issues and controversies in marketing project

Socialmediaandsports-HowPremierLeagueclubsdrivefanengagementonTwitterAgrade2018-19.pdf

Home >Business & Finance homework help >Marketing homework help >issues and controversies in marketing project

Student Number: 00000

Dissertation Module Code: MG3119/MG3123

Dissertation Supervisor x

I confirm that I understand a complete submission of coursework is by one electronic copy of my assignment via Blackboard Learn. I understand that assignments must be submitted by the deadline in order to achieve an uncapped grade. Separate guidelines apply to reassessed work. Please see the Coursework Submission Policy for details.

Any coursework or examined submission for assessment where plagiarism, collusion or any form of cheating is suspected will be dealt with according to the University processes which are detailed in Senate Regulation 6.

You can access information about plagiarism here.

The University regulations on plagiarism apply to published as well as unpublished work, collusion and the plagiarism of the work of other students.

Please ensure that you fully understand what constitutes plagiarism before you submit your work.

I confirm that I have read and understood the guidance on plagiarism. I also confirm that I have neither plagiarised in this coursework, nor allowed my own work to be plagiarised.

The submission of this coversheet is confirmation that you have read and understood the above statements.

A selection of dissertations may be put on Blackboard Learn to be read by other students. I hereby consent to my dissertation being published on the Department’s Taught Programme Office organisation on Blackboard Learn, for teaching and research purposes. YES

Social media and sports: How Premier League clubs drive fan engagement on Twitter

Name: x Student number: x Degree Course: x

College: College of Business, Arts and Social Sciences

Department: Brunel Business School Supervisor: x

Abstract

Purpose: This study aims to explore how and why sports fans engage with their Premier League teams on social media due to the lack of research in the area of social media engagement behaviours and the motivations associated. The framework employed to help achieve this was the Uses and Gratifications approach which consist of seven motivations (Information, Entertainment, Personal Identity, Integration and Social Interaction, Empowerment, Remuneration and Brand Love) and Consumers’ Online Brand-Related Activities framework that consist of three dimensions of online engagement behaviours that fans face (Consumption, Contribution and Creation).

Research Methods: The research methodology was created to gather information about how and why sports fans are engaging with their Premier League clubs. A quantitative approach was employed, through an online survey among football fans of Premier League clubs on Twitter. This was a seven-point Likert scale. Gathered data was assessed through SPSS with the help of Pearson’s correlation analysis to discover if the need Information, Entertainment, Personal Identity, Integration and Social Interaction, Empowerment, Remuneration and Brand Love had a relationship with Consumption, Contribution and Creation.

Findings: Through the analysis, findings showed that Integration and Social Interaction had the strongest relationship with all three dimension of engagement behaviours, Brand Love & Remuneration being the other two motivations with a strong relationship with the three dimensions of engagement behavioural. This study helped emerging research on social media engagemenr behaviours and motivations associated which provided sports marketers insight on how to increase their fan engagement through the motivations associated with engagement behaviours.

Acknowledgements

Firstly, I would like to thank x for her continuous support, time and guidance throughout the year, helping me get through this final year research project.

Secondly, I would like to thank all the participants in the survey who helped with my data collection that was required for this study.

Lastly, I would like to thank my family who showed their support throughout the project, but also my fellow peers who also helped me throughout this process.

TABLE OF CONTENT

ABSTRACT ________________________________________________________________________ 3 ACKNOWLEDGEMENTS ____________________________________________________________ 4 CHAPTER 1 – INTRODUCTION ______________________________________________________ 8

1.1. BACKGROUND ___________________________________________________ 8 1.2. PROBLEM DEFINITION ____________________________________________ 9 1.3. RESEARCH GAP ________________________________________________ 10 1.4. RESEARCH AIMS AND OBJECTIVES ________________________________ 10 CHAPTER 2 – LITERATURE REVIEW _______________________________________________ 11

2.1. INTRODUCTION _________________________________________________ 11 2.1. SOCIAL MEDIA - AN ENGAGEMENT TOOL ___________________________ 11 2.2. SOCIAL MEDIA ENGAGEMENT BEHAVIOURS: COBRA FRAMEWORK _____ 13 2.4. DRIVERS OF SOCIAL MEDIA ENGAGEMENT BEHAVIOURS: THE U&G THEORY ___________________________________________________________ 16 2.5. HYPOTHESIS ________________________________________________________________ 20 CHAPTER 3 – METHODOLOGY ____________________________________________________ 22 3.1. INTRODUCTION ________________________________________________ 22 3.2. RESEARCH PHILOSOPHY _________________________________________ 22 3.4. METHODOLOGICAL CHOICE ______________________________________ 23 3.9. PARTICIPANTS AND SAMPLING METHOD ___________________________ 25 3.10. PILOT STUDY __________________________________________________ 27 3.11. DATA ANALYSIS AND MEASURE __________________________________ 27 3.12. MEASUREMENT DEVELOPMENT __________________________________ 27 3.13. DATA ANALYSIS – INSTRUMENTS _________________________________ 28 3.15. ETHICAL CONSIDERATIONS _____________________________________ 29 CHAPTER 4 – RESULTS ___________________________________________________________ 30 4.1. INTRODUCTION _________________________________________________ 30 4.2. HYPOTHESIS (H1) _______________________________________________ 30 4.3. HYPOTHESIS (H2) _______________________________________________ 31 4.4. HYPOTHESIS (H3) _______________________________________________ 32 CHAPTER 5 – DISCUSSION AND CONCLUSION _____________________________________ 33 5.1. OVERVIEW _____________________________________________________ 33 5.2. LIMITATION AND FURTHER RESEARCH _____________________________ 35 REFERENCE LIST _________________________________________________________________ 37 APPENDICES _____________________________________________________________________ 50

List of figures

FIGURE 1 - TOP GLOBAL BRAND LOVE LIST __________________________________ 19 FIGURE 2 - RESEARCH FRAMEWORK _______________________________________ 20 FIGURE 3 - RESEARCH ONION ___________________________________________ 22 FIGURE 4 - TWITTER USERS _____________________________________________ 26 FIGURE 5 - GENDER ___________________________________________________ 26 FIGURE 6 - AGE ______________________________________________________ 26 FIGURE 7 - TIME SUPPORTING PREMIER LEAGUE TEAM _________________________ 26

List of tables TABLE 1 - DIMENSIONS USED IN THE STUDY AND THEIR SOURCES __________________ 28 TABLE 2 - CRONBACH'S ALPHA ___________________________________________ 29 TABLE 3 - H1: PEARSONS CORRELATION ANALYSIS ____________________________ 30 TABLE 4 - H2: PEARSON CORRELATION ANALYSIS _____________________________ 31 TABLE 5 - H3: PEARSON'S CORRELATION ANALYSIS ___________________________ 32

Chapter 1 – Introduction

1.1. Background In today’s society football has become one of the most popular sport in the UK

(World Atlas, 2018), it has been proposed by the sports marketing literature that

in sports, consumers develop a special bond with their favourite teams (Abosag

et al.,2012). Through the special bond, it evokes an emotional attachment

towards a sports club and their team identification; this has often become

associated with the term ‘engage’ in sports marketing literature (Yoshida et al.,

2014). Fans that become deeply engaged with their sports teams tend to

usually have a positive effect on a sports team as they develop non-

transactional behaviours. These behaviours can include, word-of-mouth

(positive or negative) such as conversations on social media; displays of sports

fandom; consumer-to-consumer interactions in fan communities for example

fan Tv; and reading information about the team which could be through

social/traditional media (Ahearne et al., 2005; deRuyter and Wetzels, 2000).

The fans of a sports team have become fundamental stakeholders because

they are the reason why the teams can still operate as a business and their

sense of loyalty helps build a club’s confidence and individual players

confidence (Bleacher Report, 2009). The active contribution from sports fan to

value co-creation (Popp et al., 2016), can be used to define loyalty, as they

support their clubs through the ups and downs while maintaining and

experiencing the relationship with a team they consider their own (Abosag et

al., 2012). These are behavioural patterns that are considered unique and are

known to be encountered by fans in spectator sports which can be considered a

vital manifestation of customer engagement behaviour (CEBs); which will be

explained in our literature review.

1.2. Problem definition Social media has shifted to an engagement tool for organisations and with sports

fan bases expanding as well as their level of support progressing it enables

sports organisations to benefit from social media as an engagement platform

(McCarthy et al., 2014; Williams and Chinn, 2010). The introduction of social

media has opened a new way for supporters to interact with their favourite sports

teams, athletes and even other fans (Loakimidis, 2010). A majority of sports fans

are very engaged with the sports they take interest in and for hardcore sports

fans it has become engraved in their culture and everyday lives (Popp et al.,

2016).

The popularity of social media has enabled sports organisations to adapt the way

they tell stories to their fans (Nest, 2018). Sports clubs have become highly

involved in social media, as it has opened a new communication channel with

the audience which can be measured (Cave and Miller, 2017). Although social

media can be a really beneficial marketing tool, it can lack that real depth of an

organisation truly understanding their true fan bases. It can also lead to a PR

disaster, with clubs not really having 100% control over the conversation around

the brand. This can generate a dilemma, as sports teams aspire to remain in

control of the topics surrounding their organisation while formulating an engaging

presence with their fan community (McCarthy et al., 2014). While the years go

on, a variety of sports teams have decided to integrate social media into their

marketing strategy to engage with their supporters via social media activity like

quizzes.

Previous sport management literature’s have research devoted to fan

engagement which has limited attention (Mahan, 2011; Stavros et al., 2014),

especially on social media (Wallace et al., 2011,) and from the perspectives of

the fans (Clavio and Kian, 2010; Stavros et al., 2014). The topic of investigating

issues on sports consumers’ engagement spans has been ongoing for many

years, but a majority of the studies have been offline and concentrate on

transactional behaviours (Yoshida et al., 2014). Even though there are studies

surrounding online engagement behaviours they neglect the issue of the full set

of behaviours and motivations associated with social media engagement, lacking

theoretical depth (Filo et al., 2015). To efficiently use social media, sports teams

need to understand the importance of their online presence and how they can

maintain it through factors such as: insight on their fans, motivations and

behaviours.

1.3. Research Gap The shortcomings of prior research have resulted upon us drawing on knowledge

about social media, sports and engagement to support analysis the drivers of

fans CEB while interacting with sports clubs on Twitter. The study explains that

consumer’s motivations are associated with a range of Twitter functionalities (e.g.

posts, comments, and likes) that may evolve to a more complete perception of

CEB on social media. To develop a valid judgment of consumer’s motivations,

this study is theoretically grounded in the Uses and Gratification theory (U&G), a

popular framework in relation to literature around the topic sport and social media

(Filo et al., 2015). To understand the imminent value of motivations,

measurements of a full set of online CEB (e.g. retweets and likes) through several

degrees of consumer activities will occur (Tsai and Men, 2013a). This will be

based on Consumer’s Online Brand-Related Activities (COBRA) frame-work

(Muntinga et al., 2011b), where 3 factors were taken into consideration:

Consumption, Contribution and Creation (Schivinski et al., 2016).

1.4. Research aims and objectives The aim of this study is to gather further information about what antagonises

fans to engage with their favourite sports club via social media and the

motivation behind their engagement.

Research objectives:

• To identify how and why fans engage with their Premier League clubs on

teams

• To identify the motivations that drive fan engagement through Twitter in

relation to Premier League Clubs

• To identify the impact CORBA and U&G theory have in relation to Premier

League clubs when driving fan engagement

Chapter 2 – Literature Review

2.1. Introduction This chapter includes a comprehensive review of a variety of theories and

research in the field of social media engagement, fan engagement behaviour and

the motivations behind their engagement. It will be assessed through the COBRA

framework and U&G theory. Our hypotheses will be obtained from the literature

presented and accommodated to Premier League clubs and Twitter.

2.1. Social Media - An engagement tool Many academics have conducted extensive research on the topic of social media

engagement. With the growth of social media, at an unprecedented rate, it has

become a powerful marketing tool proving to be a crucial aspect of many

businesses marketing plans. Social media platforms have empowered brands to

connect and collaborate with consumers (Mount and Martinez, 2014); through

social media, brands can utilise their extensive brand-related activities to engage

with consumers (Hollebeek and Brodie, 2016b). Engagement has been central

to the development of social media communities. In order for engagement to be

measured, a form of interaction should occur. This can take place in several

ways: conversations with brands/peers via commenting or support through an

action such as liking or retweeting (Tsai and Men, 2013a; Drula, 2012; Leander,

2011). These types of engagement have been categorised as:

• Acknowledgement (Like or reaction)

• Association (Reply, comment, mention or follow)

• Amplification (Retweet or share)

• Action (Click to the website) (Davis, 2018).

The development of successful online communities has become inextricably

linked to social media. Sports fans are a prime example of a successful online

community as they share a strong common interest (Popp et al., 2016). This is

particularly demonstrated with their existing fanbase and level of fandom

(Williams and Chinn, 2010). Sports fans are notoriously known for being versatile.

This has been noted by the sports marketing field who discovered that they exist

in various socio-economic classes and educational levels. The interpersonal

dimensions regarding the relationship between fans and the object of fandom

can be analysed through the validity of psychoanalytic approaches to pleasure,

desires and self-identity in fandom (Sandvoss, 2005). A fans experiences

differentiate their fandom levels (Hunt et al., 1999), this can range from attending

games to developing successes and losses of their club, this helps distinguishes

them as sports fans or spectator through their level of passion and emotional

significance (Dionisio et al., 2008). Sports fans tend to invest time, energy and

money into their favourite team; thus, eliciting a variety of behaviours from fans.

According to Vallerand et al. (2008), these behaviours include cheering the team

and participating in heated discussions; however, not all fans behaviour towards

a sports team is positive.

Social media has become a medium for fans to extend their fandom and engage

with their favourite sports team (Witkemper et al., 2012). Additionally, it has

allowed fans to fortify their relationship with their favourite sports organisation

(Witkemper et al., 2012). Through social media fans have become co-owners

and co-creators; thus, playing a pivotal role in building the brand’s reputation and

image (Williams and Chinn, 2010). However, the backlash social media presents

sports club with is problematic as it may be a struggle to maintain their strong

brand image. This therefore creates a 50-50 dilemma with the club as they aspire

to build an engaging fan community while possessing full control (McCarthy et

al., 2014). An example of this is Arsenal fan TV who had to undergo a process of

rebranding themselves due to the negative impact they had on Arsenal football

club (Vaghela, 2018). Yet, previous researchers have highlighted that the

creation of social media has swayed the power towards the fans, giving them

freedom to express themselves. Fans are utilising this platform to release

numerous amounts of emotions including emotional release (Wang, 2013a,

2015b). Nevertheless, the emotional release on social media from fans may not

be what the organisation desire to discover. However, as key stakeholders it is

necessary to understand their perception about the organisation (Blumrodt et al.,

2017).

Despite the research being focused on a broad topic like social media

engagement, many have failed to focus on frameworks that could be used to

validate the social media engagement occurring. However, in cases where this

has been explored, frameworks have been applied to a different context. Hence

why there is a need to explore the use of COBRA framework to help validate why

fans are engaging with Premier League teams through social media.

2.2. Social media engagement behaviours: COBRA Framework Engagement has been a topic of academic interest for years; some authors have

defined engagement as a state characterized by energy, involvement, and

efficacy (Kim, Kim, and Wachter, 2013). Alternatively, others have focused on

defining engagement as psychological state of mind that follows an interaction in

relation to the customers' activities or patterns (Thakur, 2018). VanDoorn et al.

(2010) explored the notion that customer engagement behaviour (CEB) extends

beyond the transactions and defined this as a customer’s behavioural

manifestation which focuses towards a brand or firm, beyond purchase, that

results from motivational drivers (p.254). CEB could occur at three levels:

exceptional customer experience, emotional connection and shared identity with

the company (Grewal et al., 2017). This can reflect a customer’s motivation in

terms of their interactive experiences with the engagement object such as events,

media, product offerings or the direct interaction with a brand (Hollebeek, 2011c).

CEB has been associated with numerous online brand-related activities.

According to Palazon et al. (2015), by consumers engaging (following/like) with

a brand’s page, it expresses their willingness to expand their relationship with the

brand, however, social media engagement can occur on various levels starting

from level 1 – attention, to level 7 – advocacy (Schmidt, 2017). These types of

activities have been described as COBRA (‘Consumers’ Online Brand-Related

Activities’) – a behavioural construct that offers a unifying framework in relation

to a set of brand-related online activities that correlate to the consumer interaction

with content provided by a brand on social media (Muntinga et al., 2011b). The

definition expose that of CEB are a result of motivational influences.

Past research has explored fans typology and explored their reasons for liking

brands (Wallace et al., 2014) and motivation for driving brand posts popularity

(measured by the number of likes and comments) between fans (De Vries et al.,

2012). Many authors who studied COBRA, categorised it into three:

Consumption, Contribution, and Creation (Schiviniski et al., 2016), all dimensions

correspond to the types of engagement consumers encountered with brands on

social media that can range from low to high activity (Malthouse et al., 2013).

Consumption refers to activities related to the minimal level of engagement

through social media which could be associated with reading reviews and

comments, observing brand-related posts (videos or photos) (Heinonen, 2011).

Many people on social media tend to attach their activities towards consumption

resulting in it being the most frequent type of activity (Muntinga et al., 2011b).

Contribution, which is considered the middle level of engagement, focuses on

interactors with others on social media or brands, like sharing/commenting on

content, liking content and acting on brand-related content that has been created

by the brand or other sources (Muntinga et al., 2011b; Schivinski et al., 2016).

We noticed on Twitter this occurs multiple times with 500 million tweets being

sent per day (Omnicore,2018) with a majority of them being brand-related.

Creation, which is considered the ultimate level of engagement which is

associated with consumers producing and publishing brand-related content that

a variety of consumers may consume and contribute to (Dolan et al., 2016).

Examples of these activities are web-blogs, product reviews, photos and videos

or written articles on brands (Muntinga et al., 2011b).

Twitter features such as tweeting and retweeting all represent social media

engagement behaviours that represent the COBRA frameworks (Oh et., 2017,

Gensler et al., 2013). Schiviniski et al. (2016) was able to validate the COBRA

framework through ‘Consumer’s Engagement with Brand-Related Social Media

Content’ scale via qualitative and quantitative methods which exhibited the

hierarchical correlation between the three dimensions of brand-related activities.

However, previous research conducted present similar gaps especially within

sports marketing field as most of their research has highlighted how social media

can be exploited for communication efforts in regards to sport organisation and

professional athletes (Meng et al., 2015; Wallace et al., 2011; Williams and

Chinn, 2010), and even studies dedicated to the fan perspective used different

social media platforms and league/sport teams.

Vale and Fernandes (2018) highlighted their study needed further research for

the their findings to be generalised to other SNS, cultures and leagues/sports

teams and have relied on a limited set of CEB like comments posted (Stavros et

al., 2014) or the general use of SNS like activities based on consumption use in

the context of Facebook (Clavio and Walsh, 2013; Gibbs et al., 2014). Hence

why, there is a need to explore the motivations of sports fans when engaging with

Twitter (Stavros et al., 2014).

2.3. Twitter as engagement tool Twitter has taken over the 20th century being used as online news and social

networking site where people communicate with each other (Lifewire, 2018).

Twitter is considered a ‘microblogging’ system which allows consumers to send

and receive short posts known as tweets (Economic and social research council,

2019). The platform is being utilised by consumers to follow their favourite sports

organisations and celebrities. The interactivity via users on social media

platforms like Twitter has become essential for relationship building between

organisations and the public (Saffer et al., 2013). The success of Twitter has

been tremendous with a total of 1.3 billion accounts (Brandwatch, 2017) with the

simple but effective functions being used to increasing engagement. Sports

organisations typically implement Twitter to communicate with a vast amount of

followers in a one-to-many form functions like: tweets and poll to provide live-

tweeting during games as a way to keep fans engaged (Raby, 2018). An example

of this is during the World Cup we saw hashtags being utilised frequently, as

during the World Cup there were 115 billion impressions (views on Twitter) of

tweets throughout the World Cup with all reaction to red cards, goals, subs etc

being related to the hashtag #WorldCup (Filadelfo and Bavishi, 2018).

Even though Twitter is perceived as a platform for information, it can be used for

business as a way to interact with consumers that can help stimulate and track

electronic word of mouth (EWOM) (Lowe and Laffey, 2011). Studies conducted

about social Media all display different results with each platform serving a

different purpose, with Vale and Fernandes (2018) research exploring how fans

engage with their football teams in different league via Facebook, but not Twitter,

yet both platforms displaying different features meaning customers utilise them

for different reason. Hence why there is a need to focus more on Twitter due to

the growth of the platform over the years and how the motivations associated

with social media engagement behaviours have had an affect.

2.4. Drivers of social media engagement behaviours: the U&G theory Motivations has been essential incentives that drive people’s selection of media

(Rubin,1983). Social media users feed off a unique interactive nature endured

through social media sites. This nature of social media benefits both brands and

consumers as it links them together, however, while simultaneously linking the

two networks, these social media platforms are also expected to fulfil a wider

range of needs. A popular approach adopted in literature when it comes to

exploring motivation related with various media use is the U&G theory (Katz et

al., 1973). U&G theory focuses on how individual consumers seek out particular

media types and content in order to fulfil their desires and needs, leading to

ultimate gratification (Lariscy et al., 2011).

Previous U&G researchers tend to discuss the motivation as gratification sought

and discussed why people consume certain media and the level of satisfaction

obtained from it (Ko et al., 2005). U&G shows it is significant when exploring how

individuals are active users of various communication channels (Korhan and

Ersoy, 2015) and has been adopted by various researchers to understand the

level of satisfaction gained from certain media (Malik et al., 2016). Studies

conducted by others (Smock et al., 2011; Sundar and Limperos, 2013) claim that

specific needs can be exploited by features experienced while exploring a type

of media. Thus, U&G is the perfect approach as it focuses on why people use a

particular media rather than on content helping examine three things:

1. Why people use media?

2. How people use media?

3. What they do with the media? (Shin, 2011; Dunne et al., 2010).

With the increase of social media over the years, we witnessed a number of

researchers apply the U&G theory in the context of social media for further

understanding. Chen (2011) researched identified a correlation between U&G

and social media, displaying how active Twitter users gratifies a need to connect

with others, helping support the claims of how the U&G theory was suitable for

social media usage.

U&G presumes that people are active, instead of passive, in the media use, and

social media requires the active participation of users and high-level of

interactivity (Ko et al., 2005), this could also be furthered to gather information

about CEB within social media. It has become an essential approach to

developing an understanding of what motivates consumers use of media

(Muntinga et al., 2011b, p. 17). Several motivations for consumer media use have

been identified by numerous U&G researchers with Mcquail (1983) labelling the

motivation factors in the following categories:

§ Information: This U&G theme relates to utilising social media to seek out information or to self-educate. For example, football fans seeking their

latest team news or using social media to educate themselves about a

particular player. Consumers desire to consume information directly from

brands which evokes their motivation factor leading them to social media

which updates about a particular brand or learn from other consumer’s

knowledge (Gummerus et al., 2012; Muntinga, 2013a; Zaglia, 2013;

Dholakia et al., 2004; Lin and Lu, 2011; Park et al., 2009). This could be

a factor that drives Consumption and Contribution (Guosong, 2009; Park

et al., 2009). § Entertainment: This links to employing social media as a channel for pure

entertainment and enjoyment (Whiting and Williams, 2013). It can be used

to explore brand-related activities (Baldus et al., 2015; Muntinga, 2013a)

which could be a driver for engagement. With social media platform

holding an entertainment value for consumers it could be a major factor

for why they’ve adopted (Dholakia et al., 2004; Lin and Lu, 2011; Park et

al., 2009). Research conducted by Muntinga et al., (2011b) discovered

that entertainment is a fundamental motivation towards Consumption,

Contribution and Creation. § Personal Identity: This relates to a consumers personal identity being

formed through forms of expression like their ideas, career interests etc

(Miller, 2018). It can also be expressed by presenting your self-

presentation by providing an image of one’s personality and through

receiving peer recognition (Schau and Gilly, 2003). Studies conducted

previously show how personal identity can be related to Contribution and

Creation (Guosong, 2009; Muntinga, 2013a; Tsai and Men, 2017b).

§ Integration and Social Interaction: This corresponds to how consumers are managing social media to communicate and interact with their

peers/others (Whiting and Williams, 2013). It helps with bonding with

people who share a common passion and meeting like-minded people

(Baldus et al., 2015). Researchers have found it to be related to

Consumption, Contribution and Creation (Muntinga et al., 2011b; Park et

al., 2009).

Further literature on social media, shows us the motivations above often occur

beside the following:

§ Empowerment: This correlates to how consumers/brands are being influenced, and executing the role of an opinion maker (Muntinga, 2013a;

Sundar and Limperos, 2013). An example of this would be in today’s age

influencer marketing which is a process of identifying, researching,

engaging and supporting people can create high-impact conversations

with consumers surrounding a brands product/service (Traackr, 2018).

The power of social media has increased the power consumers have as it

has become a fundamental channel for consumers to voice their opinions,

as well as demand improvements from brands (Johansson, 2018;

McCarthy et al., 2014). Empowerment was a factor that was perceived as

a driver for Creation within brand social meda pages (Tsai and Men,

2017b).

§ Remuneration: Many consumers use social media to socialise, however some may use it to reap a reward (Dolan et al., 2016) by consumers

participating in competition it could lead to them being rewarding with

prizes that could range from tangible products to intangible products

(Mangold and Faulds, 2009). An example of this is Manchester United

giving fans a chance to win a players top that is signed (Manchester

United, 2019). Muntinga et al. (2011b) research found out that a motivation

for Consumption was Remuneration and activities that are intended to

promote and offerings could be related.

§ Brand Love: This relates to how we feel towards a brand and the development of self-identification through our favourite brands (Blended

Collective, 2017). Brand love shows us the level of emotional attachment

a consumer has towards a brand (Carroll and Ahuvia ,2006, p.81). Brands

like Facebook, Apple and Amazon are receiving a tremendous amount of

brand love which is represented in figure 1 (Frary, 2016). Bergkvist and

Bech-Larsen (2010) literature was able to connect brand love with online

active engagement.

Figure 1 Top global brand love list (Frary, 2016)

U&G theory has been adopted in many journals based on the topics sports and

social media (Filo et al., 2015). Spinda and Puckette (2018) explored fans

motives through the use of snapchat to follow their sports teams and identified

fans using the application to discover information about their team off the field.

Clavio and Walsh (2013) learned consumers have a need for interaction and

information through the use of Twitter and Facebook. This shows a correlation

between the applications and U&G motivations as several are utilising social

media to gather information, however, Twitter and Facebook shift more towards

the information-seeking motivations (Spinda and Puckette, 2018).

Previous research has shown a continuous pattern which is the authors have

focused on specific motivations and how specific channels were used to arouse

these motivations. However, they have failed to take into consideration the full

set of behavioural stages a consumer could experience that is linked to

engagement via social media and understand that different fans experience

different sets of behaviours depending on the league/country. Also many studies

conducted have not taken into consideration the full set of behavioural stages a

consumer could experience that is linked to engagement via Twitter and failed to

understand that different fans experience different sets of behaviours depending

on the league/country hence why there is a need to explore the full set of

behavioural stages a consumer could experience when engaging with Twitter. 2.5. Hypothesis According to literature review, we present the following research framework

(Figure 2)

Figure 2 Research framework (Vale and Fernandes, 2018)

Our study will be focused on the power of engagement behaviours, called

Consumption, Contribution, Creation activities (Muntinga et al., 2011b), and will

taking into consideration that fans display various fandom levels (Hunt et al.,

1999), and will display a variety of gradual levels of CEB towards the club on

social media. Though we notice that sport fandom is a multisensory phenomenon

which evokes several responses, sometimes a negative response like fury or

frustration (Grove et al., 2012; Hunt et al., 1999; Wakefield and Wann, 2006),

however our study will not distinguish the valence of social media engagement

behaviours (Dolan et al,. 2016; Hollebeek and Chen, 2014a; Popp et al., 2016).

Given the nature of our research, attention will be given to the following

hypotheses:

Hypothesis (H1): Does the need for (a) Information, (b) Entertainment, (c) Personal Identity, (d) Integration and Social Interaction, (e) Empowerment, (f)

Remuneration and (g) Brand Love influences engagement with a Premier

League football club on Twitter, namely Consuming activities?

Hypothesis (H2): Does the need for (a) Information, (b) Entertainment, (c) Personal Identity, (d) Integration and Social Interaction, (e) Empowerment, (f)

Remuneration and (g) Brand Love influences engagement with a Premier

League football club on Twitter, namely Contributing activities?

Hypothesis (H3): Does the need for (a) Information, (b) Entertainment, (c) Personal Identity, (d) Integration and Social Interaction, (e) Empowerment, (f)

Remuneration and (g) Brand Love influences engagement with a Premier

League football club on Twitter, namely Creating activities?

Chapter 3 – Methodology

3.1. Introduction This chapter uses the research onion to distinguish the scope of research and

strategies that this study examines by using the layers of the model to analyse

this studies research philosophy (Lewis et al., 2016).

3.2. Research Philosophy Research philosophy is considered the external layer of the research onion &

investigates the implications a study may face efficiently (Lewis et al., 2016).

Figure 1.2 reveals that there are four main research philosophies; Positivism,

Realism, Interpretivism & Pragmatism. The research philosophies are all

mutually exclusive in their views & contain important assumptions about in the

way the world is viewed & vary based on the objectives intended for the

research & how to achieve them efficiently (Lewis et al., 2016).

The philosophical approach appropriate for this study is positivism as an existing

theory has been used to develop the hypotheses & the product of research can

be a law-like generalisation (Lewis et al., 2016).

Figure 3 Research Onion (Lewis et al., 2016)

3.3. Research Approach The following layer of the research onion portrays three main approaches:

deductive, inductive, and abductive. The deductive approach requires

development of a theory which is subjected to a rigorous test and an approach

known for testing the credibility of theories. It is naturally adopted in natural

sciences where laws present the basis of explanation (Lewis et al., 2016). Yet,

inductive approach examines building theories through primarily concentrating

on data collection (Bell and Byrman, 2015). Abductive is an approach to critic

the weaknesses associated with both approaches, despite being criticized for

the lack of clarity in relation of selection for the theory being tested via

formulating hypotheses (Research Methodology, 2019). This research uses a

deductive approach due to our hypotheses constructed around an existing

theory and verified through a designed research strategy.

3.4. Methodological Choice Methodological choice gives researchers the opportunity to use quantitative or

qualitative data.

Quantitative research tends to concentrate on numeric data which is usually

gathered from data collection techniques such as surveys or data analysis

procedures like graphical or statistical techniques which produce or utilise

numerical data (Lewis et al., 2016). This research is associated with deductive

approach and positivism due to similar features in theory testing. Researchers

would ideally take the quantitative approach when aiming to identify a theory that

correlates to the topic they are examining helping them develop hypotheses

related to the topic being studied (Barczak, 2015). For this study a mono-method

quantitative approach was taken with a single data collection being obtained

through an online questionnaire to examine the influence U&G motivations had

on COBRA.

Yet, an opposite research method is qualitative which is known for being an

inductive approach used to shape a theory (Barczak, 2015). It has been utilised

to derive meaning from a collection of non-numeric data such as case studies,

interviews and grounded theory (Bell and Byrman, 2015). Through qualitative

research, a richer theoretical perspective can be accessed through non-

standardised questions in more interactive research (Lewis et al., 2016).

3.5. Research Strategy

The research strategy investigates the connection between the chosen

philosophy and methodological choice. This empowers us to emphasise the

tactics applied when answering the research question (Lewis et al., 2016). As my

methodological choice for this project was quantitative; two strategies that could

have been adopted are experiment or survey. However, due to exploring

the particular relationship between variables a survey was more effective as

more control was given (Lewis et al., 2016). The questionnaire was utilised as a

tool to measure the influence U&G motivations have on COBRA. Thus, the

survey enabled me to generate findings from a sufficient population sample

(Lewis et al., 2016).

3.6. Time Horizon The time scale of the research is considered the next layer of the research

onion with two types of time horizons: Cross-sectional and Longitudinal. Due to

the academic course being necessarily time constrained the cross-sectional time

horizon was selected as they are quick and easy to conduct while helping with

descriptive analysis and generating hypotheses (Health Knowledge, 2017).

3.7. Research Design The research design helps ensure coherence between the research objectives,

data sources, data analysis methods and ethical issues.

The main three types of research designs are explanatory, exploratory and

descriptive. Explanatory research correlates to the effective explanation of a

phenomenon via inspecting causal relationships (Lewis et al., 2016) whereas

exploratory research contains open questions, leading to key insight being

gained. However, without presenting a final solution (Bell and Byrman, 2015).

Alternatively, descriptive research describe characteristics of the

population/phenomenon which is the focus in this study. This method is best

suited towards quantitative research as it gathers quantifiable information which

can be used for the statistical analysis of a population sample hence why the

research design had a descriptive purpose (Bhat, 2019a).

3.8. Data collection With the aid of Google forms, an online self-administered survey was designed

for data collection. Surveys are beneficial as they enable researchers to obtain

quantitative data that can be efficiently manipulated quantitatively using

descriptive and inferential statistics, thus, helping measure the relationship

between variables (Lewis et al., 2016). Through an online survey, this made

distribution easier as it extended the reach participants.

The questionnaire consisted of eight-pages with 11 sections. The demographic

questions were the first set of questions which examined demographic factors as

well as confirm whether they had an interest in Premier League football and were

users of Twitter. The remaining sections contained questions evaluating the

concepts in this project to help confirm the hypotheses – seven motivations

(Information, Entertainment, Personal identity, Integration and Social interaction,

Empowerment, Remuneration and Brand love) and three dimensions COBRA

(Consuming, Contributing and Creating) and were adapted to match the Twitter

functionalities. The data was obtained from January 2019 and February 2019.

3.9. Participants and sampling method Our research questionnaire was based on a variety of characteristics. For

participants to qualify for our study, they must have supported their Premier

League team for longer than two years. 91% of respondents met this

requirement. Participants also needed to use Twitter, otherwise they also would

not be considered, 100% of our respondents used Twitter (Figure 4). The age

was not a significant factor however, was taken into consideration with 73% of

respondents being within the age range of 18-24. A question about gender was

required, however not explored in detail with 72% of respondents being male,

26% of respondents were female and 2% preferred not to say (Figure 5).

Figure 4 - Twitter Users

Figure 5 – Gender

Figure 6 – Age

Figure 7 - Time supporting Premier League team

The questionnaire was filled by 104 respondents (Appendix B), however, after an

initial screening 13 respondents were excluded due to failure to meet the

necessary requirements for the ideal respondent. Due to the age of some

respondents, we could not consider their response due to legal reasons this

represented 3 of respondents (Figure 6). The remaining 100 respondents were

required to support their Premier League team for longer than 2 years, however,

10 of the respondents did not and due to the creditability of their level of fandom

their answers were not considered (Figure 7).

Due to the restrictions in regard to time, a sampling method was applied.

Sampling can be categorised: probability and non-probability. Probability is a

method which is focused on the utilisation of random selection of participants,

non-probability is the total opposite as the selection of samples are based on

criteria to correlate to the research question (Bhat, 2019c; Bhat 2019b). For this

project the appropriate sampling approach is non-probability, using the purposive

sampling as it is a method which is not based on random basis and was adopted

as it is a time-effective method and the industry being studied (Bell and Byrman,

2015).

3.10. Pilot study Pilot studies are small-scale preliminary studies which investigate the sufficiency

of the crucial components within the study are feasible. Also, it permits the

research to make a significant revision of the methodology, if required (Kezar,

2000; Cadete, 2017). However, pilot study completion doesn’t provide assurance

that the main questionnaire will be successful. Due to the scales being previously

tested (table 1), a pilot study was not required/utilised.

3.11. Data analysis and measure

3.12. Measurement development A questionnaire was used to measure the dimensions to support our hypotheses.

Our dimensions for all questions (excluding demographic variables) were

assessed on a seven-point Likert scale ranging from “strongly disagree” to

“strongly agree”. Our questions were obtained from Vales and Fernandes (2018)

study, however wording modifications were made to tailor scales to fit Twitter’s

features. The scale items sources can be seen in table 1.

Table 1 - Dimensions used in the study and their sources (Vale and Fernandes, 2018)

3.13. Data analysis – Instruments SPSS was employed to analyse the data collected as it explores the relationship

and trends between variables (Barrett et al., 2011). For H1, H2, and H3, a

Pearson’s correlation analysis was employed to measure the level of significance

and strength among the variables displayed in the hypotheses (Barrett et al.,

2011). The r value helped direct the path of these linear relationships (Barrett et

al., 2011).

3.14. Validity and Reliability Validity needed to be demonstrated, therefore factor analysis needed to be

applied before conducted statistical examination. However, confirmatory factor

analysis was employed by previous authors to test the measurement models

(Statistics Solutions,2013). Table 1 shows where the items were obtained from

and where factor analysis had been conducted giving an alternative empirical

support.

To measure the reliability for each dimension the Cronbach’s alpha was applied

and a summary of the results are presented in table 2 obtained from Vale and

Fernandes (2018). To confirm acceptance the internal consistency (reliability),

the Cronbach’s alpha valued had to be <0.7(Barrett et al., 2011). All dimensions

were deemed reliable as they were measured at <0.7. Our SPSS output for

Cronbach’s alpha can be found in Appendix E.

Table 2 - Cronbach's alpha (Vales and Fernandes, 2018)

3.15. Ethical considerations This study’s process of data collection and research activities was compliant

with the requirements of Brunel University’s Code of Ethics, the ethical approval

for this study was granted by the Brunel Ethics Research Committee in January

2019 (Appendix A).

Chapter 4 – Results

4.1. Introduction The following chapter will establish the results of the research findings through

Pearson’s correlation analysis, helping confirm the significant relationship stated

in the hypothesis.

4.2. Hypothesis (H1): Does the need for (a) Information, (b) Entertainment, (c) Personal Identity, (d) Integration and Social Interaction, (e) Empowerment, (f) Remuneration and (g) Brand Love influences engagement with a Premier League football club on Twitter, namely Consuming activities? Table 3 represents results that support the hypothesized relationship among the

motivational variables declared in H1 and engagement behaviour. The seven

motivations propose a significant relationship with Consuming as their p-values

were <0.01, which is lower than test’s threshold of 0.05. Pearson’s r value

supported the relationship between variables as they are positive and strong with

the r= ranging from .370 - .726; illustrating the significant relationship between

Consuming and Integration and Social Interaction. H1 is supported as all seven

motivation significantly influenced fans consuming activities with a Premier

League club on Twitter.

Table 3 – Pearson’s Correlation Analysis

Dimensions Consuming Information P=.000

R=.585** Entertainment P=.000

R=.565** Personal Identity P=.000

R=.370** Integration and Social Interaction

P=.000 R=.726**

Empowerment P=.000 R=.514**

Remuneration P=.000 R=.593**

Brand Love P=.000 R=.667**

** Correlation is significant at the 0.01 level (2-tailed)

4.3. Hypothesis (H2): Does the need for (a) Information, (b) Entertainment, (c) Personal Identity, (d) Integration and Social Interaction, (e) Empowerment, (f) Remuneration and (g) Brand Love influences engagement with a Premier League football club on Twitter, namely Contributing activities? Table 4 represents all seven motivations that are correlated with contributing

engagement activities. The p-value= for all dimensions were <0.01 validating

the significant relationship among the variables. Pearson’s r value showed a

positive and strong correlation. The r= ranged from .378 to .679 with a

significant relationship amongst Contributing and Integration and Social

Interaction (r=.679). H2 was supported since all seven motivations influenced

fans contributing activities with a Premier League club on Twitter.

Table 4 - Pearson Correlation Analysis

Dimensions Contributing Information P=.000

R=.512** Entertainment P=.000

R=.546** Personal Identity P=.000

R=.378** Integration and Social Interaction

P=.000 R=.679**

Empowerment P=.000 R=.536**

Remuneration P=.000 R=.562**

Brand Love P=.000 R=.621**

** Correlation is significant at the 0.01 level (2-tailed)

4.4. Hypothesis (H3): Does the need for (a) Information, (b) Entertainment, (c) Personal Identity, (d) Integration and Social Interaction, (e) Empowerment, (f) Remuneration and (g) Brand Love influences engagement with a Premier League football club on Twitter, namely Creating activities? The results presented in table 5 support H3 as it shows all the seven motivations

that have a significant relationship with creating activities. For all dimensions

the p-value was <0.01 helping validate the significant relationship among the

variables. The Pearson’s r value identified a strong and positive correlation with

the r=ranging from .410 to .647. The most significant relationship was Creating

and Integration and Social Interaction (.647). Table 5 supported H3 as all seven

motivation influenced fans creating activities with Premier League clubs on

Twitter.

Table 5 - Pearson's Correlation Analysis

Dimensions Creating Information P=.000

R=.410** Entertainment P=.000

R=.534** Personal Identity P=.000

R=.457** Integration and Social Interaction

P=.000 R=.647**

Empowerment P=.000 R=.598**

Remuneration P=.000 R=.616**

Brand Love P=.000 R=.558**

** Correlation is significant at the 0.01 level (2-tailed)

Chapter 5 – Discussion and Conclusion

5.1. Overview Previous studies focused on the fields of sports, social media and engagement

surrounding the issues of online engagement behaviours have failed to recognise

the full set of motivation and behaviours associated with social media

engagement therefore lacking the theoretical depth required (Filo et al., 2015).

This study helps distinguishing the drivers of fan engagement with Premier

League clubs on Twitter through a sports fan perspective. It identified

the consumer online brand-related activities model (COBRA) (Schiviniski et al.,

2016), and Uses and gratification theory (U&G) (Mcquail, 1983) as the most

appropriate to assess the motivation behind fan engagement. The U&G

motivations for social media use had been adapted to the sports context. The

framework used in the study helps extend research conducted previously through

merging drivers and engagement behaviours used on social media by focusing

on extending the existing knowledge on social media engagement behaviours

and motivations for social media use. Overall, this project helps to understand

how and why sports fans are engaging with Premier League clubs on social

media while contributing to the existing body of knowledge; Sports marketing,

studies on social media and fan engagement.

Within the studies data collection, an online survey was implemented through

Twitter. This tool estimated the relationship between COBRA dimensions and

U&G motivations. All participants were asked to assess what drove their

engagement with Premier League clubs on Twitter through several questions

related to the various dimensions and motivations.

Findings from the results, display that is it evident that the relationship between

the seven motivation and CEB are significant and positive in the context of

Premier League clubs and Twitter. This supports Chen (2011) and Ko et al.

(2015) views as each motivation played a significant role towards CEB, many

participants results displayed how Twitter users utilise the platform to connect

with others showing an active participation of user and high-level of interactivity

displaying each form of CEB (Malthouse et al., 2013). For example, our

researcher uses Twitter to connect with their favourite football club and interacts

with tweets to demonstrate their brand love whilst displaying their level of fandom

(Williams and Chinn, 2010). Social Media’s dynamic changes have been

explored through the results displaying how sports teams extend their brand-

related activities. This revealed how consumers engage differently through the

findings of what motivates consumers use of media (Hollebeek and Brodie,

2016b; Muntinga et al., 2011b, p.17). Even though all seven motivations

influenced the CEB dimensions, some motivations were stronger than others with

evidence displaying that the main motivation drivers were Integration and Social

Interaction, Brand Love and Remuneration across the CEB dimensions. As

expected, participants answers showed why Integration and Social Interaction

emerged as the main driver across the CEB dimensions. Most sports fans thrive

of interacting with peers or like-minded fans so when their sports team tweets or

releases a live poll concerning their team it motivates them to interact (Baldus et

al., 2015), as many fans utilise their Twitter pages to engage with their teams

through tweets during a football match or participating in a vote for man of the

match, which represent social engagement behaviours as portrayed by COBRA

frameworks (Oh et., 2017, Gensler et al., 2013). Therefore, this has allowed this

study to tackle the opportunity of differentiating the motivations behind fans CEB

while displaying how it can vary from social media platforms.

Displaying fandom was discussed by previous research and as Brand love was

considered a one of the main drivers for the CEB levels it showed how the various

levels of engagement consumers experience were through their brand love/bond

with their sports club (Albert et al., 2009). Many fans use Twitter to demonstrate

their brand love through displaying their level of emotional attachment towards a

brand (Carroll and Ahuvia ,2006, p.81) through different engagement behaviours;

for example liking a tweet, tweeting a picture of the sports club etc. As social

media has been the thin line for fans to extend their fandom and engage with

their favourite sports team (Witkemper et al., 2012). Lastly, results displayed

remuneration importance to CEB behaviours through Twitter with many sports

teams exploring this motivation to antagonise fans to enter their competitions to

reap rewards ranging from tangible to intangible products (Mangold and Faulds,

2009).

5.2. Limitation and Further research A study is not without its limitations. Our sampling method is one, with purposive

sampling being employed, the method has been highly prone to researcher bias.

Furthermore, our study was focused specifically on a single social media platform

and towards a specific football league limiting the results on other leagues and

social media platforms. Demographic factors could also be considered a

limitation with country being taken into consideration, as the results could have

varied due to culture and beliefs. Also, our participants age with most of the

participants age ranging from 18-24 and with the majority of the participants being

male, this could be viewed as a limitation as participants from different age

groups/genders could share different views on how football fans with their sports

club, with the older generation being more then unlikely to engage with their

sports team on social media. Lastly, the research method could be viewed as a

limitation. Questionnaires face specific limitations due to dishonesty as many

respondents could have rushed through the survey.

Further research in this field would help establish if the findings from this study

could be generalised towards other social media and other leagues/teams and

cultures. Adapting the research method to qualitative studies, to gather in-depth

insight about social media engagement behaviours to further articulate the fans’

viewpoints and experiences. Lastly, future research, could focus on a different

aspect of social media engagement, like fan loyalty to help examine the

relationship among the different motivations and online engagement.

5.3. Recommendations Our results provide sports marketers with information on what increases fans

engagement through arousing the preferred gratifications. With the growth of

social media, it means driving fan engagement through various channels has

become an important implication for football clubs through their social media

channels which can be utilised to promote targeted campaigns to build

relationships with their audience. With the importance of the Integration and

Social Interaction and Brand love; more football clubs need to ensure their

platforms shift towards more interaction amongst fans to give fans more of a

leading role and sense of power, to encourage engagement. Football clubs

should utilise their platforms to encourage fans to have discussion around

specific events that occurred. Through the polls available on various platforms

clubs, it should entice their fans to vote on specific question; e.g.: player who will

impact the match the most, selecting the starting line-up, and selecting man of

the match. With Integration and Social Interaction being a significant with the all

three levels of engagement, sports marketers could develop specific official

pages for fans to share their opinion and the club could put their input. With Brand

Love being considered a significant driver for all three levels of engagement

football clubs could focus on a range of activities, such as producing quizzes for

fans to show their knowledge of the club, as well as live Q&A’s with the clubs

most popular players could help with fans Brand Love. Lastly, Remuneration was

a considered a significant driver, sports teams could use their social media

platforms to offer fans incentives such as competitions, discounts or bargain

prices encouraging them to either read a discussion, like the page or retweet a

tweet which are associated with Consumption, Contribution and Creation.

5.4. Conclusion Twitter’s growth has opened a new platform for organisations to communicate

and engage with their audience. Many industries have profited from this growth

as it has enabled them to strengthen their relationship with fans, this has been

witnessed with Premier League clubs. The increase of the relationship has also

increased engagement behaviours and fans motivation for engaging with their

clubs which enables sports marketers understand the change in fans

engagement behaviours and how it may occur differently depending on the

platform.

Reference List Reference:

Abosag, I., Roper, S., and Hind, D. (2012) ‘Examining the relationship

between brand emotion and brand extension among supporters of

professional football clubs’, European Journal of Marketing, 46(9), pp.

1233–1251. doi:10.1108/03090561211247810.

Ahearne, M., Bhattacharya, C., and Gruen, T. (2005) ‘Antecedents and

consequences of customer-company identification: Expanding the role of

relationship marketing’ ,The Journal of Applied Psychology, 90(3),pp. 574–

585. doi:10.1037/0021-9010.90.3.574.

Baldus, B., Voorhees, C., and Calantone, R. (2015) ‘Online brand

community engagement: Scale development and validation’ Journal of

Business Research, 68(5), pp. 978–985. doi:10.1016/j.jbusres.2014.09.035.

Barczak, G. (2015) ‘Publishing Qualitative versus Quantitative Research’,

The Journal of product innovation management, 32(5), pp. 658.

Barrett, K.C., Leech, N.L. and Morgan, G.A. (2011) IBM SPSS for

Intermediate Statistics: Use and Interpretation. 4th edn. New York:

Routledge.

Bell, E. and Byrman, A. (2015) Business research methods. 4th edn.

Bergkvist, L., and Bech-Larsen, T. (2010) ‘Two studies of consequences

and actionable antecedents of brand love’, Journal of Brand Management,

17(7), pp. 504–518. doi:10.1057/bm.2010.6

Bhat, A. (2019a) ‘Descriptive Research: Definition, Characteristics,

Methods, Examples and Advantages’, Question Pro blog, n.d. Available at:

https://www.questionpro.com/blog/descriptive-research/ (Accessed: 4th

January 2019)

Bhat, A. (2019b) ‘Non-Probability Sampling: Definition, Methods and

Examples’, Question Pro blog, n.d. Available at:

https://www.questionpro.com/blog/non-probability-sampling/ (Accessed: 5th

January 2019)

Bhat, A. (2019c) ‘Probability Sampling: Definition, Methods and Examples’,

Question Pro blog, n.d. Available at:

https://www.questionpro.com/blog/probability-sampling/ (Accessed: 5th

January 2019

Bleacher Report (2009) Why Fans Are So Important. Available at:

https://bleacherreport.com/articles/129206-why-fans-are-so-important

(Accessed: 26th October 2018).

Blended Collective (2017) ‘Brand Love: Connecting with products the same

way we connect with people’, Blended Collective blog, 10th December.

Available at: https://blendedcollective.com/branding/brand-love-connecting-

with-products-the-same-way-we-connect-with-people/ (Accessed: 22nd

December 2018).

Blumrodt, J. and Huang-Horowitz, N.C. (2017) ‘Managing brand identity

strategy: how professional football wins the game’, Journal of Business

Strategy, 38(6), pp.31-37. https://doi.org/10.1108/JBS-08-2016-0083.

Brandwatch (2017) ’58 Incredible and Interesting Twitter Stats and

Statistics’, Brandwatch blog, 3rd January. Available at:

https://www.brandwatch.com/blog/44-twitter-stats/ (Accessed: 15th

December 2018).

Cadete, L. (2017) ‘ What is a pilot study?’, Students 4 best evidence blog,

31st July. Available at: https://www.students4bestevidence.net/pilot-studies/

(Accessed: 9th January 2019).

Carroll, B., and Ahuvia, A. (2006) ‘Some antecedents and outcomes of

brand love’, Marketing Letters, 17(2), pp. 79–89. doi:10.1007/s11002-006-

4219-2.

Cave, A. and Miller, A. (2017) The importance of social media in sport.

Available at: https://www.telegraph.co.uk/investing/business-of-sport/social-

media-in-sport/ (Accessed: 29th October 2018).

Chen, G. M. (2011) ‘Tweet this: A uses and gratifications perspective on

how active Twitter use gratifies a need to connect with others’, Computers in

Human Behavior, 27(2), pp. 755–762. doi:10.1016/j.chb.2010.10.023.

Clavio, G., and Kian, T. (2010) ’Uses and gratifications of a retired female

athlete’s Twitter followers’, International Journal of Sport Communication,

3(4), pp. 485–500. doi:10.1123/ijsc.3.4.485

Clavio, G., and Walsh, P. (2013) ‘Dimensions of social media utilization

among college sport fans’, Communication and Sport, 2(3), pp. 261–281.

doi:10.1177/2167479513480355

Davis, D.J. (2018) ‘The four types of social media engagement’, The Union

Metrics Blog, 30th March. Available at:

https://unionmetrics.com/blog/2016/03/types-of-social-media-engagement/

(Accessed: 15th November 2018)

De Vries, L., Gensler, S. and Leeflang, P.S.H. (2012) ‘Popularity of Brand

Posts on Brand Fan Pages: An Investigation of the Effects of Social Media

Marketing’, Journal of Interactive Marketing, 26(2), pp. 83-91.

deRuyter, K., and Wetzels, M. (2000) ‘With a little help from my fans:

Extending models of prosocial behaviour to explain supporters’ intentions to

buy soccer club shares’, Journal of Economic Psychology, 21(4), pp. 387–

409. doi:10.1016/S0167-4870(00)00010-6.

Dholakia, U. M., Bagozzi, R. P., and Pearo, L. K. (2004) ‘A social influence

model of consumer participation in network- and small-group-based virtual

communities’, International Journal of Research in Marketing, 21(3), pp.

241–263. doi:10.1016/j.ijresmar.2003.12.004.

Dionisio, P., Leal, C., and Moutinho, L. (2008) ‘Fandom affiliation and tribal

behaviour: A sports marketing application’, Qualitative Market Research,

11(1), pp. 17–39. doi:10.1108/13522750810845531

Dolan, R., Conduit, J., Fahy, J., and Goodman, S. (2016) ‘Social media

engagement behaviour: A uses and gratifications perspective’, Journal of

Strategic Marketing, 24(1), pp. 261–277. doi:10.1080/096525

4X.2015.1095222.

Drula, G. (2012). ‘Social and online media research - data, metrics and

methods.’, Review of Applied Socio-Economic Research, 3(1), pp 77.

Dunne, A., Lawlor, M.-A., and Rowley, J. (2010) ‘Young people’s use of

online social networking sites – A uses and gratifications perspective’,

Journal of Research in Interactive Marketing, 4(1), pp. 46–58.

doi:10.1108/17505931011033551

Economic and Social Research Council (2019) Research. Available at:

https://esrc.ukri.org/research/impact-toolkit/social-media/twitter/what-is-

twitter/ (Accessed: 15th December 2018).

Filadelfo, E and Bavishi, J. (2018) ‘Insight into the 2018 #WorldCup

conversation on Twitter’, Twitter blog, 17th July. Available at:

https://blog.twitter.com/official/en_us/topics/events/2018/2018-World-Cup-

Insights.html (Accessed: 15th December 2018).

Filo, K., Lock, D., and Karg, A. (2015) ’Sport and social media research: A

review’, Sport Management Review, 18(2), pp. 166–181.

doi:10.1016/j.smr.2014.11.001.

Frary, M. (2016) ‘ UK consumers are falling in brand love’, Raconteur blog,

29th July. Available at: https://www.raconteur.net/retail/uk-consumers-are-

falling-in-brand-love (Accessed: 22nd December 2018)

Gensler, S., Volkner, F., Liu-Thompkins, Y., and Wiertz, C. (2013)

‘Managing brands in the social media environment’, Journal of Interactive

Marketing, 27(1), pp. 242–256. doi:10.1016/j.intmar.2013.09.004

Gibbs, C., O’Reilly, N., and Brunette, M. (2014) ‘Professional team sport and

Twitter: Gratifications sought and obtained by followers’, International

Journal of Sport Communication, 7(2), pp. 188–213. doi:10.1123/

IJSC.2014-0005.

Grewal, D., Roggeveen, A.L., Sisodia, R. and Nordfält, J. (2017) ‘

Enhancing customer engagement through consciousness’, Journal of

Retailing, 93(1), pp.55-64.

Grove, S., Pickett, G., Jones, S., and Dorsch, M. (2012) ‘Spectator rage as

the dark side of engaging sport fans: Implications for services marketers’,

Journal of Service Research, 15(1), pp. 13–20.

doi:10.1177/1094670511428166.

Gummerus, J., Liljander, V., Weman, E., and Pihlström, M. (2012)

‘Customer engagement in a Facebook brand community’, Management

Research Review, 35(9), pp. 857–877. doi:10.1108/01409171211256578.

Guosong, S. (2009) ‘Understanding the appeal of user generated media: A

uses and gratification perspective’, Internet Research, 19(1), pp. 7–25.

doi:10.1108/10662240910927795.

Health Knowledge (2017) Introduction to study designs – cross-sectional

studies. Available at: https://www.healthknowledge.org.uk/e-

learning/epidemiology/practitioners/introduction-study-design-css

(Accessed:4th January 2019).

Heinone, K. (2011) ‘Consumer activity in social medial: Managerial

approaches to consumers’ social media behaviour’, Journal of Consumer

Behaviour, 10(6)m pp. 356-364.

Hollebeek, L., and Brodie, R. (2016b) ’Non-monetary social and network

value: Understanding the effects of non-paying customers in new media’,

Journal of Strategic Marketing, 24, pp. 169–174. doi:10.1080/0

965254X.2015.1097093.

Hollebeek, L., and Chen, T. (2014a) ‘Exploring positively-versus negatively-

valenced brand engagement’, Journal of Product and Brand Management,

23(1), pp. 62–74. doi:10.1108/JPBM-06-2013-0332.

Hollebeek, L.D. (2011c) ‘Demystifying customer brand engagement:

Exploring the loyalty nexus’, Journal of Marketing Management, 27(7-8), pp.

785-807.

Hunt, K.A., Bristol, T., and Bashaw, R.E. (1999) ‘A conceptual approach to

classifying sports fans’, Journal of Services Marketing, 13(6), pp. 439–452.

doi:10.1108/08876049910298720.

Johansson, A. (2018) ‘Social Media Gives Everyone a Voice – Including the

Crazies’, Socialnomics blog, 3rd September. Available at:

https://socialnomics.net/2018/09/03/social-media-gives-everyone-a-voice-

including-the-crazies/ (Accessed: 20th December 2018).

Katz, E., Haas, H., and Gurevitch, M. (1973) ‘Use of the mass media for

important things’, American Sociological Review, 38(1), pp. 164–181.

doi:10.2307/2094393

Kezar, A. (2000) ‘The importance of Pilot Studies: Beginning the

Hermeneutic Circle’, Research in Higher Education, 41(3), pp. 385-400.

Kim, Y.H., Kim, D.J. and Wachter, K (2013) ‘A study of mobile user

engagement (MoEN): Engagement motivations, perceived value,

satisfaction, and continued engagement intention’, Decision Support

Systems, 56(1), pp. 361-370. https://doi.org/10.1016/j.dss.2013.07.002

Ko, H., Cho, C.-H., and Roberts, M. (2005) ‘Internet uses and gratifications:

A structural equation model of interactive advertising’, Journal of

Advertising, 34(2), pp. 57–70. doi:10.1080/00913367.2005.10639191.

Korhan, O. and Ersoy, M. (2015) ‘Usability and functionality factors of the

social network site application users from the perspective of uses and

gratification theory’, Quality and Quantity, 50(4), pp. 1799-1816.

Lariscy, R.W., Tinkham, S.F. and Sweetser, K.D. (2011), ‘Kids these days:

examining differences in political uses and gratifications, internet political

participation, political information efficacy, and cynicism on the basis of age’,

American Behavioral Scientist, 55(6), pp. 749-764.

Leander, M. (2011) What is a good Engagement Rate on a Facebook

Page? Here is a benchmark for you. Available at:

https://www.michaelleander.me/blog/facebook-engagement-rate-

benchmark/ (Accessed: 8th November 2018).

Lewis, P., Saunders, M. and Thornhill, A. (2016) Research methods for

business students. 7th edn. Pearson Education Limited: Harlow, Essex.

Lifewire (2018) What Is Twitter and How Does It Work?. Available at:

https://www.lifewire.com/what-exactly-is-twitter-2483331 (Accessed: 15th

December 2018).

Lin, K.-Y., and Lu, H.-P. (2011) ‘Why people use social networking sites: An

empirical study inte- grating network externalities and motivation theory’,

Computers in Human Behaviour, 27, 1152–1161.

Loakimidis, M. (2010) ‘Online marketing of professional sport clubs:

Engaging fans on a new playing field’, International Journal of Sports

Marketing and Sponsorship, 11(4), pp. 271–282. doi:10.1108/IJSMS-11- 04-

2010-B002.

Lowe, B. and Laffey, D. (2011) ‘Is Twitter for the Birds?: Using Twitter to

Enhance Student Learning in a Marketing Course’, Journal of Marketing

Education, 33(2), pp. 183–192. doi: 10.1177/0273475311410851.

Mahan, J. (2011) ‘Examining the predictors of consumer response to sport

marketing via digital social media’, International Journal of Sport

Management and Marketing, 9(3-4), pp. 254–267. doi:10.1504/

IJSMM.2011.041575.

Malik, A., Dhir, A., and Nieminen, M. (2016) ‘ Uses and Gratifications of

digital photo sharing on Facebook’, Telematics and Informatics, 33(1), pp.

129-138.

Malthouse, E., Haenlein, M., Skiera, B., Wege, E., and Zhang, M. (2013)

‘Managing customer relationships in the social media era: Introducing the

social CRM house’ Journal of Interactive Marketing, 27(1), pp. 270–280.

doi:10.1016/j.intmar.2013.09.008

Manchester United (2019) Competitions. Available at:

https://www.manutd.com/en/fans/competitions (Accessed: 1st March 2019)

Mangold, W.G., and Faulds, D. J, (2009) ‘Social Media: The new hybrid

element of the promotion mix’, Business Horizons, 52(4), pp. 357-365.

McCarthy, J., Rowley, J., Ashworth, C., and Pioch, E. (2014) ‘Managing

brand presence through social media: The case of UK football clubs’,

Internet Research, 24, pp. 181–204. doi:10.1108/IntR-08-2012-0154.

McQuail, D. (1983) Mass communication theory. London: Sage.

Meng, M., Stavros, C., and Westberg, K. (2015) ‘Engaging fans through

social media: Implications for team identification’, Sport, Business and

Management: An International Journal, 5(3), pp. 199–217. doi:10.1108/

SBM-06-2013-0013

Miller, J. (2018) ‘How online social media persona affects personal identity’,

Searchlight blog, 28th October. Available at:

https://searchlight.vc/searchlight/dr-jozelle-miller/2018/08/28/how-online-

social-media-persona-affects-personal-identity/ (Accessed: 20th December

2018).

Mount, M. and Martinez, G.M. (2014) ‘Social Media: A TOOL FOR OPEN

INNOVATION’, California Management Review, 56(4), pp. 124–143. doi:

10.1525/cmr.2014.56.4.124.

Muntinga, D. (2013a) ‘Catching COBRAs’, Amsterdam: University of

Amsterdam.

Muntinga, D., Moorman, M., and Smit, E. (2011b) ‘Introducing COBRAs

Exploring motivations for brand related social media use’, International

Journal of Advertising, 30(1), pp. 13–46. doi:10.2501/ija-30-1-013-046.

Nest (2018) The impact of social and digital media on sport. Available at:

https://nest.latrobe/the-impact-of-social-and-digital-media-on-sport/

(Accessed: 29th October 2018).

Oh, C., Roumani, Y., Nwankpa, J.K., and Hu, H. (2017) ‘Beyond likes and

tweets: Consumer engagement behaviour and movie box office in social

media’, Information and Management, 54(1), pp. 25-37.

Omnicore (2018) Twitter by the Numbers: Stats, Demographics and Fun

Facts. Available at: https://www.omnicoreagency.com/twitter-statistics/

(Accessed: 5th November 2018)

Palazon, M., Sicilia, M. and Lopez, M. (2015) ‘The influence of ‘Facebook

friends’ on the intention to join brand pages’, Journal of Product and Brand

Management, 24(6), pp. 580-595.

Park, N., Kee, K., and Valenzuela, S. (2009) ‘Being immersed in social

networking environment: Facebook groups, uses and gratifications, and

social outcomes’, Cyber Psychology and Behaviour, 12(6), pp. 729–733.

doi:10.1089/cpb.2009.0003.

Popp, B., Wilson, B., Horbel, C., and Woratschek, H. (2016) ’Relationship

building through Facebook brand pages: The multifaceted roles of

identification, satisfaction, and perceived relationship investment’, Journal of

Strategic Marketing, 24(3-4), pp. 278–294.

doi:10.1080/0965254X.2015.1095226.

Raby, A. (2018) ‘ 5 Awesome Sports Social Media Examples to Learn

From’, Themeboy blog, 9th October . Available at:

https://www.themeboy.com/blog/killer-sports-social-media-examples-2018/

(Accessed: 15th December 2018).

Research Methodology (2019) Abductive reasoning (abductive approach).

Available at: https://research-methodology.net/research-

methodology/research-approach/abductive-reasoning-abductive-approach/

(Accessed: 27th December 2018).

Rubin, A. (1983) ‘Television uses and gratifications: The interactions of

viewing patterns and motivations’, Journal of Broadcasting and Electronic

Media, 27(1), pp. 37–51. doi:10.1080/08838158309386471.

Saffer, A. J., E. J. Sommerfeldt, and M. Taylor. (2013) ‘The Effects of

Organizational Twitter Interactivity on Organization–Public relationships’,

Public Relations Review 39 (3), pp. 213–215.

Sandvoss, C. (2005) ‘Fans: The mirror of consumption’ Cambridge: Polity

Press.

Schau, H., and Gilly, M. (2003) ‘We are what we post? Self-presentation in

personal web space’, Journal of Consumer Research, 30(3), pp.385–404.

doi:10.1086/378616

Schivinski, B., Christodoulides, G., Dabrowski, D. (2016) ‘Measuring

Consumers’ Engagement With Brand-Related Social-Media Content -

Development and Validation of a Scale That Identifies Levels of Social-

Media Engagement With Brands’, Journal of Advertising Research, 56(1),

pp. 1-18. DOI: 10.2501/JAR-2016-000.

Schmidt, G. (2017) ‘Social media is like a cocktail party. If you want

engagement you can’t just stand there!’, Espresso Blog, 9th December.

Available at: https://espresso.digital/social-media-engagement/ (Accessed:

15th October 2018).

Shin, D.-H. (2011) ‘Understanding e-book users: Uses and gratification

expectancy model’, New Media and Society, 13(2), pp. 260–278. doi:

10.1177/1461444810372163.

Smock, A., Ellison, N., Lampe, C., and Wohn, D. (2011) ‘Facebook as a

toolkit: A uses and gratification approach to unbundling feature use’,

Computers in Human Behaviour, 27(6), pp. 2322–2329. doi:10.1016/

j.chb.2011.07.011.

Spinda, J.S.W and Puckette, S. (2018) ‘Just a Snap: Fan Uses and

Gratifications for Following Sports Snapchat’, Journal of Communication

and Sport, 6(5) , pp. 627-649.

Statistics Solutions (2013) Confirmatory Factor Analysis. Available at:

https://www.statisticssolutions.com/confirmatory-factor-analysis/ (Accessed:

9th January 2019).

Stavros, C., Meng, M., Westberg, K., and Farrelly, F. (2014) ‘Understanding

fan motivation for interacting on social media’, Sport Management Review,

17(4), pp. 455–469. doi:10.1016/j.smr.2013.11.004.

Sundar, S., and Limperos, A. (2013) ‘Uses and grats 2.0: New gratifications

for new media’, Journal of Broadcasting and Electronic Media, 57(4), pp.

504–525. doi:10.1080/08838151.2013.845827.

Thakur, R. (2018) ‘Customer engagement and online reviews’, Journal of

Retailing and Consumer Services, 41(1), pp. 48-59.

Traackr (2018) Influencer Marketing. Available at:

http://www.traackr.com/influencer-marketing (Accessed: 20th December

2018).

Tsai, W. and Men, L. (2013a) ‘Motivations and antecedents of consumer

engagement with brand pages on social networking sites’, Journal of

Interactive Advertising, 13, pp. 76–87. doi:10.1080/15252019.201 3.826549.

Tsai, W., and Men, L. (2017b) ‘Consumer engagement with brands on social

network sites: A cross-cultural comparison of China and the USA.’, Journal

of Marketing Communication, 23(1), pp. 2–21.

doi:10.1080/13527266.2014.942678

Vaghela, K. (2018) Arsenal Fan TV forced into complete rebrand after talks

with club. Available at: https://www.independent.co.uk/sport/football/premier-

league/arsenal-fan-tv-news-aftv-rebrand-youtube-channel-social-media-

a8491596.html (Accessed: 10th January 2019).

Vale, L. and Fernandes, T. (2018) ‘Social media and sports: driving fan

engagement with football clubs on Facebook’, Journal of Strategic

Marketing, 26(1), pp. 37-55, DOI: 10.1080/0965254X.2017.1359655.

Vallerand, R.J. , Ntoumanis, N. , L. Philippe, F.L. , Lavigne, G.L. ,

Carbonneau, N. , Bonneville, A. , Lagacé-Labonté, C. and Maliha, G. (2008)

‘On passion and sports fans: A look at football’, Journal of Sports Sciences,

26(12), pp. 1279-1293, DOI: 10.1080/02640410802123185

VanDoorn, J., Lemon, K., Mittal, V., Nass, S., Pick, D., Pirner, P., and

Verhoef, P. (2010) ‘Customer engagement behaviour: Theoretical

foundations and research directions’, Journal of Service Research, 13(3),

pp. 253–266. doi:10.1177/1094670510375599

Wakefield, K., and Wann, D. (2006) ‘An examination of dysfunctional sport

fans: Method of classification and relationships with problem behaviors’ ,

Journal of Leisure Research, 38(2), pp. 168–186.

Wallace, L., Wilson, J., and Miloch, K. (2011) ’Sporting Facebook: A content

analysis of NCAA organizational sport pages and Big 12 conference athletic

department pages’, International Journal of Sport Communication, 4, pp.

422–444. doi:10.1123/ijsc.4.4.422 .

Wang, X. (2013a) ‘Applying the integrative model of behavioural prediction

and attitude functions in the context of social media use while viewing

mediated sports’, Computers in Human Behaviour, 29(4), pp.1538–1545.

Wang, X. (2015b) ‘Using attitude functions, self-efficacy, and norms to

predict attitudes and intentions to use mobile devices to access social media

during sporting event attendance’, Mobile Media and Communication, 3(1),

pp.75–90.

Whiting, A. and Williams, D. (2013) ‘Why people use social media: a uses

and gratifications approach’, Qualitative Market Research: An International

Journal, 16(4), pp.362-369. https://doi.org/10.1108/ QMR-06-2013-0041.

Williams, J., and Chinn, S. (2010) ‘Meeting relationship-marketing goals

through social media: A conceptual model for sport marketers’ International

Journal of Sport Communications, 3, pp. 422–437. doi:10.1123/ ijsc.3.4.422.

Witkemper, C., Hoon-Lim, C. and Waldburger, A. (2012) ‘ Social Media and

Sports Marketing: Examining the Motivations and Constraints of Twitter

Users’, Sports Marketing Quarterly, 21(3), pp. 170-183.

World Atlas (2018) The Most Popular Sports in the United Kingdom.

Available at: https://www.worldatlas.com/articles/most-popular-sports-in-the-

united-kingdom.html (Accessed: 17th October 2018).

Yoshida, M., Gordon, B., Nakazawa, M., and Biscaia, R. (2014)

‘Conceptualization and measurement of fan engagement: Empirical

evidence from a professional sport context’, Journal of Sport Management,

28(4),pp. 399–417. doi:10.1123/jsm.2013-0199.

Zaglia, M. (2013) ‘Brand communities embedded in social networks’,

Journal of Business Research, 66(2), pp. 216–223.

doi:10.1016/j.jbusres.2012.07.015.

Appendices

Appendix A – Ethical approval

College of Business, Arts and Social Sciences Research Ethics Committee Brunel University London

Kingston Lane Uxbridge UB8 3PH

United Kingdom

www.brunel.ac.uk

4 January 2019

CONDITIONAL LETTER OF APPROVAL

Applicant: Mr x

Project Title: Social media and sports: driving fan engagement with Premier league football clubs on Twitter

Reference: 13841-LR-Dec/2018- 15483-1

Dear Mr x

The Research Ethics Committee has considered the above application recently submitted by you.

The Chair, acting under delegated authority has agreed that there is no objection on ethical grounds to the proposed study. Approval is given on the understanding that the conditions of approval set out below are followed:

The data should be stored on a Brunel server, password protected, and destroyed when no longer required. On the PIS, for the Indemnity question please state that Brunel provides appropriate insurance cover for research which has received ethical approval. For the contact details, please also add yourself and your Brunel email address and remove Peter Hobson. Under "What if something goes wrong?", please add the email address '[email protected].' The agreed protocol must be followed. Any changes to the protocol will require prior approval from the Committee by way of an application for an amendment.

Please note that:

Research Participant Information Sheets and (where relevant) flyers, posters, and consent forms should include a clear statement that research ethics approval has been obtained from the relevant Research Ethics Committee. The Research Participant Information Sheets should include a clear statement that queries should be directed, in the first instance, to the Supervisor (where relevant), or the researcher. Complaints, on the other hand, should be directed, in the first instance, to the Chair of the relevant Research Ethics Committee. Approval to proceed with the study is granted subject to receipt by the Committee of satisfactory responses to any conditions that may appear above, in addition to any subsequent changes to the protocol. The Research Ethics Committee reserves the right to sample and review documentation, including raw data, relevant to the study. You may not undertake any research activity if you are not a registered student of Brunel University or if you cease to become registered, including abeyance or temporary withdrawal. As a deregistered student you would not be insured to undertake research activity. Research activity includes the recruitment of participants, undertaking consent procedures and collection of data. Breach of this requirement constitutes research misconduct and is a disciplinary offence.

Professor David Gallear

Chair

College of Business, Arts and Social Sciences Research Ethics Committee Brunel University London

Page 1 of 2

Appendix B – Online survey

Appendix C – Participant Information Sheet

Appendix D – Proof of participants

Appendix E - Cronbach’s Alpha

Information

Reliability Statistics

Cronbach's

Alpha

Cronbach's

Alpha Based on

Standardized

Items N of Items

.818 .818 4

Entertainment

Reliability Statistics

Cronbach's

Alpha

Cronbach's

Alpha Based on

Standardized

Items N of Items

.849 .849 4

Personal Identity

Reliability Statistics

Cronbach's

Alpha

Cronbach's

Alpha Based on

Standardized

Items N of Items

.848 .852 3

Integration & Social Interaction

Reliability Statistics

Cronbach's

Alpha

Cronbach's

Alpha Based on

Standardized

Items N of Items

.885 .890 4

Empowerment

Reliability Statistics

Cronbach's

Alpha

Cronbach's

Alpha Based on

Standardized

Items N of Items

.891 .893 4

Remuneration Reliability Statistics

Cronbach's

Alpha

Cronbach's

Alpha Based on

Standardized

Items N of Items

.770 .770 4

Brand Love

Reliability Statistics

Cronbach's

Alpha

Cronbach's

Alpha Based on

Standardized

Items N of Items

.926 .926 4

Consuming

Reliability Statistics

Cronbach's

Alpha

Cronbach's

Alpha Based on

Standardized

Items N of Items

.959 .960 4

Contributing

Reliability Statistics

Cronbach's

Alpha

Cronbach's

Alpha Based on

Standardized

Items N of Items

.955 .955 4

Creating Reliability Statistics

Cronbach's

Alpha

Cronbach's

Alpha Based on

Standardized

Items N of Items

.936 .937 4

Appendix F – Sources of questions