The Impact of Regulation on Customer Retention within the Irish Banking Sector - Chris Neville

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

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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.

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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

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Acknowledgements
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

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Table of Contents
Page no.
Abstract………………………………….………………………………………………………...…...…1
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

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4.1 Introduction………………………………………………………………………………………….40
4.2 Sample Description…………………………………………………………………….…………....40
4.2.1 Gender Distribution…………………………………………………………..…………..40
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

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List of figures
Page no.
Figure 1.2 Payne & Frow 2 Relationship Marketing…………………………………………..11
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

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List of Tables
Page no.
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

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Section One: Customer Retention & The Research Gap

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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.

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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.

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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.

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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 (Järvinen, 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

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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.

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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.

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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).

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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

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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).

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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).

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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

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Section Two: Theoretical Background

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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,

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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

23
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

24
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.

25
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.

26
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

27
Section Three: Research Methodology & Design

28
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).

29
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).

30
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.

31
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

32
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

33
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.

34
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.

35
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

36
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).

37
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).

38
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)

39
Section Four: Data Analysis & Findings

40
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.

41
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

42
4.2.3 Educational Attainment
Analysis 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

43
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.

44
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%

45
4.2.7 The Frequency of Banking Channels utilised
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.

46
Table 4.2.8 Frequency of banking products with primary service provider
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

47
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.

48
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
0.699
Strong positive correlation
0.01 195
4.4.2 Impact of Switching Costs on Retention
A 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

49
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.

50
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
(One tailed)
N
Q.13 I trust my service provider 0.224
Weak Positive
0.01 195
Q.14 Trust is essential in maintaining the
relationship between you and your primary service
provider.
0.263
Weak 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

51
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)
-0.35
Moderate 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.

52
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

53
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.

54
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.
(One tailed)
N
Q18. It is better for banks to be highly regulated 0.381
Moderate positive
0.01 195
Q.20 How likely are you to change banks? -0.127
None/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

55
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)
(One tailed)
N
Q.9 How likely is it that you would recommend
this company to a friend? (NPS)
-0.431
Moderate negative
0.01 195
Q.10 Overall, how easy is it for you to obtain the
financial services you need?
-0.274
Weak negative
0.01 195
Q.11 My service provider meets my expectations? -0.486
Moderate negative
0.01 195

56
Section Five: Limitations, Further Research & Conclusion

57
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

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