MBA Dissertation - The voice of the Stakeholder: Customer attitudes to the role of Corporate Social Responsibility (CSR) in the UK Banking Sector since the Financial Crisis (2007)

The voice of the Stakeholder

Customer attitudes to the role of Corporate Social

Responsibility (CSR) in the UK Banking Sector since the

Financial Crisis (2007)

Author: Amany Hamza

Submitted in partial fulfilment of the requirements for the degree of MBA

Supervisor: Dr. Alireza Nazarian

University of West London

August 2014

Acknowledgments

First and foremost, I am bound to express my heartfelt gratitude to my husband for his

encouragement and forbearance as well as my lovely kids who have been extremely patient

with me during this challenging task. The successful completion of this work is actually

attributed to their unlimited support throughout the whole process of writing my

dissertation.

On the professional level, I wish to express my profound gratitude to my supervisor, Dr.

Alireza Nazarian, whom I am forever indebted for the immense advice and guidance he has

given me. I would also like to sincerely thank the study participants who took the time to

respond to the study questionnaire.

Abstract

Seven years on from the tumultuous events of 2007 financial crisis (FC), yet, many aspects

of the banking industry are unrecognisable when compared to the pre-crisis era despite the

growth in the UK economy that seems finally to be gaining traction. One consequence of the

ethical violations and corporate excess malfeasance of many banks that brought UK banking

industry into the firing line (Herzig & Moon, 2011; Bouvain et al, 2013) has been the call for

reforms concerning its responsibilities towards the society (Williams & Elliott, 2010; Sun et

al, 2010).

This study attempts to get to the heart of much of the debate about CSR development in

light of that FC. It is concerned with the perception of CSR activities in the post FC, the

likelihood of the convergence between banks CSR activities and its customer-stakeholder

needs and the implications of CSR on their attitudes as well as on Corporate Reputation

(CR).

The study reviews various works of literature concerning the topic at hand. The

hypothesised relationships between CSR and respectively customer satisfaction, customer

purchasing decision and CR were evaluated using a quantitative method based on a

positivist research paradigm. Primary data was sourced from 92 usable questionnaires

(response rate 46%) from UK banks customers.

Drawing from the analysis, it was found that there is a significant positive relationship

between perceived CSR activities and customer-stakeholder satisfaction in the post FC

which is in line with literature of stakeholder model and supports the views of Luo &

Bhattacharya (2006). With reference to CSR practices and customer purchasing decision, the

results revealed a positive significant relationship between them, also consistent with the

results of the study of Klein & Dawar (2004).

Moreover, the analysis of this relation contributed to CSR literature by investigating the

multidisciplinary domain of CSR on customer purchasing intention. CSR was also found to

have a significant positive relationship with Corporate Reputation which shares the view of

Reputation Institute (2009, cited in Trotta et al, 2011). Remarkably, the findings indicated a

partial mediation effect of CSR on the relationship between CR and customer behavioural

intention. Concluding remarks highlight further theoretical development of CSR and

managerial implications as well as limitations for future research.

Table of Contents

Acknowledgments ................................................................................................................................... 2

Abstract ................................................................................................................................................... 3

Table of Contents .................................................................................................................................... 4

Chapter 1: Introduction .......................................................................................................................... 6

1.1. INTRODUCTION ............................................................................................................................... 6

1.2. BACKGROUND ................................................................................................................................. 7

1.3. THE PROBLEM STATEMENT ............................................................................................................... 9

1.4. RESEARCH AIM AND OBJECTIVES ...................................................................................................... 11

1.5. SCOPE OF THE DISSERTATION ........................................................................................................... 12

1.6. STRUCTURE OF THE DISSERTATION .................................................................................................... 14

1.7. CONCLUSION ................................................................................................................................ 14

Chapter 2: Literature Review ................................................................................................................ 15

2.1. INTRODUCTION ............................................................................................................................. 15

2.2. FRAMING CSR .............................................................................................................................. 15

2.3. STRATEGIC CSR ............................................................................................................................. 28

2.4. CONCLUSION ................................................................................................................................ 38

Chapter 3: Methodology ....................................................................................................................... 39

3.1. INTRODUCTION ............................................................................................................................. 39

3.2. RESEARCH PHILOSOPHY .................................................................................................................. 39

3.3. RESEARCH DESIGN ......................................................................................................................... 46

3.4. DATA TREATMENT AND DATA ANALYSIS TECHNIQUES .......................................................................... 65

3.5. CONCLUSION ................................................................................................................................ 71

Chapter 4: Analysis and Discussion of Findings .................................................................................... 72

4.1. INTRODUCTION ............................................................................................................................. 72

4.2. DESCRIPTIVE STATISTICS ................................................................................................................. 72

4.3. EMPIRICAL FINDINGS OF PARAMETRIC DATA ...................................................................................... 75

4.4. DISCUSSION OF FINDINGS ............................................................................................................... 87

4.5. CONCLUSION ................................................................................................................................ 92

Chapter 5: Conclusion and Recommendations ..................................................................................... 93

5.1. INTRODUCTION ............................................................................................................................. 93

5.2. CONCLUSION ................................................................................................................................ 93

5.3. PRACTITIONER CONTRIBUTIONS ....................................................................................................... 94

5.4. THEORETICAL CONTRIBUTIONS ......................................................................................................... 95

5.5. RECOMMENDATIONS FOR FUTURE RESEARCH AND RESEARCH LIMITATIONS .............................................. 96

References ............................................................................................................................................ 98

Appendices .......................................................................................................................................... 106

APPENDIX A – SURVEY EMAIL INVITATION ................................................................................................... 106

APPENDIX B1 – SURVEY FIRST REMINDER .................................................................................................... 107

APPENDIX B2 – SURVEY FINAL REMINDER ................................................................................................... 108

APPENDIX C – SURVEY ............................................................................................................................. 109

APPENDIX D – ACRONYMS ........................................................................................................................ 118

APPENDIX E – RESEARCH OBJECTIVE ONE – RELIABILITY ANALYSIS 1 ................................................................ 119

APPENDIX F – RESEARCH OBJECTIVE ONE – FACTOR ANALYSIS (BEFORE COMPONENT EXTRACTION) .................... 134

APPENDIX G – RESEARCH OBJECTIVE ONE- FACTOR AND RELIABILITY ANALYSES ................................................ 225

APPENDIX H – RESEARCH OBJECTIVE ONE – REGRESSION ANALYSIS ................................................................. 239

APPENDIX I – RESEARCH OBJECTIVE TWO – FACTOR AND RELIABILITY ANALYSES ................................................ 241

APPENDIX J – RESEARCH OBJECTIVE THREE – CORRELATION COEFFICIENT AND REGRESSION ANALYSES ................. 258

APPENDIX K – RESEARCH OBJECTIVE FOUR – HIERARCHICAL REGRESSION ANALYSIS ........................................... 264

Chapter 1: Introduction

1.1. INTRODUCTION

To some, 2013 has showed modest improvements in the banking industry, making 2014 the

year that banks might see their best profits since the beginnings of the financial crisis (FC)

according to S&P (Standard & Poor) credit rating agency (Croucher, 2014). To others, the UK

banking industry entered the global lexicon of infamy whereby the ten leading banks have

cost the industry hefty fines of nearly £148bn – according to the LSE’s (London School of

Economics) report – with a string of scandals since the FC. Notwithstanding, the study by the

LSE did not include the Standard Chartered settlement of £407 million last year with the US

authorities for the violation of breaching the sanctions with Iran. Still, the fines and financial

penalties of £148bn are, ironically, larger than the economic output of a country such as

Ireland (Davies, 2013). The partial nationalisation and bail out of two of the country’s

biggest banks – Lloyds Banking Group and the Royal Bank of Scotland (RBS) – using the UK

taxpayer funds have exacerbated the industry’s reputation to the extent that the FC is

regarded as analogous to reputational crisis per se (Trotta et al, 2011).

As 2014 unfolds, the preceding controversial state of the UK banking industry in the post FC

raised pertinent questions on the development of Corporate Social Responsibility (hereafter

CSR) activities to meet its customer-stakeholders’ expectations and, concurrently, address

the dynamic demands of the social system. That is, the tenet of CSR has resurged to figure

prominently in the academic and business community debate. Yet, to date, there is a dearth

of academic literature about CSR in the financial services which spans a wide range of areas

from its characteristics and nature to its implications on corporate performance and

customers’ attitudes (Chomvilailuk & Butcher, 2010; Bennett & Kottasz, 2011; Bouvain et al,

2013). Drawing from these remarks, this study intends to pinpoint key insights in this field

and shed the light on issues impeding its development, hence offer a managerial agenda to

identify and stimulate practices consistent with commonly recognised norms and ethical

behaviour.

1.2. BACKGROUND

Although the CSR credo has been with the business world for centuries (Ahenkora et al,

2013), little is known of CSR literature prior to the 1950s. Some substantial writings can be

traced back as early as the 1776 manifested in the notion of the invisible hand published in

Adam Smith’s vintage book titled The Wealth of Nations. This view holds that exigencies of

profit justify self-interest pursuit and, in tandem, respond to societal demands insofar free

market mechanism is allowed. Smith had set a precedent to the neoliberal advocates of

shareholder principles in which the sole fiduciary duty of business is wealth creation for its

owners (Garriga & Mele, 2004; Carroll & Shabana, 2010). On the other hand, Andrew

Carneige, in his seminal publication, The Gospel of Wealth (1889), argued fervently that

business has a broader role towards society at large given the credence nature of managers

as public trustees (Pearce II & Doh, 2005). As such, CSR intensified as of 1960s with the

emergence of academic and managerial interests (Garriga & Mele, 2004; Carroll & Shabana,

2010) to contribute either to the expansion of business’ broad role towards society or the

contraction and resistant advocated by the shareholder view.

The dichotomy between the narrow wealth creation for shareholders and the holistic view

of business societal role towards society is mirrored in the current state of banking industry.

The line of thinking developed in this thesis belongs to the latter stream clustered around

the societal paradigm given the interrelationship rationalisation in the business-society

interactions. In this context, business seeks to integrate both explicit and implicit societal

concerns in its DNA (its strategy and culture) (EU Commission, 2001 cited in Decker, 2004).

One such integrative framework incorporates business responsiveness by accommodating

explicit claims together with evolving proactive strand from addressing implicit concerns

(Wood, 1991).

By doing so, some empirical researches, in particular since last decade, consent that the

aggregation of external consonance and internal consistency to operationalise societal

obligations can reap many tangible advantages; in essence, this can lead to stimulate

durable relationships with broader constituency (e.g. Maignan & Ferrell, 2001;

Bhattarcharya & Sen, 2001). Although these endeavour to bring CSR from ideology to

reality, extant studies lack analytical rigour given the tendency to justify CSR in terms of a

direct link to corporate financial performance as the critical criterion (e.g. McWilliams &

Siegel, 2001; Pomering & Dolnicar, 2009; Carroll & Shabana, 2010). By doing so, academic

research address one dimension of CSR though is considered a multidimensional construct

based on the embodiment of economic, social, ethical and environmental responsibilities

that business should strive to uphold at any given time (Carroll, 1979). This has contributed

to equivocal results of the CSR effects on the corporate financial performance in which

empirical support falls short by directly measuring a non-economic construct – CSR – using

economic metrics. Given the nature of CSR as based on a qualitative relationship between

business and society, measurement should employ mediating variables to gauge this

relationship.

Accordingly, the empirical research was primarily produced from the corporate perspective

whereas the effects of CSR on customers were under-researched (Chomvilailuk & Butcher,

2010). While, Bhattacharya & Sen (2001) called for exploring CSR outcomes from customers

perspective, most of academic research addressed consumer goods with little investigation

of the services business (McDonald & Thiele, 2007).

Noting these gaps in the CSR academic literature, this study tends to fill this void and put

forward propositions for verifiable criteria for business success voiced by customer

stakeholder.

1.3. THE PROBLEM STATEMENT

It was the best of times; it was the worst of times…

so begins Charles Dickens “A Tale of Two Cities”

The increased public scrutiny of business behaviour since the near-death experience of the

global FC has borne witness to radical change in the bank industry by espousing societal

implementations to align its institutional activities with its stakeholder demands. In this

sense, it can regain the lost trust in business while also avert new regulations of closer

scrutiny of its conduct (Bouvain et al, 2013). In other words, it can be argued that banks

have rethought their role in society in which parity has once again reverted to this industry

(Condosta, 2012).

Recalling Charles Dickens quotation, the state of the banking industry is the worst of times

and the banking community has not learnt the lesson from the FC. Seemingly, this is

attributed to many issues that remain unresolved whereby a series of jaw-dropping scandals

are in flux. Cynically, in 2013, Lloyds was fined £28million for exploiting customers by

introducing a flawed incentive scheme between 2010 and 2012 (Shannon, 2013), while RBS

has been accused of pushing 'viable' businesses into default in order to seize their

properties and make a profit for the bank (Parker & Moore, 2013). A large portion of these

big losses were incurred in the subsequent years of the FC in 2007, hence the CSR practices

of the banking sector were called into question. There is doubt that these causalities lie in

the irresponsible behaviours of these practices, associated with the inability of either these

practices or the external structures of regulation to prevent these behaviours.

1.3.1. RESEARCH QUESTION

Against this backdrop, this study’s fundamental question emerged as whether the current

CSR activities in the UK banking industry have acquired accepted resonance through the

inclusion of societal expectations in the years that followed the FC, in particular:

Has the financial crisis been a wake-up call for CSR activities to resonate with customer-

stakeholder expectations to create sustainable business?

1.3.2. THE DEVELOPMENT OF THE RESEARCH HYPOTHESES

The following hypotheses were developed to help answer the aforementioned question.

The dominant debate on favouring CSR or refuting it has populated the literature that there

is no consensus on its conceptual or its practical implementation. The manifest failure of

CSR to conceive the dynamics of business and social systems is apparent in Bennett &

Kottasz’ (2012) claim that the British public’s evaluation of both the integrity and calibre of

banking industry has declined. On the other hand, there is the proposition that banks have

embraced socially responsible behaviour to address the needs of its customer-stakeholders

in the post FC of 2007. This formulated the assumption – first hypothesis – as:

H01: There is a relationship between perceived bank’s CSR activities and customer-

stakeholder satisfaction in the post-financial crisis of 2007.

The other hypotheses suggested pinning down a management agenda that elicit favourable

customer attitudes. The recent surge of ethical and social screened investment acknowledge

the possibility that there are customers who support socially responsible practices (Peters,

2007) and are likely to influence their behavioural intention (Bhattacharya & Sen, 2001).

Hence the researchable hypothesis was:

H02: There is a relationship between CSR practices and customer-stakeholders’ behavioural

intention.

CSR is regarded as a form of investment that constitutes sustainable competitive

advantages. In this vein, Porter & Kramer (2006) argue that satisfying the economic and

non-economic demands of stakeholders incorporates creating a solid reputation in the

marketplace by gaining society confidence. More so, it is considered the single most

important commodity which all transactions and trade are based upon in the banking

industry and, in the absence of it, the banking system reputation is on the line (Rothschild,

2013). This led to the hypothesis:

H03: There is a relationship between CSR fit practices and bank reputation.

The last hypothesis ascribed whether CSR practices mediate the link between customer-

stakeholders' behavioural intentions and banks reputation:

H04: There is a mediation effect of CSR practices in the relationship between customer-

stakeholders' behavioural intentions and banks reputation.

1.4. RESEARCH AIM AND OBJECTIVES

This study aimed to contribute towards a dynamic evolution of the CSR literature that is

echoed by the emerging norms and expectations of customer-stakeholders in the post FC of

2007 within the context of UK banking sector. This research sought out to investigate the

likelihood of CSR development in the banking context to meet customer-stakeholders

emerging expectations.

To this end, the objectives were based on:

• investigate whether perceived CSR activities in the post FC of 2007 have an impact

on banks’ customer-stakeholders satisfaction.

• evaluate whether there is a relationship between CSR practices and bank customer-

stakeholder behavioural intention (purchase behaviour).

• determine whether there is a relationship between CSR fit practices and bank

reputation.

• investigate whether CSR practices mediates the relationship between bank

reputation and stakeholders' behavioural intentions.

• provide an interdisciplinary and systematic framework for CSR literature by

delineating the customer attitudes towards a multidimensional CSR activities

• analyse pertinent literature underlying the CSR and Corporate Reputation (CR) link

1.5. SCOPE OF THE DISSERTATION

Corresponding to the research aim, the scope at hand was articulated around the normative

factor of social perceived value of the banking CSR activities in the post FC and the strategic

potential of CSR to create value for both the corporate entity and its constituencies. In this

setting, the analysis was derived from customer stakeholder-based views of CSR in which

fourfold of expectations – namely economic, ethical, legal and philanthropic of the so-called

Carroll’s CSR pyramid model (1979) – were used as a proxy for these views.

The study’s theoretical framework and analysis incorporated a pragmatic approach to CSR

by reconciling the emergent post FC normative views of customer stakeholder and business’

socially accepted activities obtained from the empirical analysis into a consolidative

construct of CSR development that reaps competitive advantage to contribute to business

financial well-being or, in other words, developing a strategic CSR that yields value-creation

to both ends. Building on this distinction, this thesis contributed to the literature of CSR by

investigating the attitude of customer-stakeholder towards multidimensional social

responsibilities. Furthermore, it scrutinized the case for strategic CSR to justify the

pragmatic approach to CSR activities in the banking industry based on the mediation effect

of CSR on the relationship between CR and customer attitude.

It is acknowledged that CR constitutes strategic advantage that is ascribable to the

reputational capital in which businesses leverage intangible organisational resource (Maden

et al, 2012; Peters, 2007). The notion of CR is rooted in perceptions. Hence, it is argued that

the point of departure is that CR is a collective representation of behaviour and activities

carried out by business to render valued results to various constituents (Caruana, 2008) and

therefore provide signals to that reduce uncertainty when customers choose among

products (Bouvain et al, 2013). This is particularly evident for services segment as it is

associated with high-involvement in which consumers’ process information actively before

making a purchase decision (Pomering & Dolnicar, 2009).

To accommodate this research scope, a web-based questionnaire was conducted for which

a convenience – non-probability – sampling method was employed. Consequently, the study

followed a deductive research strategy in which collected quantitative data was produced

by customers resident in the UK against the banking industry. The rationale for this

approach is considered justifiable as the UK banking sector is dominated by a few very large

banks making Britain one of the most concentrated banking systems in the world (Chalabi,

2014).

Moreover, it is also based on the collective identity elicited by the impact of the FC and

mainly in the present context of collective culpability (Bennett & Kottasz, 2012). In addition,

the intensity of the banking scandals, since the acute crisis broke out in summer 2007, made

it apparent that it is not just one part of banking that has problems; it is probably the whole

sector.

1.6. STRUCTURE OF THE DISSERTATION

This introductory chapter underpins the foundation of the study. Chapter 2 critically

discusses comprehensive literature involving the topic at hand. In Chapter 3, the

methodology is outlined through the adoption of a quantitative method where a survey was

developed through which customers voiced their opinions on banks CSR activities in the

post FC of 2007.

Chapter 4 furnished the set of analyses that were utilised to form the study findings in order

to answer the Research Question. The final chapter, Chapter 5, brings it all together

through the conclusion and recommendations.

1.7. CONCLUSION

This first chapter introduced the topic of the research, setting the foundation by

demonstrating CSR background and history. It then shed light on the formulation of the

Problem Statement leading to the Research Question. This was elaborated by discussing the

development of the Research Hypotheses. The Research Aim, Objectives and Scope were

then presented and, finally, the structure of this dissertation was then laid out.

Chapter 2: Literature Review

2.1. INTRODUCTION

This chapter presents an overview of distinct but integrated realms of literature. These

include CSR and CR. The opening section starts with critically recounting the genesis of CSR.

Afterwards, it synthesises key arguments to pursue insights into the role of business in

society to evaluate CSR construct in the twenty-first century. Guided by Carroll’s (1991) CSR

model, the definition of CSR is then discussed. The second section explores the literature

regarding Strategic CSR. A review of customer-stakeholders’ attitudes towards CSR is then

addressed to determine what has been proposed and found regarding the theoretical

relationships between the two domains. Thereafter, it demonstrates relevant theoretical

framework on the relationship between CSR and CR. A discussion of the mediation effect of

CSR marks the end of the chapter.

2.2. FRAMING CSR

The high profile scandals and ethical violations of some corporate entities of the early 1980s

and mid 2000s coupled with many new age problems – manifested in terms of poverty,

artificial market bubbling and the like (Louche et al, 2010, Sun et al, 2010) – have brought

contemporary business under siege by critical public scrutiny of its behaviour and its raison

d'être in society (Pendse, 2012). Underpinning these issues is the lack of a socially

responsible behaviour of businesses that contributed to the resurgence of interest in CSR. A

casual glance back over mid-20th century in business management reveals the upward surge

of the quest for businesses to embrace a responsible ethical behaviour in response, most

likely, to the negative externalities of its operations and activities (Pomering & Donicar,

2009) and the recurring repercussion of the capitalism model. Beyond this proposition,

cynics of CSR posit that it implies a risk to modern corporations of damaging them through

the discussion of their weaknesses instead of praising their strengths (Blowfield & Murray,

2008).

A contrasting view holds that sane corporations have responsibility towards society to

ameliorate the adverse impacts which they create to adhere to their ascribed role in society

and apply ethical and social standards to their business (Carroll & Shabana, 2010; Lindgreen

& Swaen, 2010). In support, Hay & Gray (1974) opined that the development of CSR is

touted as Quality of Life Management. Furthermore, the flurry of literature about CSR in

1960s and 1970s has promoted the theoretical context for corporate responsibility

(Blowerfield & Murray, 2008). However, it also spawned an array of overlapping concepts

that demonstrates the quest to incorporate CSR agendas that acknowledge the interests of

constituent groups in society (Maon et al, 2009) and the discernibly changes in business’s

relationship with other elements of society (Branco & Rodrigues, 2007; Smissen, 2012).

This rather a concise sketch of the variation dominated the CSR premise since the second

half of the 20th century in which a philosophically and economically intriguing debate on

the proper role of CSR has been taken place (Garriga & Mele, 2004).

Set against this outlook, the notion of CSR is regarded as an immensely contested construct

that convey vividly the long-standing debate between two discernible streams of thought

characterised as the neoliberal classic perspective of shareholder sovereignty and the neo-

Keynesian model that champions the stakeholder paradigm (Chomvilailuk & Butcher, 2010;

Mullerat, 2010). To illustrate this dilemma, key arguments around a bundle of questions

surrounding the determinants and dimension of CSR emerged with regards to the

fundamental purpose and responsibilities of businesses. Questions were raised about the

role of the business in society, its legitimate goal, the motives of CSR, the scope of the

managerial responsibility, the rationales concerned with business pursuing doing good to do

well and whether business’s primary endeavour to maximise the wealth creation of its

stockowners is synonymous to greed. The answers given have been forged by a proliferation

of theories and approaches that contributed to the development of CSR analysis (Garriga &

Mele, 2004). Noticeably, a plethora of cognate concepts such as stakeholder management,

corporate citizenship, sustainable business and business ethics have been developed in an

effort to justify arguments for why management needs to align corporation and societal

values to reap long-term prosperity (Carroll & Shabana, 2010; Herzig & Moon, 2011). While

other concepts generated such as value based management or enlightened value

maximisation advocated by contemporary adherents to the classical view (Martin et al,

2009). Despite the rise of these new concepts that are vying to supplant CSR to be the

descriptor of the field, the term Corporate Social Responsibility still serves as the reference

point in both the academic domain and the management realm.

Yet the development of CSR unfolded in uneven ways, albeit the theoretical context for CSR

is evolving, the practitioner communities might lag behind for the lack of cut-clear vision of

reliable guidance and standards to evaluate and control the actions of corporations

(Frederick, 2006). McWilliams & Siegel (2001) and McWilliams et al (2006), on the other

hand, contend that CSR became a mainstream in many business practices whereas others

might eschew the inclusion of societal values into their practices concerned about such

efforts being portrayed as dereliction of their duty to the business owners or subvert

corporate resources.

Notwithstanding, the abundant literature on CSR yet to date there is no definite consensus

exits on the definition of CSR given the complexity and the competing challenges expressed

by key stakeholders (Duarte et al, 2010; Nilsen, 2010). In this vain, it is argued that CSR

remit range from a narrow functionalist vision of business that involves economic and legal

responsibilities to a broader stance of enhancing the welfare society (Crane & Matten,

2010). Votaw (1972, cited in Garriga & Mele, 2004) summed up the multitude of meanings

given to the concept as to some it espouses responsible ethical behaviour, to others it is

tantamount to corporate liability and abiding by the law; to still others it is synonym for

philanthropic contributions. Votaw proceeded to critique the term for being a bewildering

premise leading to a high level of heterogeneity in how it is depicted. Sun et al (2010) help

to end on a positive end that CSR per se is a dynamic and contextual term bound up to its

application, societal conditions and political forces.

2.2.1. CSR DEBATE- THE ROLE OF BUSINESS IN SOCIETY

The CSR thrust rooted in the two controversy views amid the classical view based on the

shareholder view imposed by neoliberal economist adherents and the stakeholder view for

the role of business within society (Bhattacharya & Sen, 2001; Jamali, 2007; Sweeney, 2009).

The former is attributed to the invisible hand metaphor coined by Adam Smith (1776), the

18th century pioneer of political economics and is credited as the founder of capitalism

model and free market system. It implies that self-interest pursuit of business to create its

wealth spurs, de facto, society’s prosperity that is promoted by such acts (Carroll &

Buchholtz, 2009). The central claim of the free enterprise system is conceived as immoral or

unethical-free predominantly driven by the forces of free competition. The latter view was

brought forward and developed by R. Edward Freeman (1984) building on the inducement

contribution of Howard Bowen (1953, cited in Carroll & Shabana 2010) which was the initial

point in the field of CSR. Bowen (1953) in his landmark book, Social Responsibilities of the

Businessman, argues that the business community has moral obligations to society arises

from the impact of their decisions and activities whilst he goes on claiming that business

should conduct in line with the values of its society (Bartscht, 2013).

Along with the rise of CSR, detractors of CSR exemplified by Theodore Levitt (1958) warned

business to take heed of the adverse impacts of CSR on their business (Carroll & Shabana

2010; Cheers, 2011). Nobel laureate Milton Friedman (1970) – the originator of the

shareholder view- furthers Adam’s line of thinking whereby the main credo entails that

business’s only responsibility is to maximise shareholder’s wealth as long as it stays within

the rules of the game which is to say the justifications of Adam’s invisible hand view in

terms of unfettered competitive market (Crane & Matten, 2010; Bartscht, 2013). Frideman

concurs with Levitt’s view that social responsibility is subversive to business in terms it

diverts management from pursuing its legitimate goal of increasing the economic value of

stockholders who are considered the primary constituent in business. Friedman (1970)

claims that a broad stakeholder accountability of business is symptomatic of an agency

problem. In this context, he contemplated engaging into such social activities as a betrayal

of manager’s fiduciary duty to the owners. He notoriously proclaimed that acting for any

other purpose is tantamount to fraud and political subversion (Margolis et al, 2009; Crane &

Matten, 2010).

The well-established credence of shareholder primacy in the latter part of the twentieth

century sparked what has become a watershed debate on the role of business. Shareholder-

centric came under attack from a number of quarters for serving the interest of one cohort

with no regards to other stakeholders (Samy et al, 2010). A contrasting thinking emerged

epitomising the relationship between business and many stakeholder groups who have

stake and legitimate interest in the business. Providing an interesting slant on stakeholder

model, Bartscht (2013) posits that engaging in stakeholder relationships implies an

opportunity to build relative competitive advantage. Concerning this aspect, it was

acknowledged that the narrow view of maximising shareholder profit embodies a myopic

stance (Cheers, 2011). This incorporates taking the risk of producing short-term profit which

might lead to jeopardizing business viability and even shareholder wealth.

Clarkson (1995, cited in Lech 2013) proposes two typologies of stakeholders termed as

primary and secondary stakeholders. The former ascribes to prominent participants whose

support is pivotal for the existence and survival of business. It encompasses shareholders,

employees, customers, suppliers and local communities. On the other hand, the secondary

stakeholders are the non-participants who can have an impact on business and in a same

vein business’s actions can have an impact on them. The consideration of the interest of

business multiple stakeholders maintains a durable relationship which intensifies the

significance of advocating CSR ideology.

In essence, business and society are inextricably intertwined as Wood (1991) argues; hence

business has three roles to address the expectations of society. She proposes three

typologies of roles constitute business as an institution in society, as a particular corporation

in society and as individual managers. The level of analysis for these roles comprises three

principles of CSR in terms of legitimacy, public responsibility and managerial discretion. The

principle of legitimacy is rooted in society endorsing business legitimacy whereby business is

viewed as a social institution adheres to social norms of society. Furthermore, the principle

of public responsibility ultimately promotes actions that attuned to the societal needs of its

environment, whereas detrimental impacts of business practices involve admonishing its

failure. The last principle comes as a realisation of Wood (1991) that business managers are

not by some abstract actors but are individuals who have moral and ethos and need to

straddle the demands of both the shareholder and other stakeholders (Sexty, 2010).

2.2.2. DEFINING CSR AND THE EMERGENCE OF NEW VIEW

Carroll (1979, cited in Carroll & Shabna 2010) – an authoritative and progressive advocate of

CSR – has proposed a four-fold concept of CSR which manifests a set of interrelated

responsibilities that business is beholden to society at any given time. In essence, Carroll’s

analysis assimilates both the classical model and the social values underpinning CSR creed

(Carroll, 1991). Given this, Carroll’s concept entails an entire spectrum of economic and non-

economic expectations of maintaining a profitable sustainable business complemented with

the provision of products and services with economic and technical values to society, while

business is also expected to abiding by the law, by the ethical norms and standards and to

strive to promote the betterment of society (Carroll, 1999; Carroll & Buchholtz, 2009).

The four-part concept was depicted as a pyramid after been revised in 1991, as illustrated in

Figure 1. Carroll portrayed a multi-layered CSR model comprised of economic, legal, ethical

and philanthropic responsibilities that society expects business to meet. At its basis the

economic responsibility is ingrained for being the bedrock for business, hence, it undergirds

the other responsibilities (Crane & Matten, 2010), which are built upward through legal,

ethical while philanthropic responsibilities are at the tip of the pyramid. The crux of fusing

ethical and philanthropic responsibilities springs from McGuire’s (1963, cited in Carroll &

Shabana, 2010) arguing that CSR has other obligations than the growth of economic value

and obedience to the law to typify the entire CSR spectrum.

Economic Responsibilities capture the rational of the neoclassical ideology of having a

profitable business while Carroll asserts that sufficient profit is the acceptable perception as

legitimate to align the rest of the other three responsibilities, hence, the precept of

maximisation profit of neoliberal theme is unfeasible (Carroll & Shabana, 2010; Park et al,

2014). Accordingly, other responsibilities become moot considerations in the absence of a

sufficient profit that does not predispose other responsibilities to be unmet.

The underlying economic imperative is derived from its high relative weighting, as Crane &

Matten (2010) claims, in achieving the other three responsibilities and its importance for

business to strive for stimulating innovation, promoting fair work practices, creating jobs

and the like (Jamali, 2007; Yelkikalan & Kose, 2012).

The second category is the legal responsibilities; in essence, it addresses generating profit

within the local and international compulsory regulatory framework under which business

must operate. By doing so, Carroll asserts that the legal responsibilities are mandatory

whereas if business breaches them they do that at their peril on the one hand by revoking

its social contract to continue and by becoming ostracised. On the other hand, these legal

violation and illicit practices can transcend society reproach to a conviction, herein the first

two of what dubbed as ‘a triple-tier Who’s Who for officials under investigations – those

who are jail bound, those who might be sentenced and those who have the good luck

merely to be embarrassed’, as coined by Hahn (2002, cited in Sims 2003) have given

business a somewhat of tattered reputation and eroded confidence in corporate

governance integrity and ethicality.

By and large the promulgated laws and regulations by governments are touted as ‘codified

ethics’ of acceptable and unacceptable obligations placed on the business, as Carroll (1991)

suggests. To some extent, they constitute the minimum tolerable business behaviour, given

its deficiency they do not explicitly covering many morally contestable issues of newly

emerging values and still amorphous responsibilities, therefore Jamali (2007) concludes that

these legal responsibilities are reactive in nature.

Ethical dimension refers to the expected or prohibited business behaviour that is not

codified into the letter of the law. Respectively, Davis’s (1973, cited in Sun et al, 2010) goes

further acknowledging that responsible ethical behaviour can be said to embody the

periphery of values that situated beyond the legal obligation confines. These

responsibilities incorporate business values and those notions of justice, integrity, honesty,

trust, incorporeal rights of stakeholders and fairness into its practices, policies and decision

making (Crane & Matten, 2010). Sun et al (2010) argue that this dimension implies two

aspirations. First inspiration is cultivated in the Kantian deontological ethics which comprise

the fundamental principles of moral philosophy, whereby the second one emanates from

emerging values and changes in social norms, which may later lead to the creation of new

laws under the pressure of NGOs or civil groups or other stakeholders, however, most

regulations are enacted over time once some kind of consensus is reached (Carroll, 1991;

Cheers, 2011).

Lastly at the apex of the pyramid, the fourth dimension of responsibility refers to actively

engaging in local community through financial and non-financial contributions for a good

cause, promoting the quality of life of employees and the sponsorship of art or education

programs (Carroll, 1991; Jamali, 2007).

Carroll’s four-part definition of CSR has been the most durable and widely quoted model for

its relevant analysis of CSR (Carroll & Shabana, 2010), for its significant contribution of

demonstrating the false status quo concerning the paradox between economic and social

objectives, hence, this model bridges the gap between the two contradictory views.

Moreover its considerable value is associated with the identification of issues in the sphere

of each of the four preceding responsibilities such as employment discrimination,

consumerism and others (Branco & Rodrigues, 2007).

Depicting the responsibilities in four separate building blocks, on the one hand Carroll’s

emphasises the multiplicity of responsibilities that business should strive to uphold. On the

other hand this separation sheds light on a constant and dynamic tension amid these

obligations whereby this can help management accommodating an agenda that redresses

these issues (Jamali, 2007; Carroll & Buchholtz, 2009). Despite this separation, a true CSR

Figure 1 – Carroll’s Pyramid of Corporate Social Responsibility

(Carroll, 1991)

paradigm should compose the fulfilment of these four responsibilities at the same time

(Carroll & Shabana, 2010; Crane & Matten, 2010).

Taken together the foregoing discussion and Carroll’s (1979, 1991) four-fold definition and

analysis of CSR, there is a set of philosophical and normative management concerns to the

duty of business in society addresses opposite ends of a continuum. In other words, ‘the

business of business is business’ that Friedman (1970) argues fervently for only maximising

returns of shareholder and any contribution of corporate resources is deemed to be

depressing the financial value of the business. On the other hand, consideration of social,

legal, ethical and philanthropic responsibilities in business mission, values and strategy to

satisfy the burgeoning demands of these societal attributes can yield strategic advantages to

business. Some of the prominent supporters of this strand are Fombrun et al (2000),

Drucker (2002), Porter & Kramer (2006) and others. To this regard, CSR became a

mainstream in business management by advancing appropriate CSR strategies and effective

CSR activities to reconcile both the economic and the social objectives and achieve suitably

significant return to outweigh the expenditure (Vogel, 2005). Porter & Kramer (2006)

elaborate that business should stray from implying a reactive CSR strategies to a more

proactive CSR that spur the whole ambit of business operations such as value chain activities

and the like (Bartscht, 2013; Bouvain et al, 2013). This view came complementing on Davis

(1973) stance that CSR activities are deemed as institutionalised commitments of business

(Haynes et al, 2012; Idowu & Filh, 2008). Building on this distinction, CSR has moved from

ideology to be an integral part of business canvas (McDonald & Thiele, 2008; Sexty, 2010).

Using this view as a context, Mintzberg (1983, cited in Pomering & Dolnicar, 2008) calls this

theme as enlightened self-interest, in which he asserts that pure economic strategic

decision weeds out business’s commitment to address society claims (Mintzberg, 1978,

cited in Samy et al, 2010). In this regard, business’s growth and continuity are subject to

consumers’ rewarding and punishing influence, thereof managers should honour their

duties both the implicit social and explicit contracts (Isaksson, 2012).

On reflection, Carroll & Shabana (2010) present the business case for CSR corresponding to

the weak justification of CSR on normative grounds pertaining to ethics-orientation of CSR

predisposing it to be criticised by the shareholder camp. The reasoning for the business case

based on its contribution to nurture business economic bottom line as a result of business’s

culture, strategies and operational mechanisms are bound by to act in responsible

behaviour, social and legal manner. The imperative to engage in CSR activities is to produce

direct and clear link to corporate financial performance (Lindgreen & Swaen, 2010;

Blowfield & Murray, 2008). Given its narrow perspective to link CSR to corporate financial

performance as a rationale for the business case for CSR, Vogel (2005) adapts a holistic view

coined as ‘doing good to do well’ that he argues to be the essence of new CSR premise.

The high profile of CSR in the contemporary business is afforded to the support of

multilateral institutions such as the Prince of Wales International Business Leaders Forum

casting CSR activities as:

CSR means open and transparent business practices that are based on ethical values and respect for employees, communities and the environment. It is designed to deliver sustainable value to society at large, as well as to shareholder.

Sharma & Kiran, 2013

More contemporarily, EU Commission (2010, cited in Condosta, 2012) has addressed the

financial sector in its Sixth Environmental Action Program to improve transparency of their

reporting that:

[…] the financial sector’s lending and investment activities have significant indirect environmental impacts by determining which companies and activities have access to finance and the conditions attached. Facilitating disclosure of relevant information by the financial sector and companies could create an incentive for greener behaviour…

One of the striking initiatives was HSBC reporting its CSR in 2003 to communicate its

philanthropic and community engagement disclosures (Dusuki, 2008). Another

manifestation to promote social voluntary obligations in financial sector social is the Equator

Principles launched in 2003 to provide guidance on the assessment and implementation of

social risks in project financing. It was signed by 30 major international banks – such as

JPMorgan, Citibank, HSBC, Barclays and others (McDonald & Thiele, 2008) – some of which

were involved in the financial meltdown of 2007 onwards. In turn, this has been faced with

cynicism and scepticism about business’s motivations and amount to discrepancies between

CSR rhetoric and practices. Given this, it is argued that banking industry is dominated by the

shareholder paradigm (Mayer, 2013). The views of Dicken (2011) and Relaño (2011) are

quite similar to those of Mayer, they claim that UK economy market deliver on the

neoliberal model of free market capitalism.

By contrast, at the heart of Blowfield & Murray’s (2008) claim is that stakeholder view is the

feature of the modern corporate responsibility. Louche et al (2010) claim that a wide-

ranging CSR – namely economic, ethical, altruistic and strategic – has come to prominence

in the twenty first century. More interestingly, Friedman has alluded in part the importance

of the pertinent ethical custom embedded in discharging business’s function (Carroll &

Buchholtz, 2009). Thus, there are valid reasons to argue that the gaze turned towards

finding guidepost to implement and meet stakeholders’ expectations (Griseri & Seppala,

2010).

At the heart of the preceding controversies, an important question lingering in the public or

a segment of the public that have the practices of the banking industry after the jaw

dropping scandals and fiascos of the FC of 2007 adhering to a cohesive CSR to meet their

expectations and satisfy their conceived demands.

One consequence of this contentious situation is the claim that CSR analysis remains in an

embryonic stage which on one hand creates a perplexing influence on practitioners and

elude further development. On the other hand, it might be argued that the unclear

management strategies for CSR would impact stakeholders perceived CSR.

2.3. STRATEGIC CSR

An economist…and a sociologist are standing in front of a painting by Lucas Cranach in the museum in Berlin. The picture is of Adam and Eve. The economist says, ‘I see Adam with an apple and Eve with a leaf. The economic paradigm is simple. Adam is offering to trade in his apple for a leaf.’ …‘No, no,’ says the sociologist, ‘they have nothing to eat, nothing to wear, and they think that they are in paradise.

Mayer, 2013

Contemporarily, the stimulus for business to jump on the CSR bandwagon varies along a

continuum ranging from reactivity to proactivity mainstreams (Boomhill, 2007; Lindgreen &

Swaen, 2010). Likewise, Kurucz et al (2008, cited in Carroll & Shabana, 2010) have

articulated four generic impetuses of the business strategic case for CSR relative to ‘a) cost

and risk reduction; b) gaining competitive advantage; c) developing reputation and

legitimacy; d) seeking win-win outcomes through synergistic value creation.’ While it is wise

for a business to adopt a CSR approach, there is no concrete correlation between CSR and

corporate financial performance as such finding has not yet been conclusively established

(Bhattacharya & Sen, 2001; Pearce II & Doh, 2005; Smissen, 2012).

The three decade quest for the business case legitimate hinges on CSR direct link in boosting

the economic bottom line of the business (Carroll & Shabana, 2010). By contrast, Vogel’s

(2005) syncretic stewardship model for a consolidative framework is based on both direct

and indirect CSR-firm performance relationship. In this view, business can create value to its

stakeholders and capture that value in the form of an enduring and beneficial relationship

with their stakeholders and long term profitability (Freeman & Liedtka, 1997).

Substantively, stakeholder model can be thought of as the acid test of CSR for its application

validity. Outwardly, stakeholder stance is driven by a nexus of relationships envisaged the

interplay between business and diverse constituents, however its manifestation hinges on

the spelt out societal responsibility by identifying the interests of business’s key

stakeholders to integrate them into CSR strategies. Yet, the apparent strength of

stakeholder model might, at least in part, be its major weakness concerning the competing

needs and challenges for each cohort (Mostovicz et al, 2011). To help avert the threatened

conflict of these challenges, management should identify and balance the competing

interests of various stakeholders (Broomhill, 2007). In this regard, one of the key

stakeholder groups is the customer-stakeholder whose attitudes and responses towards

business conduct and behaviour can engender a vigorous criterion for the business’s

viability and profitability (Branco & Rodrigues, 2007; Isaksson, 2012).

2.3.1. CUSTOMER-STAKEHOLDER’S BEHAVIOURAL AND ATTITUDINAL DIMENSIONS AND CSR

Overwhelmingly, there is an extensive literature of CSR in the realm of management

dominated by the multifaceted debate on the feasibility of CSR to business. To illustrate, the

opening quotation marks how much the views of different premises can be contradictory.

As regards the foregoing CSR debate, it has only accommodated the views of both

contemporary economists and business practitioners alike with no regards to one justifiable

avenue pertaining to the quintessential role that customers play in the marketplace which,

arguably, can shed further light on the possible rationales of CSR benefits in terms of

customers’ perceptions of and attitudes towards socially responsible initiatives and

activities. Mulling CSR through the lens of marketing discipline can add another dimension

to the CSR frontier.

The marketing literature of CSR has emerged since the 1960s-1970s with a limited focus on

two streams namely, cause-related marketing (CRM) and environmental marketing

(Maignan & Ferrell, 2004; Beckmann, 2007). Prior research results are generally – though

not completely - supportive of the idea that there is positive association between CSR

behaviours and customers’ responses and attitudes (e.g. Brown & Dacin, 1997; Berens et al,

2007). However, research investigations of others such as Boulstridge & Carrigan (2000) and

Cardigan & Attalla (2001) cast doubt upon the link between CSR and customers’ behaviour

intentions or attitudes.

Most studies have focused on either limited customers’ attitudinal measures including

satisfaction, recommendation, loyalty, trust and the like or behavioural intentions relative

to repeat patronage, exclusive purchase, merchandise consumption, switch brands and

others (Maignan & Ferrell, 2004). These studies sought to answer important questions

raised regarding the customer’s likelihood of engaging in an evaluation of CSR and if so the

extent of it, moreover, the direct and indirect effects of CSR on the evaluation of both

company’s CSR actions and its specific product offering, customer’s purchase intensions,

his/her motivations to pick one brand with CSR attribute over the other and the effects of

CSR campaigns on their loyalty and purchase decision.

In essence, understanding customers’ reactions in the domain of CSR marketing research

strand is developed by three self-connected theories pertaining to ‘consumer inference

making, signalling theory and social identity theory. Customer inference making theory

implies that when customers form a purchase decision about a new product/service, they

may lack information about it. Whereas, they may know that this business incorporate a

social dimension into its behaviour and actions, hence, they may infer positively about the

product (Maignan & Ferrell, 2001). Congruent with this, McWilliams & Siegel (2001)

conclude that the likelihood of a business with ethical standards and norms to offer quality

products/services is high given its reliability attribute in its performance.

Signalling theory addresses the problem of information asymmetry that encounters

customers’ purchase decision making. For example, CSR attribute may act as a signal to

external parties about business’ attributes such as quality, genuine commitment, hence,

customer can distinguish between businesses with high attributes salience to those inferior

(Lech, 2013).

The last conceptual framework of social identity theory relates to customer's degree of

affinity with not just the corporation attributes but also the producing corporation. Hence,

they may identify with a business that enhances their self-esteem when buying from a

business that contributes to worthwhile cause. Building on this, the congruence between

customer characteristics and that of the business is likely to create both positive business’s

evaluation and positive recommendation about the business (Maignan & Ferrell, 2001). In

this context, Vershoor (1997, cited in Bouldstridge & Carrigan, 2000) claims that the

empirical finding of CSR’s influence on customer response demonstrated a positive

association resonated by 75% of customers switching brands to give their patronage to

businesses that behave as responsible citizen.

In effect, such business ethical contributions can have positive influence on customer’s

attitudes towards the business in the form of purchase intention as an ethical behaviour can

act as a transceiver of a differentiated strategy as well as a basis for trust, that is, it can

result in favourable evaluation of the business and in turn can create favourable attitude

towards its products (e.g. Brown & Dacin, 1997; Bhattacharya & Sen, 2001).

Furthermore, Choi & La (2013) suggest that cause-related marketing is allied with

philanthropic activities. In this context, it is argued that customers’ responses to

philanthropic initiatives are complex in which conditional donations elicit a negative

response whereas the unconditional scenario has positive influence on their responses

(Dean, 2003-2004, cited in Chomvilailuk & Butcher, 2010). The conditional donations incur

as a feature of a sales promotion. An illustrative example is the case of the American

Express card donated a penny on each use of the card while contributed a dollar for issuing

a new card. Just over four month, it collated two USD million as a donation and boosted its

market value by 28% (Sweeney, 2009).

In another sense, business can be effective into two different patterns of philanthropic

activities by maintaining a ‘low engagement’ pattern such as cash donations and/or a ‘high

commitment’ which addresses a collaboration approach to assist the efforts of external non-

profit organisations (Pearce II & Doh, 2005).

Moreover, a proactive CSR strategy can increase customer loyalty, as Maignan et al (1999,

cited in Maignan & Ferrell, 2001) claim, that is, business social values can directly influence

customers’ loyalty whereby their moral cognition works as a normative guideline that

affects their behaviour towards business (Roig et al,2013).

It is acknowledged that the sincerity of a company’s CSR motives can help building durable

relationships with customers which, in turn, empirically proved to influence directly

customers’ responses (e.g. Bernes et al, 2005); purchase intention (e.g. Klein & Dawar,

2004); customer satisfaction (Luo & Bhattacharya, 2006); product evaluation (e.g. Brown &

Dacin, 1997); overall evaluation of service quality (e.g. Salmones et al, 2005). Conversely, if

the motives behind pursuing CSR are perceived to be dubious and with ulterior endeavours,

in turn, this may leave the company with negative evaluations and run the risk of consumer

backlash (Mittal, 2008).

Another avenue in the research strand of CSR marketing relates to investigating customers’

responses to a multiple CSR domains. Prior research suggests that combined CSR program of

community involvement, cause-related marketing and environmental concerns influenced

customers’ overall company evaluation (e.g. Brown & Dacin, 1997). Consistent with this, are

the findings of Murray & Vogel (1997, cited in McDonald & Thiele, 2008) research in which a

battery of CSR activities such as socially responsible workplace, worthy causes and

consumer protection resulted in positive responses ranging from pro-employee attitudes to

customers’ improved attitudes.

Despite that potential findings from such research strand can provide sophisticated

attributional reasoning which can reduce the likelihood of falling prey to the critics of

investigating a single domain of CSR which belies the nature of its broad spectrum, there is

scant research in the extant studies. Thus, some academics call for more studies into this

research stream (e.g. Maignan & Ferrell, 2004).

Taken together these studies presumptions and empirical implications, the argument put

forward is that CSR is likely to influence customers attitude in which a multiple CSR domain

is deployed using Carroll’s CSR model.

2.3.2. CSR AND CR

To gain a good reputation, endeavour to be what you desire to appear.

Socrates, long time ago!

In analogy with the study of CSR, the CR has an array of definitions addressing different

disciplines which results in myriad dimensions that are meant to capture its analytical

framework (Caruana, 2008). In the light of the daunting challenges arising from the thorny

issues of the globalising knowledge economy era and from the mounting public scrutiny,

firms have become cognizant of the importance of building and nurturing a good business

reputation that signifies its ability to deliver valued outcomes to its stakeholders (Fombrun

& Shanley, 1990). In their review, Bennett & Kottasz (2000, cited in Trotta et al, 2011)

suggest that CR is best defined as the integration of stakeholders’ perceptions and

expectations and personal opinions that developed over time about a business know-how

and capacity to fulfil stakeholders’ interests. In this view, stakeholder’s future expectation is

likely to be articulated by his/her past perceptions of business behaviour.

Accordingly, CR implies on one hand conveying cues of business’s differentiated strategy

and the intrinsic values of its products CR to the stakeholder groups (Gatti et al, 2012), on

the other hand its multidimensional perspectives articulated upon the different perceptions

of each stakeholders group investigated (Trotta et al, 2011).

Underlying these vantage points are the similarities and differences between CSR and CR. it

can be well argued that both concepts are cultivated within corporate behaviour

investigations and stakeholder model. Arguably, if unattached to stakeholders and not

heeded to their interests, both concepts would be seen as merely abstract concepts (Trotta

et al, 2011). With reference to the differences, it is acknowledged in some studies that CR is

of multidimensional nature while CSR has a descriptive-objective nature (Trotta et al, 2011),

thereof, their complementary interaction constitute value attributable to characterising

business intangible responsibilities and hence accommodating efficient strategies to

respond to these responsibilities, ultimately, in turn capture these opportunities into

intangible assets alongside its physical ones.

Emerging from this remark is that strengthening business’s social bonds with stakeholders

can be considered a form of reputation building and maintenance which in turn undergirds a

competitive advantage in the market place (e.g. McWilliams et al, 2006; Peloza & Shang,

2011) and ultimately reaps long-term prosperity and viability of the business especially in

the turbulent business environment of today.

Subsequently, one instrumental that has widespread application for many companies

seeking to bolster their reputations is the surge up of reputation index ranking of accredited

institutions such as Reputation Institute, Fortune index of CR and Britain’s ‘Most Admired’

Companies wherein amid the rated criteria is quality of management as well as community

and environmental performance (Boulstridge & Carrigan, 2000; Peters, 2007). In one sense,

business uses these tools to heighten business accountability and constructively influence

its social behaviour. In another sense, it uses them to communicate its social commitment

and the different facets it is engage in to convey to stakeholders its coalescence with its

society to promote society well-being (Peters, 2007).

The eminence of businesses’ reputation for deploying socially responsible practices and

social attributes to their offering can enhance business financial posture through cost

reduction that accrues from customer satisfaction and productivity of employees (Isaksson,

2012). In turn, such positive outcomes accumulate a stock of a firm’s reputational capital. In

other words, if CR is not maintained negative outcomes incur translated into impoverished

revenues, the volatility of CR is touted as reputational capital which constitute business

intangible assets. Under this reasoning, Accenture - a global consulting firm – draws

attention to the upsurge in businesses’ intangibles from 38 per cent of total business value

in 1982 to 84 per cent in 1999 (Bouvain et al, 2013).

Furthermore, a reactive CSR strategy, as Broomhill (2007) claims, embodies the adoption of

socially responsible manner in business’s decisions to alleviate negative reputation and

potentially regain legitimacy. By doing good, arguably, business can mitigate the risk of

reputational losses which if not wisely treated can rigorously damage the consumers’

confidence and trust in business (Boulstridge & Carrigan, 2000) and even worse by having a

negative effect on generalised trust (Cruijsen et al, 2013).

This could be, at least in part, because it takes decades to build up a reputation, however, it

can be ruined in a split second by incidents such as the corruption scandals or the

environmental accidents, hence, causing a bottom line backlash for these businesses.

Moreover, Park et al (2014) claim that there is a direct positive link between economic and

legal CSR and CR, though an indirect impact of ethical, philanthropic CSR on CR was found in

which customer trust fully mediated this relationship. Regarding economic CSR and CR, the

product safety and its quality have a positive impact on CR, whereby the wrongdoings of

some companies for their illegal acts lead to a tarnished CR and to public resentments. With

respect to the latter two CSR activities, the logic behind this is that the perception of the

sincerity and trust surrounding CSR motives are the factors of creating positive corporate

evaluation.

2.3.3. THE MEDIATION EFFECT OF CSR

From the aforementioned review, the argument put forward is that CSR can influence the

relationship between CR and customer behavioural intentions. As such, CR can have an

impact on customer behavioural intentions through the effect of CSR. In this regard, many

authors pinpoint a positive association between CSR reputation and customers’ responses.

It is worth noting that reputation is likely to lead to customer engaging in positive word of

mouth, emotional attachment to the store and repeat patronage (e.g. Lichtenstein et al,

2004, cited in Chomvilailuk, & Butcher, 2010).

As alluded to in the foregoing sections, the prevailing assumptions insofar yield customers’

support to and favouring of social responsible businesses. The well-documented CSR effects

on customers’ responses and behaviour spring from the ensemble of CSR social attributes

that inculcate customers’ confidence and trust into business which go hand in hand with

bolstering its reputation as a social responsible business. Drawing from this, it could be said

that CSR activities mediate the relationship between CR and customer behaviour intentions

which this study tends to investigate.

2.4. CONCLUSION

This chapter is articulated around the multifaceted debate on CSR justifications either on

shareholder or stakeholder grounds. Martin et al (2009) bluntly pronounced the state of

affairs surrounding the debate on CSR as ‘both would argue, vehemently, at times that it is

an either-or proposition: if I am wrong, then you must be wrong.’ Metaphorically, the

shareholder and stakeholder could be seen as the unattuned strings of a violin. Hence, the

composed CSR mantra is one of dissonant as the violin’s bow sometimes hits only the

shareholder string to reflect the domination of the neoclassical economists view; another

time it would only hit the stakeholder’s one. Thus, the tune composed is missing a sharp

stroke to create a well-tuned mantra – the rationale behind justifying the adaptation of CSR.

To gain a dynamic articulation of this mantra, there is a need to calibrate the two strings

into a vibrant theme that strikes the listeners – the business’s constituent groups including

the shareholders cohort.

Hence, to unveil whether the presumption of an untuned theme is the status quo or the

current CSR activities have been tuned after the FC of 2007 to meet its stakeholder’s needs

and expectations, the research will seek the voice of customer-stakeholders. Set against this

outlook is the research question:

Has the FC been a wake-up call for CSR activities to resonate with customer-stakeholder

expectations to create a sustainable business?

Chapter 3: Methodology

3.1. INTRODUCTION

This chapter is built upon the pillars of formulating a coherent research design. It sheds light

on the adopted philosophical stance concerning the nature of the research enquiry which is

dovetailed with the formation of the research methodological choice and related strategy

(or strategies). That is, it implies the rationale behind the chosen methodology, the verified

research approach and data collection techniques that are developed to answer the

research question with reliable results and to fulfil its objectives. Finally, the data analysis

techniques are outlined.

3.2. RESEARCH PHILOSOPHY

The definition of a “research process” – a systematic way of collating and construing

information to generate or increase our knowledge in a rigorous analytical way to provide

valid and reliable findings – had a profound influence on the constitution of the three

phases, illustrated in Figure 2, that were used to help achieve the objectives of the research

(Saunders et al, 2012). To leverage a coherent research process, the two latter phases –

execution and analytical – were informed and guided by the development of the research

question and objectives in the formulation phase – Introduction and Literature Review.

To address this, the formulation phase provided the theoretical framework for the proposed

hypotheses that aimed at answering the research question. Embedded within this

framework is the philosophical perspective which maintains the study worldview about the

nature of what we seek to know and the process by which acceptable knowledge is

developed. Thereof, the research philosophy constitutes the assumptions that relate these

theoretical ideas to the real world (Figure 3) through two lenses relative to the issues of

what is the nature of the social entity to be researched (ontology) and how can (or should)

we develop our knowledge in this discipline (epistemology) (Creswell, 2003; Bryman & Bell,

2011).

(Adapted from Hair et al, 2007)

Figure 2 – Research Process

3.2.1. ONTOLOGY: THE NATURE OF REALITY

Ontology comprises the substantial precepts for every research blueprint which is anchored

in our beliefs about the nature of reality and the constituents of the object of investigation.

The ontological assumptions are related to what is out there to know about the social

entities. To this regard, the central point of orientation stems from whether these social

entities can or should be regarded as objective entities that have a reality independent of

the social actors or whether they can or should be constructed by them (Bryman & Bell,

2011; Camilleri, 2012). These contrasting views are respectively referred to as objectivism

and constructionism (or subjectivism) (Porta & Keating, 2008) which portray opposite ends

of continuum’s polar to which researcher embarks upon one end that would enhance the

understanding and the justification of the research strategy and data collection techniques.

While researchers who adopt the objectivist approach hold the view that social phenomena

is independent of their perceptions of it, the subjective stance views reality as being socially

constructed for which individuals develop subjective meanings of their own experiences and

backgrounds. As such, these meanings are formed through active involvement of people in

Figure 3 –

(Lee & Lings, 2008)

reality construction and through historical and cultural norms of the context (Creswell,

2003) which result in multiple perspectives of an event by virtue of the different

interpretations being engendered.

3.2.2. EPISTEMOLOGY: HOW WE JUSTIFY OUR KNOWLEDGE OF THAT REALITY

The ontological stance entails the point of departure from which the core assumptions

concerning epistemology initiated (Lee & Lings, 2008). In this context, epistemology is

concerned with the relationship between the researcher and reality. Ultimately, it underlies

the nature of knowledge, the most appropriate ways of pursuing, acquiring and/or creating

that knowledge as well as the limits of knowledge (Porta & Keating, 2008; Camilleri, 2012).

Notably, given the propositional claim of this knowledge, it needs to rest on a body of

evidence (induction) or a reliable theory (deduction) to promote valid and well-

substantiated findings, thus this knowledge can be well justified (Lee & Lings, 2008).

The underlying epistemological assumption draws on how one comes to know reality

(Camilleri, 2012). In turn, it informs the choice of research methods ranging from the

quantitative and statistical techniques, the qualitative research methods to mixed-methods

research design.

3.2.3. RESEARCH PARADIGM

At a broad level, the epistemological considerations render into the research work plan of

how to go about generating this knowledge, that is, these processes that govern the

methods by which research is carried out form the research methodology. Building on this,

what Lee & Lings (2008) term as the ‘ologies’, which are derived from research ontology,

epistemology and methodology, embody an ‘interpretive framework’, as Denzin & Lincoln

(2000, cited in Le Roux, 2012) purport. This framework forms the so-called research

paradigm; in effect these ologies directly or indirectly outline the research paradigms. More

interestingly, the word paradigm – origin Greek paradeigma – symbolises a pattern. In this

view, research paradigm is a pattern of scientific and academic ideas, key issues,

assumptions and data collection methods.

The most prevalent paradigms embody a long standing tension about whether the social

world should be studied according to the application of the methods of the natural sciences.

Advocates of the natural science’s ethos to the study of social reality cultivate the precepts

of positivist research paradigm. On the other end of the spectrum is the interpretivist

research paradigm denoting an alternative to the positivist orthodoxy which is based on an

understanding of human behaviour and subjective meaning of social action through the

eyes of different participants (Camilleri, 2012).

3.2.3.1. POSITIVISM

The tenets of the positivist stance emanate from the philosophical ideas of the French

Philosopher August Comte (1798-1857, cited in Neuman, 2006) which implies that valid

knowledge (truth) exists, is already there waiting to be revealed, and is independent of the

human mind. Hence, the researcher’s task is to uncover truth using quantitative and

statistical methods. At the ontological level, philosophical positivism is articulated around

facts that exist objectively which are directly observable and measurable (e.g. Walsham

1995; Blumberg et al 2008). Positivistic thinkers emphasise the verifiability of theories

through empirical testing of deduced hypotheses which are only considered meaningful if

they are empirically verified, thereof this leads to the discovery of universal laws of human

behaviour (Lee & Lings, 2008; Bryman & Bell, 2011).

The positivist social science takes the stance that knowledge is acquirable and

methodologically naturalistic to systematise the knowledge generation process with the

help of rigorous measures and careful collection of data to explain cause-and-effect

relationships and predict general patterns of human activity (Neuman, 2006). However, the

detached epistemological stance of the positivism and reducing the world to observable

objects and facts, in the view of critics, are not very justified. Critics attribute this to the

establishment of superficial correlation of the observable elements with no regard to the

unobservable mechanisms that underlie institutional forms and practices. Opponents of

positivism also reject the application and interpretation of science to the study of social

reality (Alvesson, 2009; Camilleri, 2012).

Notwithstanding, proponents of positivism assert that observing external reality is

prominent than developing subjective meanings of the social actions in terms of providing

adequate explanations of human thought and action which is the manifestation of direct

observation of realities and regularities (Camilleri, 2012). Positivists hold the view that

reality is patterned and has order, however, if it is bypassed, or if there is no regularity in

social reality, a rational logic of decision making and prediction would be impossible.

3.2.3.2. INTERPRETIVISM

Another intellectual tradition contrasting the epistemology of positivism is interpretivism

which holds that social life is underpinned by social interactions and socially constructed

meanings stem from people’s subjective experiences. Given the complexity of the

contemporary social world, the focus of this tradition is to develop inferential generalisation

to capture insights of this complex world rather than reducing this world into a series of law-

like generations of the positivist stance. In this sense, a qualitative analysis (versus

quantifiable) is employed in the domain of interpretive research whereby meaning-oriented

methodologies such as ethnography and in-depth interviews are highly contextual

(Saunders et al, 2012). As such, the nature of the interpretive methodology and the context-

specific orientation make generalizability – which is concerned with the results of the

undertaken research being transferrable to other situations – far more difficult. Hence,

these results cannot be widely generalisable instead they generate local understanding (Lee

& Lings, 2008; Camilleri, 2012).

Owing to the ontology’s tendency towards exploring reality through meaningful actions, this

results in forming multiple realities whereby there is no single correct route to knowledge

(Alvesson, 2009).

3.2.3.3. RATIONALE BEHIND CHOSEN PARADIGM

Emerging from the preceding remarks of the two paradigms, the framework of this study

adopted the positivism tradition. The crux of this reasoning lies in some propositions shaped

in the multifaceted debate on CSR that gripped the banking sector with regards to its

ascribed role in the post FC of 2007. Also, this study is set out to capture the social reality

pertaining to the CSR streams that gauge customer-stakeholders’ attitudes towards CSR that

symbolises its development to meet their demands. In line with this reasoning, the

positivism philosophy maintains that there is one reality that is observable and meaningful

based on a proper treatment of empirical data which is not the case with interpreivism

(Holden & Lynch, 2004). Given this, adopting a positivistic stance is consistent with the

study’s aim to find out a consensus on CSR activities that is likely to address customers’

demands and provide means for business sustainability.

Moreover, the application of scientific methods to create generalisable knowledge

stemming from the causal analysis of the operationalised concepts that constitute the

research variables resembles the study aim. This approach would equip the study with

rigorous analytical methods to investigate whether the shareholder-stakeholder debate is

pseudo or there is a real issue in this discipline which if confirmed would provide legitimate

grounds for the next implications of adhering to the positivist stance. In this context, the

causal analysis can help in promoting a management agenda by gaining insights into the

causes and effects of the research variables to inflict reflective decisions.

3.3. RESEARCH DESIGN

If we knew what it was we were doing, it would not be called research, would it?

Albert Einstein

In light of Einstein quotation, a crucial tool in the social researcher’s armoury is the research

design which is regarded as the ‘recipe for carrying out the project’ as Hair et al (2007)

pinpoints. From the outset, the researcher needs to devise a coherent research strategy

which is guided by the researcher’s adopted philosophy, research approach (relationship to

theory), the nature of research and access to data.

3.3.1. RESEARCH APPROACHES: DEDUCTIVE, INDUCTIVE AND ABDUCTIVE - FROM REASON TO RESEARCH

The ‘research approach’ indicates how data can be collected by delineating the relationship

between theory and research. There are three different approaches based upon the

reasoning adopted through the research paradigm: deductive, inductive and abductive

(Table 1).

With regards to deductive approach, the emphasis is on the development of a theory for

which an empirical scrutiny is deployed to test a hypothesis(ses) (Bryman & Bell, 2012;

Saunders et al, 2012). These hypotheses will need to be translated into operational terms

(Bryman & Bell, 2012) in the form of independent variables that can be active – variables

that the researcher can manipulate – or attribute – in contrast with the active ones as they

relate to gender, race and the like (Newman & Benz, 1998).

The point is that the independent variables are the measurable characteristics which cause

effects on the dependent variables. Hence, these measured concepts can be formed into

Table 1 – Research Approaches: Deduction, Induction, Abduction

(Saunders et al, 2012)

quantifiable data collected through quantitative instruments such as a survey questionnaire.

As such, after the rigorous evaluation – based on testing the reliability and validity – of the

measures of concepts, the hypotheses can then be tested using an appropriate statistical

technique and will only be accepted if they survive the ordeal (Sohail et al, 2008).

This scientific approach is called a hypothetico-deductive (deductive-empirical) method in

which the aim is theory testing. Hence, it is contrasted with the other two approaches:

inductive and abductive (Hair et al, 2007). The notion hypothetico-deductive first emerged

from the perceptions of philosopher Karl Popper (1959, cited in Juma'h, 2006) which rely on

the logic of testing falsifiable hypotheses for which the scientific approach is driven by

systemising the search for conflicting information. The falsification principle contrasts the

empirical verification in which hypotheses are either verified or refuted by the observed

effects. The last characteristic of deductive reasoning is the embedded causal explanation

that incorporates a sufficient level of generalisation to apply findings of the research study

to other settings (Camilleri, 2012; Saunders et al, 2012).

With inductive reasoning, the outcome is the formulation of a theory which entails

generating inferences out of observations. By its very nature, inductive research employs

qualitative methods and often uses a grounded theory approach to the analysis of data and

to the generation of theory (Porta & Keating, 2008; Saunders et al, 2012). On the other

hand, the abductive stance involves weaving back and forth between data and theory. In

effect, it leverages a complementary approach which entails a process that iterates between

deduction and induction (Hair et al, 2007).

3.3.2. FIXED AND FLEXIBLE ORIENTATIONS TOWARD RESEARCH DESIGN

Research designs are mapped based on distinguishing between two salient typologies –

fixed and flexible. One of the differences between them comes from the degree of pre-

specification of procedures that characterises the requirements for the most suitable design

to be employed such as the use of pilot testing in the quantitative approach. Another

difference is the nature of the data. The former – fixed – is characterised by data collection

techniques and analysis procedures that generate or use numerical (hard) data, thus

researchers deploy the positivism paradigm. Conversely, the latter design collects

qualitative (soft) data in the form of words, impressions and so forth which means that

social researchers rely on interpretive paradigm (Robson, 2011).

Quantitative research is most likely constructed using a deductive approach whereby the

focus is on collecting data to test theory. Hence, the strength of its implication capitalises on

three factors – concepts’ measurement, causality and generalisation. Measurement involves

the consistency of the research results and assesses whether the indicators devised to

gauge the concepts – the building blocks of theory that can be observed and measured to

explain variations when testing hypotheses – really do reflect those concepts. These sketch

respectively the research reliability and validity (Bryman & Bell, 2012).

With regards to causality, its importance is driven by the researcher’s ability to impute it in

their findings. In terms of quantitative research, the daunting challenge is to explain the

causal relationships that are responsible for some phenomena by identifying the possible

correlation between its dependent and independent variables. Moreover, this causal

explanation strives for generalising findings from a sample to a wider population. Given this,

the sample has to be as representative as possible in order to be applicable to other settings

(Hair et al, 2007; Tam, 2007).

In contrast is its qualitative counterpart whereby data gathered is not statistically

representative. Hence, researchers confine themselves to providing contextual

generalisations or making theoretical generalisations that are concerned with the empathic

understanding of human actions rather than with the explanation of these actions as in the

case of quantitative research. In this framework, qualitative research design is associated

with inductive approach for which limited or no prior specification of variables of interest is

required (Creswell, 2003; Bryman & Bell, 2012). Moreover, flexible can coincide with mixed

method which is not within this study scope.

3.3.3. RESEARCH STRATEGY

Drawing on the fixed and flexible research design typologies as sketched by Robson (2011),

the fixed designs can constitute experimental and non-experimental strategies. The typical

form of the experimental strategy owes its nature to the quantitative research design that

implies manipulating the independent variable to assess its influence on the dependent

variable whereby the researcher conducts quantitative comparisons between control and

experimental groups with regards to the dependent variable.

On the other hand, the non-experimental strategy for the fixed research design includes

survey study and secondary data collection methods. With reference to flexible design, it is

carried out by one of the following approaches: case study – which could be conducted

using qualitative, quantitative or mixed as Robson (2011) argues – whereas the remaining

strategies embody only qualitative data collection such as ethnography, interview study and

discourse analysis.

Guided by the adopted positivistic stance, a fixed survey study was used. In light of the

deductive approach of this research, the generalisability property of the quantitative survey

study, its causal analysis and condensed data fit its descriptive and explanatory nature.

Descriptive Research is designed to provide an accurate profile of what has been observed.

The outcome is a detailed sketch that can be an extension of exploratory research or, more

likely, a piece of explanatory research. Accordingly, this social research focuses on questions

as how, who, when and where to present a snapshot of events over time – longitudinal

studies – or situations at a given time – cross-sectional results. It can be a forerunner to

explanatory studies. Such studies are so-called descripto-explanatory (Saunders et al, 2012).

With reference to explanatory research, the primary purpose is to seek explanation of how

and why events occurred; thereof it strives to establish cause-and-effect relationships

(Saunders et al, 2012).

Building on this, the nature of this research subscribes to a descripto-explanatory stance.

Given the multidimensional nature of the CSR paradigm, the rationale behind conducting a

descriptive study is to obtain data that identifies and describes the characteristics of

multiple CSR domains relevant to the level of importance concerning CSR activities to

customer-stakeholders.

Moreover, at the heart of this research lies a systematic quest to reveal enlightening

insights by explaining the likelihood of a bundling of CSR activities that can influence

customers’ attitudes and behaviours as well as the possibility of CSR to affect the reputation

of the business.

3.3.4. THE DATA COLLECTION PHASE –SURVEY QUESTIONNAIRE

Questionnaire instrument is the most widely used data gathering technique within the

survey strategy. It is perceived to be used as an interactive method of sourcing primary data

(Lee & Lings, 2008; Saunders et al, 2012) that represents a snapshot of a situation at a single

point in time – cross-sectional study – or that is captured over a longer period time at a

number of points in time (Creswell, 2003; Hair et al, 2007).

Respondents are asked to respond to a consistent set of clear and unambiguous statements

or questions that might comprise open-ended questions in which respondents provide their

own answers and/or standardised, also referred to as close-ended, questions in which

predetermined mutually exclusive and exhaustive responses are formed (Babbie, 2004; Hair

et al,2007; Saunders et al, 2012).

Framing relevant questions convey a set of interrelated activities that must be considered to

develop an efficient and well-structured survey. In this sense, a good design of these

questions, a logical flow in the structure of a questionnaire, an appropriate method by

which the questionnaire is administrated and a rigour of its pilot testing would foster an

adequate reliability of the data collected and acceptable or even sometimes significant

response rates (Hair et al,2007; Saunders et al, 2012).

With reference to the methods of administration to sample, there are wide-ranging means

with which a questionnaire can be delivered, returned or collected. This is exemplified in

using self-administrated (or completion) methods which include postal and electronic

surveys whereby they are completed without a researcher present. Hence, this type of

survey requires a highly structured questionnaire with an easy-to-follow design and a clear

presentation with spreading out questions in the questionnaire to be sufficiently appealing

that participants actually complete and return it, potentially increasing the response rate

(Bryman & Bell, 2012). Saunders et al (2012) point out that a feasible length of

questionnaire should be between six to eight A4 pages for postal survey or the equivalent of

them for the online. A covering letter should accompany the questionnaire introducing it

and its content along with ethical commitment. This implies avoiding confusion and

vagueness of the research purpose as well as building up trust and confidence to induce

respondents to complete it.

Self-administrated questionnaires are especially advantageous over structured interviews

for being cheap and quicker to administer, more convenient to respondents in terms of the

time and speed of completing them and, most importantly, eliminating the social

desirability bias due to the absence of an interviewer. However, this type of questionnaire

has some drawbacks such as that it can be read as a whole without control over the

sequence in answering the questions; it could suffer from a low response rate and greater

risk of missing data (Sweeney, 2009; Bryman & Bell, 2012).

To elicit the benefits from using a self-administrated questionnaire whilst overcoming and

minimising its pitfalls, the survey devised for the research in question took the format of a

self-completion questionnaire that was administrated via the Internet using the Survey

Monkey software. Notably, the internet is having a substantial impact upon research within

which the use of web-delivered surveys is growing for a multitude of reasons that include

quick and direct form of access to sample, the economical collection of large amounts of

data, the moderate response or return rate compared to lower rates associated with postal

questionnaires, and its technical features that help spreading out questions over a number

of pages, having questions answered in a sequence and help avert the risk of missing data

by not progressing through before answering all questions on each page (Babbie, 2004;

Neuman, 2006; Barton, 2010).

3.3.4.1. THE QUESTIONNAIRE’S LAYOUT AND CONTENT

To operationalise the ‘Total Design Method’ purported by Dillman (1978, cited in Babbie,

2004), the preceding considerations were taken into account to exhort valid findings

confined by the specifications of the quantitative scientific research e.g. being logical,

objective, value-free and empirical verification. Drawing on these insights, the web-based

questionnaire was disclosed with a clear unbiased title, followed by an introductory

covering letter tapping on the aim of the study, the structure of the questionnaire,

instructions of how to complete it and an explanation of CSR terminology accompanied by

real-life examples to illustrate the responsibilities in order to make it easier for the

respondents to relate to the questions and statements and, at the end, a thank you note for

their valuable participation.

The questionnaire had a clear layout and care was taken to avoid leading questions, double-

barrelled statements and unbalanced responses. By using the features of the Survey

Monkey software, the survey was programmed so that respondents could not proceed to a

new page before answering all questions on a given page which is used to control missing

data. Another feature was used to lock the questionnaire so that at completion it would not

be done twice by the same IP address.

The survey comprised four sections over five pages and consists of 23 close-ended

questions. The justifications for that over open-ended questions are that less time is needed

for answering them which justifies the twenty minutes estimated for its completion in the

introduction, maintaining uniformity in the data gathering process and making it easier to

compare the answers of different respondents whereas open-ended questions are most

suited to exploratory research whereby little or nothing is known (Appendix C).

In section A, eight list questions (e.g. tick the appropriate box) requested background

information concerning age, education and so forth. These questions are of a factual nature

for which a single variable is used in each question to collect socio-demographic

characteristics about the sample. Even though it is preferable to have this section at the end

of the questionnaire so that the participant does not break off early, it was placed at the

beginning because one of its subset questions is designed as a filtering question to

circumscribe progressing into the questionnaire if the participant does not have a UK

account.

Section B consisted of ten questions that canvassed customer-stakeholders’ satisfaction of

perceived CSR following the FC of 2007. The participants were asked to respond using a

five-point Likert scale to a range of questions, some of which were constructed into a matrix

format for subscale questions.

The Likert rating scale was used to assess the strength of agreement or disagreement about

their banks adhering to four dimensions of CSR activities adapted from Carroll’s CSR

framework which deal with economic, ethical, legal and philanthropic dimensions in the

post FC of 2007. A five-point Likert scale ranging from 1 (Strongly disagree) to 5 (Strongly

agree) was used. Using the same five-point scale, respondents were also asked to indicate

their level of agreement or disagreement with each statement relevant to their trust into

their banks after 2007. They were requested to divulge their level of expectations of the

bank sector aligning with their demands and needs after 2007 by interpreting the Likert five-

point interval scale – 1 (Substantially below expectations) to 5 (Substantially exceed

expectations).

Since the sequence of the questions have a major influence on the accuracy of the collected

data, the logical flow of questions geared to capture respondents’ perceptions of their bank

CSR activities first and then their overall perceptions of the bank sector. This sought to get

their brain primed for the more salient questions gauging their satisfaction of the banking

sector.

Section C delved into the level of importance of Carroll’s CSR four dimensions to influence

their purchase decision of bank’s financial products in which the five-point Likert scale is

coded from 1 (Not at all important) to 5 (Very important). Finally, Section D catered to

capturing the level of agreement-disagreement with statements gauging the effect of

engaging into CSR activities on bank’s CR.

The statements and variables in the research instrument are derived from and built upon

the analysis of secondary sources constitute of literature that are based on a number of

critical theoretical threads presented in Chapter 2 and other items from earlier

questionnaires that were culled or adapted to reflect the objectives of the current study.

Question 9 was partly derived from Choi & La (2013). Question 14 was adapted from Mulki

& Jaramillo (2011). Question 21 was adapted from Ellen et al (2006) and Osterhus (1997).

Incorporating items from previous research allowed reliability and validity in the sense that

these questions have already been pilot-tested; hence, they are empirically founded

(Barton, 2010; Bryman & Bell, 2012).

3.3.4.2. PRETESTING AND PILOTING THE SURVEY

Questionnaires do not emerge fully-fledged; they have to be created or adapted, fashioned and developed to maturity after many test flights. In fact, every aspect of a survey has to be tried out beforehand to make sure that it works as intended

Oppenheum, 1999 cited in Sweeney, 2009:130

Guided by the ‘Total Design Method’ of Dillman’s (1978) proposition and the insights of

Oppenheum to ensure that the research instrument as a whole functions well and evaluate

its feasibility, the developed questionnaire should be pilot-tested prior to administrating the

final survey study to the sample. This evaluation is in the form of a small scale replica of the

actual survey to be carried out to reveal issues related to wording, sequencing, questions

duplication, the adequacy of the range of responses to each question and any weaknesses in

the design. As this would suggest, calibrating the questionnaire draft in accordance to these

revealed insights will help enhancing the validity of the questions and the reliability of the

data that will be collected. It will also acquaint the researcher with an indication of the

response rate to be expected of the final study (Sweeney, 2009; Barton, 2010).

The first draft of the questionnaire was presented to the research supervisor and then pre-

tested among academics and professionals. The feedback received reported duplication in

some questions and some wording errors. Hence, the draft of 26 questions was refined to

23 questions and some examples of CSR activities in the banking sectors were given for

more clarity. The survey was redrafted and then tested with a sample of ten respondents of

bank customer-stakeholders. The number of ten participants in the pilot is acceptable which

is in line with the recommendation of Saunders et al (2012) as a minimum number to

conduct a pilot for most questionnaires.

Each participant received an email informing them that the questionnaire for which a link

was attached was for a pilot study and they were encouraged to provide their feedback on

irrelevant questions, inappropriate flow of the questions, technical jargon or ambiguous

scale items.

Concerns over the usage of American terms for describing the types of bank accounts were

voiced during the second stage and also the pilot indicated a low response to few

statements that needed to be associated with examples of these CSR activities in the

banking sector. Accordingly, typographical changes were made and these statements with

low response contained an example related to these CSR undertaken in the banking sector.

These recommendations were incorporated into the survey before the final administration

of the survey.

3.3.4.3. THE SURVEY ADMINISTRATION AND RESPONSE RATE

After adjusting the second draft of the questionnaire following the pilot study, the survey

was fielded from the 14th of July until 12th of August 2014 and included two reminders. An

invitation email including the URL link was sent to respondents who can click-thru

sequences on Survey Monkey web site to complete the questionnaire online (Appendix A).

The email was sent to all 200 email addresses on the researcher’s list. Within the first five

days 38 responses were collected. Using a feature of the Survey Monkey software, the non-

respondents were located. Thereof, the first follow-up email was sent after six days to all

recipients. It included a thank you note to early respondents and the located non-

respondents received a reminder to answer with a copy of the link.

The first reminder produced only 26 additional responses (Appendix B1). Therefore, ten

days later, a final reminder was sent with the closing date for the survey to highlight the

urgency of completing it (Appendix B2). This resulted in a further 62 responses and the

questionnaire was closed at midnight on 12th August.

Guided by the techniques used during the data collection – analysed and synthesised in the

methodology literature, sufficient response rate for the research in question was achieved

whereby 127 questionnaires were returned thus yielded an initial response rate of 63%. Of

these, 4 questionnaires were disqualified by using the filter criteria for allowing only

respondents who currently have UK account to progress. In addition, 31 questionnaires

were excluded from analysis as they were only partially completed. Although the survey was

programmed for not advancing to the next page if a question is skipped, the 31

uncompleted questionnaires were incurred by exiting the website of the survey. The final

response rate is 46% for the 92 usable questionnaires that were accepted as valid for the

data analysis.

3.3.5. SAMPLING METHOD

The setting for this empirical study was the UK banking industry given its vital role to the

development of the country’s economy based stemming from its part in bridging surpluses

and deficits in the economy. Within this context, the study population and sample elements

were drawn.

Sampling constitutes a key step in the social research process. It is the method by which

specific cases or events are selected for participation in a study whereby the gist of it is to

estimate some unknown characteristics of the population (Zhowa, 2010). As its name

implies, a sample is a segment of the population that a researcher selects to arrive at a

conclusion regarding the whole population (Bryman & Bell, 2012). Accordingly, a population

or universe is that aggregation of the units in a study which have some homogeneous

characteristics that may influence the variables of interest (Lee & Lings, 2008; Zhowa, 2010).

The method of selection was articulated by one of two approaches namely: probability and

non-probability methods. With probability sampling (or representative sampling), some

random-selection mechanisms are employed in which the chance of each unit being

selected from the population is known, thus each case has an equal possibility of being

selected. Consequently, a probability sample is considered representative of the population

from which it is drawn (Babbie, 2004; Neuman, 2006; Han, 2006; Bryman & Bell, 2011). The

aim of recruiting this technique is to keep sampling error to a minimum. This error refers to

the degree of deviation between a sample and its population (Neuman, 2006).

Garnering a representative sample is based on five sufficient steps as presented in Figure 4.

A target population embodies the specific pool of sampling units that the researcher aspires

to generalise the results of. Obtaining a sampling frame is essential for providing a working

definition of the target population as it encompasses all units in the population from which

the sample will be drawn (Saunders et al, 2012). Another critical factor in creating a

representative sample is contingent on its size. In essence, the larger the size of the sample,

the higher the likelihood of the precision and accuracy of data collection from it because

that is more likely to reduce error in generalising to the population. Moreover, the type of

Figure 4 – The Process of Probability

Defining the target population

Choosing the sampling frame

Determining the sample size

Selecting the most appropriate

sampling technique

Checking that the sample is

representative of the population

(Saunders et al, 2012)

analysis that is intended to be used will determine the threshold of the sample size. Another

two constrains that can affect the choice of the sample size are the amount of time and cost

that are needed to collect, check and analyse the data (Bryman & Bell, 2012, Saunders et al,

2012).

Probability sampling techniques include simple random, systematic random, stratified

random and cluster sampling. The choice between these techniques depends on which is

most appropriate to answer the research question and address its objectives. The first

technique entails randomly selecting the sample elements from the list of all units of the

population. A slight modification is systematic sampling, where every Kth (e.g. 15th) unit in

the sampling frame is selected at regular intervals (Babbie, 2004; Hair et al, 2007).

With stratified random sampling, the sampling frame is divided into relevant strata –

relatively homogenous subgroups – and then randomly or systematically sampling within

these strata. Thus, each of the strata is represented proportionally to accurately mirror the

population (Hair et al, 2007). As for cluster sampling, it involves breaking the population into

discrete groups (clusters) and then samples are drawn from the aggregated units or clusters.

In this criterion, the sampling frame comprises a complete list of clusters rather than

individual cases (Neuman, 2006; Hair et al, 2007).

The fundamental idea behind employing probability sampling techniques is that it is more

likely to yield a representative sample that allows for drawing a statistical generalisation

from it to its population. To achieve a perfect representative sample, a sampling frame of all

units must be available which can hardly ever be achieved for some research inquiries. In

addition, it is considerably more expensive and time-consuming which does not fit with

limited research sources. However, there are other ways that could be considered to

evaluate the worth of a good sample strategy such as sample size, the level of response rate

and the construction of the instrument questions (Lee & Lings, 2008).

Constructing scientifically sound samples can be constituted by using non-probability

sampling methods which address those challenges of employing a probability sampling in

terms of safeguarding the use of non-random techniques in which units of the sample are

selected on the basis of different settings such as convenience, personal judgment,

snowballing and quota sampling. Given this, non- probability samples can be used for such

quantitative studies where it is not possible to establish a clear frame (Turner, 2003; Brown,

2012). On the other hand, the subjective judgement involved with selecting such samples is

conducive to be used for sampling in qualitative research which leads to generalising

findings to theory – theoretical generalisation – than statistically generalising to a

population- effect generalisation (Lee & Lings, 2008; Lynchi, 2011). Subsequently drawing a

representative sample is not necessarily required since the significance of the research

findings relates to its relevance to the research question and objectives; that is, statistical

generalisation of findings is not the goal (Neuman, 2006; Lee & Lings, 2008). The canons of

non-random techniques are briefly outlined hereunder.

In convenience sampling (or availability sampling), sampling units are selected out of

convenience (Babbie, 2004; Bryman & Bell, 2012). Whilst the main drawback for using

convenience sampling is embedded in the generalisability of findings concerning the

selection bias of participants being different from the target population, it is widely used in

social research inquiries because of benefits such as accessibility and a low non-response

(Lee & Lings, 2008; Saunders et al, 2012).

A snowball sampling, as the name implies, is a referral sample for which the researcher uses

the initial respondents to help identify other cases relevant to the research topic and then

repeats the process again until it reaches a saturation point where there are no new names

given. However, the danger of using such a technique is embedded in the problems of bias

as respondents are most likely to identify others based on interrelationships (Saunders et al,

2012).

A purposive technique involves selecting units for a specific purpose on the basis of the

researcher’s judgement. These units are the ones that will be the most useful to answer the

research question or representative of the target population (Babbie, 2004). However, the

views of Hair et al (2007) are quite similar to those voiced by Neuman (2006) and Lee &

Lings (2008) that this technique is not necessarily representative of a population.

Another non-probability technique is the quota sampling that resembles stratified random

sampling, however the selection of units is entirely non-random (Bryman & Bell, 2012;

Saunders et al, 2012). Although this technique may reflect a population in terms of the

relative proportions of people in different categories, opponents of probability sampling

attribute its representation of a population to superficial characteristics that are influenced

by bias in selection of sample units (Bryman & Bell, 2012).

The economic havoc wreaked by most UK banks that were the catalysts of the FC in 2007

has induced a collective identity for this sector. In turn, this FC has yielded certain common

perceptions amid public, as Bennett & Kottasz (2012) argue. Moreover, the UK banking

sector is dominated by few very large banks which, after the FC of 2007, became even more

concentrated with the merge of some banks together such as that between Halifax Bank of

Scotland (HBOS) and Lloyds TBS to create the Lloyds Group (Chalabi, 2014). These factors

spurred conducting the research for the UK entire banking sector given the temporal effect

of the FC that has created a collective identity for the whole sector (Bennett & Kottasz,

2012).

Given the above reasoning, along with the infeasibility to identify and create a sampling

frame due to the confidentiality policies in the banking sector, a non-probability sampling

method in the form of convenience and purposive sampling were recruited. The underlying

justification is driven by constructing a coherent sampling strategy to test the research

hypotheses statistically with the consideration to capture the advantages of implementing a

non-probability method in terms of drawing a convenience sample to collect a large number

of completed questionnaire economically through sample units that are most readily

available to participate and who can provide the data required.

In this setting, response rate techniques with a screening feature were planned to achieve a

high response rate with controlled missing data to minimise non-sample errors. On the

other hand, purposive sampling was also used in conjunction with the requirements of the

research question to collect data from participants with low income less than £14,999 to

explore the financial exclusion issue of banks.

The proposed hypotheses were tested on a sample of 127 participants who are current

customers at one or more of UK banks. The respondents participating in the survey were

selected on the basis of varied demographic characteristics, such as age being within a wide

range from below 25 to 55 and above years, both male and female customers were invited

from different education backgrounds, income categories and diversity in the type of

employment status was ensured.

3.4. DATA TREATMENT AND DATA ANALYSIS TECHNIQUES

The data set was exported from Survey Monkey into Excel format and then imported into

the Statistical Package for the Social Science (SPSS Version 22.0) to analyse the data. Data

preparation constituted coding the data and adjusting the level of measurements to the

variables. To this point, the measurements were allocated in accordance with the data type

and the technique to apply for the analysis.

3.4.1. SCALES OF MEASUREMENT

There are four levels of measurements are depicted in ascending power order as following

first nominal scales which represent variables with numeric labels whereby having no order

of magnitude classifies them as the least powerful scales. Variables measured using this

scale, hence, cannot be placed in rank order. These are non-metric scales that suited non-

parametric statistics such as Chi-square statistic (Hair et al, 2007). In this sense, nominal

scale is used as a level of measurement to classify the gender and relationship status

variables for this study.

The inability of ranking variables on nominal scales contrasts with ordinal scales. As its name

implies, variables can be ranked. However, the distance between scale points is not equal

across the range (Bryman & Bell, 2012). The ranking characteristic of this scale allows for

higher level of analysis than with nominal data relevant to non-parametric statistics such as

Spearman’s correlation. Given this, ordinal scale was allocated to the education and the

duration of maintaining a UK bank account variables.

The interval and ratio scales address the arithmetic quality that differences between points

on the scale are identical. Whilst ratio scales incorporate the qualities of the other three

scales, they diverge from interval for stating the relative difference between any two values

for a particular variable, that is, this scale is the highest level of measurement (Lee & Lings,

2008).

While Likert scale is characterised as an ordinal scale, it can be argued that Likert scale can

be treated as an interval scale given the justification that the gaps between its points are

equal in magnitude across the whole range of the scale (Han, 2006; Lee & Lings, 2008; Hair

et al, 2007). In addition, this scale is characterised as a metric scale employed with

parametric statistics such as Correlation Analysis, Multiple Regression (Hair et al, 2007)

which this study implemented to analyse the collected data. Based on this, the independent

variables (IVs which are the predictors) and dependent variables (DVs - also known as

outcome variables) of this study are measured using Likert five-point scale which is assumed

to be interval whereby the gaps between its points are equidistant as illustrated in Figure 5.

Figure 5 - Five-point Likert Scale

1 2 3 4 5

Strongly Neutral Strongly

Disagree Agree

3.4.2. RELIABILITY ANALYSIS

One way of testing internal reliability is the Cronbach’s alpha method which was used in this

research to assess whether the items that make up the scale were internally consistent.

Cronbach’s (coefficient) alpha is the most common measure of scale reliability that ranges

from 0 to 1 within which a value of 0.7 to 0.9 indicates good reliability and 0.7 is the

accepted benchmark for Cronbach’s alpha. However 0.60 can be an acceptable level of

internal reliability in exploratory research. Consequently, high reliability is explained by

(Han, 2006)

highly correlated items that are measuring the same thing whereby low reliability denotes

that the items measuring the scale have very little in common (Hair et al, 2007; Bryman &

Bell, 2012).

3.4.3. FACTOR ANALYSIS

Aggregating a group of interrelated variables into a smaller set of factors is one of the main

objectives to perform factor analysis which is regarded as a versatile means to provide

preliminary solution for multivariate data analysis. Two methods can be used in factor

analysis, Principle Component Analysis (PCA) and Common Factor analysis. PCA allows for

the analysis of both the common and unique variance of a score hence used for data

reduction whereas Common Factor analysis is only concerned with the common (shared)

variance thus it is used in uncovering construct dimensionality. Based on this, calibration

sample was subject to PCA (Field, 2009).

The initial step in the preliminary analysis is concerned with checking R-matrix for any

extreme scenarios such as multicollinearity of highly correlated variable and low singularity

correlation. The suitability of the sample size has to be considered by assessing the Kaiser-

Meyer-Olkin (KMO) statistic and Bartlett’s Test of Sphericity. The threshold of 0.6 for KMO

indicates an adequate sample size, also Barlett’s test signals the significance of the overall

correlations in R-matrix (Field, 2009).

Using PCA, the number of components is extracted based on the Kaiser criterion of Eigen

values over one, also scree plot aides in the decision by visually spotting where the point of

inflexion occurs to retain only components to the left of this point. Regarding rotation, two

methods can be used to improve factor solution by maximising the loadings of some of the

items. An oblique rotational method allows factors to correlate whereby the other method

– orthogonal – does not. Thus, the former rotation was sought for the analysis for which

factor loading was set as 0.4 as recommended by Field (2009).

3.4.4. CORRELATION ANALYSIS

This analysis gauges the degree of covariation between two variables. It can be conducted

by using one of the two bivariate correlation coefficients – Pearson’s product-moment

correlation coefficient (PMCC) and Spearman’s rho. While the latter deals with ordinal data,

the former calculates interval/ratio data which is the level of measurement assigned for the

study’s IVs and DVs. Hence, this is the used statistic to quantify the strength of the linear

relationship between a pair of variables (Hair et al, 2007).

Pearson r assesses the strength and direction of association between two variables such as

CSR fit and CR in which the correlation coefficient ranges between -1 and +1. A Pearson r

value between +0.9 and +1 denotes a very strong positive correlation, whereby a value

between -0.9 and -1 still indicates a very strong correlation but negative which means when

one variable increases, the other variable decreases. Moreover, the correlation has no

meaning if it is not statistically significant whereby the p-value is less than 0.05. This implies

that the relationship is statistically significant hence the null hypothesis is rejected (Bryman

& Bell, 2012).

3.4.5. REGRESSION ANALYSIS

It is closely connected to Pearson’s r with regards that correlations between variables are

linear, however, this analysis allows to ‘predict an outcome variable from one predictor

variable (simple regression) or several predictor variables (multiple regression)’ (Field,

2009). The coefficient of determination or R squared entails the amount of variability in one

variable explained by the other variable. It can have any value between 0.00 to 1.0 whereby

the greater the R2 the stronger the association. The F- statistics and its associated

probability in the ANOVA table assess the statistical significance of the overall regression

model (Hair et al, 2007).

In the coefficients table, the regression coefficients (b values) point out the amount of

change in the outcome variable resulting from a one unit increase in the predictor. To

evaluate the statistical significance of betas (b vales), the t-statistic tests the null hypothesis

for the value of b, whereby less than 0.05 it is rejected and b-value is statistically significant.

A predictor variable with insignificant beta is not a good predictor of the dependent variable

and should be removed from the regression model (Hair et al, 2007).

3.4.6. MEDIATION ANALYSIS

Baron & Kenny's mediation approach involves following four steps (Figure 6) to analyse

whether certain variable – a mediator – exerts an effect by intervening a relationship

between an independent (IV) and dependent variable (DV) (Janice, 2012).

Step 1: Involves portraying a structural model to estimate path c in which the IV is assessed

whether it correlates significantly with the DV. Based on the existence of a significant

correlation between both variable, the rest of the procedure is validated.

Step 2: Establishes path a in which the direct relationship between the IV and mediator is

tested whereby mediator is regressed on the IV. They must correlate to validate next step.

Step 3: Includes testing path b by performing a hierarchical regression whereby, in first step,

the DV is regressed on the mediator while, in second step, DV is regressed on the IV.

Step 4: Tests path c’ by assessing the relationship between the independent and outcome

variables. If it becomes insignificant, then there is full mediation while if this relation

remains significant then it confirms a partial mediation.

Independent variable

Dependent variable

C’ (Path c)

Mediator

3.4.7. ETHICAL CONSIDERATIONS

Within the realm of conducting a research, there are some obligations that revolve around

ethical concerns starting from the appropriateness of the research to issues emerge in each

phase of the research process. This includes not avoiding any risk of causing harm or

intruding on privacy to access data, disclosure about the nature of the research and

sufficient information to avoid lack of informed consent and maintaining confidentiality of

data and anonymity of participants’ identities (Hair et al, 2007; Bryman & Bell, 2012). In

compliance with this continuum of ethical principles, this dissertation is also regulated by

the Code of Research Practice of The University of West London which sets out researchers’

broad responsibilities.

In doing so, a disclosure of the nature and purpose was encapsulated in the introduction of

the online questionnaire as well as the invitation email sent to take part in the study. This

invitation stated explicitly that participants’ privacy will be protected and that their

participation is voluntary whereby they have the right to decline or not to participate in the

study (see Appendix II). Confidentiality and anonymity of all participants were dealt with as

(Janice, 2012)

Figure 6 – Mediation Model

questionnaires were anonymous and participants were informed that all data collected will

remain confidential and are protected according to the Data Protection Act 1998 (DPA).

Data will be processed and analysed objectively and a summary of the research findings can

be obtained if requested.

3.5. CONCLUSION

The study adopted a quantitative method and followed a deductive approach. A

questionnaire survey was designed as the primary data source. The collected dataset was

analysed using rigorous relevant methods to get the most out of the data in order to have a

deep investigation and render sufficient results.

Chapter 4: Analysis and Discussion of Findings

4.1. INTRODUCTION

Given the baseline for the research design to collate the data and methods of analysing it in

the methodology chapter, this chapter explores the empirical findings of descriptive and

parametric statistics.

4.2. DESCRIPTIVE STATISTICS

To tap into the socio-demographic profiles of respondents, a Univariate analysis was

conducted via frequency distributions and diagrams to explore the data of one variable at a

time. With regards to age distribution, most of the respondents – 41 out of the 92 – were

aged 35-44 years (44.6%). The younger age group (less than 25 years) contributed with only

5 respondents (5.4%) while 22 (23.9%) belonged to the middle age group (26-34 years).

There were 14 respondents (44.6%) from the older age group (45-54 years) with the

remaining 10 (10.9%) belonging to oldest one (55 years and above). As illustrated in Table 2,

the figures in the Percent and Valid Percent are the same as there is no missing data.

Which of the following categories best describes your age?

Frequency Percent Valid Percent

Cumulative

Percent

Valid Below 25 5 5.4 5.4 5.4

26-34 22 23.9 23.9 29.3

35-44 41 44.6 44.6 73.9

45-54 14 15.2 15.2 89.1

55 and above 10 10.9 10.9 100.0

Total 92 100.0 100.0

Table 2 – Age of Respondents (Questionnaire Section A- Q1)

As for the gender distribution, it was evenly spread across the dataset with 50 female

(54.3%) and 42 male (45.7%) (Figure 7).

Figure 8 presents the relationship status of respondents, about 50 (54.4%) are married while

the remaining 45.65% are spread out over the other different relationships.

Regarding the type of employment, 66 respondents were in full time employment (66.30%)

followed by 18.48% of being self-employed. Only 1.09% are on retirement (Figure 9).

Figure 7 – Gender of Respondents (Questionnaire Section A- Q2)

Figure 8 – Relationship status of Respondents (Questionnaire Section A- Q3)

Table 3 – Respondents’ Annual Income (Questionnaire Section A- Q6)

A large group of respondents (35.9%) has an annual income of £75,000 and above. The

breakdown of the responses shows that 8.9% earn less than £14,999. The deployment of

the purposive sampling technique helped in the inclusion of this segment to ensure covering

all relevant questions that address the research objectives. Equally, around 13% of

respondents earn within the income brackets of £30,000 - £44,999 and £45,000 - £59,999.

What is your current household income (£ gross)?

Frequency Percent Valid Percent

Cumulative

Percent

Valid Less than 14,999 8 8.7 8.7 8.7

15,000 - 29,999 17 18.5 18.5 27.2

30,000 - 44,999 12 13.0 13.0 40.2

45,000 - 59,999 12 13.0 13.0 53.3

60,000 - 74,999 10 10.9 10.9 64.1

75,000 and above 33 35.9 35.9 100.0

Total 92 100.0 100.0

Figure 9 – Respondents’ Type of Employment (Questionnaire Section A- Q5)

Figure 10 shows that the majority have more than ten years’ experience with their banks

which makes up almost 59% of the sample, while only 16.30% have been with their banks

for less than five.

4.3. EMPIRICAL FINDINGS OF PARAMETRIC DATA

Before analysing the dataset, the data was prepared pertaining to editing, coding and data

transformation as appropriate; the data was also examined for anomalies. The research

question and objectives were addressed through the statistical analysis of the data in four

analytical frameworks. This included performing a number of relevant analysis comprised of

reliability analysis to test for the level of consistency among the items within each

framework. It was followed by conducting a Factor Analysis for each of the first and the

second frameworks. The rationale behind using the Factor Analytic approach is to reduce

the large dataset into a smaller set of salient items, hence producing a more manageable

number of variables to submit for the subsequent analysis of Multiple Regression

(Multivariate analysis) in the analysis of each of the aforementioned frameworks. For the

third framework, Pearson product-moment correlation coefficient was performed. The last

Figure 10 – Respondents’ relationship duration with their banks (Questionnaire Section A- Q8)

analytical framework tapped on the mediation effect of CSR on customer-stakeholder

purchasing decision (behavioural intention) and bank’s corporate reputation. This was

tested by using Baron & Kenny's Mediation procedure (1986, cited in Aggarwal, 2004).

4.3.1. RESEARCH OBJECTIVE ONE

Investigate whether perceived CSR activities in the post FC of 2007 has an impact on banks’

customer-stakeholders satisfaction

4.3.1.1. RELIABILITY ANALYSIS

Initially, the Cronbach’s alpha was checked to assess the interrelatedness of items that

gauge customers’ perception of CSR activities. The estimation of the intercorrelation among

these items came satisfactory as 0.96 which reflects a reliable scale (Table 4). Although the

scale met the criterion of a very good coefficient alpha, yet, according to Hair et al (2007),

an alpha of ≥0.95 should be inspected to eschew a limited breadth of items focus if they do

not measure difference aspects of the concept. To address this, the inter-item correlation

matrix was visually scanned for high correlation where r ≥ 0.85 (Ioannou, 2009) or r ≥ 0.80

(Field, 2009) as this would exhibit considerable redundancy among items.

The preliminary test of multicollinearity revealed that correlation coefficient was within the

acceptable margins. Given this, there was not any multicollinearity of perfect linearly

relationship between the items. Another investigation was sought pertaining to checking

the determinant of the correlation matrix whereby if it is greater than 0.00001 then

multicollinearity is not a problem. Thus the determinant value was 1.615E-13- which is

0.00016 which did not signal multicollinearity (Appendix E).

Table 4 – Reliability Statistics for perceived CSR activities

Cronbach's Alpha

Cronbach's Alpha Based

on Standardized Items N of Items

0.961 0.962 33

Two items with low correlation where r is less than threshold 0.3 were detected in the inter-

item correlation matrix. However, by deleting these items, alpha value will not change. This

was seen as an early stage to eliminate these items because more rigorous analysis can be

sought by checking their level of significance in next stage to consider discarding them from

the analysis if they have an adverse effect. Consequently, it was decided not to exclude

them as they may contribute differently to the content coverage of the subscale.

The overall coefficient alpha was 0.96 thus the scale was adequately reliable. It reflected

that all items are positively contributing to the overall reliability. The justification of such

value can be a function of the scale length for which factor analysis was used as a remedy to

cluster the 33 items into a small set of components with efficient traits to explain as much of

the variance in the original data set which would be sufficient enough to perform the

regression analysis (Field, 2009; Iatridis, 2011).

4.3.1.2. FACTOR ANALYSIS

The calculated KMO statistic on the 33 items gave a result of 0.896 which verified the

sampling adequacy. A KMO in the region of 0.8-0.9 is considered perfect and indicated that

the sample size was adequate for the factor analysis solution. Furthermore, the Bartlett’s

test of sphericity χ² (528) = 2331.783, p < .005 (Table 5) indicated that correlations between

items were sufficiently large for factor analysis. While, items Q16 and Q18 have high p-value

(> 0.05) with some other items in the R-matrix, overall there was a positive strong

correlation among the residual items of the matrix (Appendix F). Moreover, the Bartlett’s

test was highly significant, hence, before deciding to exclude these two items, their

communalities were considered. The values came as 0.717 and 0.583 respectively which

reflected that both items contribute fairly well to the factor structure and should not be

discarded in order not to lose important information. The yardstick was to compare

communalities before and after extraction in following steps. Overall, this allowed for

factorising the 33 items using PCA to investigate these relationships further and gain deeper

insight.

Table 5 – KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling

Adequacy. .896

Bartlett's Test of

Sphericity

Approx. Chi-Square 2331.783

Df 528

Sig. .000

An initial analysis was performed to obtain Eigen values for each component in the data. Six

components had Eigenvalues over Kaiser’s criterion of 1. The first component explained

46.86% of total variance and, in combination, the six components explained about 69.05%

of the variance. The point of inflexion in the scree plot occurred at the second point

(component). Both Kaiser’s and scree plot criteria have justified retaining two components.

The second component constituted of two items which is not an adequate number of items

for providing feasible factor solution. Hair et al (1998, cited in Coleman, 2011) advocate for

more than three items to generate a reliable solution. Hence, three components with Eigen

values greater than one were extracted and oblique rotation was conducted to optimise the

factor structure by maximising the loadings of some of the items whereby a factor loading of

0.4 – which is in line with Field’s (2009) suggestion – was used.

This structure has yielded insufficient value of alpha coefficient for the second component

as Cronbach’s alpha was 0.532 (Appendix G). However, deleting Q16 from the construct

would improve alpha value to 0.802, excluding this item hence was corroborated. After

deleting Q16, PCA was rerun then the previous analytical approach of extracting and

rotating was reiterated. This led to two components retained. They together accounted for

54.02% of the total variance and therefore the factor extraction results were generally

satisfactory.

The first component was labelled Economic & Legal focus (EC&LG) given the salience of

those items with the higher loadings. The second component emerged from Philanthropic &

Ethical statements and was named as PH&ET. Moreover, through this process Q18 proved

to be inadequate as it has low communality (0.91), thus it was not calculated within any of

the components (Table 6).

The final two components intercorrelated with r value of 0.634 whereby an r of 0.40 to 0.69

is mediocre as recommended by Cohen & Holliday (1982, cited in Bryman & Cramer, 2005)

thereof, overall, there was a positive association between the two components (Appendix

H).

Table 6 – The Extracted Factor Components and their Alpha values

Items Component

Cronbach’s Alpha EC&LG PH&ET

Q9Financial_Statements .904 .953

Q12Fees .883

Q12Interest_Rates_Accounts .858

Q12Interest_Rates_Loan .740

Q12Open_Or_Close_Branches .734

Q9Transparency .687

Q12Treated .686

Q12Withdraw_Money .684

Q12Personal_Information_Safe .647

Q12Financial_Stability .627

Q9legal_Obligations .616

Q10 .613

Q9Honest_Relationship .612

Q9Borrowings_And_Savings .589

Q9Offers .572

Q9Confidentially .568

Q11 .566

AQ12Advice_Quality .520

Q9MeetCustomers_Needs .465

Q9Financial_literacy .915 .917

Q9Giving_Back_To_Community .822

Q9Social_Attachment .806

Q9Executive_Remuneration .717

Q9Environmentally_branches .638

Q13 .557

Q9Being_Accountable .527

Q17 .498

Q9Valued_Customer_Recognition .498

Q9Financial_Inclusion_SMEbanking .461

Q14 .452

Q9Combating_Bribery .444

Q18

4.3.1.3. MULTIVARIATE REGRESSION ANALYSIS

Based on the findings of factor analysis, the original hypothesis that investigated the

relationship between the perceived CSR activities and customer satisfaction was

reformulated as follows:

H1.a: There is a relationship between perceived CSR’ EC&LG activities and customer-

stakeholder satisfaction in the post FC of 2007.

H 1.b: There is a relationship between perceived CSR’ PH&ET activities and customer-

stakeholder satisfaction in the post FC of 2007.

Multiple linear regression analysis was performed to assess the relationship between the DV

– customer satisfaction – and the two IVs – EC&LG and PH&ET. Enter method was used to

bring both IVs into the model. The results incorporated that correlation matrix reported a

significant positive relationship among all the variables with one-tailed significance of 0.000.

Within the R-matrix, the highest correlation was between EC&LG and customer satisfaction

(r=0.712). The matrix also did not cast any doubt on multicollinearity issues which was in

line with Variance Inflation Factor (VIF) benchmark as being less than ten according to Field

(2009) and did not exceed the warrant point of five which is the borderline of diagnosing

some multicollinearity (Appendix I). Furthermore, the R-squared showed that EC&LG and

PH&ET approximately accounts for 57.7% of the variation in customer satisfaction. The

regression model was statistically significant with F-ratio=60.738 and probability

level=0.000.

It transpired that EC&LG (beta=0.496, p<0.05) and PH&ET (beta=0.341, p<0.05) are

positively and significantly related to customer satisfaction. From the magnitude of the b-

values, the 0.496 is the estimated increase in likelihood to have a satisfied bank customer-

stakeholder associated with a one-unit increase in EC&LG CSR activities. Likewise, customer

satisfaction would rise 0.341 for every one-unit increase in PH&ET.

Table 7 – Multiple linear regression analysis: Impact of CSR activities on Customer Satisfaction

Model

Unstandardized

Coefficients

Standardized

Coefficients t Sig.

B Std. Error Beta

1 (Constant) 3.109 .061 51.370 .000

EC&LG .438 .079 .496 5.564 .000

PH&ET .301 .079 .341 3.829 .000

Taken together, these figures provide evidence of model fit, revealing that the null

hypothesis of no relationship between customer-stakeholder satisfaction and both EC&LG

and PH&ET CSR activities is rejected, that is, this confirmed supporting the alternative

hypothesis of a relationship. Moreover, the findings from the regression model embodied a

statistically significant positive relationship between these variables. Based on this, H1.1 and

H 1.2 are supported.

4.3.2. RESEARCH OBJECTIVE TWO

Find out whether there is a relationship between CSR practices and bank customer-

stakeholder behavioural intention (purchase behaviour).


The Cronbach’s alpha value for CSR practices was 0.923 which reflected a good degree of

reliability. Four items were very highly correlated with r≥0.80 (Field, 2009; Ioannou, 2009).

Rhese items were Q19Compliance with more than minimum regulation, Q19Welfare and

goodwill, Q19Low-involvement of philanthropic and Q19High-involvement. r values ranged

from 0.807 to 0.893 were detected and deleted from the analysis to avoid multicollinearity.

Coefficient alpha value was still good after the removal of these items (Cronbach’s

alpha=0.882). Moreover, careful screening of Item-Total Statistics table verified that

deleting any other items would not substantially increase the coefficient.

Table 8 – Reliability Estimates of CSR practices subscale

Scale

Mean if

Item

Deleted

Scale

Variance

if Item

Deleted

Corrected

Item-Total

Correlation

Squared

Multiple

Correlation

Cronbach's

Alpha if Item

Deleted

Q19Reasonable_Interest_Rates 35.36 44.540 .411 .496 .884

Q19Payments_Fees_Transparency 35.29 43.243 .615 .592 .871

Q19Account_Information_Confidentiality 35.28 41.590 .691 .679 .865

Q19CEO_Cuts 36.39 42.263 .431 .490 .887

Q19Financial_Inclusion 36.37 41.818 .492 .407 .881

Q19ValuedCustomer_Treating 35.22 41.842 .761 .742 .862

Q19Honest_Financial_Advice 35.26 41.602 .755 .754 .862

Q19Compliance_With_Law 35.34 41.127 .737 .669 .862

Q19Projects_With_Adverse_Impacts 35.85 39.471 .646 .546 .868

Q19CEO_dont_Misreport 35.63 39.752 .745 .673 .860

4.3.2.2. FACTOR ANALYSIS

Both the KMO (0.878) and Bartlett’s test of sphericity χ² (45)=556.572, p<0.05 indicated the

suitability of the data for performing factor analysis. Next step involved determining a set of

components which had Eigenvalues over Kaiser’s criterion of 1. The suitable factorial

method incorporated using Oblique (Direct Oblimin) rotation with factor loading of 0.4.

Two components were constructed which explained about 16.28% of the variance in the

customer purchasing decision of bank’s products and services. From the pool of ten items,

component one included six items within the domain of Economic & Legal practices in

accordance to their loading magnitude, thus labelled ECP&LGP. On the other hand, the

other four items portrayed the traits of Ethical & Philanthropic practices hence named

ETP&PHP. The two components have an adequate correlation (r=0.346). The coefficient

alpha for ECP&LGP was 0.898 while alpha for ETP&PHP came as 0.809. That is, both had

reliable scales with meaningful indices that gauged customers’ behavioural intention.

4.3.2.3. REGRESSION ANALYSIS

A multiple linear regression analysis was performed for which ECP&LGP and ETP&PHP

articulated the IVs to assess whether they have an impact on customer purchasing decision.

The R-squared revealed that approximately 30.9% of variation in customer purchasing

decision is explained by IVs. The F-statistic (19.929) in the ANOVA table transpired that the

regression model is significant at 0.000 level.

Furthermore, ECP&LGP had beta=0.301, p<0.05 and ETP&PHP had beta=0.375, p<0.05

indicated that both were significant predictors of customer purchasing decision (Appendix

I). The IVs of CSR practices on purchasing decision (DV) were statistically significant in the

model, thereof a statistically significant positive relationship exists between purchasing

decision and CSR practices. As such, this lent support to the research hypothesis where

customer-stakeholder purchasing decision is associated with CSR practices.

4.3.3. RESEARCH OBJECTIVE THREE

Determine whether there is a relationship between CSR fit practices and bank reputation.


The Cronbach’s alpha for the subscale items of CSR fit practices was 0.879 after deleting

Q23 which had a negative r value in the R-matrix. According to Hair et al (2007), all items

must be positively correlated. Consequently, the deletion of this item was shown to improve

the overall coefficients value from 0.781 to 0.879 which is regarded as a very good value

that has exceeded the recommended threshold limits of 0.6. Cronbach alpha coefficient

before the deletion of item Q23 is illustrated in Appendix J.

4.3.3.2. CORRELATION COEFFICIENT ANALYSIS

The correlation coefficient analysis showed that there was a significant linear association

between bank reputation (DV) and the subscale of CSR practices (IV). According to Table 9,

bank reputation was positively correlated at the 1% level of significance with CSR subscale

(Q21) at r=.372**, r=.464**, r=.495** and r=.582** respectively.

Table 9 – Correlation Coefficients for bank reputation and CSR fit practices subscale

Mean St.(Dev)

Q21CSR_s

trategy Q21Confidence

Q21Reputable

_Business

Q21High_

CSR_rating Q22

Q21CSR_strategy 3.91 .847 1

Q21Confidence 4.00 .784 .695** 1

Q21Reputable_

Business 3.98 .784 .543** .643** 1

Q21High_CSR

_rating 3.98 .784 .593** .679** .732** 1

Q22More

preference will be

given to banks

3.54 .965 .372** .464** .495** .582** 1

N of respondents 92 92 92 92 92

Note: ** indicates that Correlation is significant at the 0.01 level (2-tailed).

Most CSR subscale items had moderate positive correlation with bank reputation, while high

CSR rating criteria had strong – as advocated by Field (2009) when r is higher than .50 –

associative relationship with bank reputation. Moreover, Table 9 revealed that the means

for all the items were above the mid-point (3.0) of the five –point scale.

From the positive correlation of the variables and the statistically significant level, the null

hypothesis of no relationship between CSR fit practise and bank reputation was rejected

and the alternative hypothesis was verified.

4.3.4. RESEARCH OBJECTIVE FOUR

Investigate whether CSR practices mediates the relationship between bank reputation – the

independent variable (X) – and stakeholders' behavioural intentions – the dependent

variable (Y).

4.3.4.1. MEDIATION ANALYSIS

The procedure of Baron & Kenny (1986, cited in Aggarwal, 2004) used designate CSR

practices as the mediator – denoted as M – between bank reputation (X) and stakeholders'

behavioural intentions (Y).

A Linear regression analysis was performed between bank reputation and customer

behavioural intention (purchase behaviour) to assess the validation of conducting the

mediation processes based on the criterion of a significant correlation between these

variables. Meeting this criterion, three models were constructed to test the mediation effect

of CSR practices.

Table 10 – Regression Models of Mediation Effect (CSR practices)

Model Independent

Variable (X)

Dependent

Variable (Y) R-Square

Coefficient

(Predictor)

P-Value

(Predictor)

Model 1

Path c Bank reputation

Purchase

behaviour .370 .609 .000

Model 2

Path a Bank reputation CSR Practices .301 .549 .000

Model 3

Path c’

Bank reputation

CSR Practices

Purchase

behaviour .577

.310

.544

.000

.000

The results for Model 1 (path c) emerged from the verified relationship between bank

reputation and purchase behaviour (b=0.609 and p<0.05). This model entailed the direct

relationship between these two variables. Likewise, Model 2 (path a) was constructed from

the statistically significant positive relationship between bank reputation and CSR practices

(b=0.549, p<0.05). By performing hierarchical regression analysis, the last Model 3 (path c’)

stemmed from the significant positive relationship between CSR practices, bank reputation

and purchase behaviour. This model unveiled the effect of CSR practices variable whereby a

significant positive regression coefficient of 0.310 (p<0.05) between bank reputation and

purchase behaviour was indicated. Also CSR practices remained significant with p<0.05

when it was added into the relationship. On the other hand, when comparing the beta of

Model 1 with that of Model 3, b values had a significant drop from 0.609 to 0.310 (29.9%)

which indicated that CSR practices influenced the relationship. Results of the mediation

analysis confirmed a partial mediating role of positive CSR practices in the relation between

bank reputation and customer behavioural intention.

4.4. DISCUSSION OF FINDINGS

The analyses of the collected data have revealed key findings that could be explicated within

the ambit of the research aim of contributing towards a dynamic evolution of the CSR

construct. The discussion draws out on the empirical findings in relation to the study

literature.

4.4.1. CUSTOMER-STAKEHOLDER’S PERCEPTION OF CSR ACTIVITIES IN THE POST FC OF 2007

The empirical results with regards to Research Objective One supported the hypothesised

relationship between perceived CSR activities and customer-stakeholder satisfaction. This

positive relation indicates that banks have been accountable for the failures of their

practices around the FC of 2007 which emanated from adhering to satisfying shareholders

at the expense of other stakeholders. This is in line with the argument of Carroll & Shabana

(2010) that businesses’ accountability for their impact should extend beyond the narrow

view of shareholder model to incorporate the interests of other stakeholders by integrating

social activities in order to leverage the means of satisfying its stakeholders.

The fact that a good number of customers have been found to contribute to this study

indicates that banks perceive them as an important segment of stakeholders. As this study

has shown, customer-stakeholder satisfaction is engendered owing to the inclusion of their

interests and meeting their expectations. Hence, the argument made by Freidman

advocating a primacy of shareholder is no longer feasible. Moreover, as the findings show,

the claim of Windsor (2001, cited in Garriga & Mele, 2004) that the paradigm of short-

termism gain and shareholder primacy is still the leitmotiv in business lacks credibility.

As such, contemporary disciples of Friedman’s neoliberal premise of shareholder such as

Barry 2000, Henderson, 2005 and Jensen, 2001 are not opposing social responsibility actions

by companies. Sternberg (1997) defends embracing socio-economic posture in line with

business stakeholders to spur efficiency as the exclusion of any stakeholder might affects its

ability to attain economic ends (Branco & Rodrigues, 2007).

This stakeholder view challenged the single-minded focus of shareholder primacy pointing

that the interests of shareholders and stakeholders are aligned rather than in conflict. In this

context, the societal values alleged by stakeholders are expected to be satisfied as business

functions by the consent of society, thereof these expectations are justifiably attested by

business (Lindgreen & Swaen, 2010). The study’s statistical results reveal that the jointly

approach of aligning stakeholders’ needs to business activities positively influenced

customer-stakeholder perceptions of these activities. They were labelled in the empirical

analysis as EC&LG and PH&ET.

The findings concur with Carroll’s (1991) CSR model which incorporates these four activities.

As it has been reported in the literature review, business has sprung up as an economic unit

whereas its driver is a profit motive. It also has an obligation to produce valuable goods and

services that meet consumers’ needs at a fair price (Branco & Rodrigues, 2007; Duarte et al,

2010). The salient embodiment of this category is relating business economic objectives to

producing goods and services of value to society in tandem to thriving to generate profit.

Hence, these responsibilities are required in order to secure their license to operate. The

study’s relevant analysis has shared this view whereby customers’ satisfaction of perceiving

the economic value from their dealings with businesses precedes the other activities.

The second category in Carroll model is the legal responsibilities which captures ‘playing by

the rules of the game’ of Friedman’s metaphor, thence, it is presupposed that they coexist

with the economic responsibilities as a rationale to the free market paradigm. This activity

shared the same weight of importance with Carroll’s model to achieve customer’

satisfaction in the research findings. Carroll (1991) pinpoints that ethical responsibilities

imply doing what is right and taking into account the moral duty that business has to

society. Philanthropic activities are allied to the idea of giving back to society as the

recognition of business to be a good citizen (Crane & Matten, 2010).

The study results have reported a discrepancy in the order of the last two CSR activities

where perceived philanthropic activities had higher weighting with regards to customer

satisfaction than ethical activities. On that point, for both the economic and legal

responsibilities Carroll (1991) asserts that they are required while the ethical responsibilities

are expected and the philanthropic is desired. By doing so, his model provides insightful

assessment of the relative weighting of these responsibilities to set priorities upon them.

However, Visser (2005) rigidly criticises the relative importance that Carroll has assigned to

each responsibility for being biased towards USA context. He has emphasised on the culture

context for these assigned priorities giving the example of the high importance of

philanthropy in Africa to others.

Carroll & Buchholtz (2009) argue that the responsibilities are not mutually exclusive nor

intended to be sketched as a continuum from economic to social obligations. The

theoretical clouding with regards to the order of these activities can be cleared out based on

the practical outcome of this study in which the relative order of these activities adheres to

the attribute attached to it. In this context, the perceived CSR activities that have caused

customer satisfaction were economic, legal, and philanthropic with ethical as last domain.

This might be as a result of business being recovering from the ethical issues provoked by

the FC of 2007. Moreover, it could also be derived from the ill-defined characterisation of

newly emerging values which can result in an equivocal stance in which there may not be a

definitive right answer to resolve many of these ethical issues and result into conflict with

the other responsibilities (Jamali, 2007).

4.4.2. CSR PRACTICES AND CUSTOMER-STAKEHOLDER BEHAVIOURAL INTENTIONS

The research findings revealed a significant relationship between CSR practices and

customer purchasing decision. These outcomes have rekindled Forte & Lamont’s (1998,

cited in Boulstridge & Carrigan, 2000) claim that the societal role of the business influences

the customer’s criterion in purchasing decision. In a conjunctive scenario, Mohr & Webb

(2005, cited in Chomvilailuk & Butcher, 2010) point out that customer’s purchasing decision

and company evaluation are positively influenced by CSR initiatives. The study results

confirm these arguments and shed light on the importance of different multiple CSR

practices which were labelled as ECP&LGP while ETP&PHP on customer purchase decision.

These practices built on Carroll’s CSR model in the foregoing discussion. The order of CSR

practices is congruent with Carroll’s model. This may be attributable to the different

dimensions that have been gauged using the model. In the analysis of perceived CSR

activities and customer satisfaction, the dimension measured the level of satisfaction of the

perceived CSR. Within the CSR practices and purchasing decision, the dimension measured

the level of importance of CSR practices in relation to customer behaviour.

This study shares the view of Pirsch et al (2006, cited in Chomvilailuk & Butcher, 2010) that

societal attributes which are woven into business operations and core competences can

elicit significant positive customers’ behavioural and attitudinal measures such as patronage

intention. The high level of economic importance that was highlighted in the research

findings tap on the core competencies of business as CSR economic practice induce cost

effective products to customers.

4.4.3. CSR AND BANK REPUTATION

The emergence of a significant positive relationship between CSR and bank reputation is

congruent with the findings of Reputation Institute (2009, cited in Trotta et al, 2011)

whereby a positive direct relationship between CSR and CR is reported in the sense that

when the commitment to CSR is augmented, the value of CR would be boosted. Moreover,

Martin & Ruiz (2007, cited in Chomvilailuk & Butcher, 2010) conjecture a direct link between

a customer’s liking for the bank and the bank CSR reputation.

The second statement in Q21 with regards to customers’ confidence in business had a

significant good correlation with r= 0.464. This came in line with previous studies (Fombrun,

1996; Trotta et al, 2011) in which CR is regarded as an indicator of business’s legitimacy

premised on its credibility in maintaining society’s trust in business and potentially

influencing the purchasing behaviour of that public.

4.4.4. MEDITATION EFFECT OF CSR ON CR AND CUSTOMER-STAKEHOLDER BEHAVIOURAL INTENTION

The mediation effect emerged from the data is consistent with the findings of Lichtenstein

et al (2004, cited in Chomvilailuk & Butcher, 2010). The study findings showed that there is a

partial mediation effect of CSR on the relation between CR and customer purchasing

behaviour. This would provide a new understanding of the role of CSR for its mediation

effect on such relation. This approach would facilitate CSR role in developing business

sustainability through its indirect effect on the business economic bottom line.

While Carroll & Shabana (2010) argue that the justification of the business case for CSR is

based on a direct link to economic ends, the findings add credence to the business case by

justifying it on more plausible indices based on the indirect effect of CSR on business

economic value.

4.5. CONCLUSION

The findings of the four analyses supported the alternative hypotheses of a positive

correlation between CSR and customer satisfaction, customer purchase behaviour and CR

respectively. The findings for the CSR mediation effect also revealed a partial mediation of

CSR on the relationship between CR and customer purchase behaviour. The discussion of

these findings was compared with findings of pertinent studies from the literature review.

Chapter 5: Conclusion and Recommendations

5.1. INTRODUCTION

The previous chapter evolved around the critical discussion of the study findings in the

context of the literature. This involved comparing the empirical findings to the results of

previous studies. The discussion was guided by four research objectives that were geared

towards the empirical testing of the hypothesised relationships. Consequently, the objective

of this chapter is to draw conclusions from these findings to answer the research question

and address the research objectives. This is followed by demonstrating the theoretical and

practitioner contributions that this research makes. It also discloses recommendations for

future research and limitations concerning this research.

5.2. CONCLUSION

At the outset, this study’s objectives aimed at investigating the likelihood of CSR

development in the post FC of 2007 with regards to two avenues. The first was customer-

stakeholders’ satisfaction of perceived CSR activities in the FC whereas the second was

related to the implications of strategic CSR on CR as well as the possibility of influencing

customers purchasing decision.

As illustrated in the analytical framework, using Carroll’s (1991) CSR four dimensions to

assess whether these dimensions affect customer satisfaction and their purchasing decision,

the empirical outcomes highlighted some similarities as well as an angle of difference with

Carroll model. The similarity pertains to the order of the economic and legal CSR

dimensions. The findings showed that these two dimensions came in the same order as

Carroll model.

Aligned with Carroll’s model in terms of designating CSR economic activities as the base for

the other three activities, the findings demonstrated the banks’ commitment to deliver

highly satisfactory economic value to their customers. This manifests their recognition of

the importance of customer-stakeholder group to their continuity.

As for the legal dimension, it has been argued that while business is obliged to perform in a

law-abiding manner, most businesses would cultivate CSR practices as self-regulatory to

keep at bay more legalisations (Freeman & Liedtka, 1997). In support, the perceived CSR

legal activities seemed to encounter high level of customer satisfaction, indicating how most

banks have been able to seize the advantages of adhering to CSR by maintaining a plausible

satisfactory level of legal compliance.

Some key findings have emerged from the preceding remarks pertaining to banks’

discerning CSR practices that elicit high satisfactory levels for the activities that are

conceived to be most important to customers when making purchasing decision. These

findings support the view of a win-win scenario exhorted via the value creation perspective

of strategic CSR (Mullerat, 2010).

Accordingly, this reveals that the dynamics of banks’ CSR practices are in line with

customers’ expectation. As such, CSR has evolved whereby practitioners have developed

CSR activities by sustaining value-creation for their customer-stakeholders. This, along with

the four verified hypotheses, unveiled the answer to the research question. And the study

was able to establish that the FC of 2007 has been a wake-up call for banks’ CSR activities to

resonate customers’ expectations and needs.

5.3. PRACTITIONER CONTRIBUTIONS

While the inclusion of stakeholders’ interests into business strategies can act as a point of

differentiation and be a source of sustainable competitive advantage (Fombrun, 1996 cited

in Nilsen, 2010), it is pivotal to map out the level of importance of CSR practices to fulfil

them accordingly. This was the case with regards to the difference in the order of the ethical

and philanthropic dimensions between Carroll CSR model and the empirical outcomes. For

the satisfaction avenue, philanthropic had preceded the ethical dimension, but was the

other way around for the case of the purchasing decision. In this context, while the level of

ethical CSR activities had a moderate importance on customer purchasing decision, the level

of customer satisfaction of perceived CSR ethical activities was the least fulfilled dimension.

This discrepancy can provide insights on the level of CSR efforts that need to be maintained

to, on one hand, capitalise on the core competences in how to be active in this dimension

and, on the other hand, achieve competitive advantage by attaching attributes favoured by

customer-stakeholders.

Furthermore, the mediation effect that CSR exerts on banks reputation to influence

customers’ purchasing decision can enhance their respective financial well-being and hence

achieve a pragmatic approach to CSR. While CSR can provide competitive advantages to a

business, if banks’ CSR motives are questionable, they could have far detrimental effects on

the business possibly amounting to customers exerting their purchasing influence as a

means of punishing them. Taken together, CSR can be considered the business’s compass

guiding them to develop societal activities that create value to both ends when fulfilling the

role that business was set out to achieve.

5.4. THEORETICAL CONTRIBUTIONS

These contributions are threefold. As emphasised in the introduction, CSR literature on the

financial sector is under-researched and, with regards to CSR marketing, there is a distinct

lack in investigating the effect of multiple CSR activities on customers’ attitudes. Given this,

the study’s intended contribution was to provide empirical findings to fill this void and

contribute to better understand one of the most contestable fields in contemporary

management. The application of strategic CSR can yield sustainable competitive advantages

if applied in tandem to the dynamics of social structure.

The second contribution stems from the study findings showing positive significant CSR-

customer relationships. This stresses that CSR became a management mainstream which

shed further light on the prominence of stakeholder orientation to shareholder. Moreover,

adhering to stakeholder approach resulted in the significant findings of this study from

which emerged the indirect impact of CSR on CR and hence customer purchase behaviour.

This in turn have an effect on business economic ends.

The debate on whether CSR should be abandoned is no longer valid. However, the focus

should be on what kind of benefits businesses can capitalise on to leverage efficient CSR

practices and adoption. As for the third contribution, the stakeholder modus operandi

attribute provides a systematic framework approach to the CSR literature which helps

mapping out stakeholders’ needs.

5.5. RECOMMENDATIONS FOR FUTURE RESEARCH AND RESEARCH LIMITATIONS

This study provided new insights in CSR topics by arguing the indirect effect of CSR in

yielding competitive advantage that gives credence to the business case for CSR. As the field

of banking and CSR-CR is relatively a new one, research in many avenues on CSR can be

unlocked. One interesting area in investigating the business case for CSR is that of CSR

mediation effect. Another avenue is to investigate multiple CSR domains on different

customer attitudes as, so far, most extant studies offer very limited insights into customers’

attitudes relative to one or two dimensions of CSR.

Regarding stakeholder approach, the focus-to-date has been limited to customers and

employees whereas other stakeholders could influence business performance in different

ways. This would provide better understanding of the field therefore a replication of this

study in other contexts is noteworthy as well as extending it into other countries.

Nevertheless, the results are quite robust. The study’s drawback stems from the

employment of a non-random sampling technique. This could represent a study limitation in

terms of generalizability. However, the response rate was 46% which led to in-depth

investigation considered representative of the population (Ismail et al, 2012).

As a final remark, all of the research objectives, as stated in Chapter 1, were met.

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Appendices

APPENDIX A – SURVEY EMAIL INVITATION

Dear (name of respondent),

I hope my email finds you well.

I am writing to you requesting the completion of a survey on CSR (Corporate Social Responsibility). It is part of my MBA Dissertation at University of West London Business School.

The research aims to investigate “Customer attitudes to the role of Corporate Social Responsibility (CSR) in the UK Banking Sector since the financial crisis in 2007”. The respondents need to have a UK Bank Account and the survey ensures that before continuing.

The survey is administered using Survey Monkey and, to complete the survey, you need to go to the following link:

https://www.surveymonkey.com/s/YL28TTG

The connection is secured and the survey ensures the confidentially of the information received. All data will be anonymous and no inferences regarding any individual will be made.

If you require more information or assistance or would like to receive a copy of the results please do not hesitate to contact me on my email address below.

Thank you for your assistance in this important research.

Best Regards,

_______________________

Amany Hamza

Executive MBA student at University of West London Business School

Email: [email protected]

https://www.surveymonkey.com/s/YL28TTG

mailto:[email protected]

APPENDIX B1 – SURVEY FIRST REMINDER


Thank you very much for those who completed the survey sent out on the 14th of July.

This is a reminder for those who haven’t been able to complete it yet. We’d appreciate it very much if you can complete it as soon as possible.

For any questions, please feel free to contact me on my email below.

Thank you very much for your cooperation.

Best Regards,

_______________________

Amany Hamza




APPENDIX B2 – SURVEY FINAL REMINDER


Thank you very much for those who completed the survey sent out on the 14th of July.

This is a reminder for those who haven’t been able to complete it yet. There is still a chance to complete and contribute to a research that could benefit of all us.

We’d appreciate it very much if you can complete the survey as soon as possible as we will be closing it by the 12th of August.

For any questions, please feel free to contact me on my email below.

Thank you very much for your cooperation.

Best Regards,

_______________________

Amany Hamza




APPENDIX C – SURVEY

APPENDIX D – ACRONYMS

CSR Corporate Social Responsibility

CR Corporate Reputation

DV Dependent Variable

EC&LG Economic & Legal

ECP&LGP Economic Practices & Legal Practices

ETP&PHP Ethical Practices & Philanthropic Practices

FC Financial Crisis

IV Independent Variable

KMO Kaiser-Meyer-Olkin

PCA Principle Component Analysis

PH&ET Philanthropic & Ethical

Appendix E- Research Objective one - Reliability Analysis 1

Reliability Statistics

Cronbach's Alpha

Cronbach's Alpha Based on

Standardized Items N of Items

.961 .962 33

Inter-Item Correlation Matrix

Q9Borrowings_And_Savings

Q9Transparency

Q9Financial_Statements Q9Offers


Q9Transparency

Q9Financial_Statements

Q9Offers

Q9Executive_Remuneration

Q9Financial_Inclusion_SMEbanking

Q9MeetCustomers_Needs

Q9Social_Attachment

Q9Confidentially

Q9Valued_Customer_Recognition

Q9Honest_Relationship

Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery

Q9Giving_Back_To_Community

Q9Financial_literacy

Q9Environmentally_branches

Q10

Q11

Q12Financial_Stability

Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality

Q12Personal_Information_Safe

Q12Fees

Q12Interest_Rates_Accounts

Q12Interest_Rates_Loan

1.000 .559 .533 .495 .407

.559 1.000 .553 .518 .467

.533 .553 1.000 .428 .215

.495 .518 .428 1.000 .291

.407 .467 .215 .291 1.000

.512 .478 .365 .328 .566

.503 .503 .434 .490 .468

.579 .502 .240 .330 .537

.520 .390 .452 .371 .388

.413 .484 .363 .383 .457

.559 .605 .473 .414 .584

.570 .580 .421 .440 .600

.563 .489 .550 .440 .516

.446 .374 .376 .290 .471

.457 .455 .215 .333 .474

.410 .341 .113 .202 .538

.514 .329 .198 .169 .486

.633 .660 .450 .492 .572

.492 .578 .408 .498 .445

.592 .539 .528 .395 .489

.448 .433 .442 .302 .329

.474 .616 .455 .453 .398

.510 .578 .461 .427 .451

.423 .338 .455 .260 .431

.523 .761 .519 .403 .442

.667 .583 .503 .392 .380

.513 .529 .450 .274 .378

.549 .480 .376 .355 .383



Q9Financial_Inclusion_SMEba

nkingQ9MeetCustom

ers_Needs


Q9Transparency


Q9Offers




Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees



.407 .512 .503 .579

.467 .478 .503 .502

.215 .365 .434 .240

.291 .328 .490 .330

1.000 .566 .468 .537

.566 1.000 .609 .557

.468 .609 1.000 .455

.537 .557 .455 1.000

.388 .415 .520 .230

.457 .385 .614 .396

.584 .504 .595 .345

.600 .398 .605 .463

.516 .341 .438 .344

.471 .319 .427 .384

.474 .382 .561 .588

.538 .448 .431 .645

.486 .385 .392 .529

.572 .584 .573 .575

.445 .521 .694 .527

.489 .442 .592 .450

.329 .385 .441 .335

.398 .434 .679 .406

.451 .529 .666 .452

.431 .293 .370 .259

.442 .490 .568 .442

.380 .413 .492 .430

.378 .455 .524 .483

.383 .459 .403 .357


Q9Social_Attachment

Q9Confidentially

Q9Valued_Customer_Recogniti

on


Q9Transparency


Q9Offers




Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees



.579 .520 .413 .559

.502 .390 .484 .605

.240 .452 .363 .473

.330 .371 .383 .414

.537 .388 .457 .584

.557 .415 .385 .504

.455 .520 .614 .595

1.000 .230 .396 .345

.230 1.000 .506 .623

.396 .506 1.000 .700

.345 .623 .700 1.000

.463 .626 .624 .670

.344 .538 .494 .607

.384 .522 .510 .492

.588 .439 .629 .457

.645 .298 .489 .359

.529 .356 .402 .384

.575 .492 .410 .573

.527 .383 .474 .577

.450 .587 .427 .531

.335 .529 .393 .509

.406 .559 .675 .646

.452 .421 .677 .672

.259 .416 .375 .508

.442 .385 .464 .575

.430 .472 .462 .531

.483 .390 .448 .470

.357 .344 .351 .484



Q9Being_Accountable

Q9legal_Obligations


Q9Transparency


Q9Offers




Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees



.559 .570 .563 .446

.605 .580 .489 .374

.473 .421 .550 .376

.414 .440 .440 .290

.584 .600 .516 .471

.504 .398 .341 .319

.595 .605 .438 .427

.345 .463 .344 .384

.623 .626 .538 .522

.700 .624 .494 .510

1.000 .670 .607 .492

.670 1.000 .648 .596

.607 .648 1.000 .554

.492 .596 .554 1.000

.457 .627 .345 .542

.359 .459 .335 .332

.384 .504 .318 .379

.573 .595 .608 .398

.577 .513 .416 .321

.531 .600 .505 .385

.509 .399 .503 .464

.646 .599 .497 .472

.672 .595 .528 .421

.508 .348 .361 .395

.575 .525 .426 .329

.531 .488 .479 .409

.470 .393 .423 .352

.484 .474 .519 .275


Q9Combating_Bribery

Q9Giving_Back_To_Communit

yQ9Financial_lit

eracy


Q9Transparency


Q9Offers




Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees



.446 .457 .410 .514

.374 .455 .341 .329

.376 .215 .113 .198

.290 .333 .202 .169

.471 .474 .538 .486

.319 .382 .448 .385

.427 .561 .431 .392

.384 .588 .645 .529

.522 .439 .298 .356

.510 .629 .489 .402

.492 .457 .359 .384

.596 .627 .459 .504

.554 .345 .335 .318

1.000 .542 .332 .379

.542 1.000 .590 .594

.332 .590 1.000 .441

.379 .594 .441 1.000

.398 .411 .479 .455

.321 .438 .538 .343

.385 .492 .452 .477

.464 .411 .355 .399

.472 .493 .462 .465

.421 .487 .469 .502

.395 .318 .235 .370

.329 .445 .346 .377

.409 .396 .326 .397

.352 .435 .328 .501

.275 .352 .286 .442


Q9Environmentally_branches Q10 Q11



Q9Transparency


Q9Offers




Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees



.514 .633 .492 .592 .448

.329 .660 .578 .539 .433

.198 .450 .408 .528 .442

.169 .492 .498 .395 .302

.486 .572 .445 .489 .329

.385 .584 .521 .442 .385

.392 .573 .694 .592 .441

.529 .575 .527 .450 .335

.356 .492 .383 .587 .529

.402 .410 .474 .427 .393

.384 .573 .577 .531 .509

.504 .595 .513 .600 .399

.318 .608 .416 .505 .503

.379 .398 .321 .385 .464

.594 .411 .438 .492 .411

.441 .479 .538 .452 .355

1.000 .455 .343 .477 .399

.455 1.000 .670 .657 .530

.343 .670 1.000 .608 .486

.477 .657 .608 1.000 .546

.399 .530 .486 .546 1.000

.465 .647 .705 .567 .681

.502 .561 .623 .498 .560

.370 .380 .371 .549 .552

.377 .664 .721 .625 .540

.397 .591 .542 .561 .466

.501 .623 .543 .546 .441

.442 .587 .488 .494 .478


Q12Withdraw_Money Q12Treated

AQ12Advice_Quality


Q9Transparency


Q9Offers




Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees



.448 .474 .510 .423

.433 .616 .578 .338

.442 .455 .461 .455

.302 .453 .427 .260

.329 .398 .451 .431

.385 .434 .529 .293

.441 .679 .666 .370

.335 .406 .452 .259

.529 .559 .421 .416

.393 .675 .677 .375

.509 .646 .672 .508

.399 .599 .595 .348

.503 .497 .528 .361

.464 .472 .421 .395

.411 .493 .487 .318

.355 .462 .469 .235

.399 .465 .502 .370

.530 .647 .561 .380

.486 .705 .623 .371

.546 .567 .498 .549

1.000 .681 .560 .552

.681 1.000 .777 .432

.560 .777 1.000 .410

.552 .432 .410 1.000

.540 .706 .598 .491

.466 .599 .518 .428

.441 .598 .506 .450

.478 .528 .487 .365


Q12Personal_Information_Saf

e Q12FeesQ12Interest_Rates_Accounts



Q9Transparency


Q9Offers




Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees



.423 .523 .667 .513 .549

.338 .761 .583 .529 .480

.455 .519 .503 .450 .376

.260 .403 .392 .274 .355

.431 .442 .380 .378 .383

.293 .490 .413 .455 .459

.370 .568 .492 .524 .403

.259 .442 .430 .483 .357

.416 .385 .472 .390 .344

.375 .464 .462 .448 .351

.508 .575 .531 .470 .484

.348 .525 .488 .393 .474

.361 .426 .479 .423 .519

.395 .329 .409 .352 .275

.318 .445 .396 .435 .352

.235 .346 .326 .328 .286

.370 .377 .397 .501 .442

.380 .664 .591 .623 .587

.371 .721 .542 .543 .488

.549 .625 .561 .546 .494

.552 .540 .466 .441 .478

.432 .706 .599 .598 .528

.410 .598 .518 .506 .487

1.000 .491 .428 .450 .365

.491 1.000 .762 .735 .670

.428 .762 1.000 .792 .627

.450 .735 .792 1.000 .631

.365 .670 .627 .631 1.000


Q12Open_Or_Close_Branche

s Q13 Q14 Q16 Q17


Q9Transparency


Q9Offers




Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees



.549 .482 .490 .115 .492 .245

.480 .595 .458 .094 .448 .266

.376 .415 .448 .241 .472 .219

.355 .357 .360 -.075 .368 .174

.383 .566 .553 -.217 .411 .171

.459 .598 .444 -.049 .370 .186

.403 .518 .540 .093 .412 .222

.357 .607 .393 -.028 .525 .141

.344 .368 .388 .185 .364 .253

.351 .534 .474 -.056 .350 .185

.484 .562 .544 .042 .452 .225

.474 .533 .561 .075 .545 .193

.519 .519 .463 .119 .360 .177

.275 .423 .442 .073 .409 .208

.352 .528 .526 .074 .421 .241

.286 .557 .404 -.095 .405 .145

.442 .400 .327 .122 .472 .192

.587 .701 .531 .105 .458 .255

.488 .604 .424 .082 .430 .140

.494 .548 .492 .178 .471 .299

.478 .407 .373 .303 .297 .205

.528 .559 .478 .150 .509 .290

.487 .523 .514 .118 .534 .264

.365 .301 .334 .108 .248 .171

.670 .562 .465 .204 .375 .139

.627 .442 .460 .126 .388 .126

.631 .540 .416 .142 .330 .144

1.000 .466 .473 .154 .357 .035


Q18


Q9Transparency


Q9Offers




Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees



.245

.266

.219

.174

.171

.186

.222

.141

.253

.185

.225

.193

.177

.208

.241

.145

.192

.255

.140

.299

.205

.290

.264

.171

.139

.126

.144

.035Inter-Item Correlation Matrix


Q9Transparency


Q12Open_Or_Close_Branches

Q13

Q14

Q16

Q17

Q18

.549 .480 .376 .355 .383

.482 .595 .415 .357 .566

.490 .458 .448 .360 .553

.115 .094 .241 -.075 -.217

.492 .448 .472 .368 .411

.245 .266 .219 .174 .171




nkingQ9MeetCustom

ers_Needs


Q13

Q14

Q16

Q17

Q18

.383 .459 .403 .357

.566 .598 .518 .607

.553 .444 .540 .393

-.217 -.049 .093 -.028

.411 .370 .412 .525

.171 .186 .222 .141


Q9Social_Attachment

Q9Confidentially


on


Q13

Q14

Q16

Q17

Q18

.357 .344 .351 .484

.607 .368 .534 .562

.393 .388 .474 .544

-.028 .185 -.056 .042

.525 .364 .350 .452

.141 .253 .185 .225



Q9Being_Accountable

Q9legal_Obligations


Q13

Q14

Q16

Q17

Q18

.484 .474 .519 .275

.562 .533 .519 .423

.544 .561 .463 .442

.042 .075 .119 .073

.452 .545 .360 .409

.225 .193 .177 .208


Q9Combating_Bribery


yQ9Financial_lit

eracy


Q13

Q14

Q16

Q17

Q18

.275 .352 .286 .442

.423 .528 .557 .400

.442 .526 .404 .327

.073 .074 -.095 .122

.409 .421 .405 .472

.208 .241 .145 .192





Q13

Q14

Q16

Q17

Q18

.442 .587 .488 .494 .478

.400 .701 .604 .548 .407

.327 .531 .424 .492 .373

.122 .105 .082 .178 .303

.472 .458 .430 .471 .297

.192 .255 .140 .299 .205



AQ12Advice_Quality


Q13

Q14

Q16

Q17

Q18

.478 .528 .487 .365

.407 .559 .523 .301

.373 .478 .514 .334

.303 .150 .118 .108

.297 .509 .534 .248

.205 .290 .264 .171






Q13

Q14

Q16

Q17

Q18

.365 .670 .627 .631 1.000

.301 .562 .442 .540 .466

.334 .465 .460 .416 .473

.108 .204 .126 .142 .154

.248 .375 .388 .330 .357

.171 .139 .126 .144 .035



s Q13 Q14 Q16 Q17


Q13

Q14

Q16

Q17

Q18

1.000 .466 .473 .154 .357 .035

.466 1.000 .639 -.091 .413 .110

.473 .639 1.000 .010 .573 .158

.154 -.091 .010 1.000 .195 .254

.357 .413 .573 .195 1.000 .339

.035 .110 .158 .254 .339 1.000


Q18


Q13

Q14

Q16

Q17

Q18

.035

.110

.158

.254

.339

1.000

Item-Total Statistics

Scale Mean if Item Deleted

Scale Variance if Item Deleted

Corrected Item-Total

Correlation


Q9Transparency


Q9Offers




Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees



101.18 396.570 .732 .

100.87 395.631 .728 .

100.63 402.214 .596 .

100.96 402.504 .528 .

101.58 401.983 .630 .

101.46 404.229 .626 .

101.30 394.214 .740 .

101.62 401.051 .621 .

100.75 400.717 .639 .

101.26 396.700 .674 .

100.99 395.000 .761 .

101.21 392.363 .760 .

100.90 399.540 .669 .

101.11 403.219 .592 .

101.60 400.573 .658 .

101.66 403.962 .559 .

101.48 401.483 .584 .

101.21 396.869 .790 .

101.21 391.792 .727 .

100.78 394.919 .754 .

100.39 401.779 .648 .

100.70 391.203 .800 .

101.02 393.252 .767 .

100.64 402.628 .542 .

100.84 394.687 .762 .

100.87 394.950 .710 .

101.03 398.977 .688 .

101.14 398.298 .635 .


Squared Multiple

Correlation

Cronbach's Alpha if Item

Deleted


Q9Transparency


Q9Offers




Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees



. .959

. .959

. .960

. .960

. .960

. .960

. .959

. .960

. .960

. .959

. .959

. .959

. .960

. .960

. .960

. .960

. .960

. .959

. .959

. .959

. .960

. .959

. .959

. .960

. .959

. .959

. .959

. .960Item-Total Statistics




Correlation


Q13

Q14

Q16

Q17

Q18

101.14 398.298 .635 .

101.52 403.615 .709 .

101.35 397.746 .656 .

100.48 418.296 .132 .

101.51 395.923 .615 .

101.80 408.313 .293 .


Squared Multiple

Correlation


Deleted


Q13

Q14

Q16

Q17

Q18

. .960

. .960

. .960

. .963

. .960

. .963

Appendix F - Research Objective one - Factor Analysis-before components extraction

Correlation Matrixa


Q9Transparency

Correlation Q9Borrowings_And_Savings

Q9Transparency1.000 .559 .533

.559 1.000 .553

.533 .553 1.000Correlation Matrixa



Q9Transparency.533 .495 .407

.553 .518 .467

1.000 .428 .215Correlation Matrixa



nking



.467 .478 .503

.215 .365 .434Correlation Matrixa


Q9Social_Attachment



.503 .502 .390


Q9Confidentially


on



.390 .484 .605

.452 .363 .473

Correlation Matrixa


Q9Being_Accountable



.605 .580 .489


Q9legal_Obligations

Q9Combating_Bribery



.489 .374 .455



yQ9Financial_lit

eracy



.455 .341 .329




Q9Transparency.514 .633 .492 .592

.329 .660 .578 .539

.198 .450 .408 .528Correlation Matrixa


Q12Withdraw_Money



.539 .433 .616


Q12TreatedAQ12Advice_Q

uality



.616 .578 .338

.455 .461 .455

Correlation Matrixa


e Q12Fees



.338 .761 .583






.583 .529 .480



s Q13 Q14


Q9Transparency.549 .482 .490 .115

.480 .595 .458 .094

.376 .415 .448 .241Correlation Matrixa

Q16 Q17 Q18



.094 .448 .266

.241 .472 .219

Correlation Matrixa


Q9Transparency

Correlation


Q9Offers




Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees




Q13

Q14

Q16

Q17

Q18

Sig. (1-tailed) Q9Borrowings_And_Savings

Q9Transparency


Q9Offers




.533 .553 1.000

.495 .518 .428

.407 .467 .215

.512 .478 .365

.503 .503 .434

.579 .502 .240

.520 .390 .452

.413 .484 .363

.559 .605 .473

.570 .580 .421

.563 .489 .550

.446 .374 .376

.457 .455 .215

.410 .341 .113

.514 .329 .198

.633 .660 .450

.492 .578 .408

.592 .539 .528

.448 .433 .442

.474 .616 .455

.510 .578 .461

.423 .338 .455

.523 .761 .519

.667 .583 .503

.513 .529 .450

.549 .480 .376

.482 .595 .415

.490 .458 .448

.115 .094 .241

.492 .448 .472

.245 .266 .219

.000 .000

.000 .000

.000 .000

.000 .000 .000

.000 .000 .020

.000 .000 .000

.000 .000 .000

.000 .011

Correlation Matrixa


Correlation


Q9Offers




Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees




Q13

Q14

Q16

Q17

Q18


Q9Transparency


Q9Offers




1.000 .428 .215

.428 1.000 .291

.215 .291 1.000

.365 .328 .566

.434 .490 .468

.240 .330 .537

.452 .371 .388

.363 .383 .457

.473 .414 .584

.421 .440 .600

.550 .440 .516

.376 .290 .471

.215 .333 .474

.113 .202 .538

.198 .169 .486

.450 .492 .572

.408 .498 .445

.528 .395 .489

.442 .302 .329

.455 .453 .398

.461 .427 .451

.455 .260 .431

.519 .403 .442

.503 .392 .380

.450 .274 .378

.376 .355 .383

.415 .357 .566

.448 .360 .553

.241 -.075 -.217

.472 .368 .411

.219 .174 .171

.000 .000 .000

.000 .000 .000

.000 .020

.000 .002

.020 .002

.000 .001 .000

.000 .000 .000

.011 .001 .000

Correlation Matrixa



nking

Correlation


Q9Offers




Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees




Q13

Q14

Q16

Q17

Q18


Q9Transparency


Q9Offers




.215 .365 .434

.291 .328 .490

1.000 .566 .468

.566 1.000 .609

.468 .609 1.000

.537 .557 .455

.388 .415 .520

.457 .385 .614

.584 .504 .595

.600 .398 .605

.516 .341 .438

.471 .319 .427

.474 .382 .561

.538 .448 .431

.486 .385 .392

.572 .584 .573

.445 .521 .694

.489 .442 .592

.329 .385 .441

.398 .434 .679

.451 .529 .666

.431 .293 .370

.442 .490 .568

.380 .413 .492

.378 .455 .524

.383 .459 .403

.566 .598 .518

.553 .444 .540

-.217 -.049 .093

.411 .370 .412

.171 .186 .222

.000 .000 .000

.000 .000 .000

.020 .000 .000

.002 .001 .000

.000 .000

.000 .000

.000 .000

.000 .000

Correlation Matrixa


Q9Social_Attachment

Correlation


Q9Offers




Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees




Q13

Q14

Q16

Q17

Q18


Q9Transparency


Q9Offers




.434 .240 .452

.490 .330 .371

.468 .537 .388

.609 .557 .415

1.000 .455 .520

.455 1.000 .230

.520 .230 1.000

.614 .396 .506

.595 .345 .623

.605 .463 .626

.438 .344 .538

.427 .384 .522

.561 .588 .439

.431 .645 .298

.392 .529 .356

.573 .575 .492

.694 .527 .383

.592 .450 .587

.441 .335 .529

.679 .406 .559

.666 .452 .421

.370 .259 .416

.568 .442 .385

.492 .430 .472

.524 .483 .390

.403 .357 .344

.518 .607 .368

.540 .393 .388

.093 -.028 .185

.412 .525 .364

.222 .141 .253

.000 .000 .000

.000 .000 .000

.000 .011 .000

.000 .001 .000

.000 .000 .000

.000 .000 .000

.000 .000

.000 .014

Correlation Matrixa

Q9Confidentially


on

Correlation


Q9Offers




Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees




Q13

Q14

Q16

Q17

Q18


Q9Transparency


Q9Offers




.452 .363 .473

.371 .383 .414

.388 .457 .584

.415 .385 .504

.520 .614 .595

.230 .396 .345

1.000 .506 .623

.506 1.000 .700

.623 .700 1.000

.626 .624 .670

.538 .494 .607

.522 .510 .492

.439 .629 .457

.298 .489 .359

.356 .402 .384

.492 .410 .573

.383 .474 .577

.587 .427 .531

.529 .393 .509

.559 .675 .646

.421 .677 .672

.416 .375 .508

.385 .464 .575

.472 .462 .531

.390 .448 .470

.344 .351 .484

.368 .534 .562

.388 .474 .544

.185 -.056 .042

.364 .350 .452

.253 .185 .225

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.014 .000

Correlation Matrixa


Q9Being_Accountable

Correlation


Q9Offers




Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees




Q13

Q14

Q16

Q17

Q18


Q9Transparency


Q9Offers




.473 .421 .550

.414 .440 .440

.584 .600 .516

.504 .398 .341

.595 .605 .438

.345 .463 .344

.623 .626 .538

.700 .624 .494

1.000 .670 .607

.670 1.000 .648

.607 .648 1.000

.492 .596 .554

.457 .627 .345

.359 .459 .335

.384 .504 .318

.573 .595 .608

.577 .513 .416

.531 .600 .505

.509 .399 .503

.646 .599 .497

.672 .595 .528

.508 .348 .361

.575 .525 .426

.531 .488 .479

.470 .393 .423

.484 .474 .519

.562 .533 .519

.544 .561 .463

.042 .075 .119

.452 .545 .360

.225 .193 .177

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000

Correlation Matrixa

Q9legal_Obligations

Q9Combating_Bribery

Correlation


Q9Offers




Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees




Q13

Q14

Q16

Q17

Q18


Q9Transparency


Q9Offers




.550 .376 .215

.440 .290 .333

.516 .471 .474

.341 .319 .382

.438 .427 .561

.344 .384 .588

.538 .522 .439

.494 .510 .629

.607 .492 .457

.648 .596 .627

1.000 .554 .345

.554 1.000 .542

.345 .542 1.000

.335 .332 .590

.318 .379 .594

.608 .398 .411

.416 .321 .438

.505 .385 .492

.503 .464 .411

.497 .472 .493

.528 .421 .487

.361 .395 .318

.426 .329 .445

.479 .409 .396

.423 .352 .435

.519 .275 .352

.519 .423 .528

.463 .442 .526

.119 .073 .074

.360 .409 .421

.177 .208 .241

.000 .000 .000

.000 .000 .000

.000 .000 .020

.000 .002 .001

.000 .000 .000

.000 .001 .000

.000 .000 .000

.000 .000

Correlation Matrixa


yQ9Financial_lit

eracy

Correlation


Q9Offers




Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees




Q13

Q14

Q16

Q17

Q18


Q9Transparency


Q9Offers




.215 .113 .198

.333 .202 .169

.474 .538 .486

.382 .448 .385

.561 .431 .392

.588 .645 .529

.439 .298 .356

.629 .489 .402

.457 .359 .384

.627 .459 .504

.345 .335 .318

.542 .332 .379

1.000 .590 .594

.590 1.000 .441

.594 .441 1.000

.411 .479 .455

.438 .538 .343

.492 .452 .477

.411 .355 .399

.493 .462 .465

.487 .469 .502

.318 .235 .370

.445 .346 .377

.396 .326 .397

.435 .328 .501

.352 .286 .442

.528 .557 .400

.526 .404 .327

.074 -.095 .122

.421 .405 .472

.241 .145 .192

.000 .000 .000

.000 .000 .001

.020 .142 .029

.001 .027 .054

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000

Correlation Matrixa


Correlation


Q9Offers




Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees




Q13

Q14

Q16

Q17

Q18


Q9Transparency


Q9Offers




.198 .450 .408 .528

.169 .492 .498 .395

.486 .572 .445 .489

.385 .584 .521 .442

.392 .573 .694 .592

.529 .575 .527 .450

.356 .492 .383 .587

.402 .410 .474 .427

.384 .573 .577 .531

.504 .595 .513 .600

.318 .608 .416 .505

.379 .398 .321 .385

.594 .411 .438 .492

.441 .479 .538 .452

1.000 .455 .343 .477

.455 1.000 .670 .657

.343 .670 1.000 .608

.477 .657 .608 1.000

.399 .530 .486 .546

.465 .647 .705 .567

.502 .561 .623 .498

.370 .380 .371 .549

.377 .664 .721 .625

.397 .591 .542 .561

.501 .623 .543 .546

.442 .587 .488 .494

.400 .701 .604 .548

.327 .531 .424 .492

.122 .105 .082 .178

.472 .458 .430 .471

.192 .255 .140 .299

.000 .000 .000 .000

.001 .000 .000 .000

.029 .000 .000 .000

.054 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000

Correlation Matrixa


Q12Withdraw_Money

Correlation


Q9Offers




Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees




Q13

Q14

Q16

Q17

Q18


Q9Transparency


Q9Offers




.528 .442 .455

.395 .302 .453

.489 .329 .398

.442 .385 .434

.592 .441 .679

.450 .335 .406

.587 .529 .559

.427 .393 .675

.531 .509 .646

.600 .399 .599

.505 .503 .497

.385 .464 .472

.492 .411 .493

.452 .355 .462

.477 .399 .465

.657 .530 .647

.608 .486 .705

1.000 .546 .567

.546 1.000 .681

.567 .681 1.000

.498 .560 .777

.549 .552 .432

.625 .540 .706

.561 .466 .599

.546 .441 .598

.494 .478 .528

.548 .407 .559

.492 .373 .478

.178 .303 .150

.471 .297 .509

.299 .205 .290

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .002 .000

.000 .001 .000

.000 .000 .000

.000 .000 .000

.000 .000

Correlation Matrixa


uality

Correlation


Q9Offers




Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees




Q13

Q14

Q16

Q17

Q18


Q9Transparency


Q9Offers




.455 .461 .455

.453 .427 .260

.398 .451 .431

.434 .529 .293

.679 .666 .370

.406 .452 .259

.559 .421 .416

.675 .677 .375

.646 .672 .508

.599 .595 .348

.497 .528 .361

.472 .421 .395

.493 .487 .318

.462 .469 .235

.465 .502 .370

.647 .561 .380

.705 .623 .371

.567 .498 .549

.681 .560 .552

1.000 .777 .432

.777 1.000 .410

.432 .410 1.000

.706 .598 .491

.599 .518 .428

.598 .506 .450

.528 .487 .365

.559 .523 .301

.478 .514 .334

.150 .118 .108

.509 .534 .248

.290 .264 .171

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .006

.000 .000 .000

.000 .000 .002

.000 .000 .000

.000 .000 .006

Correlation Matrixa


e Q12Fees

Correlation


Q9Offers




Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees




Q13

Q14

Q16

Q17

Q18


Q9Transparency


Q9Offers




.455 .519 .503

.260 .403 .392

.431 .442 .380

.293 .490 .413

.370 .568 .492

.259 .442 .430

.416 .385 .472

.375 .464 .462

.508 .575 .531

.348 .525 .488

.361 .426 .479

.395 .329 .409

.318 .445 .396

.235 .346 .326

.370 .377 .397

.380 .664 .591

.371 .721 .542

.549 .625 .561

.552 .540 .466

.432 .706 .599

.410 .598 .518

1.000 .491 .428

.491 1.000 .762

.428 .762 1.000

.450 .735 .792

.365 .670 .627

.301 .562 .442

.334 .465 .460

.108 .204 .126

.248 .375 .388

.171 .139 .126

.000 .000 .000

.000 .000 .000

.000 .000 .000

.006 .000 .000

.000 .000 .000

.002 .000 .000

.000 .000 .000

.006 .000 .000

Correlation Matrixa



Correlation


Q9Offers




Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees




Q13

Q14

Q16

Q17

Q18


Q9Transparency


Q9Offers




.503 .450 .376

.392 .274 .355

.380 .378 .383

.413 .455 .459

.492 .524 .403

.430 .483 .357

.472 .390 .344

.462 .448 .351

.531 .470 .484

.488 .393 .474

.479 .423 .519

.409 .352 .275

.396 .435 .352

.326 .328 .286

.397 .501 .442

.591 .623 .587

.542 .543 .488

.561 .546 .494

.466 .441 .478

.599 .598 .528

.518 .506 .487

.428 .450 .365

.762 .735 .670

1.000 .792 .627

.792 1.000 .631

.627 .631 1.000

.442 .540 .466

.460 .416 .473

.126 .142 .154

.388 .330 .357

.126 .144 .035

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .004 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000

Correlation Matrixa


s Q13 Q14

Correlation


Q9Offers




Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees




Q13

Q14

Q16

Q17

Q18


Q9Transparency


Q9Offers




.376 .415 .448 .241

.355 .357 .360 -.075

.383 .566 .553 -.217

.459 .598 .444 -.049

.403 .518 .540 .093

.357 .607 .393 -.028

.344 .368 .388 .185

.351 .534 .474 -.056

.484 .562 .544 .042

.474 .533 .561 .075

.519 .519 .463 .119

.275 .423 .442 .073

.352 .528 .526 .074

.286 .557 .404 -.095

.442 .400 .327 .122

.587 .701 .531 .105

.488 .604 .424 .082

.494 .548 .492 .178

.478 .407 .373 .303

.528 .559 .478 .150

.487 .523 .514 .118

.365 .301 .334 .108

.670 .562 .465 .204

.627 .442 .460 .126

.631 .540 .416 .142

1.000 .466 .473 .154

.466 1.000 .639 -.091

.473 .639 1.000 .010

.154 -.091 .010 1.000

.357 .413 .573 .195

.035 .110 .158 .254

.000 .000 .000 .138

.000 .000 .000 .187

.000 .000 .000 .010

.000 .000 .000 .237

.000 .000 .000 .019

.000 .000 .000 .321

.000 .000 .000 .190

.000 .000 .397

Correlation Matrixa

Q16 Q17 Q18

Correlation


Q9Offers




Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees




Q13

Q14

Q16

Q17

Q18


Q9Transparency


Q9Offers




.241 .472 .219

-.075 .368 .174

-.217 .411 .171

-.049 .370 .186

.093 .412 .222

-.028 .525 .141

.185 .364 .253

-.056 .350 .185

.042 .452 .225

.075 .545 .193

.119 .360 .177

.073 .409 .208

.074 .421 .241

-.095 .405 .145

.122 .472 .192

.105 .458 .255

.082 .430 .140

.178 .471 .299

.303 .297 .205

.150 .509 .290

.118 .534 .264

.108 .248 .171

.204 .375 .139

.126 .388 .126

.142 .330 .144

.154 .357 .035

-.091 .413 .110

.010 .573 .158

1.000 .195 .254

.195 1.000 .339

.254 .339 1.000

.138 .000 .009

.187 .000 .005

.010 .000 .018

.237 .000 .048

.019 .000 .051

.321 .000 .038

.190 .000 .017

.397 .000

Correlation Matrixa


Q9Transparency

Sig. (1-tailed)

Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees




Q13

Q14

Q16

Q17

Q18

.000 .000 .011

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .020

.000 .000 .142

.000 .001 .029

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.138 .187 .010

.000 .000 .000

.009 .005 .018

Correlation Matrixa


Sig. (1-tailed)

Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees




Q13

Q14

Q16

Q17

Q18

.011 .001 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .002 .000

.020 .001 .000

.142 .027 .000

.029 .054 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .002 .001

.000 .000 .000

.000 .000 .000

.000 .006 .000

.000 .000 .000

.000 .000 .000

.000 .004 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.010 .237 .019

.000 .000 .000

.018 .048 .051

Correlation Matrixa



nking

Sig. (1-tailed)

Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees




Q13

Q14

Q16

Q17

Q18

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .001 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.001 .000 .000

.000 .000 .000

.000 .000 .000

.000 .002 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.019 .321 .190

.000 .000 .000

.051 .038 .017

Correlation Matrixa


Q9Social_Attachment

Sig. (1-tailed)

Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees




Q13

Q14

Q16

Q17

Q18

.000 .014

.000 .014

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .002

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .001 .000

.000 .000 .000

.000 .000 .000

.000 .006 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.190 .397 .039

.000 .000 .000

.017 .090 .007

Correlation Matrixa

Q9Confidentially


on

Sig. (1-tailed)

Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees




Q13

Q14

Q16

Q17

Q18

.014 .000 .000

.000 .000

.000 .000

.000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.002 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.039 .297 .345

.000 .000 .000

.007 .038 .015

Correlation Matrixa


Q9Being_Accountable

Sig. (1-tailed)

Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees




Q13

Q14

Q16

Q17

Q18

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000

.000 .000

.000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .001

.000 .000 .001

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.345 .239 .128

.000 .000 .000

.015 .033 .046

Correlation Matrixa

Q9legal_Obligations

Q9Combating_Bribery

Sig. (1-tailed)

Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees




Q13

Q14

Q16

Q17

Q18

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000

.000 .000

.000 .000

.001 .001 .000

.001 .000 .000

.000 .000 .000

.000 .001 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .001

.000 .001 .000

.000 .000 .000

.000 .000 .000

.000 .004 .000

.000 .000 .000

.000 .000 .000

.128 .246 .242

.000 .000 .000

.046 .023 .010

Correlation Matrixa


yQ9Financial_lit

eracy

Sig. (1-tailed)

Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees




Q13

Q14

Q16

Q17

Q18

.000 .000 .000

.000 .002 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .001 .001

.000 .001 .000

.000 .000

.000 .000

.000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.001 .012 .000

.000 .000 .000

.000 .001 .000

.000 .001 .000

.000 .003 .000

.000 .000 .000

.000 .000 .001

.242 .183 .123

.000 .000 .000

.010 .084 .033

Correlation Matrixa


Sig. (1-tailed)

Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees




Q13

Q14

Q16

Q17

Q18

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.001 .000 .000 .000

.000 .000 .001 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.001 .000 .000 .000

.123 .160 .219 .045

.000 .000 .000 .000

.033 .007 .092 .002

Correlation Matrixa


Q12Withdraw_Money

Sig. (1-tailed)

Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees




Q13

Q14

Q16

Q17

Q18

.000 .001 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000

.000 .000

.000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.045 .002 .077

.000 .002 .000

.002 .025 .002

Correlation Matrixa


uality

Sig. (1-tailed)

Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees




Q13

Q14

Q16

Q17

Q18

.000 .000 .006

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .001

.000 .000 .012

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000

.000 .000

.000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .002

.000 .000 .001

.077 .131 .152

.000 .000 .009

.002 .005 .051

Correlation Matrixa


e Q12Fees

Sig. (1-tailed)

Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees




Q13

Q14

Q16

Q17

Q18

.006 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .001 .000

.001 .000 .000

.012 .000 .001

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000

.000 .000

.000 .000

.000 .000 .000

.000 .000 .000

.002 .000 .000

.001 .000 .000

.152 .026 .117

.009 .000 .000

.051 .093 .115

Correlation Matrixa



Sig. (1-tailed)

Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees




Q13

Q14

Q16

Q17

Q18

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .004

.000 .000 .000

.001 .001 .003

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000

.000 .000

.000 .000

.000 .000 .000

.000 .000 .000

.117 .088 .072

.000 .001 .000

.115 .086 .370

Correlation Matrixa


s Q13 Q14

Sig. (1-tailed)

Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees




Q13

Q14

Q16

Q17

Q18

.000 .000 .000 .397

.000 .000 .000 .039

.000 .000 .000 .297

.000 .000 .000 .345

.000 .000 .000 .239

.000 .000 .000 .128

.004 .000 .000 .246

.000 .000 .000 .242

.003 .000 .000 .183

.000 .000 .001 .123

.000 .000 .000 .160

.000 .000 .000 .219

.000 .000 .000 .045

.000 .000 .000 .002

.000 .000 .000 .077

.000 .000 .000 .131

.000 .002 .001 .152

.000 .000 .000 .026

.000 .000 .000 .117

.000 .000 .000 .088

.000 .000 .072

.000 .000 .195

.000 .000 .462

.072 .195 .462

.000 .000 .000 .031

.370 .147 .066 .007

Correlation Matrixa

Q16 Q17 Q18

Sig. (1-tailed)

Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees




Q13

Q14

Q16

Q17

Q18

.397 .000 .090

.039 .000 .007

.297 .000 .038

.345 .000 .015

.239 .000 .033

.128 .000 .046

.246 .000 .023

.242 .000 .010

.183 .000 .084

.123 .000 .033

.160 .000 .007

.219 .000 .092

.045 .000 .002

.002 .002 .025

.077 .000 .002

.131 .000 .005

.152 .009 .051

.026 .000 .093

.117 .000 .115

.088 .001 .086

.072 .000 .370

.195 .000 .147

.462 .000 .066

.031 .007

.031 .000

.007 .000

Determinant = 1.62E-013a.

KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy.

Bartlett's Test of Sphericity Approx. Chi-Square

df

Sig.

.896

2331.783

528

.000

Communalities

Initial Extraction


Q9Transparency


Q9Offers




Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees




Q13

Q14

Q16

Q17

Q18

1.000 .695

1.000 .681

1.000 .693

1.000 .598

1.000 .704

1.000 .541

1.000 .701

1.000 .774

1.000 .653

1.000 .776

1.000 .742

1.000 .727

1.000 .690

1.000 .641

1.000 .705

1.000 .693

1.000 .701

1.000 .739

1.000 .762

1.000 .631

1.000 .634

1.000 .843

1.000 .728

1.000 .533

1.000 .848

1.000 .723

1.000 .755

1.000 .661

1.000 .690

1.000 .554

1.000 .717

1.000 .672

1.000 .583

Extraction Method: Principal Component Analysis.

Total Variance Explained

Component

Initial Eigenvalues Extraction Sums of Squared LoadingsTotal % of Variance Cumulative % Total % of Variance Cumulative %

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

15.465 46.863 46.863 15.465 46.863 46.863

2.022 6.127 52.990 2.022 6.127 52.990

1.610 4.877 57.867 1.610 4.877 57.867

1.371 4.154 62.021 1.371 4.154 62.021

1.194 3.618 65.640 1.194 3.618 65.640

1.124 3.407 69.047 1.124 3.407 69.047

.911 2.759 71.806

.792 2.400 74.206

.774 2.346 76.552

.708 2.145 78.697

.683 2.070 80.767

.665 2.016 82.783

.629 1.905 84.689

.539 1.634 86.322

.531 1.610 87.932

.485 1.471 89.403

.441 1.336 90.739

.436 1.322 92.061

.338 1.024 93.085

.317 .962 94.047

.297 .899 94.946

.234 .708 95.655

.223 .677 96.331

.198 .599 96.931

.170 .516 97.447

.158 .478 97.925

.144 .436 98.360

.125 .378 98.738

.110 .333 99.071

.088 .267 99.338

.084 .253 99.591

.073 .222 99.814

.061 .186 100.000


Component Number

333231302928272625242322212019181716151413121110987654321

Eig

enva

lue

20

15

10

5

0

Scree Plot

Appendix F - Research Objective one - Factor Analysis-beforecomponents extraction

Correlation Matrixa


Q9Transparency



Q9Transparency


Q9OffersQ9Executive_Remuneration



Q9Social_Attachment

Q9ConfidentiallyQ9Valued_Customer_Recognition


Q9Being_Accountable

Q9legal_Obligations

Q9Combating_BriberyQ9Giving_Back_To_Community

Q9Financial_literacyQ9Environmentally_branches

1.000 .559 .533 .495 .407

.559 1.000 .553 .518 .467

.533 .553 1.000 .428 .215

.495 .518 .428 1.000 .291

.407 .467 .215 .291 1.000

.512 .478 .365 .328 .566

.503 .503 .434 .490 .468

.579 .502 .240 .330 .537

.520 .390 .452 .371 .388

.413 .484 .363 .383 .457

.559 .605 .473 .414 .584

.570 .580 .421 .440 .600

.563 .489 .550 .440 .516

.446 .374 .376 .290 .471

.457 .455 .215 .333 .474

.410 .341 .113 .202 .538

.514 .329 .198 .169 .486

.633 .660 .450 .492 .572

Correlation Matrixa



nkingQ9MeetCustom

ers_Needs


Q9Transparency





Q9Social_Attachment



Q9Being_Accountable

Q9legal_Obligations



.407 .512 .503 .579

.467 .478 .503 .502

.215 .365 .434 .240

.291 .328 .490 .330

1.000 .566 .468 .537

.566 1.000 .609 .557

.468 .609 1.000 .455

.537 .557 .455 1.000

.388 .415 .520 .230

.457 .385 .614 .396

.584 .504 .595 .345

.600 .398 .605 .463

.516 .341 .438 .344

.471 .319 .427 .384

.474 .382 .561 .588

.538 .448 .431 .645

.486 .385 .392 .529

.572 .584 .573 .575

Correlation Matrixa

Q9Social_Attachment

Q9Confidentially


on


Q9Transparency





Q9Social_Attachment



Q9Being_Accountable

Q9legal_Obligations



.579 .520 .413 .559

.502 .390 .484 .605

.240 .452 .363 .473

.330 .371 .383 .414

.537 .388 .457 .584

.557 .415 .385 .504

.455 .520 .614 .595

1.000 .230 .396 .345

.230 1.000 .506 .623

.396 .506 1.000 .700

.345 .623 .700 1.000

.463 .626 .624 .670

.344 .538 .494 .607

.384 .522 .510 .492

.588 .439 .629 .457

.645 .298 .489 .359

.529 .356 .402 .384

.575 .492 .410 .573

Correlation Matrixa


Q9Being_Accountable

Q9legal_Obligations


Q9Transparency





Q9Social_Attachment



Q9Being_Accountable

Q9legal_Obligations



.559 .570 .563 .446

.605 .580 .489 .374

.473 .421 .550 .376

.414 .440 .440 .290

.584 .600 .516 .471

.504 .398 .341 .319

.595 .605 .438 .427

.345 .463 .344 .384

.623 .626 .538 .522

.700 .624 .494 .510

1.000 .670 .607 .492

.670 1.000 .648 .596

.607 .648 1.000 .554

.492 .596 .554 1.000

.457 .627 .345 .542

.359 .459 .335 .332

.384 .504 .318 .379

.573 .595 .608 .398

Correlation Matrixa

Q9Combating_Bribery


yQ9Financial_lit

eracy


Q9Transparency





Q9Social_Attachment



Q9Being_Accountable

Q9legal_Obligations



.446 .457 .410 .514

.374 .455 .341 .329

.376 .215 .113 .198

.290 .333 .202 .169

.471 .474 .538 .486

.319 .382 .448 .385

.427 .561 .431 .392

.384 .588 .645 .529

.522 .439 .298 .356

.510 .629 .489 .402

.492 .457 .359 .384

.596 .627 .459 .504

.554 .345 .335 .318

1.000 .542 .332 .379

.542 1.000 .590 .594

.332 .590 1.000 .441

.379 .594 .441 1.000

.398 .411 .479 .455

Correlation Matrixa


I think that my bank's actual

social activities and ethical behaviour

comply with what they

committed to in the media and other channels

since the Financial Crisis

of 2007

I feel that I am getting an

economic value in my dealings with my bank (Good quality products that

efficiently satisfy my needs and

requirements)


Q9Transparency





Q9Social_Attachment



Q9Being_Accountable

Q9legal_Obligations



.514 .633 .492 .592

.329 .660 .578 .539

.198 .450 .408 .528

.169 .492 .498 .395

.486 .572 .445 .489

.385 .584 .521 .442

.392 .573 .694 .592

.529 .575 .527 .450

.356 .492 .383 .587

.402 .410 .474 .427

.384 .573 .577 .531

.504 .595 .513 .600

.318 .608 .416 .505

.379 .398 .321 .385

.594 .411 .438 .492

.441 .479 .538 .452

1.000 .455 .343 .477

.455 1.000 .670 .657

Correlation Matrixa




Q9Transparency





Q9Social_Attachment



Q9Being_Accountable

Q9legal_Obligations



.592 .448 .474 .510

.539 .433 .616 .578

.528 .442 .455 .461

.395 .302 .453 .427

.489 .329 .398 .451

.442 .385 .434 .529

.592 .441 .679 .666

.450 .335 .406 .452

.587 .529 .559 .421

.427 .393 .675 .677

.531 .509 .646 .672

.600 .399 .599 .595

.505 .503 .497 .528

.385 .464 .472 .421

.492 .411 .493 .487

.452 .355 .462 .469

.477 .399 .465 .502

.657 .530 .647 .561

Correlation Matrixa

AQ12Advice_Quality




Q9Transparency





Q9Social_Attachment



Q9Being_Accountable

Q9legal_Obligations



.510 .423 .523 .667 .513

.578 .338 .761 .583 .529

.461 .455 .519 .503 .450

.427 .260 .403 .392 .274

.451 .431 .442 .380 .378

.529 .293 .490 .413 .455

.666 .370 .568 .492 .524

.452 .259 .442 .430 .483

.421 .416 .385 .472 .390

.677 .375 .464 .462 .448

.672 .508 .575 .531 .470

.595 .348 .525 .488 .393

.528 .361 .426 .479 .423

.421 .395 .329 .409 .352

.487 .318 .445 .396 .435

.469 .235 .346 .326 .328

.502 .370 .377 .397 .501

.561 .380 .664 .591 .623

Correlation Matrixa



s

I think the overall

approach of my bank's social responsibility activities is aligned with customers’ needs and

demands in the post financial crisis of 2007


Q9Transparency





Q9Social_Attachment



Q9Being_Accountable

Q9legal_Obligations



.513 .549 .482 .490

.529 .480 .595 .458

.450 .376 .415 .448

.274 .355 .357 .360

.378 .383 .566 .553

.455 .459 .598 .444

.524 .403 .518 .540

.483 .357 .607 .393

.390 .344 .368 .388

.448 .351 .534 .474

.470 .484 .562 .544

.393 .474 .533 .561

.423 .519 .519 .463

.352 .275 .423 .442

.435 .352 .528 .526

.328 .286 .557 .404

.501 .442 .400 .327

.623 .587 .701 .531

Correlation Matrixa

Overall, I think that no ethical problems have occurred at my

bank in the years following the Financial Crisis of 2007

I think that banks in

general are likely to have learned the

lesson in terms of navigating a

balance between the

pursuit of profit and operating in a socially responsible

manner

Has your confidence towards the

banking industry

changed in the past seven

years?


Q9Transparency





Q9Social_Attachment



Q9Being_Accountable

Q9legal_Obligations



.490 .492 .245

.458 .448 .266

.448 .472 .219

.360 .368 .174

.553 .411 .171

.444 .370 .186

.540 .412 .222

.393 .525 .141

.388 .364 .253

.474 .350 .185

.544 .452 .225

.561 .545 .193

.463 .360 .177

.442 .409 .208

.526 .421 .241

.404 .405 .145

.327 .472 .192

.531 .458 .255

Correlation Matrixa


Q9Transparency


Correlation

I think that my bank's actual social activities and ethical behaviour comply with what they committed to in the media and other channels since the Financial Crisis of 2007

I feel that I am getting an economic value in my dealings with my bank (Good quality products that efficiently satisfy my needs and requirements)


Q12Withdraw_Money

Q12Treated

AQ12Advice_QualityQ12Personal_Information_Safe

Q12FeesQ12Interest_Rates_Accounts

Q12Interest_Rates_LoanQ12Open_Or_Close_Branches

I think the overall approach of my bank's social responsibility activities is aligned with customers’ needs and demands in the post financial crisis of 2007

.633 .660 .450 .492 .572

.492 .578 .408 .498 .445

.592 .539 .528 .395 .489

.448 .433 .442 .302 .329

.474 .616 .455 .453 .398

.510 .578 .461 .427 .451

.423 .338 .455 .260 .431

.523 .761 .519 .403 .442

.667 .583 .503 .392 .380

.513 .529 .450 .274 .378

.549 .480 .376 .355 .383

.482 .595 .415 .357 .566

.490 .458 .448 .360 .553

Correlation Matrixa



nkingQ9MeetCustom

ers_Needs

Correlation




Q12Withdraw_Money

Q12Treated





.572 .584 .573 .575

.445 .521 .694 .527

.489 .442 .592 .450

.329 .385 .441 .335

.398 .434 .679 .406

.451 .529 .666 .452

.431 .293 .370 .259

.442 .490 .568 .442

.380 .413 .492 .430

.378 .455 .524 .483

.383 .459 .403 .357

.566 .598 .518 .607

.553 .444 .540 .393

Correlation Matrixa

Q9Social_Attachment

Q9Confidentially


on

Correlation




Q12Withdraw_Money

Q12Treated





.575 .492 .410 .573

.527 .383 .474 .577

.450 .587 .427 .531

.335 .529 .393 .509

.406 .559 .675 .646

.452 .421 .677 .672

.259 .416 .375 .508

.442 .385 .464 .575

.430 .472 .462 .531

.483 .390 .448 .470

.357 .344 .351 .484

.607 .368 .534 .562

.393 .388 .474 .544

Correlation Matrixa


Q9Being_Accountable

Q9legal_Obligations

Correlation




Q12Withdraw_Money

Q12Treated





.573 .595 .608 .398

.577 .513 .416 .321

.531 .600 .505 .385

.509 .399 .503 .464

.646 .599 .497 .472

.672 .595 .528 .421

.508 .348 .361 .395

.575 .525 .426 .329

.531 .488 .479 .409

.470 .393 .423 .352

.484 .474 .519 .275

.562 .533 .519 .423

.544 .561 .463 .442

Correlation Matrixa

Q9Combating_Bribery


yQ9Financial_lit

eracy

Correlation




Q12Withdraw_Money

Q12Treated





.398 .411 .479 .455

.321 .438 .538 .343

.385 .492 .452 .477

.464 .411 .355 .399

.472 .493 .462 .465

.421 .487 .469 .502

.395 .318 .235 .370

.329 .445 .346 .377

.409 .396 .326 .397

.352 .435 .328 .501

.275 .352 .286 .442

.423 .528 .557 .400

.442 .526 .404 .327

Correlation Matrixa







of 2007




requirements)

Correlation




Q12Withdraw_Money

Q12Treated





.455 1.000 .670 .657

.343 .670 1.000 .608

.477 .657 .608 1.000

.399 .530 .486 .546

.465 .647 .705 .567

.502 .561 .623 .498

.370 .380 .371 .549

.377 .664 .721 .625

.397 .591 .542 .561

.501 .623 .543 .546

.442 .587 .488 .494

.400 .701 .604 .548

.327 .531 .424 .492

Correlation Matrixa



Correlation




Q12Withdraw_Money

Q12Treated





.657 .530 .647 .561

.608 .486 .705 .623

1.000 .546 .567 .498

.546 1.000 .681 .560

.567 .681 1.000 .777

.498 .560 .777 1.000

.549 .552 .432 .410

.625 .540 .706 .598

.561 .466 .599 .518

.546 .441 .598 .506

.494 .478 .528 .487

.548 .407 .559 .523

.492 .373 .478 .514

Correlation Matrixa

AQ12Advice_Quality



Correlation




Q12Withdraw_Money

Q12Treated





.561 .380 .664 .591 .623

.623 .371 .721 .542 .543

.498 .549 .625 .561 .546

.560 .552 .540 .466 .441

.777 .432 .706 .599 .598

1.000 .410 .598 .518 .506

.410 1.000 .491 .428 .450

.598 .491 1.000 .762 .735

.518 .428 .762 1.000 .792

.506 .450 .735 .792 1.000

.487 .365 .670 .627 .631

.523 .301 .562 .442 .540

.514 .334 .465 .460 .416

Correlation Matrixa



s

I think the overall



Correlation




Q12Withdraw_Money

Q12Treated





.623 .587 .701 .531

.543 .488 .604 .424

.546 .494 .548 .492

.441 .478 .407 .373

.598 .528 .559 .478

.506 .487 .523 .514

.450 .365 .301 .334

.735 .670 .562 .465

.792 .627 .442 .460

1.000 .631 .540 .416

.631 1.000 .466 .473

.540 .466 1.000 .639

.416 .473 .639 1.000

Correlation Matrixa






balance between the


manner


banking industry


years?

Correlation




Q12Withdraw_Money

Q12Treated





.531 .458 .255

.424 .430 .140

.492 .471 .299

.373 .297 .205

.478 .509 .290

.514 .534 .264

.334 .248 .171

.465 .375 .139

.460 .388 .126

.416 .330 .144

.473 .357 .035

.639 .413 .110

1.000 .573 .158

Correlation Matrixa


Q9Transparency


Correlation

Overall, I think that no ethical problems have occurred at my bank in the years following the Financial Crisis of 2007

I think that banks in general are likely to have learned the lesson in terms of navigating a balance between the pursuit of profit and operating in a socially responsible manner

Has your confidence towards the banking industry changed in the past seven years?


Q9Transparency





Q9Social_Attachment



.490 .458 .448 .360 .553

.492 .448 .472 .368 .411

.245 .266 .219 .174 .171

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .020

.000 .000 .000 .002

.000 .000 .020 .002

.000 .000 .000 .001 .000

.000 .000 .000 .000 .000

.000 .000 .011 .001 .000

.000 .000 .000 .000 .000

.000 .000 .000 .000 .000

.000 .000 .000 .000 .000

.000 .000 .000 .000

Correlation Matrixa



nkingQ9MeetCustom

ers_Needs

Correlation





Q9Transparency





Q9Social_Attachment



.553 .444 .540 .393

.411 .370 .412 .525

.171 .186 .222 .141

.000 .000 .000 .000

.000 .000 .000 .000

.020 .000 .000 .011

.002 .001 .000 .001

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000 .014

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

Correlation Matrixa

Q9Social_Attachment

Q9Confidentially


on

Correlation





Q9Transparency





Q9Social_Attachment



.393 .388 .474 .544

.525 .364 .350 .452

.141 .253 .185 .225

.000 .000 .000 .000

.000 .000 .000 .000

.011 .000 .000 .000

.001 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.014 .000 .000

.014 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000 .000

Correlation Matrixa


Q9Being_Accountable

Q9legal_Obligations

Correlation





Q9Transparency





Q9Social_Attachment



.544 .561 .463 .442

.452 .545 .360 .409

.225 .193 .177 .208

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .002

.000 .000 .000 .000

.000 .000 .000 .001

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000

.000 .000 .000

Correlation Matrixa

Q9Combating_Bribery


yQ9Financial_lit

eracy

Correlation





Q9Transparency





Q9Social_Attachment



.442 .526 .404 .327

.409 .421 .405 .472

.208 .241 .145 .192

.000 .000 .000 .000

.000 .000 .000 .001

.000 .020 .142 .029

.002 .001 .027 .054

.000 .000 .000 .000

.001 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .002 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

Correlation Matrixa







of 2007




requirements)

Correlation





Q9Transparency





Q9Social_Attachment



.327 .531 .424 .492

.472 .458 .430 .471

.192 .255 .140 .299

.000 .000 .000 .000

.001 .000 .000 .000

.029 .000 .000 .000

.054 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

Correlation Matrixa



Correlation





Q9Transparency





Q9Social_Attachment



.492 .373 .478 .514

.471 .297 .509 .534

.299 .205 .290 .264

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .002 .000 .000

.000 .001 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .001 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

Correlation Matrixa

AQ12Advice_Quality



Correlation





Q9Transparency





Q9Social_Attachment



.514 .334 .465 .460 .416

.534 .248 .375 .388 .330

.264 .171 .139 .126 .144

.000 .000 .000 .000 .000

.000 .000 .000 .000 .000

.000 .000 .000 .000 .000

.000 .006 .000 .000 .004

.000 .000 .000 .000 .000

.000 .002 .000 .000 .000

.000 .000 .000 .000 .000

.000 .006 .000 .000 .000

.000 .000 .000 .000 .000

.000 .000 .000 .000 .000

.000 .000 .000 .000 .000

.000 .000 .000 .000

Correlation Matrixa



s

I think the overall



Correlation





Q9Transparency





Q9Social_Attachment



.416 .473 .639 1.000

.330 .357 .413 .573

.144 .035 .110 .158

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.004 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

Correlation Matrixa






balance between the


manner


banking industry


years?

Correlation





Q9Transparency





Q9Social_Attachment



1.000 .573 .158

.573 1.000 .339

.158 .339 1.000

.000 .000 .009

.000 .000 .005

.000 .000 .018

.000 .000 .048

.000 .000 .051

.000 .000 .038

.000 .000 .017

.000 .000 .090

.000 .000 .007

.000 .000 .038

.000 .000 .015

.000 .000 .033 Page 66

Correlation Matrixa


Q9Transparency


Sig. (1-tailed)

Q9Being_Accountable

Q9legal_Obligations






Q12Withdraw_Money

Q12Treated




.000 .000 .000 .000 .000

.000 .000 .000 .000 .000

.000 .000 .000 .002 .000

.000 .000 .020 .001 .000

.000 .000 .142 .027 .000

.000 .001 .029 .054 .000

.000 .000 .000 .000 .000

.000 .000 .000 .000 .000

.000 .000 .000 .000 .000

.000 .000 .000 .002 .001

.000 .000 .000 .000 .000

.000 .000 .000 .000 .000

.000 .000 .000 .006 .000

.000 .000 .000 .000 .000

.000 .000 .000 .000 .000

.000 .000 .000 .004 .000

.000 .000 .000 .000 .000

Correlation Matrixa



nkingQ9MeetCustom

ers_Needs

Sig. (1-tailed)

Q9Being_Accountable

Q9legal_Obligations






Q12Withdraw_Money

Q12Treated




.000 .000 .000 .000

.000 .000 .000 .000

.000 .001 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.001 .000 .000 .001

.000 .000 .000 .000

.000 .000 .000 .000

.000 .002 .000 .006

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

Correlation Matrixa

Q9Social_Attachment

Q9Confidentially


on

Sig. (1-tailed)

Q9Being_Accountable

Q9legal_Obligations






Q12Withdraw_Money

Q12Treated




.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .002 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.001 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.006 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

Correlation Matrixa


Q9Being_Accountable

Q9legal_Obligations

Sig. (1-tailed)

Q9Being_Accountable

Q9legal_Obligations






Q12Withdraw_Money

Q12Treated




.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000 .000

.000 .000 .001 .001

.000 .000 .001 .000

.000 .000 .000 .000

.000 .000 .000 .001

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .001

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .004

Correlation Matrixa

Q9Combating_Bribery


yQ9Financial_lit

eracy

Sig. (1-tailed)

Q9Being_Accountable

Q9legal_Obligations






Q12Withdraw_Money

Q12Treated




.000 .000 .000 .000

.000 .000 .001 .001

.000 .001 .000

.000 .000 .000

.001 .000 .000

.000 .000 .000

.000 .000 .000 .000

.001 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .001 .012 .000

.001 .000 .000 .000

.000 .000 .001 .000

.000 .000 .001 .000

.004 .000 .003 .000

Correlation Matrixa







of 2007




requirements)

Sig. (1-tailed)

Q9Being_Accountable

Q9legal_Obligations






Q12Withdraw_Money

Q12Treated




.000 .000 .000 .000

.001 .000 .000 .000

.000 .000 .001 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

Correlation Matrixa



Sig. (1-tailed)

Q9Being_Accountable

Q9legal_Obligations






Q12Withdraw_Money

Q12Treated




.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

Correlation Matrixa

AQ12Advice_Quality



Sig. (1-tailed)

Q9Being_Accountable

Q9legal_Obligations






Q12Withdraw_Money

Q12Treated




.000 .000 .000 .000 .000

.000 .000 .000 .000 .000

.000 .000 .001 .000 .000

.000 .001 .000 .000 .000

.000 .012 .000 .001 .001

.000 .000 .000 .000 .000

.000 .000 .000 .000 .000

.000 .000 .000 .000 .000

.000 .000 .000 .000 .000

.000 .000 .000 .000 .000

.000 .000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000 .000

Correlation Matrixa



s

I think the overall



Sig. (1-tailed)

Q9Being_Accountable

Q9legal_Obligations






Q12Withdraw_Money

Q12Treated




.000 .000 .000 .000

.000 .000 .000 .000

.000 .004 .000 .000

.000 .000 .000 .000

.001 .003 .000 .000

.000 .000 .000 .001

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .002 .001

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000

.000 .000 .000

Correlation Matrixa






balance between the


manner


banking industry


years?

Sig. (1-tailed)

Q9Being_Accountable

Q9legal_Obligations






Q12Withdraw_Money

Q12Treated




.000 .000 .033

.000 .000 .046

.000 .000 .023

.000 .000 .010

.000 .000 .084

.001 .000 .033

.000 .000 .007

.000 .000 .092

.000 .000 .002

.000 .002 .025

.000 .000 .002

.000 .000 .005

.001 .009 .051

.000 .000 .093

.000 .000 .115

.000 .001 .086

.000 .000 .370

Correlation Matrixa


Q9Transparency


Sig. (1-tailed)






.000 .000 .000 .000 .000

.000 .000 .000 .000 .000

.000 .000 .000 .000 .000

.000 .000 .000 .000 .000

.009 .005 .018 .048 .051

Correlation Matrixa



nkingQ9MeetCustom

ers_Needs

Sig. (1-tailed)






.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.051 .038 .017 .090

Correlation Matrixa

Q9Social_Attachment

Q9Confidentially


on

Sig. (1-tailed)






.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.090 .007 .038 .015

Correlation Matrixa


Q9Being_Accountable

Q9legal_Obligations

Sig. (1-tailed)






.000 .000 .000 .004

.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.015 .033 .046 .023

Correlation Matrixa

Q9Combating_Bribery


yQ9Financial_lit

eracy

Sig. (1-tailed)






.004 .000 .003 .000

.000 .000 .000 .000

.000 .000 .000 .001

.000 .000 .000 .000

.023 .010 .084 .033

Correlation Matrixa







of 2007




requirements)

Sig. (1-tailed)






.000 .000 .000 .000

.000 .000 .000 .000

.001 .000 .000 .000

.000 .000 .000 .000

.033 .007 .092 .002

Correlation Matrixa



Sig. (1-tailed)






.000 .000 .000 .000

.000 .000 .000 .000

.000 .000 .000 .000

.000 .002 .000 .000

.002 .025 .002 .005

Correlation Matrixa

AQ12Advice_Quality



Sig. (1-tailed)






.000 .000 .000 .000 .000

.000 .002 .000 .000 .000

.000 .001 .000 .000 .000

.000 .009 .000 .000 .001

.005 .051 .093 .115 .086

Correlation Matrixa



s

I think the overall



Sig. (1-tailed)






.000 .000 .000

.000 .000 .000

.000 .000 .000

.001 .000 .000 .000

.086 .370 .147 .066

Correlation Matrixa






balance between the


manner


banking industry


years?

Sig. (1-tailed)






.000 .000 .370

.000 .000 .147

.000 .066

.000 .000

.066 .000

Determinant = 3.25E-013a.




df

Sig.

.900

2285.941

496

.000

Communalities

Initial Extraction


Q9Transparency


Q9Offers




Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees




Q13

Q14

Q17

Q18

1.000 .569

1.000 .593

1.000 .572

1.000 .346

1.000 .576

1.000 .460

1.000 .586

1.000 .616

1.000 .445

1.000 .527

1.000 .624

1.000 .638

1.000 .501

1.000 .401

1.000 .652

1.000 .649

1.000 .465

1.000 .665

1.000 .578

1.000 .601

1.000 .486

1.000 .680

1.000 .616

1.000 .380

1.000 .719

1.000 .652

1.000 .567

1.000 .513

1.000 .599

1.000 .490

1.000 .429

1.000 .091



Component


1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

15.449 48.279 48.279 15.449 48.279 48.279 13.962

1.838 5.743 54.022 1.838 5.743 54.022 11.766

1.583 4.945 58.967

1.209 3.778 62.745

1.140 3.562 66.307

1.096 3.426 69.733

.897 2.804 72.537

.780 2.438 74.974

.708 2.214 77.188

.696 2.175 79.363

.683 2.134 81.498

.633 1.978 83.476

.623 1.948 85.423

.537 1.678 87.101

.496 1.549 88.650

.473 1.479 90.129

.441 1.377 91.506

.375 1.173 92.678

.324 1.012 93.690

.303 .946 94.637

.246 .767 95.404

.229 .717 96.121

.210 .655 96.776

.174 .543 97.319

.159 .498 97.817

.146 .455 98.272

.125 .392 98.664

.113 .352 99.015

.089 .278 99.294

.084 .262 99.556

.075 .236 99.792

.067 .208 100.000


Component

Rotation Sums of Squared Loadingsa

Total

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

13.962

11.766


When components are correlated, sums of squared loadings cannot be added to obtain a total variance.a.

Pattern Matrixa

Component1 2


Q12Fees




Q9Transparency

Q12Treated

Q12Withdraw_Money



Q9legal_Obligations

Q10



Q9Offers

Q9Confidentially

Q11

AQ12Advice_Quality




Q9Social_Attachment



Q13

Q9Being_Accountable

Q17



Q14

Q9Combating_Bribery

Q18

.904

.883

.858

.740

.734

.687

.686

.684

.647

.627

.616

.613

.612

.589

.572

.568

.566

.520

.465

.915

.822

.806

.717

.638

.557

.527

.498

.498

.461

.452

.444

Extraction Method: Principal Component Analysis. Rotation Method: Oblimin with Kaiser Normalization.a

Rotation converged in 10 iterations.a.

Component Correlation Matrix

Component 1 2

1

21.000 .634

.634 1.000

Extraction Method: Principal Component Analysis. Rotation Method: Oblimin with Kaiser Normalization.

Appendix G - Research Objective One - Factor and Reliability Analyses




df

Sig.

.896

2331.783

528

.000

Communalities

Initial Extraction


Q9Transparency


Q9Offers




Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees




Q13

1.000 .695

1.000 .681

1.000 .693

1.000 .598

1.000 .704

1.000 .541

1.000 .701

1.000 .774

1.000 .653

1.000 .776

1.000 .742

1.000 .727

1.000 .690

1.000 .641

1.000 .705

1.000 .693

1.000 .701

1.000 .739

1.000 .762

1.000 .631

1.000 .634

1.000 .843

1.000 .728

1.000 .533

1.000 .848

1.000 .723

1.000 .755

1.000 .661

1.000 .690

1.000 .554

Communalities

Initial Extraction

Q14

Q16

Q17

Q18

1.000 .554

1.000 .717

1.000 .672

1.000 .583



Component

Initial Eigenvalues Extraction Sums of Squared Loadings

Total % of Variance Cumulative % Total % of Variance Cumulative %

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

15.465 46.863 46.863 15.465 46.863 46.863

2.022 6.127 52.990 2.022 6.127 52.990

1.610 4.877 57.867 1.610 4.877 57.867

1.371 4.154 62.021 1.371 4.154 62.021

1.194 3.618 65.640 1.194 3.618 65.640

1.124 3.407 69.047 1.124 3.407 69.047

.911 2.759 71.806

.792 2.400 74.206

.774 2.346 76.552

.708 2.145 78.697

.683 2.070 80.767

.665 2.016 82.783

.629 1.905 84.689

.539 1.634 86.322

.531 1.610 87.932

.485 1.471 89.403

.441 1.336 90.739

.436 1.322 92.061

.338 1.024 93.085

.317 .962 94.047

.297 .899 94.946

.234 .708 95.655

.223 .677 96.331

.198 .599 96.931

.170 .516 97.447

.158 .478 97.925

.144 .436 98.360

.125 .378 98.738

.110 .333 99.071

.088 .267 99.338


Component


30

31

32

33

.088 .267 99.338

.084 .253 99.591

.073 .222 99.814

.061 .186 100.000


Component Number

333231302928272625242322212019181716151413121110987654321

Eig

enva

lue

20

15

10

5

0

Scree Plot


Communalities

Initial Extraction


Q9Transparency


Q9Offers




Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees




Q13

Q14

Q15

Q16

Q17

Q18

1.000 .572

1.000 .623

1.000 .569

1.000 .322

1.000 .630

1.000 .532

1.000 .585

1.000 .638

1.000 .620

1.000 .591

1.000 .642

1.000 .698

1.000 .524

1.000 .573

1.000 .633

1.000 .619

1.000 .419

1.000 .711

1.000 .643

1.000 .608

1.000 .550

1.000 .683

1.000 .621

1.000 .397

1.000 .816

1.000 .675

1.000 .634

1.000 .597

1.000 .693

1.000 .507

1.000 .676

1.000 .434

1.000 .431

1.000 .269



Component


1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

16.058 47.228 47.228 16.058 47.228 47.228 14.311

2.027 5.961 53.190 2.027 5.961 53.190 3.280

1.652 4.859 58.049 1.652 4.859 58.049 11.658

1.382 4.063 62.112

1.250 3.676 65.788

1.129 3.321 69.110

.914 2.688 71.798

.851 2.503 74.301

.774 2.277 76.578

.708 2.083 78.661

.684 2.010 80.671

.665 1.957 82.628

.629 1.849 84.477

.540 1.587 86.065

.534 1.572 87.637

.498 1.464 89.100

.459 1.351 90.451

.438 1.287 91.738

.338 .995 92.733

.320 .942 93.675

.298 .877 94.552

.246 .725 95.276

.228 .671 95.948

.201 .591 96.538

.195 .575 97.113

.170 .501 97.614

.156 .457 98.071

.135 .396 98.467

.115 .338 98.805

.109 .319 99.124

.087 .256 99.380

.080 .234 99.614

.071 .209 99.823

.060 .177 100.000


Component


Total

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

14.311

3.280

11.658



Pattern Matrixa

Component1 2 3

Q12Fees




Q10

Q11

Q9Transparency

Q15


Q13


Q12Treated



Q9Offers

AQ12Advice_Quality


Q12Withdraw_Money

Q14


Q16


Q9Social_Attachment


Q9Combating_Bribery

Q9Confidentially

Q9Being_Accountable



Q18


Q17


Q9legal_Obligations

.997

.860

.859

.858

.756

.751

.743

.723

.605

.568 -.418

.566

.546

.542

.536

.461

.456 .403

.441

.431

.631

-.580

-.532

-.494 .402

.789

.708

.666

.659

.630

.568

.507

.474

.473

.454




Component 1 2 3

1

2

3

1.000 -.191 .615

-.191 1.000 -.117

.615 -.117 1.000




Cronbach's Alpha



.532 .545 4


Q16Q9Financial_lit

eracyQ9Social_Attac

hmentQ9Executive_R

emuneration

Q16


Q9Social_Attachment


1.000 -.095 -.028 -.217

-.095 1.000 .645 .538

-.028 .645 1.000 .537

-.217 .538 .537 1.000





Correlation

Squared Multiple

Correlation

Q16


Q9Social_Attachment


7.99 4.846 -.132 .059 .802

9.17 2.783 .566 .468 .232

9.13 2.598 .611 .473 .173

9.09 3.179 .418 .383 .376



Deleted

Q16


Q9Social_Attachment


.802

.232

.173

.376


Communalities

Initial Extraction


Q9Transparency


Q9Offers




Q9Social_Attachment

Q9Confidentially



Q9Being_Accountable

Q9legal_Obligations

Q9Combating_Bribery




Q10

Q11


Q12Withdraw_Money

Q12Treated

AQ12Advice_Quality


Q12Fees



1.000 .570

1.000 .599

1.000 .576

1.000 .346

1.000 .578

1.000 .467

1.000 .584

1.000 .625

1.000 .438

1.000 .520

1.000 .622

1.000 .635

1.000 .503

1.000 .392

1.000 .642

1.000 .651

1.000 .453

1.000 .668

1.000 .580

1.000 .597

1.000 .481

1.000 .674

1.000 .616

1.000 .376

1.000 .721

1.000 .649

1.000 .560

1.000 .516

Communalities

Initial Extraction


Q13

Q14

Q15

Q17

Q18

1.000 .516

1.000 .610

1.000 .501

1.000 .609

1.000 .431

1.000 .089



Component


1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

16.042 48.613 48.613 16.042 48.613 48.613 14.534

1.838 5.570 54.183 1.838 5.570 54.183 12.143

1.625 4.924 59.107

1.296 3.926 63.033

1.141 3.456 66.489

1.111 3.367 69.856

.898 2.723 72.578

.804 2.437 75.016

.710 2.152 77.168

.699 2.118 79.286

.683 2.070 81.356

.633 1.919 83.275

.623 1.889 85.164

.537 1.628 86.792

.500 1.516 88.308

.475 1.440 89.748

.456 1.381 91.129

.392 1.189 92.318

.327 .991 93.310

.304 .920 94.229

.249 .753 94.983

.242 .734 95.717

.211 .638 96.355

.200 .606 96.961

.174 .526 97.487

.157 .476 97.963


Component


Total

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

14.534

12.143


Component


26

27

28

29

30

31

32

33

.157 .476 97.963

.140 .424 98.387

.115 .348 98.735

.112 .341 99.076

.089 .269 99.345

.081 .244 99.590

.071 .215 99.804

.065 .196 100.000


Component


Total

26

27

28

29

30

31

32

33



Pattern Matrixa

Component

1 2


Q12Fees




Q12Treated

Q9Transparency

Q12Withdraw_Money



Q9legal_Obligations


Q10


Q9Confidentially

Q9Offers

Q11

AQ12Advice_Quality

Q15




Q9Social_Attachment



Q13

Q9Being_Accountable

Q17



Q14

Q9Combating_Bribery

Q18

.908

.884

.859

.739

.735

.691

.690

.689

.652

.632

.622

.619

.616

.593

.576

.574

.567

.526

.505

.470

.914

.812

.810

.714

.627

.561

.517

.495

.485

.464

.455

.429




Component 1 2

1

21.000 .635

.635 1.000


Apendix H- Research Objective One- Regression Analysis

Descriptive Statistics

Mean Std. Deviation N

Q15

ECandLG

PHandET

3.11 .883 92

.0000000 1.00000000 92

.0000000 1.00000000 92

Correlations

Q15 ECandLG PHandET

Pearson Correlation Q15

ECandLG

PHandET

Sig. (1-tailed) Q15

ECandLG

PHandET

N Q15

ECandLG

PHandET

1.000 .712 .656

.712 1.000 .634

.656 .634 1.000

. .000 .000

.000 . .000

.000 .000 .

92 92 92

92 92 92

92 92 92

Variables Entered/Removeda

ModelVariables Entered

Variables Removed Method

1 PH&ET, EC&LGb . Enter

Dependent Variable: I think the overall approach of my bank's social responsibility efforts after the financial crisis of 2007 are satisfactory

a.

All requested variables entered.b.

Model Summary

Model R R SquareAdjusted R

SquareStd. Error of the

Estimate

1 .760a .577 .568 .580

Predictors: (Constant), PH&ET, EC&LGa.

ANOVAa

ModelSum of Squares df Mean Square F Sig.

1 Regression

Residual

Total

40.927 2 20.464 60.738 .000b

29.986 89 .337

70.913 91


a.

Predictors: (Constant), PH&ET, EC&LGb.

Coefficientsa

Model

Unstandardized CoefficientsStandardized Coefficients

t Sig.

Collinearity Statistics

B Std. Error Beta Tolerance

1 (Constant)

EC&LG

PH&ET

3.109 .061 51.370 .000

.438 .079 .496 5.564 .000 .598 1.672

.301 .079 .341 3.829 .000 .598 1.672

Coefficientsa

Model


VIF

1 (Constant)

EC&LG

PH&ET

1.672

1.672


a.

Appendix I - Research Objective Two - Factor and Reliability Analyses


Mean Std. Deviation Analysis N

Q19Reasonable_Interest_Rates

Q19Payments_Fees_Transparency

Q19Account_Information_Confidentiality

Q19CEO_Cuts

Q19Financial_Inclusion

Q19Projects_With_Adverse_Impacts

Q19ValuedCustomer_Treating

Q19Honest_Financial_Advice

Q19CEO_dont_Misreport

Q19Compliance_With_Law

4.20 .975 92

4.26 .850 92

4.27 .939 92

3.16 1.252 92

3.18 1.195 92

3.71 1.218 92

4.34 .842 92

4.29 .871 92

3.92 1.061 92

4.22 .936 92

Correlation Matrixa

Q19Reasonable_Interest_Rate

s

Q19Payments_Fees_Transpar

ency

Correlation Q19Reasonable_Interest_Rates



Q19CEO_Cuts







Sig. (1-tailed) Q19Reasonable_Interest_Rates



Q19CEO_Cuts







1.000 .627 .458

.627 1.000 .626

.458 .626 1.000

.046 .156 .261

.138 .277 .200

.123 .351 .436

.575 .613 .745

.449 .623 .667

.216 .363 .506

.326 .481 .683

.000 .000

.000 .000

.000 .000

.333 .069 .006

.094 .004 .028

.122 .000 .000

.000 .000 .000

.000 .000 .000

.019 .000 .000

.001 .000 .000

Correlation Matrixa

Q19Account_Information_Confi

dentiality Q19CEO_Cuts




Q19CEO_Cuts










Q19CEO_Cuts







.458 .046 .138

.626 .156 .277

1.000 .261 .200

.261 1.000 .501

.200 .501 1.000

.436 .406 .513

.745 .260 .309

.667 .167 .338

.506 .589 .471

.683 .317 .337

.000 .333 .094

.000 .069 .004

.006 .028

.006 .000

.028 .000

.000 .000 .000

.000 .006 .001

.000 .056 .000

.000 .000 .000

.000 .001 .001

Correlation Matrixa


Q19Projects_With_Adverse_Im

pacts




Q19CEO_Cuts










Q19CEO_Cuts







.138 .123 .575

.277 .351 .613

.200 .436 .745

.501 .406 .260

1.000 .513 .309

.513 1.000 .462

.309 .462 1.000

.338 .569 .762

.471 .646 .595

.337 .577 .631

.094 .122 .000

.004 .000 .000

.028 .000 .000

.000 .000 .006

.000 .001

.000 .000

.001 .000

.000 .000 .000

.000 .000 .000

.001 .000 .000

Correlation Matrixa






Q19CEO_Cuts










Q19CEO_Cuts







.575 .449 .216

.613 .623 .363

.745 .667 .506

.260 .167 .589

.309 .338 .471

.462 .569 .646

1.000 .762 .595

.762 1.000 .595

.595 .595 1.000

.631 .743 .637

.000 .000 .019

.000 .000 .000

.000 .000 .000

.006 .056 .000

.001 .000 .000

.000 .000 .000

.000 .000

.000 .000

.000 .000

.000 .000 .000

Correlation Matrixa






Q19CEO_Cuts










Q19CEO_Cuts







.216 .326

.363 .481

.506 .683

.589 .317

.471 .337

.646 .577

.595 .631

.595 .743

1.000 .637

.637 1.000

.019 .001

.000 .000

.000 .000

.000 .001

.000 .001

.000 .000

.000 .000

.000 .000

.000

.000

Determinant = .002a.




df

Sig.

.850

556.572

45

.000

Communalities

Initial Extraction




Q19CEO_Cuts







1.000 .617

1.000 .680

1.000 .717

1.000 .634

1.000 .558

1.000 .657

1.000 .788

1.000 .767

1.000 .758

1.000 .680



Component


1

2

3

4

5

6

7

8

9

10

5.229 52.290 52.290 5.229 52.290 52.290 4.528

1.627 16.275 68.564 1.627 16.275 68.564 3.516

.814 8.140 76.705

.619 6.193 82.897

.394 3.939 86.836

.368 3.683 90.520

.310 3.104 93.624

.288 2.878 96.502

.206 2.065 98.567

.143 1.433 100.000


Component


Total

1

2

3

4

5

6

7

8

9

10

4.528

3.516



Component Number

10987654321

Eig

enva

lue

6

5

4

3

2

1

0

Scree Plot

Component Matrixa

Component1 2





Q19CEO_dont_MisreportQ19Payments_Fees_Transparency



Q19CEO_CutsQ19Reasonable_Interest_Rates

.857

.853

.824

.806

.784

.722

.709

.529 .528

.470 .643

.548 -.563


2 components extracted.a.

Pattern Matrixa

Component1 2







Q19CEO_Cuts




.838

.837

.816

.793

.770

.595 .401

.836

.753

.732

.710



Structure Matrix

Component1 2









Q19CEO_Cuts


.874 .450

.849 .495

.838 .404

.824

.740

.734 .607

.536 .829

.462 .785

.784

.747



Component 1 2

1

21.000 .346

.346 1.000


Component Score Coefficient Matrix

Component1 2




Q19CEO_Cuts

Q19Financial_InclusionQ19Projects_With_Adverse_Impacts



Q19CEO_dont_MisreportQ19Compliance_With_Law

.247 -.163

.232 -.069

.209 .001

-.094 .338

-.052 .297

.015 .265

.213 .015

.196 .042

.032 .270

.138 .120

Extraction Method: Principal Component Analysis. Rotation Method: Oblimin with Kaiser Normalization. Component Scores.

Component Score Covariance Matrix

Component 1 2

1

21.119 .691

.691 1.119

Extraction Method: Principal Component Analysis. Rotation Method: Oblimin with Kaiser Normalization. Component Scores.

Reliability Analysis for ECP&LGP

Case Processing Summary

N %

Cases Valid

Excludeda

Total

92 100.0

0 .0

92 100.0

Listwise deletion based on all variables in the procedure.a.


Cronbach's Alpha



.898 .900 6

Item Statistics

Mean Std. Deviation NQ19Payments_Fees_Transparency


Q19ValuedCustomer_TreatingQ19Account_Information_Confidentiality



4.26 .850 92

4.20 .975 92

4.34 .842 92

4.27 .939 92

4.29 .871 92

4.22 .936 92


Q19Payments_Fees_Transpar

ency

Q19Reasonable_Interest_Rate

sQ19ValuedCustomer_Treating

Q19Account_Information_Confi

dentialityQ19Payments_Fees_Transparency






1.000 .627 .613 .626 .623

.627 1.000 .575 .458 .449

.613 .575 1.000 .745 .762

.626 .458 .745 1.000 .667

.623 .449 .762 .667 1.000

.481 .326 .631 .683 .743










.623 .481

.449 .326

.762 .631

.667 .683

1.000 .743

.743 1.000





Correlation

Squared Multiple

CorrelationQ19Payments_Fees_Transparency






21.32 14.108 .721 .581 .880

21.38 14.304 .567 .466 .905

21.24 13.613 .822 .718 .865

21.30 13.247 .776 .662 .871

21.28 13.568 .796 .719 .869

21.36 13.793 .686 .622 .885



DeletedQ19Payments_Fees_Transparency






.880

.905

.865

.871

.869

.885

Scale Statistics

Mean Variance Std. Deviation N of Items25.58 19.434 4.408 6

Reliability Analysis for ETP&PHP


N %

Cases Valid

Excludeda

Total

92 100.0

0 .0

92 100.0



Cronbach's Alpha



.809 .813 4

Item Statistics


Q19CEO_Cuts


Q19CEO_dont_MisreportQ19Projects_With_Adverse_Impacts

3.16 1.252 92

3.18 1.195 92

3.92 1.061 92

3.71 1.218 92


Q19CEO_CutsQ19Financial_I

nclusionQ19CEO_dont_

Misreport

Q19Projects_With_Adverse_Im

pacts

Q19CEO_Cuts



1.000 .501 .589 .406

.501 1.000 .471 .513

.589 .471 1.000 .646

.406 .513 .646 1.000





Correlation

Squared Multiple

Correlation

Q19CEO_Cuts



10.82 8.394 .593 .413 .779

10.79 8.649 .596 .368 .776

10.05 8.711 .707 .545 .729

10.27 8.376 .624 .475 .762



Deleted

Q19CEO_Cuts



.779

.776

.729

.762

Scale Statistics

Mean Variance Std. Deviation N of Items13.98 14.263 3.777 4

Regression Analysis for Research Objective Two


ModelVariables Entered

Variables Removed Method

1 REGR factor score 2 for analysis 1, REGR factor score 1 for analysis 1b

. Enter

Dependent Variable: I think that the more meaningful the social activities a bank engages in are, the more preference will be given to them

a.


Model Summaryb



Estimate

1 .556a .309 .294 .811

Predictors: (Constant), REGR factor score 2 for analysis 1, REGR factor score 1 for analysis 1a.


b.

ANOVAa


1 Regression

Residual

Total

26.238 2 13.119 19.929 .000b

58.588 89 .658

84.826 91


a.

Predictors: (Constant), REGR factor score 2 for analysis 1, REGR factor score 1 for analysis 1b.

Coefficientsa

Model


t Sig.

95.0% Confidence ...

B Std. Error Beta Lower Bound

1 (Constant)

ECP&LGP

ETP&PHP

3.543 .085 41.891 .000 3.375 3.712

.291 .091 .301 3.210 .002 .111 .471

.362 .091 .375 3.993 .000 .182 .542

Coefficientsa

Model

95.0% Confidence ...

Upper Bound

1 (Constant)

ECP&LGP

ETP&PHP

3.712

.471

.542


a.

Residuals Statisticsa

Minimum Maximum Mean Std. Deviation N

Predicted Value

Residual

Std. Predicted Value

Std. Residual

1.45 4.31 3.54 .537 92

-2.203 1.402 .000 .802 92

-3.900 1.435 .000 1.000 92

-2.716 1.728 .000 .989 92


a.

Appendix J- Research Objective Three- Correlation Coefficient and Reliability analyses



Q21CSR_strategy

Q21Confidence

Q21Reputable_Business

Q21High_CSR_rating

Q22

3.91 .847 92

4.00 .784 92

3.98 .784 92

3.98 .784 92

3.54 .965 92

Correlations

Q21CSR_strategy Q21Confidence


Q21CSR_strategy Pearson Correlation

Sig. (2-tailed)

N

Q21Confidence Pearson Correlation

Sig. (2-tailed)

N

Q21Reputable_Business Pearson Correlation

Sig. (2-tailed)

N

Q21High_CSR_rating Pearson Correlation

Sig. (2-tailed)

N

Q22 Pearson Correlation

Sig. (2-tailed)

N

1 .695** .543** .593**

.000 .000 .000

92 92 92 92

.695** 1 .643** .679**

.000 .000 .000

92 92 92 92

.543** .643** 1 .732**

.000 .000 .000

92 92 92 92

.593** .679** .732** 1

.000 .000 .000

92 92 92 92

.327** .464** .495** .582**

.001 .000 .000 .000

92 92 92 92

Correlations

Q21High_CSR_rating Q22


Sig. (2-tailed)

N


Sig. (2-tailed)

N


Sig. (2-tailed)

N


Sig. (2-tailed)

N

Q22 Pearson Correlation

Sig. (2-tailed)

N

.593** .327**

.000 .001

92 92

.679** .464**

.000 .000

92 92

.732** .495**

.000 .000

92 92

1 .582**

.000

92 92

.582** 1

.000

92 92

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

Correlations




Sig. (2-tailed)

N


Sig. (2-tailed)

N


Sig. (2-tailed)

N


Sig. (2-tailed)

N

1 .695** .543** .593**

.000 .000 .000

92 92 92 92

.695** 1 .643** .679**

.000 .000 .000

92 92 92 92

.543** .643** 1 .732**

.000 .000 .000

92 92 92 92

.593** .679** .732** 1

.000 .000 .000

92 92 92 92

.327** .464** .495 .582**

Correlations

Q21High_CSR_rating

I think that the more

meaningful the social activities a bank engages in are, the more preference will

be given to them


Sig. (2-tailed)

N


Sig. (2-tailed)

N


Sig. (2-tailed)

N


Sig. (2-tailed)

N

.593** .327**

.000 .001

92 92

.679** .464**

.000 .000

92 92

.732** .495**

.000 .000

92 92

1 .582**

.000

92 92

.582** 1Correlations



I think that the more meaningful the social activities a bank engages in are, the more preference will be given to them

Pearson Correlation

Sig. (2-tailed)

N

.327** .464** .495** .582**

.001 .000 .000 .000

92 92 92 92

Correlations

Q21High_CSR_rating

I think that the more

meaningful the social activities a bank engages in are, the more preference will

be given to them

I think that the more meaningful the social activities a bank engages in are, the more preference will be given to them

Pearson Correlation

Sig. (2-tailed)

N

.582** 1

.000

92 92

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

Reliability

Scale: ALL VARIABLES


N %

Cases Valid

Excludeda

Total

92 100.0

0 .0

92 100.0



Cronbach's Alpha



.781 .800 5

Item Statistics


Q21CSR_strategy

Q21Confidence


Q21High_CSR_ratingWould you recommend your bank based on its socially responsible behaviour ?

3.91 .847 92

4.00 .784 92

3.98 .784 92

3.98 .784 92

3.09 .957 92




Q21High_CSR_rating Q23

Q21CSR_strategy

Q21Confidence


Q21High_CSR_rating

Q23

1.000 .695 .543 .593 -.004

.695 1.000 .643 .679 .102

.543 .643 1.000 .732 .208

.593 .679 .732 1.000 .252

-.004 .102 .208 .252 1.000





Correlation

Squared Multiple

Correlation

Q21CSR_strategy

Q21Confidence



15.04 6.130 .578 .527 .733

14.96 5.954 .706 .614 .692

14.98 5.934 .713 .580 .690

14.98 5.758 .771 .637 .670

15.87 7.521 .159 .105 .879



Deleted

Q21CSR_strategy

Q21Confidence



.733

.692

.690

.670

.879

Reliability

Scale: ALL VARIABLES


Cronbach's Alpha



.879 .880 4

Item Statistics


Q21CSR_strategy

Q21Confidence


Q21High_CSR_rating

3.91 .847 92

4.00 .784 92

3.98 .784 92

3.98 .784 92




Q21High_CSR_rating

Q21CSR_strategy

Q21Confidence


Q21High_CSR_rating

1.000 .695 .543 .593

.695 1.000 .643 .679

.543 .643 1.000 .732

.593 .679 .732 1.000





Correlation

Squared Multiple

Correlation

Q21CSR_strategy

Q21Confidence


Q21High_CSR_rating

11.96 4.372 .687 .512 .867

11.87 4.356 .779 .614 .829

11.89 4.494 .726 .577 .850

11.89 4.384 .768 .620 .833



Deleted

Q21CSR_strategy

Q21Confidence


Q21High_CSR_rating

.867

.829

.850

.833

Appendix K- Research Objective Four - Hierarchical Regression Analysis


Model Variables EnteredVariables Removed Method

1

2SectionC_final1b . Enter

Q22b . Enter

Dependent Variable: Q20a.


Model Summary



Estimate

1

2.714a .510 .505 .784

.760b .577 .568 .732

Predictors: (Constant), REGR factor score 1 for analysis 1a.

Predictors: (Constant), REGR factor score 1 for analysis 1, I think that the more meaningful the social activitiesa bank engages in are, the more preference will be given to them

b.

ANOVAa


1 Regression

Residual

Total

2 Regression

Residual

Total

57.604 1 57.604 93.733 .000b

55.309 90 .615

112.913 91

65.185 2 32.592 60.775 .000c

47.728 89 .536

112.913 91

Dependent Variable: I think that, when/if I switch banks, I will form my decision highly based on their social responsibly activities

a.

Predictors: (Constant), REGR factor score 1 for analysis 1b.

Predictors: (Constant), REGR factor score 1 for analysis 1, I think that the more meaningful the social activitiesa bank engages in are, the more preference will be given to them

c.

Coefficientsa

Model


t Sig.B Std. Error Beta

1 (Constant)

SectionC_final1

2 (Constant)

SectionC_final1

Q22

3.109 .082 38.036 .000

.796 .082 .714 9.682 .000

1.841 .346 5.328 .000

.606 .092 .544 6.600 .000

.358 .095 .310 3.760 .000


Excluded Variablesa

Model Beta In t Sig.Partial

Correlation


Tolerance

1 Q22 .310b 3.760 .000 .370 .699


Predictors in the Model: (Constant), SectionC_final1b.