The Impact of Regulation on Customer Retention

within the Irish Banking Sector

Masters thesis submitted in fulfilment of the requirements for the M.Sc.

Business and Management

Christopher Neville

Trinity College Dublin

July, 2016

Abstract

This dissertation aims to break new ground and unravel some of the mysteries surrounding the

impact of financial regulation and oversight on customer retention in the banking sector.

Unequivocally regulation impacts the manner in which banks conduct their day to day

operations and further how customers obtain, interact with, and utilise banking services. By

extension of this point regulation may be impactful in customer retention or conversely in

churn or attrition. This paper employs a survey research strategy and is best described as a

simple mixed methods methodological approach.

Taken together, the findings indicate that generally customers perceive regulation positively.

Many of the participants indicated that it is better for banks to be highly regulated and that

many of the regulatory requirements were adequate as opposed to inadequate or excessive.

Furthermore, regulation was found to be related to pertinent antecedents of customer retention

such as trust, satisfaction and switching costs. Whilst this concept has never been explored

before it does appear that regulation is in the cauldron and on the whole appears to facilitate

customer retention.

1

Declaration

I declare that this thesis is a presentation of my own original research. This thesis has not been

submitted as an exercise for a degree at any other university. Except where otherwise stated the

work presented has been carried out by the author alone. Where contributions of others are

included efforts were duly made to indicate this with clear reference to the literature.

I agree that Trinity College Dublin, University of Dublin may lend or copy this thesis upon

request.

Chris Neville

Student Number: 12307634

24/07/2016

Acknowledgements

2

First and foremost I would like to express my sincerest gratitude to my thesis supervisor Dr.

Sarah Browne, for her continued support and guidance through a challenging but rewarding

process. Thank you for always finding a timeslot in your hectic schedule. I appreciated the

autonomy and cutting questions you presented me with, all of which helped mould this thesis

into its current shape. I would also like to thank Dr. Padraic Regan for the first class feedback

and knowledge imparted during the research methods module.

I would like to extend my sincerest appreciation to my sister Natalie Neville. It goes with

saying that you have been one of the steering factors behind all my academic and personal

success. I know all of the support came from a truly selfless place, that being said I cannot

accurately describe how indebted and grateful I am.

To my parents and to my partner Laura. I know at times I may have been difficult to deal/live

with. I want to thank you for the unfailing support, continuous encouragement and the patience

you all afforded me.

Finally, I wish to thank all of the participants for their input and time. Everyone’s perspectives

were valued and I strived to represent them as they were manifested.

Thank you all very much.

Chris Neville

July 21st 2016

Table of Contents Page no.

Abstract………………………………….………………………………………………………...…...…1

3

Declaration………………………………………………………………………………....…………......2

Acknowledgements.……………………….………………………………………….………….........….3

1.0 Introduction to Customer Retention & Research Question……………………………….….

…..8

1.1 Introduction……………………………………………………………………………….…………..9

1.2 Relationship Marketing…………………..……………….…………………………………….…...10

1.3 Customer Relationship Management………..………………………………………………………12

1.4 Customer Retention………………..………………………………………………………………..13

1.5 Scope of Customer Retention Within the Banking Sector……...…………………………………...15

1.6 The Role of Regulation…..………………………………………………………………………….16

1.7 Research Contributions and Objectives…………………………………..………………………....18

1.8 Thesis Outline……………………………………………………………………………………….19

2.0 Theoretical Background…………………………………………………………………………...20

2.1 Introduction………………………………………………………………………………………….21

2.2 The Impact of Switching Costs on Customer Retention……….…………………………………....21

2.3 The Impact of Trust on Customer Retention………………………………………………...……...23

2.4 The Impact of Customer Satisfaction on Customer Retention……………………………………...25

3.0 Research Methodology & Design………………………………………………………………….27

3.1 Introduction………………………………………………………………………………………….28

3.2 Research Philosophy & Paradigm……………………………………………………….…………..28

3.2.1 Positivism…………………………………………………………………………….…...29

3.2.2 Realism…………………………………………………………………………………...29

3.2.3 Pragmatism……………………………………………………………………………….30

3.2.4 Interpretivism……………………………………………………………………………..30

3.3 Research Approach………………………………………………………………………………….31

3.4 Methodological Choice……………………………………………………………………………...31

3.5 Research Strategy…………………………………………………………………………………....32

3.6 Questionnaire Design………………………………………………………………………..............32

3.7 Time Horizon………………………………………………………………………………..............34

3.8 Sampling…………………………………………………………………………………………….34

3.9 Data Analysis and Interpretation…………………………………………………………………….36

3.10 Ethical Considerations………………………..……………………………………………………37

3.11 Summary…………………………………………………………………………………………...38

4.0 Data Analysis & Findings………………………………………………………….……………....39

4.1 Introduction………………………………………………………………………………………….40

4.2 Sample Description…………………………………………………………………….…………....40

4.2.1 Gender Distribution…………………………………………………………..…………..40

4

4.2.2 Age Profile of the Sample………………………………………………………………...41

4.2.3 Educational Attainment…………………………………………………………………..42

4.2.4 The Frequency of Banks within the Sample……………………………………………...43

4.2.5 The Frequency of Switching In the last twelve months…………………………………..43

4.2.6 Relationship Longevity with Primary Service Provider…………….……………………44

4.2.7 The Frequency of Banking Channels utilised……………………..……………………...45

4.2.8 The Frequency of Banking Products with Primary Service Provider…………….............45

4.3.1 Perception of Regulation…………………………………………………………………………..46

4.4.1 The Impact of Regulation on Switching Costs…………………………...……………………….47

4.4.2 The Impact of Switching Costs on Customer Retention……………………….………………….48

4.5.1 The Impact of Regulation on Trust……..…………………………………………………………49

4.5.2 The Impact of Trust on Customer Retention……………………………………………………...50

4.6.1 Satisfaction………………………………………………………………………………………..51

4.6.2 The Impact of Regulation on Customer Satisfaction……………………………………………..53

4.6.3 The Impact of Customer Satisfaction on Customer Retention…………………………………....54

5.0 Limitations, Further Research & Conclusion…………………………………………………....56

5.1 Limitations…………………………………………………………………………………..............57

5.2 Further Research…………………………………………………………………………………….59

5.3 Conclusion…………………………………………………………………………………..............62

6.0 Appendices………………………………………………………………………………………….63

6.1 Survey Instrument…………………………………………………………………………………...64

6.2 Bar Charts & Survey Results………………………………………………………………..............69

6.3 Statistics Relating to Bar Charts…………………………………………………………………….75

6.4 Correlation Output………………………………………………………….……………………….77

7.0 Bibliography………………………………………………………………………………..............70

List of figuresPage no.

Figure 1.2 Payne & Frow 2 Relationship Marketing…………………………………………..11

5

Figure 1.8 Thesis Outline……………………………………………....………………………19

Figure 2.4 Conceptual Model…………………………………………………………………..26

Figure 3.9 Correlation Interpretation…………………………………………………………..37

Figure 3.11 The Research Onion………...………………...………………….……………….38

Figure 4.3.1a Perception of the Importance of Regulation…………………………….………46

Figure 4.3.1b Consumer Perception of Regulatory Measures…………………………………47

Figure 4.4.2 Switching Costs………………………………………………………………..…48

Figure 4.5.1 The Impact of Regulation on Trust………………………………….……………49

Figure 4.5.2 The Importance of Trust………………………………………………………….50

Figure 4.6.1 Satisfaction……………………………………………………………………….52

Figure 4.6.2 Impact of Regulation on Satisfaction………………………………………….…53

List of TablesPage no.

6

Table 4.2.1 Sample Gender

Distribution……………………………………………………….41

Table 4.2.2 Age profile of the Sample…………………………………………………………41

Table 4.2.3 Table of Educational Attainment………………………………………………….42

Table 4.2.4 The Frequency of Banks within the Sample………………………………………43

Table 4.2.5 Frequency of Switching in the previous year……………………………………..44

Table 4.2.6 Relationship longevity with Primary Service Provider…………………………...44

Table 4.2.7 Frequency of Banking Channels used……………………………………………..45

Table 4.2.8 Frequency of Banking Products used……………………………………………..46

Table 4.4.2 Switching Costs and Retention…………………………………………………....48

Table 4.5.1 Regulation and Trust………………………………………………………………50

Table 4.5.2 Impact of Trust on Customer Retention…………………………………………...51

Table 4.6.1 Factors influential in Satisfaction……………………………………...………….52

Table 4.6.2 Impact of Regulation on Customer Satisfaction…………………………………..54

Table 4.6.3 Customer Satisfaction and Retention……………………………………………...55

7

Section One: Customer Retention & The Research Gap

8

1.1 Introduction

There is a substantial and growing body of literature on customer retention. This appears to be

for good reason as according to Aspinall et al (2001) 54% of firms believed that customer

retention is of greater importance than acquisition. A seminal study conducted by Reichheld et

al (1990) found that reducing defection rate by 5% led to an 85% increase in one bank branch's

profits. In traditional market dynamics, any price or quality changes are expected to be passed

on to consumers, albeit to varying degrees (Mankiw, 2014). By this logic, it is conceivable that

regulatory measures have non-negligible effects on customers. In support of this argument

(Jalilian et al., 2007) highlight how regulation tapers efficiency and ultimately profits.

Consequently, the aim of this research is to shed new light on the impact of financial regulation

and oversight on customer retention in the banking sector. At present, very little is known

about customer retention in the banking sector, much less is known about how regulation might

be impactful in achieving this end.

This section disaggregates from the largest theoretical field of marketing into relationship

marketing and customer relationship marketing. This is necessary to provide vital context and

to establish the importance of customer retention. Additionally, this section also provides a

comprehensive review of the literature pertaining to customer retention and more specifically

customer retention within the banking sector. Furthermore, it includes important definitions of

what is meant by regulation and discusses some of the literature published on the matter. The

penultimate component of this section provides a clear articulation and justification of the

research question. The final element of the section provides an outline for this paper.

9

1.2 Relationship Marketing

The purpose of this segment is to provide insight into relationship marketing (RM). However,

in order to develop a greater understanding of relationship marketing we must first define what

it is we mean by marketing. Gronroos (1990) posits that the purpose of marketing is to

“establish, maintain, and enhance relationships with customers, and other partners, at a profit,

so that the objectives of the parties are met. This is achieved by mutual exchange and fulfilment

of promises” (p.138). Tacit within this definition is that organisational and customer

relationships extend beyond transactional motives and involve a mutual co-operation, if

relationships are to be sustained.

According to Payne and Frow (2013) since the 1980s the strategic management of customer

relationships has moved to the forefront of business activities. In the context of the banking

sector, increasing competition has been a catalyst to the escalating importance of customer

loyalty and retention (Alrubaiee & Al-Nazer, 2010). Consequently, there has been an iterative

and gradual paradigm shift away from “telling and selling” towards a more customer-centric

relationship orientation. In other words, relationships are viewed as dynamic and long term as

opposed to once off and transactional (Payne & Frow, 2013). Aijo (1996) offers a different

perspective; he conceptualizes this paradigm shift as a digression away from attaining new

customers towards caring for and maintaining existing customers. Nonetheless, maintaining

relationships with existing customers is being examined with ever increasing vigour.

In recent years there has been a substantial and growing investment in initiatives and resources

which are utilised to manage relationships (Payne & Frow, 2013). Both the growing investment

and appreciation of customer relationships appear to be economically motivated and are well

founded within the literature. At a macro level, relationship management has been recognized

as contributing to the competitiveness of a firm (Chahal & Bakshi, 2015). Numerous authors

emphasize the strategic importance of relationship marketing in the contemporary financial

services sector for example (Berry, 1995; Alrubaiee & Al-Nazer, 2010). More specifically,

Hanks (2007) estimates that a modest 5% increase in customer retention could potentially

increase profitability to the magnitude of 75%. In terms of cost reduction, Bhat & Darzi (2016)

highlight that the cost of acquiring a customer surpass that of retaining an existing one. Thus,

maintaining relational exchanges can favourably impact a firm's receipts and payments.

10

Since the 1980s, the area of relationship management has developed markedly and has been at

the forefront of many marketing scholars and practitioners’ analyses. Morgan and Hunt (1994)

provide a broad interpretation of relationship marketing as “all marketing activities directed

towards establishing, developing, and maintaining successful relational exchanges” (p.22).

Gordon defines relationship marketing as “the ongoing process of identifying and creating new

values with individual customers and then sharing the benefits from this over a lifetime of

association” (1998, P.9). Fundamentally, both definitions emphasize iterative value creation

and a continuance of exchanges.

Relationship marketing as described by

Smyth and Fitch (2009) as a broad concept

that encompasses the management of

relationships with all pertinent stakeholders.

The overarching function of relationship

marketing is to sustain the exchange

process. Customer Relationship

Management (CRM) as depicted in Figure

1.2 (adjacent) is a subset of relationship

management.Figure 1.2 Payne & Frow (2013, P.4)

The purpose of this section was to disaggregate the theoretical fields from top down i.e.

retention is a facet of relationship marketing and relationship marketing is a facet of the field of

marketing. As highlight by Figure 1.2 (above) there are two interrelated terms that have been

used to describe how firms manage relationships. They are; relationship marketing and CRM

(Payne & Frow, 2013). The next section will provide a more in depth discussion of CRM.

11

1.3 Customer Relationship Management (CRM)

In recent years, Customer Relationship Management has amassed great attention from both

marketing practitioners and academics (Baht & Darzi, 2016). CRM essentially involves the

strategic use of technology to ameliorate customer relationships (Payne & Frow, 2013). In the

early 2000s, aided by the rapid and ubiquitous developments in technology, CRM rose to

prominence. Organisations became attuned to the enhanced opportunities of CRM and began to

utilise Information Technology to establish a greater degree of alignment between the desires

and characteristics of the firm and its customer (Payne & Frow, 2013).

Bhat & Darzi (2016) highlight that no universally accepted definition of CRM has emerged.

One definition has been offered by Kotler et al (2009) who define CRM as “the process of

carefully managing detailed information about individual customers and all customer ‘touch

points’ to maximise customer loyalty”. Payne & Frow (2005) offer a similar perspective

highlighting that CRM is a dynamic and cross-functional process that aims to ameliorate and

elongate relationships with consumers. Despite the fact the CRM is a subset of relationship

marketing it has undoubtedly changed the course and definition of relationship marketing

(Sheth, 2002). According to Fournier & Avery (2011) keeping CRM oriented towards

relational needs as opposed to the drive for profitability will pose a significant challenge.

The central intent of customer relationship management is to understand customers and the

elements that are causal to establishing long-term relationships or retention (Thakur, 2014; Al

Hawari, 2015). CRM in the service sector has been orientated towards augmenting service

quality and consequently positively impacting retention and repatronization (Swift, 2001).

Thus, CRM can be utilised by firms as a mechanism of obtaining competitive advantage by

means of improved customer experience (Ahmad and Hashim, 2010).

The adaptation of CRM is now considered a key factor to an organization (Bose, 2002;

Heinonen, 2014). These technologies have significantly enhanced an organization's capability

to manage the heterogeneous clients. According to Sin et al (2005) the use of CRM has a

positive impact on performance in the banking sector. By utilising customer data, CRM

provides a platform for communication, the provision of additional services, and the cultivation

of relationships (Jarvinen, 2014).

The previous passages aimed to provide an understanding of the macro level context, defining

what is meant by marketing and discussing the closely linked concepts of Relationship

12

Management and CRM. An understanding of the aforementioned fields is rudimentary, as

customer retention is highly related to these fields. The section to follow will discuss customer

retention in significant depth and explain why it is important in the context of the banking

sector.

1.4 Customer Retention

In recent decades, customer retention has become increasingly significant in the backdrop of

high churn, customer attrition and growing customer acquisition costs (Bird, 2005; Voss &

Voss, 2008). According to De Madariaga and Valor (2007) the key success factor for survival

in developed or mature markets is maintaining long-term affiliations with customers. It is

therefore perhaps unsurprising that, customer retention has cemented itself as one of the most

pertinent obstacles facing Chief Executive Officers worldwide (Ball, 2004).

Lovelock et al. (1999) posit that attaining a new customer costs five or six times the magnitude

of retaining an existing customer. The notion that acquisition is considerably more expensive

than retention is ubiquitous within the retention literature (Reichheld & Schefter, 2000; Payne

& Frow, 2013). Furthermore, according to Levy (2008) new customers purchase on average

10% less and are less involved in the buying and relationship process overall. Therefore many

organisations have sought to increase their share of market by augmenting the customer

retention levels.

The important concept of customer lifecycle value is highlighted by Kotler (1974, P.24) the

concept of CLV relates to the “present value of the future profit stream expected over a given

time horizon of transacting with the customer”. Similarly, Blattberg et al. (2008) describe the

concept as the net present value of a customer at the date of acquisition until termination.

Intuitively, retaining customers for the long run has a paramount role in optimizing the profit

stream.

Farquhar (2003) states that maintaining existing customers is the intuitive prerequisite to the

establishment of long term customer-organisational relations. Gupta et al (2004) highlights the

significance of customer retention as a performance metric, highlighting that a 1% increase in

customer retention equated to the impact of a 5% decrease in a firm's cost of capital.

Furthermore, these findings are supported by Dawkins and Reichheld (1990) who examined a

wide range of business sectors. Their research suggests that a 5% increase in retention brings

about a 25-90% range of improved profitability.

13

There is a substantial and expanding body of literature pertaining to customer retention.

Despite this, no universally accepted definition has materialized. That being said, there are

overriding similarities and common threads to be found across the different definitions. In

simple terms customer retention insinuates a long term relationship, however numerous other

concepts have become interwoven. Oliver (1997, P.392) interprets customer retention as a

“deeply held commitment to rebuy or repatronize a preferred product or service consistently in

the future, despite situational influences and marketing efforts having the potential to cause

switching behaviour”. A more functional and time bound definition has been offered by

Buchanan & Gillies (1990, P.523) who depict retention as “the percentage of customers at the

beginning of the year that still remain at the end of the year”.

Customer retention has been broached from many divergent theoretical lenses such as

economic, behavioural and psychological standpoints. The concept has also been examined

across different sectors, industries and geographical locations. According to Buttle (2009)

retention studies are predominantly examined from the perspective of the supplier and how

they can better manage relations with customers. Various factors such as customer trust,

perceived quality and switching costs have been identified as causal in the process of retaining

customers (Ranaweera and Prabhu, 2003). These factors have formed the basis for the research

hypothesis and will be examined in greater depth in the sections that follow.

14

1.5 Scope of Customer Retention in the Banking Sector

Customers are the nucleus of any enterprises existence, without them there would be no

revenue, benefits, or market value (Gupta & Zeithaml, 2006). With this in mind, customer

sentiment can be a crucial performance indicator. This is exemplified by Persson and Ryals

(2010) who highlight that practitioners within the financial services sector are calling for the

insertion of customer oriented measures in financial statements. Continuous developments in

technology have to a degree, facilitated these endeavors, allowing companies to collect

consumer data at reduced costs. These developments have springboarded organisations to

adopt more customer centric approaches (Kumar et al., 2009).

As referred to in the previous segments, the cultivation of long-term relationships is of

foremost importance to the sustenance of the financial services sector. Accordingly, the loss of

clients is viewed with considerable concern (Sweeney & Swait, 2008). In previous years, many

banks departed from the conventional banking model that involved accepting deposits and

using the funds to offer loans. We have witnessed a growing proliferation of services offered

by banks to include credit cards, investment management services and even insurance services

(Crane and Bodie, 1996).

In the United States, the financial assets of banks accumulate to two thirds of Gross Domestic

Product (GDP). In Europe however, banks play a more significant role in capital markets. In

contrast to the United States bank assets are greater than three times the magnitude of GDP

(IMF, 2013). In Ireland in particular the value or surpluses added by banks in 2011 was

€10.7bn which equates to almost 7% of Irish GDP (IMF, 2013). However, in the wake of the

great financial crisis of 2008 the majority of the Irish banks have become nationalised. The

resulting heightened regulatory pressures, increasing globalisation and technological

innovation have necessitated dynamism within the sector (Beck, 2014).

The Irish banking sector can be characterised as a competitive industry, in which banks do not

solely compete against each other but also against other financial and non-financial enterprises

(Kinene, 2005). In recent years, the increased competition in the sector from non traditional

entrants such as Paypal has resulted in a reduced number of bank branches in an effort to

reduce fixed costs and remain competitive. In response to these closures there has been an

increase in automatic teller machines and a proliferation of electronic transaction mechanisms

(Cohen et al., 2007).

15

The competitive environment poses a threat of creating a corkscrew of downward price

pressures, and a melee for market share (Johnson et al., 2011). As Irish banks offer near

homogeneous products and services it could be argued that the Irish banking industry bears a

great degree of semblance with the maturity phase of the product lifecycle (Hundre et al.,

2013). Unless a bank can extend beyond the existing product quality within the market, it is

improbable that they will obtain continual competitive advantage (Chang, Chan & Leck, 1997).

With many banks finding it difficult to differentiate themselves substantially based on price

and quality this further cements the importance of customer retention as a means of

competitive advantage. Regulation enforces standards that reduce the ability of banks to

differentiate greatly and reduce the ability of banks to be agile and respond quickly to changes

in the market place.

Bennett and Higgins (1988) detail how enhanced service quality is inextricably associated to

higher revenues, increased cross selling rates, and improved levels of customer retention. In

particular, Dawkins and Reichheld (1990) found that reducing defection rate by 5% led to an

85% increase in one bank branch's profits. The greater costs associated with acquisition (Rust

and Zahorik, 1993) mean that there are obvious benefits to keeping retention rates up, however

this is not a straightforward task (Taylor, 2003).

1.6 The Role of Regulation

In recent years the banking sector in Ireland and further afield has come under heightened

regulatory pressures. This is in large due to the ‘Great Financial Crisis’ (Barth et al, 2013) but

other external developments such as cyber security and data protection have been antecedents

to these changes. Based on a report conducted by consultancy juggernaut Price Waterhouse

Cooper (2015), a staggering 89% of CEOs in the financial services sector In Ireland were

concerned about the impact regulation will have on future growth. Their report (Ibid.) details

how many banks have moved decisively to meet these regulatory requirements, however they

use the analogy of a rubix cube to describe how any regulatory actions may have adverse

consequences if twisted the wrong way. However, many banks find themselves in a quandary,

unsure of what future regulations they will be asked to fulfil (Chortareas et al., 2012).

A well functioning banking system can be a major catalyst to economic development (Levine,

2005; IMF, 2013). However, the converse is also true, banking systems do not always perform

soundly, with the recent financial crisis of 2008 underscoring this undesirable truth. All firms

16

that operate in the broader financial sector are ‘regulated entities’ and accordingly must adhere

to formal regulations and guidelines. In particular, banking is one of the most regulated sectors

worldwide (Chortareas et al., 2012). In this context, regulation is broadly defined by Khemani

and Shapiro (1993, P.73) as the “imposition of rules by government, backed by the use of

penalties that are intended specifically to modify the economic behaviour of individuals and

firms in the private sector”. More specifically, the Central Bank of Ireland (2016) defines

regulated activities as “the provision of products and services that are provided in this State by

a regulated entity and which are subject to the regulation of the Central Bank”.

Whilst numerous studies have pointed to the role of regulation in preventing banking failures

(Hovakimian and Kane, 2000) other studies have posited that regulation may thwart efficiency

and ultimately the bottom line (Jalilian et al., 2007). These points introduce the two different

theoretical lenses through which regulation is examined, which are the “public interest view”

and the “Private interest view” (Barth et al., 2013). The “public interest view” proposes that the

governing bodies act to protect the interests of the public and aim to prevent market failures.

Conversely, the “private interest view” suggests that regulation is used to benefit a minority

and not the general public (Barth et al., 2013). Whether regulation has a net positive or

negative effect is significant bone of contention within the literature and there exists many

conflicting predictions (Barth et al., 2013). Because many studies focus exclusively on types of

regulations and unique geographical areas, the generalizability of the existing studies is

uncertain (Berger et al., 2008).

17

1.7 Research Question and Contributions

The issue of customer retention has been heavily explored by academics and practitioners since

the mid nineties (Ang & Buttle, 2006). The antecedents of retention have been extensively

addressed from a variety of different angles. However, as of yet no studies have explicitly

analysed whether the role of regulation, supervision and monitoring enhance or impede

customer retention. Inherent within the literature is an indication of the potential impacts of

regulation on profitability (Jalilian et al., 2007; Chortareas et al., 2012; PWC, 2015). Customer

retention within the purview of the banking sector may be viewed as a fundamental building

block of profitability, however the impact of regulation on customer retention remains

unexplored.

Regulation can reduce the scope of banking activities thus curtailing the bank's ability to

diversify their income streams (Barth et al., 2013). Furthermore, if greater capital requirements

are imposed for banks there will be a subsequent decline in the availability of credit to

customers (Berger et al., 1995) thus impacting the level of satisfaction clients experience. With

the imposition of new regulatory measures, banks may impart some of the burden of these

measures onto their customers (KPMG, 2013). Therefore, the intended research question is;

‘What impact does regulation have on customer retention within the Irish banking sector?’

This exploration is intended to clarify the impacts that regulatory measures may have on

customer retention and it’s pertinent antecedents. The antecedents of customer retention that

are examined in this paper are satisfaction, switching costs, and trust. These antecedents mirror

those identified by Ranaweera and Prabhu (2003).

18

1.8 Thesis Outline

The structure of this thesis will reflect figure 1.8 found below. The first section sought to

disaggregate from the largest theoretical field of marketing downwards through relationship

marketing and CRM. Additionally, the first section sought to give a pretext on the banking

industry. Lastly, the opening section highlighted the need and importance of the research

question. The section that follows will provide further theoretical background and introduce the

hypothesis which will be tested. The third section details the research methodology in

significant depth. The fourth and perhaps most significant section deals with the analysis and

findings of the study. The fifth section will be comprised of three different elements; the

limitations of the research; further research and improvements and the conclusion of the

research. Section six and seven offer appendices and bibliography respectively.

Figure 1.8 Thesis Outline

19

Section Two: Theoretical Background

20

2.1 Theoretical background

In traditional market dynamics any price changes or externalities might be expected to be

forwarded on to customers. Consequently, it is realistic to assume that the existing regulation

and regulatory changes may impact customers (KPMG, 2013). This section extends on from

the vital context that was provided in section one. The objective of this section is to outline the

factors that are commonly cited as impactful in customer retention and to illuminate how

regulation may impact these variables.

2.2 Impact of Switching Costs on Retention

There are numerous factors that may impact on customer retention. One such factor is that of

switching costs or switching barriers. Switching costs occur when customers expend time and

effort to learn how to use a product or service (Brush et al., 2012). A plethora of studies

explore the role of switching costs in establishing long term relationships (De Matos et al.,

2013). According to Brush et al. (2012) switching costs are synonymous with the

discontinuation of a relationship with an existing supplier and the commencement of a

relationship with a new supplier. These costs provide a disincentive for customers to leave the

organisation (White & Yanamandram, 2007). Switching cost theory illustrates how enterprises

may obtain competitive advantage by making it costly or disincentivising existing customers to

defect (Brush et al., 2012).

When perceived switching cost are high customer retention is expected to be high and vice

versa (Ranaweera & Prabhu, 2003). Hauser et al. (1994) established that switching costs can

act as a mediating factor against low customer satisfaction. Similarly, switching barriers have

been noted to affect both trust and service quality (Aydin et al. 2005). Lee & Neale (2012,

P.365) define switching costs as “inconveniences or penalties that entrap customers to service

providers”. Another definition is offered by Bansal and Taylor who describe switching cots as

the customer's “assessment of the resources and opportunities needed to perform the switching

act” (1999, P. 203).

The capacity to retain customers is a significant concern to all enterprises, but even more so, to

those who invest heavily in acquisition and advertising (Chen & Hitt, 2002). Seminal work

carried out by Panther and Farquhar (2004) illustrates that customers within the banking sector

chose to persist with their existing bank if they evaluate the perceived cost of time, effort and

uncertainty exceed the potential benefits of switching. In service industries such as banking,

21

where there are high switching costs, customers with low satisfaction may continue to purchase

the service (Curasi and Kennedy, 2002). High switching costs have been linked to high internal

cross selling of goods and services (Brush et al, 2012).

Research conducted by Burnham et al. (2003) states that there is a minimum of three different

types of explicit switching cost these include: financial, procedural and relational. Firstly,

financial switching costs relate to fees of breaking contract or penalties. Secondly procedural

costs relate to the time, effort and uncertainty attached to adopting a new service. Lastly,

relational costs pertain to the loss of personal relationship or identification with the brand and

employees. Ranaweera and Prabhu (2003) suggest that switching costs should ‘add value to the

service’ so that they limit or moderate customer resentment. Below are the hypotheses in

relation to switching costs. The notation HA signifies the alternative hypothesis whilst Ho

relates to the null hypothesis.

HA 1: Regulation increases switching costs.

Ho 1: Regulation has no effect on switching costs.

HA 2: Switching costs increase customer retention.

Ho 2: Switching costs have no effect on customer retention

22

2.3 The Impact of Trust on Retention

Dimitriadis et al. (2011) cite that trust is a dynamic and multifaceted construct that has many

differing interpretations and definitions within the relationship marketing literature. For

example, Ganesan (1994), Sirdeshmukh et al. (2002) and Grayson et al. (2008) all depict and

gauge trust disparately. Despite the paramount importance of trust, no universal definition has

emerged from the literature (Kantsperger & Kunz, 2010). Morgan & Hunt (1994) believe trust

to be the level of confidence in an exchange partner's integrity and reliability. A similar

conceptualisation is offered by Mayer et al. (1995) who define trust as ”the willingness of a

party to be vulnerable to the actions of another party based on the expectation that the other

will perform a particular action important to the trustor, irrespective of the ability to monitor

or control that other party” (P. 712).

According to Lewis and Weigert (1985) the psychology literature trichotomized trust as

consisting of cognitive, affective, and behavioral components. Affective trust relates to the

confidence a customer has in their provider based on the level of care experienced (Rempel et

al., 1985). Secondly, cognitive trust relates to the willingness of a customer to trust based on

their reliability and ethical conduct. Lastly, behavioural trust constitutes the actions that stem

from or are a consequence of simultaneous cognitive and affective trust (Lewis & Weigert,

1985). Alternatively, within the social psychology literature there appears to be two constructs

of trust, they are; honesty and benevolence (Wetzels et al., 1998). Honesty is described as

adherence to promises and benevolence is depicted as degree of interest in customers’ welfare.

Abratt and Russell (1999) illustrated that trust, service quality and price are influential in the

customer's initial selection of a bank. These factors appear to be as influential in the

maintenance and continuation of relationships. According to Bendapudi & Berry (2007) trust

lessens the cost of negotiating agreements and reduces the customers apprehension of

opportunistic behaviour by the supplier. Trust is widely cited as a central component of

repurchasing behaviour (Prabhu & Ranaweera, 2003; Ball et al., 2004).

Dimitriadis et al. (2011) propose that trust can be causal in turning satisfaction into customer

retention. Similar studies highlight that trust plays a mediating role between post purchase

satisfaction and the future behavioural intentions of customers (Ha, Janda, & Muthaly, 2010;

Fang et al., 2011). Hart and Johnson (1999) posit that trust is actually a stronger driver or

predictor of customer retention than customer satisfaction. Prabhu & Ranaweera (2003) offer a

23

firm rebuttal of this point, highlighting that not enough research has been undertaken to

examine the relative explanatory power of the two seminal constructs.

According to a report conducted by Ernst & Young (2010) 45% of customers indicated that the

great recession of 2008 negatively or very negatively impacted their trust of the banking sector.

As a result of the decline in trust, many customers sought to diversify, seeking financial

services from more than one provider (Ernst & Young, 2010). Perceptions of banks further

deteriorated when payments of bonuses persisted despite the need for substantial taxpayer

support (Ernst & Young, 2010). Consequently, it was imperative for banks to consider ways to

ameliorate trust with their clients. One mechanism for achieving higher levels of trust is by

adhering to ethical practices (Ernst & Young, 2010). The null and alternative hypotheses

pertaining to this section are found below.

HA 3: Regulatory controls increase consumer trust.

Ho 3: Regulatory controls have no impact on consumer trust.

HA 4:Trust increases customer retention.

Ho 4: Trust has no impact on customer retention.

24

2.4 The Impact of Customer Satisfaction on Retention

The sovereignty of customer satisfaction as a component of customer retention has long since

been recognised and is researched eminently in the preexisting literature (Arbore and Busacca,

2009). Consequently, many banks have directed their strategies towards customer satisfaction

as a means to augment their financial performance (Arbore and Busacca, 2009; Hossain & Leo,

2009). Satisfaction however, appears to be a necessary but not a wholly sufficient condition for

retention, because satisfaction alone cannot assure long term custom (Nasab & Ling, 2012). To

complement satisfaction factors such as trust and switching costs have been identified as

impactful on retention (Ranaweera and Prabhu, 2003).

That being said, satisfied customers are linked with a myriad of benefits for banks as they tend

to be loyal and more inclined to recommend the bank to others (Ranaweera and Prabhu, 2003;

De Matos et al., 2013). Terpstra and Verbeeten (2014) found that satisfied customers may be

willing to purchase a firm's services even if there is a price premium associated with doing so.

Additionally, higher customer satisfaction has also been found to increase cross selling of

financial products in bank branches (Grigoroudis, Tsitsiridi, and Zopounidis, 2013).

Importantly, customer satisfaction leads to better financial performance (Hauser, Simester and

Wernerfelt, 1994; Fathollahzadeh et al., 2011).

There are numerous different depictions of satisfaction within the academic literature. A broad

definition is offered by Hansemark and Albinsson (2004) who describe it as “an overall

customer attitude towards a service provider, or an emotional reaction to the difference

between what customers expect and what they receive, regarding the fulfillment of some need,

goal or desire”. Similarly, Vesel and Zabkar (2009) conceptualize satisfaction as the

fulfillment that a customer feels based on their interaction with a company.

Variations in the quality and value of services will subsequently result in variations in customer

satisfaction and by extension loyalty (Auh & Johnson, 2005). In regards to banking, personal

interaction quality has been identified as something influential with regards to customer

satisfaction. Likewise, convenience has been identified to positively impact customer

satisfaction (Arbore and Busacca, 2009). Convenience encompasses factors such as proximity

to bank, bank opening hours, parking availability, & ATM availability (Jones, 2004; Manrai,

2007)

HA 5: Regulation increases customer satisfaction.

25

Ho 5: Regulation has no impact on customer satisfaction.

HA 6: Customer satisfaction increases customer retention.

Ho 6: Customer satisfaction has no impact on customer retention.

The conceptual model below (Figure 2.4) illustrates the intended hypothesis.

Figure 2.4 Conceptual Model

26

Section Three: Research Methodology & Design

27

3.1 Introduction

In the previous chapter the research gap was outlined in great depth. This chapter details the

research design and the research methodologies utilized to address the research question. Sim

& Wright (2000) intuitively suggest that the research question determines the adopted

methodological approaches and the data collection techniques. However, Silverman (1993)

claims that there are no binary right or wrong methodological approaches but merely a

spectrum of more or less suitable approaches.

Broadly speaking, the structure of this chapter reflects that of the research onion as detailed by

Saunders, Lewis and Thornhill (2012). Consequently, section 3.2 will outline the research

paradigms, values, and philosophy adopted. Section 3.3 will detail the research approach.

Section 3.4 will discuss the methodological choice. Section 3.5 is a substantial section which

will outline the research strategy. Section 3.6 will discuss the questionnaire design. Section 3.7

will outline the time horizon. Section 3.8 will present the sampling methods employed and the

response rate. Section 3.9 details the data analysis and Interpretation methods. The penultimate

section presents the ethical considerations of undertaking this research. Lastly, section 3.11

offers a brief summary of this chapter.

3.2 Research Philosophy & Paradigm

At every juncture in our research we make assumptions, beit about the nature of reality or

about human knowledge (Saunders, Lewis & Thornhill, 2012). These assumptions invariably

mould how we address the research question and how we interpret or discuss the materialized

findings (Crotty, 1998). Heron (1996) suggests that values are the driving force behind human

action and consequently can be impactful on the research results. If the researcher can

adequately convey their values they demonstrate axiological skill and credibility (Ibid.).

Research philosophy, as described by Saunders, Lewis, & Thornhill (2012, P.127) refers to

“the development of knowledge and the nature of that knowledge”. In the same vein, the

research philosophy adopted can be seen to be indicative of the way in which the researcher

views the world. Johnson and Clark (2006) highlight that business and management researchers

ought to be aware of the implications and philosophical commitments that the choice of

research strategy may result in. The four major research philosophies underpinning business

research include positivism, interpretivism, realism and pragmatism (Saunders, Lewis,

Thornhill, 2012).

28

3.2.1 Positivism

The philosophical stance of positivism is likened to that of a natural scientist. According to Gill

and Johnson (2010) this stance is orientated towards collecting data about observable realities

in order to establish regularities and cause and effect relationships. Consequently, this research

paradigm seeks to have a robust methodological structure so that results can be easily

replicated (Gill & Johnson 2010). The positivist paradigm leans on quantifiable variables that

are suited to statistical analysis. According to Saunders, Lewis & Thornhill (2012) commonly

used research methods and forms of analysis include experiments, questionnaires, secondary

data analysis and statistical analysis. Another pertinent facet of this paradigm is that it assumes

that the researcher is value neutral. The concept of value neutrality however is contentious

(Saunders, Lewis & Thornhill 2012).

3.2.2 Realism

Similar to the philosophical stance of positivism, realism is a predominantly scientific line of

enquiry. According to Saunders, Lewis and Thornhill (2012) the crux of realism is that what

we sense is ultimately reality, and that objects exist independent of the mind. Realism is

dichotomised into direct and critical components. Direct realism relates to a case in which our

experience mirrors the world accurately i.e. what you see is what you get. On the other hand

critical realists argue that our experience is based on our sensations and perceptions of things

and not the things themselves directly i.e. our senses may deceive us (Saunders, Lewis and

Thornhill, 2012). In the context of the business environment critical realism would

acknowledge the ability of employees, departments and the firm to shape the understanding of

what is being examined. Conversely, direct realism is somewhat rigid and unchanging

(Saunders, Lewis and Thornhill, 2012).

29

3.2.3 Pragmatism

Pragmatism contends that concepts or theory are only meaningful if they reinforce action

(Kelemen and Rumens 2008). Pragmatists recognise that there is no binary right or wrong way

to view the world. In the pragmatists view no single point of view can ever give an entire

picture of the world. Therefore, the most crucial determinant of a researcher's position is

ultimately the research question (Nastasi et al. 2007). If a research question doesn’t distinctly

suggest which philosophy should be adopted, then this adds further weight to the pragmatist

viewpoint, i.e. that it is possible to work with multiple viewpoints (Saunders, Lewis, Thornhill,

2012). Pragmatism doesn’t imply the use of multiple methods, but rather they employ the

methods that facilitate credible, reliable and pertinent data to be collected (Kelemen and

Rumens 2008).

3.2.4 Interpretivism

The interpretive paradigm is normally associated with small samples and qualitative research

(Saunders, Lewis, Thornhill, 2012; Denzin & Lincoln, 2005). The interpretive paradigm is

normally less structured relative to the positivist paradigm (Ragsdell, 2009). This is because

interpretive research seeks to make sense of subjective realities. In other words the interpretive

paradigm contends that individuals perceive both physical and social realities in different ways.

Hence, this approach emphasizes the role of individuals or ‘social actors’ (Saunders, Lewis, &

Thornhill, 2010). According to (Ang, 2014) this enables researchers to establish a socially

constructed depiction of reality. The less structured approach, different interpretations and

investigative bases may result in greater variation of results (Hallebone and Priest, 2009).

However, some researchers posit that the interpretivist perspective is most compatible with

business and management research (Ang, 2014; Saunders, Lewis, & Thornhill, 2012).

Therefore based on the understanding detailed in previous paragraphs the researcher believes

that this research bares the greatest degree of resemblance to the interpretivist paradigm.

30

3.3 Research Approach

The sole purpose of research is to develop and refine theory until it can adequately approximate

reality. In this regard there are three predominant approaches to developing theory, which are

referred to as inductive, abductive and deductive approaches (Saunders, Lewis & Thornhill,

2012). The abductive approach relates to a situation in which the researcher starts with a

‘surprising fact’ or conclusion as opposed to a premise (Ketokivi & Mantere, 2010). In other

words a known or phenomenon are utilised to generate testable conclusions. In contrast, the

inductive approach allows meaning to emanate throughout the data collecting process thus,

facilitating the identification of patterns and relationships (Johnson & Clark, 2006). This

approach facilitates theory building and generation. Lastly, the deductive approach describes a

situation in which the researcher presupposes an explicit theory for investigation. Data is then

collected to evaluate the research hypothesis. In other words, the deductive approach involves

theory falsification or verification. This research most closely aligns with the deductive

approach.

3.4 Methodological Choice

According to Burrell & Morgan (1979) methodology refers to the different strategies that can

be utilised by researchers to address a research question. Saunders, Lewis & Thornhill, (2012)

highlight that one of the first methodological choices relates to whether quantitative, qualitative

or mixed methods are employed. A common heuristic used to distinguish these methods is that,

qualitative relates to non numeric data (words, video, etc.). Conversely, quantitative refers to

numeric data (Saunders, Lewis & Thornhill, 2012). Commonly business and management

research designs employ both quantitative and qualitative components. While a questionnaires

technique is synonymous with the quantitative technique, many questionnaires contain open

ended questions. In this way it is problematic to see quantitative and qualitative research as

binary options, but rather as a continuum (Saunders, Lewis & Thornhill, 2012).

According to Creswell and Clark (2007) varying priority or weight can be delegated to

quantitative or qualitative within the purview of mixed methods research. In simple terms one

method can play a supporting, dominant or equal role contingent on the research question. By

extension the researcher and those who commission or supervise the student may also guide the

prioritisation of one method (Saunders, Lewis & Thornhill, 2012). The term embedded mixed

methods research describes a situation in which one method supports the other (Creswell and

31

Clark, 2007). In this study, qualitative data was used only to support the the predominant

quantitative approach.

3.5 Research Strategy

The previous section discussed the methodological choice. The methodological choice and the

research strategy are for the most part closely linked (Denzin and Lincoln 2005). The term

strategy essentially describes the manner in which a goal is achieved. By extension, research

strategy is how the research intends to answer the research question (Saunders, Lewis &

Thornhill, 2012). This research has adopted a survey strategy that is normally coupled with the

deductive research approach. The survey approach is ubiquitous within the domain of business

and management research.

Surveys using questionnaires are extremely common and as with any research strategy have

considerable strengths and weaknesses. The most significant drawback of adopting a survey

method is the capacity to execute it poorly (Ang, 2014). However, surveys can be utilised to

establish how a population thinks or behaves in regards to a phenomena. Surveys are generally

both easy to explain and understand, and enable the collection of highly standardised data in a

fairly economical manner (Sekaran, 2000). A quantitatively based survey strategy facilitates

the use of descriptive and inferential statistics. This strategy can produce models that explain

the nature of relationships between variables (Hallebone and Priest, 2009).

3.6 Questionnaire Design

The questionnaire utilized in this study was formed based on rigorous examination of the

existing academic literature. To enhance credibility with potential participants the

questionnaire was given a brief and straightforward title as suggested by Johnson & Clark

(2006). Simply put, the questionnaire had four components. The first component provided a

brief summary of the study, an estimated time of completion and assurance of confidentiality

and anonymity. The second component consisted of demographic and administrative questions

(gender, age, educational attainment, banking provider etc.), this segment was eight questions

in duration. Evan & Miller (1966) highlight that questionnaires should commence with easy to

answer subjects to decrease possible attrition. The third component involved the use of existing

academic measures for the hypothesised phenomenon. Lastly, new measures were incorporated

to answer the hypothesis as no previous studies or measures of the required kind where

32

available. The survey instrument used was twenty five questions long to ensure that the

goodwill of the participants was not abused.

With regards to questionnaires there are a number of different types of questions that can be

asked. Firstly questions may be open or closed. Open relates to questions which allow

respondents to express their sentiments in their own words. Conversely, closed questions

confine respondents to predetermined responses. For the most part, the questionnaire utilised

was formed with closed questions. Closed questions represent a convenient way of collecting

the data and are comparatively easier to analyse (Wolcott, 1994). Many examples of closed

questions can be found in the questionnaire (Appendix 1, Q1,3,6,7,8). The different types of

closed questions utilized included multiple choice, classification and rating scale questions.

Likert scales are the most commonly used summated rating scale and allow participants to

convey their level of agreement or disagreement with a given statement (Blumberg et al.,

2008). Thirteen of the twenty five questions utilised a one to five likert scale. Twelve of the

thirteen questions ranged from strongly disagree to strongly agree. The remaining question

which measured propensity to switch banks ranged from Not at all likely to Very likely. Some

questions such as the NPS (Q.9, Appendix 1) and the Net Easy Score (Q.10, Appendix 1) were

extracted exactly as they were, as they were recognised metrics in the literature. Question nine

was the NPS, a method commonly used by companies to gauge satisfaction. The NPS ranges

from one to ten on a numerical scale, with one being not at all likely and ten being extremely

likely. The NES on the other hand ranges from one to seven, with one being extremely difficult

and seven being extremely easy.

According to Saunders, Lewis and Thornhill (2012) the ordering of questions can be

potentially impactful on participants responses. The questionnaire was designed with this in

mind and stringent efforts were made to avoid leading questions. Efforts were made to ensure

the questionnaire was logically structured as suggested by Moreno (1998). In order to avoid

any misinterpretations a pilot test was carried out with eight participants. On the basis of this

corrective amendments were made to the questionnaire. At this point the survey was forwarded

to two academic professionals one with a strong grounding in marketing and another who has a

strong command of instrument development and research methodology. On the basis of this

valuable feedback, the final amendments were made to the questionnaire. The questionnaire

was distributed from June 26th until July 10th, 2016 and can be found in Appendix 1.

33

3.7 Time Horizon

According to Saunders, Lewis & Thornhill (2012) one of the pressing issues a researcher must

address is over what time horizon the research will be conducted. In this regard there is two

predominant categorisations i.e. cross sectional and longitudinal. Cross sectional is described

as a ‘snapshot’ taken at a particular time. Conversely, longitudinal research is likened to a

series of snapshots (Saunders, Lewis & Thornhill, 2012). Many cross sectional studies utilize

the survey strategy, as is the case with this research. In reality, due to the time constrained

nature of the research longitudinal research was rendered impossible, this will be discussed

further in the limitations and further research sections.

3.8 Sampling

In order to get a better understanding of what a sample is, we must first define what is meant

by population. According to Berenson & Levine (1988) the population is the entire collection

of items, persons or things that warrant consideration. As previously alluded to the population

of this study is essentially all non commercial customers of Irish banks. The sample is a

pertinent facet of research methodology. Berger and Benbow (2006) define the term sample

quite broadly as “A group of units, proportion of material, or observations taken from a larger

collection of units, quantity of material, or observations that serves to provide information that

may be used as a basis for making a decision concerning the larger quantity” (P.552).

According to Cavana et al. (2001) no sampling method is perfectly random and as a

consequence it is impossible to have a quintessentially random sample.

In order to obtain respondents for this study two non-probability sampling techniques were

utilized. They were volunteer and haphazard techniques as described by (Saunders, Lewis, &

Thornhill, 2012). Two volunteer sampling techniques were used i.e. snowball and self selection

sampling. Snowball sampling involves identifying respondents and asking them to identify or

expose the research to further members of the population. This process is continued iteratively

until the sample is sufficiently large (Saunders, Lewis, & Thornhill, 2012). According to Lee

(1993) this method can result in a homogeneous sample. Secondly, self selection sampling was

employed, this occurs when the need for cases is openly publicised through media or by asking

individuals to take part.

34

Convenience sampling which is sometimes referred to as opportunity sampling is generally the

most efficient and economical form of sampling (Blumberg et al, 2008). Sample participants

are generally selected on the basis that they are ready, available and convenient to the

researcher (Denscombe, 2007). Consequently, convenience sampling can be prone to bias.

Firstly, the most popular form of convenience sampling that is known as haphazard sampling

was employed (Saunders, Lewis, & Thornhill, 2012). In this sampling method participants

appear in the sample because of the ease of obtaining them.

Response rates represent a salient concern for researchers who distribute questionnaires

(Saunders, Lewis, Thornhill, 2012). Response rates are intuitively defined by De Rada (2005)

who describes them as the number of finished questionnaires that are returned divided by the

number of questionnaires which were distributed. Two conflicting interpretations of response

rates have emerged within the literature. According to Edwards et al. (2002) low response rates

can impact the reliability of any research. Alternatively, others have downplayed the

significance, arguing that it does not necessarily increase reliability and the precision of results

(Dillman, 1991). Nevertheless, it is favourable to achieve a high response rate to lessen the risk

of non response bias and to have the best chance of having a representative sample (Groves and

Peytcheva 2008).

According to Sauermann & Roach (2013) online surveys have become an increasingly

important mechanism for conducting research, but are often blighted low response rates.

However, there are many suggested practises to increase response rates. Firstly, the potential

respondents were briefed about the objectives of the study, secondly, potential respondents

were provided an estimated duration of the study, thirdly participants were assured of

confidentiality and anonymity. Sauermann & Roach (2013) highlight that personalization

enhances the chance of prospective participants responding by as much as 48%. Whilst the

survey remained entirely unchanged, efforts were made to personalise any interaction with the

participants were possible. Respondents were informed to complete the survey when they had a

chance as suggested by Kalman (1988) and accordingly respondents trickled through for a

number of days preceding the issuance of the questionnaire.

After examining the completed questionnaires, ten responses were rejected on the grounds that

the participants did not currently hold an Irish bank account. One hundred and ninety five

responses were accepted. This sample size is adequate to conduct the main statistical analysis

in this paper. The survey response rate was 64%, of the three hundred and twenty issued, two

35

hundred and five returned fully completed. According to Baruch and Holtom (2008) response

rates in excess of 50% are regarded as reasonable.

3.9 Data Analysis & Interpretation

There are a variety of different statistical techniques that researchers can employ to analyse

data (Ang, 2014). These techniques however can be dichotomised into parametric and

nonparametric tests (Saunders, Thornhill & Lewis 2012). The term parametric is derived from

parameter, which means a characteristic of a population. Parametric tests (e.g Pearson's product

moment correlation) presuppose that the population is normally distributed. Conversely, non

parametric tests are more ductile, they do not have as rigid requirements on the population

from which the sample is being drawn (Johnson & Clark, 2006). Non parametric tests can

oftentimes be labeled distribution free tests. As much of the data collected in this study is not

normally distributed, but rather right or left skewed non parametric tests are suitable (Johnson

& Clark, 2006).

Non parametric tests are somewhat of a double edged sword, in that they are less stringent but

they also tend to be less powerful. Non parametric tests may fail to recognize relationships or

differences which are in fact statistically significant. (Ang, 2014) As a result, it is always

preferable to use a parametric test, if it is possible. The specific non parametric test utilised in

this study is Spearman’s Rank Order correlation (rho). Spearman’s Rank Order Correlation can

be employed to gauge the strength of the relationship between two continuous variables

(Saunders, Thornhill & Lewis 2012). This method is utilized regularly within the domain of

business and management research and is particularly useful for ordinal or ranked data (Ang,

2014).

The tests where conducted using the popular statistical program, SPSS. The tests utilized will

be one tailed, as the nature of the relationships between variables is specified in the hypothesis.

The significance level will be specified in the discussion section and will be equal to 0.05 or

0.01. The output is interpreted in accordance with the scale (Figure 3.9, found on the following

page) developed by Hair et al. (2006).

36

Figure 3.9 Correlation Interpretation

3.10 Ethical Consideration

This study involves interaction with individuals and examines human behaviour. Consequently,

ethical considerations were necessary at all stages of the research. This study met the

requirements of the Ethics Board at Trinity College Dublin. This study is carried out in

accordance with the TCD Good Research Practice. As a result, all participants were assured

confidentiality and anonymity. According to Alsmadi (2008) potential participants may feel

threatened if studies are not anonymous. Fuller (1974) outlined that research, which is not

anonymous, suffers with decreased response rates. Conversely, confidentiality relates to those

who undertake the research (Kumar & Phrommathed, 2005). All data collected, will remain

solely and safely in my possession. Lastly, the purpose of this study was succinctly and clearly

explained to participants. Furthermore, all participants were informed that completing the

survey was entirely voluntary (Sekaran, 2000).

37

3.11 Summary

This section offers a brief summary of section three. Section 3.2 addressed the research

philosophy, this study bears the greatest degree of semblance with interpretivism. In regards to

the research approach (section 3.3) this study adopts a inductive approach. The methodological

choice (section 3.4) was mixed methods simple, the data however was predominantly

quantitative. The research strategy adopted was a survey method. The instrument development

was detailed in section 3.6. Section 3.7 briefly discussed the time horizon of the study, this

study is undoubtedly cross sectional in nature. Section 3.8 was a substantial section that

outlined the sampling methods used and the response rates. The data analysis and interpretation

techniques were outlined in section 3.9. Finally, ethical considerations were discussed in

section 3.10. The Research onion below (Figure 3.11) offers a summary of this chapter.

Figure 3.11 The Research Onion (Saunders, Lewis & Thornhill, 2012)

38

Section Four: Data Analysis & Findings

39

4.1 Introduction

The central focus of this study is to establish the impact that regulation is having on customer

retention in the Irish banking sector. In chapter one and two, the importance and elements of

customer retention were outlined. Chapter three detailed the methodological choices used to

collect customer data. This section will provide comprehensive description, analysis and

discussion of the data set. The first component will detail the demographic characteristics and

elements of the customer supplier relationship. The second aspect will explore the hypothesis

and other relevant findings.

4.2 Sample Description

This segment will profile the participants based on their demographic factors such as age,

gender, and educational attainment. Secondly, this section will use the customer data to

develop a more conclusive understanding of industry trends for example market share and

retention rates. Additionally, an outline of the regulatory requirements that many customers are

exposed to will be detailed. Lastly, the customer perceptions of these requirements will be

discussed.

4.2.1 Gender Distribution

Respondents were asked to give very basic and brief demographic details. The sample that

originally consisted of 205 participants had to be reduced to 195 on the grounds of ineligibility.

The 10 participants who were ineligible were not customers of banks that currently operate in

Ireland. The 195 participants were broke down as follows, 112 were females and the remaining

83 were males. This translates to 57.4% representation of females and 42.6% representation of

males. The gender distribution is summarised in Table 4.2.1 (found on the following page).

Studying the impact of gender is not the intention of this research, from an exploration of the

literature there is no indication that gender may impact customer retention in the banking

industry.

40

Table 4.2.1 Sample Gender Distribution

Gender Frequency Percentage

Male 83 42.6%

Female 112 57.4%

Total 195 100%

4.2.2 Age Profile of the Sample

The average age of the sample overall was quite low at 29.5 years of age. The female cohort

had an average age of 29.3 years, while the males had a 29.8 years average age. There was a

standard deviation of 10.2 years within the sample. The vast majority of the sample 70.2% was

between the ages of 20-30. The second highest representation was between 30-40 with 17.4%.

The 40-50 and 50+ age bucket accounted for 12.4% cumulatively. Table 4.2.2 gives a summary

of the age profile of the sample. The age profile of the respondents will be discussed in further

detail in the limitations section of the paper.

Table 4.2.2 Age profile of the Sample

Age Male Female

18-30 60 77

31-40 14 20

41-50 4 11

50+ 7 4

Average Age 29.8 29.3

41

4.2.3 Educational AttainmentAnalysis of the sample shows that twenty nine or 14.9% of the participants had a

Certificate/Ordinary Degree equivalent of level 6/7 NFQ. The number of respondents who had

completed Honours/Bachelors’ Degree or level 8 NFQ was eighty three or 42.6%. Thirdly, a

total of forty five or 23.1% had a level 9 NFQ or above. Although the CSO report from 2011

shows very significant increases in levels of educational attainment, the population is

significantly above the average.

A comparison with the a report compiled by the Central Statistics Office (2011) shows that the

sample used in this study are on the whole educated to a higher degree than the general

population. Nearly two thirds of the respondents had obtained greater than a level 8 on the

NFQ as opposed to 38% of 25-64 year olds (CSO, 2011). Typically, educational attainment is

related to increased earnings potential and higher labour force participation and as a result may

influence the level of awareness of the complex regulatory landscape and/or influence other

variables such as trust (Oreopoulos & Salvanes, 2011). One could also argue that amongst the

lower educated that switching costs may be perceived to be higher for complex products, which

will be discussed further research section 5.2.

Approximately 17% of participants had been educated to leaving certificate level and No/Some

Schooling represented the smallest proportion of participants with a meager 2.1%. This will be

elaborated on further within the limitations component found in chapter five. The summarised

results can be found below in Table 4.2.3.

Table 4.2.3 Table of Educational Attainment

Educational Attainment Female Male Percentage Grand Total

Certificate/Ordinary Degree (Level 6/7 NFQ) 22 7 14.9% 29

Honours/Bachelors' Degree (Level 8 NFQ) 42 41 42.6% 83

Master's Degree or Doctorate (Level 9/10 NFQ)

24 21 23.1% 45

Leaving Certificate Graduate 21 13 17.4% 34

No/Some Schooling 3 1 2.1% 4

Total 112 83 100.0% 195

42

4.2.4 The Frequency of Banks within the Sample

It is imperative to establish a better understanding of the financial services providers within the

Irish banking sector. In this regard, using the sample data can be insightful to establish some

context. Officially, the participants identified six banks that operate in Ireland. That being said,

it is clear based on the data found in Table 4.2.4, that the banks which have been informally

dubbed the ‘big four’ are the most significant players, with a massive 97.5% market share

cumulatively. According to the data Allied Irish Bank (AIB) has the largest market share of

42% followed by Bank of Ireland who have approximately one third of the market space. The

third most significant player was Permanent TSB who had a 12.3% market share. The last of

the ‘big four’ Ulster Bank had 9.7% share of the market.

Table 4.2.4 The frequency of banks within the sample

Service Provider Number of Respondents Percentage of Respondents

Allied Irish Bank 82 42.05%

Bank of Ireland 65 33.33%

EBS 4 2.05%

KBC 1 0.51%

Permanent TSB 24 12.31%

Ulster Bank 19 9.74%

Total 195 100.00%

4.2.5 Number of Respondents who Switched Bank in the last year

Buchanan & Gillies (1990) defined retention as the “percentage of customers at the beginning

of the year that still remain at the end of the year” (P.523). Accordingly, the respondents of

the study were asked to indicate whether or not they had switched in the last year. In response

it was established that seven females had, these females represented 3.6% of the sample.

Similarly, three males indicated they had switched, accounting for 1.5% of the overall sample.

Overall, a meager 5.1% of the sample changed banks.

43

The overwhelming majority 94.9% of clients remained with their banks, indicating for one

reason or another customer retention in the banking sector appears extremely high. Table 4.2.5

provides a summary of the results below.

Table 4.2.5 Frequency of Switching in the previous year

Switched Female Male Total Female Male Total

No 105 80 185 53.85% 41.03% 94.87%

Yes 7 3 10 3.59% 1.54% 5.13%

Total 112 83 195 57.44% 42.56% 100.00%

4.2.6 Relationship Longevity with Service Provider

Whilst Buchanan and Gillies (1990) constrained their definition of retention to those customer

remaining after one year, it is also insightful to see how retention extends out over longer

durations. Relationship longevity is important for a myriad of reasons. For example, Bhat &

Darzi (2016) highlight that customer acquisition is significantly more costly than retaining an

existing customer as alluded to earlier. Overall, the sample indicates that many customers bear

long relationships with their providers. Within the sample 83.5% indicated that they had been

with their provider for over 3 years. With the remaining 16.5% indicating that their relationship

was less that three years. Table 4.2.6 offers a summary of these findings below.

Table 4.2.6 Relationship longevity with primary service provider

Duration with Service Provider

Female Male Total Female Male Total

5 years plus 73 55 128 37.4% 28.2% 65.6%

Between 3 and 5 years 19 16 35 9.7% 8.2% 17.9%

Between 1 and 3 years 8 5 13 4.1% 2.6% 6.7%

Less than 1 year 12 7 19 6.2% 3.6% 9.8%

Total 112 83 195 57.4% 42.6% 100%

4.2.7 The Frequency of Banking Channels utilised

44

There are numerous channels by which customers may obtain financial services from their

provider. Based on the sample collected the most popular method of usage was online banking

with 89.2% indicating they utilize the channel. Surprisingly, the conventional channel of

branch banking has a reported usage of just 61.5%. Lastly, phone banking ranked the least

popular method of obtaining financial services with a 21.5% reported usage. Based on the

sample customers used on average 1.71 channels to carry out their banking requirements.

Table 4.2.7 Frequency of Banking Channels utilised

Banking Channels Utilised No. Percentage

Online Banking 193 89.2%

Branch Banking 119 61.5%

Phone Banking 42 21.5%

Average number of banking channels used 1.71 -------------------

4.2.8 Frequency Banking Products with Primary Service Provider

In recent years, there has been a proliferation of the products that banks offer their customers.

This section required customers to indicate what services they obtain from their primary

service provider. Unsurprisingly, almost all participants or 98.9% of participants indicated that

they currently had a current account and debit card. Savings accounts where the next most

popular product with 43.6% of the sample indicating their usage. Approximately, one quarter

(25.1%) indicated that they obtained a credit through their bank. 10.7% of the sample indicated

the relied on their service provider for personal loans and a small proportion of 6.67%

indicating they had mortgages with their primary provider. Importantly, the sample had on

average 1.86 banking products with their primary service provider, which is indicative of

strong cross buying of financial services. Table 4.2.8 offers a summary on the following page.

Table 4.2.8 Frequency of banking products with primary service provider

45

Products availed of by customers No. Percentage

Current account & Debit Card 193 98.9%

Savings Account 85 43.6%

Credit Card 49 25.1%

Personal Loan 21 10.7%

Mortgage 13 6.67%

Average number of products used per customer 1.86 -------------------

4.3.1 Perception of Regulation

The questionnaire design was not solely based around answering the hypothesis, but also about

providing broader context to the subject area. In this capacity, two questions focused solely on

the perception of regulation. The first question in this regard asked participants to outline the

degree to which they agreed with the statement ‘It is better for banks to be highly regulated’.

As the bar chart below (Figure 4.3.1a) indicates that an overwhelming majority (84.6%) either

agree or strongly agree with the statement. Looking at the opposite end of the spectrum only

1.5% of the sample disagree or strongly disagree. The remaining 13.8% neither disagree nor

agree. This suggests that the participants have positive sentiments pertaining to the role of

regulation in banking.

Figure 4.3.1a Perception of Importance of Regulation

46

The second and final question (Q.24, Appendix 1) also deals with regulation in isolation and

provides more interesting findings. Based on content analysis, common banking regulations

were established. The participants were provided a brief explanation of these regulatory

measures and asked to deem them inadequate, adequate, or excessive. Figure 4.3.1b below

reveals that to a large extent the majority of people feel that the regulatory requirements

enforced on banks are adequate. However, there were exceptions to this, namely that many

participants felt 20% mortgage deposits were an excessive measure. All things considered, the

popular consensus appears to be that regulation is neither over burdensome or insufficient.

Figure 4.3.1 b Consumer Perception of Regulatory Measures

4.4.1 The Impact of Regulation on Switching Costs

It seems intuitive that stringent regulatory requirements may disincentivise customers to leave.

To test this notion Question 21 and Question 22 were correlated using Spearman’s rho.

Participants were firstly asked to if they believed it had become more difficult to change banks

in the last 5 years, this measure was then correlated with respondents’ perception of whether

regulation had made it more difficult to change banks. These variables had a Spearman’s rank

correlation coefficient of 0.699, which is considered a strong positive correlation. This finding

was significant at a P value of 0.01. Based on these results it is possible to reject the null

hypothesis (Ho 1) that regulation has no impact on switching costs.

47

Table 4.4.1 Switching Costs and Regulation

Q. 21 In the last five years it has become more difficult to change banks

Measure Spearman's rho Correlation Significance level (One tailed)

N

Q.22 Regulation has made it more difficult to change banks

0.699Strong positive correlation

0.01 195

4.4.2 Impact of Switching Costs on RetentionA vast and growing body of literature examines the role of switching costs or switching

barriers in retaining customers. This study hypothesised that switching costs increase customer

retention. Due to the construction of the questionnaire no meaningful correlation could be

conducted to adequately address this hypothesis that switching costs increase retention.

However, the results of Question 23 illustrated that in general people within the sample feel if

switching costs are increased they will be less inclined to switch banks. A vast majority of

65.6% either agree or strongly agreed with this statement. Of the 195 participants, 21% neither

agree nor disagree, the remaining 13.3% disagree or disagree strongly. Undoubtedly, this

supports the hypothesis that high switching costs increase customer retention. Figure 4.4.2

illustrates this breakdown below.

Figure 4.4.2 Switching Costs

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4.5.1 The Impact of Regulation on Trust

Despite the importance of regulation in the day to day operation of banks, there remains a

paucity of evidence on how regulation impacts trust and more broadly customer retention. An

objective of this study was to investigate this relationship. It was hypothesised that regulation

increases trust. As can be seen from the bar chart (figure 4.5.1) a convincing 65.1% of the

sample report that regulation positively impacts their decision to trust their financial services

provider.

Figure 4.5.1 The impact of Regulation on Trust

Question 13 (Appendix 1) was correlated with the participants evaluation of whether regulation

positively impacted their decision to trust their provider Question 15 (Appendix 1). This test

produced a Spearman’s rank correlation of 0.224, which is considered a weak positive

correlation. In other words, the participants reported level of trust is on average positively

related to their evaluation of the importance of regulation in the context of trust. Similarly,

there was a weak positive correlation between participants who felt trust was essential in

maintaining relationships (Question 14) and those who felt that regulation and oversight

impacted their decision to trust their provider (Question 15). The coefficient of 0.263 was

significant at the P value of 0.01. Taken together, these correlations indicate that the null

hypothesis that regulation has no impact on trust can be rejected.

49

Table 4.5.1 Regulation and Trust

Q.15 Regulation (e.g. central bank oversight) positively impacts my decision to trust my financial services provider

Measure Spearman's rho Correlation Significance level (One tailed)

N

Q.13 I trust my service provider 0.224Weak Positive

0.01 195

Q.14 Trust is essential in maintaining the relationship between you and your primary service provider.

0.263Weak Positive

0.01 195

4.5.2 The Impact of Trust on Customer Retention

The positive link between trust and customer retention is well established in the literature. This

study hypothesised that trust between customer and service provider increases customer

retention. To address this section a combination of simple descriptive statistics and statistical

tests of significance have been employed. The bar chart below (Figure 4.5.2) categorically

corroborates that trust is an important factor in the retention process. According to the bar chart

86.7% of the sample agree or strongly agree that trust is essential in maintaining their

relationships with their primary financial services provider. A meager 2.6% disagree or

strongly disagree and the remaining 10.8% neither agree nor disagree.

Figure 4.5.2 Importance of Trust

50

A further measure was used in order to assess the relationship between trust and retention.

Firstly, participants were asked if they trusted their service provider (Q.13, Appendix 1). This

was then correlated with a measure of propensity to leave (Q.20, Appendix 1). The results of

the correlational analysis indicated a negative moderate correlation of -0.35 at the 0.01

significance level on a one tailed test. In other words, on average the less likely you are to

leave the higher the intrinsic trust you should have. Taken together, these results suggest that

there is a positive association between trust and customer retention. Therefore, these results

suggest that the null hypothesis (Ho X) that trust has no impact on customer retention can be

rejected. The results of the correlational analysis are laid out below in table 4.5.2.

Table 4.5.2 Impact of Trust on customer retention

Q.13 I trust my primary service provider

Measure Spearman's rho Correlation

Significance level (One tailed)

N

Q. 20 How likely are you to change banks? (Propensity to Switch)

-0.35Moderate negative

0.01 195

4.6.1 Satisfaction

This study had a variety of measures related to satisfaction. Some of these measures like the

NES and NPS were employed to directly address the research question. That being said, some

questions were needed to provide a better understanding of the factors which impact

satisfaction in the context of banking. In this regard participants were asked to choose three

from a list of five pre selected factors; cost & fees, branch accessibility, online service

availability, product range, and service quality. Participants could also specify any other

factors.

A vast majority of participants 84.1% stated online service availability was impactful in their

satisfaction with their provider. This is in keeping with section 4.1.8 which identifies online

banking as the most utilised channel. The second most influential factor proportionately was

costs and fees with 63.6% identifying. Surprisingly only 50.3% indicated service quality was

one of the most influential factors. Product range and opening hours ranked last and second last

respectively with 10.7% and 35.9%. No respondents utilized the other/please specify option.

These findings can be found summarised below in table 4.6.1.

51

Table 4.6.1 Factors Influential in Satisfaction

Three most influential factors in customer satisfaction No. Percentage

Online Service Availability 164 84.1%

Cost & Fees 124 63.6%

Service Quality 98 50.1%

Opening Hours 70 35.9%

Product Range 21 10.7%

What is interesting is that regardless of the measure of satisfaction participants of this study on

the whole reported favourable levels of satisfaction. The measure of satisfaction used was

derived from Khan (2012) and related to adherence to expectations. As can be seen from the

graph below and contrary to anecdotal evidence 68.7% of the sample agreed or strongly agreed

that their financial service provider meets their expectations. Conversely, 10.2% disagree or

strongly disagree and the remaining 21% neither agree nor disagree.

Figure 4.6.1 Satisfaction

52

4.6.2 Impact of Regulation on Satisfaction

The main focus of this study is to establish the impact of regulation on customer retention and

its antecedents. In this regard, participants were asked if they felt regulation and oversight

ensured that financial services where of the required standard. The bar chart below (Figure

4.6.2) illustrates that 71.3% of participants agree or strongly disagree. Contrarily, a minority of

4.1% of the participants disagree or strongly disagree. A considerable 24.6% neither agree nor

disagree. All things considered the consensus is predominantly positive.

Figure 4.6.2 Impact of Regulation

Furthermore, a Spearman's rank correlation was carried out between Question 17 and Question

18 (Appendix 1) i.e. participants were asked if they felt regulation and oversight ensured that

financial services where of the required standard. This measure was then correlated with

question eighteen, which asks if it is better if banks are highly regulated. The Spearman's

correlation coefficient was 0.381 that signifies a moderate positive relationship and was

significant at P level of 0.01. This signifies that those who believe it is better for a bank to be

highly regulated generally believe that regulation is important in delivering services to the

required standard. This is not a perfect measure but provides some evidence that the null

hypothesis that regulation doesn’t impact satisfaction can be rejected.

53

As highlighted above participants were asked if they felt regulation and oversight ensured that

financial services where of the required standard. This measure was then correlated with the

propensity of the customers to leave. The coefficient was -0.127 indicating an extremely weak

relationship, this was significant at a significance level of 0.05. This correlation is limited and

does not appear to be the best way to address the hypothesis that regulation positively impacts

satisfaction. What can be inferred is that those who believed regulation had a positive impact in

ensuring the services were of a required standard were less inclined to switch banks. All things

considered it appears regulation has a positive impact on customer satisfaction, but the strength

of this relationship is unknown.

Table 4.6.2 Impact of Regulation on Customer Satisfaction

Q. 17 Regulation and oversight ensures financial services are of the required standard.

Measure Spearman's rho Correlation Significance level (One tailed)

N

Q18. It is better for banks to be highly regulated 0.381Moderate positive

0.01 195

Q.20 How likely are you to change banks? -0.127None/Extremely weak

0.05 195

4.6.3 The impact of Customer Satisfaction on Customer Retention

In the literature, satisfaction has long since been associated with customer retention. This study

adopted multiple measures of satisfaction, as no universally accepted conceptualisation exists.

The first Spearman correlation was based on Reichheld's (2003) NPS (Q.9, Appendix 1)

against a measure of propensity to change banks (Q.20, Appendix 1). The correlation was -.431

indicating a moderate negative correlation. Intuitively, this is logical as the more likely you are

to recommend a bank to a friend or colleague the less inclined you should be to leave the bank.

This correlation is significant at a P value of 0.01. Thus we can reject the null hypothesis that

there is no relationship between satisfaction and retention.

An alternative measure of satisfaction was adopted based on Khan (2012). This measure (Q.11,

Appendix 1) was correlated against the measure of propensity to stay (Q.20, Appendix 1). The

coefficient was -0.486 which is considered a moderate negative correlation. What this result

depicts is that if a customer's expectations are met they should be less inclined to leave. This

54

correlation is also significant at a P value of 0.01. Therefore, this mounts a further case to reject

the null hypothesis that there is no relationship between satisfaction and retention.

According to the HBR article by Dixon, Freeman & Toman (2010) 94% of customers who

experienced low effort indicated they were more satisfied and highlighted their intention to

repurchase from the company. Furthermore, 88% of customers who reported low effort

highlighted that they would be prepared to increase their spending. The last correlation

consisted of the NES against the a measure of propensity to leave. The correlation coefficient

was -0.274 indicating that the easier it is to obtain the financial services customer need the less

inclined they are to leave. This is considered a weak negative correlation and is significant at P

value of 0.01. Thus, we can reject the null hypothesis as this finding provides further

confirmation that satisfaction and customer retention are linked.

Table 4.6.3 Customer Satisfaction and Retention

Q. 20 How likely are you to change banks? (Propensity to Switch)

Measure Spearman's rho Correlation Significance level (One tailed)

N

Q.9 How likely is it that you would recommend this company to a friend? (NPS)

-0.431Moderate negative

0.01 195

Q.10 Overall, how easy is it for you to obtain the financial services you need?

-0.274Weak negative

0.01 195

Q.11 My service provider meets my expectations? -0.486Moderate negative

0.01 195

55

Section Five: Limitations, Further Research & Conclusion

56

5.1 Limitations

Silverman (1993) astutely highlighted that there are no binary right or wrong methodological

approaches. By extension, this truism highlights that every research approach has limitations.

These limitations even exist in an area such as customer retention which has been examined

from economic, behavioural and psychological standpoints and tackled both qualitatively and

quantitatively. This section aims to give a critical appraisal of the strengths and weaknesses of

the paper, such that the fundamental theory can develop iteratively.

The first and most significant issue is that no research has previously addressed the research

question or hypotheses in this paper. Naturally, this limited the opportunity to consult with and

draw from recognised and esteemed literature on the subject area. This subsequently negates

the potential for additional insights that may have resulted in more decisive instrument

development, analysis and interpretation.

In particular aspects of the discussion section namely section 4.4.2 no meaningful correlations

could be conducted. That is not to say that valid measures weren’t utilised, but in some cases it

was not logical to conduct a test of significance on measures which don’t address the

hypothesis. In those cases descriptive statistics were used. Furthermore as with any study which

uses Spearman's Rho, it is important to heed caution to the truism that correlation doesn’t imply

causality (Saunders, Thornhill, & Lewis, 2012).

Thirdly, this paper is subject to rather obvious caveats. Firstly, in the theoretical background

section the definitions of satisfaction, trust, switching costs and even retention are significant

bones of contention. In other words, these terms do not have universally recognized definitions.

Another pertinent limitation is that little is known about whether the participants as customers

are profitable or not. This discernment is illustrated by Buckinx and Van Den Poel (2005) who

highlight that certain customers don’t warrant consideration when managing long term

relations. In other words it is not inconceivable that regulation may impact profitable and

unprofitable customers differently. It is reasonable to suggest that retail customers represent the

lowest margins across financial products and therefore typically customer retention strategies

would be limited at the individual customer level.

Whilst Cavana et al. (2001) argue that no sampling method is truly random undoubtedly one of

the most pertinent limitations of this study emanates from the use of a convenience sampling

strategy. Convenience sampling is a non-probability sampling method. In this approach

57

participants are chosen merely because the are available and hence it is prone to bias

(Denscombe, 2007). This approach however is the least time consuming and most economical

form of sampling (Blumberg et al, 2008). It was highly favourable to the researcher to adopt

this approach given the time bound nature of the undertaking. In order to discern the

representativeness of the sample, the sample mean, standard deviation, skewness, and kurtosis

was used (found in Appendix 3).

This study collected 205 responses in total which represented 195 valid responses, it is thought

that this sample size is adequate for statistical analysis. However, it goes without saying that a

larger sample would improve the accuracy of the findings. Two features of the sample drew

attention; firstly the average age was quite young, secondly the educational attainment of the

sample was generally higher than expected. This may be indicative of the sampling error of

overcoverage. Furthermore, all surveys were conducted online, this is therefore indicative that

it was a computer literate or technology savvy sample. This could be viewed as the sampling

error of undercoverage.

On the whole, the sample exhibited low branch usage and tended to favour online mechanisms.

Whilst this study is not longitudinal in nature, it does appear that the banking sector is in the

midst of a paradigm shift away from conventional methods (ATM and Branch usage) towards

online methods. The sample had only a small number of respondents who availed of mortgage

services from their primary service provider. Given the complex nature of mortgages it is

conceivable that mortgages users may differ in perspective than typical participants, especially

given the recent difficulties in the mortgage market i.e. high numbers of arrears cases and

repossessions (Goggin, 2013). To conclude, the sample characteristics coupled with the fact the

that this study focuses solely on Ireland, limits the generalizability of the results.

58

5.2 Further Research

This research has added an additional dimension to the area of customer retention, that of

regulation. The illumination of the impacts of regulation was the most significant contribution

of this paper. However, the prospects for future research are vast. As we have established

retention is an ongoing process between both customers and suppliers. The first area of further

research is an extension of this insight. Hougaard and Bjerre (2003) highlight that because both

parties are heavily involved in the exchange process, that it is essential to develop a greater

understanding of the dynamic from both customer and supplier sides. This study focused on

individual customers in isolation. Thus, it would be beneficial for research to be conducted

examining the context of the supplier. This could be carried out by conducting interviews with

marketing practitioners in the banking sector, to establish their opinion of the impact of

regulation.

Based on the feedback from the pilot study participants identified that they weren’t overly

cognizant of the prevailing regulatory requirements. The survey research strategy has

limitations, in the case of this study it only obtains a predefined or specified answer.

Consequently, focus groups may also be viable as a means of delving deeper and establishing

the opinions of the public. It may be beneficial to conduct a longitudinal study, and establish

how opinions change over time. Again, it is conceivable that the opinion of regulation and

oversight now differs fundamentally from those held during the Celtic Tiger.

Furthermore, it would be interesting to study the impact of regulation at different stages of the

product lifecycle, for example many regulatory requirements are imposed when setting up a

bank account, a customer in the later stages of the lifecycle may be less affected. Secondly, the

geographical scope of the study could be expanded to a cross national study. Lastly, it may also

be beneficial to asses the impact of regulation on customer retention in other highly regulated

industries for example the insurance industry.

59

5.3 Conclusion

Customer retention is one of the core tenets of the field of marketing and is one of the cardinal

aims of relationship marketing. The importance of retention is irrefutable. Dawkins and

Reichheld (1990) highlight how a 5% increase in retention can lead to an 85% increase in

profits at branch level in the banking sector. Furthermore, Gupta et al. (2004) found that a 1%

increase in retention is equivalent to a 5% decrease in a firm’s cost of capital. This study

provided a comprehensive review of the literature relating to regulation, retention and the

pertinent antecedents of retention.

Banking is undoubtedly a highly regulated industry. The regulation and oversight in the

industry impact the day to day operation of the bank. However, according to the findings

regulation is perceived in a predominantly positive light by the consumer. A staggering 84.6%

of the sample indicated that they believe it is better for a bank to be highly regulated.

Furthermore, eight of the nine regulatory requirements found from the content analysis were

believed to be adequate as opposed to inadequate or excessive. Taken together these findings

indicate that on the whole the sample attest to the need for regulation.

In relation to switching costs 65.6% of the sample indicated that if the obstacles associated

with switching were increased that they would be less inclined to switch. Secondly, a strong

positive Spearman correlation of 0.699 was found between Q.21 and Q.22. What could be

discerned from this is that those who believe it has become more difficult to change banks on

the whole agree that regulation has made it more difficult to do so. This section provided

evidence that regulation increases switching costs and further that switching costs increase

retention.

In relation to trust 65.1% highlighted that regulation positively impacts their decision to trust

their service provider. Furthermore, there was a weak positive correlation between those who

trusted their service provider and those who believed trust is essential in maintaining their

relationship between their service provider. Thus, it was possible to reject Ho 3, as the evidence

indicated that regulation has a positive role to play in trust. Furthermore, it was identified that

86.7% of the participants believed trust was essential in maintaining their relationships with the

primary financial services provider. In addition a moderate negative correlation was found

between participants propensity to leave and their levels of trust. In other words the higher the

60

value of trust the less likely people intended to change provider, thus there was sufficient

evidence to reject Ho 4.

The most pertinent factors identified in relation to satisfaction where online service availability

and cost/fees with 84.1% and 63.5%. Some what surprisingly 68.7% of the sample indicated

that their primary service provider met their expectations. The vast majority of the sample

(71.3%) indicated that regulation ensured financial services were of the required standard. This

highlights that participants believe regulation plays a part in satisfaction. Furthermore, those

who indicated that it is better for a bank to be highly regulated in general believed that

regulation ensures services are of the required standard with a moderate positive Spearman

correlation of 0.381. Taken together, the results indicate that regulation may have a causal role

in satisfaction in the banking sector. Thus, the evidence suggests that Ho 5 (Regulation has no

impact on satisfaction) can be rejected.

The link between customer retention and satisfaction is well established and the measures used

in this study were indicative. A moderate negative Spearman correlation of -0.431 was found

between the Net Promoter Score and the likelihood to leave. Additionally, a moderate negative

Spearman correlation of -0.486 was found between the measure of satisfaction extracted from

Khan (2012) found in question 11. Both correlations signify that as satisfaction increases then

so too does the propensity to stay. Taken together, these findings suggest that null hypothesis

(Ho 6) that customer satisfaction has no impact on customer retention can be rejected.

In summation, the findings indicate that generally regulation is perceived positively by

customers. Many of the participants indicated that it is better for banks to be highly regulated

and that many of the regulatory requirements were adequate as opposed to inadequate or

excessive. Regulation was found to be related to pertinent antecedents of customer retention

such as trust, satisfaction and switching costs. Whilst this paper delved into unchartered

territory the findings on the whole were indicative that regulation appears to have a non

negligible impact or appears to facilitate customer retention.

61

Section Six: Appendix

62

6.1 Appendix 1 - Survey Instrument

63

64

65

66

67

68

6.2 Appendix 2 - Bar Charts of Survey Results

69

70

71

72

73

74

75

6.3 Appendix 3 - Statistics Regarding Bar Charts

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6.4 Appendix 4 - Correlation Output

77

78

79

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