Dissertation complete copy 250416

Major Independent Study

Fans’ Perceptions of Competitive Balance and Its Impact on Willingness-to-Pay for a Single Ticket: A Stated Preference Approach in relation to English

Rugby Union and Rugby League.

Russell White – c3388462

Leeds Beckett University Carnegie Faculty of Sport and Education

Submitted in Part fulfillment of the degree of Sport Business Management

Declaration

I can confirm that this MIS constitutes my own work.

I can confirm that the text in this submission does not exceed the upper word limit of 12,000 words.

Researcher’s signature:

Russell White: _________________________

Supervisor’s signature:

Alex Bond: ____________________________

1

Table of Contents

Acknowledgments 4

Abstract 5

Chapter 1 – Introduction 6 1.1 – Research Aims and Objective 1.2 – Rationale

Chapter 2 – Review of the Literature 10 2.1 – Introduction 102.2 – Determinants of Demand 102.3 – Competitive Balance 112.4 – Measurements of Competitive Balance 142.5 – Perceived Competitive Balance 152.6 – Team Identification 16

Chapter 3 – Methodology 17 3.1 – Introduction 173.2 – Sport Spectator Identification Scale (SSIS 173.3 – Primary Data Analysis 173.4 – Sample Design and Overview 213.5 – Ethical Considerations 22

Chapter 4 – Results and Discussion 23 4.1 – Introduction 234.2 – Descriptive Statistics 23

4.2.1 – Team Identification (Team ID) 234.2.2 – Perceived Competitive Balance (PCP) 244.2.3 – Willingness-to-Pay (WTP) 26

4.3 – Team Identification’s Influence on Perceptions of Competitive Balance 274.4 – Team Identification’s Influence on Competitive Intensity 284.5 – Team Identification’s Influence on Willingness-to-Pay 304.6 – Competitive Balance & Competitive Intensity’s Influence on WTP 31

Chapter 5 – Conclusion 33 5.1 – Recommendations 36

Chapter 6 – Personal Reflection 36

References 37

Appendices 45

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List of FiguresFigure 1 – Socio-demographics of the sample………….…………………………20-21

Figure 2 – Team identification averages for rugby union and rugby league fans….24

Figure 3 – Team identification averages for season ticket holders and non-season ticket holders………………………..……………………………………………………..25

Figure 4 – Team identification averages for male and female…………………….…25

Figure 5 – Regression analysis of team identifications influence on rugby union fans’ perceptions of CB……………………………..…………………………………………..28

Figure 6 – Regression analysis of team identifications influence on Rugby union fans’ perceptions of competitive intensity…………………………………………….……....29

List of Appendices1.0 – Participation Consent Form

2.0 – Participation Information Sheet

3.0 – The Final Questionnaire

4.0 – Carnegie Faculty MIS Progress Report Form 01/11/15






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Acknowledgments

Here I would like to take time to thank all of those that have contributed to the

development of this study.

First and foremost, Alex Bond my supervisor has consistently provided me with

extensive knowledge, support and advice throughout the year and this has allowed

me to grasp some of the tougher aspects of this field. Coupled with being my MIS

supervisor and at times an unofficial tutor, Alex has allowed me to reach new heights

when it comes to academic work and this work I hope reflects just that.

Secondly, there have been a number of other lecturers on the course that have

provided both excellent support and extensive topic knowledge and to name just a

few would be a disservice to the others. However, Hazel Hartley has taught me two

Sport Law modules during my 2nd and 3rd years. Hazel’s willingness to go the extra

mile for her students that are willing to do the same is highly commendable. This year

alone her support, vast experience and knowledge as well as scrutinising of each

piece of work to ensure the greatest quality has allowed me to produce the highest

grade of my university career so far and has allowed me to understand not just my

own ability but also the great depths academics must go in doing so.

A big thank you must also be issued to my family and friends that provided me with

extensive support and encouragement throughout my three years at university and

has significantly helped me in attaining my degree. A special thanks must be given to

my parents, which have gone above and beyond throughout my academic life so far

to provide me with great opportunities.

I dedicate this work to you all.

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Abstract

This piece of work set out to investigate the perceptions of competitive balance

(PCB) of rugby union and rugby league fans and whether it has an impact on their

willingness to pay for a single ticket. Along the way, team identification levels and

perceptions of competitive intensity (PCI) were also measured. Adapting the

questionnaire from Pawlowski’s and Budzinski’s (2013) study on European football

fans’ perceptions of CB, the questionnaire was filtered onto several different fan

forums and Facebook pages. The questionnaire possessed the Sport Spectator

Identification Scale introduced by Wann and Branscombe (1993) as well as relevant

CI questions formulated from the work of Kringstad and Gerrard (2004). A number of

regression analysis tests were used to determine relationships between team ID,

PCB, PCI and WTP. Results indicated that as team identification increased so did the

rugby union fans’ perceptions of CB. When each factor of CB was measured, the

findings suggested rugby unions preferred to watch a game with a clear outsider and

uncertainty of outcome, contrasting literature suggests that imbalanced home and

away teams is more important. Perceptions of CI was seen to be more important to

rugby union fans. Although interestingly the First Utility Super League has undergone

extensive restructuring in recent years, however the Rugby League fans’ stated a

very minor positive relationship to an open league structure, albeit insignificant.

Suggesting the recent structural changes may have been redundant. The analysis of

fans’ WTP was rather inconclusive but with limitations to questioning previously

distinguished, this could have been expected. Significance of findings, limitations and

recommendations for future research are presented.

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1.0 Introduction

A comparison of live attendance figures between the most established major team

sports in the UK (Cricket, Football, rugby union and Rugby League) was performed

between the years 2010-2011 and 2014 and 2015 (Mintel, 2015). It was established

that both rugby union and rugby league had significantly lower attendances than all

football and cricket leagues; cricket’s attendance records for 2011-2014 averaged

2.22 million, the English Premier League (EPL) attendance for the seasons 2010/11 -

2014/15 expectedly exceeds this enormously averaging 13.58 million (Mintel, 2015).

In comparison, rugby league for seasons 2011-2014 averaged 1.8 million

attendances, which was still 0.12 million more than the rugby union figures

experienced for seasons 2010/11-2014/15 (Mintel, 2015). These major differences

between both disciplines of rugby and other major UK team sports highlight

something needs to be done to increase rugby’s attendance levels. Particularly as

the live sporting event is the “principal product” for all professional sports

(Greenwood, Kanters and Casper, 2006).

The Competitive balance (CB) theory introduced in the seminal work of Rottenberg

(1956), Neale (1964) and Sloane (1971) has long been established as one of the

biggest determinants of spectator attendance, with many academics agreeing it is

crucial to the prosperity of any sport league (Noll, 1974; Sloane, 1980; Forrest,

Simmons and Buraimo, 2009; Kaplan, Nadeau and O’Reilly, 2011). Rottenberg

(1956) and Neale (1964) propose that due to sports abnormalities in comparison to

other industries (joint-production), it is regarded that competitors must be equally

matched to engender fan interest and generate high levels of revenue. Since the

work of Rottenberg and Neale, CB has undergone extensive research to find

concepts to help explain fan attendance; the uncertainty of outcome hypothesis

(UOH) (Knowles, 1992; Zimbalist, 2002), seasonal and long run uncertainty (Cairns

et al., 1986; Kesenne, 2007; King et al., 2010) and competitive intensity (Kringstad

and Gerrard, 2004; 2007; Gerrard, 2009) have been thoroughly researched.

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Additionally, team identification (team ID) has been studied to provide yet another

explanation to the queries circling spectator demand. The concept links spectator’s

fundamental psychosomatic association with their team and their behaviour as

consumers (Madrigal and Chen, 2008). The concept stems from the seminal work of

Wann and Branscombe (1993) and the shared assumptions are that greater levels of

team ID lead to greater spectator attendance (Parry, Wann and Jones., 2014), added

levels of investment in time and money spent on their club (Wann and Branscombe,

1993) and higher levels of enjoyment at live events (Wann and Schrader, 1997).

Although there is a resounding agreement throughout literature that fan team

identification correlates with consumer behaviours, sports knowledge and purchasing

patterns. This study will be able to examine identification levels against spectator’s

perceptions of CB and their willingness -to-pay for a single live event.

The aforementioned aspects of CB are commonly referred to as objective

competitive balance (OCB), and these studies statistically measure CB and attempt

to explain the gap in the literature surrounding the prominence of match and

seasonal uncertainty on fan attendance (Pawlowski and Budzinski, 2013). Therefore,

a distinction is required to establish between fans’ actual behaviour and how they

perceive competitive balance as opposed to ascribing CB’s impact on spectators’

attendance based on existing measures of CB (Pawlowski and Budzinksi, 2013). It is

thought that a stated preference approach to CB will provide a greater insight into

certain sports economics (Budzinski and Pawlowski, 2014). Investigating this in

accordance with the guidelines of both studies by Pawlowski and Budzinski (2013)

and Nalbantis et al., (2015), it will allow primary data to be gathered and directly

associated with rugby union and rugby league fans’ perceptions of CB as well as

provide an insight into their current levels of PCB and if there is any effect on their

willingness-to-pay for a single ticket. With this in mind, below illustrates the study’s

aim coinciding with objectives that have been created to aid the attainment of the

aim.

1.1 Research Aims & ObjectivesAim:

To understand rugby league's and rugby union's fans' perceptions of competitive

balance and the impact it has on their willingness to pay.

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Objectives:

• Critically investigate Team identification levels of rugby league and rugby union

fans.

• Critically investigate rugby union and rugby league fans’ perceptions of

Competitive Balance.

• Critically analyse rugby league’s and rugby union fans’ willingness to pay for a

single ticket.

• Critically analyse any differences between the rugby union and rugby league fans.

2.2 RationaleWhilst studying BA (Hons) Sport Business Management, the notion of CB was

introduced in the Economics and Finance module during 2nd year. After careful

consideration and research performed for both MIS proposal and the level 5 module,

it was apparent that both CB research was inconclusive and that Rugby, specifically

based in the UK, had been researched in relation to CB only very slightly. Williams

(2012) critically analyses and reviews the competitive balance (CB) measures within

the professional rugby union in England. Williams highlights that there is a “gap in the

literature” surrounding the subject and rugby. In addition, he adds:

“further research on competitive balance (CB) within rugby union and other professional leagues in Europe and beyond, is required to broaden an understanding of rugby’s competitive dynamic” (Williams, 2012 pp. 88-102).

Hogan, Massey and Massey (2013) also highlight the very little attention rugby has

received in relation to CB studies, highlighting that due rugby union’s recent

professionalisation, it makes it an interesting sport to research. Rugby league

proposes an interesting case in its own right due to the struggles it has faced with

competing against other major team sports and the major structural changes

undergone in the last two decades (Meir, 2000). Additionally, with all the CB research

that has been completed, very little conclusive evidence has been produced that

affirms CB does have an effect on spectator attendances (Syzmanski, 2003; Buraimo

and Simmons, 2008; Pawlowski and Budzinski, 2013).

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Furthermore, career aspirations include; working within the marketing or business

industry helping firms infiltrate new markets and providing them with detailed reports

on concerns to market behaviours. Hopefully, this piece of work will assist any

forthcoming career paths as well as provide an insight into the attendance figures

and potential generated income of rugby union and rugby league competitions.

2.0 Review of Literature

2.1 IntroductionBoorland and MacDonald (2003) suggest that understanding the nature of sport and

the determinants that can affect demand, are helpful when examining professional

sports leagues. McMillan (1997) explains that in economic terms, sport is labelled as

“peculiar” due to its product producing no output; as well as the event or match

(product) being “jointly produced” (Neale, 1964; Trenberth and Hassan, 2012). With

this in mind, major discrepancies in spectator attendances for any sports league and

its members is a large concern (Douvis, 2014). Thus, the following chapter of this

investigation will provide an understanding of the literature and developed theories of

CB, Team ID and CI in relation to spectator’s willingness to pay.

2.2 Determinants of DemandConsistent with the seminal work of Neale (1964) and Sloane (1971), there has been

extensive research into the determinants of demand for sport presented by Noll

(1974), Cairns et al (1986), Welki and Zlatoper (1991) and Dawson (2000). Schofield

(1983) categorised the variety of different aspects that affect professional sports

attendance into; economical, demographical, game attractiveness and enduring

preferences. Likewise, Avgerinou (2007) more recently divided the determinants of

demand for any sport into the following; short term (UOH), long term (fan

preferences), economical and demographical factors. Although there are a number of

determinants considered significant in affecting spectator demand, a shared

perception from academics in this area of literature; is that for professional sports

leagues, CB is a commanding determinant for prosperity and survival (Rottenberg,

1956; Neale, 1964; Noll, 1974; Sloane, 1980; Forrest and Simmons; Booth, 2009).

Budzinski and Pawlowski (2014: 3) emphasise the combination of CB and the

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uncertainty of outcome hypothesis (UOH) is in the interest of all members of a

sporting event; “as increased CB; increases UOH; increases demand; increases

revenue”. Additional determinants include; demographic (Fink et al, 2002), economic

(Fort, 2010), fan satisfaction (Shonk & Chelladurai, 2008), socio-motivational factors

(Zhang et al, 2001), stadium quality (Zygmont and Leadley, 2005), team success

(Gitter and Rhoades, 2010) and team identification (Wann and Branscombe, 1993).

2.3 Competitive BalanceMaxcy and Mandello (2006), Spalding (2014) and Jungic et al (2015) amongst

others, have extensively documented CB throughout literature surrounding sports

economics. Renowned for its prominence to the sustainability of sports leagues, CB

frequently causes a concern for sports economists, industry managers and

spectators (Kringstad, 2008). CB incorporates the UOH that surrounds sporting

events, introduced into sports economics by the seminal work of Rottenberg (1956)

(Humphreys, 2002; Lee and Fort, 2008). The theory stems from the “assumption”

that sport fans’ maintain a desire to attend matches where teams are of equivalent

abilities (competitively balanced); proposing that this creates a greater uncertainty of

the result, thus, generate larger attendance figures (Knowles et al., 1992: 72; Forrest

and Simmons, 2002; Kaplan, Nadeau and O’Reilly, 2011; Zimbalist, 2002).

Ultimately, demand is expected to be affected by the concept of CB through the

hypothesis of the uncertainty of the outcome (Scully, 1989; Kringstad, 2008). Unlike

other business ventures, professional sports teams require the survival of other

teams to be successful (Rottenberg, 1956). Neale comments on the peculiarity of

professional sports leagues, in relation to American sports teams; and explains when

San Diego Chargers in 1961 near enough eradicated all competitors, a loss of fan

interest was observed (1964). Therefore, this suggests that fans prefer equality and

many commanding teams must think “Oh Lord make us good, but not that good”

(Neal, 1964:2). Similarly, the 1950s saw the New York Yankees win their seventh title

in eight years, due to the unequally distributed talent and subsequent competitive

disparity (Sanderson and Siegfried, 2006). Levin et al (2000) explain until each team

has an equal probability of reaching postseason play, CB cannot be understood

properly.

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Post-Neale, sport economists have focused on measuring team strengths, match

uncertainty as well as different variations of uncertainty (medium-term and long-term)

to see whether it possesses a positive functional relationship with consumer demand

(Peel and Thomas, 1997; Falter and Perginon, 2000; Sacheti et al, 2014; Mills and

Fort, 2014). On the contrary, other sports economists have focused on analysing CB,

identifying trends and evaluating sports league’s policy changes (Dobson et al, 2001;

Fort and Maxcy, 2003; Peeters, 2011; Kent et al, 2013; Owen and King, 2013).

In addition, to match uncertainty, many academics have looked at both seasonal and

long-run championship uncertainty (Kesenne, 2007; Cairns, Jennet and Sloane,

1986). It is suggested that the longer the competition lasts and the greater the

chance of more teams winning a positive impact on demand should be seen (Cairns,

1987). Measures of seasonal uncertainty vary from the number of games required to

make the playoffs or win the championship (Borland and Lye, 1992), to the

significance of the match for the championship, playoffs or relegations (Dobson et al,

2001; Madalozzo and Villar, 2009). The measures are often used to help explain

spectator demand, with the anticipation of less significant matches drawing few

numbers of spectators (King, Owen and Audas, 2011). Their study concluded that

seasonal uncertainty increased spectator demand, greater than the normal single

match uncertainty (King, Owen and Audas, 2011).

Long run domination or consecutive-season domination, refers to the anticipation of

one or few teams dominating a given league (competitive imbalance) and

subsequently decreasing the championship uncertainty and its spectator demand

(King, Owen and Audas, 2011). It is also considered to promote fear of loss of both

“profit and revenue” for both the league and its teams (Downward, Dawson &

Dejonghe, 2009: 219). The possibility of matches being competitively imbalanced for

consecutive seasons is regarded as something fans don’t wish to spectate (Kesenne,

2007; Forest and Simmons, 2002). The concern shared by any professional sport

that witnesses prolonged dominance by a single team, is the effects it has on their

league’s revenue and spectator demand; detrimental impacts such as these has

given rise to the study of CB (O’Reilly, Nadeau and Kaplan, 2011). The principle of

CB is simply to produce a league with a greater equality between its teams so that

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fan welfare and satisfaction improve, which in turn improves league revenue

(O’Reiley et al, 2008; Schmidt and Berri, 2001).

Although, the UOH has undergone extensive research, when used as a base for

policy interventions it is treated with animosity due to its lack of conclusive evidence

(Buraimo and Simmons, 2008). In fact, from 22 studies, 45.45% provided support for

the UOH, 31.8% provided weak support for the concept, whilst the remainders

provided zero support (Szymanski, 2003; Boorland and Macdonald, 2003). Wilson

and Sim (1995), Bainbridge et al (1996) and Iho ad Heikkila (2009) all found the UOH

had a diminutive impact on consumer demand within European football fans. In fact,

Buraimo and Simmons (2009) concluded consumers would much rather watch their

team play a much inferior team, with the likelihood of winning much greater. In

contrast, Falter and Perignon (2000) concluded that UOH did lead to an increase in

spectator demand for football in France. Equally, Borland (1987) and Peel and

Thomas (1997) discovered similar affirmative effects of UOH in Australian Rules

football and English Rugby League, respectively (cited in Sacheti et al, 2014).

Szymanski (2003) suggests that the lack of consensus could be a result of a lack of

differentiation between match uncertainty, seasonal uncertainty and championship

uncertainty. Equally, Sacheti et al propose “whether the absolute strength of teams

does indeed exert an effect on demand, independent of relative team strength or

UOH” (2014: 2034). CB has shown little conclusive evidence of the importance of

match uncertainty or seasonal outcomes, in relation to the spectator demand for

European Football (Pawlowski and Budzinski, 2013).

It is evident that the concept of CB is complex, encompassing a variety of different

aspects of competition (Bennet & Fizel, 1995; Quirk & Fort, 1992). Kringstad and

Gerrard (2004: 120; Kringstad, 2008) introduced the concept of “competitive

intensity” which refers to “the degree of competition in a league with regards to its

“prize structure”. This refers to the many aspects of a league’s structure and their

post-season tournaments that many teams qualify for whilst also competing in the

domestic competition (Kringstad and Gerrard, 2004; Kringstad, 2008). This concept

is narrowly linked to CB, however, does not inevitably move in the same way and this

makes it difficult to infiltrate within the existing concept of CB (Kringstad and Gerrard,

2004: Kringstad, 2007). For example, a league may face reduced CB from an

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increase in variations of team abilities, yet see an increase in CI due to changes to its

prize structure (Kringstad, 2008). If this increase in CI is large enough, spectator

demand may rise overall (Kringstad, 2007). The fundamental principle that CI

attempts to capture is this concept of match significance introduced by Jennet (1984:

cited in Kringstad & Gerrard, 2004).

2.4 Measurements of Competitive BalanceConsidering the extensive research on the uncertainty of outcome and its contentious

stance in sports economics, little consensus or discussion has arisen from “the

nature of its measurement” (Downward and Dawson, 2003: 303; Buraimo and

Simmons, 2008). The measures of match uncertainty often use the following two

variables; match betting odds or teams’ relative performance (league standing, points

total or win percentages) prior the event (Owen, King and Audas, 2011). Hart, Hutton

and Sharot (1975), Falter and Perignon (2000), Benz et al (2009) and Madalozzo and

Villar (2009) all attempted to determine outcome uncertainty by using the team’s pre-

match league place as an indicator for pre-match uncertainty. However, all studies

can be argued as not adequately capturing the true form of a team or taking into

account home advantage (Forrest and Simmons, 2002). Peel and Thomas (1988),

Czarnitzki and Stadtmann (2002) and Lemke et al (2009), amongst others have used

pre-match betting odds to measure the level of uncertainty. Concerns surrounding

this variable are the bias of odds setting as well as the inability to recall historical

records for such odds (Buraimo and Simmons, 2008; Dobson and Goddard, 2001;

Owen, King and Audas, 2011). Moreover, perhaps the three types of uncertainty

should be measured interactively. For example, betting odds should be formulated

into a quadratic procedure along with league standings (Sloane, 2006).

As previously mentioned the measures with concerns to seasonal uncertainty

include; number of games required to make the playoffs or win the championship

(Borland and Lye, 1992), to the significance of the match for the championship,

playoffs or relegations (Madalozzo et al, 2009) or the number of points teams in

contention trail the leader (Meehan et al, 2007). A downfall of these measures is they

contain information unlikely known to the spectator when they decided to attend,

such as a number of games required to make the playoffs (Dawson and Downward,

2005). Likewise, whilst this variable provides a suitable guideline in illustrating who

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remains in contention for the championship (Owen, King and Audas, 2011); a

comparative measure between a team’s expected performance and its rivals would

be considered better, although more difficult to perform (Sloane, 2006).

Contrastingly, it is possible to measure play-off (seasonal) or match uncertainty by

stimulating or forecasting the matches not yet played in the season (Bojke, 2008;

Owen, King and Audas, 2011). However, such methods are more technologically

demanding hence used in a limited number empirical studies (Goodard and Sloane,

2014). The last type of uncertainty (long-run) has been significantly less studied

(Goddard and Sloane, 2014); measures include an incorporation of the previously

mentioned measures however implemented over a lengthier period of time (Boorland

and MacDonald, 2003).

2.5 Perceived Competitive BalanceZimberlast (2002) suggests to gain a comprehensive connection between

competitive balance and spectator attendance, an understanding of fans’ perception

is key (cited in Coates and Humphreys, 2010). Leach (2006: 117) in relation to

professional football comments there is a “lack of certainty about outcome

uncertainty”, suggesting a refusal of the UOH. However, Budzinski and Pawlowski

(2014: 9) regard the rejection of CB and UOH and their relationship with spectator

attendance as a “premature conclusion”. Adding that the little empirical evidence

stems from associating CB and outcome uncertainty with global statistical measures,

which don’t undisputedly reflect the “perceptions” of the fans (Pawlowski and

Budzinski, 2013: 9). Pawlowski and Budzinski differentiate between objective

competitive balance (OCB) and perceived competitive balance (PCB), unlike other

studies that have made the two identical (2013). PCB looks to describe the behaviour

of spectator’s in terms of consistency of “mind and actions”, as opposed to OCB

which attempts to determine fan’s behaviour in terms of statistical data (Budzinski

and Pawloski, 2013: 10). The study indicates that due to a “threshold effect” fans

perceive any additional CB above the threshold as inconsequential, however if CB

drops below that threshold discontinuous demand should be expected (Budzinski

and Pawlowski, 2013: 22). Moreover, the study indicates prior experiences differently

determine an individual fans’ perceptions of similar OCB levels – “framing effect”

(Budzinski and Pawloski, 2013: 22). Pawlowski and Budzinski (2013) conclude it’s

required a consideration that fans perceive CB inversely from previous statistically

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measured methods to help understand the effects of CB on the economic success,

revenues, profits, etc. in any given league. Nalbantis, Pawlowski and Coates (2015)

progress from the previous PCB study by Pawloski and Budzinski (2013) to study the

relationship between fans’ willingness to pay (WTP) and their perceptions of CB.

Their study illustrates a positive correlation between the two variables, but

interestingly follows the similar “threshold effect” cited in the Pawlowski and

Budzinski (2013) paper. They conclude that fans are willing to pay more for a ticket

and even the quality of their seat but only until a point where after increased

“suspense” has no additional impact (Nalbantis, Pawlowski and Coates, 2015).

2.6 Team IdentificationOne of the most established concepts within sports consumption is the underlying

emotional connection supporters possess with a sports team, quantified by team

identification (Stewart and Smith, 1999; Madrigal and Chen, 2008). Thus, a

fundamental construct within team management is to explain consumption behaviour,

as a means of financial gain (Wann and Branscombe, 1993). Many academics

conclude that higher team identification leads to an increase in demand (Wann and

Branscombe, 1993; Trail, Fink and Anderson, 2003; Fink et al, 2009). Seminal team

identification work of Wann and Bransombe (1990) is rooted within the Social Identity

Theory (SIT). This explains that individuals attach themselves to groups that provide

positive reflections of their own self-perception, which implies identification

formulates through membership to a group often derived from race, class,

demographics and geographical location (Hogg et al., 1995). A “multidimensional

typology” like Wann and Branscombe’s (1993) SSIS, attempts to interpret the “multi-

faceted nature of the sports consumer” (Stewart et al., 2003; quoted in Warren, 2011:

16).

A review of the sports fan team identification literature presents positive associations

with many sporting fans’ behaviours (Greenwood, Kanters and Casper., 2006). It is

presented that higher identified fans will attend more games (Wakefield, 1995; Wann

et al., 1999; Parry, Wann and Jones, 2014), spend more time watching their team

play (Wann and Branscombe, 1993), possess a more optimistic approach to the

future success of their team (Wann and Branscombe, 1993), view live events as

more enjoyable (Madrigal, 1995; Wann and Schrader, 1997) and possess a greater

15

willingness to invest watching their team play (Wann and Branscombe, 1993). In

relation to this study, it will be interesting to observe whether the aforementioned

attributes of WTP and PCB, will be affected by the sample’s team identification.

3.0 Methodology

3.1 IntroductionThis chapter illustrates the methods employed throughout this study. It will begin by

discussing the paradigm that was followed and an evaluation of the limitations and

justifications. The following section will analyse the tools and design research

implemented in this study.

3.2 Sports Spectator Identification ScaleThe team identification implemented within this survey consists of the seven items of

Sports Spectator Identification Scale (SSIS) with a 10 point response format as

opposed to the customary 8 point (strongly agree to strongly disagree), so it remains

constant with the rest of the survey (Wann and Branscombe, 1993). The components

of the SSIS measure the individual’s perceptions of being a fan of the particular

team, the eminence of winning, the degree to which the individual sees themselves

as a fan of that team, the magnitude to which their friends see them as a supporter,

how closely the individual follows the progress of the team, how often the fan

displays or wears the team’s apparel or badge, and to what degree the individual

dislikes their respective team’s greatest adversaries (Wann and Branscombe, 1993).

The SSIS is a valid and reliable measure of team identification and has been used

throughout the literature. The SSIS combines the seven elements to create a single

16

measure of identification (Greenwood, Kanters and Casper, 2006). The seven items

assess an individual from their perceptions of being a fan of the particular team to the

extent to which his/ her friends (see appendix for all seven items) (Wann and

Branscombe, 1993). The SSIS is suggested as the most effective measure of

identification to predict consumption behaviour (Wann et al., 2003), thus justification

for its use in this questionnaire (see appendix 3.0)

Greenwood, Kanters and Casper (2006) highlight that the extensive use of SSIS

throughout the literature (Gayton et al., 1998; Wann, 1996; Wann et al., 2003),

verifies the scale’s reliability and comprehensive psychometric properties. The

psychometric strength is continuously reinforced, with recent studies by Theodrakis

et al., (2012), Parry, Wann and Jones (2014) and Park & Dittmore (2014) all

employing the measurement.

3.3 Primary Data AnalysisTo examine fans’ perceptions of CB in the Aviva Premiership and First Utility Super

League and its impact on their willingness-to-pay, an online questionnaire was

filtered through rugby league and rugby union fan forums and Facebook pages.

Much like other PCB studies completed (Pawlowski & Budzinski, 2013; Pawlowski,

Coates and Nalbantis, 2015), the data gathered is quantitative. Specifically, the

make-up of this questionnaire follows recent similar stated preference studies of the

Nalbantis, Pawlowski & Coates (2015) and Pawlowski & Budzinski (2013) and

Pawlowski (2013b); all of which were performed in relation to professional European

football.

Stated preference studies differ from the usual competitive balance studies in the

literature. In the previous chapter of this study, the various “tried and true”

measurements of CB that heavily feature in literature were listed in detail (Utt and

Fort, 2002: 373). Standard deviation, Gini coefficient, C5 index and Herfindahl –

Hirschman methods that interpret the distribution of winning percentages, seasonal

imbalance, concentration rates of the league’s top five teams and the sharing of the

championship’s title, are all calculated using secondary data (Gurel & Gokce, 2012;

Leeds and von Allmen, 2005; Depken, 1999). However, designing and implementing

17

a questionnaire based on the recent studies conducted by Pawlowski and Budzinski

(2013) allowed primary research to be collected.

An integral process of an SP study is the carefully considered design and

operationalization of the elicitation questions (Nalbantis et al, 2015; Reja et al, 2003).

Poorly worded questions, poor visual design and over complicated questionnaires

can result in “item” or “unit” no response (Reja et al, 2003: 160). The elicitation

questions found in this particular survey are based around the consumer’s WTP; the

respondents were asked to provide their ‘maximum’ WTP for upcoming matches

(Nalbantis et al, 2015). These questions are “open ended” and this allows the

respondent to provide an individual preference as opposed to the constrictions of

choosing an alternative like “closed questions” (Foddy, 1993). These open-ended

questions allow participants to respond impetuously, which can alleviate any potential

(hypothetical) bias that may occur when a respondent is given suggested

alternatives, much like when closed questions are used (Reja et al, 2003; Green et

al, 1998). These open-ended questions do possess disadvantages, such as taking

longer to code and greater item non-response (Reja et al, 2003; Louviere et al,

2001). Additionally, Loomis (2011) explains that stated preference (SP) surveys can

comprise for hypothetical bias and it can arise when the respondents reported WTP

exceeds the amount they would pay in an experiment that would involve their actual

money. This frequently occurring SP bias is insufficiently understood and its absence

of “theoretical or systemic” explanation, means it remains problematic for SP studies

(Mitani and Flores, 2010: 3).

However, it is suggested the more acquainted with the product or service the

consumer is, the significantly less likely the hypothetical bias is to occur (Schlapfer

and Fischhoff, 2012). Thus, this online questionnaire was distributed onto specific

rugby League and rugby union fan forums (ShedWeb, Leicester Tigers Forum &

Scrum V) as well as broad fan forums (Total Rugby League Fans Forum & the Rugby

Forum) plus fan Facebook pages (Rugby Union World Wide Fan Zone). This ensured

that the respondents completing the questionnaire would have sufficient industry

knowledge such as ticket deals or values and subsequently this would reduce the

disparity between true and hypothetical bias towards their WTP (Nalbantis et al,

2015).

18

“The expansion of the internet and diffusion of web-based tools” makes online

questionnaires a simple and practical technology for collecting data and preferences

of customers (Randelli et al, 2012: 803). Online questionnaires possess many

advantages such as the reduced cost and increased the speed of data collection that

was had in this study compared to more traditional variations of survey

implementation (Callegaro et al, 2015; Hardigan et al 2012; Strabac and Aalberg,

2011; Fricker and Schonlau, 2002). Additionally, time and geographical constraints

were non-existent, as once the survey was posted online, it was conceivable to

collect data continuously as well as allow access to anyone from anywhere in the

world (Callegaro et al 2015). Due to the self-administration variable of online surveys,

respondents were able to cooperate at their own pace, which in turn allowed them to

provide thorough and increased accuracy in their answers (Callegero and Wells,

2008).

Academics argue that using the internet to distribute a study’s questionnaire does

omit those in society without internet access, whilst also still not alleviating the issue

of question clarity (Gratton and Jones, 2010). However, with over 8 out of 10 adults

now online with any internet accessible device and 98% of adults aged 16-24 and 25-

34 online (OfCom, 2014). Therefore, it is possible to confidently disregard that

argument as very little of the population are omitted from using online questionnaires

as a data collection method (OfCom, 2014). Additionally, it is reported that 83% of all

online users are online to gather knowledge and information about their hobbies and

interests as well as 52% users online to obtain news on sport (PEW, 2011). The use

of the aforementioned various social media platforms (Facebook and fan forums) has

increased in recent years since sports fans have shifted their fandom to online

activities; thus, these platforms heavily feature in a number of research articles

surrounding consumer behaviours and motives (Ruihley and Hardin, 2014; Hur et al,

2007; Seo and Green, 2008).

Prior to distributing the questionnaire on to the selected platforms, a group of 10 were

provided with a draft of the questionnaire to offer feedback with regards to the length,

understanding, and phrasing of questions (Creswell, 2007). The main issues

highlighted from the feedback was the length of the survey due to the study

19

incorporation of duplicate questions for each discipline of rugby (see appendix 4 for

example). Therefore, exactly similar worded questions were omitted and the

questions combined to alleviate this issue. Other alterations were made to the

questionnaire due to the direct translation from German left some questions

incoherent and influent (appendix 3.0 illustrates the final questionnaire). The

questionnaire’s original 4-scale Likert scale was replaced with a 10-scale; based on

the work of Cooke et al (2001) and Dawes (2002). Although this leaves a reliance on

the respondent using a numerical response for which a precise meaning has not

been provided; this limitation is balanced with a lot of the population familiar with the

notion of grading ‘out of 10’ (Dawes, 2008). Additionally, it is suggested increasing

the number of variances in the scale does increase the reliability (Hartley and Betts,

2010).

Finally, once the data was collected and the research terminated, the computer

software ‘Statistical Package for the Social Sciences’ (SPSS) was used to statistically

analyse the data collected. SPSS has a broad range of statistics and almost every

analysis technique required for social sciences or business application (Berkowitz,

1998). The software takes non-numerical collected data, then codes the data and

transforms it into numerical form providing a translation into statistical information

(Gratton and Jones, 2010; IBM, 2016). For example, a question such as; what

discipline does your rugby team play? Can be coded as 1 for rugby union and 2 for

rugby League. A variety of tests were performed to gauge any comparisons between

the two sets of fans, these include; t-tests, cross-tabulations, and regressions.

3.4 Sample Design and OverviewThe net sample size was n=140. As previously mentioned this study was adapted

from the Pawlowski and Budzinsksi (2013) questionnaire. For this questionnaire to be

effective the target sample had to be located via various suitable online platforms

(fan forums and Facebook pages). This illustrates a non-random sample, the various

online methods used, provided the best chance in acquiring a large data set from an

appropriately targeted audience and acquire data that best fits the criteria (Neuman,

2013).

20

Figure1 - This provides a simplified cross-tabulation descriptive breakdown of the sample's socio-demographic

characteristics.

Socio – Demographics Rugby union sample Rugby League

sample

Gender (male; female) (92; 7) (37; 4)

Highest Qualification(still at school; GCSEs; A-Levels;

Degree; PhD; Other)

(2; 1; 19; 69; 3; 5) (0; 2; 12; 23; 1; 3)

Employment Status(full-time; part-time; student;

pensioner; not working by choice)

(37; 5; 45; 5; 7) (18; 0; 18; 0; 5)

Household size(1-4; 5-9; 10-14) (68; 28; 3) (33; 7; 1)

Personal Income(0-£500; £501-£1000; £1001-£1500;

£1501-£2000; £2001-£2500; £2501-

£3000; £3001-£3500; £3501 >)

(30; 13; 8; 8; 15; 5; 7;

13)

(14; 5; 8; 4; 2; 2; 3; 3)

Household Income(0-£500; £501-£1000; £1001-£1500;

£1501-£2000; £2001-£2500; £2501-

£3000; £3001-£3500; £3501 >)

(10; 8; 7; 8; 9; 10; 5; 42) (6; 5; 1; 6; 5; 2; 3; 13)

Mintel (2015) depicts that the pool of spectators and viewers for rugby union is very

narrowly and heavily dominated by males aged 65+, 37%. Additionally, only 28% of

the population asked said that they watched rugby league and rugby union live at a

stadium, 11% and 17% respectively (Mintel, 2015). This suggests the questions

relating to customer’s WTP as well as CB questions in relation to live events will be

targeting a much smaller proportion of rugby’s spectator population. Figure 1

illustrates the socio-demographics of the sample from this study. It is very clear to

see from this analysis the questionnaire was heavily male dominated. This was

expected, from the evidence provided by Mintel (2015). Additionally, on average 31.4

% of the respondents declared they had a net personal income (after taxes and

deductions) of £0 - £500, which would be expected when 45% of the respondents

21

were students. Which perhaps is one reason why both sample’s WTP average was

predominately low (as seen in figure 4). The high percentage of students that took

part in this study could well be down to the various methods of data collection used

such as Facebook pages and fan forums. This is important to consider whether or

not the sample used to collect this data was entirely representative of all the rugby

union and rugby league fans in the UK.

3.5 Ethical Considerations“Ethics is the study of good conduct, character, and motives” and it is concerned with

defining what is good or respectful for all people (Rani and Sharma, 2012: 45). One

of the most crucial ethical considerations is ‘informed consent’; this means each

participant is provided with sufficient knowledge regarding the research and they

have the ability to authorise or decline involvement voluntarily (Rani and Sharma,

2012; Gratton and Jones, 2010) (consent form can be seen in appendix 1.0).

McNamee et al (2007) add that frequently this aspect is disregarded and information

levels can fall below the necessary standards such as neglecting important details of

both the study and survey or written in a confusing manner. Thus, an information

sheet was provided prior to the consent form in an attempt to avoid this limitation

(appendix 2.0). Gratton and Jones (2010) also emphasise the importance of

confidentiality and anonymity. This consideration was comfortably alleviated by

reassuring the participants that after the data had been collected, no unauthorised

person will have access to the data set as well as making the data non-identifiable to

any participant.

22

4.0 Results and Discussion

4.1 IntroductionThis chapter will address the research’s main aim and objectives, outlined in the

introduction chapter of this study. Consequently, a detailed breakdown and analysis

will be provided of fans’ perceptions of CB for both rugby union and rugby league,

their willingness-to-pay for a single ticket and overall investigation into any contrasts

in behaviour between the two sets of fans.

4.2 Descriptive Stats4.2.1 Team IdentificationFan’s team identification was measured using seven separate questions; ranging

from whether they like to see their team win or whether they display their club’s

badge (see appendix for all related questions). In total, the entire Team Identification

mean total = 70. Performing an independent t-test (appendix) established the mean

for the rugby union sample = 47.7 and the rugby League sample = 45.4. This data

suggests that rugby union fans have a stronger identification with their respective

team than rugby league fans. The independent t-test also allows for a Levene’s test

23

for Equality of Variances; this test determines whether the two conditions (rugby

union or rugby league) have about the same or different amounts of variability around

their mean score (Starkweather, 2010). For these results, sig. value = 0.84 and this

determines that the mean score for the rugby union sample does not vary too much

more than the mean scores from rugby league. However, with the p-value = 0.392,

the differences are not statistically significant. The figure below illustrates which

conditions of team ID were scored higher on average than the others.

Fan’s that hold a season ticket the mean = 53.2, for non-STH the mean = 45,

suggesting that STH has a higher identification to their club which would be

expected. The Levene’s test for Equality in Variances determines that the variability

of the two scores are different and the p= 0.001, thus this difference is statistically

significant. Figures 2 & 3 below illustrate the greatest factors of Team ID for season

ticket holders (STHs), non-season ticket holders (non-STHs), males and females.

Figure 2 – This provides the team Identification averages for both Rugby union and Rugby League

Which discpline does your

team play? N Mean Std. Deviation Std. Error Mean

It Is Important My RC Wins Rugby union 99 7.85 2.215 .223

Rugby League 41 7.17 2.448 .382

I See Myself As A Fan Of My

RC

Rugby union 99 7.81 2.315 .233

Rugby League 41 7.29 2.442 .381

My Friends See Me As A Fan

Of My Club

Rugby union 99 7.29 2.528 .254

Rugby League 41 6.51 2.609 .407

It Is Important To Me That I

Am A Fan Of My RC

Rugby union 99 6.83 2.511 .252

Rugby League 41 6.54 2.628 .410

I Dislike The Greatest Rivals

Of My RugbyClub

Rugby union 99 5.13 3.033 .305

Rugby League 41 5.63 2.557 .399

I Often Display My RC Name

or Crest or Badge

Rugby union 99 5.32 2.649 .266

Rugby League 41 4.90 3.208 .501

I Closely Follow My RC Via

Tv or Online or News or

Radio

Rugby union 99 7.48 2.712 .273

Rugby League41 7.32 2.706 .423

With regards to gender, the male sample’s mean = 47.1 and women sample’s mean

= 45.9, which suggests that male supporters of rugby are more identified to their club.

24

Performing the same Levene’s test determined sig.= 0.42, illustrating that the two

conditions have largely similar variability. However, p= 0.79 determines it is not quite

statistically significant between males and females. As expected each of the

independent factors of team ID, STH scored higher on average than those not STHs.

However, STH on average scored lower than non-STH which regards to disliking

their greatest rivals. Both genders on average scored displaying their club's badge as

the lowest indicator of their Team ID. However, males scored seeing themselves as a

fan highest on average, with women scoring it is most important to see their team win

on average.

4.2.2 Perceived Competitive Balance

Fan’s perceptions of Competitive balance were measured by asking the importance

of the following statements; prior the game it is impossible to know the outcome,

home and away teams win just as often and whether there is a clear outsider. The

maximum PCB mean total = 30, another independent t-test was performed and

determined that the averages were very similar for each discipline, rugby union =

16.4 and rugby league = 16.3.

Figure 3 – This provides the team identification averages for STHs and Non-STHs

Are you a season ticket

holder at your club? N Mean Std. Deviation Std. Error Mean

It Is Important My RC Wins Yes 35 8.06 1.862 .315

No 105 7.51 2.418 .236

I See Myself As A Fan Of My

RC

Yes 35 8.74 1.821 .308

No 105 7.30 2.410 .235

My Friends See Me As A

Fan Of My Club

Yes 35 8.37 1.911 .323

No 105 6.63 2.617 .255

It Is Important To Me That I

Am A Fan Of My RC

Yes 35 7.66 2.114 .357

No 105 6.44 2.605 .254

I Dislike The Greatest Rivals

Of My RugbyClub

Yes 35 4.83 2.549 .431

No 105 5.43 3.006 .293

I Often Display My RC Name

or Crest or Badge

Yes 35 6.94 2.338 .395

No 105 4.62 2.733 .267

I Closely Follow My RC Via

Tv or Online or News or

Radio

Yes 35 8.63 2.030 .343

No105 7.04 2.787 .272

25

Figure 4 – This provides the team identification averages for male and females

Gender N Mean Std. Deviation Std. Error Mean

It Is Important My RC Wins Male 129 7.63 2.257 .199

Female 11 7.91 2.844 .858

I See Myself As A Fan Of My RC Male 129 7.67 2.356 .207

Female 11 7.45 2.464 .743

My Friends See Me As A Fan Of

My Club

Male 129 7.09 2.534 .223

Female 11 6.82 3.060 .923

It Is Important To Me That I Am

A Fan Of My RC

Male 129 6.74 2.501 .220

Female 11 6.73 3.101 .935

I Dislike The Greatest Rivals Of

My RugbyClub

Male 129 5.26 2.890 .254

Female 11 5.45 3.174 .957

I Often Display My RC Name or

Crest or Badge

Male 129 5.21 2.841 .250

Female 11 5.09 2.663 .803

I Closely Follow My RC Via Tv

or Online or News or Radio

Male 129 7.52 2.690 .237

Female 11 6.45 2.770 .835

Levene’s test concludes that the variability of the two disciplines in relation to PCB

are about the same. However, p = 0.92 determining that there is no statistical

significance between the two conditions. This same test was performed for PCB

against the sample’s gender and STHs. With male sample’s mean = 16.4 and

women’s = 15.6 and STH sample mean = 15.2 and non-STH mean = 16.7. This

suggests that non-STH males would perceive CB the lowest. The Levene’s test for

both conditions did show that the two gender scores and two STH scores did not

differ very much from each other as well determining that no statistically significant

difference was found.

Both fans of rugby league and rugby union scored highest in: “before the game it is

impossible to know which team will win”. However, rugby union Fans deemed both

home and away teams winning as least important, whereas rugby league supporters

deemed having no clear outsider is least important. Both male and female and STH

and non-STH scored before the game it is impossible to know the outcome as most

important and similarly scored home and away teams winning just as often as least

important.

26

4.2.3 Willingness-To-Pay

Fan’s willingness-to-pay was examined by observing how much they would be

prepared to pay to either increase their league’s excitement or to ensure their

league’s excitement does not decrease. Cross tabulations were performed to view

the differences between disciplines, gender, season ticket holders and income

preferences. Crosstabs allowed us to observe the percentages of each category

chosen by each variable. On average, over 75% of the rugby union fans said they

would be prepared to pay more to increase the level of competitiveness in the Aviva

Premiership. Likewise, over 85% of the rugby league fans stated they would be to

pay more in the First Utility Super League for the same outcome. Surprisingly, only

65% of the rugby union spectators would be prepared to pay more to ensure the

competitiveness in the Aviva Premiership does not decrease. Like the previous WTP,

a greater number of rugby league Fans (80%) were prepared to pay more to ensure

competitiveness does not decrease. The amounts that the spectators would be

willing to pay varied from £1-£2 to £21+.

4.3 Influence of Team Identification on the Perceptions of Competitive Balance

Anticipating that the entire sample size is a representation of supporters for domestic

English rugby (league and Union); the regression analysis illustrated a positive

relationship between Team ID and PCB. In fact, the coefficient = .40 with p= .000,

well within the social sciences required statistically significant level. This result

suggests that as a fan becomes more identified, they also perceive CB as more

important. This is interesting to observe as previous studies in relation to PCB such

as Pawlowski and Budzinski (2013) illustrate a relationship between CB and fan

attendance. Whereas this study is in relation to fan’s team identification and CB and

it shows a similar relationship but between higher identified fans and CB. Pawlowski

and Budzinski (2013) concluded that PCB does matter to spectators that attend

European Football matches and from this dataset it is apparent that PCB does matter

to English rugby union fans that more identified to they are to their team.

Implementing the same analysis but splitting the data into disciplines provided us

with two positive relationships varying in strength. The rugby League sample’s results

were not statistically significant but produced a positive relationship of 0.212.

27

Suggesting that when rugby league fans’ team identification increases, they do

perceive CB more importantly but being insignificant does not allow us to confidently

conclude those findings. However, the results calculated in relation to rugby union

illustrates both a positive relationship (coefficient= .50), as well as strongly significant,

p-value = .000. This data suggests that rugby union fans possess a greater

perception of CB, the more identified they become with their rugby club. Thus, while

previous studies have concluded that improved CB intensifies fan attendance in

Australian Football (Lenten, 2009), higher identification levels lead to greater

attendance in English football (Parry, Jones and Wann, 2014) and that CB does

matter to fans of German, Danish and Dutch Football (Pawlowski and Budzinski,

2013); this study can support this and confidently say that as English rugby union

fans’ become more identified they deem CB to be more important.

Linear regression was performed to also find out which individual factor of PCB had

the strongest relationship with team identification for each discipline. The rugby

league sample provided no statistically significant results, therefore, more research

will be required to conclude which specific factor of CB is perceived as important the

higher their team identification becomes. Contrastingly, the analysis did highlight the

more identified rugby union fans’ became with their team the greater they perceive

no clear outsiders and uncertainty of outcome as important. Furthermore, this

suggests that higher identification rugby union fans’ possess with their club, the more

important they see the uncertainty of outcome, much like the assumptions had

throughout the literature that sports spectators prefer to see a game that has an

uncertain result (Zimberlast, 2002). Interestingly these results also add to and

supports the study of Hogan, Massey and Massey (2013) which conclude that fans of

European rugby union also have a positive relationship with match uncertainty.

Hogan, Massey and Massey (2013) also state that European rugby Fans prefer to

watch a game between home and an away sides that are imbalanced. As seen in

figure 2, this as well is supported by this study that illustrates as English rugby union

fans become more identified to their rugby club, they too prefer to see an imbalance

between home and away teams albeit insignificant.

Figure 5 – Regression analysis of Team Identification influence on Rugby union fans’ Perceptions of CB

Model Unstandardized Coefficients Standardized

Coefficients

t Sig.

28

B Std. Error Beta

1 (Constant) 24.291 3.908 6.215 .000

Before the game it is

impossible to know which

team will win.

2.298 .629 .362 3.652 .000

Home and away teams win

just as often.-.695 .606 -.114 -1.147 .254

There is no clear outsider in

any of the games.2.427 .589 .389 4.124 .000

a. Which discpline does your team play? = Rugby union

b. Dependent Variable: IDTotal

4.4 Influence of Team Identification on Competitive Intensity

An additional linear regression was completed with Team ID as the dependent

variable against competitive intensity (CI). The test in relation to the whole sample

concluded a positive relationship of 0.404 with p= .000, which suggests that as fan’s

team ID increases the more important competitive intensity is perceived. When a

regression was performed individually in relation to both disciplines, a statistically

significant result was produced for the rugby union fans. The regression illustrated a

strong positive relationship between the two variables (see figure 6 below). A much

smaller positive relationship can also be observed for rugby League (coefficient

=0.18 rounded up), albeit insignificant. This suggests rugby union fans perceive CI

more importantly, the greater their team identification. Nonetheless, the two positive

results illustrate both sets of fans do prefer to see a league that possesses variations

to its prize structure which aligns with the previous work of Kringstad and Gerrard

(2007) on modern league structures. Although further research will be required so

that a statically significant result can be found.

Figure 6 – Regression analysis of Team Identifications influence on Rugby union fans’

perceptions of CI

Model

Unstandardized Coefficients

Standardized

Coefficients

t Sig.B Std. Error Beta

1 (Constant) 21.052 4.560 4.617 .000

CITOTAL .687 .113 .525 6.081 .000

a. Which discpline does your team play? = Rugby union

29

b. Dependent Variable: IDTotal

When executing a linear regression of Team ID total set against each CI question an

interesting observation can be had. Rugby union fans’ that Team ID increase

perceived the fight for post-season competition as most important; a very strong

relationship = .63 and p-value= .000. Whereas, rugby league fans’ had a negative

relationship albeit insignificant for this particular question. In contrast, the analysis

illustrates rugby league supporter's perceived a lengthy fight for the title as most

important and a very strong relationship can be found, beta= 0.74 and p= 0.22.

However, rugby union supporters demonstrated a much smaller relationship between

this question and elevated team identification levels. Interestingly, the rugby league

sample provided both an insignificant and a minor positive relationship between

increased team identification and importance of more teams being relegated. This

doesn’t support the overall consensus in the literature that often suggests a change

to the structure will positively impact match attendances (Dobson, Goddard and

Wilson, 2001). Much like the structural changes that of occurred in the First Utility

Super League, however, these results suggests that rugby league fans do not only

perceive relegation as of little importance to their league structure but that the

decision to make the First Utility Super League an open league, was made without

significant research.

4.5 Influence of Team Identification on Willingness-to-Pay

Analysing the entire sample’s relationship between team ID and WTP resulted in very

a minor relationship for both questions. However, to increase the league’s

competitiveness resulted in a positive relationship albeit very minor, whereas

ensuring the league’s competitiveness did not decrease produced a minor negative

relationship. This suggests that as the sample’s team identification increased they

were more willing to pay to increase the competitiveness. This is supported by

previous studies by Wann (1996) and Wann & Branscombe (1999) that conclude

higher identified fans are more likely to invest their time and money into their sport.

However, to ensure the competitiveness of their league did not decrease, the fans in

this study were less inclined to pay more. This contradicts the previous studies of

Wann (1999) and Wann and Branscombe (1993). Nonetheless, both results were

30

not statistically significant to the standard of social sciences (.05), producing p-values

=.658 and .434 therefore further research would be required to confidently support

these findings.

Both disciplines were individually analysed using the same regression test but no

significant results were produced. The test illustrates that the sample’s rugby union

fans’ WTP would actually decrease, albeit a minute decrease, for both questions.

This suggests that the more identified they become the less prepared they are to

invest on their league’s competitiveness. These findings contradict the majority of the

studies formulated around this topic (Wann and Branscombe, 1993; Sutton et al.,

1997), that concludes fans are more prepared to spend money on their team the

more identified they become. On the other hand, rugby league fans demonstrated

mixed results; indicating that the more affiliated with their club they become the less

willing they are to pay to ensure the league’s competitiveness doesn’t decrease

(coefficient= -0.42).This finding contradicts previous studies that suggest otherwise,

affirming as previously mentioned that the more identified fans become the more

likely they are to spend their earnings (Wann, 1999). However, they would be more

prepared to spend money to increase the league’s competitiveness; the results

indicate that a higher identification to their team leads to a .54 increase in their WTP.

This finding coincides with the existing literature however as neither disciplines

provided significant results further research will be required to confidently conclude

these findings.

Moreover, with rugby union and rugby league fans stating that they would be less

willing to pay more to ensure competitiveness does not decrease suggests that both

disciplines aren’t sensitive to CB (Pawlowski and Budzinkski, 2013). With rugby

league fans showing a strong positive relationship to increase competitiveness, whilst

rugby union fans’ produced a negative relationship; this suggests that although

higher identified rugby league fans aren’t hugely sensitive to CB but they could be

more sensitive than higher identified rugby union spectators. Consequently, the

competitive imbalance may be seen as more of a problem for highly identified rugby

league fans (Pawlowski and Budzinski, 2013).

4.6 Influence of Competitive Balance and Competitive Intensity on Fans’ WTP

31

Performing a linear regression with CB and CI totals as dependent variables, it

provides a relationship between them both and the fans’ WTP. Firstly, none of the

analysis tests provided a significant result, however, did provide varying degrees of

strength in regards to their association. As fans of both rugby league and rugby union

perceive CB more they both are more prepared to increase the excitement of their

respective leagues by making a financial contribution (coefficients, Union= .14 &

League= .28). A similar resemblance is had between the two sets of fans with

regards to ensuring the competitiveness of the league does not decrease. However,

this time, both sets of fans provided negative relationships; this suggests that the

higher they perceive CB they will not be prepared to make a financial contribution to

ensure their league’s competitiveness does not decrease (again League with a

stronger coefficient -.25).

The second regression analysis showed almost no relationship between both sets of

fans perceptions of competitive intensity and their WTP. The rugby union set of fans

provided two positive relationships which suggest they will be willing to pay more to

increase and maintain competitiveness the greater competitive intensity is. However,

these relationships are very weak, .04 and .05, respectively. Rugby league fans, on

the other hand, would be marginally more prepared to pay more to increase their

League’s competitiveness, .09. However, the analysis illustrates an increase of

competitive intensity for rugby league fans actually reduces their willingness to pay to

ensure competition does not decrease.

5.0 Conclusions & Recommendations

This final section will conclude this study in its entirety, focusing on strengths and

limitations of all the aspects included. Recommendations will follow this, stipulating

any details required for future research on this topic as well as future research

possibilities.

This study set out to find the perceptions of rugby union and rugby league fans’ and

their willingness to pay for a single ticket. This piece of work followed the studies of

Pawlowski and Budzinski (2013) and Nalbantis, Pawlowski and Coates (2015), both

32

of which take an unconventional view of CB. The review of literature gave a

comprehensive overview to the extent of which determinants of demand are

renowned for affecting attendance. Additionally, competitive balance, its subordinate

concepts (UOH and CI) and the array of previously tried and tested measurements

as well as the team identification concept were included. Much of the literature

highlights the inconclusive evidence for CB and can be concluded that this leads

from the subsequent disagreement of its correct measurement method. In fact, the

review of the literature surrounding PCB, although limited, concludes that SP

approaches are a better way to determine how fans’ consider CB and the effect it has

on revenues and attendances (Pawlowski and Budzinski, 2013; Nalbantis, Pawlowski

and Coates, 2015). Subsequently, it would be unsurprising if more competitive

balance studies pivot around this concept in the future.

Section 4.3 of this study highlights that rugby union fans’ do perceive CB as more

important the more identified they become with their rugby club and this supports the

notion that CB does matter to fans (Pawlowski and Budzinksi, 2013). Additionally, a

similar relationship can be observed in relation to the rugby league fans’. However, it

was a non-significant result and therefore further research will have to be conducted

to find out whether they too demonstrate a relationship.

Previous literature documents that European rugby union fans identify imbalanced

home and away matches as the most important aspect of competitive balance. This

relationship can be observed in section 4.3 (figure 3) however the relationship is not

statistically significant but provides a basis for further research. Instead, the study

can conclude that the strongest determinant of CB for more identified rugby union

fans is match uncertainty, followed narrowly by a clear outsider. Unfortunately, none

of the individual factors of CB provided a significant result in relation to the rugby

league sample set.

The most intriguing observation from section 4.4 albeit insignificant, is that rugby

league fans do not perceive relegation as very important the more identified they

become with their club. With changes as recent as 2015 to the structure of the First

Utility Super League and with literature largely suggesting structural changes

improve attendances (Kringstad and Gerrard, 2004; Gerrard, 2007), this study

33

suggests that with further research those decisions and may have been unnecessary

and disprove the literature.

Results for sections 4.5 and 4.6 provided no statistically significant results when the

regressions were performed for each discipline. Nalbantis, Pawlowski & Coastes

(2015) found that fans that viewed games as more suspenseful were more willing to

make a financial contribution. However, this study provides no statically significant

relationship between higher levels of CB, CI or team ID, and the rugby union or rugby

league fans’ WTP. The results from this study support Pawlowski and Budzinski

(2013) conclusion, that stipulates these WTP scenarios should be treated with

caution and perhaps the bias (aforementioned in section 3.3) should be taken into

account.

Moreover, the number of insignificant results observed within this study could have

occurred due to limitations in relation to this study’s methodology. This study does

also possess strengths and with both of these in mind, hopefully, forthcoming studies

can take them into account to complete effective future research, mirroring the

strengths and rectifying the weaknesses. With only a handful of other PCB studies

previously performed, the study had to be structured to best suit English rugby and

the study’s aim and objectives. Previous similar SP studies have all been in relation

to Football and specifically European football (Pawlowski and Budzinksi, 2013;

Nalbantis et al, 2015). This previous literature provided this study with a basic outline

to follow with regards to data collection. For example, the careful dissection and

transfer of the Pawlowski and Budzinski (2013) questionnaire and use of social

media platforms to collect the data much like Nalbantis et al (2015).

However, the greatest limitation this study faced - and a major reason perhaps for

such a large number of insignificant results – particularly for the rugby league sample

was the sample’s size and representativeness. The questionnaire that was used was

posted on a number of specific club fan forums (ShedWeb, Leicester Tigers Forum &

Scrum V) as well as broad fan forums (Total Rugby League Fans Forum & the Rugby

Forum) plus fan Facebook pages (Rugby Union World Wide Fan Zone), where it

wasn’t cordially received. Possibly for a number of reasons; for example, online

surveys that separate questions on to each page (like the survey used for this study)

34

is suggested to result in longer time for completion and lower response rate

(Vehovar, Manfreda and Batagelj, 2000; Tourangeau et al., 2004). Additionally, the

survey for this study used a 10 point Likert scale as previously mentioned, this

requires respondents to scroll through questions which increases completion time

and it is suggested to be more beneficial to use smaller scales (De Bruijne and

Wijnant, 2014). Finally, a common occurring theme with participant’s non-response

rate with online surveys is the high survey break off (closing the browser) (Wells et

al., 2013; Bosnjak et al., 2013). Moreover, the socio-demographic data of the sample

size (depicted in methodology) provides further evidence that the sample may not

have been a true representation of both rugby union and rugby league fans from the

UK; with the vast majority of the sample population being students and stating the

lowest monthly income bracket (£0-£500). With these limitations in mind it and with

only 41 rugby league fans in the sample, it could be argued that this study’s sample

was not completely representative of English rugby union fans and almost certainly

not representative of English rugby league fans.

On the other hand, this study’s greatest asset was its simplicity. The questionnaire

provided by Pawlowski and Budzinski (2013) has been very thought through and can

be simply related to any sport and any league. Moreover, providing the survey is

posted online, there are no expenditure costs to take into account and with no human

contact, the ethical consideration process can be quickly progressed. An

amalgamation of these aspects allows this study to be repeated in the future hassle-

free.

5.1 Recommendations With regards to recommendations for future research on this topic, it is important to

stress that plenty of time be allocated to collect a large set of data and produce a big

enough sample size, which is much more representative of the rugby union and

rugby league fans in the UK. Additionally, different aspects of this study such as the

fans’ WTP scenarios or the concept of PCB and PCI could be investigated in another

minor UK team sports such as cricket, which has received little research in regards to

CB. Furthermore, the concepts of perceptional CI and CB could be measured over a

longer period of time, much like many OCB studies.

35

6.0 Personal Reflection

This final section is arguably one of the most important of the entire Major

Independent Study. It will provide a comprehensive summary of my development

throughout the project and how it has helped me to become an independent learner.

This piece of work requires us research a topic of our choice and produce word

document of no more than 12,000 words. Initially, a substantial amount of

36

background reading was had prior and during the completion of this piece. This is a

crucial aspect of the entire project and I believe because of this it has massively

improved my reading ability. With over 130 academic resources used, a thorough

and precise ability to read and select important information was crucial. Moreover,

consistently and correctly writing academically through the entire piece of work was

challenging and on a scale that required much endurance however extensive

formative feedback along the way from both my MIS supervisor and lecturers from

other modules in my final year has allowed me to confidently write academically.

Another skills this major independent study has allowed me to improve was time

management. With an initial slow start to the project over uncertainties, it was key to

stay persistent. To ensure targets were met throughout the completion of this study,

strict schedules were arranged with my supervisor as well as frequent meetings

throughout the year (see appendices 4.0 – 4.5). This, alongside deadlines for other

modules has consistently forced me to maintain exemplary time management and

organizational skills. Additionally, I found using the data analysis software, SPSS one

the toughest parts of the whole study. With very little statistical experience it was a

slow progress. However arranging workshops with the university’s Skills for Learning

team and strict application, I soon figured out SPSS and analyzing all different

aspects of my data using different tools proved very enjoyable. Finally, I hope this

piece of work reflects my avid interest for sport economics and it has certainly

affirmed my aspirations of either completing a Master’s Degree in a similar field

and/or gaining valuable experience or a career with a major business or marketing

firm.

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Appendices

1.0 Participation Information Sheet

Project Title: A comparative study between Rugby union and Rugby League to establish fan’s perception of Competitive Balance and the impact it has on their willingness-to-pay.

Researcher: Russell White ([email protected]: Alex Bond ([email protected]

Invitation to participate

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The Researcher would really appreciate your participation in this study in-relation to fans’ perceptions of Competitive Balance (CB) and its subsequent impact on their willingness-to-pay (WTP). Please take the time to read this information sheet and decide whether or not you would like to be involved.

Purpose of the study.

This study will investigate the experiences, knowledge and perceptions of a group of participants who regularly spectate Rugby union and Rugby League fixtures with references to their perceptions of CB and the impact it has on their WTP. Currently, there is limited research on this topic surrounding European Rugby leagues. Therefore, this study will allow for the perceptions of CB and its impact on fans’ WTP to be fully investigated, acknowledging recommendations to be made about CB education and knowledge.

Do I Have to take part?

No, participation is entirely voluntary.

If I agree to be involved, what happens next?

The questionnaire will take approximately 10 minutes to complete. Once completed, the data will be stored online on a password secure computer. The participant will then be given a unique reference number which allows the researcher to withdraw their data if they do not wish to be part of the study following the completion of the questionnaire.

Can I change my mind and withdraw from the project?

Yes, you can withdraw from the study at any point without a reason, as it is completely

voluntary.

Will my taking part in the study be kept confidential?All information collected during this research project is treated with the strictest confidentiality, along with it being completely anonymous. Neither the establishment, nor any individual will be identifiable.

What will happen to the results of the research study?The results of the study will be stored on a password-protected computer by the researcher, and only the supervisor of this study will see them. The results of the study will be destroyed following the completion of the dissertation.

What do I do if I have a complaint about this research? If you have any complaints, you can contact the supervisor of this research study:Alex Bond([email protected])

Who has reviewed the study?

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The local research ethics officer, according to the Leeds Beckett University ethics policy.

Contact details for further informationRussell White ([email protected])

What next?

If you are happy to proceed please complete the consent form and begin the online questionnaire.

Thank you for reading this information and hopefully taking part in this project.

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2.0 Participation Consent Form

Have you received a copy of the information letter? YES NO

Have you had an opportunity to ask questions about the study? YES NO

Have your questions been answered satisfactorily? YES NO

I understand that I will be completing a questionnaire YES NO

I understand that participation in this study is entirely voluntary YES NO

I understand that I am free to refuse participation and have YES NO

the right to withdraw from participation at any time and for any reason

I understand that my participation will be as an anonymous YES NO

individual and my identity will be protected at all times

I agree to take part in this study YES NO

I am over 16 years of age YES NO

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3.0 Final Questionnaire – Online created with Google Forms

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Appendix 4.0 Carnegie Faculty MIS Progress Report Form

Please use this form within meetings with your Supervisor to keep a record of progress throughout your MIS. This will help you to complete the Personal Reflection section of your MIS and you are required to submit a minimum of 6 Progress Report Forms within your MIS Appendices.

Meeting Details

Date: 01/10/2016 Time:11.00am

Attendees: Russell White & Alex Bond

Issues brought by student:

Issues with regards to proposal – Review of Literature and Methodology what should be included.

Issues raised or comments by supervisorReview of literature not specific enough to the research title, aims and objectives.

Recommendations / Actions for next meeting:Divide the Review of literature into sections; D of D, CB, Measurements of CB, PCB and WTP.

Agreed date/time of next meeting: 16/11/16

Student Signature Supervisor Signature

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4.1 - Carnegie Faculty MIS Progress Report Form


Meeting Details

Date: 16/11/16 Time:11.00am

Attendees: Russell White & Alex Bond

Issues brought by student:This should be completed prior to the meeting and may include items such as progress to date; any particular problems; and any assistance that is required.

Questionnaire adaption and Ethical consideration help.

Issues raised or comments by supervisor

Questionnaire should be adapted from Pawlowski’s and Budzinksi’s (2013) study. Increased specificity in the ethics application. i.e. which forums were used and details regarding the sample set.

Recommendations / Actions for next meeting:

Improve the ethics application and relate





Meeting Details

Date: 17/12/16 Time:17.00pm

Attendees: All members of Alex Bond’s supervisees.


Questionnaire creation of Google Forms, ensuring each aspect of the application could be used and navigated easily.


Ensure that the questionnaire is readable and completed so that when ethical approval was gained it could be distributed.


Finish the completion of the questionnaire and ensure it is ready to pilot once ethical approval was met.





Meeting Details

Date: 01/02/16 Time:9.00am

Attendees: Russell White and Alex Bond


Review of literature needed bulking and improving from the proposal. Final sign off of questionnaire so that data collection can begin.


Not enough detail in reference to CB (short, medium and long-term). And nothing on Competitive intensity, Team Id and SSIS.


Include the aforementioned details in a readable structure. Begin to data collect.





Meeting Details

Date: 26/02/16 Time:18.00pm

Attendees: Alex Bond and all of his supervisees.


Methodology


Method must be written in 3rd person and past tense. Research design and all approaches to methodology must be included.


Write a draft in preparation for the next meeting or individually arranged meeting with Alex.





Meeting Details

Date: 17/03/16 Time:17.00pm

Attendees: Alex Bond and his supervisees.


Data analysis and the use of SPSS (regression, cross tabs and t-tests).


Ensure that all data is computed before analysis is started and don’t solely rely on descriptive data analysis.


Go away and analyse the data already gathered and get a feel for SPSS, using tutorials to help you if any problems are met.

Agreed date/time of next meeting: N/A


Dissertation complete copy 250416

Documents