in the concert. It would appear; however, that

attendance to concerts for escape and social reasons could have a potentially positive

impact on level of identification. That is, for some fans, an increase in fan

identification resulted, as a consequence of attendance.

High Level of Fan Identification

Participants acknowledging that they had high levels of fan identification to a

particular concert indicated that the aesthetics of a concert performance motivated

them to attend concerts. Aesthetics refers to the appreciation of the natural beauty

and nature of music. One respondent stated that “I love their music, and love what

they do and I’m there to appreciate it and wanting to hear it live”. Although the

aesthetics of the performance were very important for some highly identified fans,

especially in relation to the “technical and the skill”, other highly identified fans

were more tolerant to live technical skill and it didn’t matter if their artist/band

didn’t deliver a pitch perfect or aesthetically pleasing performance. One example

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that came up was the Whitney Houston concert, where participants who attended

this concert who were highly identified with Whitney, displayed unwavering

commitment “even though she couldn’t sing, I was just happy to see her in concert”.

This was also particularly true for a lot of highly identified fans who expressed seeing

nostalgic bands like Aqua. Even though fans were told that the band lip synced their

performance, one fan stated “I was just like I don’t care! With a lot of pop acts there

is that level of identification with them that you know all this, and you know that

they will be miming, and you know that you know it won’t really be them

performing as much in the respect that other artists would, but you don’t care”. This

unwavering commitment however, seemed to be related to the genre of artist, as

other participants, highly identified with more alternative bands would be outraged

if their favourite artist came on stage and mimed. This seemed to be group

consensus that it depended on the nature of the music that you identified with,

“with pop concerts it’s not just about the song, it’s about the dancing, the production

and all the entertainment, like Brittany Spears, and she’s got all the dancing and

stuff, and coming down from the roof, and you know there is no way someone could

sing and do that at the same time”.

In relation to behaviours, highly identified fans would never leave their position, not

even to go to the toilet, “like how can you not go to the toilet for 2 hours?!” This

didn’t mean that highly identified fans were always in the thick of the crowd and the

mosh pit, “not running around and stuff cause that would be detracting from the

experience”, but instead were more immersed in watching the performance just

“standing and listening” or “deliberately getting seats so we can soak it all up”. One

participant expressed being at a concert for an artist they loved and not going “in the

mosh pit and didn’t go in the circle pit and just basically for the most of the concert

stood with my arms crossed without even moving. It might appear that I didn’t really

want to be there, but when the set finished these guys walked past me and I heard

one of them say that, that guy must have really liked that concert, and that was

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interesting because I thought people would get this idea that I wasn’t, I just really

wanted to appreciate the show”.

Whilst some highly identified fans will seek to be at the front of the crowd and be

pushed up against the stage bars, others are willing to pay much extra for seated

tickets, but in both cases these fans emphasise their absorption in the show. Whilst

fans without such a high degree of fan identification might spend concert time

bragging to friends and taking photos, these fans will not even “take 5 minutes out to

update my [Facebook] status”. In relation to money, fans with a high level of fan

identification for a particular artist explain that they “spend a bit more money to go

and see like [sic] my favourite band”. They would also pay more money to have

“front row [tickets], or those extra bits and pieces like meet and greets” and going

backstage. Some fans who had a high level of identification have even tried to go

backstage without backstage passes, or wait around after the show trying to get a

glimpse of the artist, or for a chance to get something signed whilst the band/artist

evacuates the venue.

Fans with a high level of identification felt “cheated at a concert if you go there and

they don’t talk”. They attend concerts to ‘get to know’ the performer on another level

and don’t expect to hear artists “sound exactly the same as they do on recording”.

For highly identified fans who don’t get to personally meet an artist or band

member, they feel a desire in “meeting this person through their performance”. A

common theme amongst participants with a high level of involvement for a

particular artist was the yearning to attend more intimate shows, such as festival

“side shows” that are typically dedicated to more highly attached fans, with tickets to

these shows sometimes exclusively promoted to fan club members.

Whilst fans with low levels of identification expressed spending time at the bar and

in the beer garden with friends, most participants who expressed high levels of

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identification for a particular band strongly believed in not consuming alcohol at

concerts as they don’t want to “miss anything”.

Fans with higher levels of fan identification expressed the need to show affiliation

with their favourite artists by ‘liking’ them on Facebook. The primary reasons for this

behaviour were jointly related to receiving notifications related to the band/artist

such as touring information, as well as “to keep track of what they are doing” and “to

show people that you like them and if you have friends in common, you know they

like the band as well so if you want to see a concert you can ask them”. This

reiterates the social structures of fan identification, where fan identification very

much comprises elements of both social and personal identity. Whilst it is important

for fans to express an individual connection with an object, connection with others

identifying with the same object is just as important.

3.6.3 Product Involvement

Low Product Involvement

Some participants who stated that they didn’t really like going to concerts (that is,

they possessed a low level of product involvement in relation to popular music

concert attendance) said the only reason they would attend is if they had a high level

of fan identification, “if I really liked the band”, or if they were “dragged along by

friends, and you know it’s probably that thing of, if all my friends are going, what am

I gonna do on that day… I would just go with them”.

Those with self-acknowledged low levels of product involvement also said that when

they had happened to go to a concert with friends (one of which they neither had a

high level of product involvement nor a high level of fan identification) would spend

time in the beer garden and seek other things to do at the concert. One participant

stated, “If I thought I’ve got nothing else to do, my friends going, I’d go and then just

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look at what I can do while it’s happening, even though I had no interest in the

band”. This would suggest that in order to attract people with low levels of product

involvement, and those that also have low levels of fan identification, that

alternative activities at the concert may be a way to attract these fans. For example,

one participant expressed going to a Metallica concert with friends, but they didn’t

really like concerts or Metallica. “Guitar Hero” was sponsoring the concert and there

was a Guitar Hero competition while the concert was on, and they spent most of

their time at that.

A chance for escape and the need to find a diversion from work and the normal,

unexciting activity of everyday life was also another reason participants with a low

level of product involvement would be motivated to attend a concert. The concert

however, would have to have some form of unique entertainment value, for example,

a high level of stagecraft, a “once in a lifetime opportunity” such as seeing a band

that had been broken up, or if the band had a lot of history associated with them,

such as The Rolling Stones.

High Level of Product Involvement

Focus group participants who self-identified as having a high level of product

involvement, that is, they possess a high level of interest, arousal, or emotional

attachment with attending popular music concerts (Rothschild, 1984; Bloch, 1986),

explained that they sometimes are motivated to attend concerts just to engage in

behaviour that is normally prohibited in a normal social setting. They have attended

concerts where they “don’t care so much about the music”. They attend to be

“around like people” and engage in concert related behaviour such as drinking, being

loud, dancing, moshing and crowd surfing, where for just that moment in time, their

behaviour is socially accepted. That is, people expect that type of behaviour at

concerts, but the behaviour would not be tolerated in any other part of their lives.

One participant stated, “When I went to Metallica, who I hate, I enjoyed it, we were

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up dancing, but I wasn’t there for the band, I was there because the concert was

going to be fun”. Further, when the discussion of alcohol consumption was raised (as

it pertained to behaviour that may not be so accepted in other aspects of normal

life), the same participant than also added “alcohol enhances the enjoyment of a

concert considerably, because I dance more and it lowers my inhibitions”. In this

particular focus group there also happened to be fans with a higher level of fan

identification with Metallica than this participant, who questioned why this

participant wouldn’t just “buy a live CD and listen to it at home and sit there and

drink, it would cost you a lot less”. Discussion that followed revealed that consuming

alcohol was only part of the process of “inhibition lowering” and the atmosphere and

entertainment and the ability to “go crazy” and “let loose” were the main aim.

3.6.4 Potential Relationships between Product Involvement and Fan

Identification

Low Product Involvement and Low Fan Identification

Participants in the focus groups (who possessed a low level of both fan identification

and product involvement at a particular concert), attended concerts for “the

Facebook status kind of thing”. These individuals were lured by the atmosphere,

status and social aspect of the event and were often dragged to concerts by friends.

Participants agreed that social media was having a big influence on their decisions to

attend particular concerts and events (to increase social status and conform to group

activities), and they admitted using Facebook ‘check in’, Twitter and Instagram in

order to be ‘tagged’ and ‘followed’. Respondents discussed how there is a “bigger

sense of community” to big events that now incorporate and encourage ‘promotion’

of events. For example one respondent explained that for one concert they attended

there was an image that could be downloaded from the artist’s website prior to going

to the concert, so you could check in with the photo and tag everyone who attended.

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Beyond this social aspect, respondents also feel that extra activities at concerts need

to be introduced and promoted, more like festivals. The groups came to a consensus

that promoters “need to get these people in with some type of novelty” for example

“like a foam party or like at Metallica how they had the guitar hero competition and

the green slime V Tent”.

High Product Involvement and High Fan Identification

Participants who self-nominated as having a high level of involvement in relation to

concert attendance and a high level of fan identification at a particular concert,

identified that in relation to behaviours they were the people that needed to buy

their tickets first, buy multiple items of merchandise and also engage in behaviour

such as following the artist on Twitter and Facebook. It would appear that in terms

of marketing, little needs to be done to promote concerts to fans possessing both a

high level of product involvement and a high level of fan identification, “we are

going anyway” expressed one participant.

Low Product Involvement and High Fan Identification

Those that didn’t have a high level of product involvement, that is, they did not

really enjoy attending concerts to engage in concert related behaviour, said they felt

rather uncomfortable at concerts, but couldn’t miss the opportunity to see their

favourite artist or band. One participant expressed that “I may really like a band or

an artist but I don’t really like the environment of concerts”. Participants who had

this level of fan identification and product involvement said that they would prefer

seeing their favourite band in an intimate setting “instead of just playing stadiums”.

What makes these people attend concerts however is the fact that artists/bands will

play songs from their upcoming records, songs that you cannot hear without

attending the concert. They also emphasised that they enjoy “aspects of the band

that you don’t normally get to interact with, like them talking between songs, or

being asked to go on stage”. Lower scale concerts, at smaller and more intimate

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venues appear to be the ideal setting for this group of consumers. Seated only

concerts, would also offer this fan group a more relaxed concert experience.

High Product Involvement and Low Fan Identification

Some participants expressed that they absolutely love going to concerts to bands

that they don’t have any real attachment to. It gives them a chance to be “a bit more

loose-ish, just go for the experience and alcohol”. Others expressed that they attend

for aesthetic reasons, for “the pure love for music”. During group discussion it also

became apparent that getting people to attend concerts can be a great avenue for

increasing artist/band likeability and loyalty. One participant expressed that their

“experience of seeing someone live and seeing how they do a live performance, it

actually makes you want to follow them more or like them more”. In terms of

marketing to this group of consumers it appears the presence of alcohol (therefore

18+ concerts), and the creation of an experience not to be missed would be essential

for this group of consumers. Little emphasis would need to be placed on the artist

themselves, whilst entertainment, side activities, stagecraft and the opportunity to

have a real concert like experience should be prominent.

Proposed Relationship between Fan Identification and Product Involvement

Based on the discussion it appears that an overall relationship between fan

identification and product involvement may exist. A person with a higher level of fan

identification may be perceived to have a higher level of product involvement in

reference to the concert product, but this indeed would not be true for every

individual. Whilst fans with very low levels of fan identification can have a very high

level of product involvement, that is “there are people who just like going to concerts

and just buy tickets to anything ‘cause they like to go to concert's”, fans with high

levels of fan identification may not necessarily have the highest level of emotional

attachment to the concert, but in fact are driven to attend by other motivational

factors related to the close attachment they hold with the artist or band.

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Whilst there were instances where focus group members had attended concerts to

bands they “hate” or have a low level of fan identification for, the findings suggest

that fan identification may play a more substantial role in relation to concert

attendance than product involvement. The groups revealed that fans with a low level

of fan identification, with little attachment to the artist/band and other fans would

be motivated to attend a popular music concerts for social interaction, status

enhancement, and as an escape, a night out away from work and/or kids. These fans

would be walking around, socialising, getting drunk and would not be engaged in

the actual performance (and possibly have a high level of product involvement).

Those on the other end of the scale would attend for aesthetics, hero worship and to

get physically close to the object of their fanaticism. These fans would possess an

unwavering commitment to the artist “even if the singing was bad, like at the Whitney

Houston concert”; they would be fully immersed and would not drink alcohol as to

not “miss anything”.

Fans with a low level of product involvement, who don’t really have a strong interest

in concert attendance, will attend concerts if they are lured by friends, or if the event

is unique in some way and is expected to involve elements of stagecraft that are

perceived as ‘not to be missed’. With the right combination of intrigue, consumers

with a low level of product involvement will still seek a means of escape from

everyday life and potentially attend a popular music concert. Fans with high levels of

fan identification, which also possess a low level of product involvement, however,

may feel the need to attend a concert (even though they may not like it) as a way to

increase their status as a fan.

3.6.5 Summary of Motivations across Fan Identification and Product

Involvement

Table 3.2 provides a summary of motivations for popular music concert attendance,

highlighting the different motivations for concert attendees with different levels of

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product involvement and fan identification. Fans possessing a low level of product

involvement will be motivated to attend popular music concerts when their friends

are attending, but will be more interested in socializing and spending time with

friends around the bar. For them, attendance would be a means of escape and

elements of excitement and stagecraft associated with the concert will need to be

present for attendance from this group of consumers.

Individuals with low levels of product involvement will also attend concerts if they

correspondingly possess a moderate to high level of fan identification. When an

individual has some form of an attachment to an artist they may also be motivated

to attend a popular music concert, even though their interest in concert attendance

in general is quite low. Fans with a high level of fan identification will attend a

concert to experience concert specific music. Despite the fan having a low interest in

concert attendance alone, a highly identified fan will want to experience all aspects

of the artist, including new songs that will be performed at concert that are not

released, and other types of performance such as acoustic versions of songs and

improvisations. Where the artist (to whom the fan possesses a high level of

identification) also has some form of nostalgic response for the fan, this may also

motivate them to attend.

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Table 3.2: Summary of motivations across types and levels of involvement

Product Involvement Fan Identification

Low High Low High

Personal Nostalgia X* X* X

Social Interaction

Friends X X X X**

Other Fans X X

Status Enhancement X* X* X

Escape X X

Aesthetics X X X

Physical Skill of Artist X* X X

Uninhibited Behaviour X X** X**

Physical Attractiveness of Artist X* X

Hero Worship X* X* X

Experience New and Concert Specific Music

New X X**

Concert Specific X* X X

Shading = Motivation explicitly identified for this group * May be present when individual also possesses a high level of fan identification **May be present when individual also possesses a high level of product involvement

As highly identified fans also want to maintain their high fan status, attendance at a

concert may be a form of status enhancement, and therefore even a highly identified

fan who has no interest in concert attendance in general, will attend a concert for

the artist of their affection in order to increase this status. Missing an opportunity

for hero worship and witnessing the physical skill of the artist may also motivate

fans with a low level of product involvement (but a high level of fan identification)

to attend a popular music concert.

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Consumers with a high level of product involvement enjoy all aspects of the concert

experience, irrespective of the artist performing the concert. They enjoy the social

interaction to be had with friends and other fans and the entertainment and

atmosphere. Individuals with a high level of product involvement have an artistic

appreciation of music in general, and value an artist’s physical skill. They will be

motivated to attend concerts just to experience new music and enjoy the elements of

the concert music that can only be experienced at concerts such as acoustic sets,

covers and extended guitar riffs. The dominant motivation for attendance for

individuals possessing a high level of product involvement is uninhibited behaviour.

They enjoy the opportunity to act outside the norm, and to dance, drink, mosh,

crowd surf and go a little bit crazy. Personal nostalgia, status enhancement, physical

attractiveness of the artist and hero worship will also be motivations for fans

possessing both a high level of fan identification and a high level of product

involvement.

Individuals having a low level of fan identification will have little attachment to the

artist performing the concert and therefore will be motivated to attend for escape

opportunity and the chance to spend time with friends. Fans with a low level of

identification who have an artistic appreciation for music, and may be musicians

themselves may also attend a concert for the inherent beauty of the music.

Individuals who have a low level of fan identification, but possess a high level of

product involvement (i.e. concert attendance is important to them), will be

motivated to attend concerts for the chance to engage in uninhibited forms of

behaviour and to experience new music.

Fans with a high level of identification will be motivated to attend popular music

concerts for a number of reasons that are associated with the artist and their status

as a fan. Personal nostalgia, interacting with other fans, status enhancement,

aesthetics, physical skill of the artist, physical attractiveness of the artist and

experience concert specific music for that artist will be important to a highly 80 | P a g e

identified fan. A highly identified fan that also possesses a high level of product

involvement will also welcome the opportunity to involve friends, and may also have

a combined motivation to engage in uninhibited behaviour. A highly identified fan

however will not solely be motivated to attend for escape or to experience new music

(as the attachment to the artist is driving their motivation for attendance).

3.6 Discussion

As shown in Table 3.1, the focus groups revealed 10 primary motivations for concert

attendance. The data show that motivation for popular music concert attendance is

indeed a multifaceted construct, comprising of Hero Worship, Aesthetics, Nostalgia,

Social Interaction, Uninhibited Behaviour, Physical Attractiveness, Escape, Status

Enhancement, Physical Skills, New and Concert Specific Music (as well as pull

factors associated with destination and venue). Of these motivations, the research

also pinpointed four motivations unique to popular music concert attendance that

have yet to be highlighted as significant motivations for other types of events in the

literature. These include personal nostalgia, uninhibited behaviour, status

enhancement, and to experience new and concert specific music.

Whilst previous research for similar events have identified the motivations of

aesthetics (in sport, for example Fink, Trail and Anderson, 2002), social interaction

(sport, jazz, performing arts, Fink, Trail and Anderson, 2002; Formica and Uysal,

1996; and Swanson et. al., 2008 respectively), escape (sport and performing arts,

Fink, Trail and Anderson, 2002 and Swanson et. al., 2008), this research facilitated

the development of more appropriate context-specific definitions (presented in

Table 3.1). This study also observed that uninhibited behaviour was a particularly

important motivation for popular music concert attendance, thereby reinforcing and

extending Earl's (2001) introspective assumptions.

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The focus groups revealed some unique findings in relation to popular music concert

attendance. One of the most common motivation responses was ‘personal nostalgia’,

where participants across all groups expressed a desire to relive old memories of

music that gave them a “blast from the past” and took them back to their childhood.

Participants had many happy associations with artists made famous in the past, and

expressed a level of personal nostalgia and reliving the happy personal associations

they have with these artists as a motivation for attending recent popular music

concerts.

A reoccurring theme evident across all focus groups was the notion of status

enhancement. Participants discussed a type of competitive behaviour that would

motivate some fans to attend a particular concert in order to increase their ‘status’ as

a fan. This was deemed to derive from the belief that “you are a bigger fan if you can

say that you have attended more concerts”. Part of this motivation also centred

around the concept of being able to “look cool” and put that you are at a concert as

your ‘status update’ on Facebook. The final motivation specific to popular music

concert attendance identified in the focus groups was the opportunity to experience

new music, and music that can only be encountered at a concert. This included

music that had not yet been released, hearing the artist play covers of another artist,

play songs acoustically or in general hear “stuff that you can’t normally listen to on a

CD”. The motivation related to uninhibited behaviour also appeared to be popular

for participants who had little attachment to the artist for the concert they were

attending. For those that truly loved attending popular music concerts, there was

nothing more important than being able to get lost in the music by drinking,

dancing and moshing with the masses.

Another dominant theme arising from discussion (although not technically classed

as a motivation) was the opportunity to visit a venue or destination that one would

not normally visit. Destination in this sense acts as a ‘pull factor’, where participants

indicated that venue and destination of a popular music concert could either

motivate or demotivate them from wanting to attend, and for some participants, 82 | P a g e

destination or venue highly influenced whether they would choose to attend a

concert or not. Discussion revealed that people “like a chance to get out of the norm”

and that holding a concert at a particularly interesting venue like the Opera House,

or at an exciting destination like Byron Bay would be a significant driver of

attendance for some people.

Findings from the focus group also offer practical implications. The emergence of

motivations for attendance such as nostalgia, uninhibited behaviour, stagecraft,

escape, venue and destination suggest that it is possible that popular music concert

organisers may be able to employ different marketing tactics to broaden the appeal

of specific concerts, beyond the promotion of genre and artist. It is important to

note however that each motivation may not be mutually exclusive, and it is possible

that concert attendance reflects a combination of motivations. Bowen and Daniels

(2005), in their study on motivations to music festival attendance used cluster

analysis to identify four distinct groups of visitors attending music festivals,

demonstrating that it is indeed possible to go beyond a reliance on music itself or a

specific artist to attract audiences. Results of this study show, this may also apply for

popular music concerts, where there is an absence of other activities, diversions and

non-musical attractions that are typically associated with music festivals (Bowen and

Daniels, 2005). Building on the data in Table 3.2, Table 3.3 organises fan

identification and product involvement in a matrix, and motivations for concert

attendance are shown for each of the four possible groups.

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Table 3.3: Product Involvement and Fan Identification Matrix

Low Fan Identification High Fan Identification

Low Product Involvement

Nostalgia

Social Interaction (Friends) Status Enhancement Escape Experience Concert Specific Music

Physical Skill of Artist

Hero Worship

Social Interaction (Other fans)

Low Fan Identification High Fan Identification

High Product Involvement

Nostalgia

Social Interaction (Friends) Social Interaction (Other fans) Aesthetics Aesthetics

Uninhibited Behaviour Experience Concert Specific Music Experience 'New' Music Status Enhancement

Physical Skill of artist

Physical Attractiveness of artist

3.7 Limitations

The limitations of this study can primarily be attributed to the qualitative nature of

the data. Whilst qualitative research methods often reveal rich findings, they need to

be treated as exploratory, as due to small samples, they may not be reflective of the

entire population. The motivations identified may be sample specific and only

tentative conclusions can be drawn from this single study. The results are also

limited to a specific age demographic, restricted to people aged between 18 and 32

years. It is possible that consumers in older age groups may have different

motivations for attending popular music concerts and have different forms and

levels of product involvement and fan identification. In reference to the sample size,

focus groups were continued until the moderator did not identify new insights, in

accordance with guidelines traditionally followed in the marketing research field

(Calder, 1977). Saturation of responses started to occur after only the second focus

group.

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There is also a possibility that interpretations of findings are susceptible to

researcher bias (Cox et al, 1976). The researcher acted as the moderator of the focus

groups, and the quality of the results may depend heavily on the moderator’s ability

to guide discussion. Secondly, the unstructured nature of the data and subjective

style of analysis also means that interpretations of the focus group data may be

subject to biases. The researcher may have unintentionally selected and interpreted

findings to support a particular type of view (Malhotra, 2006). Therefore whilst these

findings generate understanding and provide meaning within their own limitations,

a follow-up quantitative study is required in order to generalise findings in relation

to the constructs explored in the focus groups.

3.8 Implications for Study 3

The major insights gained through this research suggest a theoretical basis of

motivations for popular music concert attendance, which can serve as a framework

for further empirical research in this area. The next study of this project will test the

proposed theoretical base and the relationships between motivations, fan

identification, product involvement and concert attendance. Further, the results of

this exploratory study facilitate development of a standard instrument to measure

consumer’s motivations for attending popular music concerts. They also aid in the

identification of questionnaire items for the proceeding study, and in hypothesis

development. In addition, the results provide a data source which can be used as a

reference when and interpreting and the quantitative results. More detail on how

the results of the focus groups are specifically applied to guide Study 3 is discussed in

the next chapter.

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CHAPTER 4

Study 3 - Testing Relationships between Fan

Identification, Product Involvement and

Motivations

4.1 Introduction

Chapter 3 outlined the method, procedures and results for the second study of this

project, which involved focus groups conducted to explore the constructs of fan

identification, product involvement and motivations for popular music concert

attendance. The results of Study 2 have been used to guide the development of a

questionnaire to measure these constructs in a follow-up quantitative study, so that

the relationships between fan identification, product involvement, motivations and

concert attendance can be examined, and their influence on concert attendee

behaviour tested. Chapter 4 will introduce the hypotheses to be tested and examines

the methods, procedures and results of the online questionnaire. First, a description

of the chosen design is provided, followed by questionnaire construction which

includes the development of measures and procedures for data collection. The

chapter will conclude with results and discussion.

4.2 Aim of Study 3

The aim of Study 3 is to empirically test the influence of fan identification, product

involvement and motivations for popular music concert attendance on concert

attendee behaviour, that is, average number of popular music concerts attended per

year, number of popular music concerts for a particular artist, the amount

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consumers are willing to pay for popular music concert tickets, and willingness to

travel to popular music concerts.

The primary research questions for Study 3 are:

1. What is the influence of fan identification on product involvement?

2. What is the relationship between fan identification and motivations for

popular music concert attendance?

3. What is the relationship between product involvement and motivations for

popular music concert attendance?

4. What is the impact of fan identification, product involvement and

motivations for popular music concert attendance on concert attendee

behaviour, specifically;

(a) Number of popular music concerts attended per year, on average;

(b) Number of popular music concerts attended for a specific artist;

(c) Amount willing to pay for popular music concert tickets; and

(d) Distance willing to travel to popular music concerts.

4.2.1 Development of Hypotheses

Hypotheses were developed, in combination with the literature, from the findings of

Study 1 and Study 2 of this project. The next section discusses the derivation of each

of the hypotheses for this study. For organisational and clarity purposes, hypotheses

are organised relative to fan identification, product involvement and motivations,

therefore hypothesis numbering is not necessarily in order. A conceptual model

displaying the hypothesised relationships is illustrated in Figure 4.1 (see p. 94).

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Hypotheses related to Fan Identification

Fan identification is defined in this project as a personal connection with the artist

or band (adapted from Reysen and Branscombe, 2010) and was contrasted with

product involvement, defined as an individual’s interest in or attachment to a

particular product or service developed from Richins and Bloch (1986) and Te’eni-

Harari and Hornik (2010). As discussed in Chapter 1, an individual could be involved

in concert attendance because concerts are important to them, or the artist

performing the concert is important to them. It would follow then, that an

individual possessing a high level of attachment to a particular artist (fan

identification), may find concerts more interesting or be more interested in concert

attendance (product involvement), as concert attendance would provide a means for

the individual to connect with the artist. This was also supported by the focus group

findings in Study 2. It is therefore hypothesized that:

H8: Fan identification is positively related to product involvement

The sporting literature acknowledges that highly identified fans have been found to

attend more events, pay more for tickets, buy sponsors' products and purchase more

licensed merchandise, whilst less identified fans are seen as the cause of attendance

fluctuations (Fink et al, 2002; 2009). Highly identified fans, therefore, exhibit greater

loyalty, more price tolerance and less performance sensitivity, than less identified

fans (Gwinner & Swanson, 2003). Consistent with findings related to sporting

attendance, results from Study 1 reveal that fans categorised as having higher levels

of fan identification were willing to pay more for concert tickets, and attend multiple

shows, which also included multiple shows for the same artist. Given this, three

hypotheses emerge:

H5a: Fan identification is positively related to average number of

popular music concerts per year

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H5b: Fan identification is positively related to number of

popular music concerts for a specific artistic

H6: Fan identification is positively related to amount willing to pay

Another finding from Study 1, related to fan identification, was that individuals with

higher levels of fan identification were willing to travel much further distances to

concerts for artists with whom they possess a close attachment. Therefore the

following hypothesis also emerges:

H7: Fan identification is positively related to willingness to travel

Fan identification is a strong predictor of fan consumption behaviour (Fink et al.,

2002; Madrigal, 1995; Wakefield, 1995; Wann & Branscombe, 1993) and various

researchers have proposed relationships between fan identification and motivations

(Trail et al, 2000; Trail & James, 2001; Wann, 1995). Fink, Trail and Anderson (2002)

have also identified that the combination of motivations for attendance to sporting

events is different for males and females.

Results of the netnographic research in Study 1 suggest that popular music concert

attendees with varying levels of fan identification also possess very disparate

motivations for attending popular music concerts. These findings may indicate that

fan identification theory performs as similarly for music fans, as it does for sport

fans. It is therefore hypothesized:

H9: Fan identification is related to motivations for popular music concert

attendance

H19: Motivations for popular music concert attendance will differ between

males and females

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Hypotheses related to Product Involvement

As described in Chapter 1, product involvement is defined as the consumer’s interest

in the product - concerts. A person identified as possessing a high level of product

involvement has been found to exhibit greater brand loyalty (Te’eni-Harari and

Hornik, 2010, p. 499) and is more likely to purchase the corresponding

product/service (Richins and Bloch, 1986). It is well established in the branding

literature that brand loyal consumers are repeat purchasers and more price tolerant

(Keller, 2013). It is therefore hypothesised that:

H1b: Product involvement is positively related to number of popular music

concerts attended, per year

H1b: Product involvement is positively related to number of popular music

concerts attended for a specific artist

H2: Product involvement is positively related to amount willing to pay

Findings from the focus group discussions in Study 2 reveal that individuals who

enjoy attending popular music concerts, often desire to attend concerts in attractive

and distinctive locations such as an Opera House or geographical regions of natural

beauty such as Byron Bay, NSW, Australia. Participants also acknowledged that they

would often prefer to travel to locations other than attend a concert in their local

city. It is therefore also hypothesised that:

H3: Product involvement is positively related to willingness to travel

Product involvement has been described to be an important construct for

influencing consumers’ cognitive and behavioural responses (Laaksonen, 1994), and

this was noticeably evident in the findings from the focus groups. Participants who

reported possessing varying degrees of interest in popular music concerts (that is,

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exhibiting different levels of product involvement), also indicated very different

motivations for attending popular music concerts. It is therefore additionally

hypothesised that:

H4: Product involvement is related to motivations for popular music

concert attendance

Hypotheses related to motivations for popular music concert attendance

Whilst there are no empirical studies on motivation for attendance at popular music

concerts, motivations are seen as the fundamental reason for behaviour (Mayo &

Jarvis, 1981; Snepenger, 2006). Through Study 1 and Study 2, it is evident that concert

attendee behaviour is driven by different internal factors, and these internal factors

appear to affect varied elements of consumer behaviour, not just attendance at

events. Consumers may be willing to pay more or less depending on the internal

factor arousing their desire to attend a popular music concert, which in turn may

also influence whether or not the consumer is willing to travel to an event based on

the significance of that need. Consequently, four hypotheses emerge in regard to the

influence of motivations on concert attendee behaviour. These are:

H10a: Motivations are related to average number of

popular music concerts attended, per year

H10b: Motivations are related to number of popular music concerts

attended for a specific artist

H11: Motivations are related to amount willing to pay

H12: Motivations are related to willingness to travel

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The mediating role of motivations for popular music concert attendance

Direct relationships are hypothesised between fan identification and concert

attendee behaviour and product involvement and concert attendee behaviour. It is

also hypothesised that both fan identification and product involvement are directly

related to motivations for popular music concert attendance. It is unknown however,

how much motivations will account for the relationships between fan identification,

product involvement and concert attendee behaviour. As motivations are deemed

internal factors that arise and direct consumer behaviour, it is possible that these

motivations, are innately decided as a result of one’s level of fan identification and

product involvement, and therefore motivations may ultimately be the only ‘true’

driver of behaviour. Therefore in order to evaluate the relative importance of each of

these factors on concert attendee behaviour, it is necessary to evaluate the mediating

role of motivations. This assumption leads to the hypotheses:

H13: Motivations mediate the relationship between product involvement and

number of popular music concerts


amount willing to pay for tickets


willingness to travel

H16: Motivations mediate the relationship between fan identification and




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4.2.2 Conceptual Model

The proposed conceptual model for testing the relationships between fan

identification, product involvement and motivations on concert attendee behaviour

is shown in Figure 4.1.

Whilst this research provides preliminary insight into the relationships between fan

identification, product involvement, motivations and the concert attendee

behavioural variables, this type of study has yet to be applied to any type of music

context. In light of this, judgement was used in making decisions regarding the

specification of relationships between the variables. Rationale related to the

placement of variables in the structural model centred on the notion that

consumers, before attending a concert, possess a particular level of fan identification

and involvement with concerts. It was therefore hypothesised that the level of

attachment to an artist and the level of involvement in concerts would intrinsically

influence motivations, which in turn would influence concert attendee behaviour.

Throughout the study, however, no causal inferences are made. This is in line with

Cronin, Brady, and Hult (2000) and Dean (2007), who suggest that cross sectional

designs, prevent causal inference and presumed causal ordering is therefore, only an

untested assumption. Similar to the argument proposed by Dean (2007),

relationships existing between the constructs are interpreted in terms of significant

relationships (either positive or negative), and future research should be conducted

utilising a longitudinal design to enable causal inference.

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Figure 4.1: Conceptual model for popular music concert attendee behaviour

Product Involvement

Fan Identification

Motivations

PLSR SIGN RP

NOS PA PS SE ESC AEST UB HW SI

Concerts per year

Concerts per artist a. b.

H8

H9

H4

H10a, H10b, H11, H12

H5a, H5b, H6, H7

H1a, H1b, H2, H3

Willingness to Travel

Amount Willing to Pay

Concert Attendance

H13a, H13b, H14, H15, H16, H17, H18 Mediation Moderation H19

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4.3 Method

For Study 3, a structured online survey was administered by an online research

company ‘Research Now’, to a randomised sample of Australian consumers who had

attended a popular music concert within the six months prior to data collection (see

Appendix E for participant information sheet). A survey design allows for the

collection of quantitative data relating to trends, attitudes, or opinions of a

population (Creswell, 2009). Of the different survey administration methodologies,

online surveys are the fastest growing data collection method (Burns & Bush, 2010).

They allow for faster turnaround of data than other traditional survey methods such

as intercept surveys and mail. Another advantage of online surveys is sample control

(Malhotra, 2010).

When conducting surveys is it important that the desired target is reached. An

incident rate refers to the percentage of the population that possess a characteristic

necessary to be included in a survey (Burns & Bush, 2010). In line with reports from

the Australian Bureau of Statistics which indicate that 44.6% of 18-24 year olds and

40.2% of 25-34 year olds attend popular music concerts (ABS, 2010a), the incidence

rate of adults (18+ years) who have attended a popular music concert in a six month

period was estimated by ‘Research Now’ to be 41%. The number of adults in Australia

account for approximately 75% of the population (ABS, 2011), and therefore, an

incidence rate of 41% for concert attendees may be perceived as low. Therefore a

data collection method was sought that could easily screen for respondents who had

attended a popular music concert in the last six months. The research company

commissioned to access the population maintains online panels of potential

respondents. Therefore an online survey was deemed an efficient means of data

collection to avoid having to contact a large number of people that did not qualify to

take the survey.

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4.3.1 Sample

The final sample comprised n=502 responses (once the data had been prepared and

cleaned). Table 4.1 provides a demographic profile of Study 3 respondents.

Table 4.1 shows that, over half the respondents were female (63.1%), and 36.9% were

male. The age of respondents ranged from 18 to 86 years of age, with an average age

of 38.21 years old. More than half of the respondents (59.2%) were represented in the

18-29 years and 30 – 39 years categories. The majority of respondents worked full

time (56.6%), with an annual personal income between $50,000 and $74,999 (29.1%),

and a combined annual household income of $100,000 or more (40.2%).

Interestingly, more than two thirds of the respondents were either singles or couples

without dependent children (69.3%). Respondents had attended concerts from a

wide range of popular music genres including; pop rock (n=135, 26.9%), followed by

rock (n=105, 20.9%), pop (n=69, 13.7%), alternative (n=48, 9.6%) and country and

metal (n=25, 5.0% for both). A wide variety of artists were also represented in the

sample. Bruce Springsteen achieved the highest level of reported attendance (male: n

= 21, 11.4%; female: n = 25, 7.9%). This was followed by Metallica (n=9, 4.9%), Keith

Urban (n=6, 3.2%) and KISS (n=6, 3.2%) for males, and Pink (n=19, 6.0%), Keith

Urban (n=16, 5.0%) and Lady Gaga (n=10, 3.2%) for females.

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Table 4.1: Respondent Profile

Demographic Category Percentage Gender Female 63.1

Male 36.9

Age 18-29 years 31.1 30-39 years 28.1 40-49 years 20.5 50-59 years 14.5 60+ years 5.8

Annual Personal Income

Less than $25,000 12.5 $25,000 - $49,999 24.7 $50,000 - $74,999 29.1 $75,000 - $99,999 15.3 $100,000 or more 18.3

Annual Household Income

Less than $25,000 2 $25,000 - $49,999 9.8 $50,000 - $74,999 17.7 $75,000 - $99,999 19.5 $100,000 or more 40.2

Not Applicable 10.8 Marital Status

Single without dependent children

30.7

Single with dependent children 4.6 Couple without dependent children

38.6

Couple with dependent children 26.1

Employment Status

Unemployed 2 Casual 7.6 Home Duties 7.2 Part Time 13.3 Full Time 56.6 Retired 4.4 Student Working Full Time 2.2 Student Working Casual or Part Time

5

Student Only 1.8

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4.3.2 Measures

The questionnaire used in this study comprised multiple sections and utilized

various multi-item scales; fan identification, product involvement and motivations

(see Appendix F for a copy of the questionnaire). Scales from the literature for fan

identification and product involvement were adapted to a popular music context.

However, the Concert Attendee Motivation Scale (CAMS) was developed for this

research from a review of the literature and findings from Study 2.

Product Involvement

Product involvement is viewed to be a constant and stable variable (Havitz and

Howard, 1995; Iwasaki and Havitz, 1998; Quester and Smart, 1996) and is just as an

important and equally applicable precursor to the purchase of services, as it is in

relation to physical products (Gabbott and Hogg, 1999).

Marketing scholars have conceptualised and developed scales to measure the

construct of involvement. Laurent and Kapferer (1985) proposed a multi-

dimensional model, whilst Zaichkowsky (1985) presented a uni-dimensional

measurement scale. There does not appear to be a clear consensus in the consumer

behaviour literature in reference to the conceptualisation of involvement (O’Cass,

2000), however the majority of researchers see involvement as multi-dimensional

and rely on the seminal scale developed by Laurent and Kapferer (1985)

(Michaelidou and Dibb, 2006).

According to Kapferer and Laurent (1985; 1993), different involvement profiles

should be developed for each type of individual consumer. They use a Consumer

Involvement Profile (CIP) which measures different antecedents of involvement

using an empirical instrument consisting of a number of subscales. Laurent and

Kapferer (1985) suggest five antecedents of involvement: interest, pleasure, sign, risk

importance and risk probability (see Table 4.2). A consumer profiled as having a

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minimal level of involvement will score low on all dimensions, and a consumer with

strong involvement will score high on all dimensions. Product involvement has been

found to affect a consumer’s decision making process, their search for information,

how they receive and process advertising communication and purchase decisions

(Laurent and Kapferer, 1985). It is therefore important to measure enduring

involvement in order to capture consumer behaviour of individuals, independent of

purchase or other situational factors that may temporarily affect consumer response

during the research process. Laurent and Kapferer’s (1985) measure is assumed to be

the most appropriate scale for achieving this.

Table 4.2: The consumer involvement profile scale (CIP): the five facets of involvement

Facets of involvement (CIP) Description of facets

Interest The personal interest a person has in a product category, its personal meaning or importance

Pleasure The hedonic value of the product, its ability to provide pleasure and enjoyment

Sign The sign value of the product, the degree to which it expresses the person's self

Risk importance The perceived importance of the potential negative consequences associated with a poor choice of the product

Risk probability The perceived probability of making such a poor choice

Source: Kapferer and Laurent (1985; 1993)

Laurent and Kapferer (1985) suggest that taking into account the antecedents of

involvement allows researchers to make predictions on the consequences of varying

degrees of involvement (where the level of involvement can be deduced from

observed measurements on the five antecedents (Rodgers and Schneider, 1993)).

Whilst the CIP has typically been applied to the purchase of physical goods, scholars

argue that the CIP is appropriate for measuring consumer behaviour associated with

service goods. Murray (1991) suggested that the purchase of services is riskier than

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physical goods and Gabbott and Hogg (1999) state that the multifaceted nature of

the CIP has been said to reflect an appropriate view of involvement for services,

particularly in reference to the inclusion of the two risk facets.

This research used the 16 items (reflecting five facets of involvement) based upon the

English translation of the original CIP items presented in French by Laurent and

Kapferer (1985). A number of attempts have been made at translating the CIP but

scholars argue that these translations, although in English, still retained a “French

language ‘accent’” (Rodgers and Schneider, 1993, p. 335). Rodgers and Schneider

(1993), therefore, presented a 16-item English version of Laurent and Kapferer’s CIP

scale, which comprised modified translations of each of the items so that the scale

was stated in conversational English (see Table 4.3). Gabbott and Hogg (1999)

adopted and modified the CIP to make sense when applied to service products. The

authors did not publish the specific item wording, but they were able to produce a

result consistent with results reported by Laurent and Kapferer (1985) and Kapferer

and Laurent (1993) with these slight wording modifications. Therefore, for this

study, the Rodgers and Schneider (1993), conversational English CIP scale was

adopted and the wording slightly modified, where necessary, to reflect involvement

with attendance to popular music concerts (see Appendix G for the original English

translations of the CIP scale).

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Table4.3: Modified CIP Scale Items by Rodgers and Schneider (1993)

CIP Scale Items

Interest INTR1 I attach great importance to popular music concerts. INTR2 Popular music concerts interest me a lot. INTR3 I couldn't care less about attending popular music concerts. Pleasure PLSR1 I really enjoy attending popular music concerts. PLSR2 Whenever I attend a popular music concerts, it is like giving myself a gift. PLSR3 Attending popular music concerts is pleasurable. Sign SIGN1 I can tell a lot about a person from the concert he or she attends. SIGN2 That I attend popular music concerts say a lot about me. SIGN3 My attendance to popular music concerts gives others a glimpse of who I am. Risk Importance MPRT1 When I choose a concert to attend, it is not a big deal if I make a mistake. MPRT2 I get annoyed when I attend a concert that doesn't meet my needs. MPRT3 I would be upset if, after I attended a concert, I found I had made a poor choice.

Risk Probability

PROB1 When I can select from several concerts, I always feel rather unsure about which one to pick.

PROB2 When choosing to go to a concert from among other activities, I always feel confident that I will make the right choice

PROB3 Whenever I purchase tickets to a concert, I never really know whether they are the ones I should have bought.

PROB4 Choosing which popular music concert to attend is rather difficult.

Note: All items are measured with 5-point Likert scales, with anchors (1) strongly disagree to (5) strongly agree.

Fan Identification

Fan identification in relation to popular music fans was defined as a personal

connection with the artist or band (adapted from Reysen and Branscombe, 2010).

The construct of fan identification has predominately, both theoretically and

empirically, been applied in a sporting context. Whilst the concept of fandom in

reference to popular music is not new, much of the fandom literature is purely

qualitative (e.g. Fraser & Brown, 2002; Soukup, 2006) and no attempt has been made

to measure fan identification in a popular music context. Only one study has

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acknowledged that identification measures may be applicable across contexts

(Reysen and Branscombe, 2010), and therefore the question still exists as to whether

music fans (and concert attendees) display the same differing levels of identification

and behaviour inherent in sport fan literature. As a result, there is a need to explore

fan identification from a popular music perspective before relying solely on

measures developed in the sporting arena.

In light of this, fan identification was measured by using Reysen and Branscombe’s

(2010) Fanship Scale (see Table 4.4) which measures a personal connection with an

interest for all fan types, and has been found to be significantly positively correlated

with the sport spectator identification scale (Developed by Wann and Branscombe,

1993). The scale used in this study comprised nine items from Reysen and

Branscombe’s (2010) scale, each measured on a 5-point Likert scales ranging from (1)

strongly disagree to (5) strongly agree. For each of the items, the words ‘my interest’

were replaced with the name of the headlining act of the last popular music concert

the respondent had attended.

Table 4.4: Fanship Scale Items

1. I have rescheduled my work to accommodate ‘my interest’

2. I am emotionally connected to ‘my interest’

3. I spend a considerable amount of money on ‘my interest’

4. I want everyone to know I am connected to ‘my interest’

5. I would devote all my time to ‘my interest’ if I could

6. I would be devastated if I were told I could not pursue ‘my interest’

7. I strongly identify with ‘my interest’

8. When ‘my interest’ is popular I feel great

9. I want to be friends with people who like ‘my interest’

Source: Reysen & Branscombe (2010, p. 180)

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Motivations (Mediator)

Existing studies on motivation have yet to include a specific focus on popular music

concerts. Studies on motivation are well grounded theoretically and empirically in

the literature, but unlike product involvement, motivations for attendance to events

have been shown to differ not only between very disparate types of events, but ones

that are very similar (e.g. a wine festival and a food festival). A literature review was

conducted to identify motivations for varied events in the literature (see Appendix

H). These motivations comprised the document provided to the focus group

participants in Study 2.

A scale for measuring motivations for popular music concerts was then developed

from this literature review and findings from Study 2. The items for each motivation

were generated by modifying existing items to a popular music context, where

possible. Additional items were generated from the focus group transcripts for those

motivations that had previously not been given empirical attention in the literature.

Academics (4) in the marketing field were asked to evaluate the scale and a pre-test

was conducted before administration. The scale used in the pre-test comprised 40

items related to the 10 motivation dimensions identified in Study 2 (see Table 4.5).

Content, criterion and construct validity as well as internal consistency were

examined and the psychometric properties of the scale assessed to determine the

accuracy and reliability of the Concert Attendee Motivation Scale (CAMS). Details of

these procedures and a summary of the findings are provided later in this chapter.

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Table 4.5: Concert Attendance Motivations Scale (CAMS) Items

Nostalgia N1 I like to attend a [Pipe the text from Q1] concert because it takes me back to when I listened to them in my childhood N2 I like to attend [Pipe the text from Q1] concerts because I didn't get to see them as a child N3 Attending a [Pipe the text from Q1] concert allows me to relive happy memories from the past Aesthetics A1 I appreciate the beauty inherent in the performance of [Pipe the text from Q1] concerts A2 I think the production and theatrical performance of a [Pipe the text from Q1] concert is beautiful A3 I have an artistic appreciation for the technical skill of the artists performing at a [Pipe the text from Q1] concert Escape E1 Attending a [Pipe the text from Q1] concert represents an escape for me from my day to day activities E2 A [Pipe the text from Q1] concert is a great change of pace from what I regularly do E3 I looked forward to the [Pipe the text from Q1] concert because it is different to other leisure activities I normally do E4 I attended the [Pipe the text from Q1] concert to relieve the boredom of everyday life Physical Attraction PA1 I enjoy watching [Pipe the text from Q1] because they are physically attractive PA2 The main reason I attended the [Pipe the text from Q1] concert is because I find the performers attractive PA3 The sex appeal of an individual band member/artist was more important to me than the music at the [Pipe the text from Q1]

concert Status Enhancement SE1 The more [Pipe the text from Q1] concerts I attend, the bigger the fan I am SE2 I like to talk and brag about [Pipe the text from Q1] concerts I have been to SE3 I am not a true fan of [Pipe the text from Q1] if I do not go to their concert/s SE4 Going to [Pipe the text from Q1] concerts that other people don't go to makes me feel special SE5 I believe the more [Pipe the text from Q1] concerts I attend, the more people will be impressed by me Physical Skills PS1 I appreciate the physical skills of [Pipe the text from Q1] PS2 I enjoy watching a well-executed [Pipe the text from Q1] concert performance PS3 It is important for [Pipe the text from Q1] to showcase their skill level at concerts Social Interaction SI1 Interacting with other fans is a very important part of attending a [Pipe the text from Q1]concert SI2 I talk to other people sitting/standing near me at a [Pipe the text from Q1] concert SI3 A [Pipe the text from Q1] concert is a great way to socialise with strangers SI4 I feel part of a group with similar interests when attending a [Pipe the text from Q1] concert SI5 I attended the [Pipe the text from Q1] concert to spend time with my friends SI6 I attended the [Pipe the text from Q1] concert to be with people who enjoy the same things I do Concert Specific Music CSM1 It is important to me to hear music at [Pipe the text from Q1] concerts that has not yet been released CSM2 I enjoy hearing [Pipe the text from Q1] play covers at concerts CSM3 I enjoy hearing acoustic versions of [Pipe the text from Q1] songs at concerts Hero Worship HW1 Being in close proximity to [Pipe the text from Q1] is important to me HW2 I need to attend a [Pipe the text from Q1] concert to show my support and dedication HW3 Attending concerts is an important way to show [Pipe the text from Q1] that I am a fan HW4 Supporting [Pipe the text from Q1] is important to me Uninhibited Behaviour UB1 When I attend a [Pipe the text from Q1] concert I engage in social behaviour that may otherwise not be allowed in a normal

social setting UB2 The [Pipe the text from Q1] concert experience stimulates me to act in a way that I would not normally act UB3 Being able to dance, 'head-bang' or air guitar in an uninhibited setting is an important reason why I attended the [Pipe the text

from Q1] concert UB4 Experiencing music at very high decibels is an appealing feature of a [Pipe the text from Q1] concert

Note: Q1 asked respondents ‘Who was the headlining act at the last popular music concert you went to?’ Items in italics and underlined are items removed at the confirmatory factor analysis stage.

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Dependent Variables

The number of popular music concerts attended and the amount willing to pay for

concerts were measured on single numerical scales. These dependent variables were

identified as a result of the literature review and included in the preliminary

conceptual models. The definitions for attendance however, were not clearly defined

in the literature, and two alternatives were tested. That is, concert attendance

included; a) number of concerts attended per year, on average, and b) number of

times the individual had seen the identified headlining act. This distinction allows

predictions to be made in reference to the number of popular music concerts an

individual will attend in general, and predictions regarding the number of concerts

an individual will attend for an individual artist.

Based on previously discussed literature, a highly identified fan will attend more

events (Fink et al, 2002; 2009) and additionally, a consumer highly involved in

concerts is likely to attend more concerts (Richins & Bloch, 1986). Therefore,

consistent with research in the sporting literature (see Funk, Filo, Beaton &

Pritchard, 2009), an outcome measure of concert attendance was included as a

measure of past behaviour to examine the explanatory ability of these two factors in

the model. Although the measure of past concert attendance does not directly

measure frequency of behaviour, nor prediction of future behaviour, it is expected to

function as a proxy indicator of attendance frequency.

Willingness to travel was identified as another dependent variable from the findings

of the netnographic research in Study 1 and the focus groups in Study 2, and

comprised three dimensions; willingness to travel to multiple cities, multiple states

and overseas. All willingness to travel items were measured on 5-point Likert scales

ranging from (1) strongly disagree to (5) strongly agree.

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4.3.3 Data Preparation

One of the objectives of data preparation is to review the questionnaires with the

objective of increasing accuracy and precision (Malhotra, 2006). As the

questionnaire for this study was administered using an online panel recruited by a

professional research company, a large number of the problems typically associated

with hard copy data collection were eliminated through the programming of the

questionnaire. Illegible, incomplete and inconsistent responses were non-existent

due to the structured format of the questionnaire and background programming

that prevented respondents from skipping or missing any of the questions or

entering inconsistent responses. For example, the programming behind the question

asking for ‘annual household income’ prevented respondents from choosing a

response that was less than their indicated ‘annual personal income’. Forced

completion programming also meant there were no missing values. Measures were

put in place to detect flat lining of responses, that is, response values that showed

little variation across a number of questions. Questionnaires were returned to the

field in order to replace respondents if this occurred. An initial screening question

also ensured that only respondents who had attended a concert in the six months

prior to doing the survey were eligible for participation. Therefore, the main tasks

implemented in the data preparation phase were primarily variable re-specification

activities and assessment of normality for numerical variables. These activities are

detailed in Appendix I (data cleaning), Appendix J (product involvement normality),

Appendix K (fan identification normality) and Appendix L (motivations normality),

and mentioned again in relation to the relevant models for product involvement

(Appendix M) and motivations (Appendix N).

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4.3.4 Method of Analysis

Analysis of Study 3 involved two stages. First, all the multi-item measures were

subjected to exploratory factor analysis, confirmatory factor analysis (CFA) and

validity and reliability assessments. Second, the AMOS structural equation

modelling program was used to examine the structural models and test the research

hypotheses. Differences tests, specifically independent samples t-tests, were

conducted using SPSS in order to address hypothesis 19 (motivations will differ for

males and females). Each of these steps involved statistical considerations and

required decisions with respect to standards of interpretation. Table 4.6 presents a

summary of the standards and their sources used during the analysis. This table will

be used to avoid unnecessary repetition with respect to decision rules.

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Table 4.6: Standards of interpretation used during statistical analyses

Step Standard for Interpreting

Output Source

Confirmatory

Factor Analysis

AVE > 0.50 Fornell & Larcker (1988)

Construct Reliability > 0.7 Fornell & Larcker (1988)

CFA & Structural

Model CMIN/df - 3:1 Ratio Hair et al (2010)

Preliminary Fit

Criteria

Factor Loadings - too small

(<0 .5) or too large (> 0.95)

Should be 0.5 or higher, ideally

above 0.7

Bagozzi and Yi (1988; 2012)

Hair et al (2000)

(Note: For sample

> n = 250, with > 30

measured variables)

CFI > 0.9 Hair et al (2010), Bagozzi

and Yi (1988; 2012)

GFI > 0.9 Hair et al (2010), Bagozzi

and Yi (1988; 2012)

RMSEA ≤ 0.7 Browne & Cudeck (1992);

Hair et al (2010)

PCLOSE > 0.05 Browne & Cudeck (1992)

SRMR ≤ 0.8 Browne & Cudeck (1992);

Hair et al (2010)

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4.4 Results

This section first reports the exploratory and confirmatory factor analyses of each of

the multi-item scales used in the structural model. Following this, the psychometric

properties of each of the multi-item scales was assessed by considering the content,

criterion, construct validity and internal consistency of the product involvement, fan

identification and motivation scales. As some of these stages are quite detailed, each

construct will be presented separately. Finally, the structural models are examined

and the research hypotheses tested.


This section provides the results of exploratory and confirmatory factor analyses for

the product involvement construct. Three models are presented; a 5-factor

(expected), 4-factor and 3-factor model. Construct validity, discriminant validity and

criterion validity was assessed and compared between the models (see Table 4.7).

The details regarding the psychometric testing of the three models are provided and

explained in the following sections.

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Table 4.7: Product Involvement: Comparison of 3-factor, 4-factor and 5-factor CFA Measurement Models – Factor Loadings, AVE Estimates, Construct Reliability and Criterion Validity

Table 4.8 shows the comparison of fit across the three models. As shown in Table 4.8, a three factor solution for product involvement produced superior fit for the data related to popular music concerts.

Table 4.8: Comparison of fit across the three models

5-Factor 4-Factor 3-Factor

CMIN/df 4.752 4.453 1.753

CFI 0.922 0.923 0.992

GFI 0.924 0.926 0.986

RMSEA 0.087 0.083 0.039

PCLOSE 0.000 0.000 0.772

SRMR 0.0598 0.0593 0.025

1 2 3 (λ) (δ) 1 2 3 4 (λ) (δ) I P S RI RP (λ) (δ)

INTR1 0.756 0.572 0.428 0.757 0.573 0.427 0.715 0.511 0.489INTR2 0.75 0.563 0.438 0.747 0.558 0.442 0.735 0.540 0.460INTR3PLSR1 0.825 0.681 0.319 0.824 0.679 0.321 0.839 0.704 0.296PLSR2 0.612 0.375 0.625 0.616 0.379 0.621 0.609 0.371 0.629PLSR3 0.761 0.579 0.421 0.76 0.578 0.422 0.777 0.604 0.396SIGN1 0.615 0.378 0.622 0.616 0.379 0.621 0.61 0.372 0.628SIGN2 0.802 0.643 0.357 0.802 0.643 0.357 0.818 0.669 0.331SIGN3 0.773 0.598 0.402 0.772 0.596 0.404 0.784 0.615 0.385MPRT1MPRT2 0.628 0.394 0.606 0.637 0.406 0.594MPRT3 0.661 0.437 0.563 0.652 0.425 0.575PROB1 0.850 0.723 0.278 0.848 0.719 0.281 0.848 0.719 0.281PROB2 0.785 0.616 0.384 0.786 0.618 0.382 0.786 0.618 0.382PROB3PROB4 0.727 0.529 0.471 0.728 0.530 0.470 0.729 0.531 0.469

AVE 0.55 0.66 0.68 0.55 0.66 0.68 0.42 0.53 0.56 0.55 0.42 0.62Construct Reliability

0.83 0.79 0.81 0.83 0.79 0.81 0.59 0.69 0.79 0.78 0.59 0.83

Criterion Validity

0.323 0.201 0.327

Note: Criterion Validity = Concurrent validity assessed by determining the correlation between the factors of the Product Involvement Scale and the average number of popular music concerts attended per year. All correlation coefficients signinficant at p < 0.001 level

3 - FACTOR MODEL 4 - FACTOR MODEL 5 - FACTOR MODEL

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Confirmatory Factor Analysis of the 5-factor Model

As there was a priori theoretical expectation that there would be five factors to the

product involvement scale (see Table 4.2, p. 99), CFA was run first to fit the data to

the five factor model.

Overall Model Fit

As a first pass, the strength of the relationships between the constructs and the

variables was assessed by examining the variance explained in each variable by the

construct (squared multiple correlation, or SMC). On examination, three of the 16

items had SMC values below 0.3, indicating that these items were a poor measure for

the designated construct. These included two risk related items, MPRT1 (SMC =

0.012) and PROB3 (SMC = 0.048), and one ‘Interest’ item, INTR3 (SMC = 0.144) (see

Table 4.3, p. 101 for item details). These items were dropped from the model and the

analysis re-run. The model at this stage comprised 13 items reflecting the five

dimensions of product involvement, with items ranging from two to three on each

dimension. The results of the analysis reveal that the model somewhat fit the data.

The chi-square statistic was significant (χ2 = 202.738, df = 44), and the normed chi-

square measure (CMIN/df = 4.608) was outside the generally accepted 3:1 ratio for

better fitting models (Hair et al, 2010). The CFI and GFI were above 0.9 (0.935 and

0.939 respectively). In addition, the RMSEA which is related to the amount of error

in the model (Yau et al, 2007) was on the higher side at 0.085 (CI = 0.073; 0.097), and

the test for close fit (PCLOSE = 0.000) was rejected, however, the model achieved a

SRMR of 0.0598, which is satisfactory because an SRMR of over 0.1 would suggest a

problem with fit (Hair et al, 2010). Whilst some of these fit indices are acceptable,

results indicated that there could be problems with the model.

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Construct Validity

Convergent Validity

In order to determine convergent validity of the five factor scale, factor loadings,

reliability and average variance extracted was considered. It is suggested that all

factor loadings should be 0.5 or higher, and ideally 0.7 or higher (Hair et al, 2010).

The standardised parameter estimates for each of the items for all constructs, were

all above 0.5, with 9 of the 13 (69%) items possessing loadings above 0.7. Reliability

of the constructs was determined using the construct reliability (CR) calculation

presented by Fornell and Larcker (1981), which is given as:

(1)

Where iλ represents the ith factor loading on a corresponding factor, and iδ

represents the error variance term for a construct. two of the constructs gave a CR

estimate of less than 0.7, which included the constructs for Interest and Risk

Importance. These constructs gave a reliability estimate of 0.69 and 0.59 respectively

(see Table 4.7, p. 110). Reliability between 0.6 and 0.7 can be considered acceptable

provided that other conditions for construct validity are met (Hair et al, 2010). This

means that the Interest construct may still be satisfactory; however, the Risk

Importance construct was not.

In order to examine the amount of variance that is captured among the items of the

constructs, average variance extracted (AVE) was also calculated. The calculation is

(2)

∑ ∑

∑

= =

=

+= n

i

n

iii

n

ii

CR

1 1

2

1

2

)()(

)(

δλ

λ

nAVE

n

ii∑

== 1

2λ

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where iλ is the standardised factor loading and i is the number of items (Hair et al,

2010). All AVE scores ranged from 0.416 to 0.623, with the AVE for Risk Importance

falling below the 0.5 benchmark (Fornell and Larcker, 1981; Hair et al, 2010).

Taking into consideration these three measures in combination (factor loadings,

reliability and AVE), convergent validity of the 5-factor product involvement scale

may not acceptable due to the inconsistencies of the Risk Importance Construct.

Further testing of the scale continued, however, to gain a thorough understanding of

the product involvement dimensions.

Discriminant Validity

In order to establish that each of the different motivation constructs within the

Product Involvement Scale was unique and distinct, the average variance extracted

for each construct was compared with the squared correlations of the other

constructs (Fornell and Larcker, 1981; Hair et al, 2010). As shown in Table 4.9, there

are major problems with some of the squared inter-construct correlation estimates

being larger than the corresponding AVE estimates. The Interest construct is not

distinct from the Sign or Pleasure construct. The discriminant validity of this scale is

therefore questionable, as some of the variance in the items may have more in

common with another construct, then the construct they have been assigned.

Table 4.9: Product Involvement: Discriminant Validity of 5-factor Measurement Model - AVE Estimates and Squared Correlations

Construct AVE I P S RP RI

Interest 0.53 - 0.78 0.84 0.10 0.30 Pleasure 0.56 0.72 - 0.30 0.07 0.34 Sign 0.55 0.82 0.30 - 0.10 0.22 Risk Probability 0.62 0.10 0.01 0.10 - 0.59

Risk Importance 0.42 0.30 0.34 0.22 0.01 -

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Appropriateness of 5-Factor Model

As demonstrated above, the 5-Factor Model for Product Involvement proposed in

the literature by Laurent and Kapferer (1985), whilst somewhat fitting the popular

music concert data, has significant problems with construct validity (namely,

convergent validity) and discriminant validity. Therefore an EFA was conducted to

examine the underlying structure of the variables in order to seek a better factor

solution.

Exploratory Factor Analysis

As the data was normally distributed, Maximum Likelihood extraction method was

used. Direct Oblimin (oblique) rotation was selected as the factors of the product

involvement scale were shown to be correlated in the previous analysis. Laurent and

Kapferer (1985) also recommend an oblique rotation as there is no a priori

expectation that the five facets of involvement are mutually independent (Rodgers

and Schneider, 1993). The correlation matrix reporting the bivariate correlations

between each pair of variables showed that all variables have at least one correlation

greater than 0.3, meaning the data was suitable for factor analysis (Francis, 2013).

The Kaiser-Meyer-Olkin (KMO) Measure of Sampling Adequacy reports the amount

of variance in the data that can be explained by the factors. This value was 0.861

which is considered meritorious (Kaiser, 1974). The Bartlett’s Test of Sphericity is

significant (p < 0.001) meaning that there were significant correlations to be

investigated. Anti-image Matrices were used to further determine the suitability of

factor analysis (Allen and Bennett, 2010). All the KMO values for each variable in the

anti-image matrix were above 0.624 (which is greater than 0.5) and therefore none of

the variables needed to be dropped from the analysis at this stage.

The communalities table indicates how much variance can be explained by each of

the variables (Allen and Bennett, 2010). The commonalities for four of the 16 items

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was quite low (0.284 or less), whilst the majority of others were greater than 0.6.

Two of the four items with low communalities belonged to the theoretical factor

‘Risk Importance’ (MPRT1 and MRTP2), the others, a risk probability item (PROB3)

and an ‘Interest’ item (INTR3), which had both proven difficult in previous analyses.

As a result, the factor structure was not as expected. The results in the Total

Variance Explained table show that there were four underlying factors to the data, as

opposed to the theoretical five factor solution which was assumed from the

literature. Results show that 49.403% of the variance can be explained by these four

factors.

Interpreting the Factors

All items loaded strongly on only one factor, and all loadings were greater than 0.3,

except the first risk importance item (MRPT1) which had a factor loading of 0.259.

The third risk probability item (PROB3) also had quite a low factor loading of 0.328.

Both of these items were removed from the analysis. The majority of the remaining

loadings were above 0.6 (10 of the remaining 14).

Confirmatory Factor Analysis of the 4-Factor Model

Responses to the remaining 14 items were examined using confirmatory factor

analysis (CFA). The AMOS structural equation modelling program was used to

examine the fit of the data to the 4-factor model identified from the EFA using

Maximum Likelihood extraction. To reduce repetitiveness; from this point on, fit

indices will be displayed in a table and overall model fit will be assessed in terms of

the criteria set out in Table 4.6, p. 108.

Overall Model Fit

As a first pass, the strength of the relationships between the constructs and the

variables was assessed by examining the variance explained in each variable by the

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construct (squared multiple correlation, or SMC). On examination, one of the 14

items (INTR3) had an SMC value below 0.3 (0.184), indicating that this item was a

poor measure for the designated construct (originally an ‘Interest’ item). This item

was dropped from the model and the analysis re-run.

Table 4.10: Fit Indices – Four Factor Product Involvement Model

CMIN/df 4.453

CFI 0.923

RMSEA 0.083

PCLOSE 0.000

SRMR 0.059

The model at this stage comprised 13 items reflecting four dimensions of product

involvement, with items ranging from two to four on each dimension. As shown in

Table 4.10, the normed chi square was still outside the 3:1 ratio, the RMSEA was quite

high and the hypothesis of close fit was still rejected. These results indicated that

further refinement of the scale was necessary. Again, further testing continued to

gain a thorough understanding of the psychometric properties of the scale.

Construct Validity

Convergent Validity

In order to determine convergent validity, factor loadings, reliability and average

variance extracted was considered. The standardised parameter estimates for each of

the items for all constructs, were all above 0.5, with 9 of the 13 (69%) items

possessing loadings above 0.7 (see Table 4.7, p. 110). Reliability of the constructs was

again determined using the construct reliability (CR) calculation presented by

Fornell and Larcker (1981). All construct reliability scores were above 0.7, excluding

construct four which comprised two ‘Risk Importance’ items (MRPT2 and MRPT3).

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This construct had a reliability estimate of 0.59 which is unacceptable (Hair et al,

2010).

In order to examine the amount of variance that was captured among the items of

the constructs, average variance extracted (AVE) was also calculated. AVE scores

ranged from 0.42 to 0.68, with the Risk Importance construct falling below the 0.5

benchmark (Fornell and Larcker, 1981; Hair et al, 2010). Taking into consideration

these three measures in combination (factor loadings, reliability and AVE),

convergent validity of the four factor product involvement scale was also deemed

inadequate.


As shown in Table 4.11, all AVE estimates in the four factor model are larger than the

corresponding squared inter-construct correlation estimates. Therefore discriminant

validity is demonstrated as each item has more variance in common with its

assigned construct than with any other construct.

Table 4.11: Product Involvement: Discriminant Validity of 4-factor Measurement Model - AVE Estimates and Squared Correlations

Construct AVE 1 2 3 4 1 0.55 - 0.33 0.43 0.01 2 0.66 0.33 - 0.24 0.01

3 0.68 0.43 0.24 - 0.10

4 0.42 0.07 0.01 0.12 -


As demonstrated above, a 4-Factor Model of Product Involvement for popular music

concert attendance is an improvement on the 5-factor model proposed in the

literature by Laurent and Kapferer (1985). The 4-factor model somewhat fits the

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popular music concert data, but, whilst there were now no discriminant validity

issues, the model still had significant problems with construct validity (namely,

convergent validity), which involved the construct with items relating to risk

importance. It is evident from both the 5-factor model and the 4-factor model that it

was the items related to risk importance, one risk probability item (PROB3) and the

third interest item (INTR3) that were creating problems for modelling product

involvement relating to popular music concert attendance, with the major problem

associated with the inconsistencies evident in the risk importance items.

Due to the problems with both the 5-factor and 4-factor models of product

involvement, a 3-factor solution was then derived and compared with both the 5-

factor and 4-factor solutions (see Table 4.7 and 4.8, p. 110). First, EFA was performed

using Maximum Likelihood extraction with Direct Oblimin rotation and a fixed

number of factors to be extracted (three) was specified. The three factor solution was

generated but again, the risk importance items (MPRT1, MPRT2 and MPRT3), the

troublesome risk probability item (PROB3) and interest item (INTR3) produced low

communalities (0.035, 0.062, 0.066, 0.122 and 0.183 respectively) and low factor

loadings. These items were removed and EFA with Maximum Likelihood extraction

with Direct Oblimin rotation produced a 3-factor model with a KMO of 0.874

(irrespective of whether the number of factors were restricted to three or not).

Confirmatory Factor Analysis of the 3-Factor Model

The 3-factor model with 11-items was examined using confirmatory factor analysis

(CFA) using Maximum Likelihood extraction. On examination, all of the 11 items had

an SMC value above 0.3 indicating that all items were adequate measures for their

designated construct. The model comprised 11 items reflecting three dimensions of

product involvement, with items ranging from three to four on each dimension.

Again, the normed chi-square and RMSEA were too high and the test for close fit

was rejected (see Table 4.12).

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Table 4.12: Fit Indices – Three Factor Product Involvement Model

CMIN/df 5.380

CFI 0.929

RMSEA 0.094

PCLOSE 0.000

SRMR 0.062

Modification

Examination of the error covariance terms revealed that there may be

misspecification issues regarding the 3-factor CFA model for product involvement. A

systematic review of the modification indices was conducted to identify large

modification indices associated with the pairing of error terms. Misspecifications

associated with the pairing of error terms may indicate an overlap in item content

within the product involvement scale (Byrne, 2010), which was certainly evidenced

by previous discriminant validity testing. As a result, three items were further

deleted to alleviate data redundancy and improve the 3-factor product involvement

scale. These deletions resulted in a major improvement of the fit (see Table 4.13).

Whilst the chi-square statistic was significant, normed chi-square was now within

the accepted 3:1 ratio, CFI and GFI improved, RMSEA was now lower and the

hypothesis of close fit was not rejected. These fit indices now suggested that a 3-

factor model representing product involvement with popular music concerts was a

good fit. Details of the final dimensions of the product involvement scale for popular

music concerts will explained later in this section (see p. 121), after further

psychometric testing.

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Table 4.13: Product Involvement: Comparison of fit indices between Original 3-factor and final Modified 3-factor Measurement Model

Fit Indices Original 3-factor

Model Modified 3-factor Model

df 41 17 χ2 220.600 29.808

CMIN/DF 5.380 1.753 GFI 0.927 0.986 CFI 0.929 0.992

RMSEA 0.094 0.039 PCLOSE 0.000 0.772 SRMR 0.062 0.025

Construct Validity

Convergent Validity


variance extracted were considered. The standardised parameter estimates for each

of the items for all constructs, were all above 0.5, with seven of the eight (88%) items

possessing loadings above 0.7 (see Table 4.7, p. 110). Reliability of the constructs was

again determined using the construct reliability (CR) calculation presented by

Fornell and Larcker (1981). All construct reliability scores were now above 0.7, with

all factors having a reliability score of between 0.79 and 0.83.


the constructs, average variance extracted (AVE) was again calculated. All AVE

scores ranged from 0.55 to 0.68, well above the 0.5 benchmark (Fornell and Larcker,

1981; Hair et al, 2010), indicating that the items for each of the constructs share a

high proportion of variance (see Table 4.7, p. 110). Taking into consideration these

three measures in combination (factor loadings, reliability and AVE), convergent

validity of the 3-factor product involvement scale was deemed adequate.

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In order to establish that each of the constructs within the 3-factor product

involvement scale was unique and distinct, the average variance extracted for each

construct was compared with the squared correlations of the other constructs

(Fornell and Larcker, 1981; Hair et al, 2010). As shown in Table 4.14, all AVE estimates

were now larger than the corresponding squared inter-construct correlation

estimates. Therefore discriminant validity was demonstrated as each item had more

variance in common with its assigned construct than with any other construct.

Table 4.14: Product Involvement: Discriminant Validity of final 3-factor Measurement Model - AVE Estimates and Squared Correlations

Construct AVE 1 2 3 1 0.55 - 0.24 0.42 2 0.66 0.24 - 0.24

3 0.68 0.42 0.33 -

Criterion Validity

Criterion validity was examined by assessing the concurrent validity of the 3-factor

Product Involvement Scale (PIS) and comparing the factors of the PIS to the average

number of popular music concerts attended per year. It is suggested that those with

a high level of product involvement with popular music concerts would be more

involved with popular music concerts and therefore attend more popular music

concerts per year. All three product involvement factors showed a significant

positive correlation (all p < 0.001) with the average number of concerts attended per

year, with Pearson coefficients ranging from 0.220 – 0.323. Therefore an individual

with a higher level of product involvement on any of the 3-factors was significantly

more likely to attend more popular music concerts a year on average, than someone

with a lower level of product involvement. These significant correlations provide

121 | P a g e

good evidence of concurrent validity. It is important to note however, that predictive

validity has not been established as the data for the product involvement scale and

the average number of times respondents attend popular music concerts a year, was

collected at the same time.


As demonstrated above, a 3-Factor Model of Product Involvement for popular music

concert attendance is an improvement in psychometric terms, on both a 4-factor

model and the 5-factor model proposed in the literature by Laurent and Kapferer

(1985).

The 3-factor model does not only produce more superior fit indices, but also

possesses components that are convergent and have good discriminant validity. The

3-factor model for product involvement was also shown to make theoretical sense

when correlated with the average number of popular music concerts attended per

year. For a side by side comparison of the three models refer back to Table 4.7 and

4.8 (see p. 110).

Final Product Involvement Measurement Model

The final model comprised three dimensions; Pleasure, Sign Value and Risk

Probability. This model differs from Laurent and Kapferer’s (1985) model in three

ways: (1) one of the interest items has merged with the sign dimension, (2) all other

interest items drop out completely, and (3) the risk importance items have dropped

out completely from the model and there is no longer a risk importance dimension.

The following sections discuss and attempt to explain why this 3-factor model of

product involvement may differ from Laurent and Kapferer’s (1985) 5-facet CIP Scale.

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Table4.15: Final Product Involvement Measurement Model: Item wording, Factor Loadings, AVE Estimates and Construct Reliability

Item Description Pleasure Sign Risk

Probability

PLSR1 I really enjoy attending popular music concerts. 0.825

PLSR3 Attending popular music concerts is pleasurable. 0.761

INTR1 I attach great importance to popular music concerts. 0.756

SIGN1 I can tell a lot about a person from the concert he or she attends.

0.615

SIGN2 That I attend popular music concerts say a lot about me. 0.802

SIGN3 My attendance to popular music concerts gives others a glimpse of who I am.

0.773

PROB1 When I can select from several concerts, I always feel rather unsure about which one to pick.

0.850

PROB4 Choosing which popular music concert to attend is rather difficult.

0.727

AVE

0.680 0.548 0.662

Construct Reliability 0.827 0.831 0.828

(1) Merging of Interest and Sign Items

The results in Table 4.15 show that for the 3-factor model, one of the interest (INTR1)

items merges with the three sign items. The sign construct measures the degree to

which a product/service expresses the person’s self. On examination of the wording

of the sign items (see Table 4.16) and the interest item (INTR1), it is evident that

these items share similar meaning. For a product or service to say a lot about a

person and give people a glimpse of who they are, then it makes sense that, that

same individual may attach great importance to that same product or service. It is

suggested that it is the wording of INTR1 that allows this item to load with the sign

construct, in that the word ‘importance’ is confused with a greater self-importance

and not just a high level of interest.

Table 4.16: Product Involvement: Sign construct with INTR1

INTR1 I attach great importance to popular music concerts. SIGN1 I can tell a lot about a person from the concert he or she attends. SIGN2 That I attend popular music concerts say a lot about me. SIGN3 My attendance to popular music concerts gives others a glimpse of who I am.

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The merging of interest and sign may also be attributed to the close relationship

between personality (sign) and interest. A number of studies have examined this

relationship and reported overlaps and shared dimensions between the constructs

(Larson and Borgen, 2002; Schneider, Ryan, Tracey and Rounds, 1996). Gursoy and

Gavcar (2003) justify the shared variance between pleasure/interest (which they

identified as a merged construct) and sign for their international leisure tourists’

involvement profile, as a consequence of the overlap between interest and

personality (sign). Individuals who have a high level of interest in popular music

concerts may also possess a personality where music and concert attendance says a

lot about who they are.

(2) Dropping out of other interest items

In relation to the third interest item (INTR3), which caused difficulties for the 3, 4

and 5-factor models in this study, Rodgers and Schneider (1993) also found this item

problematic. For them, this interest item would either have loadings larger than 0.40

on factors other than interest or pleasure and for other applications would not have

an appreciable loading on either interest or pleasure (as was found in this study).

The wording used for this item in Rodgers and Schneider’s (1993) study was

“____________ leaves me totally indifferent”, which was modified to “I couldn’t care

less about attending popular music concerts” for this study. Rodgers and Schneider

(1993) suggested that the clarity or meaning of the term “indifferent” may have been

lost in the French to English translation of the CIP scale and therefore affects the

performance of this item. In reference to the current study, all respondents had

attended a popular music concert within the last six months of completing the

survey; therefore they obviously had some degree of interest in relation to popular

music concert attendance, which may have also caused inconsistencies and

confusion in responses.

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The remaining interest item (INTR2) originally loaded with the pleasure items, but

during the modification stage of the 3-factor model, this item was completely

removed. Results from past research have shown that the pleasure and interest

facets often merge in practice (aggregated 10 product categories, Jain and Srinivasan,

1990; perfume, clothing, electronic equipment, audio recordings, cars, Rodgers and

Schneider, 1993; shoes/sneakers, Quester and Lim, 2003). However, Gabbott and

Hogg (1999) in their study utilising the CIP scale for service products (which

included services such as credit cards, film, hotel, hairdresser, dry cleaner and

solicitor), identified a clear distinction between pleasure and interest. It is important

to note though, that when performing the factor analysis on the results for these

services, the authors used the whole dataset (that is, all the services combined) to

generate their results. It could be argued that the interest and pleasure an individual

may show in a solicitor may be very different to the interest and pleasure one might

have with a more hedonic service such as going to see a film. An individual may have

a very high interest in seeing films and it would make sense that they would also find

the film very pleasurable. On the other hand, an individual may have a very high

interest in obtaining the services of a solicitor for some important reason, but it is

highly doubtful that obtaining a solicitor is ‘pleasurable’ and ‘like giving a gift to

yourself’ which the items for the pleasure facet suggest. Therefore it is argued that

the aggregation of these very different services may have allowed Gabbott and Hogg

(1999) to obtain results that showed a clear distinction between interest and

pleasure for service goods. This point was actually shown by the authors in a second

study used to profile consumer involvement for each of the service products in

relation to the five antecedents of involvement. These profiling results show that

indeed, entertainment services such as film provide much higher interest, pleasure

and hedonic value than legal services such a solicitor. In fact, the amount of pleasure

reported for film was 3.6 times higher than the pleasure of obtaining a solicitor.

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On examination of the wording of INTR2 (see Table 4.17 below), it is evident that for

popular music concerts, interest and pleasure would appear to be indistinguishable.

That is, if an individual is interested in popular music concert attendance, they also

enjoy attending popular music concerts and find them pleasurable.

Table 4.17: Product Involvement: Original Pleasure construct with INTR2

INTR2 Popular music concerts interest me a lot. PLSR1 I really enjoy attending popular music concerts. PLSR2 Whenever I attend a popular music concerts, it is like giving myself a gift. PLSR3 Attending popular music concerts is pleasurable.

Pleasure and interest dimensions have also been found to be synonymous in other

studies in the recreation, leisure and tourism context (Dimanche et al, 1991, 1993;

Jamrozy et al, 1996; Gursoy and Gavcar, 2003). It is possible, that for popular music

concerts, it may be hard to distinguish an individual’s interest and pleasure in

concert consumption due to the already hedonic nature of popular music concerts,

and the nature of music involvement itself. To derive pleasure from a music related

service product, it makes sense that one must first have an interest in music.

Failure to make distinctions between the interest and pleasure gained from a

product has been found in a study conducted by Rodgers and Schneider (1993), who

found a merging of interest and pleasure items into a single factor on every single

application of the CIP across 11 product categories. They suggested that for US

consumers (as opposed to French consumers in early involvement studies by

Laurent and Kapferer), interest and pleasure were indistinguishable from one

another and the dimensionality of the multidimensional CIP scale may be subject to

cultural variations. Therefore another possible explanation is that similar cultural

variations exist between French and Australian consumers.

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(3) Disappearance of the Risk Importance Dimension

For an explanation for the disappearance of the ‘Risk Importance’ construct it is

beneficial to examine the wording of the items for this construct (Table 4.18).

Table 4.18: Original Risk Importance facet

MPRT1 When I choose a concert to attend, it is not a big deal if I make a mistake. MPRT2 I get annoyed when I attend a concert that doesn't meet my needs. MPRT3 I would be upset if, after I attended a concert, I found I had made a poor choice.

The inconsistencies associated with these items may be more to do with the nature

of concert attendance than any ambiguities in the wording or meaning of the items.

Individuals, who attend concerts, attend for many different reasons (as shown in

Study 2). Whilst the primary motivation to attend a popular music concert may be to

see a particular performer live, there are also many other reasons for an individual to

be motivated to attend a popular music concert. Although there may be perceived

risk in choosing the best concert to attend, what would constitute a ‘poor choice’

(MPRT3) or a ‘mistake’ (MPRT1) when it comes to popular music concerts? When

would a popular music concert not meet an individual’s needs (MPRT2)?

Irrespective of whether the chosen concert was the best, individuals still have had a

night away from the kids or the norm (escape); have had the chance to socialise and

also the opportunity to engage in uninhibited behaviour, to name some motivations.

More needs to be known about what constitutes a ‘good’ concert before any other

conclusions might be drawn about these items. However, the findings related to risk

importance are consistent with Gabbott and Hogg (1999) who found that

entertainment services (such as film) score much lower on the risk importance facet

then non entertainment services.

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Final thoughts on the Product Involvement Construct

The findings of this section on product involvement suggest that consumers think

about attendance at popular music concerts in terms of three dimensions: Pleasure,

Sign Value and Risk Probability. Further, Australian consumers perceive little

distinction between interest and pleasure, that is, they are interested in popular

music concerts because they provide them with pleasure. Interest also seems to be

connected to the way in which a person expresses one’s self, so popular music

concerts are not only interesting and pleasurable, but they are also meaningful to

the consumer. Lastly, consumers recognise that there is some perceived probability

of making a poor choice when it comes to buying tickets to popular music concerts

and choosing to attend popular music concerts over other activities (risk

probability). The fact that the ‘Risk Importance’ dimension drops out, however,

indicates a lack of internal consistency, and it could be that the items may have

caused confusion for the respondents. One possible explanation may reside in

confusion regarding perceptions of negative consequences concerning concert

attendance. That is, whilst there is a probability of making a poor choice, there is no

perceived importance placed on the potential negative consequences associated with

the poor choice of a popular music concert.

First Order versus Second Order Model

Second order models can provide a more parsimonious and interpretable model

than first order models with correlated factors. First order models can be more

suitable when there are lower order factors that are substantially correlated and a

higher order factor is hypothesized to account for the relationships among the lower

order factors (Chen, West and Sousa, 2006). Therefore, first order and second order

versions of the product involvement model were tested to ensure best representation

of the construct in the final structural model. As can be seen in Figure 4.2, the first

order model showed strong correlations (0.52 – 0.57) between the three dimensions

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of product involvement; sign value, risk probability and pleasure. These correlations

suggested the presence of a second order factor (Byrne, 2010); consistent with the

theory that product involvement is a multifaceted construct. The second order

model was therefore constructed and the results compared with the first order

analysis.

Figure 4.2: Product Involvement – First order measurement model

The fit of a second order structure can only be statistically tested if four or more first

order factors are hypothesized (Chen, West and Sousa, 2006). That is, for the three

factor model, one more constraint needed to be placed on the model in order for it

to be identified. A strategy termed the critical ratio difference (CRDIFF) method was

employed to resolve the issue of just-identification (Byrne, 2010). This method

produces a list of critical ratios for the pairwise differences among the residual terms

in the model. On implementation, it was found that the risk probability residual and

the pleasure residual were good candidates for the imposition of equality constraints

as their estimated CRDIFF value was not significant, meaning that the difference

between the estimate for the residual for the risk probability parameter and the

pleasure residual were statistically the same. Therefore in order for the second order 129 | P a g e

model to be over identified with one degree of freedom, the variance for the risk

probability residual was held constant with the value for the pleasure residual. An

illustration of the second order product involvement model is shown in Figure 4.3.

Figure 4.3: Product Involvement – Second order measurement model

A comparison of the fit indices is displayed in Table 4.19. All of these fit measures are

essentially the same, and therefore the second order model explains the product

involvement construct well. Therefore, the second order product involvement model

was utilised in the structural model.

Table 4.19: Product Involvement: Fit Comparisons between first and second order measurement models

First Order Second Order df 17 18 χ2 29.808 31.589

CMIN/DF 1.753 1.755 GFI 0.986 0.985 CFI 0.992 0.991


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This section provides the results of exploratory and confirmatory factor analyses for

the fan identification construct. Convergent and criterion validity are also assessed.


As Reysen and Branscombe's (2010) fanship scale has not been tested in other

contexts since its development, the first step of analysis was to ensure that the

relationships among the fan identification scale items were adequate for explaining

an individual’s attachment to the headlining act of the reported popular music

concert. Therefore, exploratory factor analysis was conducted to confirm the one

factor structure of the fan identification scale presented in the literature by Reysen

and Branscombe (2010). As the data was normally distributed (see Appendix K for

normality testing and EFA results), Maximum Likelihood extraction method was

used. Direct Oblimin (oblique) rotation was selected, for if multiple factors emerged

it was likely they would be correlated. As expected, EFA results indicated that there

was one strong underlying factor to the data (see Appendix K).

Confirmatory Factor Analysis

The fan identification scale was subject to CFA using a Maximum Likelihood

extraction. The results of the analysis are provided in Table 4.20. The CFA findings

indicate that the 9-item model fit the data reasonably well, however, the normed

chi-square was outside the accepted 3:1 ratio and the hypothesis of close fit was

rejected (PCLOSE = 0.011).

Modification Indices

Examination of the error covariance terms revealed that there may be

misspecification issues regarding the CFA model for fan identification. A large

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modification index was identified with the pairing of error terms associated with

item 7 and three other items (see p. 101 for items). This misspecification, that is, the

measurement error covariance, may represent an overlap in item content within the

fan identification scale (Byrne, 2010). Item 7 asks respondents whether they strongly

identify with the headlining act, which would create redundancy when the entire

scale, although worded differently, captures level of identification. Item 7 was

therefore removed and the CFA re-run. This deletion resulted in an improvement of

the fit indices (see Table 4.20).

Table 4.20: Fan Identification: Comparison of fit indices between 9-item and 8-item Measurement Model

Fit Indices 9-item Model 8-item Model df 27 20 χ2 96.306 58.478

CMIN/DF 3.567 2.924 GFI 0.956 0.970 CFI 0.971 0.981


Results for the 8-item model indicate that normed chi-square (CMIN/df = 2.924) was

now within the generally accepted 3:1 ratio for better fitting models (Hair et al, 2010)

and also in contrast to the previous model 9-item, the hypothesis of close fit was not

rejected (PCLOSE = 0.131).

Construct Validity

The next step of the analysis was to determine the validity and reliability of the fan

identification measure.

Convergent Validity

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variance extracted was considered. The standardised parameter estimates for each of

the items were all above 0.5; with seven of the eight (88%) items possessing loadings

above 0.7 (see Table 4.21). Reliability of the constructs was again determined using

the construct reliability (CR) calculation presented by Fornell and Larcker (1981)

which was 0.90, well above the 0.7 reliability criterion.


the constructs, average variance extracted (AVE) was also calculated. The AVE score

was 0.54, above the 0.5 benchmark (Fornell and Larcker, 1981; Hair et al, 2010),

indicating that the items for each of the constructs share a high proportion of

variance (see Table 4.21). Taking into consideration these three measures in

combination (factor loadings, reliability and AVE), convergent reliability of the fan

identification scale was adequate.

Table 4.21: Fan Identification: Evaluation of the Measurement Model - Factor Loadings, AVE Estimates, Construct Reliability and Criterion Validity

Factor Loadings Squared Factor Loadings (λ) Delta (δ) Item_1 0.665 0.442 0.558 Item_2 0.784 0.615 0.385 Item _3 0.728 0.530 0.470 Item _4 0.768 0.590 0.410 Item _5 0.737 0.543 0.457 Item _6 0.719 0.517 0.483 Item _8 0.719 0.517 0.483 Item _9 0.754 0.569 0.431

AVE 0.54

Construct Reliability 0.90

Criterion Validity 0.216 Note: Criterion Validity = Concurrent validity assessed by measuring the correlation between the Fan

Identification scale and the number of times a respondent had been to see the identified artist. Result is

significant at p < 0.001 level.

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Criterion Validity

Criterion validity was examined by assessing the concurrent validity of the fan

identification scale to two criteria: (1) the number of times respondents had seen the

headlining act in concert and (2) how much respondents were willing to pay for a

ticket to see the headlining act. The fan identification scale was significantly

positively correlated with both the number of times respondents had seen the

headlining acting (r = 0.216, p < 0.001) and how much they were willing to pay to see

the headlining act (r = 0.193, p < 0.001). Therefore, consistent with sport marketing

literature and attendance to sporting events, highly identified popular music fans are

more likely to attend more events and pay significantly more for tickets to popular

music concerts (see Trail and James, 2001).

4.4.3 Motivations

The following section details the procedure undertaken to develop an instrument for

accurately measuring motivations for popular music concert attendance, which for

ease of reference has been termed the Concert Attendee Motivation Scale (CAMS).

Procedure

The proposed CAMS was developed from a review of the literature and findings from

Study 2. As noted previously, the items for each motivation were generated by

modifying existing items to a popular music context, where possible. Additional

items were generated from the focus group transcripts for those motivations that

had previously not been given empirical attention in the literature. Academics in

the marketing field were asked to evaluate the scale and a pre-test was conducted

before administration.

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Content Validity (Face Validity)

A panel of four marketing academics and doctoral students were recruited as expert

judges to assess the wording of items for each of the motivation constructs. Items

were assessed for their ability to reflect the motivation construct being measured

and judges were also asked to consider whether the scale covered all the potential

motivations in relation to popular music concert attendance. Slight wording

changes were made to ensure that the items accurately reflected each of the factors.

Instrument Pretesting (Exploratory Factor Analysis)

For the pre-test, an online research company ‘Research Now’ was commissioned to

access Australian consumers who had attended a popular music concert within the

six months prior to data collection (n=60). The questionnaire used in the pre-test

comprised 40 items related to the 10 motivation dimensions identified in Study 2. To

ensure that the relationships among the given set of items were adequate for

explaining the 10 motivation dimensions, an exploratory factor analysis was then

performed on the data.

Maximum Likelihood extraction was used as the data was considered normally

distributed, that is, possessing skewness and kurtosis values within the range of +/-

2(SE), with all variables falling within an absolute value of 2. Applying these rules,

the skewness and kurtosis values are within the range of what is considered a

reasonable approximation to the normal curve (Lomax and Hahs-Vaughn, 2012).

Direct Oblimin (oblique) rotation was selected as the factors (motivations for

attendance) were likely to be correlated (Crompton and McKay, 1997).

As expected, the results showed that there were 10 strong underlying factors to the

data with a Kaiser-Meyer-Olkin (KMO) Measure of Sampling Adequacy of 0.935. The

communalities indicating how much variance can be explained by each of the

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variables was quite low for item 4 (0.249), whilst the majority of all the remaining

items were greater than 0.6 (Allen and Bennett, 2010). According to Francis (2013), a

loading is significant if it is greater than 0.3, provided that at least 50 participants

were used in the study. In this study (n=60), all items loaded strongly on only one

factor, and all loadings were greater than 0.3, except item four, and item 14 which

was just on the cusp at 0.302. Both of these items were removed and the analysis was

re-run. As expected, the results still displayed a strong underlying 10 factor structure,

with a KMO of 0.936 which is considered ‘marvellous’ (Kaiser, 1974), explaining

61.20% of the variance in the sample. Thus the final CAMS comprised 38 items

reflecting 10 dimensions of motivations for popular music concert attendance; Hero

Worship, Aesthetics, Nostalgia, Social Interaction, Uninhibited Behaviour, Physical

Attractiveness, Escape, Status Enhancement, Physical Skills, New and Concert

Specific Music (see Table 4.5, p. 104 for item descriptions). The number of items per

dimension ranged from three to six.

Overall Model Fit

Responses to the 38 motivation items were examined using confirmatory factor

analysis (CFA). As a first pass, the strength of the relationships between the

constructs and the variables was assessed by examining the variance explained in

each variable by the construct (squared multiple correlation, or SMC). On

examination, three of the 38 items had SMC values below 0.3, indicating that these

items were poor measures for their designated construct, and therefore these items

were removed (E4, PS1 and SI5). Modification indices also revealed misspecifications

associated with the pairing of error terms for one of the Status Enhancement items

(SE5). It is believed that this misspecification was related to data redundancy, and

that there was an overlap in meaning regarding the wording of this item and the

other status enhancement items. Therefore, it too was removed.

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The model now comprised 34 items reflecting the 10 motivation dimensions, with

items ranging from two to five on each dimension. Results of CFA reveal that the

model fit the data reasonably well (see Table 4.22).

Table 4.22: Fit Indices – CAMS

CMIN/df 2.166

CFI 0.941

RMSEA 0.048

PCLOSE 0.761

SRMR 0.056

Convergent Validity


variance extracted were considered. Whilst at minimum, factor loadings should be .5

or higher, they should ideally be .7 or higher as the square of a standardised factor

loading represents how much variation in an item is explained by the latent factor,

where a loading of .71 would explain half the variation in the item with the

remaining variance attributed to error (Bagozzi and Yi, 1988; Hair et al, 2000).

Bagozzi and Yi (2012) also suggest that some leeway is possible with large models

that have many latent variables and indicators, as an occasional factor loading as low

as .5 can still yield satisfactory model fit and composite reliability. Therefore the

authors suggest that formulae for reliability need not be applied rigidly to structural

equation models. The factor loadings for each of the items for all constructs, were

all above 0.5, with 28 of the 35 (80%) items possessing loadings above 0.7 (see Table

4.23). Reliability of the constructs was determined using the construct reliability

(CR) calculation presented by Fornell and Larcker (1981). All construct reliability

scores were above 0.7, excluding the constructs for physical skills and concert

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specific music. These constructs gave a reliability estimate of 0.65 and 0.66

respectively (see Table 4.23), which can be considered acceptable provided that

other conditions for construct validity are met (Hair et al, 2010).


the constructs, average variance extracted (AVE) was also calculated. AVE scores

ranged from 0.39 to 0.69, with Physical Skills (0.49) falling just below 0.5 benchmark

(Fornell and Larcker, 1981; Hair et al, 2010) and Concert Specific Music, falling well

below (0.39). All other constructs exceeded the benchmark, indicating that the items

for each of these constructs share a high proportion of variance (see Table 4.23).

Taking into consideration these three measures in combination (factor loadings,

reliability and AVE), it was decided that reliability and AVE measures for Physical

Skills and all other motivation dimensions were adequate, however, the Concert

Specific Music (CSM) dimension could not be improved and would need to be

removed for convergent validity of the CAMS to be acceptable.

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Table 4.23: Motivations: Evaluation of the Measurement Model - Factor Loadings, AVE Estimates, Construct Reliability and Criterion Validity

Note: See Table 4.5, p. 104 for item descriptions.

Modification of CAMS post Convergent Validity examination

Deletion of the Concert Specific Music dimension resulted in little change regarding

the fit indices for the CAMS; therefore the measure was still intact (see Table 4.24).

N A E PA SE PS SI CSM HW UBSquared Factor

Loadings (λ) Delta (δ)

N1 0.879 0.773 0.227N2 0.695 0.483 0.517N3 0.807 0.652 0.348A1 0.857 0.734 0.266A2 0.796 0.634 0.366A3 0.763 0.583 0.417E1 0.776 0.603 0.397E2 0.813 0.661 0.339E3 0.803 0.645 0.355

PA1 0.787 0.619 0.381PA2 0.854 0.729 0.271PA3 0.810 0.656 0.344SE1 0.780 0.609 0.391SE2 0.809 0.654 0.346SE3 0.709 0.502 0.498SE4 0.801 0.642 0.358PS1 0.801 0.642 0.358PS3 0.583 0.340 0.660SI1 0.854 0.730 0.270SI2 0.736 0.542 0.458SI3 0.817 0.668 0.332SI4 0.711 0.506 0.494SI6 0.663 0.440 0.560

CSM1 0.606 0.367 0.633CSM2 0.652 0.426 0.574CSM3 0.617 0.381 0.619HW1 0.807 0.651 0.349HW2 0.844 0.712 0.288HW3 0.833 0.693 0.307HW4 0.836 0.698 0.302UB1 0.858 0.735 0.265UB2 0.853 0.728 0.272UB3 0.765 0.586 0.414UB4 0.623 0.388 0.612

AVE 0.64 0.65 0.64 0.67 0.60 0.49 0.58 0.39 0.69 0.61Construct Reliability

0.84 0.85 0.84 0.86 0.86 0.65 0.87 0.66 0.90 0.86

Factor Loadings

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Table 4.24: Motivations: Comparison of fit indices between Original 10-factor CAMS and final 9-factor CAMS

Fit Indices Original 10-Factor

CAMS 9-Factor CAMS

df 482 398 χ2 1044.012 877.140

CMIN/DF 2.166 2.204 GFI 0.885 0.893 CFI 0.941 0.947



In order to establish that each of the different motivation constructs within the

CAMS was unique and distinct, the average variance extracted for each construct

was compared with the squared correlations of the other constructs (Fornell and

Larcker, 1981; Hair et al, 2010). As shown in Table 4.25, all AVE estimates were larger

than the corresponding squared inter-construct correlation estimates. Therefore

discriminant validity was demonstrated as each item had more variance in common

with its assigned construct than with any other construct.

Table 4.25: Motivations: Discriminant Validity - AVE Estimates and Squared Correlations

Construct AVE N A E PA SE PS SI HW UB

Nostalgia 0.64 - Aesthetics 0.65 0.132 -

Escape 0.64 0.123 0.398 - Physical Attraction 0.67 0.081 0.068 0.043 -

Status Enhancement 0.60 0.135 0.097 0.080 0.594 - Physical Skills 0.49 0.024 0.358 0.298 0.001 0.000 -

Social Interaction 0.58 0.199 0.151 0.181 0.217 0.32 0.045 - Hero Worship 0.69 0.193 0.326 0.295 0.291 0.428 0.129 0.365 -

Uninhibited Behaviour 0.61 0.220 0.102 0.097 0.327 0.527 0.000 0.410 0.404 -

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Criterion Validity

Criterion validity was examined by assessing the concurrent validity of the CAMS

and comparing the factors of the CAMS to two criteria: (1) level of identification with

the headlining act performing at the concert (last concert they attended) and (2)

number of times respondents had seen the headlining act (consistent with sport

marketing literature (see Trail and James, 2001). All motivation factors showed a

significant positive correlation (all p < 0.001) with the 8-item fan identification scale

(α = 0.902), with coefficients ranging from r = 0.282 (Physical Skills) to r = 0.725

(Hero Worship). These correlations make intuitive sense. An individual with a high

level of fan identification is more likely to be motivated to attend a concert to

engage in hero worship behaviour, than they would to only appreciate the physical

skills of an artist. In addition, the motivational factors were significantly positively

correlated (all p < 0.001) with the number of times respondents had seen the

relevant artist in concert. Correlation coefficients ranged from 0.127 (Escape) to 0.314

(Status Enhancement). It makes sense that, an individual attending a concert, in

order to increase their status as a fan would see that artist a higher number of times

than someone just wanting to escape for the night. The significant correlations

between both the fan identification scales and number of concerts attended with the

CAMS provide evidence of concurrent validity. However, predictive validity has not

been established as the data for the fan identification scale, and the number of times

respondents had seen the referenced artist, were collected at the same time as the

motivations data.

First Order versus Second Order Model

In order to determine if motivations could be represented as a higher order factor,

first order and second order versions of the motivations model were tested to ensure

best representation of the construct in the final structural model. Figure 4.4 shows

that the first order model demonstrates some strong correlations (i.e. > 0.5) between

141 | P a g e

the nine motivation dimensions, which may suggest the presence of a higher order

factor (Byrne, 2010). The second order model was therefore constructed and the

results compared with the first order analysis.

Figure 4.4: Motivations – First order measurement model

As stated previously, the fit of a second order structure can only be statistically

tested if four or more first order factors are hypothesized (Chen, West and Sousa,

2006). The motivations construct hypothesizes nine dimensions of motivations and

therefore there were no problems with the second order structure being over

identified. An illustration of the second order model is shown in Figure 4.5.

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Figure 4.5: Motivations – Second order measurement model

A comparison of the fit indices is displayed in Table 4.26. The fit indices have

weakened, however, a CFI value of 0.90 or above is considered good when the

number of observed variables is greater than 30, as is the case for this model (Hair et

al, 2010). In addition, although the second order model is statistically different to the

first order model (∆χ2(27) = 360.157, p < 0.001), the second order model explains a

good proportion of the covariance of the first order model (χ2(398) = 877.140 / χ2

(425) =

1237.297 = 71%). As the second order model is a more parsimonious way of

representing motivations and will simplify the interpretation of the structural

model, it was decided that motivations for popular music concert attendance be

represented as a higher order construct with nine lower order factors.

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Table 4.26: Motivations: Fit Comparisons between first and second order measurement models

First Order Second Order df 398 425 χ2 877.140 1237.297

CMIN/DF 2.204 2.911 CFI 0.947 0.910


4.4.4 Structural Model

The following section of this chapter provides details on the structural model which

was used to predict the hypothesised relationships among the constructs fan

identification, product involvement, motivations and the four dependent variables;

average number of popular music concerts per year, number of popular music

concerts for a specific artist, amount willing to pay, and willingness to travel. As the

theoretical base suggested a particular model, this was initially used as the proposed

structure of the model (for each dependent variable) to test the planned hypotheses.

Slight modifications were then made to this model to produce an alternate model for

modelling the same relationships. The results of both models will be explained and

presented in this section.

Concert Attendance

a) Number of popular music concerts per year, on average

Figure 4.6 illustrates the structural model obtained using covariance based structural

equation modelling in AMOS for the dependent variable; average number of popular

music concerts attended per year. A detailed illustration which includes items for all

the first order latent variables is provided in Appendix O.

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Overall Model Fit

The results of the analysis revealed that the model fit the data reasonably well. The

chi-square statistic was unsurprisingly significant (χ2 = 2058.294, df = 1058), given

that this statistic is particularly sensitive to sample size (Bagozzi and Yi, 2012).

However, the model did produce reasonable goodness-of-fit measures. The normed

chi-square measure (CMIN/df = 2.224) is inside the generally accepted 3:1 ratio for

better fitting models (Hair et al, 2010) and the comparative fit index (CFI) was just

above 0.90 at 0.905. In addition, the RMSEA was 0.049 (CI = 0.047; 0.052) which is

quite low, indicating that the model fit the population well (Browne and Cudeck,

1992). The model also achieved an SRMR of 0.074, where an SRMR greater than 0.1

would suggest a problem with fit (Hair et al, 2010), and the p-value testing the close

fit hypothesis was not rejected (PCLOSE = 0.635).

145 | P a g e

Figure 4.6: Structural model results for concert attendance

Note: *** p < 0.001, ** p <0.01, * p <0.05 Primary values represent a) Average number of concerts per year, and values in brackets represent b) Number of times headlining act is seen

Product Involvement

Fan Identification

Motivations Concert

Attendance 0.713***

-0.131

0.474***

0.234***

0.677***

0.024

R2 = 0.17

R2 = 0.51

R2 = 0.74

PLSR SIGN RP


0.588*** 0.942*** 0.579***

0.525*** 0.599*** 0.563*** 0.628*** 0.794*** 0.385*** 0.724*** 0.899*** 0.749***

(0.374***)

(-0.210*)

(0.230**)

(R2 = 0.19)

146 | P a g e

Results

The standardized path coefficients, along with their t-values and significance are

provided in Table 4.27, as well as the R-squared values for each of the endogenous

variables.

Table 4.27: Average Number of Popular Music Concerts: Structural Model Results

Path Standardised

beta coefficient t-value p-value

R2

Product Involvement 0.508

Fan Identification → Product Involvement 0.713 8.525 <.001

Motivations 0.740

Fan Identification → Motivations 0.677 8.260 <.001

Product Involvement → Motivations 0.234 3.674 <.001

Number of Concerts Per Year 0.165

Fan Identification → Number of Concerts Per Year -0.131 -1.212 0.226

Product Involvement → Number of Concerts Per Year 0.474 4.960 <.001

Motivations → Number of Concerts Per Year 0.024 0.216 0.829

R-squared results for the final model for number of popular music concerts

(displayed in Table 4.27) indicate that this model explains 17% of the variance in

number of popular music concerts attended per year. Fan identification and product

involvement explain a high proportion of the variation in motivations for popular

music concert attendance (74%), and fan identification explains just over half of the

variation in product involvement (51%).

The correlations between the latent variables in the model were inspected to

determine the strength of the relationships between the constructs. The

standardised regression coefficients indicated that there exists a strong, positive and

statistically significant relationship between fan identification and product

involvement, and fan identification and motivations for popular music concert

attendance. The strength of these relationships was approximately the same,

producing beta coefficients of 0.713 (p <0.001) and 0.677 (p <0.001) respectively.

147 | P a g e

Positive, statistically significant relationships exist between product involvement

and motivations for popular music concerts, and product involvement and number

of popular music concerts. Product involvement had a stronger influence on number

of popular music concerts directly (Beta = 0.474, p <0.001), than it did on

motivations for attendance (Beta = 0.234, p <0.001). There was no statistically

significant relationship between fan identification and number of popular music

concerts per year, or motivations for popular music concert attendance and number

of popular music concerts (p >0.05).

Mediation

The conceptual model for number of popular music concerts proposed that

motivations for popular music concerts acts as a mediating variable between fan

identification and number of popular music concerts, and product involvement and

number of popular music concerts. As there was no significant relationship between

the mediator (motivations) and the dependent variable (number of popular music

concerts) (p = 0.829), there was no mediation involving motivations (Baron and

Kenny, 1986).

b) Number of times the individual had seen the identified headlining act

The model explained slightly more of the variation in the number of times an

individual had seen the indicated headlining act (R2 = 0.19) than it did explaining the

number of average concerts attended per year (R2 = 0.17) (see Table 4.28).

Table 4.28: Number of Concerts for Particular Artist: Structural Model Results

Path Standardised

beta coefficient

t-value p-value

R2

Number of Concerts For Particular Artist 0.191

Fan Identification → Number of Concerts for Particular Artist 0.374 3.576 <.001

Product Involvement → Number of Concerts for Particular Artist -0.210 -2.616 0.009

Motivations → Number of Concerts for Particular Artist 0.230 2.146 0.032

148 | P a g e

As opposed to the number of popular music concerts attended on average per year,

when only the indicated artist was considered, fan identification, motivations and

product involvement were all significant in predicting the number of times an

individual had seen the evaluated artist. There was a moderate positive relationship

between fan identification and number of times the headlining act was seen (Beta =

0.374, p <0.001), and a weak positive relationship between motivations for popular

music concert attendance and number of times the headlining act was seen (Beta =

0.230, p <0.01). Product involvement, however, had a weak negative influence on the

number of times the evaluated artist was seen (Beta = -0.210, p <0.05).

Mediation

When the number of times an individual has seen the headlining act is considered as

the dependent variable, results reveal that motivations for popular music concert

attendance may partially mediate the relationship between fan identification and

number of times the headlining act is seen, and product involvement and number of

times the headlining act is seen. Partial mediation is assumed as both fan

identification and product involvement remain significant with the inclusion of

motivations in the model (Baron and Kenny, 1986). Examination of the 95%

confidence interval for the true value for both of the indirect effects indicate that: 1)

the confidence interval for the true value of the mediation effect of motivations

between fan identification and number of times the headlining act was seen,

contains zero, meaning there is no mediation effect, and 2) the confidence interval

for the true value of the mediation effect of motivations between product

involvement and number of times the headlining act was seen does not contain zero,

and therefore indicates partial mediation (Byrne, 2010). The mediation effect

however, is quite small, with an indirect effect of 0.053 (see Table 4.29).

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Table 4.29: Number of Concerts for Particular Artist: Mediating effects of motivations

Path Direct Effect

Indirect Effect

95% CI for Indirect Effect

Total Effect

Type of Mediation

Fan Identification → Number of Concerts Particular Artist 0.374 0.045 (-0.119; 0.220) 0.165 - Product Involvement → Number of Concert Particular

Artist -0.210 0.053 (0.041; 0.427) 0.030 Partial

In addition to the simultaneous mediation analysis using the results from the

covariance based structural equation modelling in AMOS, an individual mediation

analysis was conducted on each of the motivations in order to test the unique effect

of each motivation for popular music concert attendance on the relationship

between product involvement and number of times an individual has seen the

evaluated headlining act.

Whilst Baron and Kenny’s procedure for testing mediation is well cited in the

literature, it has more recently been revealed that Baron and Kenny’s criteria for

testing mediation is flawed and much of the recent literature disputes some of Baron

and Kenny’s tests (Zhao, Lynch & Chen, 2010). New developments regarding the

technicalities of mediation analysis have led methodological scholars to recommend

an alternative approach be used to test mediation (Preacher & Hayes, 2004; Preacher

et al, 2007; Zhao et al, 2010). To specifically address this issue, Preacher, Rucker and

Hayes (2007) have developed a “versatile modelling tool freely-available for SPSS and

SAS that integrates many of the functions of existing and popular published

statistical tools for mediation and moderation analysis” (Hayes, 2012, p. 1), called

PROCESS. This method is now highlighted as superior for calculating mediation

analyses and is now the accepted technique for conducting both mediation and

moderation tests for submission to scholarly journals (Zhao et al, 2010).

Therefore, to test the mediating effect of motivations, the Preacher, Rucker and

Hayes (2007) PROCESS macro bootstrapping procedure (n = 5000, Model 4) was

employed. For descriptive purposes, the PROCESS macro tests the effect of the

independent variable (product involvement) on the mediator (the nine motivations), 150 | P a g e

as well as the effects of the mediator on the outcome variable (number of concerts

for a particular artist). The results are presented in Table 4.30. A result is significant

if the 95% bootstrapped confidence interval for the indirect effect of the interaction

does not include zero. Partial mediation will be present if the direct effect is still

significant and full mediation present when the direct effect of the independent

variable on the dependent variables becomes non-significant due to the inclusion of

the mediating motivation variable.

Table 4.30: Mediating effects of separate motivations on the relationship between

product involvement and number of popular music concerts for particular artist

Motivation Direct Effect

Indirect Effect


Total Effect Type of

Mediation

Nostalgia 0.166 0.079 (0.037; 0.135) 0.013 Partial

Aesthetics 0.156 0.089 (0.024; 0.163) 0.014 Partial

Escape 0.198 0.048 (-0.008; 0.107) 0.010 -

Physical Attraction 0.081 0.164 (0.103; 0.239) 0.013 Full

Status Enhancement 0.081 0.164 (0.104; 0.239) 0.013 Partial

Physical Skills 0.200 0.045 (-0.002; 0.092) 0.009 -

Social Interaction 0.063 0.182 (0.115; 0.266) 0.011 Full

Hero Worship -0.011 0.257 (0.166; 0.358) -0.002 Full Uninhibited Behaviour

0.098 0.147 (0.089; 0.221) 0.014 Full

Results indicate that nostalgia, aesthetics and status enhancement act as partial

mediators between product involvement and number of times the headlining act is

seen. Physical attraction, social interaction, hero worship and uninhibited behaviour

fully mediate the relationship, and escape and physical skills have no influence on

the relationship between product involvement and number of times the headlining

act is seen.

151 | P a g e

Amount willing to pay for tickets

Figure 4.7 illustrates the structural model obtained using covariance based

structural equation modelling in AMOS for the dependent variable; amount willing

to pay for popular music concerts in general. A detailed illustration which includes

items for all the first order latent variables is provided in Appendix O.

Overall Model Fit

Table 4.31 indicates that the model fit the data reasonably well. The chi-square

statistic was again unsurprisingly significant (χ2 = 2358.547, df = 1064). However, all

other fit indices were acceptable.

Table 4.31: Fit Indices – Amount Willing to Pay

CMIN/df 2.217

CFI 0.905

RMSEA 0.049

PCLOSE 0.667

SRMR 0.073

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Product Involvement

Fan Identification

Motivations Amount Willing

to Pay 0.710***

-0.050

-0.046

0.233***

0.679***

0.328**

R2 = 0.07

R2 = 0.50

R2 = 0.74

PLSR SIGN RP


0.571*** 0.960*** 0.567***

0.527*** 0.601*** 0.565*** 0.627*** 0.795*** 0.389*** 0.726*** 0.896*** 0.747***

Figure 4.7: Structural model results for amount willing to pay

Note: *** p < 0.001, ** p <0.01, * p <0.05

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Results


provided in Table 4.32, as well as the R-squared values for each of the endogenous

variables.

Table 4.32: Amount Willing to Pay: Structural Model Results

Path Standardised


R2



Motivations 0.739



Amount Willing to Pay 0.067

Fan Identification → Amount Willing to Pay -0.050 -0.449 0.653

Product Involvement → Amount Willing to Pay -0.046 -0.544 0.587

Motivations → Amount Willing to Pay 0.328 2.810 0.005

R-squared results show that this model explains only 7% of the variation in the

amount consumers are willing to pay for popular music concerts. Results indicate a

moderate, positive, statistically significant relationship between motivations for

popular music concert attendance and the amount people are willing to pay for

popular music concerts (Beta = 0.328, p<0.001). There was no statistically significant

relationship between fan identification and the amount willing to pay for tickets, nor

between product involvement and amount willing to pay for tickets (p>0.05).

Mediation

The conceptual model for amount willing to pay for tickets proposed that

motivations for popular music concerts acts as a mediating variable between fan

identification and amount willing to pay for tickets, and product involvement and

amount willing to pay for tickets. The results of this model reveal that motivations 154 | P a g e

for popular music concert attendance fully mediates the relationship between fan

identification and amount willing to pay for tickets, and also the relationship

between product involvement and amount willing to pay for tickets. Full mediation

occurred as the relationship between fan identification and amount willing to pay

for tickets, and product involvement and amount willing to pay for tickets became

insignificant when motivations for popular music concert attendance were included

in the model. Additionally, the 95% confidence interval for the true value for both of

the indirect effects also did not contain zero, which indicated a significant mediation

effect. The direct, indirect and total effects are included in Table 4.33. Motivations

for popular music concerts had the strongest mediating effect on the relationship

between fan identification and amount willing to pay for tickets with a mediation

effect of 0.215. Whilst motivations for concert attendance also fully mediated the

relationship between product involvement and amount willing to pay for tickets

significantly, the mediation effect was quite small in comparison, with a mediation

effect of 0.076.

Table 4.33: Amount Willing to Pay: Mediating effects of Motivations

Path Direct Effect

Indirect Effect


Total Effect

Type of Mediation

Fan Identification → Amount Willing to Pay -0.050 0.215 (0.079; 0.404) 0.165 Full

Product Involvement → Amount Willing to Pay -0.046 0.076 (0.030; 0.141) 0.030 Full

In addition to the simultaneous mediation analysis using the results from the

covariance based structural equation modelling in AMOS, an individual mediation

analysis was conducted on each of the motivations in order to test the unique effect

of each motivation for popular music concert attendance on the relationship

between fan identification and amount willing to pay, and product involvement and

amount willing to pay. Again, in order to achieve this, the Preacher, Rucker and

Hayes (2007) PROCESS macro bootstrapping procedure (n = 5000, Model 4) was

155 | P a g e

employed. The results are presented in Table 4.34 for fan identification and Table

4.35 for product involvement.

Table 4.34: Mediating effects of separate motivations on the relationship between fan

identification and amount willing to pay


Indirect Effect



Mediation



Escape 0.153 0.050 (0.008; 0.110) 0.008 Partial

Physical Attraction 0.186 0.017 (-0.028; 0.062) 0.003 -


Physical Skills 0.162 0.042 (0.020; 0.075) 0.007 Partial

Social Interaction 0.130 0.074 (0.020; 0.144) 0.010 Partial

Hero Worship 0.158 0.045 (-0.033; 0.133) 0.007 -

Uninhibited Behaviour 0.170 0.034 (-0.018; 0.086) 0.006 -

Table 4.34 shows that nostalgia, aesthetics, escape, status enhancement, physical

skills and social interaction act as partial mediators between fan identification and

amount willing to pay.


product involvement and amount willing to pay


Indirect Effect



Mediation


Aesthetics 0.103 0.127 (0.072; 0.210) 0.013 Full

Escape 0.148 0.083 (0.027; 0.154) 0.012 Full

Physical Attraction 0.204 0.027 (0.001; 0.066) 0.006 Partial


Physical Skills 0.153 0.078 (0.040; 0.134) 0.012 Partial

Social Interaction 0.116 0.114 (0.054; 0.191) 0.013 Full

Hero Worship 0.131 0.100 (0.016; 0.198) 0.013 Full Uninhibited Behaviour

0.175 0.055 (0.086; 0.117) 0.010 Partial

156 | P a g e

Table 4.35 shows that nostalgia, physical attraction, status enhancement, physical

skills and uninhibited behaviour partially mediate the relationship between product

involvement and amount willing to pay, whilst aesthetics, escape, social interaction

and hero worship fully mediate the relationship.


Figure 4.8 illustrates the structural model obtained using covariance based structural

equation modelling in AMOS for the dependent variable; willingness to travel. A

detailed illustration which includes items for all the first order latent variables is

provided in Appendix O.

Overall Model Fit

Table 4.36 indicates that the model fit the data reasonably well. The chi-square

statistic was again significant (χ2 = 2466.277, df = 1158), however all other fit indices

were acceptable.

Table 4.36: Fit Indices – Willingness to Travel

CMIN/df 2.130

CFI 0.912

RMSEA 0.047

PCLOSE 0.944

SRMR 0.071

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Figure 4.8: Structural model results for willingness to travel

Note: *** p < 0.001

Product Involvement

Fan Identification

Motivations Willingness to

travel 0.709***

0.325***

-0.046

0.231***

0.679***

0.414***

R2 = 0.49

R2 = 0.50

R2 = 0.74

PLSR SIGN RP


0.570*** 0.961*** 0.567***

0.522*** 0.596*** 0.557*** 0.630*** 0.797*** 0.379*** 0.727*** 0.895*** 0.747***

158 | P a g e

Results


provided in Table 4.37, as well as the R-squared values for each of the

endogenous variables.

Table 4.37: Willingness to Travel: Structural Model Results

Path Standardised


R2



Motivations 0.738



Willingness to Travel 0.491

Fan Identification → Willingness to Travel 0.325 3.581 <.001

Product Involvement → Willingness to Travel -0.012 -0.180 0.857

Motivations → Willingness to Travel 0.414 4.184 <.001

R-squared results for the final model for willingness to travel to popular music

concerts (displayed in Table 4.37) indicate that this model explains 49% of the

variation in the amount consumers are willing to pay for popular music concerts.

Results indicate a moderate, positive, statistically significant relationship

between motivations for popular music concert attendance and the distance

consumers are willing to travel to popular music concerts (Beta = 0.414, p<0.001).

There also exists a moderate, positive, statistically significant relationship

between fan identification and willingness to travel (Beta = 0.325, p<0.001) There

was no statistically significant relationship between product involvement and

willingness to travel (p>0.05).

Mediation

The results of this model reveal that motivations for popular music concert

attendance partially mediates the relationship between fan identification and

willingness to travel, and fully mediates the relationship between product

159 | P a g e

involvement and willingness to travel. Partial mediation between fan

identification and willingness to travel occurred as the relationship was

weakened as a result of the inclusion of motivations in the model; however, the

relationship between fan identification and willingness to travel is still

significant. Full mediation occurred between product involvement and

willingness to travel as the relationship between these two latent variables

becomes insignificant when motivations for popular music concert attendance

were included in the model. The 95% confidence interval for the true value for

the indirect effects also did not contain zero, which indicated a significant

mediation effect (see Table 4.38). Motivations for popular music concerts had the

strongest mediating effect on the relationship between fan identification and

willingness to travel with a mediation effect of 0.281. Whilst motivations for

concert attendance fully mediated the relationship between product involvement

and willingness to travel significantly, the mediation effect was quite small in

comparison, with a mediation effect of 0.096.

Table 4.38: Willingness to Travel: Mediating effects of Motivations

Path Direct Effect

Indirect Effect


Total Effect

Type of Mediation

Fan Identification → Willingness to Travel 0.325 0.281 (0.224; 0.468) 0.606 Partial

Product Involvement → Willingness to Travel -0.012 0.096 (0.047; 0.166) 0.084 Full

Once again, in addition to the simultaneous mediation analysis, an individual

mediation analysis was conducted on each of the motivations in order to test the

unique effect of each motivation on the relationship between fan identification

and willingness to travel, and product involvement and willingness to travel. The

Preacher, Rucker and Hayes (2007) PROCESS macro bootstrapping procedure (n

= 5000, Model 4) was again employed. The results are presented in Table 4.39 for

fan identification and Table 4.40 for product involvement.

The results indicate that nostalgia, aesthetics, physical attraction, status

enhancement, social interaction, hero worship and uninhibited behaviour

160 | P a g e

partially mediate the relationship between fan identification and willingness to

travel (see Table 4.39).


fan identification and willingness to travel


Indirect Effect



Mediation



Escape 0.701 0.023 (-0.015; 0.064) 0.016 -



Physical Skills 0.721 0.003 (-0.024; 0.027) 0.002 -


Hero Worship 0.532 0.192 (0.104; 0.286) 0.102 Partial

Uninhibited

Behaviour 0.543 0.181 (0.124; 0.251) 0.100 Partial

Results also indicate that all motivations, excluding physical skills, partially

mediate the relationship between product involvement and willingness to travel

(see Table 4.40).


product involvement and willingness to travel


Indirect Effect



Mediation



Escape 0.532 0.113 (0.051; 0.184) 0.060 Partial



Physical Skills 0.607 0.038 (-0.009; 0.091) 0.023 -


Hero Worship 0.199 0.446 (0.349; 0.554) 0.089 Partial

Uninhibited

Behaviour 0.384 0.261 (0.185; 0.354) 0.100 Partial

161 | P a g e

4.4.5 Difference Tests

Motivations and Gender

Based on findings from motivation studies in sport, motivations for popular

music concert attendance were hypothesised to differ between males and

females. In order to test this, independent samples t-tests were conducted.

Results indicated that females (M(females) = 2.36, S.D. = 1.13) were more likely to be

motivated to attend popular music concerts based on the physical attractiveness

of the artist (t(500) = 2.145, p < 0.05), than males (M(Males) = 2.14, S.D. = 1.07). There

were no other significant differences in motivations for popular music concert

attendance between males and females.

4.5 Results of Hypothesis Tests

In total, 19 hypotheses were formulated to test the relationships hypothesized in

the conceptual model. Tables 4.41 and 4.42 display the proposed hypotheses and

findings. The majority of hypotheses were supported. Neither product

involvement nor fan identification was directly related to the amount people

were willing to pay for popular music concert tickets, providing no support for

H2 or H6. These relationships were mediated by motivations for popular music

concert attendance. Fan identification did not impact the average number of

popular music concerts attended per year as hypothesized (H5a), nor did

motivations mediate this relationship (H16a). In fact, motivations did not have a

direct effect on average number of popular music concerts per year (H10a);

therefore it did not mediate the relationship between product involvement and

average number of popular music concerts per year (H13a). Product involvement

had no direct influence on willingness to travel (H3) and although it was

hypothesised there would be no relationship between product involvement and

number of popular music concerts attended for a particular artist (H1b), a

significant negative relationship was actually found. Contrary to H18, motivations

only partially mediated the relationship between fan identification and 162 | P a g e

willingness to travel. Further discussion of the results is presented in the

following section.

Table 4.41: Hypotheses 1 – 12 and summary of results

Number Hypothesis Supported

H1a Product involvement is positively related to average number of popular music concerts per year

YES

H1b Product involvement is not related to number of popular music concerts by a particular artist

NO

H2 Product involvement is positively related to amount willing to pay for tickets to popular music concerts.

NO

H3 Product involvement is positively related to willingness to travel.

NO

H4 Product involvement is positively related to motivations for popular music concert attendance.

YES

H5a Fan identification is positively related to average number of popular music concerts per year

NO

H5b Fan identification is positively related to number of popular music concerts by a particular artist

YES

H6 Fan identification is positively related to amount willing to pay for tickets to popular music concerts.

NO

H7 Fan identification is positively related to willingness to travel. YES

H8 Fan identification is positively related to product involvement. YES

H9 Fan identification is positively related to motivations for popular music concert attendance.

YES

H10a Motivations for popular music concert attendance are related to average number of popular music concerts per year

NO

H10b Motivations for popular music concert attendance are related to number of popular music concerts by a particular artist

YES

H11 Motivations for popular music concert attendance are related to amount willing to pay for tickets

YES

H12 Motivations for popular music concert attendance are related to willingness to travel.

YES

163 | P a g e

Table 4.42: Hypotheses 13 - 19 and summary of results

Number Hypothesis Supported

H13a Motivations mediate the relationship between product involvement and average number of popular music concerts per year

NO

H13b Motivations mediate the relationship between product involvement and number of popular music concerts by a particular artist

PARTIAL

H14 Motivations mediate the relationship between product involvement and amount willing to pay for tickets.

YES

H15 Motivations mediate the relationship between product involvement and willingness to travel.

YES

H16a Motivations mediate the relationship between fan identification and average number of popular music concerts per year

NO

H16b Motivations mediate the relationship between fan identification and number of popular music concerts by a particular artist

YES

H17 Motivations mediate the relationship between fan identification and amount willing to pay for tickets.

YES

H18 Motivations mediate the relationship between fan identification and willingness to travel.

PARTIAL

H19 Motivations for popular music concert attendance will differ between males and females.

YES

4.6 Discussion of Results

This section interprets the findings from Study 3 and offers an explanation for the

results for each of the hypothesis tests. Fan identification, product involvement

and motivations will be discussed in regard to their influence on the four

dependent variables; average number of popular music concerts per year, number

of concerts for a particular artist, amount willing to pay for tickets, and

willingness to travel. Details regarding the mediating role of motivations between

fan identification, product involvement and the four dependent variables will also

be provided. All results related to fan identification will be addressed first,

followed by product involvement, motivations and discussion of mediating

effects. Explanation of results will conclude with tests for differences and a

164 | P a g e

chapter summary will be provided. Evaluations of the hypotheses tested are

considered in their relevant sections.


In this study, fan identification was hypothesised to be positively related to:

• Product involvement (H8);

• Motivations for popular music concert attendance (H9);

• Number of popular music concerts attended per year (H5);

• Amount willing to pay for popular music concerts (H6); and

• Willingness to travel to multiple cities, states and countries to

attend popular music concerts (H7).

Fan identification in relation to popular music fans was defined as a personal

connection with the artist or band (adapted from Reysen and Branscombe, 2010),

and the construct was measured with 8-items from Reysen and Brancombe’s

(2010) fanship scale. Results indicated that fan identification was positively

related to product involvement and motivations for popular music concerts. In

reference to the dependent variables in the study, fan identification had no direct

influence on the number of popular music concerts attended per year, nor was

the amount individuals were willing to pay for concert tickets. Fan identification

however was positively related to the number of popular music concerts an

individual will attend for a specific artist and was also positively related to

willingness to travel. The relationship between fan identification and amount

willing to pay for tickets was however, mediated by motivations for popular

music concert attendance.

H8: Fan identification is positively related to product involvement

The results of the analysis indicate that there is a strong positive relationship

between fan identification and product involvement, meaning that fans with a

higher level of fan identification are considerably more likely to consider popular

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music concerts as more important to them, than fans with lower levels of fan

identification.

H9: Fan identification is positively related to motivations for popular music

concert attendance

Of the nine motivations for popular music concert attendance identified in Study

2, a highly identified fan should theoretically possess strong correlations with all

motivations, excluding perhaps escape and uninhibited behaviour. Escape may

not be a significant motivator for highly identified fans as the level of attachment

to the artist would be driving attendance, and highly identified fans may not

want to engage in uninhibited behaviour (such as drinking and moshing) as to

not miss any of the concert (as findings from the focus groups in Study 2 would

suggest). The results of the analysis indicate that there is a strong positive

relationship between fan identification and motivations for popular music

concert attendance, meaning that fans with a higher level of fan identification

will have stronger motivations for attending popular music concerts. In fact, post

hoc investigations indicate that highly identified fans are most likely to be

motivated to attend popular music concerts for hero worship (r = 0.723, p <0.001),

status enhancement (r = 0.556, p <0.001), and uninhibited behaviour (r = 0.542, p

<0.001) than motivations such as physical skills (r = 0.289, p <0.001), nostalgia (r

= 0.394, p <0.001), and escape (r = 0.409, p <0.001) (see Table 4.43). Given the

findings from the focus groups, the presence of uninhibited behaviour in the top

motivations is surprising. It may be, however, that there exists a close

relationship between hero worship and uninhibited behaviour. Earl (2001) argues

that the act of hero worship with regard to live performances involves getting

physically close to famous people and gaining ‘trophies’ such as guitar picks from

artists. In order to do this, fans would typically have to be up close, near the front

row, amid all the action of the mosh pit. Earl (2001) also contends that hero

worship is a form of homage to an artist, and therefore it is likely that

uninhibited behaviour may form a ritual part of tribute and praise to an artist, for

a highly identified fan.

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Table 4.43: Correlations between Fan Identification and Motivations

Motivation Pearson Correlation Coefficient

Hero Worship .723**

Status Enhancement .556**

Uninhibited Behaviour .542**

Social Interaction .497**

Aesthetics .479**

Physical Attraction .443**

Escape .409**

Nostalgia .394**

Physical Skills .289**

Note: ** p <0.001

H5: Fan identification is positively related to popular music concert attendance

Results related to this hypothesis are consistent with findings in the sporting

literature. Wann and Branscombe (1993) found that highly identified fans attend

more home and away games for a particular sporting team. Findings from this

research suggest that music fans behave similarly, that is, fans with higher levels

of fan identification will attend a higher number of concerts for an artist with

whom they have a close attachment. However, contrary to Wann and

Branscombe (1993), who suggest that fans with lower levels of fan identification

are the cause of attendance fluctuations, findings related to popular music

concerts indicate that fan identification is not a necessary condition for popular

music concert attendance in general.

H6: Fan identification is positively related to amount willing to pay

Based on the literature regarding sport fans, fan identification was proposed to

have a positive impact on amount willing to pay for popular music concert

tickets, that is, fans with a higher level of attachment to a particular artist would

be willing to pay more for concert tickets. Contrary to Fink et al (2002), level of

fan identification had no direct impact on what people were willing to pay for

popular music concert tickets, and other factors may be better predictors of

amount willing to pay.

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H7: Fan identification is positively related to willingness to travel

Hypothesis 7 tested the influence of fan identification on an individual’s

willingness to travel to multiple cities, states and countries for popular music

concerts. Wann and Branscombe (1993) identified that highly identified sport

fans attend more away games for a sporting team than less identified fans.

Consistent with findings in sport, the results of the analysis indicate a moderate

positive relationship between fan identification and willingness to travel. This

means that highly identified fans are more likely to travel further distances to

popular music concerts than fans with low levels of identification.

Summary

Findings reveal that fan identification has a strong influence on motivations for

popular music concert attendance. Individuals with higher levels of fan

identification are also more likely to have a high level of product involvement

(interest in popular music concerts), and are more likely to travel further

distances, including to other cities, states and countries to attend popular music

concerts. Fan identification has no direct influence on the average number of

popular music concerts an individual will attend per year, nor does it influence

the amount an individual is willing to pay for popular music concert tickets. Fan

identification however, did influence the number of times an individual will go to

see a specific artistic. This means that whilst highly identified fans may attend

more concerts for the artist/band with whom they have a high level of

attachment, a high level of fan identification with any artist will not result in an

increase of popular music concert attendance in general. The mediating effect of

motivations will be discussed in the mediating effects section later in this

chapter.


In this study, product involvement was hypothesised to be positively related to:

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• Motivations for popular music concert attendance (H4);





Product involvement in relation to popular music concerts was defined as the

level of interest, arousal, or emotional attachment that a consumer has with a

product or service (Rothschild, 1984; Bloch, 1986), and the construct was

measured by adapting items from, and extending Laurent and Kapferer’s (1985)

CIP scale. Results indicated that product involvement was positively related to

motivations for popular music concerts. In reference to the dependent variables

in the study, product involvement was only positively related to the number of

popular music concerts attended per year, on average and actually had a negative

influence on the number of popular music concerts an individual will attend for

one artist in particular. Product involvement had no direct influence on amount

willing to pay for tickets, nor willingness to travel. These two latter relationships

however, were mediated by motivations for popular music concert attendance.

H4: Product involvement is positively related to motivations for popular music

concert attendance

Of the nine motivations for popular music concert attendance identified in Study

2, a concert goer with a high level of product involvement should possess strong

correlations with all motivations, excluding those specifically related to the artist

performing the concert. The results of the analysis indicate that there is a weak

positive relationship between product involvement and motivations for popular

music concert attendance, meaning that concert attendees with a higher level of

product involvement will possess slightly stronger motivations for attending

popular music concerts. In fact, post hoc investigations indicate that concert

goers with high levels of product involvement are more likely to be motivated for

hero worship (r = 0.530, p <0.001), social interaction (r = 0.440, p <0.001), and

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aesthetics (r = 0.542, p <0.001) than motivations such as physical attraction (r =

0.194, p <0.001), nostalgia (r = 0.280, p <0.001), and uninhibited behaviour (r =

0.409, p <0.001) (see Table 4.44). The relationship between product involvement

and hero worship may be explained by the strong relationship between fan

identification and product involvement.

Table 4.44: Correlations between Product Involvement and Motivations

Motivation Pearson Correlation Coefficient

Hero Worship .530**

Social Interaction .440**

Aesthetics .419**

Escape .388**

Status Enhancement .354**

Physical Skills .341**

Uninhibited Behaviour .331**

Nostalgia .280**

Physical Attraction .194**

Note: ** p <0.001

H1: Product involvement is positively related to popular music concert

attendance

Product involvement was proposed to have no impact on the number of repeat

times an individual will see a particular artist. The results of the analysis indicate

that there is a weak negative relationship between product involvement and

number of concerts for a particular artist. Concert goers with a high level of

product involvement possess a high level of interest in concert going, but as a

high level of product involvement does not involve an attachment to a particular

artist performing a concert, then it is unlikely that an individual with no

attachment to an artist would attend a concert for that same artist, multiple

times. Results indicate that as product involvement increases, the number of

concerts attended for a particular artist actually decreases. Therefore, whilst

individuals with a high level of product involvement will attend a significantly

higher number of concerts per year, they are unlikely to attend multiple shows

for the same artist.

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H2: Product involvement is positively related to amount willing to pay

The results of the analysis indicate that there is no significant relationship

between product involvement and the amount willing to pay for popular music

concert tickets. Therefore, level of product involvement, nor level of fan

identification have a direct impact on what people were willing to pay for tickets,

and other factors may be better predictors of amount willing to pay.

H3: Product involvement is positively related to willingness to travel

The results of the analysis indicate there is no significant relationship between

product involvement and willingness to travel. This means that it doesn’t matter

how high one’s level of interest in popular music concert attendance is, their level

of interest is unrelated to their willingness to travel to events, suggesting that

there may be other factors involved in willingness to travel.

Summary

Findings related to product involvement reveal that product involvement is a

strong predictor of the number of popular music concerts an individual will

attend on average, in a one year period, that is, people with a higher level of

product involvement will attend more popular concerts per year on average. An

individual possessing a higher level of product involvement however is less likely

to see a specific artistic multiple times. Product involvement also has a weak

influence on motivations for popular music concert attendance. Product

involvement has no direct influence on the amount an individual is willing to pay

for popular music concert tickets, nor does it directly influence the distance an

individual is willing to travel to a concert. The relationship between product

involvement and amount willing to pay, and product involvement and

willingness to travel however, are both mediated by motivations for popular

music concert attendance and will be discussed in the mediating effects section

(section 4.6.4, p. 174)

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4.6.3 Motivations

In this study, motivations for popular music concert attendance were

hypothesised to be positively related to:





Motivations for popular music concert attendance are defined as “an internal

factor that arouses, directs, and integrates a person’s behaviour” (Murray, 1964,

p.7), and the construct was measured using the Concert Attendee Motivation

Scale (CAMS) which was developed as a result of this research (specifically the

findings from Study 2 and Study 3). Motivations for popular music concert

attendance were found to positively influence the amount consumers are willing

to pay for popular music concerts (H11), and had even a stronger influence on

willingness to travel (H12). Motivations for popular music concert attendance,

however, did not impact on the number of concerts an individual would attend a

year, on average, but were found to influence the number of popular music

concerts an individual will attend for a specific artist.

H10: Motivations are related to popular music concert attendance

Whilst motivations have no impact on the number of concerts an individual

chooses to attend per year, results indicate that motivations for attendance do

impact the number of concerts an individual will choose to attend for the same

artist. Interestingly, post hoc analyses reveal that physical attraction is the only

motivation that is likely to significantly increase the number of times an

individual will see the same artist (Beta = 0.141, t(9) = 2.616, p = 0.009). This

finding may be explained by celebrity endorsement literature. Research has

demonstrated that an attractive celebrity is seen to be more persuasive (Aaker

and Myers 1987; Eagly and Chaiken 1993), where by an attractive celebrity has

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been shown to increase attitudes towards an advertisement (Kamins 1990) and

product (Priester and Petty 2003), and also generate greater intentions to buy a

brand (Ohanian 1991). A communicator’s physical attractiveness has also been

found to have an influence on behaviour (Dion & Stein, 1978, Debevec & Kernan,

1984), where a physically attractive communicator need not rely on supporting

arguments to persuade an audience (Norman, 1976). Therefore, with popular

music artists seen as a celebrity themselves, it is reasonable to expect that a

physically attractive artist, with little marketing effort, generate greater purchase

intention with regards to tickets sales to their concert. Research related to

celebrity endorsers and physically attractive communicators also suggests that

the inclusion of the artist in advertising communications for a concert may have a

positive impact on concert ticket sales.

H11: Motivations are related to amount willing to pay

The results of the structural model analysis indicate that motivations for

attendance do have a moderate positive influence on amount willing to pay. Post

hoc analyses also reveal that those motivated to attend popular music concerts

for Aesthetics (Beta = 0.117, t(9) = 2.045, p = 0.041) and Physical Skills (Beta = 0.105,

t(9) = 2.065, p = 0.039) are willing to pay significantly higher amounts for popular

music concert tickets than those motivated by Nostalgia, Escape, Physical

Attraction, Status Enhancement, Social Interaction, Hero Worship and

Uninhibited Behaviour (p >0.05).

H12: Motivations are related to willingness to travel

Individuals with particular motivations for attending popular music concerts may

be likely to travel further to popular music concerts. The results of the structural

model analysis indicate that motivations for attendance have a moderate positive

influence on willingness to travel. Post hoc analyses also reveal that those

motivated to attend popular music concerts for Uninhibited Behaviour (Beta =

0.237, t(9) = 4.595, p < 0.001), Hero Worship (Beta = 0.232, t(9) = 4.282, p < 0.001)

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and Aesthetics (Beta = 0.110, t(9) = 2.353, p = 0.019) are willing to travel

significantly further in order to attend popular music concerts than those

motivated by Nostalgia, Escape, Physical Attraction, Status Enhancement,

Physical Skills and Social Interaction (p >0.05).

Summary

Table 4.45 summarises the direct influence of motivations on the dependent

variables. Specifically, those individuals motivated by aesthetics and physical

skills are significantly more likely to pay more for concerts and those motivated

by aesthetics, hero worship and uninhibited behaviour are significantly more

likely to travel further distances to attend popular music concerts. Motivations

have no direct influence on the number of popular music concerts an individual

will attend in a one year period, but an individual attending for the physical

attraction of the artist is more likely to see that same artist multiple times.

Table 4.45: Motivations Positively Influencing the Dependent Variables Dependent Variable Motivations

Average Number of Concerts per Year None

Number of Concerts per Artist Physical Attraction

Amount Willing to Pay Aesthetics

Physical Skill

Willingness to Travel Aesthetics

Hero Worship


4.6.4 Mediating Effects

In this study, motivations for popular music concert attendance were

hypothesised to mediate the relationship between:

• Product involvement and concert attendance (H13);

• Product involvement and amount willing to pay (H14);

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• Product involvement and willingness to travel (H15);

• Fan identification and concert attendance (H16);

• Fan identification and amount willing to pay (H17); and

• Fan identification and willingness to travel (H18).



Whilst product involvement directly influences the number of popular music

concerts attended, there is no direct relationship between motivations for

attendance and number of popular music concerts, therefore motivations does

not mediate the relationship between product involvement and number of

popular music concerts attended.

Product involvement was found to have a direct influence on the number of

concerts an individual will attend for a specific artist, that is, the higher the level

of product involvement, the lower the number of concerts an individual will

attend for the same artist. Motivations for popular music concert attendance

were also found to partially mediate the relationship between product

involvement and number of concerts for a specific artist. This means that

motivations for attendance are actually accounting for some of the relationship

between product involvement and number of popular music concerts for a

specific artist.

Specifically, physical attraction, social interaction, hero worship and uninhibited

behaviour fully mediate the relationship between product involvement and

number of concerts attended for a specific artist, meaning that individuals

motivated for these reasons are more likely to attend multiple concerts for a

particular artist irrespective of their level of product involvement. The presence

of nostalgia, aesthetics and status enhancement (partial mediators) will weaken

the effect of product involvement, that is, its direct influence on the number of

popular music concerts for a particular artist. Therefore, product involvement

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will only reduce the number of times an individual will see the same artist if that

person was motivated to attend one of the artist’s concerts for escape reasons, or

that they were motivated by the physical skills of the artist.



Product involvement does not directly influence the amount an individual is

willing to pay for popular music concerts in the structural model; however,

motivations for popular music concert attendance were found to fully mediate

the relationship between product involvement and amount willing to pay. That

is, product involvement may be related to amount willing to pay (as was

originally hypothesised), but when motivations are included in the model, this

relationship is no longer significant. This finding suggests that motivations

transmit the possible effect on the relationship between product involvement and

the amount people are willing to pay for tickets.

Specifically, aesthetics, escape, social interaction and hero worship fully mediate

the relationship, meaning that when an individual is motivated for these reasons,

that motivation is the only determinant of what they are willing to pay for tickets

(i.e. product involvement has no direct influence). Nostalgia, physical attraction,

status enhancement, physical skills and uninhibited behaviour only partially

mediate the relationship, meaning that for those individuals attending for these

reasons, their level of product involvement (how much they enjoy the concert

experience) may still have a direct influence on the amount they are willing to

pay.



Product involvement does not directly influence willingness to travel in the

structural model; however, motivations for popular music concert attendance

were found to fully mediate the relationship between product involvement and

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willingness to travel. That is, if we were to examine the influence of product

involvement on willingness to travel, we may find a relationship (as was originally

hypothesised), but when motivations are included in the model, this relationship

is no longer significant. This suggests that motivations account for the

relationship between product involvement and the distance an individual is

willing to travel to a popular music concert. Individually, all motivations partially

mediate the relationship between product involvement and distance willing to

travel, excluding physical skills.



Neither fan identification, nor motivations have a direct impact on the number of

popular music concerts attended per year, and therefore mediation is not

possible.

Motivations also did not mediate the relationship between fan identification and

number of popular music concerts for a specific artist, meaning fan identification

independently affects the number of popular music concerts for a specific artist.



Motivations for popular music concert attendance were found to fully mediate

the relationship between fan identification and amount willing to pay. This

suggests that motivations influence the amount consumers are willing to pay for

tickets. Specifically, the motivations nostalgia, aesthetics, escape, status

enhancement, physical skills and social interaction will increase the amount

individuals will pay for popular music concert tickets.

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A combination of fan identification and motivations will influence the distance

an individual is willing to travel to a popular music concert. Fans with higher

levels of fan identification, that are also motivated by nostalgia, aesthetics,

physical attraction, status enhancement, social interaction, hero worship and

uninhibited behaviour are more likely to travel further to concerts. Fan

identification will directly influence willingness to travel however, if individuals

are motivated to attend for escape reasons, or for the physical skill of the artist.

Summary

The mediating effect of motivations for popular music concert attendance is

important for explaining the number of concerts an individual will attend for a

specific artist, the amount they are willing to pay for concert tickets and the

distance they are willing to travel to concerts. Table 4.46 summarises the

mediating effects of motivations for the relationships between the other

independent variables (product involvement and fan identification) and the four

dependent variables.

In relation to the average number of concerts an individual will attend for a

particular artist; motivations will only impact the relationship between product

involvement and the number of concerts for a specific artist. The motivations;

physical attraction, social interaction, hero worship and uninhibited behaviour

fully mediate this relationship, meaning that those individuals attending a

concert for these reasons will be more likely to attend more concerts for a specific

artist, irrespective of their level of product involvement. However, consumers

motivated by escape and physical skills, who also have a higher level of product

involvement, will be less likely to attend multiple concerts for one artist in

particular.

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In reference to the amount willing to pay for tickets; individuals motivated by

aesthetics, escape, social interaction and hero worship will pay more for popular

music concert tickets regardless of their level of product involvement.

A higher level of fan identification is required if individuals motivated by escape

and the physical skills of the artist are to travel further distances to popular music

concerts.

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INDEPENDENT VARIABLES

DEPENDENT VARIABLES

Product Involvement Fan Identification Direct Effect

Mediating Effect of Motivations Direct Effect

Mediating Effect of Motivations Full Partial No Full Partial No

Average number of popular music concerts per year

POSTIVE X X X X X X X

Number of popular music concerts for a

particular artist

NEGATIVE

Physical Attraction, Social Interaction,

Hero Worship, Uninhibited Behaviour

Nostalgia, Aesthetics,

Status Enhancement

Escape, Physical Skills X X X X

Amount willing to pay for tickets X

Aesthetics, Escape,

Social Interaction, Hero Worship

Nostalgia, Physical Attraction,

Status Enhancement, Physical Skills,


X X X

Nostalgia, Aesthetics,

Escape, Status Enhancement,

Physical Skills, Social Interaction

X

Distance willing to travel to concerts X X

Aesthetics, Escape,

Social Interaction, Hero Worship,

Nostalgia, Physical Attraction,

Status Enhancement, Uninhibited Behaviour

Physical Skills POSITIVE X

Aesthetics, Social Interaction,

Hero Worship, Nostalgia,

Physical Attraction, Status Enhancement,


Escape, Physical Skills

Table 4.46: Mediating Effects of Motivations

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4.6.5 Differences

H19: Motivations for popular music concerts will differ between males and

females

Results indicate that males and females will primarily attend popular music

concerts for the same reasons; however, females are more likely to attend popular

music concerts based on the physical attractiveness of the artist than males.

4.7 Summary

This chapter examined the proposed conceptual models and presented the

results of the analysis. The findings of the study show that fan identification and

product involvement are useful constructs for explaining concert attendee

behaviour. Specifically, in comparison to other applications, the fan identification

construct performs similarly for popular music concert attendees. In relation to

product involvement however, the dimensionality of an individual’s interest in

popular music concerts, differs to other products and services. Findings show

that a consumer’s interest in popular music concerts comprises three dimensions:

Pleasure, Sign Value and Risk Probability, as opposed to other applications which

indicate an Interest and Risk Importance dimension. This finding extends the

literature related to product involvement (see Laurent and Kapferer (1985) and

Rodgers and Schneider (1993)), in that it demonstrates the use of the construct in

another context; specifically for a hedonic service. Findings also support Gabbott

and Hogg’s (1990) finding that entertainment services score much lower on the

risk importance items than non-entertainment services. Additionally, this

research extends Gabbott and Hogg (1999), by finding that risk importance is

insignificant for popular music concerts.

Results of this research also establish that motivations for popular music concerts

differ to those of other events. Whilst previous research for similar events have

identified the motivations of aesthetics (in sport, for example Fink, Trail and

Anderson, 2002), social interaction (sport, jazz, performing arts, Fink, Trail and

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Anderson, 2002; Formica and Uysal, 1996; and Swanson et. al., 2008 respectively),

and escape (sport and performing arts, Fink, Trail and Anderson, 2002 and

Swanson et. al., 2008), this research facilitated the development of more

appropriate context-specific definitions related to popular music concert

attendance. It was also found that uninhibited behaviour was a particularly

important motivation for popular music concert attendance, providing support

for Earl’s (2001) introspective idea. Additionally, findings from this research

reveal that nostalgia will motivate consumers to attend popular music concerts.

This motivation does not appear to have been identified as a significant

motivation for any other type of event in the literature.

From a practical stand point, the five key findings of this research are:

(1) Aesthetics, Escape, Social Interaction, Hero Worship, Nostalgia,

Physical Attraction, Status Enhancement, Physical Skills and

Uninhibited Behaviour are significant motivations for popular music

concert attendance.

(2) The number of popular music concerts consumers attend on average,

per year depends ultimately on an individual’s level of product

involvement.

(3) The number of concerts an individual will attend for any given artist

will directly depend on level of fan identification (fans with higher

levels of attachment to the artist will go to see the artist more), and

motivations for attendance; specifically physical attraction.

(4) The amount consumers are willing to pay for popular music concerts

primarily depends on an individual’s motivation for attending a

specific popular music concert. Individuals motivated by aesthetics and

physical skills are particularly more likely to pay more for popular

music concerts.

(5) A consumer’s willingness to travel to popular music concerts will be

related to their level of fan identification and motivations for

attendance. Motivations for popular music concerts partially mediate

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the relationship between fan identification and willingness to travel,

and fully mediate the relationship between product involvement and

willingness to travel. Individuals motivated by uninhibited behaviour,

hero worship and aesthetics are more likely to travel to popular music

concerts.

The next chapter incorporates findings from Study 1 and Study 2 to conclude the

overall project by extending the discussion to the overall research findings,

project contributions, limitations and directions for future studies.

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CHAPTER 5

Discussion & Conclusion

5.1 Introduction

The ability to draw consumers to live music performances is vital to the success

of distinct musical acts, and also for the perpetuation of the music industry as a

whole. Previous studies have identified a number of important variables that

drive attendee behaviour in reference to other types of events and performances;

for example fan identification in the context of sport spectator consumption

behaviour (Trail et al, 2003), motivations for attending jazz festivals (Formica and

Uysal, 1996), and product involvement for attending a film (Gabbott and Hogg,

1999). Such findings have demonstrated that attendance at events is driven by a

number of factors internal to the consumer. Therefore, the central objective of

this research was to bring together previously identified factors to investigate the

influence of motivations, fan identification and product involvement on concert

attendee behaviour, in a popular music context. Literature on motivations, fan

identification and product involvement in other contexts was reviewed to provide

an initial understanding of the topic areas to be studied in a popular music

context. A three-study research design was then utilised to examine concert

attendee behaviour which included; the average number of popular music

concerts an individual will attend per year, the number of popular music concerts

an individual will attend for a specific artist, the amount an individual is willing

to pay for popular music concert tickets and the distance an individual is willing

to travel to popular music concerts.

This chapter summarises the findings of the research and outlines how these

findings extend prior knowledge of the constructs: motivations, fan identification

and product involvement, whilst explaining their applicability to aiding the

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understanding of concert attendee behaviour. Practical implications for

marketing managers, including concert promoters are provided and limitations

of the project are used to identify areas for future research.

5.2 Concluding Remarks

This project aimed to gain a greater understanding of concert attendee behaviour

in a popular music context. In reference to this, four key research questions were

ultimately addressed. The research questions were:

1) What are consumers’ motivations for popular music concert attendance?

2) What is the relative influence of motivations, fan identification and product

involvement on popular music concert attendance?


involvement on the amount consumers are willing to pay for concert tickets?


involvement on the distance consumers are willing to travel to concert

events?

The following section addresses each of these research questions by first

discussing findings related to motivations for popular music concert attendance.

The influence of motivations, fan identification and product involvement will

then be discussed with reference to the concert attendee behaviour variables;

including average number of popular music concerts per year, and number of

popular music concerts for a specific artist, amount willing to pay and willingness

to travel.

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5.2.1 Motivations for Popular Music Concert Attendance

Study 1 indicated that consumers possess very different motivations for

attendance to popular music concerts which led to further exploration of

motivations for popular music concert attendance in Study 2. Content analysis of

the data from the focus groups conducted in Study 2 revealed ten motivations for

concert attendance; Hero Worship, Aesthetics, Nostalgia, Social Interaction,

Uninhibited Behaviour, Physical Attractiveness, Escape, Status Enhancement,

Physical Skills, New and Concert Specific Music. These preliminary findings

suggested that motivations for popular music concert attendance do in fact differ

to motivations for other types of events (for example, sporting events, see Fink,

Trail and Anderson, 2002; Wann, 1995). Specifically, of the ten motivations that

drive consumers to attend popular music concerts, the research pinpointed four

motivations associated with popular music concert attendance that have yet to be

highlighted as significant motivations for other types of events. These include

personal nostalgia, uninhibited behaviour, status enhancement and to experience

new and concert specific music.

Whilst previous research for similar events have identified the motivations of

aesthetics (in sport, for example Fink, Trail and Anderson, 2002), social

interaction (sport, jazz, performing arts, Fink, Trail and Anderson, 2002; Formica

and Uysal, 1996; and Swanson et. al., 2008 respectively) and escape (sport and

performing arts, Fink, Trail and Anderson, 2002 and Swanson et. al., 2008); this

research facilitated the development of context-specific definitions relevant to

popular music concerts. It was also confirmed beyond the introspective study by

Earl (2001) that uninhibited behaviour is a particularly relevant motivation for

popular music concert attendance.

The Concert Attendee Motivation Scale (CAMS) developed in Study 3 was shown

to provide a valid and reliable measure for assessing motivations for popular

music consumption. When considering the ten motivations identified in the 186 | P a g e

focus groups however, the quantitative results obtained in Study 3, determined

the construct for ‘concert specific music’ to be unreliable and convergent validity

issues were discovered. The concert specific music dimension was therefore

removed from the CAMS. Consequently, the final CAMS comprised nine

dimensions of motivations for popular music concert attendance. Each of the

components was convergent and possessed good discriminant validity. The

significant correlations between the motivations for popular music concert

attendance and the two criterion variables; fan identification and the number of

concerts attended for the same artist, also demonstrated that the CAMS had

criterion validity.

A number of studies on motivations for attendance to events, particularly in

sport, are primarily conducted with college students. One of the key strengths of

the CAMS is that the scale has been developed using members of the general

population who have attended a popular music concert in the last six months,

meaning that the scale reflects the motivations of the desired target group from a

wide variety of music interests within the popular music genre (including rock,

pop, alternative and country). Therefore, this study contributes to theory and

knowledge of concert attendee behaviour by indicating motivations for concert

attendance and providing a valid and reliable scale for their measurement.

5.2.2 Concert Attendance

In Australia, popular music concerts have the highest attendance rate of all arts

and cultural events including: art galleries, museums, classical music concerts,

theatre performances, dance performances, musicals and operas, and other

performing arts (ABS, 2011a). What drives people to attend (or prevents

attendance) has been described to be a function of “customer’s needs, interests,

attitudes, and preferences” (Bernstein, 2007, p. 16). When considering

motivations for attendance, level of fan identification and product involvement, 187 | P a g e

this project demonstrates that a consumer’s relative interest in popular music

concerts (product involvement) was the only significant predictor of the average

number of popular music concerts an individual will attend per year.

Whilst there was an a priori expectation that there would be five facets to

product involvement; interest, pleasure, sign value, risk probability and risk

importance (Laurent and Kapferer, 1985), findings related to concert attendee

behaviour indicate that a consumer’s level of interest, arousal or emotional

attachment (Rothschild, 1984; Bloch, 1986; Richins and Bloch, 1986; Te’eni-Harari

and Hornik, 2010) in popular music concerts is comprised of three dimensions;

pleasure, sign value and risk probability. Though these results contradict findings

of the original consumer involvement profile developed by Laurent and Kapferer

(1985), findings related to product involvement with popular music concerts do

reinforce findings related to product involvement for other hedonic products and

services. Previous studies have identified that for some products and services

there may not be a clear distinction between interest and pleasure (Jain and

Srinivasan, 1990; Rodgers and Schneider, 1993; Quester and Lim, 2003), and this

distinction becomes even less apparent for hedonic products and services (Hogg,

1999). Specific discussion relating to this can be found in Chapter 4, pp. 135 – 139.

In reference to popular music concerts it would appear that interest and pleasure

are indistinguishable. That is, consumers are interested in popular music

concerts, because they are pleasurable, which would be primarily due to the

hedonic nature of this consumption experience (Holbrook and Hirschman, 1982).

Therefore, for popular music concerts the interest dimension of product

involvement is dissolved and captured in the pleasure dimension.

It has been suggested that the purchase of services is riskier than physical goods

(Murray, 1991) and Gabbott and Hogg (1999) state that the multifaceted nature of

the CIP reflects an appropriate view of product involvement for services,

particularly in reference to the inclusion of the two risk facets (risk probability

and risk importance). The results of this project, however, suggest that hedonic

services such as popular music concerts, whilst having some probability of risk,

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have minimal to negligible consequences associated with them. When testing the

dimensionality of product involvement relative to popular music concerts it was

found that the risk importance dimension of the CIP did not apply to popular

music concerts. This appears to be consistent with Gabbott and Hogg’s (1999)

study, whereby entertainment services (such as film) score much lower on the

risk importance facet than non-entertainment services. Therefore, whilst concert

attendees perceive some probability of making a poor concert choice, they don’t

perceive there to be any significant negative consequences for making a poor

choice. Results from Study 2 and Study 3 of this project suggest this may be due

to the hedonic nature of music concerts and the variety of motivations that may

be satisfied from attending them. Consumers with higher levels of product

involvement were more likely to be motivated to attend popular music concerts

for hero worship, social interaction and aesthetics (Study 3) and some

participants in Study 2 with high levels of product involvement expressed that

they “didn’t care so much about the music” and that they enjoyed being “around

like people”. Therefore, even if consumers perceive there to be some risk

probability associated with choosing which popular music concert to attend, this

risk may not be so much associated with the difficulty of choosing a concert that

will deliver a good performance, but more so a difficulty in distinguishing

between concerts. Difficulty in determining which concert to attend from other

concerts and other activities may be due to the fact that all concerts offer a

chance for hero worship, social interaction and an artistic appreciation of the

artist (aesthetics). Consequently, even in the event of a poor performance, other

motivational needs are still met, and therefore there is little importance placed

on the risk associated with poor choice.

In light of these findings, a consumer who; finds concerts high in hedonic value

and appreciates their ability to provide pleasure and enjoyment, recognises

concerts to express a part of themselves and perceives trivial negative

consequences associated with the poor choice of a concert, will attend a higher

number of popular music concerts per year, on average, then someone without

this level of interest. 189 | P a g e

It was proposed that fan identification and motivations for popular music concert

attendance would also influence the average number of popular music concerts a

consumer will attend per year. However, this was not the case in the current

project. Fan identification had no direct influence on the average number of

popular music concerts attended. Whilst a close attachment to a particular artist

(fan identification) may influence the number of concerts an individual will

attend for that specific artist, it does not automatically follow that, the same

individual will attend more concerts per year, particularly if the artist does not

perform every year. Results of this research suggest that for popular music

concerts, fan identification will influence the number of popular music concerts a

consumer will attend for an artist with whom they highly identify, but being

highly identified with a particular artist does not mean that an individual will

attend more concerts in general. Although, motivations did not mediate the

relationship between fan identification and number of popular music concerts for

a particular artist, consumers with higher levels of fan identification were more

likely to be motivated to attend popular music concerts for hero worship, status

enhancement and uninhibited behaviour.

Motivations for popular music concerts are also artist specific, meaning that

motivations alone will not predict how many popular music concerts an

individual will attend per year on average, but consumers motivated to attend a

particular artist because of their physical attraction, will go to more concerts for

that artist than someone motivated for other reasons. Participants’ comments

from the focus groups in Study 2 provide support for this finding. Whilst it

appears that attending concerts purely motivated by the physical attractiveness

of the artist is predominately female behaviour (Study 2 and Study 3), males in

the focus groups also expressed that going to see an attractive artist may be the

only reason they would go to a concert that their partner wanted to attend.

In summary, consumers with higher levels of product involvement are more

likely to attend more popular music concerts on average per year, however

attending more concerts means by a variety of artists and not a higher number of

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concerts for one artist in particular. Fan identification is a necessary condition for

attending more concerts for a specific artist and for females, being purely

motivated to attend a concert for an artist who is physically attractive, will mean

that they will see that artist a significantly higher number of times than

individuals who are motivated to see the same artist for other reasons.

5.2.3 Amount Willing to Pay

Popular music artists and concert promoters in Australia are continually looking

at ways to reduce ticket prices for Australian music fans in order to increase

attendance at popular music concerts; however costs for Australians to see

international artists, will always be higher than costs for American and European

music fans due to large expenditures associated with equipment transport and a

strong Australian dollar (McCabe, 2013). In order to increase attendance, many

artists have been forced to adopt tiered ticket pricing, typically late in the ticket

selling phase in an attempt to sell leftover tickets (McCabe, 2013). Some

promoters (for example, Paul Dainty, promoter for Bon Jovi) are now even pre-

empting less than full venues and making lower priced tickets available from day

one in an attempt to relieve “economic doom and gloom perceptions” (Paul

Dainty, quoted in McCabe, 2013). Obviously there is a point, where ticket prices

can no longer be reduced and promoters will need to look at other ways of

increasing attendance.

Findings from this research suggest that motivations for popular music concert

attendance will determine how much a consumer is willing to pay for popular

music concerts. Whilst motivations associated with nostalgia, escape, physical

attraction, social interaction, hero worship and uninhibited behaviour will not

influence the amount a consumer is willing to pay for a popular music concert

ticket, consumers driven to attend concerts for aesthetic reasons, the physical

skills of the artist, and to some extent status enhancement, are willing to pay

more to attend popular music concerts. Contrary to studies on attendees to

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sporting performances (Wann & Branscombe, 1993), findings of this research

suggest, that for popular music fans; higher levels of fan identification were not

directly associated with amount willing to pay for tickets. Whilst relationships

between fan identification and product involvement on amount willing to pay

exist, these relationships are fully mediated by motivations for attendance.

Specifically, consumers will pay more for concerts when motivated to see artists

for their aesthetic beauty and musical skill.

5.2.4 Willingness to Travel

Findings from Study 1 revealed that consumers categorized as possessing high

levels of fan identification (dysfunctional fans) were willing to travel vast

distances to attend a popular music concert for an artist with whom they had a

close attachment. However, no research could be found that considers the drivers

of willingness to travel for any specific event. Based on the results from Study 1, it

was hypothesised that fans with higher levels of fan identification would be more

likely to travel further distances to popular music concerts. Study 3 findings

provide support for this hypothesis, and in fact, both fan identification and

motivations for popular music concert attendance were found to explain nearly

half of the variation in willingness to travel. Fans with higher levels of fan

identification were moderately more likely to travel further distances to popular

music concerts than fans with lower levels of identification.

Whilst motivations account for some of the relationship between fan

identification and willingness to travel, fan identification is a necessary

determinant for those consumers motivated to attend for escape and the physical

skills of the artist. The importance of level of fan identification on willingness to

travel, however, was lower for those motivated to attend a popular music concert

for nostalgia, aesthetics, physical attraction, status enhancement, social

interaction, hero worship and uninhibited behaviour.

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5.3 Implications

This project makes contributions to the understanding of concert attendee

behaviour and has a number of implications for research in marketing, as well as

practical implications for music marketers. The theoretical and managerial

applications of the results are discussed respectively in the following section.

5.3.1 Theoretical Contributions

This research provides a model for the prediction and explanation of concert

attendee behaviour in reference to the four outcome variables, that is, the

average number of popular music concerts an individual will attend per year, the

number of concerts an individual will attend for a specific artist, the amount

consumers are willing to pay for concert tickets, and the distance they are willing

to travel to live performances. Factors influencing concert attendee behaviour

have not been previously explored in a popular music context. The current

project extends our knowledge of event attendee behaviour by investigating the

influence of fan identification, product involvement, and motivations for popular

music concert attendance; and their interrelationships and links to behaviour.

The development and testing of this model fosters four key contributions to

marketing theory.

First, the project offers a quantitative application of fan identification in a

popular music context, which has been predominately explored by a qualitative

means in the fandom literature (Schimmel, Harrington and Beilby, 2007). The

research demonstrates a specific application of Reysen and Branscombe’s (2010)

fanship scale and answers their call for future research to be conducted not only

on participants who were not college students, but also for other categories of

fans. This research, regarding the application of fan identification to a popular

music context may provide support for the authors’ claims that sports fans are

similar to fans of other interests, but findings from the current research indicate

that they are definitely not the same. Generalisations of past findings concerning

sport fans to fans of other interests are therefore not recommended.

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Second, this research demonstrates an application of Laurent and Kapferer’s

(1985) Consumer Involvement Profile (CIP) for another hedonic service, popular

music concerts. The findings contribute to academic knowledge regarding the

dimensionality of the CIP which has been shown to differ for various products

and services. Specifically, three facets of the CIP pertain to involvement with

popular music concerts, namely, pleasure, sign value and risk probability. The

hedonic nature of popular music consumption meant that interest in popular

music concerts was captured in pleasure and sign value, and it was also found

that risk importance has no applicability to involvement with popular music

concerts.

Third, the Concert Attendee Motivation Scale (CAMS) developed as a result of

findings from Study 2 and Study 3 was found to provide a valid and reliable

measure for assessing motivations for popular music concert attendance. Whilst

one of the dimensions of motivations for popular music concert attendance

originally identified in the focus group findings as ‘concert specific music’ was

removed from the final scale due to reliability and convergent validity issues (see

Limitations and Future Research for further discussion), the CAMS offers a

preliminary scale for measuring motivations specific to popular music concert

attendance. This contribution is noteworthy as motivations have been shown to

differ between not only very disparate, but also similar events (for example,

Nicholson and Pearce, 2001). Furthermore, findings from Study 2 highlight four

motivations specific to popular music concert attendance that have not been

indicated as significant motivations for other types of events, namely, nostalgia,

uninhibited behaviour, status enhancement and concert specific music. Other

motivations identified for popular music concert attendance were similar to

those for other events and include aesthetics, escape, physical attractiveness of

the artist, status enhancement, physical skill of the artist and social interaction.

The final key contribution to marketing theory from this project lies in the

identification of the concert attendee behaviour variable – willingness to travel.

The results from both Study 1 and Study 2 indicated that the distance a consumer

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is willing to travel to a popular music concert could be dependent on level of fan

identification and motivations for attendance. Results of Study 3 support this

proposition and fan identification and motivations for popular music concert

attendance were found to explain nearly half of the variation in a consumer’s

willingness to travel to popular music concerts (49%). Therefore whilst previous

research has examined the influence of fan identification on other behavioural

outcomes such as attendance and amount willing to pay, no research to date has

considered willingness to travel, for which fan identification has much superior

predictive power.

5.3.2 Practical Implications

Live popular music performances have continuously been described as being “an

essential part of popular music’s gestation, creation, development, and

establishment (Kronenburg, 2011), however the live music industry’s aims remain

primarily economic, that is, to fill seats and to sell tickets (Duffett, 2012). Findings

from this research may help popular music concert promoters and artists to

achieve marketing goals with harmonious balance, where the goal of selling

tickets does not outweigh the importance of creating enjoyable fan experiences.

The findings of this project therefore have managerial implications for all aspects

of marketing including the design of product offerings, marketing

communication and merchandising. The following sections will address

implications for concert attendance, merchandising, product offerings, ticket

pricing, marketing communications and travel to events.

Increasing attendance

Based on key findings, it is possible to extend beyond the promotion of genre

styles and artists to attract consumers to popular music concerts, by considering

factors internal to the consumer; that is, motivations, product involvement and

fan identification. Each of these factors has a varying degree of influence on

concert attendee behaviour.

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Findings related to the influence of product involvement on the average number

of popular music concerts attended per year are important for music marketers

wanting to increase attendance to live performances in general. Consumers with

a high level of product involvement enjoy the entertainment and pleasure derived

from popular music concert attendance. Concert attendance is also central to the

people they are, and consumers with a high level of involvement will typically

enjoy concerts irrespective of the risk of a poor performance. These findings may

be important for designing product offerings for less popular artists and hard to

sell concerts. Consumers with higher levels of product involvement care little

about the music itself and are primarily motivated to attend concerts for hero

worship, social interaction and aesthetics. These motivations could be used as a

basis for making amendments to the concert product and marketing

communication aimed at targeting this type of consumer. For example, side

activities typically associated with music festivals that create opportunity for

social activities and interaction may entice attendance from consumers with high

levels of product involvement. The social interaction benefits of attendance could

also be conveyed in corresponding marketing communication. As product

involvement has no influence on the amount a consumer is willing to pay for a

popular music concert, these activities provide a more economical alternative to

ticket discounting for artists and concert promoters.

Merchandising

The identification of both the physical attraction and nostalgia motivation may

provide guidance for the creation of artist specific merchandise. Artists or

performers returning to the stage from a previous decade of popularity may illicit

a nostalgic response for a large group of consumers. For example a greatest hits

Madonna tour may elicit a nostalgic comeback of slouch socks, tutu skirts, off the

shoulder singlet tops, wrists full of bracelets, cross earrings and large hair bows

(see Image 1). Incorporation of Madonna licensing on these types of merchandise

could provide more additional/alternative merchandising revenue than

traditional merchandising options typically seen at popular music concerts.

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Image 5.1: Madonna in the 80’s

Source: Michael Putland, http://madonnapopculture.blogspot.com.au/2011/04/madonnas-impact-on-fashion.html

Opportunity may also exist for artists and bands with attractive lead singers or

band members to produce merchandise exhibiting the physically attractive artist.

Consumers motivated to attend popular music concerts because of the physical

attractiveness of an artist have been shown to attend more events for that

particular artist and therefore these consumers are exposed to more merchandise

purchasing opportunities. A consumer motivated to attend, for example a Bon

Jovi concert, because of the physical attractiveness of Jon Bon Jovi (nominated by

OK magazine as one of the hottest lead singers of all time, 2013), may be more

likely to purchase merchandise displaying Jon’s actual face and body, as opposed

to a something with a small design and the band name (see Image 2).

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Image 2: Attractiveness related merchandise versus traditional merchandise

Source: http://www.sharenator.com/Whats_your_fave_bandssingers_whatever/#img-32004

Product Offering and Marketing Communications

The emergence of motivations for attendance such as nostalgia, uninhibited

behaviour, escape, aesthetics, physical skill and physical attractiveness and social

interaction, suggest that it is possible that popular music concert organisers may

be able to employ different marketing tactics to broaden the appeal of specific

concerts, beyond the promotion of genre and artist. With motivation seen as a

fundamental reason for behaviour (Mayo and Jarvis, 1981; Snepenger, 2006) it is

suggested that the uncovering of these motivational factors that drive popular

music concert attendance will aid in the creation of new promotional strategies,

which in turn will facilitate the growth of the music concert domain. For

example, nostalgic advertising in combination with advertisements promoting

the guitarist Slash as one of the best guitarists to play a solo at a live music

concert may provoke alternative motivations for attendance to a Guns n’ Roses

music concert rather than traditional promotion of the band alone. In fact,

consumers motivated to attend popular music concerts for the aesthetics and

physical skills of the artist were willing to pay more for music concerts. Therefore

promotion of these motivations for technically skilled artists will also provide

alternatives to ticket discounting.

Source: www.backstreet-merch.com

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Travel

Consumers with higher levels of fan identification are more likely to travel

further distances to attend popular music concerts than less identified fans,

therefore communication of a particular artist may be necessary to get audiences

to travel to events. Motivations however partially mediate the relationship

between fan identification and willingness to travel, meaning that consumers

who are motivated to attend a specific concert for nostalgia, aesthetics, physical

attraction, status enhancement, social interaction, hero worship or uninhibited

behaviour and who also possess a certain level of attachment to an artist, will be

more likely to travel to popular music concert events. Marketing communication

of artists incorporating any of these motivational perspectives within the

advertising is therefore more likely to entice consumers to popular music

concerts outside of their local area.

Cultural attractions, such as popular music concerts, can play a vital role in the

attractiveness of a destination (Hughes; 1987; Kim et. al., 2007; Richards, 2002).

Status enhancement was a significant motivator for highly identified fan, and

consumers motivated to attend popular music concerts were also willing to travel

further to attend events. This type of competitive behaviour was found to

motivate some fans to attend a particular concert in order to increase their

‘status’ as a fan. This was deemed to derive from the belief that “you are a bigger

fan if you can say that you have attended more concerts”. Part of this motivation

also centred around the concept of being able to “look cool” and note that you are

at a concert as your ‘status update’ on Facebook. This behaviour, whist status

enhancing for the individual (Ong, et al., 2011), can also have positive

implications for the concert, venue and destination through facilitating

interactive, user-driven promotion (Zouganeli et al., 2011). Fans with higher levels

of identification wanting to attend a particular concert for status enhancement

are willing to travel further and pay more for concerts tickets. Opportunity

therefore exists for the creation of packaged events that incorporate transport

and exclusivity for highly identified status enhancing fans, creating benefits for

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not only artists and concert promoters, but also music tourism and destination

marketing.

5.4 Limitations and Directions for Future Research

This research has strengths in that it provides insight into concert attendee

behaviour. However, is not without limitations.

One of the main limitations of this study may come from the lack of previous

research specially related to popular music. A heavy emphasis was placed on

previous studies in the sporting arena to guide and direct the project, and

although the concept of fandom has been considered in a popular music context;

a lack of empirical studies meant that all quantitative measures utilised in the

current study had to be adapted to a popular music context.

Although development of the CAMS was generated using a large representative

sample of the target population, it is possible there exists other motivations for

popular music concert attendance that were not identified as motivations for

other types of events from the literature, and that were not identified in the focus

groups prior to scale development. Additionally, whilst the CAMS provides a

relatively valid and reliable measure for popular music concert attendance it is

important to note that only concurrent validity was established. Future research

should examine the predictive validity of the CAMS by utilising the scale in a

different study for the same target population and correlating it with the current

data. The development of the CAMS represents an early attempt to provide a tool

for measuring motivations for popular music concert attendance. Future research

should also focus on replication and continual development of the CAMS.

Overall, the performance of the scale was acceptable, including validity and

reliability. However, further refinement would demonstrate the robustness

and/or improve the quality of the scale. Specifically, concert specific music was

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repeatedly identified as a motivation for attending popular concerts in the focus

groups; however the items generated from the focus group transcript when tested

with the final survey data were not convergent and did not offer a reliable scale

for measuring the concert specific music motivation. Additional work is needed

to strengthen these items (and identify others), and the scale retested so that the

CAMS measures all motivations for popular music concert attendance.

Additionally, construct reliability scores and AVE estimates for the physical skills

dimension were just on optimal cut-off values. Additional refining of the items

for this measure may also further improve the performance of the CAMS.

The CAMS will allow academics and practitioners to gain a better understanding

of the drivers of concert attendee behaviour. However, each motivation may not

be mutually exclusive, and it is possible that concert attendance reflects a

combination of motivations. How consumers form attachments to artists, and

interest in popular music concerts, have not been explored. Future research

should further investigate the formation of different levels of attachment and

involvement to aid the development of marketing strategies aimed at increasing

fan involvement which in turn may increase awareness and patronage (Gwinner

and Swanson, 2003).

Another limitation of this study can be directly attributed to common method

variance (CMV). CMV is a potential problem in behaviour research when self-

report questionnaires are used to collect data at the same time, from the same

participants. CMV is defined as “variance that is attributable to the measurement

method rather than to the constructs the measures represent” (Podsakoff et al,

2003, p. 879). CMV can create inflated correlations as some respondents may

have a tendency to provide consistent answers to survey questions, that if

measured independently, may not be related (Chang, Witteloostuijn & Eden,

2010). Whilst common method variance may be present in the data, a number of

approaches typically recommended in the literature to avoid CMV were

employed in this project (Podsakoff et al, 2003; Change et al, 2010). First, the

order of the questions was randomised in the questionnaire, different scale types

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were utilised, and also the way in which respondents interacted with the scales in

the online survey was varied. The final structural model was also quite

complicated (involving mediating and moderating effects), which can reduce the

likelihood of CMV (Podsakoff et al, 2003; Chang et al, 2010).

Further, fan identification, product involvement and motivations together

explained 17%, 19%, 7% and 49% of the variance in the four dependent variables;

average number of popular music concerts attended, number of concerts for a

specific artist, amount willing to pay and willingness to travel, respectively. Thus,

future work may wish to identify other factors that contribute to the explanation

of these dependent variables. Explanation will be important if a true

understanding of popular music concert behaviour is to be obtained. The use of

past behaviour as a proxy provides another limitation of this research, as current

measures of fan identification and product involvement have been essentially

used to predict past behaviour. Future research should adopt a longitudinal

design so that causal effects can be inferred from this model. The cross sectional

nature of this study also means that temporal relationships between the

constructs cannot be assumed. As this research represents a very preliminary

investigation into the area of concert attendee behaviour, relationships between

the variables have only been hypothesised and interpreted in terms of significant

relationships and the direction and strength of those relationships. Therefore a

limitation of this study rests on the notion that causal inference cannot be

inferred from cross sectional data, and a longitudinal study would need to be

conducted in the future for any degree of causal inference or causal ordering of

the variables effecting concert attendee be made. The results regarding the

amount of variance explained in concert attendance may exemplify one of the

limitations that arise from this study due to the cross sectional nature of the data.

The R-squared value for the amount of variance the other variables explain in

reference to concert attendance is quite low (17%) compared to some of the other

dependent variables that are a measure of future behaviour. This result may be

due to the use of past attendance behaviour as a proxy measure for attendance

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frequency, which again, would only be rectified by a future longitudinal study,

which was beyond the scope of this research.

Additionally, the impact of motivations, fan identification and product

involvement on concert attendee behaviour may differ depending on the artist

and music category identified, and individual characteristics such as age, marital

status and income. These features have not been examined in this study. Bowen

and Daniels (2005), in their study on motivations for music festival attendance

used cluster analysis to identify four distinct groups of visitors attending music

festivals, demonstrating that it is indeed possible to go beyond a reliance on

music itself or a specific artist to attract audiences. Results of this study show this

too may be true for popular music concerts, where there is an absence of other

activities, diversions and non-musical attractions that are typically associated

with music festivals (Bowen and Daniels, 2005). Future research should attempt

to characterize popular music fans in order to tailor marketing efforts to distinct

consumer groups.

5.5 Conclusion

Popular music concerts can play a vital role in art and culture (ABS, 2011a). Whilst

concert promoters tend to focus on the music genre and/or artist (Shuker, 2008),

marketers are looking for new ways to increase attendance. Individuals attend

concerts for many different reasons, and consumption behaviour in relation to

popular music concerts is varied. Concert attendees range from those that exhibit

‘ordinary audience behaviour’ (Cavicchi, 1998), attending concerts for pure

pleasure and enjoyment and possessing no significant connection to the

performer, to the ‘Dysfunctional fan’ (Beaven and Laws, 2007) who will disrupt

their life and take advantage of any opportunity to encounter their favourite

artist. The notion of fandom and the tendency for individuals to form

attachments to music celebrities, actors and athletes (Soukup, 2006) has been

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well established in the popular culture literature (e.g. Gray, Sandvoss and

Harrington, 2007; Sandvoss, 2005; Hills, 2002; Harris and Alexander, 1998),

however, little has been reported about the motivational drivers that influence

popular music concert consumption.

Results of this study indicate that fan identification, product involvement and

motivations play an important role in explaining concert attendee behaviour in

relation to popular music. The first key research question for this project was:

What are consumers’ motivations for popular music concert attendance, and

are those motivations related to the number of concerts an individual attends,

the amount they are willing to pay for tickets and their willingness to travel?

Nine specific motivations for attendance to popular music concerts were found to

drive concert attendee behaviour, including: Hero Worship, Aesthetics,

Nostalgia, Social Interaction, Uninhibited Behaviour, Physical Attractiveness,

Escape, Status Enhancement and Physical Skills. Motivations for attendance were

important in explaining the number of times an individual will attend concerts

for a specific artist, how much an individual is willing to pay for popular music

concerts and their willingness to travel to popular music concerts.

The second key research question for this study asked:

What is the influence of fan identification and product involvement on

popular music concert attendance, amount willing to pay, and willingness to

travel?

Findings from this research indicate that in combination with motivations and

fan identification, product involvement will only influence the average number of

popular music concerts an individual will attend a year. Fan identification,

however, was important in determining the number of popular music concerts an

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individual will attend for a specific artist and the distance an individual is willing

to travel to popular music concerts.

The current project will enable marketers to create more value for consumers by

offering products that are better able to meet consumers’ needs (Caru and Cova,

2006). The understanding of concert attendee behaviour gained from this

research will also ensure that both the concert product and experiences with the

marketing of popular music concerts is significant to the consumer. How

concerts are packaged and communicated will also continue to be relevant and

meaningful to existing and new markets.

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APPENDICES

APPENDIX A: Study 2 Participant Information Sheet Newcastle Business School University Drive Callaghan 2308 [email protected]

Information Statement for the Research Project:

Profiling and Segmenting the Popular Music Concert Market

Document Version 2; dated 01/03/2012 You are invited to participate in the research project identified above which is being conducted by Alicia Perkins, a PhD candidate from the Newcastle Business School at the University of Newcastle. The research is part of Alicia’s studies at the University of Newcastle, supervised by Associate Professor Alison Dean and Dr. Stacey Baxter from the Newcastle Business School. Why is the research being done? The purpose of the research is to gain insight and understanding into what influences and motivates people to attend popular music concerts, including what sources of information are utilised when making a purchase decision. The information will help us to identify ways to improve product offerings, service delivery and communication campaigns aimed at increasing consumer satisfaction in relation to popular music concerts. Who can participate in the research? Students who are enrolled in an undergraduate marketing course in Semester 1, 2012 are being invited to participate. What choice do you have? Participation in this research is entirely your choice. Only those people who give their informed consent will be included in the project. Whether or not you decide to participate, your decision will not disadvantage you. If you do decide to participate, you may withdraw from the project at any time without giving a reason and have the option of withdrawing any data which identifies you.

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mailto:[email protected]

What would you be asked to do? If you agree to participate, you will be asked to participate in one focus group discussion with Alicia during the 2012 Easter break at Callaghan or Ourimbah Campus. Lunch and light refreshments will be provided. How much time will it take? The focus group will be scheduled for 1-2 hours duration, at a time and day convenient to group members. What are the risks and benefits of participating? The focus groups will seek your views on aspects of popular music concert attendance. Whilst we cannot promise you any benefit from participating in this research, participation will allow you to experience a focus group first hand and also give you insight into aspects of marketing theory applied in a practical context. Participants may be potentially identifiable to other focus group members, but they will not be identified in the reporting of the results. All focus group participants will be instructed to maintain the confidentiality of the group discussion. How will your privacy be protected? The raw data (focus group recordings and notes) will only be accessed by Alicia. Although first names of participants may be necessary to facilitate discussion during the running of the focus group, names of individuals will not be identified in the final report. The transcribed focus group data will be retained for at least five years and will be stored in the office of the Project Supervisor (SRS116, University of Newcastle). How will the information collected be used? The data will be reported and presented in a thesis to be submitted for Alicia’s degree and for preparation of academic papers. No student or group will be identified. Focus Groups will be audio recorded. If you wish, you will be able to review the recording and/or transcripts to edit or erase your contribution. All participants will be offered a summary of the results at the conclusion of the study. If you would like a copy of the results, please indicate by circling ‘yes’ in the appropriate section on your consent form. What do you need to do to participate? Please read this information statement and be sure you understand its contents before you consent to participate. If there is anything you do not understand, or you have questions, contact the researcher. If you would like to participate, please contact Alicia Perkins, [email protected]. Alicia will then advise you of times, dates and venues for the focus groups.

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You must bring a completed and signed consent form to your allocated focus group to be eligible to participate on your chosen day. Further information If you would like further information please contact Alicia Perkins by email or the Project Supervisor, Alison Dean by email or phone ([email protected], 4921 7393). Thank you for considering this invitation. Alicia Perkins Alison Dean PhD Candidate Project Supervisor Complaints about this research This project has been approved by the University’s Human Research Ethics Committee, Approval No. H-2012-0020. Should you have concerns about your rights as a participant in this research, or you have a complaint about the manner in which the research is conducted, it may be given to the researcher, or, if an independent person is preferred, to the Human Research Ethics Officer, Research Office, The Chancellery, The University of Newcastle, University Drive, Callaghan NSW 2308, Australia, telephone (02) 49216333, email [email protected].

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APPENDIX B: Study 2 Focus Group Consent Form Associate Professor Alison Dean Newcastle Business School University Drive Callaghan 2308 [email protected]

Consent Form for the Research Project:

Profiling and Segmenting the Popular Music Concert Market

Alicia Perkins, Associate Professor Alison Dean, Dr Stacey Baxter

Document Version 1; dated 01/03/2012 I agreeto participate in the above research project and give my consent freely. I understand that the project will be conducted as described in the Information Statement, a copy of which I have retained. I understand I can withdraw from the project at any time and do not have to give any reason for withdrawing. I consent to (please tick):

• Participating in one focus group discussion with Alicia Perkins at an agreed time and having my voice recorded;

• Being anonymously quoted in the reporting of the research;

I understand that my personal information will remain confidential to the researchers. I have had the opportunity to have questions answered to my satisfaction. I would like to receive a copy of the study results. Print Name: __________________________________________________________

Email Address:_______________________________________________________ To arrange focus group time, and receive a copy of the study results (if selected above). Mobile Phone Number:______________________________________________________

Signature: ____________________________________Date: _________________

□YES □NO

□YES □NO

□YES □NO

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APPENDIX C: Moderator’s Guide for Study 2 Focus Groups

Focus Group Moderator’s Guide

I. BACKGROUND/INTRODUCTIONS

Moderator will:

Introduce them self and thank participants for agreeing to come.

Thank you for volunteering your time and coming this morning. My name is ALICIA PERKINS and I am a PhD student at the University of Newcastle. I will be moderating our discussion today.

Explain group guidelines and indicate how long the focus group will last.

We have the discussion scheduled for 1-2 hours today. During the group I want you to discuss issues in relation to attendance to popular music concerts. The purpose is to help identify what influences and motivates people to attend popular music concerts.

I am here just to facilitate the session today. You won’t hurt my feelings or make me feel good with whatever opinions you might give. I am interested in hearing your point of view even if it is different from what others have expressed. There are no right or wrong answers.

I’m going to make every effort to keep the discussion focused and within our time frame. If too much time is being spent on one question or topic, I may move the conversation along so we can cover all of the questions.

Address confidentiality

I will be audio-taping the discussion because I don’t want to miss any comments. But, I will only be using first names today and there will not be any names attached to the comments in my final report. You may be assured complete confidentiality. Are there any questions before we start?

Participant introduction:

On that note, please introduce yourselves – first names are fine. Please describe to us in a few words the best music concert you have attended. Let’s just go around the table.

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II. DISCUSSION TOPICS

EXPLAIN PROCESS:

Our topic of discussion today is identifying whether there are certain types of involvement that affect someone’s decision to attend a popular music concert and additionally, what motivates someone to attend. I would like to get your feedback on the topic as well as your perceptions and experiences. We will be focusing on a different topic at a time, but always in the context of popular music concerts.

i. Overall reaction

This first section is to gain your overall reaction to popular music and popular music concerts.

What words come to mind when you think of popular music? Why do you attend popular music concerts? Has/would anyone ever attend a concert for an artist/band that they hadn’t heard of or if

they didn’t really know their music? For what reasons would you attend?

ii. Information Search:

We are now going to discuss a new topic on types of information search. In this topic I am going to ask you to consider things related to information sources, advertising and how you find and search for concerted related information.

How do you find out about music concerts? Can you think of where concerts are advertised?

Where do you look/search for concert related information? If you knew of an upcoming concert, where would you look for ticket prices? Where would you buy your tickets from? How do you keep up to date with your favourite artists/bands? Are you a member of any fan club or online discussion groups for your favourite/band

artist? Is anyone using any apps for their portable technologies to keep track of concerts and/or

artists/bands?

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iii. Motivations:

That brings us to another new topic. In this section we are going to consider someone’s motivation for attending a popular music concert.

Motivations are – DEFINITION Do you attend different concerts for different reasons? Probe – What reasons? Do you only attend because you like the artist/band performing? What motivates you to attend a popular music concert? Let’s have a look from the list of motivations identified in the literature (Refer to handout);

do you think you also attend for some of those reasons? Are there any motivations that you think may not have been discussed in the literature?

iv. Product Involvement:

In this next topic we will be considering a construct called product involvement.

Does anyone know what product involvement is? Product involvement – DEFINITION (Refer to handout) Do any of you consider yourself to have a low level of product involvement in relation to

popular music concert attendance? For what reasons do you attend popular music concerts? Does anyone consider themselves as having a high level of product involvement with

popular music concerts? For what reasons do you attend popular music concerts? So, would we agree that people with different levels of product involvement attend

concerts for different reasons? Explain. What about different behaviours?

v. Fan Identification:

In this next topic we will be considering a construct called fan identification.

Does anyone know what fan identification is? Fan identification – DEFINITION (Refer to handout) Has anyone ever attended a concert with a low level of fan identification towards the

artist who is performing? What motivated you to attend the concert? Has anyone ever attended a concert with a high level of fan identification towards the

artist who is performing? What motivated you to attend the concert?

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Do people with different levels of fan identification have different motivations for attending concerts? Explain.

What about different behaviours?

vi. Product Involvement versus Fan Identification:

In this section we will be considering both product involvement and fan identification.

Based on what we now know about product involvement and fan identification; in your experience is a high level of product involvement is necessary for concert attendance?

Is a high level of fan identification is necessary for concert attendance? Do people attend concerts with any degree of product involvement and fan identification? If you have a high level of fan identification would you be more likely to have a higher

level of product involvement? Do you possess any other relationships/patterns between product involvement, fan

identification and concert attendance?

III. PRODUCT INVOLVEMENT/FAN IDENTIFICATION MATRIX

Now I’d like to get your opinion on what might motivate a person to attend a concert, based on this product involvement/fan identification matrix (Refer to handout).

Okay. Take a moment to look at the matrix.

i. Overall reaction: Does everyone understand the matrix?

ii. Looking at the matrix: (Consider: low/low, low/high, high/low, high/high) Thinking about the last concert you attended, which group were you in? Explain. What motivated you to attend that concert? How did you find out about the concert? Which groups in the matrix attend the most concerts?

IV. CLOSING

Offer an opportunity for any short final comments participants would like to make.

Thank you very much for your input today. We are just about out of time. Are there any last comments that anyone would like to make?

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APPENDIX D: Study 2 Focus Group Handouts

i. Motivations Figure 1. Motivations for concert attendance

Motive Definition Source Vicarious Achievement The need for social prestige, self-esteem and sense of

empowerment that an individual can receive from their association with a popular artist/band.

Adapted from Fink, Trail and Anderson (2002)

Acquisition of Knowledge

The need to learn more about the artist/band or individual band members through interaction and media consumption.


Aesthetics The artistic appreciation of the music due to its inherent beauty


Social Interaction The need to interact and socialise with others of like interests to achieve feelings that one is part of a group, sense of belonging.

Adapted from Fink et al, (2002); Earl (2001) and Oakes (2010)

Escape The need to find a diversion from work and the normal, unexciting activity of everyday life.


Family The opportunity to spend time with one's family doing something everyone enjoys.


Physical Attractiveness of Artist(s)

Watching concerts because of the physical attractiveness or 'sex appeal' of an individual artist/band member or band.


Physical Skill of Artist(s)



Identity Enhancement

Accessing the experience to live a different identity and/or to intensify a fragmented identity

Firat and Dholakia (1998); Caru and Cova (2006)

Concert Specific Music

Hearing 'live' music that is not released on CD's and videos - meaning attendance is the only means of experiencing some particular aspect of the artists' performance (experience in full the visual dimension, unique performances (e.g. covers and improvisation).

Earl (2001)

Joy of Live Performances

Excitement that cannot be created by a recording, awareness of unpredictability

Earl (2001) and Oakes (2010)

Sampling without commitment

Experiencing unfamiliar groups without commitment. Earl (2001)

Hero Worship Getting physically close to famous people, form of pilgrimage and paying of homage to music heroes, thrill of proximity


Opportunity for uninhibited behaviour

Social behaviour that may be precluded in a domestic setting (deafening sound levels: volume, darkness).

Earl (2001)

Status Enhancement

Enhance the status of a fan in subsequent social encounters with someone who did not get to see the artist live

Oakes (2010)

Stagecraft Visual surprise, dramatic spectacle Oakes (2010)

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ii. Product Involvement versus Fan Identification Definitions

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iii. Product Involvement / Fan Identification Matrix

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APPENDIX E: Study 3 Participant Information Sheet

Associate Professor Alison Dean Newcastle Business School University Drive Callaghan 2308 [email protected]

Information Statement for the Research Project:

The Effect of Product Involvement, Fan Identification and Motivations on Popular Music Concert Attendance

Document Version 1; dated 13/03/2013

You are invited to participate in the research project identified above which is being conducted by Alicia Perkins, a PhD candidate from the Newcastle Business School at the University of Newcastle. The research is part of Alicia’s studies at the University of Newcastle, supervised by Associate Professor Alison Dean and Dr. Stacey Baxter from the Newcastle Business School. Why is the research being done? The purpose of the research is to gain insight and understanding into what influences and motivates people to attend popular music concerts. The information will help us to identify ways to improve product offerings, service delivery and communication campaigns aimed at increasing consumer satisfaction in relation to popular music concerts. Who can participate in the research? Anyone who has attended a popular music concert in the last six months is being invited to participate. What choice do you have? Participation in this research is entirely your choice. Only those people who give their informed consent will be included in the project. Whether or not you decide to participate, your decision will not disadvantage you. If you do decide to participate, you may stop completing the questionnaire at any time and have the option of withdrawing from the project without giving a reason. What would you be asked to do? If you agree to participate, you will be asked to complete an online questionnaire distributed by Research Now.

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How much time will it take? The questionnaire will take approximately 15 minutes, which you can complete at a time convenient to you. What are the risks and benefits of participating? The questionnaire will seek your views on aspects of popular music concert attendance. As a participant, you will have signed up to be a part of a Research Now panel and are therefore interested in completing surveys. You will also be paid in line with Research Now’s incentive program. As no identifying information is to be collected, respondents will not be able to receive a summary of the results; however you will receive the benefit of having played an important role in ensuring that the wider community benefits from the research and publications that will come as a result of the research. How will your privacy be protected? The raw data will be compiled in spread sheet format by Research Now and provided to the researcher (Alicia). The researcher will have no contact with respondents, nor will any respondents be identifiable. The raw data will be retained for at least five years and will be stored in the office of the Project Supervisor (SRS116, University of Newcastle). How will the information collected be used? The data will be reported and presented in a thesis to be submitted for Alicia’s degree and for preparation of academic papers. No participant will be identified. What do you need to do to participate? Please read this information statement and be sure you understand its contents before you consent to participate. If there is anything you do not understand, or you have questions, contact the researcher. Further information If you would like further information please contact Alicia Perkins by email or the Project Supervisor, Alison Dean by email or phone ([email protected], 4921 7393). Thank you for considering this invitation. Alicia Perkins Alison Dean PhD Candidate Project Supervisor

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Complaints about this research This project has been approved by the University’s Human Research Ethics Committee, Approval No. H-2013-0077. Should you have concerns about your rights as a participant in this research, or you have a complaint about the manner in which the research is conducted, it may be given to the researcher, or, if an independent person is preferred, to the Human Research Ethics Officer, Research Office, The Chancellery, The University of Newcastle, University Drive, Callaghan NSW 2308, Australia, telephone (02) 49216333, email [email protected].

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APPENDIX F: Questionnaire for Study 3 *Note: Questionnaire was formatted by Research Now for online administration and all items were presented in randomised order.

A popular music concert involves going to see any band/artist that is popular among the

masses (E.g. Pink, Metallica, Keith Urban, Elton John) at a stadium, entertainment centre or similar.

Screening Question Have you attended a popular music concert in the last 6 months?

□ Yes (Continue to Question 1)

□ No (Thank you, unfortunately you are not eligible to complete this survey) Question 1 Who was the headlining act at the last popular music concert you went to? _______________________ Question 2 Where did you see ‘answer from Question 1’?

□In your local area/region

□ In another area/region in the same state as you live

□In another state

□ In another country Question 3 Did you attend multiple ‘answer from Question 1’ concerts for the same tour?

□ Yes (Go to Question 4)

□ No (Go to Question 6) Question 4 How many other ‘answer from Question 1’ concerts did you attending during the tour?

□ 1

□ 2

□ 3

□ 4

□ 5 or more

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Question 5 Where did you attend the other ‘answer from Question 1’ concerts? (Choose all that apply)

□In your local area/region on a different night/s

□ In another area/region in the same state as where you live

□In another state

□ In another country Question 6 Do you consider ‘answer from Question 1’ to be your favourite artist/band?

□ Yes

□ No Question 7 What type of ticket did you purchase to see ‘answer from Question 1’?

□ Seated, because I wanted to sit

□ Seated, because there were no standing tickets left □ Seated, because it was a seated only concert

□ Standing, because I wanted to stand

□ Standing, because there were no seated tickets left

□Other (please explain) ______________________________ Question 8 What genre do you consider ‘answer from Question 1’music to fall into (choose one only)?

Alternative Punk Blues Country Dance Techno Hip Hop/Rap Jazz Pop Pop/Rock R & B Rock Metal Other, please specify

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Fan Identification Question 9 – (to be measured on 5-point Likert scales, Strongly Disagree to Strongly Agree)

I have rescheduled my work to accommodate ‘answer from Question 1’

I am emotionally connected to ‘answer from Question 1’

I spend considerable amount of money on ‘answer from Question 1’

I want everyone to know that I am connected to ‘answer from Question 1’

If I could I would devote all of my time to ‘answer from Question 1’

I would be devastated if I were told I could not follow ‘answer from question 1’

I strongly identify with ‘answer from Question 1’

I feel great when ‘answer from Question 1’ is popular

I want to be friends with people who like ‘answer from Question 1’

Product Involvement Question 10 – (to be measured on 5-point Likert scales, Strongly Disagree to Strongly Agree)

I attach great importance to popular music concerts

Popular music concerts interest me a lot

I couldn’t care less about attending popular music concerts

I really enjoy attending popular music concerts

Whenever I attend a popular music concert, it is like giving myself a gift

Attending popular music concerts is pleasurable

I can tell a lot about a person from the concert he or she attends

That I attend popular music concerts says a lot about me

My attendance to popular music concerts gives others a glimpse of who I am

When I choose a concert to attend, it is not a big deal if I make a mistake

I get annoyed when I attend a concert that does not meet my needs

I would be upset if, after I attended a concert, I found I had made a poor choice

When I can select from several concerts, I always feel rather unsure about which one

to pick

When choosing to go to a concert from among other activities, I always feel confident that I will make the right choice

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Motivations Question 11- (to be measured on 5-point Likert scales, Strongly Disagree to Strongly Agree) Physical Skills

I appreciate the physical skills of ‘answer from Question 1’

I enjoy watching a well-executed ‘answer from Question 1’concert performance

It is important for ‘answer from Question 1’to showcase their skill level at concerts

I will only watch ‘answer from Question 1’if they demonstrate great physical skill in their performance

Social Interaction

Interacting with other fans is a very important part of attending a ‘answer from

Question 1’concert

I talk to other people sitting/standing near me at a ‘answer from Question 1’concert

A ‘answer from Question 1’concert is a great way to socialise with strangers

I feel part of a group with similar interests when attending a ‘answer from Question

1’concert

I attended the ‘answer from Question 1’ concert to spend time with my friends

I attended the ‘answer from Question 1’ concert to be with people who enjoy the same

things I do

Experience Concert Specific Music

It is important to me to hear music at ‘answer from Question 1’concerts that has not

yet released

I enjoy hearing ‘answer from Question 1’play covers at concerts

I enjoy hearting acoustic versions of ‘answer from Question 1’songs at concerts Listening to live music at a ‘answer from Question 1’concert is better than listening to recorded music

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Hero Worship

Being in close proximity to ‘answer from Question 1’is important to me

I need to attend a ‘answer from Question 1’concert to show my support and dedication

Attending concerts is an important way to show ‘answer from Question 1’that I am a

fan

Supporting ‘answer from Question 1’is important to me


When I attend a ‘answer from Question 1’concert I engage in social behaviour that may otherwise not be allowed in a normal social setting The ‘answer from Question 1’concert experience stimulates me to act in a way that I would not normally act Being able to dance, ‘head-bang’ or air guitar in an uninhibited setting is an important reason why I attended the ‘answer from Question 1’concert Experiencing music at very high decibels is an appealing feature of a ‘answer from Question 1’concert

Personal Nostalgia

I like to attend a ‘answer from Question 1’concert because it takes me back to when I listened to them in my childhood I like to attend ‘answer from Question 1’concerts because I didn’t get to see them as a child Attending a ‘answer from Question 1’concert allows me to relive happy memories from the past

Aesthetics

I appreciate the beauty inherent in the performance of ‘answer from Question

1’concerts

I think the production and theatrical performance of a ‘answer from Question

1’concert is beautiful

I have an artistic appreciation for the technical skill of the artists performing at a ‘answer from Question 1’concert

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Escape

Attending a ‘answer from Question 1’concert represents an escape for me from my day to day activities A ‘answer from Question 1’concert is a great change of pace from what I regularly do

I looked forward to the ‘answer from Question 1’concert because it is different to other leisure activities I normally do I attended the ‘answer from Question 1’concert to relieve the boredom of everyday life

Physical Attraction

I enjoy watching ‘answer from Question 1’because they are physically attractive

The main reason I attended the ‘answer from Question 1’concert is because I find the performers attractive The sex appeal of an individual band member/artist was more important to me than the music at the ‘answer from Question 1’concert

Status Enhancement

The more ‘answer from Question 1’concerts I attend, the bigger the fan I am

I like to talk and brag about ‘answer from Question 1’concerts I have been to

I am not a true fan of ‘answer from Question 1’if I do not go to their concert/s

Going to ‘answer from Question 1’ concerts that other people don’t go to makes me

feel special

I believe the more ‘answer from Question 1’concerts I attend, the more people will be impressed by me

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Question 12 My main motivation for attending ‘answer from Question 1’was: (pick one only)

To appreciate the physical skills of ‘answer from Question 1’

To interact with my friends and/or other fans

To experience ‘answer from Question 1’’smusic that can only be heard at a concert

To worship and to show my dedication to ‘answer from Question 1’

To engage in uninhibited behaviour (e.g. dancing, moshing, head banging, very loud

music)

To relive a time from my past

For the inherent beauty of the music

To escape everyday life

To admire the physical attractiveness of ‘answer from Question 1’or a member of ‘answer from Question 1’ To spend time with family

To show others that I am a true ‘answer from Question 1’fan

□ Other, please specify ____________________________________

Question 13 I have seen ‘answer from Question 1’:

1 time only 2 times 3 – 5 times 6 – 10 times More than 10 times

Question 14 On average I would attend popular music concerts:

Once a year Twice a year 3 – 5 times a year 6 – 10 times a year More than 10 times a year

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Question 15 (to be measured on 5-point Likert scales, Strongly Disagree to Strongly Agree)

I am willing to travel to multiple cities to see ‘answer from Question 1’

I am willing to travel to multiple states to see ‘answer from Question 1’

I am willing to travel overseas to see ‘answer from Question 1’

I would attend concerts by other artists/bands in the same genre as ‘answer from

Question 1’

I would attend concerts by other artists/bands outside ‘answer from Question 1’’s

genre

Question 16 How much did you pay for the ticket to see ‘answer from Question 1’?

$___________ Question 17 How much would you have been willing to pay for a ticket to see ‘answer from Question 1’?

$___________ Question 18 How much would you be willing to pay for tickets to other bands in the same genre as ‘answer from Question 1’?

$___________ Question 19 How much would you be willing to pay for a ticket to other bands outside the genre of ‘answer from Question 1’?

$___________ Question 20 Did you leave your seat or standing position during the concert?

□ Yes (Go to Question 18) □ No (Go to Question 19)

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Question 21 For what purpose did you leave your seat/position? (Tick all that apply)

To socialise with friends To get a drink from the bar To purchase food or non-alcoholic beverage To go to the bathroom To get some fresh air To make/take a phone call Other, please specify ___________________________

Question 22 Did you do any of the following at the ‘answer from Question 1’concert?

Purchase merchandise Get merchandise signed Wait around to see/meet ‘answer from Question 1’after the show Go backstage Wear a previously owned ‘answer from Question 1’t-shirt Dress up in a meaningful outfit to identify with ‘answer from Question 1’ Consume alcohol Push to the front of the crowd Dance Mosh Go out after the concert Meet up with other fans

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Question 23 In reference to ‘answer from Question 1’, please indicate if you do any of the following:

Like ‘answer from Question 1’on Facebook

Follow ‘answer from Question 1’on Social Media (e.g. Twitter)

Have joined a ‘answer from Question 1’Fan Club

Interact in a ‘answer from Question 1’fan community

Engage in discussion on a ‘answer from Question 1’discussion forum

Collect recorded music by ‘answer from Question 1’

Download ‘answer from Question 1’music

Perform ‘answer from Question 1’web searches

Follow the personal life of ‘answer from Question 1’

Seek physical contact with ‘answer from Question 1’

Wear a ‘answer from Question 1’t-shirt other than at a concert

Collect factual data on ‘answer from Question 1’including artist history

Demographics Question 24 I am:

□ Male

□ Female Question 25 I am:

19 years old or under 20 – 29 years old 30 – 39 years old 40 – 49 years old 50 – 59 years old 60 years old or over

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Question 26 My annual income is:

Less than $25,000 $25,000 - $49,999 $50,000 - $74,999 $75,000 - $99,999 $100,000 or more

Question 26 My annual household income is:

Less than $25,000 $25,000 - $49,999 $50,000 - $74,999 $75,000 - $99,999 $100,000 or more

Question 27 What is your marital status? Single without dependent children Single with dependent children Couple without dependent children Couple with dependent children Question 28 What is your employment status? Unemployed Casual Part time Full time Student also working full time Student working causal or part time Student only

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APPENDIX G: English Translations for the CIP Scale

Rodgers and Schneiders CIP Scale - English Translation

Laurent and Kapferer's CIP Scale - English Translation

Interest Interest

I attach great importance to ________. What ________ I buy is extremely important to me.

________ interests me a lot. I'm really interested in ________.

________ leaves me totally indifferent. I couldn't care less about ________.

Pleasure Pleasure

It would give me pleasure to purchase ________ for myself.

I really enjoy buying ________.

When you buy ________, it is a bit like giving a gift to yourself.

Whenever I buy ________, it’s like giving myself a present.

Having ________ is a pleasure for me. To me, ________ is quite a pleasure (or: I quite enjoy ________).

Sign Sign

You can tell something about a person by the ________ s(he) picks out.

You can tell a lot about a person from the ________ he or she buys.

The ________ you buy tells a little bit about you. The ________ a person buys, says something about who they are.

The ________ I buy shows what type of man/woman I am. The ________ I buy reflects the sort of person I am.

Risk Importance Risk Importance

When you choose a ________, it is not a big deal if you make a mistake.

It doesn't matter too much if one makes a mistake buying ________.

It certainly is annoying to purchase ________ that doesn't meet my needs.

It's very irritating to buy ________ which isn't right.

I would be really upset if, after I bought some ________ I found I had made a poor choice.

I should be annoyed with myself, if it turned out I'd made the wrong choice when buying ________.

Risk Probability Risk Probability

When you purchase ________, you are never certain you made the right choice.

When I'm in front of the ________ section, I always feel rather unsure about what to pick.

Whenever you buy ________, you never really know whether it is the one you should have bought.

When you buy ________, you can never be quite sure it was the right choice or not.

When I can select from several ________, I always feel a bit at a loss in making my choice.

Choosing a ________ is rather difficult.

Choosing ________ is rather complicated. When you buy ________, you can never be quite certain about your choice.

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APPENDIX H: Proposed Unique Motivations for Popular Music Concert Attendance

Motivations Definition Source

Vicarious Achievement

The need for social prestige, self-esteem and sense of empowerment that an individual can receive from their association with a popular artist/band.


Acquisition of Knowledge

The need to learn more about the artist/band or individual band members through interaction and media consumption.


Aesthetics The artistic appreciation of the music due to its inherent beauty


Social Interaction

The need to interact and socialise with others of like interests to achieve feelings that one is part of a group, sense of belonging.

Adapted from Fink et al, (2002); Earl (2001) and Oakes (2010)

Escape The need to find a diversion from work and the normal, unexciting activity of everyday life.


Family The opportunity to spend time with one's family doing something everyone enjoys.


Physical Attractiveness of Artist(s)

Watching concerts because of the physical attractiveness or 'sex appeal' of an individual artist/band member or band.


Physical Skill of Artist(s)



Identity Enhancement

Accessing the experience to live a different identity and/or to intensify a fragmented identity

Firat and Dholakia (1998); Caru and Cova (2006)

Concert Specific Music

Hearing 'live' music that is not released on CD's and videos - meaning attendance is the only means of experiencing some particular aspect of the artists' performance (experience in full the visual dimension, unique performances (e.g. covers and improvisation).

Earl (2001)

Joy of Live Performances

Excitement that cannot be created by a recording, awareness of unpredictability


Sampling without commitment

Experiencing unfamiliar groups without commitment. Earl (2001)

Hero Worship

Getting physically close to famous people, form of pilgrimage and paying of homage to music heroes, thrill of proximity


Opportunity for uninhibited behaviour

Social behaviour that may be precluded in a domestic setting (deafening sound levels: volume, darkness).

Earl (2001)

Status Enhancement

enhance the status of a fan in subsequent social encounters with someone who did not get to see the artist live

Oakes (2010)

Stagecraft Visual surprise, dramatic spectacle Oakes (2010)

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APPENDIX I: Data Cleaning and Re-specification Activities for the Survey Data

Note: None of these data cleaningn or respecification activities affected the main variables used in this study.

1. Variables were renamed to meaningful codes to assist with analysis.

2. Recoded ‘Type of Ticket’ to include common ‘Other’ categories:

a. Categories added i. General Admission – no seating available, outdoor concert

ii. Free tickets, Gift iii. VIP, Backstage, Corporate Box

3. Recoded ‘Genre’ to include ‘Other’ popular categories

a. Categories added i. Indie

4. Main Motivation

a. Added “Entertainment/Fun” b. The “Family” code also now includes, ‘to keep partner company’ c. Added “See support band” d. Added “Once in a lifetime opportunity”

5. Reasons for leaving seat

a. Added “Dance” b. Added “To get a better view/position” c. Added “To smoke”

6. Fixed Spelling and punctuation for band and artists names

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APPENDIX J: Product Involvement Normality Testing

Product Invovlement Histograms

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Normality

Looking at the Shapiro-Wilk Tests of Normality it appears that responses to all the product involvement questions may not be normally distributed. Whilst this is not ideal as one of the assumptions for factor analysis is that each variable should be approximately normally distributed, factor analysis is fairly robust against violations of this assumption (Allen and Bennett, 2010). The Shapiro-Wilk Test of Normality is also quite sensitive to small deviations from normality and there are only five response options for each question. Of the 16 variables, 6 variables have skewness values within the range of +/-2(SE), with ALL variables falling within an absolute skewness and kurtosis value of two. Applying these rules, the skewness and kurtosis values are within the range of which is considered a reasonable approximation to the normal curve (Lomax and Hahs-Vaughn, 2012).

Product Involvement Descriptive Statistics

Item Mean S.D. Skewness Kurtosis

Statistic Std. Error Statistic Std. Error

PI_1 3.23 1.114 -.175 .109 -.607 .218

PI_2 3.77 .971 -.591 .109 .071 .218

PI_3 2.14 1.079 .643 .109 -.312 .218

PI_4 4.10 .841 -.783 .109 .520 .218

PI_5 3.94 1.004 -.826 .109 .194 .218

PI_6 4.19 .810 -1.059 .109 1.574 .218

PI_7 3.21 1.092 -.284 .109 -.521 .218

PI_8 3.08 1.099 -.081 .109 -.610 .218

PI_9 3.10 1.136 -.147 .109 -.696 .218

PI_10 2.84 1.029 .054 .109 -.463 .218

PI_11 3.62 1.002 -.457 .109 -.317 .218

PI_12 3.59 1.056 -.457 .109 -.414 .218

PI_13 2.62 1.118 .253 .109 -.648 .218

PI_14 3.82 .851 -.451 .109 .239 .218

PI_15 2.63 1.112 .219 .109 -.672 .218

PI_16 2.69 1.083 -.016 .109 -.821 .218

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APPENDIX K: Fan Identification Normality Testing and EFA

Fan Identification Histograms

Fan Identification Descriptive Statistics


Statistic Std. Error Statistic Std. Error

Fan_ID_1 2.42 1.371 .582 .109 -.927 .218

Fan_ID_2 2.79 1.238 .139 .109 -.881 .218

Fan_ID_3 2.60 1.232 .331 .109 -.847 .218

Fan_ID_4 2.72 1.194 .211 .109 -.840 .218

Fan_ID_5 2.02 1.126 .937 .109 .061 .218

Fan_ID_6 2.82 1.314 .161 .109 -1.131 .218

Fan_ID_7 3.09 1.174 -.093 .109 -.770 .218

Fan_ID_8 3.24 1.165 -.186 .109 -.680 .218

Fan_ID_9 3.06 1.194 -.144 .109 -.742 .218

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Normality

Looking at the Shapiro-Wilk Tests of Normality it appears that responses to all the motivation questions may not be normally distributed. Whilst this is not ideal as one of the assumptions for factor analysis is that each variable should be approximately normally distributed, factor analysis is fairly robust against violations of this assumption (Allen and Bennett, 2010). The Shapiro-Wilk Test of Normality is also quite sensitive to small deviations from normality and there are only five response options for each question. Of the nine variables, six variables have skewness values within the range of +/-2(SE), with ALL variables falling within an absolute skewness and kurtosis value of two. Applying these rules, the skewness and kurtosis values are within the range of which is considered a reasonable approximation to the normal curve (Lomax and Hahs-Vaughn, 2012).


As the data was normally distributed, Maximum Likelihood extraction method was used. Direct Oblimin (oblique) rotation was selected as the factors were likely to be correlated. An orthogonal rotation should also not be used when there is a theoretical expectation as it will distort any general factor in the data (Stewart, 1981).

The correlation matrix reporting the bivariate correlations between each pair of variables shows that all variables have at least one correlation greater than 0.3, meaning the data are suitable for factor analysis (Francis, 2013).

The Kaiser-Meyer-Olkin (KMO) Measure of Sampling Adequacy reports the amount of variance in the data that can be explained by the factors. This value is 0.941 which is marvellous (Kaiser, 1974). The Bartlett’s Test of Sphericity is significant (p = 0.000) meaning that there are significant correlations to be investigated (See Figure 1 below).

Figure 1: KMO and Bartlett’s Test

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Anti-image Matrices are used to further determine the suitability of factor analysis (Allen and Bennett, 2010). All the KMO values for each variable in the anti-image matrix are above 0.928 (which is much greater than 0.5) and therefore we do not have to consider dropping any variables from the analyses at this stage.

The communalities table indicates how much variance can be explained by each of the variables (Allen and Bennett, 2010). The commonalities ranged from 0.443 – 0.614.

As expected, the Total Variance Explained table shows that there was one strong underlying factor to the data (See Figure 2).

Figure 2: Total Variance Explained

Results show that 54.319% of the variance can be explained by this factor.

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APPENDIX L: Motivations Normality Testing

Motivation Histograms

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Normality

Looking at the Shapiro-Wilk Tests of Normality it appears that responses to all

the motivation questions may not be normally distributed. Whilst this is not

ideal as one of the assumptions for factor analysis is that each variable should be

approximately normally distributed, factor analysis is fairly robust against

violations of this assumption (Allen and Bennett, 2010). The Shapiro-Wilk Test of

Normality is also quite sensitive to small deviations from normality and there are

only five response options for each question. Of the 40 variables, 13 variables have

skewness values within the range of +/-2(SE), with ALL variables falling within an

absolute skewness and kurtosis value of two. Applying these rules, the skewness

and kurtosis values are within the range of which is considered a reasonable

approximation to the normal curve (Lomax and Hahs-Vaughn, 2012).

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Motivation Descriptive Statistics


Statistic Std. Error Statistic Std.

Error PS_1 3.76 1.082 -.704 .109 -.041 .218 PS_2 4.39 .744 -1.128 .109 1.210 .218 PS_3 4.11 .853 -.820 .109 .424 .218 PS_4 2.78 1.173 .001 .109 -.859 .218 SI_1 2.89 1.182 .050 .109 -.819 .218 SI_2 3.12 1.223 -.189 .109 -.941 .218 SI_3 2.92 1.179 -.025 .109 -.837 .218 SI_4 3.36 1.130 -.404 .109 -.494 .218 SI_5 3.21 1.250 -.255 .109 -.931 .218 SI_6 3.21 1.207 -.313 .109 -.820 .218

CSM_1 3.21 1.086 -.141 .109 -.538 .218 CSM_2 3.49 1.144 -.413 .109 -.582 .218 CSM_3 3.74 1.032 -.584 .109 -.116 .218 CSM_4 4.09 .888 -.640 .109 -.314 .218 HW_1 2.86 1.248 .085 .109 -.998 .218 HW_2 2.85 1.196 .112 .109 -.775 .218 HW_3 3.20 1.219 -.197 .109 -.850 .218 HW_4 3.11 1.154 -.113 .109 -.731 .218 UB_1 2.35 1.243 .427 .109 -.992 .218 UB_2 2.55 1.268 .287 .109 -1.009 .218 UB_3 2.39 1.275 .490 .109 -.883 .218 UB_4 3.02 1.303 -.104 .109 -1.081 .218 N_1 2.96 1.362 -.106 .109 -1.205 .218 N_2 2.69 1.384 .233 .109 -1.207 .218 N_3 3.37 1.229 -.446 .109 -.688 .218 A_1 3.69 1.014 -.546 .109 -.082 .218 A_2 3.68 1.025 -.446 .109 -.355 .218 A_3 3.88 .970 -.637 .109 -.018 .218 E_1 3.64 1.075 -.665 .109 -.025 .218 E_2 3.72 1.031 -.736 .109 .264 .218 E_3 3.80 1.004 -.789 .109 .368 .218 E_4 2.85 1.286 .070 .109 -1.048 .218

PA_1 2.56 1.345 .348 .109 -1.044 .218 PA_2 2.31 1.278 .528 .109 -.939 .218 PA_3 1.97 1.157 .982 .109 -.066 .218 SE_1 2.55 1.326 .329 .109 -1.092 .218 SE_2 2.48 1.244 .376 .109 -.905 .218 SE_3 2.17 1.181 .693 .109 -.534 .218 SE_4 2.43 1.242 .446 .109 -.839 .218 SE_5 1.97 1.150 .984 .109 -.005 .218

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Exploratory Factor Analysis – First Run

As the data was normally distributed, Maximum Likelihood extraction method was used. Direct Oblimin (oblique) rotation was selected as the factors (motivations for attendance) were likely to be correlated. An orthogonal rotation should also not be used when there is a theoretical expectation as it will distort any general factor in the data (Stewart, 1981).

The correlation matrix reporting the bivariate correlations between each pair of variables shows that all variables have at least one correlation greater than 0.3, meaning the data are suitable for factor analysis (Francis, 2013).

The Kaiser-Meyer-Olkin (KMO) Measure of Sampling Adequacy reports the amount of variance in the data that can be explained by the factors. This value is 0.935 which is marvellous (Kaiser, 1974). The Bartlett’s Test of Sphericity is significant (p = 0.000) meaning that there are significant correlations to be investigated (See Figure 1 below).


Anti-image Matrices are used to further determine the suitability of factor analysis (Allen and Bennett, 2010). All the KMO values for each variable in the anti-image matrix are above 0.844 (which is much greater than 0.5) and therefore we do not have to consider dropping any variables from the analyses at this stage.

The communalities table indicates how much variance can be explained by each of the variables (Allen and Bennett, 2010). The commonality for item four was quite low (0.249), whilst the majority of others were greater than 0.6.

As expected, the Total Variance Explained table shows that there were 10 strong underlying factors to the data (See Figure 2).

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Results show that 59.596% of the variance can be explained by these 10 factors. An examination of the Scree Plot indicates that the scree appears to start at factor 11 (Figure 3).

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Figure 3: Cattell’s Scree Test


According to Francis (2013), a loading is significant if it is greater than 0.3, provided that at least 50 participants were used in the study. In this study (n=60), all items loaded strongly on only one factor, and all loadings were greater than 0.3, except item four, and item 14 which was just on the cusp at 0.302. The loading for item 4 ‘I will only watch [Q1 RESPONSE] if they demonstrate great physical skill in their performance’ was suppressed as it was below 0.3. The majority of the remaining loadings were above 0.6. Both item four and item 14 ‘Listening to live music at a [Q1 RESPONSE] concert is better than listening to recorded music’ were removed and the analysis was re-run.

Factor Analysis – Second Run

The analysis was performed again using Maximum Likelihood extraction with a Direct Oblimin rotation. There was a slight increase in The Kaiser-Meyer-Olkin (KMO) Measure of Sampling Adequacy (0.936) with the Bartlett’s test still significant (p = 0.000).

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As expected, the Total Variance Explained table still shows a strong underlying 10 factors to the data, explaining now 61.20% of the variance (See Figure 6).



The Direct Oblimin rotated factor structure for the 38 motivation items are shown below (see Table 1 and Table 2).

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Table 1: Direct Oblimin Rotated Factor Structure of Items 1 – 22 (excluding Item 4 and 14)

Item Factor Loadings

1a 2b 3c 4d 5e 6f 7g 8h 9i 10j 1. I appreciate the physical skills of [Q1

RESPONSE]

0.540

2. I enjoy watching a well-executed [Q1 RESPONSE]concert performance

0.615

3. It is important for [Q1 RESPONSE]to

showcase their skill level at concerts

0.573

5. Interacting with other fans is a very important part of attending a [Q1 RESPONSE]concert

0.749

6. I talk to other people sitting/standing near me at a [Q1 RESPONSE] concert

0.799

7. A [Q1 RESPONSE]concert is a great way to socialise with strangers

0.730

8. I feel part of a group with similar interests when attending a [Q1 RESPONSE] concert

0.510

9. I attended the [Q1 RESPONSE] concert to spend time with my friends

0.469

10. I attended the [Q1 RESPONSE] concert to be with people who enjoy the same things I do

0.600

11. It is important to me to hear music at [Q1 RESPONSE]concerts that has not yet been released

0.495

12. I enjoy hearing [Q1 RESPONSE] play covers at concerts

0.489

13. I enjoy hearing acoustic versions of [Q1 RESPONSE]songs at concerts

0.612

15. Being in close proximity to [Q1 RESPONSE] is important to me 0.700

16. I need to attend a [Q1 RESPONSE] concert to show my support and dedication 0.772

17. Attending concerts is an important way to show [Q1 RESPONSE] that I am a fan 0.728

18. Supporting [Q1 RESPONSE]is important to me 0.717

19. When I attend a [Q1 RESPONSE] concert I engage in social behaviour that may otherwise not be allowed in a normal social setting

-0.721

20. The [Q1 RESPONSE]concert experience stimulates me to act in a way that I would not normally act

-0.722

21. Being able to dance, ‘head-bang’ or air guitar in an uninhibited setting is an important reason why I attended the [Q1 RESPONSE]concert

-0.519

22. Experiencing music at very high decibels is an appealing feature of a [Q1 RESPONSE]concert

-0.392

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Table 2: Direct Oblimin Rotated Factor Structure of Items 23 - 40

Item Factor Loadings

1a 2b 3c 4d 5e 6f 7g 8h 9i 10j 23. I like to attend a [Q1 RESPONSE] concert

because it takes me back to when I listened to them as a child

-0.96

24. I like to attend [Q1 RESPONSE]concerts because I didn’t get to see them as a child

-0.643

25. Attending a [Q1 RESPONSE] concert allows me to relive happy memories from the past

-0.724

26. I appreciate the beauty inherent in the performance of [Q1 RESPONSE]concerts

0.954

27. I think the production and theatrical

performance of a [Q1 RESPONSE]concert is beautiful

0.652

28. I have an artistic appreciation for the technical skill of the artists performing at a [Q1 RESPONSE]concert

0.572

29. Attending a [Q1 RESPONSE]concert represents an escape for me from my day to day activities

0.725

30. A [Q1 RESPONSE]concert is a great change of pace from what I regularly do

0.761

31. I looked forward to the [Q1

RESPONSE]concert because it is different to other leisure activities I normally do

0.650

32. I attended the [Q1 RESPONSE]concert to relieve the boredom of everyday life

0.451

33. I enjoy watching [Q1

RESPONSE]because they are physically attractive

0.760

34. The main reason I attended the [Q1 RESPONSE] concert is because I find the performers attractive

0.746

35. The sex appeal of an individual band member/artist was more important to me than the music at the [Q1 RESPONSE]concert

0.612

36. The more [Q1 RESPONSE]concerts I attend, the bigger the fan I am

0.676

37. I like to talk and brag about [Q1

RESPONSE]concerts I have been to

0.600

38. I am not a true fan of [Q1 RESPONSE]if I do not go to their concert/s

0.708

39. Going to [Q1 RESPONSE] concerts that

other people don’t go to makes me feel special

0.671

40. I believe the more [Q1 RESPONSE]concerts I attend, the more people will be impressed by me

0.733

Percentage of Variance: 30.6 9.27 3.983 3.73 2.442 2.04 2.2 1.8 1.857 1.67

Note: a = Hero Worship, b = Aesthetics, c = Nostalgia, d = Social Interaction, e = Uninhibited Behaviour, f = Physical Attractiveness, g = Escape, h = Status Enhancement, i = Physical Skills, j = New and Concert Specific Music.

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APPENDIX M: Product Involvement Models

First Order Model

df 17

χ2 29.808

CMIN/DF 1.753

GFI 0.986

CFI 0.992

RMSEA 0.039

PCLOSE 0.772

SRMR 0.0250

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Second Order Model

df 18

χ2 31.589

CMIN/DF 1.755

GFI 0.985

CFI 0.991

RMSEA 0.039

PCLOSE 0.780

SRMR 0.0261

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APPENDIX N: Motivations Models First Order Model

df 398

χ2 877.140

CMIN/DF 2.204

GFI 0.893

CFI 0.947

RMSEA 0.049

PCLOSE 0.637

SRMR 0.0547

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Second Order Model

df 425

χ2 1237.297

CMIN/DF 2.911

GFI 0.825

CFI 0.910

RMSEA 0.062

PCLOSE 0.000

SRMR 0.0830

∆χ2(27)= 360.157

p-value = <0.0001

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APPENDIX O: Final Structural Models

Average Number of Popular Music concerts per Year

df 2366.108

χ2 1064

CMIN/DF 2.224

CFI 0.905

RMSEA 0.049

PCLOSE 0.635

SRMR 0.0739

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Amount Willing to Pay

df 2358.547

χ2 1064

CMIN/DF 2.217

CFI 0.905

RMSEA 0.049

PCLOSE 0.667

SRMR 0.0733

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df 2466.277

χ2 1158

CMIN/DF 2.130

CFI 0.912

RMSEA 0.047

PCLOSE 0.944

SRMR 0.0713

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APPENDIX P: Structural Model Specification Activities

All modifications made to the final structural models are detailed in Chapter 4. In

all models however, excluding ‘Willingness to Travel’, a negative error variance

occurred for the residual associated with PROB1 – an item on the Risk Probability

facet of Product Involvement. The following details and provides justification for

dealing with this situation.

Dealing with the negative error variance associated with PROB1

Negative error variance estimates occur frequently (Jöreskog and Lawley, 1968),

and may indicate something is wrong with the model, data, or estimator.

Negative error variances or ‘Heywood’ cases can arise from several causes.

Anderson and Gerbing (1984) suggest that sample size and model specification

aspects such as the number of indicators and having too many factors are related

to the incidence of improper solutions. It is also possible that non positive error

variances could simply be due to sampling fluctuation (Chen et al., 2001). Chen,

Bollen, Paxton, Curran and Kirby (2001) suggest that researchers should not use

negative error variance estimates as an indicator of model misspecification and

propose a strategy for dealing with negative error variance estimates.

(1) Check that the model is identified.

The t-Rule was applied to ensure that the number of parameters to be

estimated in the model did not exceed the number of unique variance and

covariance’s in the sample variance-covariance matrix (Bollen, 1989). All

models were completely over identified, with all models having in excess

of one thousand degrees of freedom.

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(2) Estimate the model without constraining the error variance to be positive.

As required in this step, the estimation converges. The converged solution

indicates a single negative error variance is present.

(3) Determine whether negative error variance is due to outliers or influential

cases.

In this step, the dataset was examined for the presence of any unusual

values or outliers. No unusual influential cases were identified. A check for

univariate outliers was performed to identify any extreme values regarding

the problem variable. There were six cases that had a variance z-score

greater than 3.29 (representing only 1.2% of the sample), though for all six

cases the z-score had a value of only 3.315 which is just on the cut off, and

this small number of cases were unlikely to effect the estimates. This was

actually confirmed by re-running the analysis with these six cases

removed, and the value for the negative error variance actually increased.

(4) Check for empirical under identification.

Kenny (1979) states that “if in the sample there is perfect collinearity, or if

some covariance or effect is empirically zero the model will be empirically

under identified” (p. 145). Evidence of empirical under identification could

not be found as all correlations between constructs were greater than zero,

and did not exceed 0.70 (Tabachnick & Fidell, 2001).

(5) Test whether negative error variances might be due to sampling fluctuations

In order to determine whether the negative error variance estimates might

be due to sampling fluctuations a Wald test was conducted. A significant

result would suggest that the error variance is below zero in the

population and model misspecification should be suspected. A non-

significant result however, is consistent with the idea of sampling

variability leading to the negative estimate (Chen et al., 2001).

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The Wald test hypotheses:

H0 = θk≥ 0

H1 = θk< 0

Where, θk equals the variance parameter of interest. The test statistic for

the Wald test is:

W = 𝜃�k - θk0 / (s.e [𝜃�k])

= 0.049 / 0.084

= -0.583

A test statistic of -0.583 for the Wald test gives a p-value of 0.560, which

indicates that the negative error variance is not significant, and is likely to

be a result of sampling variability and not model misspecification.

(6) Check the magnitude of the negative estimate

a. If the negative estimate of variance is not far from zero, constrain to

zero.

b. If negative estimate of variance is large, constraint unlikely to help.

The value of the negative error variance was not far from zero (-0.048) and

therefore a constraint at zero would provide less biased parameter

estimates than no constraint.

(7) Interpret estimates as usual.

Gerbing and Anderson (1987) have investigated the consequences of

constraining an error variance to be nonnegative and have found that fit

measures are not greatly affected, with the possible exception of the last

constraint in which the error variance was set to a positive number. In this

case, the negative error variance is associated with one of the risk probability

items which measure a first order factor on the second order construct,

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product involvement. Therefore the loading of the item with the negative

error variance (now constrained) will be increased and the other indicator on

the risk probability factor may slightly decrease with the improper solution,

but all remaining loadings will be largely unaffected across the unconstrained

and constrained solutions (Gerbing and Anderson, 1987). The resulting

estimates were therefore interpreted as usual, and those parameters that were

most closely associated with the troublesome error variance estimates which

were likely to have a higher bias were not detrimental to the interpretation of

the structural model.

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