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UNIVERSITY OF GHANA 
 
 
 
SWITCHING BEHAVIOUR AMONG BANK CUSTOMERS IN GHANA 
 
 
 
 
 
BY 
REXFORD OWUSU OKYIREH 
(10507664) 
 
 
 
 
 
THIS THESIS IS SUBMITTED TO THE DEPARTMENT OF MARKETING AND 
ENTREPRENEURSHIP, UNIVERSITY OF GHANA BUSINESS SCHOOL, 
LEGON IN PARTIAL FULFILMENT OF THE REQUIREMENT 
FOR THE AWARD OF MASTER OF PHILOSOPHY IN MARKETING 
 
JULY, 2016
 
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DECLARATION 
 
I do hereby declare that this thesis is my own original work and has not been submitted either 
in whole or in part to any institution for any degree. All references used in the work have 
been fully acknowledged. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
……………………………………………..    ……………………….. 
      REXFORD OWUSU OKYIREH     DATE 
(ID:10507664) 
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CERTIFICATION 
 
I hereby certify that this thesis was supervised in accordance with procedures laid down by 
University of Ghana.    
 
 
 
 
 
 
 
……………………………………………..    ……………………….. 
      DR PRINCE KODUA      DATE 
(SUPERVISOR) 
 
 
 
 
……………………………………………..    ……………………….. 
      PROF. BEDMAN NARTEH     DATE 
(CO-SUPERVISOR) 
 
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DEDICATION 
 
I dedicate this work to my wife Mrs. Marijke Okyireh for her financial support and 
encouragement during the course of study at the graduate school. This work is also dedicated 
to my lovely children Elsie and Elaina Owusu Okyireh, for their support in my studies. 
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ACKNOWLEDGEMENT 
 
I wish to acknowledge the contribution of my supervisor, Dr Prince Kodua for his tireless 
dedication, contribution and constructive criticisms towards the completion of this thesis. I 
could not have come this far without him. I also want to acknowledge the support of my co-
supervisor Professor Bedman Narteh for his insightful comments towards the completion of 
this thesis. Above all I am grateful to God for giving me life and strength throughout the 
entire programme. 
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TABLE OF CONTENTS 
DECLARATION.................................................................................................................................... i 
CERTIFICATION ................................................................................................................................ ii 
DEDICATION...................................................................................................................................... iii 
ACKNOWLEDGEMENT ................................................................................................................... iv 
TABLE OF CONTENTS ..................................................................................................................... v 
LIST OF TABLES ............................................................................................................................... ix 
TABLE OF FIGURES .......................................................................................................................... x 
ABSTRACT .......................................................................................................................................... xi 
CHAPTER ONE ................................................................................................................................... 1 
INTRODUCTION ................................................................................................................................. 1 
1.0 BACKGROUND OF THE STUDY ............................................................................................. 1 
1.1 PROBLEM STATEMENT AND RESEARCH GAPS ................................................................ 3 
1.2 OBJECTIVES OF STUDY ........................................................................................................... 4 
1.3 RESEARCH QUESTIONS........................................................................................................... 4 
1.5 SIGNIFICANCE OF STUDY ...................................................................................................... 5 
1.6 SCOPE AND LIMITATION ........................................................................................................ 5 
1.8 CHAPTER DISPOSITION ........................................................................................................... 6 
CHAPTER TWO .................................................................................................................................. 7 
LITERATURE REVIEW .................................................................................................................... 7 
2.0 INTRODUCTION ........................................................................................................................ 7 
2.1 SOCIAL EXCHANGE THEORY ................................................................................................ 7 
2.2 DEMOGRAPHIC TRANSITION THEORY ............................................................................... 8 
2.3 SWITCHING BEHAVIOUR ........................................................................................................ 8 
2.4 DRIVERS OF SWITCHING BEHAVIOUR................................................................................ 9 
2.4.1 Price ....................................................................................................................................... 9 
2.4.2 Technology .......................................................................................................................... 10 
2.4.3 Customer Satisfaction .......................................................................................................... 11 
2.4.4 Effective Advertising Competition ...................................................................................... 11 
2.4.5 Involuntary Switching .......................................................................................................... 12 
2.5 SERVICE ISSUES ...................................................................................................................... 12 
2.6 OTHER DRIVERS OF SWITCHING BEHAVIOUR ............................................................... 13 
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2.6.1 Service Quality ..................................................................................................................... 13 
2.6.2 Reputation ............................................................................................................................ 14 
2.6.3 Customer Commitment ........................................................................................................ 15 
2.6.4 Switching Cost ..................................................................................................................... 15 
2.7 SOCIO-ECONOMIC STATUS (SES) AND CONSUMER SWITCHING BEHAVIOUR ....... 15 
2.7.1 Age and Switching Behaviour ............................................................................................. 16 
2.7.2 Income and Switching Behaviour ........................................................................................ 17 
2.7.3 Education and Switching Behaviour .................................................................................... 17 
2.8 SWITCHING BEHAVIOUR IN THE SERVICES SECTOR .................................................... 17 
2.8.1 Insurance Industry ................................................................................................................ 17 
2.8.2 Healthcare Industry .............................................................................................................. 19 
2.8.3 Telecommunication Industry ............................................................................................... 20 
2.8.4 Hospitality Industry ............................................................................................................. 24 
2.8.5 Real Estate Industry ............................................................................................................. 25 
2.9 SWITCHING BEHAVIOUR IN THE BANKING SECTOR .................................................... 26 
2.10 CRITIQUE OF STUDIES ON CUSTOMER SWITCHING BEHAVIOR .............................. 34 
2.11 CONCEPTUAL FRAMEWORK ............................................................................................. 37 
2.11.1 Price and Switching Behaviour .......................................................................................... 37 
2.11.2 Technology and Switching Behaviour ............................................................................... 38 
2.11.3 Service Quality and Switching Behaviour ......................................................................... 38 
2.11.4 Advertisement and Switching Behaviour........................................................................... 39 
2.11.5 Involuntary Factors and Switching Behaviour ................................................................... 39 
2.11.6 Customer Satisfaction ........................................................................................................ 40 
2.11.7 Responses to Service Failure ............................................................................................. 40 
2.11.8 Service Products ................................................................................................................. 40 
2.12 DEMOGRAPHIC VARIABLES .............................................................................................. 41 
2.12.1 Socio-Economic Status (SES) and Switching Behaviour .................................................. 41 
CHAPTER THREE ............................................................................................................................ 43 
CONTEXT OF THE STUDY ............................................................................................................ 43 
3.0 INTRODUCTION ...................................................................................................................... 43 
3.1 HISTORY OF BANKING IN GHANA ..................................................................................... 43 
3.2 GHANA (PHYSICAL SETTING) ............................................................................................. 44 
3.3 BRIEF HISTORY OF THE GHANA CURRENCY .................................................................. 44 
3.3.1 The Birth of the Cedi ........................................................................................................... 45 
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3.4 OUTLINE OF PAYMENT SYSTEMS IN GHANA ................................................................. 45 
3.5 RULES GOVERNING AUTOMATIC TELLER MACHINE (ATM) AND POINT OF SALE 
SYSTEMS IN GHANA .................................................................................................................... 47 
3.6 THE GHANAIAN BANKING INDUSTRY .............................................................................. 48 
3.7 DEVELOPMENTS IN BANKS AND NON-BANK FINANCIAL INSTITUTIONS ............... 49 
3.7.1 Overview .............................................................................................................................. 49 
3.7.2 Assets and Liabilities ........................................................................................................... 49 
3.8 STABILITY OF THE FINANCIAL SYSTEM .......................................................................... 50 
3.8.1 Macro-Financial Stress Tests ............................................................................................... 50 
CHAPTER FOUR ............................................................................................................................... 51 
METHODOLOGY ............................................................................................................................. 51 
4.0 INTRODUCTION ...................................................................................................................... 51 
4.1 PHILOSOPHICAL PERSPECTIVES AND PARADIGMS ...................................................... 51 
4.2 RESEARCH PURPOSE ............................................................................................................. 52 
4.3 RESEARCH APPROACH ......................................................................................................... 53 
4.4 RESEARCH DESIGN ................................................................................................................ 54 
4.5 SOURCES OF DATA AND DATA COLLECTION METHODS ............................................ 55 
4.5.1 Questionnaire Design and Administration ........................................................................... 56 
4.6 POPULATION, SAMPLE AND SAMPLING TECHNIQUE ................................................... 58 
4.7 ETHICAL CONSIDERATION .................................................................................................. 59 
4.8 CHAPTER SUMMARY ............................................................................................................. 59 
CHAPTER FIVE ................................................................................................................................ 60 
DATA ANALYSIS AND DISCUSSION OF FINDINGS ............................................................... 60 
5.1 PROFILE OF THE RESPONDENTS ........................................................................................ 60 
5.2 DESCRIPTIVE STATISTICS .................................................................................................... 61 
5.3 CONFIRMATORY FACTOR ANALYSIS ............................................................................... 63 
5.4 DISCRIMINANT VALIDITY ................................................................................................... 65 
5.5 ANOVA ...................................................................................................................................... 66 
5.6 HYPOTHESES TESTING USING LOGISTIC REGRESSION................................................ 66 
5.7 MODERATING EFFECT OF CUSTOMER AGE .................................................................... 68 
5.8 DISCUSSION OF FINDINGS ................................................................................................... 70 
5.9 RELATIONSHIP BETWEEN DRIVERS OF SWITCHING BEHAVIOR, DEMOGRAPHIC 
VARIABLES AND DIMENSIONS OF SWITCHING BEHAVIOR .............................................. 72 
CHAPTER SIX ................................................................................................................................... 76 
SUMMARY, CONCLUSION AND RECOMMENDATION ......................................................... 76 
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6.0 INTRODUCTION ...................................................................................................................... 76 
6.1 SUMMARY OF STUDY ........................................................................................................... 76 
6.2 REVISED CONCEPTUAL FRAMEWORK ............................................................................. 78 
S6.3 CONCLUSION ......................................................................................................................... 79 
6.4 RECOMMENDATIONS ............................................................................................................ 81 
6.4.1 Practice ................................................................................................................................. 81 
6.4.2 Theory and Future Research ................................................................................................ 82 
BIBLIOGRAPHY ............................................................................................................................... 84 
APPENDIX .......................................................................................................................................... 98 
 
 
 
 
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LIST OF TABLES 
 
 
Table 5. 1 Profile of respondents ............................................................................................ 61 
Table 5. 2 t test (descriptive statistics) .................................................................................... 62 
Table 5. 3 Confirmatory factor analysis ................................................................................. 64 
Table 5. 4 Descriptive statistics and correlations ................................................................... 65 
Table 5. 5 ANOVA results ..................................................................................................... 66 
Table 5. 6 Logistic regression on bank service switching ...................................................... 68 
Table 5. 7 Logistic regression on bank service switching ...................................................... 69 
 
 
 
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TABLE OF FIGURES 
 
Figure. 1 Proposed Conceptual Framework……………………………………………51 
Figure. 2  The Payment System…………………………………………………………55 
Figure. 3  Revised Conceptual Framework……………………………………………..86   
 
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ABSTRACT 
The banking industry in Ghana over the years has experienced significant growth owing to 
reforms and deregulation that characterised the sector. This however has changed and the 
sector is beset with slow growth as a result of fierce competition of keeping existing 
customers and attracting new ones and this has shifted the focus of marketing into a 
relationship paradigm. Despite the challenges in the banking sector, customers continue to 
seek value and this however, makes it important to know why switching occur. The factors 
that makes customers move from one bank to another is based on demographic factors such 
as age, gender, education and income. The study used a sample size of 329 and a convenience 
sampling method was employed in the research. Logistic regression was used for the 
analysis.  The findings revealed that, a significant increase in dissatisfaction of bank services 
will result in about three times likelihood to switch. Again, age was found to be potential 
moderator of the relationship between the independent variables and the dependent variable. 
The study recommends that banks must segment markets well in order to tailor products to 
them as it ensures the needs of different segments being met. Moreover, the design of service 
products must include technology and price in order to retain customers.  
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CHAPTER ONE 
INTRODUCTION 
 
1.0 BACKGROUND OF THE STUDY 
Ghana’s economy witnessed a decline in the late 1970s and the early part of 1980s. The poor 
economic performance affected the banking industry immensely and subsequently became less 
competitive. In view of this slow growth, the Ghanaian banking industry experienced reforms 
through International Monetary Fund (IMF) and World Bank structural programme (Owusu-
Frimpong, 2008). This later pushed for further reforms in 2006 where Bank of Ghana (BoG) 
deregularised the banking system. Owing to the deregulation, rivalry in the sector has intensified 
enormously according to many scholars (Anabila & Awunyo-Vitor, 2013; Sureshchander et al., 
2003. This has made the focus of marketing shift to relationship with customers.   
 
Presently, the IMF in the April 2015 World Economic Outlook reports that, global growth in the 
banking sector has halted at 3.4percent in 2014 as compared to 2013. This is not different from 
emerging markets which has also suffered in its growth to 4.6percent in 2014 from 5.0percent in 
2013. This according to the BOG (2014) report is as a result of slowdown in economies such as 
China and Russia through cyclical factors, domestic policy tightening and political tensions. 
 
In West Africa specifically Ghana, the banking industry has seen dramatic changes over the years 
and continues to improve with regulations and guidelines guiding its operations. Currently there 
are 28 licensed banks with 967 bank branches (BoG Annual Report, 2014). This shows 
significant increase of 311 in the last 4 years when it was 656. In view of these significant 
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changes, there are enormous pressures on banks to deliver superior value to customers to continue 
to be profitable. 
 
The quest by Ghanaian banks to deliver superior value has led to an increasing adoption of 
relationship banking with customer as the focal point in business survival. As a result of this 
phenomenon, banks are looking for new ways of achieving loyalty despite some challenges such 
as legislation, technology and globalisation (Blankson et al., 2009; Narteh, 2013; Owusu-
Frimpong, 2008). Additionally, the characteristics of the population has indicated an upsurge in 
homes, which is change in gender roles, improved training and advancement in technology 
development, consumers have become more conversant in choice of products and services on 
offer. These characteristics according to Nimako and Nyame (2015) play a key role in influencing 
decisions of customers due to the uniqueness of behaviour that is often exhibited. The 
characteristics include age, gender, income and education have it been under scrutiny by some 
researchers (Narteh & Owusu-Frimpong, 2011, Nartey 2013, Mburu & Selapisa, 2012) due to the 
changes in behaviour pattern in geographical settings. 
 
These developments have increased significantly and service providers have consistently over the 
period struggled with  perceived poor quality service and this has a negatively reflected on profit 
(Reichheld and Sasser, 1990), initial investment costs (Andaleeb, Rashid & Rahman, 2016), and 
the acquisition of new customers (Walsh, Albrecht, Kunz & Hofacker, 2016). To buttress this 
point, the cost of retaining existing customers is comparatively cheaper than acquiring new ones 
(Kandampully, Zhang & Bilgihan, 2015) and that the loss of customers to other service providers 
makes it worrying for service firms.  
 
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Mahmoud, Tweneboah-Koduah and Danku (2011), claim that despite the challenges in the 
banking sector, it is undebatable that the banking sector has been the leader for creativity, 
innovation, competitiveness and sophistication of IT services in the country. In this regard the 
banking industry in Ghana with its numerous issues has become very competitive and rigorous 
and requires personalized and differentiated services, focused on the promotion of loyalty and 
satisfaction of customers in order to be successful (Khaled & Rasoul, 2008). In expanding the 
discursion, Afsar et al. (2010) posits that the onus is on banks to maintain existing customers and 
tries to attract new ones through customer satisfaction to secure long term profitability. 
 
1.1 PROBLEM STATEMENT AND RESEARCH GAPS 
Switching behaviour in other service industries have been of great concern to researchers over the 
years. While Ofori-Okyere and Kumadey (2015) explored switching in the healthcare industry, 
Wen-Bao (2010) examined switching in the insurance industry. Other industries considered over 
the period include telecommunication industry (Arthur et al., 2012; Effah-Bediako et al., 2013; 
Chadha & Bhandari, 2014; Nimako & Nyame, 2015) and banking industry (Abawiera, Dwomoh, 
Owusu, Pinkrah, & Antwi, 2014; Asab, Pirzada, Nawaz & Javed, 2014; Boohene, Agyapong & 
Gonu, 2013; Clemes, Gan, & Zhang, 2010). 
 
The Bank of Ghana (2014), reports that growth in the banking sector has halted at 3.4percent in 
2014 as compared to 2013. This isn’t different from emerging markets and developing economies 
such as Ghana which has also suffered in its growth to 4.6percent in 2014 (BoG 2014). Despite 
the downward trend in the banking sector, there exists fierce competition to win customers hence 
the need to offer personalised and differentiated services to customers (Khaled & Rasoul, 2008). 
To achieve loyalty and satisfaction, it is important to know the reasons why switching occur and 
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sufficient literature has established that (Boohene et al., 2013; Clemes et al., 2010; Narteh, 2013; 
Narteh & Owusu-Frimpong, 2011; Nimako & Nyame, 2015; Nimako & Mensah, 2014). 
 
Regardless of the in-depth knowledge in switching behaviour, the effect of demographic variable 
on switching behaviour has not been given adequate attention in extant literature. Nartey (2013) 
also allude to the fact that research on switching behaviour has been scanty especially in 
developing countries like Ghana. Additionally, Clemes et al. (2010) also recommend that 
different geographical areas should be considered to ascertain the factors in developing countries. 
Moreover, Nartey (2013) identified service encounter failures as the most important factor in 
switching decisions on customers but none of the studies have sought to moderate the 
demographic variables and how it impact on the switching behaviour of customers. Previous 
studies such as Morgan (2012), Nimako and Nyame (2015), for instance reports that age and 
income have a positive relationship on switching behaviour. On the other hand, Effah-Bediako et 
al., (2013) argues that age and gender do not influence switching behavior and these 
inconsistencies has given impetus for this current study which are guided by the objectives below. 
 
1.2 OBJECTIVES OF STUDY 
1. To assess the antecedents of switching behaviour among bank customers in Ghana.  
2. To assess the impact of demographic variables on customer switching behaviour. 
1.3 RESEARCH QUESTIONS 
1. What factors accounts for customer switching behaviour? 
2. What are the demographic variables that influence switching behaviour in the Ghanaian 
banking sector? 
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1.5 SIGNIFICANCE OF STUDY 
The study will make theoretical and practical contribution to the marketing literature hence 
providing policymakers, consultants and academicians with a framework for understanding 
switching behaviour amongst customers in the banking sector. Practically, the study seeks to 
inform and educate professionals on the need to effectively segment consumer markets in order to 
tailor products to them. Additionally, the study further advance that the age differences of 
consumers clearly shows the service products that are likely to be used. This makes it important 
to know the type of products to be designed in order to satisfy the different age segments. Again, 
the study can guide policy makers on the need to institutionalize reforms to be able to increase 
switching cost.  
Theoretically, the research advances the discussion on demographic variables and its implication 
on how important it is in marketing literature. Additionally, it is evident that the factors that 
makes customers switch from one service provider to another cannot be generalized as different 
segments of customers are affected by different factors. It will enhance the scholarly field thereby 
setting the tone for further research on the Ghanaian banking industry. 
 
1.6 SCOPE AND LIMITATION 
 
Limitation, according to Creswell (2005) is “potential weaknesses or problems with the study 
identified by the researcher”. In line with this view, the limitations often relate to methodology. 
The limitation in the current study is as a result of some respondents not returning questionnaires 
and others showing no interest in the study. This was mitigated by having a lot of participants to 
choose from in order to have the required sample size. The research is focused on the banking 
industry in Ghana and by this; customers with bank accounts are of interest to the researcher. The 
study focuses on customers of Ga East Municipal Assembly only and this is because of the 
proliferation of banks in the municipality. In view of this, the researcher is interested in 
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experiences with banks which can influence a customer’s intention to either switch or stay with 
the bank. 
 
1.8 CHAPTER DISPOSITION 
The study is organized into six chapters; Chapter one describes the background to the study by 
bringing out the research problem, the research objectives and the research questions. Again, the 
chapter also outlines the issues of concern to the researcher. Chapter two also discusses the 
literature review and the various theoretical approaches, the definition of switching behaviour, the 
drivers of switching behaviour, socio-economic status of consumers, followed by review of 
related studies in the banking industry in Ghana. This section concludes with the conceptual 
framework forming the basis of the study.  Chapter three details the context of the study that 
highlights Ghana as an emerging market and also gives a background of the banking industry in 
Ghana. Chapter four provides detailed description of the methodology used in the study. It also 
states the profile of respondents, the choice of methodology used. Chapter five focuses on the 
analyses and discussion of the empirical results. It also presents the findings of the study 
comparable to the literature. Chapter six summaries the findings of the study and the theoretical 
contributions to academic knowledge as well, providing a number of managerial implications, 
and conclusions.  
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CHAPTER TWO 
LITERATURE REVIEW 
 
2.0 INTRODUCTION 
The section presents an outline of switching behaviour and how customer’s activities affect this 
phenomenon in the banking industry in Ghana. The literature review focuses on the theoretical 
framework that underpins the study and the major factors that affect the way customers switch 
from one service provider to the other. The factors under consideration include price, service 
quality, effective advertising competition, involuntary switching, technology, customer 
satisfaction and service products. 
 
2.1 SOCIAL EXCHANGE THEORY 
Homans (1958) postulated the social exchange theory which says that, individuals have the 
freedom to make decisions by analyzing the costs and benefits attached to choices. The theory 
further states that people are hedonistic and try to maximize rewards whilst minimizing costs. 
Thus it is expected that customers make decisions concerning banking services on the bases of 
choosing a service that offer superior value. Again, service firms like banks that do not improve 
and innovate on products are likely to lose customers because the customer has an insatiable 
quest to look for better and improved service delivery. 
 
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2.2 DEMOGRAPHIC TRANSITION THEORY 
The demographic transition theory was developed by Thompson (1929) and states that as people 
progress from one developmental stage to another their preferences, expectations and interests 
change with time. In view of this, the theory is the most suitable for understanding how people 
with demographic characteristics such age, education and income can display a switching attitude 
from one service to other when their preferences and expectations change over time. 
 
2.3 SWITCHING BEHAVIOUR 
Switching behaviour is the reflection of customers deciding to stop purchase of a service from a 
firm permanently and this assertion is shared by Boltaon and Bronkhurst (1995) and Boote 
(1998). Perner (2006) assert that switching behaviour is a multifaceted study of factors, which 
stimulate the behaviour of consumers towards switching their purchase between brands. 
 
Keaveny and Parthasarathy (2001) and Sathish, Kumar, Naveen and Jeevanantham (2011) also 
define switching behaviour is an act of switching from one service provider to another and this as 
a result of not being satisfied with the service. Other studies (Akwensivie, 2014; Bansal & Taylor, 
1999; Garland, 2002; Narteh & Owusu-Frimpong, 2011; Nimako 2012; Tahtinen & Halinen, 
2002) also agree that switching behaviour is the act of customers abandoning one service provider 
for another. The forms of switching can either be total or partial (Colgate & Hedge, 2001; 
Stewart, 1998). Total switching is easier to identify as customers who engage in total switching 
because they close accounts and move to another (Bolton & Bronkhorst, 1995; Boote, 1998). On 
the other hand, partial switching is the loss of customers’ engagement with the service provider 
and this is difficult to detect than the total switching (Siddiqui, 2011). 
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From the above definition, it is clear that switching occurs as a result of dissatisfaction and that 
the reasons underlying customers propensity to switch is enormous. Gerrard and Cunningham 
(2004) assert that the ability of a customer to change a service provider is as a result of multiple 
factors.  
 
2.4 DRIVERS OF SWITCHING BEHAVIOUR 
Switching is the result of multiple factors and these may work in isolation or not (Gerrard & 
Cunningham, 2004). Keaveney (1995) proposed the first model in switching behaviour in service 
industry which is based on critical factors that affects how customers switch. In addition Vishal 
(2014) have also proposed advertisement, switching cost as determinants of switching behaviour. 
However, researchers (Mittal & Lassar, 1998; Vishal, 2014) have proposed that Keaveney scale 
needs further testing in specific service industries. The following factors have been identified as 
the major factors proposed to impact on switching behaviour. 
 
2.4.1 Price 
Zeithaml (1988) defines price as “what is given up or sacrificed to have a product or a service” 
and “a perception of unfavourable prices of services can make customers switch regardless of 
being satisfied or not” (Clemes et. al. 2010; Campbell, 1999). Colgate and Hedge (2001) claims 
that price is the most important factor in switching decisions and that customers consider the 
charges of the bank before patronising the service.  
 
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In the banking context, price has wider connotations such as interest rates, bank charges, fees, 
surcharges, penalties, price deals, coupons, and/or price promotions and special charges on 
products (Gerrard and Cunningham, 2004). According to Keaveney (1995), customers switch 
services due to poor pricing perceptions and thus unfavourable pricing may have a direct impact 
on customer’s intention to switch. This view is also in support of the research by Nyarko (2015) 
that concluded that, bank charges is very crucial in determining the switching patterns of 
customers.  
 
A study conducted by Nartey and Owusu-Frimpong (2011) report that price has a weak 
relationship with switching behaviour. This claim is also shared by some researchers such as 
(Antwi-Boateng, Owusu-Prempeh & Asuamah, 2013; Chigamba & Fatoki, 2011). The ability of 
profit to fall is as a result of high switching rate which affects firms’ profit (Mburum & Selapisa, 
2012; Aydin & Özer, 2005) in the long term. This however connotes that the customers who are 
price sensitive have the tendency to switch from one service provider to another which ample 
literature supports this claim. 
 
2.4.2 Technology 
Technology in the banking sector has been on an upsurge owing to the competitive nature and 
service firms have seen the attractiveness in employing technology in its operations in the quest 
to gain advantage (Zhang and Prybutok, 2005; Bauer et. al., 2005). The introduction of 
technology in the banking sector has given rise to electronic ways of transacting business using 
platforms such as automatic teller machine (ATM), telephone and internet (Ibrahim et al., 2006; 
Daniel 1999). Nartey and Owusu-Frimpong (2011) in their study found that, technology related 
issues were very critical in the selection of banks by customers. This implies that, customers of 
banks consider technology related issues like internet banking and ATM services before they sign 
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on to the bank. Some researchers (Parasuraman et. al., 2005; Rayport and Sviokla, 1995) have 
outlined the merits of technology in the banking sector which includes better convenience, lesser 
fee and delighted customers. These technological advancement in the banking sector ultimately 
results to customer satisfaction. 
 
2.4.3 Customer Satisfaction 
Customer satisfaction is a term that measures how products and services supplied by a company 
meet or exceed customer expectation. “Customer satisfaction is defined as the post purchase 
evaluation of a product or service taking into consideration the expectations” (Kotler & 
Armstrong, 2012).  Pairot (2008) posits that, the ability of a firm to meet the needs of customers 
will make them satisfied. Wirtz (2003) in his study proposed the results of customer satisfaction 
and argued that repeat purchase and loyalty is how firms can measure profitability. 
  
It is evidential that the ethos that makes customer satisfaction worthy of attention is the long term 
benefits the firm gains as a result of having superior products tailored to consumers (Kristensen, 
Dahlgaard, & Kanji, 1992; Zeithaml et al., 2006; McColl-Kennedy & Schneider, 2000). Aaker 
and Jacobson (1994) argue that a company with satisfied customer base is significant to economic 
returns. Cudjoe, Anim and Nyanofio (2015) in a related study conclude that customer’s 
satisfaction is to a larger extent influenced by the level of total service quality.  
 
2.4.4 Effective Advertising Competition 
Advertising is how products and services get promoted for customers to know about it (Nawaz, 
Javed & Asab, 2014). The importance of advertising is of great concern to service providers 
especially banks in the highly competitive market. The power to attract customers to the bank is 
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as a result of careful planning of advertising materials to make this happen (Cengiz et. al., 2007; 
Clemes et. al., 2007). Despite the little research (Zhang, 2009) on the relationship between 
advertising and switching behaviour, it remains one of the cardinal factors in predicting 
customers’ ability to switch. Dunn (1995) argues that, it is essential in advertising to entice 
customers to use services at all times. Davies (1996) maintains that advertising effectiveness 
guides customers’ purchase decision. In view of the above assertions about the importance of 
advertisement on switching behaviour, there are some discrepancies in literature where Clemes et 
al., (2010) found a negative relationship between effective advertising competition and switching 
behaviour in the Chinese retail banking sector. 
 
2.4.5 Involuntary Switching 
Keaveney (1995) defines involuntary switching as the unexpected factors that affect customers 
and service providers. Extant literature (Fried & Smith, 1993; Ganesh, Arnold & Reynolds, 2000; 
Khan & Khanna, 2010) has proven that involuntary switching is one of the cardinal factors that 
make switching inevitable. This however is crucial hence the moving of services to other places 
beyond the reach of customers can end service relationships (Taylor et al., 2009). 
 
2.5 SERVICE ISSUES 
These are issues that arise when dealing with service failures or conflict situations (Zikiene & 
Bakanauskas, 2009). Inseparability being a service construct is brought to the fore due to direct 
encounter between a bank’s employee and the customer. Banks try to offer error-free services 
which are difficult to achieve. Zeithaml et al, (2005) affirm that, customers react to service failure 
in different expressions such as anxiety, anger and disappointment. 
 
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In addition to service issues, there exist service products and it consists of interaction quality, 
physical environment quality and outcome quality in a hierarchical context (Dagger, Sweeney & 
Johnson, 2007; Clemes et al., 2007). Despite the argument by Beckett et. al., (2000) that financial 
products have similarities, other researchers (Ogilvie, 1997; Kiser, 2002) also argue that products 
offered by banks influences customers’ ability to switch. Service firms can embrace technology to 
deliver wide range of products to its customers so as the firm to be profitable (Streiter et. al., 
1999). In the work of Nartey and Owusu-Frimpong (2011) they agree that technology is vital in 
influencing customers to switch. This assertion is also shared by some researchers such as Zhang 
and Prybutok (2005) and Bauer et. al., (2005). Zhang (2009) is of the view that service firms like 
banks that are not technologically innovative in products delivery may cause customers to switch.  
 
2.6 OTHER DRIVERS OF SWITCHING BEHAVIOUR  
2.6.1 Service Quality  
Vishal (2014) defines service quality as the degree of discrepancy between customer’s normative 
expectation for the service and their perceptions for the service performance. In the light of this, 
service quality changes from industry to industry (Parasuraman et al., 1988, 1994). To expand the 
discursion, Parasuraman et al., (1985, 1988) postulate five dimensional SERVQUAL model 
which Lasser et al., (2000) later expanded the ethos of the model in other service industries. The 
model assumes five dimensions; reliability, tangibles, empathy, assurance and responsiveness, 
and these factors determine how a customer weighs the quality of a service. 
  
The banking industry is very turbulent with customers often seeking for better and improved 
services. A high level of service quality is important in order to prevent bank customers from 
switching (Clemes et al., 2007) and in the work of Safakli (2007) superior service quality has a 
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positive relationship with customer switching behaviour. The delivery of service quality enhances 
customer retention, helps attract new customers through word of mouth advertising, leads to 
higher market shares and increases financial performance (Hinson, Mohammed, & Mensah, 
2006). 
 
A study conducted by Nyarko (2015) considered 350 respondents and reports that there is a 
significant relationship between service quality and switching behaviour. Some authors 
(Chakravarty, Feinberg & Rhee, 2004; Colgate & Hedge, 2001; Gerrard & Cunningham, 2004) 
agree to the findings of Nyarko (2015). Vishal (2014) posits that high service quality is critical 
for customer retention and that 42percent of account holders switched to another bank in service 
related issues in the US banking industry (Berggren & Dewar, 1991).   
 
2.6.2 Reputation 
Bennett and Kottasz (2000) defines reputation as “amalgamated of all expectations, perceptions 
and opinions of an organization developed over time by customers, employees, suppliers, 
investors and the public at large in relation to the organisations qualities, characteristics and 
behaviour based on personal experience, hearsay or organization’s past actions.” Reputation is a 
key indicator in its determinants of customers to switch or not because it is challenging to 
duplicate, non-substitutable and provides the firm with a sustainable competitive edge (Hall, 
1993; Wang et. al., 2003). Clemes et. al., (2010) posits that reputation can lead to increased 
customer loyalty with both customers and banks benefiting from it and that timely and accurate 
service reduce risk, hence making customers confident about the bank. 
 
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2.6.3 Customer Commitment 
According to Dwyer, Shurr and Oh (1987) commitment is an indication of both parties are 
interested in maintaining and strengthening their relationships. Morgan and Hunt (1994) assert 
that customer commitment has an impact on retaining a customer and in a related study; Gordon 
(2003) investigated the impact of customer commitment on switching intentions and concluded 
that committed customers were less likely to switch.  
2.6.4 Switching Cost 
The definition of switching cost in the banking sector connotes the range of costs that bank 
customers incur if they wish to transfer their banking relationship, in part or in full from one 
service provider to another (Matthews & Murray, 2007). Switching cost can be determined 
according to Lee and Cunningham (2001) not only by the costs which arise as a result of a 
relationship with a service provider, but also costs from one service provider to another. 
Burnham, Frels and Mahajan (2003) stated that switching cost compels customers to stay with 
their current service provider due to the cost associated to the exit. Switching cost according to 
Ranaweera and Prabhu (2003) retains customers who are satisfied as well as dissatisfied 
customers. This means that customers get locked up with a service provider so long as the exit 
barriers are high. Additionally, Kaur and Mahajan (2012) affirm that higher switching barriers 
result in lower switching intention, hence the customer cannot switch.  
 
2.7 SOCIO-ECONOMIC STATUS (SES) AND CONSUMER SWITCHING BEHAVIOUR 
A lot of studies (Boohene et al., 2013; Clemes et al., 2010; Narteh & Owusu-Frimpong, 2011; 
Nimako & Nyame, 2015; Nimako & Mensah, 2014) have reported that there are factors which 
determine customer switching behavior in different service sectors and these factors range from 
demographic factors to organizational services. These factors according to (Antwi-Boateng et al., 
2013; Mburu & Selapisa, 2012; Morgan, 2012; Tripathi & Singh, 2012; Karani, & Fraccastoro, 
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2010; Shin & Kim, 2008; Ranganathan, Seo, & Babad, 2006; Teo, Tan, & Peck, 2004; Gilbert, 
Lee-Kelley & Barton, 2003; Carroll, Howard, Peck & Murphy, 2002; Brosnan & Davidson, 
1996) are moderated by socio-demographic variables such as age, gender, income and education. 
 
2.7.1 Age and Switching Behaviour 
Switching behaviour has been examined and ample literature (Quester et al., 2007; Siles et al., 
1994) and reports that demographic characteristics can be used to differentiate the behaviour of 
one section of customers from another. Clemes, Gan, Zhang (2010) reports that the young age 
group have higher propensity to switch banks compared to older ones. Accordingly younger 
customers switch banks as a result of greater convenience, higher quality services and lower 
prices or favourable interest rates (Clemes et. al., 2010). This notion is also supported by Clemes 
et al., (2007a) who reported that younger customers are most likely to switch banks. To further 
enhance the discourse, some researchers (Gautam & Chandhok, 2011; Morgan, 2012) have 
argued that age and gender influence the switching behaviour of consumers. 
 
In a related study, Nartey and Owusu-Frimpong (2011) indicated that age has the tendency to 
influence consumers switching behaviour, though the study didn’t emphatically confirm the 
extent to which it affects switching.  
However other studies (Effah-Bediako, Deh & Asuamah, 2013; Nimako & Nyame, 2015), have 
dissenting view that age does not significantly affect switching behaviour. The studies further 
explain that the tendency of a customer to switch is dependent on age. This inconsistency needs 
deeper understanding to ascertain the true meaning in literature. 
 
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2.7.2 Income and Switching Behaviour 
According to Clemes et al, (2007a) customers with high income expect better service and failure 
to meet the expectation results in switching. It can be deduced that high income customers expect 
better services from their bank as a result of purchasing power. Nimako and Nyame (2015) 
reported that income positively affects switching behaviour and that the higher the income the 
more switching becomes inevitable. Effah-Bediako et al, (2013) reports on the contrary that 
income is a moderating variable in consumer switching and it is not consistent with earlier 
findings. Family income however is a predictor of switching behaviour  (Mburu & Selapisa, 
2012; Morgan, 2012; Tripathi & singh, 2012; Karani, & Fraccastoro, 2010). It is however evident 
that, customers with more income have tendencies to switch easily without bothering about cost 
involved compared to those with lower income levels. It is however imperative to consider how 
income affects the switching behaviour patterns of customers and to get deeper understanding of 
the inherent factors are missing in literature. 
 
2.7.3 Education and Switching Behaviour 
Literature makes it pronounced that educational level is positively linked to switching (Dholakia 
& Uusitalo, 2002; Keaveney & Parthasarathy, 2001; Ranganathan et al, 2006; Shin & Kim; 
2008). Shin and Kim (2008) further contend that customers with higher educational background 
are relatively more prone to switching than customers with lower educational status. 
 
2.8 SWITCHING BEHAVIOUR IN THE SERVICES SECTOR 
2.8.1 Insurance Industry 
Studies on switching behaviours have been examined in the insurance industry. For instance 
Wen-Bao (2010) conducted a study on top five insurance companies in Taiwan and Hong Kong 
and used a stratified sampling technique for the two metropolitan areas. 215 questionnaires were 
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administered to customers with only one insurance policy with majority of customers aged 
between 26 and 42.  
 
The study reports that the relationship between emotional intelligence and customer intentions to 
switch is highly significant. According to Salovery and Mayer (1990; 1993), “emotional 
intelligence is the perceptions, cognitions and understanding of one’s own and other’s emotions 
and the abilities to manage and utilize such emotions”.  According to Wen-Bao (2010), emotional 
intelligence is negatively related to switching behavior. In addition, switching behaviours are 
highly correlated with consumer relationship involvements. In view of these output, insurance 
companies should establish a long relationship with customers to enhance profitability. 
 
Again in Ghana, Boadu, Dwomo-Fokuo, Boakye and Frimpong (2014) conducted a study in the 
insurance industry in Ghana. The study investigated the disasters resulting in life and property.  
The sample size was 330 and random sampling technique was used in the study. The study 
concludes that the acquisition of customers to any business enterprise is important to the survival 
in the heavily competitive business environment. Therefore service providers of insurance 
products need no exception since according to the study; referrals play a key role in the survival 
of a company. The study again postulates that customers are ever ready to recommend their 
company to potential customers once services offered are good. In the reverse of this, bad 
experience will ultimately result in negative word of mouth which will drive customers away.  
According to Boadu et al. (2014), customer satisfaction and customer retention are major drivers 
of profit, customer base and market share; hence the need to engage in dialogue between 
providers of service and receivers of service to help iron out difficulties to increase retention. 
From the study, the intention to switch is dependent on price of insurance products and if the 
premiums are high, the consumer is tempted to consider other substitutes making consumers to 
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switch. Hence efforts must be made to reduce or have competitive pricing strategies to attract and 
retain customers. Additionally, core service failures must be avoided to make customers not to 
patronize the services of the insurance companies. 
 
2.8.2 Healthcare Industry 
Ofori-Okyere and Kumadey (2015) assessed service failures and customer complaints in the 
delivery of health care in three Ghanaian municipal hospitals. The study adopted a mixed method 
approach and 1500 questionnaires were used for the study including hospital administrators, 
doctors, physician assistants, nurses, pharmacists, dispensary technicians and of the three 
hospitals.  Sampling techniques used for the study included snowball, purposive and convenient 
sampling which according to the study gave enough chance for participants to be used for the 
study. The findings of the study revealed that, negative word of mouth about service failures will 
emerge so long as patients receive bad service. Thus friends and family will be told not to visit 
the particular health facility under scrutiny. Additionally, patients being the customers of the 
health facility will switch to a substitute health facility hence decreasing the clientele base, 
market share and profit at large.  
 
According to Ofori-Okyere & Kumadey (2015), the findings are consistent with previous studies 
that assume that anytime customers face dissatisfaction, they exhibit several alternatives as 
behaviours (Blodgett et al., 1995; Day, 1984; Day & Ash, 1979; Hirschman, 1970; Kim Dao, 
2013; Singh & Wilkes, 1996; TARP, 1986; Singh,1988). Ofori-Okyere and Kumadey (2015) 
further argued that customers will exit the service after experiencing failures when nothing is 
done to particularly recover it. This clearly means that the next competitor gets the opportunity to 
serve these customers. Patients will experience services that offer value for money and will 
continue unabated to patronize services of the provider as long as the service is good. 
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In a related study, Ayimbillah, Abekah-Nkrumah and Domfeh (2011) assessed patient’s 
satisfaction to health delivery in the northern part of Ghana. It was an explorative study with 324 
as sample size and stratified and convenient sampling techniques was used to gather the responses 
from respondents. Ayimbillah et al. (2011) revealed that clients easily switch due to service 
failure and this is very consistent with literature. Again, the expectation of delay is as a result of 
long systems put in place and these affect the quality and speed of service. When customers are 
not pleased with core service, they switch to a substitute health facility. The study also 
recommended that core service failures must be addressed quickly to gain trust of customers to 
reduce defection.  
 
2.8.3 Telecommunication Industry 
Chadha and Bhandari (2014) examined customer switching behaviour in the telecommunication 
industry in India. Exploratory research design was used and a sample size of 117 was used for the 
analysis. The study reported that network and services are the major driving force that makes 
customers to switch from one telecom network to another. In other words core service failures 
contribute immensely to the propensity for switching to occur. Additionally, tariffs affect how 
customers switch due to high prices as well as deceptive pricing and this from the study is the 
second factor that explains why customers switch. The third factor was technology which is how 
fast or slow the state of the art is. Chadha and Bhandari (2014) focused was on 2G, 3G and 4G 
which according to the customers makes them switch. The implication of the study makes it 
paramount for telecom companies to understand that, the factors that make consumers to switch is 
enormous hence the need to accept the existence of the phenomenon. Again consumers always 
keep price in view hence, charges that comes in tariffs should be considered to have life time 
value of the customer. 
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Arthur, Ahenkra and Asamoah (2012) in a related study, assessed the determinants of switching 
behavior in the Ghanaian telecom industry with a sample size of 261 within the Kumasi 
Metropolis in the Ashanti Region. Random sampling was used to get information from executives 
whilst convenience sampling was used for customers of the service providers. The use of chi-
square and descriptive statistics was used for the study. According to the author, 23% were 
subscribers of Tigo, 44.1% MTN, 12.6% Vodafone and 18.8% Airtel. This clearly indicates that 
MTN has the highest subscriber base in reference to the study. According to Arthur et al. (2012), 
high tariffs are the most important factor the Ghanaian consumer considers when switching from 
one network to another. The other factors include; service disruptions, hidden charges, inadequate 
information by service providers, unreliable help lines and attractive features offered by 
competition. The study concludes that high tariffs is very significant in switching behaviours 
hence customers must be made aware of tariffs in peak and off-peak times to enable them make 
good decisions on when to make calls. Again packages and bundles must be made available for 
customers to choose from. The study also revealed that the propensity to switch is dependent on 
income and level of education. This invariably means that, the more educated an individual is the 
more likely the customer will switch from one telecommunication to another. 
 
In relation to the telecom sector, Nimako and Owusu (2015) looked at six telecom companies in 
Ghana with a sample size of 756. The study employed the survey design from subscribers across 
the country. The findings of the study show that the attractiveness of a competitors’ offer can 
influence switching behavior hence the need to improve on products and services to be attractive 
to the consumer. Moreover, firms continue to improve on their services in order to outwit 
competition hence the reason customers are attracted to such firms. In the wake of this imminent 
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attractiveness, it is very important for firms to give the customer reasons to be delighted to reduce 
defection and make them loyal. 
 
The implications are that certain strategies must be employed to reduce and win-back defected 
customers such as communicating with customers regularly, listening to front liners, and treating 
valuable customers well, all in reducing switching by customers. Similarly, Effah-Bediako, Deh 
and Asuamah (2013), assessed the effect of switching decisions of mobile service users in Ghana. 
The study employed cross-sectional, descriptive, quantitative and survey research design with a 
sample size of 198. Convenience sampling technique was used for the study and the data analysis 
was interpreted with the use of cross-tabulation and chi-square.  
 
Effah-Bediako et al. (2013) reports that, males thus 61.1% have higher tendencies to switch than 
females and again, 69.5% of Muslims are likely to switch service providers on the basis of price 
than Christians. Furthermore majority of Christians thus 80.1% switch service providers on the 
basis of service encounter failures than Muslims. The study also reports that, 76.1% of 
respondents who do not know their personality trait switch service provider on the basis of price 
than collectivists and individualistic traits. The outcome of the research indicates that age, gender 
and family income as a moderating role is not consistent with earlier researchers (Brosnan & 
Davidson, 1996; Carroll et al., 2002; Gilbert et al., 2003; Karani, & Fraccastoro, 2010; Mburu & 
Selapisa, 2012; Morgan, 2012; Tripathi & singh, 2012; Ranganathan et al., 2006; Shin & Kim, 
2008; Teo et al., 2004; Zhu, 2002;) who reported of significant effects of gender and age on the 
factors that influences consumers on switching behavior of mobile services. 
 
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The implication of Effah-Bediako et al. (2013) is that socio-demographic variables (religion, 
personality, region, school) except family income, age and gender have a significant effect on the 
switching behaviours of consumers. Hence the need for proper segmentation of service offers to 
warrant interest of diverse groups of consumers. 
 
Furthermore in Pakistan, Kouser, Qureshi, Shahzad and Hasan (2012) assessed customers’ 
satisfaction and switching behavior in cellular services. The aim of the research was to 
understand the reasons that make customers switch to other cellular networks. The study 
considered 500 as the sample size and used convenience sampling as a technique to carry out the 
research.  Kouser et al. (2012) reports that price (cost) of service is the most significant factors 
that makes customers to switch. Again, core service failure also makes it imperative for 
customers to switch. The implication of the study is that service providers must minimize cost 
and ensure reliable service in order to ensure that customers do not switch to other competitors. 
 
In a related study, Soares and Proença (2015) conducted a study on service failures and 
considered a sample size of 40,813 and the sample size comprised of customers who had had 
problems with service encounter. The study reported that service failures have a negative 
influence on customers’ repurchase and this implies that customers are likely to switch. The 
findings of the study makes it emphatically clear that core service failures cannot be tolerated by 
customers to still remain loyal to the firm. So long as customers have a good substitute to a failed 
service, switching becomes inevitable. Again, an effective service recovery is very paramount in 
service failures as this help reduce the rate of defection. 
 
Significantly, Yeboah-Boateng, Olou and Yeboah-Ofori (2014) examined the implications of 
switching Barriers on subscriber retention in developing countries. The study used the cross-
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sectional survey and considered pre-paid customers of 400 and convenience sampling technique 
was used for the study. The findings of the study showed that switching barriers have a negative 
effect on subscriber retention in developing countries especially in the Ghanaian 
telecommunication industry. This means that customers can switch from one network to the other 
with incurring high cost because of mobile number portability. Despite this being a major 
revelation, telecommunication companies are very attractive to customers hence the company 
with the most unique selling preposition wins the customer. This has brought fierce competition 
in the industry making customers have more options at their disposal to either switch or not to.  
 
In the same vein, Nimako and Nyame (2015) assessed the impact of demographic variables, 
religiosity and porting behavior of mobile phone subscribers. The study adopted a cross sectional 
survey approach and administered structured questionnaires to 736 mobile phone subscribers 
from six telecommunication networks in Ghana: Vodafone Ghana, Tigo, MTN Ghana, Expresso, 
Glo and Airtel Ghana. Ghana. Out of the nine hypothesis proposed only five were supported 
whilst the rest remain unsupported. Hence the report were as follows: a significant relationship 
existed between demographic variables, porting behavior, length of relationship with service 
providers and switching behavior whilst demographic variables and religiosity did not predict 
switching behaviour of mobile subscribers in Ghana. Thus mobile network operators should 
segment their subscribers according to their demographic characteristics such as age, income, old 
and new subscribers, educational background and design programs to suit their needs. 
 
2.8.4 Hospitality Industry 
Nimako and Mensah (2013) assessed guest behavioral intentions in the hospitality industry. 
Using the self-administered questionnaire 359 respondents was selected for the study with 
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convenient sampling as a technique. The response were analysed using the structural equation 
model approach. The findings of the study indicated that loyalty is influenced by positive word-
of-mouth communication, satisfaction, perceived service quality, perceived value and perceived 
value of ambient factors. This means that loyalty in the hospitality industry are dependent on the 
factors listed and when core service failure occurs, it will adversely affect word of mouth 
communication  making customers to switch to another service provider. Similarly, Han, Kim and 
Hyun (2011) conducted a study on service performance, customer satisfaction and switching 
barriers in the hotel industry. Convenience sampling was used and a sample size of 358 
respondents was considered for the study. The study adopted the quantitative approach where 
structural equation model and factor analysis were used to analyse the responses. 
 
The study reported that “the components of switching barriers moderated the influence of 
customer satisfaction rooted in core service and encounter service performances on switching 
intention”. Additionally, customers’ intention to switch reduces when there is lack of attractive 
alternatives, relational investment and switching costs. Han et. al., (2011) argue that negative 
switching barriers easily create feelings of entrapment as this is consistent with previous studies 
(Han et al., 2009; Jones et al., 2000; 2007). Finally, the study concludes that management of 
hotels should implement relationship marketing activities to strengthen interpersonal relations for 
both guests and the hotel. 
 
2.8.5 Real Estate Industry 
Preko, Agbanu, and Feglo (2014) used a simple random to sample 248 customers of Elite 
Kingdom, a real estate company in Ghana. The main aim was to identify whether customer 
delight and satisfaction is dependent on service provided by an organization.  Preko et al. (2014) 
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reported that, customer satisfaction and customer delight depends on quality of service. The 
findings of the study imply that, quality of service is dependent on the service experience of 
customers hence different customers view quality from different perspectives. Once the service 
exceeds expectations, it results in customer delight which makes them loyal. Moreover, quality 
service perceived by customers makes them loyal and recommends service to potential customers 
too. This finding obviously reduces switching rate and leads to long term profitability. The study 
concludes that service firms should aim to delighting their customers in order to make them loyal 
which in effect reduce switching. 
 
Switching occurs in all service sectors and it is important to know how the issues have been 
captured in other service sectors in order to understand the phenomenon. For the purposes of the 
research it is also important to explore the banking sector to determine whether the issues 
represented can be described in relation to how customers switch. 
 
2.9 SWITCHING BEHAVIOUR IN THE BANKING SECTOR  
In Pakistan for example, a study conducted by Asab, Pirzada, Nawaz and Javed (2014), used a 
descriptive study to assess the factors influencing customer switching behavior and they used a 
sample size of 250 and used convenience sampling technique. The study looked at five variables 
namely; bank branches, religious beliefs, advertisement, service quality and profit and interest. 
The result was evident that service quality, bank branches and profits and interest by the bank 
asserted positive impact on switching behavior of customers of Pakistani banks. This implies that 
the quality of service cannot be compromised because it’s the driving force of customers in the 
banks. Again, bank branches are vital in bringing the service to the door step of customers hence 
efforts must be made to increase and expand the bank branches. On the issue of profit and interest 
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too, the bank must continue to improve on their interest rates and profits to in order to attract and 
even retain existing customers.  
 
In Malaysia for example, Subramaniam and Ramachandran (2012) evaluated switching behavior 
in Banks and used a sample size of 540 and employed convenience sampling technique in getting 
responses from participants. The study and multiple regression to test and understand how much 
of the variance is explained by a set of predictors. The study considered seven factors (price, 
reputation, service quality, advertising, involuntary switching, distance, switching cost) 
influencing the switching behavior of Malaysian consumers. The result of Subramaniam and 
Ramachandran (2012) showed that price and reputation were seen significant in predicting the 
switching behaviours of Malaysian consumers. Furthermore, the factors identified by previous 
researchers about switching behavior of Malaysian consumers is approximately 7% and this 
indicates that, other hidden factors like internet banking which might have deduced the distance, 
cost, advertising, involuntary action were not important in consumers’ decision making. 
 
Vishal (2014) examined the drivers of customers’ switching behaviour in banking industry and 
considered a sample size of 296. The research design was descriptive statistics with convenience 
sampling as a sampling technique. The major findings of the study according to the research do 
not work in isolation it’s the outcome of negative service experiences that result in most of the 
factors. The study identified nine factors (customer commitment, perceived service quality, 
effective advertising,  service products offered, customer satisfaction,  responses to service 
failure, reputation and image of bank, price including interest rates charged or paid, and 
involuntary switching) of which customer commitment, perceived service quality and effective 
advertising ranked top three factors influencing the switching behaviour of Indian customers. The 
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implications are enormous as banks are encouraged to shape service offerings to strengthen 
customer relationship. Again, banks should develop strategies that enhance positive behvioural 
responses to customer satisfaction, interest rates, advertising and service quality. Furthermore it’s 
recommended that the banks should be proactive in managing switching intentions such as 
meeting customers’ expectation in service delivery, preventing service problems and dealing with 
customers who not happy. Others include offering competitive pricing as well as increasing 
switching cost in order to lock the customers in. In wake competitive era in attracting customers, 
the study recommends that loyalty programmes should be designed for affinity groups to enhance 
advocacy. Word of mouth is an important tool in advertising and efforts must be made to making 
satisfied customers to speak good about the brand in order to inure to their benefits. Lastly, the 
banks must update customers about products and services already signed on to increase 
transparency. This in effect will reduce defection by customers. 
 
Notwithstanding the study by Vishal (2014) that looked at drivers of customers’ switching 
behavior, Gurjeet & Mahajan (2012), in another study explored customer switching intentions 
through relationship marketing paradigm and aim was to investigate the reasons underlying 
customer switching intentions. The study used the survey approach with a sample size of 765 and 
multiple regression was used for the study. It reports that all three factors (quick and effective 
response, core services up to expectations and reasonable charges) have a significant impact on 
switching intentions. 
 
Cohen, Gan, Yong and Chong (2007) looked at retention strategies by banks in New Zealand. 
The aim of the research was to assess the impact of retention constructs that has the propensity to 
influence consumers’ decision. The study used 514 as the sample size and the use of survey were 
employed to carry out the research. The most important construct according to the study was 
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customer satisfaction and that to retain a customer, satisfaction is vital in the firms’ service 
delivery. Once the customer is satisfied, there is the assumption that it will lead to repeat 
purchase. The second most influencing factor according to the study is corporate image of the 
bank. The way the banks are positioned in the mind of the consumers is of great hence as it most 
of the customers consider the image and pride with banking. Hence if the image of the bank 
commands respect, prestige and recognition, customers according to the study will enjoy staying 
with bank. The third factor according to the study is switching barriers.  
 
According to Cohen et al (2007), when exit costs are high, it inhibits customers’ propensity to 
switch to other competitors. Again the switching costs according to the study include offers and 
discounts of facilities that customers have signed on to with certain terms and conditions. This 
makes it vital for banks to design services to satisfy and delight customers in order to remain 
loyal, and for the customer, once expectations are met there is loyalty however, firms’ must move 
beyond satisfaction to customer delight. That is when service offered exceeds expectation. This 
delight will leave a lasting impression in the mind of the customer and will reduce the defection 
rate, hence making them loyal. Again, Cohen et. al., (2007) report that that as customers age, they 
are more likely to stay with current bank. Customers have joy with a particular bank as they age 
hence switching becomes difficult as perhaps substitutes do not offer anything new or different. 
Hence firms’ must continue to offer superior value of service to customers to ensure that 
customers’ continue to remain at the bank. 
 
Lastly, the study reports that, the higher the education of customers the most likely to switch 
banks perhaps because great expectation of services. The needs of customers’ keep changing 
owing to the behaviour changes as well as lifestyles. The most educated customers’ expectation 
are high therefore when there is a service failure, they switch. This onus lies on the banks to 
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continue deliver and exceed customers’ expectation and this will reduce the switch. Besides, a 
satisfied customer may give positive word of mouth to the firm. 
 
Similar to this, Clemes, et al, (2010) examined the determinants of switching behavior in China. 
It was hypothesised that the antecedents like price, reputation, service quality, effective 
advertising competition, involuntary switching, distance, switching costs, distance and 
demographic characteristics will influence customer switching behaviour. With the aid of focus 
group discussions, questionnaires were developed and administered to customers of banks in 
Jiaozuo City, Henan Province, China. Out of 700 questionnaires administered, 421 were retrieved 
and analyzed. Clemes et al. (2010) reported that price, reputation, service quality, effective 
advertising, involuntary switching, distance and switching costs accounts for switching 
behaviour. Additionally it was reported that young customers and high-income groups are more 
likely to switch banks. Drawing on these findings the implications are that professionals in the 
field of marketing should implement service-marketing strategies to decrease customer defection 
rates and increase bank profits. Moreover, this research provides useful information for 
investigating customer switching behaviour in the retail banking industry in other countries.  
 
In West Africa, Kura, Mat, Gorondutse, Magaji and Yusuf (2012) examined the precursors of 
switching behavior among customers in the Nigerian banking industry. The study used 100 
sample size and used the structural equation model. The study proposed five key constructs; 
assurance and customer switching, empathy and customer switching, assurance and word of 
mouth communication, empathy and word of mouth communication, word of mouth 
communication and customer switching. The study found three of the constructs as having a 
positive relationship thus assurance and word of mouth communication; empathy and word of 
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mouth communication and word of mouth communication and customer switching. However, the 
study established that the relationship between assurance and customer switching is not 
significant. Additionally, the relationship between empathy and customer switching is not 
significant as well. The findings of Kura et al. (2012) imply that banks should continue to deliver 
good services to warrant positive word of mouth in order to reduce switch hence increasing 
loyalty. When switching is reduced organisations can harness a lot from the customer. 
 
In a related study in Ghana Abawiera (2014) examined important factors of customer satisfaction 
of rural banks in the Ashanti Region. A sample size of 300 was used and two random sampling 
techniques were used to select the sample and probit regression was used to carry out the 
analysis. The study showed that customer satisfaction depends on customer complaints; hence 
firms must heed to complain of customers in order to prevent switching. Complains are as a result 
of a dissatisfaction of a service and its imperative to note that customers can make and unmake an 
organization. Again the study showed that accessibility of bank to customers is very necessary 
because that is where the customer comes in contact with the services of the firm. The closer the 
bank, the closer customer engagements therefore the location of banks should be considered in 
order to bring banking to the doorstep of customers’. Other interesting findings were that, 
customers considered tidiness and cleanliness as key component in retention strategies. Despite 
this being third from the findings of the study, it is essential for policy makers and decision 
makers to continue to have very good ambience as well as cleanliness in the environment. Lastly, 
speed of service and knowledge base of the bank were last according to the findings. Hence, the 
bank needs to create the right conditions of ensuring good service delivery to retain and attract 
new ones. It also implies that service failures will result in customer defunct which is always 
detrimental to the success of the bank. 
 
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In a similar study Okoe, Adjei and Osarenkhoe (2013) assessed the quality of service in the 
Ghanaian Banking Industry of four indigenous and foreign banks in Ghana. Using a cross-
sectional approach and a sample size of 400 was used for the study. Two indigenous banks: GCB 
Bank and Cal Bank and two foreign banks: Standard Chartered Bank and Ecobank were selected 
for the study.  The study employed purposive sampling technique and mixed method approaches 
to conduct the research. Furthermore Okoe, Adjei and Osarenkhoe (2013) reported that, there are 
gaps that exist between customer expectation and perception of service delivery. Moreover, 
dissatisfied customers’ would not necessarily switch however, there are factors that compel 
customers to switch beyond dissatisfaction that is reliability and responsiveness. The study makes 
it emphatically clear that customers’ ability to switch is dependent on access to bank every time, 
good customer service, interest rates and bank charges. Hence, banks have the onus to deliver 
superior value to clients or customers to ensure effective retention which maximizes a firm’s 
profit. 
 
Furthermore Boohene, Agyapong and Gonu (2013) examined some retention factors which 
influence customers’ decision to stay in Ghana Commercial Bank (GCB) situated in the Agona 
Swedru municipality. They sought to assess customers’ perceptions of the research variables 
listed; service quality, customer trust, switching barriers, customer satisfaction and customer 
commitment and how it influences their decision to remain with the Ghana Commercial bank. 
Using data collected from 430 respondents, the results showed that a moderately positive 
relationship existed between service quality and retention and customer trust and retention. 
Secondly, a strong positive relationship existed between switching barriers and customer 
retention and customer commitment and retention. On the contrary, there was a weak positive 
relationship between customer satisfaction and customer retention. The findings implied that all 
research variables showed a positive relationship with customer retention. Therefore, 
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management of Ghana commercial bank should invest in strategies that will continuously 
encourage customers to remain with them and no other banks in that vicinity. 
 
In a more recent study, Nimako and Mensah (2014) investigated the relationship between 
customer satisfaction and customer reactions in the Ghanaian banking industry. Structured 
questionnaire were administered to 650 customers of 10 banking institutions in Ghana: Societe-
Generale Social Security Bank Ghana, United Bank for Africa, Fidelity Bank, Ecobank Ghana, 
Agricultural Development Bank, National Investment Bank, Ghana Commercial Bank, 
Bosomtwe Rural Bank, Atwima Nwabiagya Rural Bank and Barclays Bank and this was possible 
with 448 questionnaires. Nimako and Mensah (2014) reported that complaining responses and 
frequency of
complaining were significantly correlated. Secondly, complaining responses and 
overall satisfaction were also significant. On the contrary, proposed hypothesis one and two of the 
study was not supported. The report of the study implies that complainers are more likely to be 
people who are more dissatisfied with banking services. However if they don’t complain, they 
will opt for other means to express their dissatisfaction such as damaging word of mouth 
communication about the bank.  
 
More important to these implications is that the frequency of complaining does not unavoidably 
lead to dissatisfaction. Therefore banking institutions should see the act of complaining as a way 
to correct mistakes in order to make customers satisfied (McColl & Schneider, 2000; Priluck & 
Lala, 2009; Vos, Huitema, & de Lange-Ros, 2008). 
 
 
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Narteh and Owusu-Frimpong (2011) examined students’ choice criteria in retail bank selection in 
sub-Saharan Africa. The aim of the research was to design programs to retain customers. Out of 
400 questionnaires to graduates and undergraduates in the University of Ghana Business School 
and Accra city campuses, 223 questionnaires were retrieved and analyzed. Narteh and Owusu-
Frimpong (2011) reported that student as customers ranked the following factors: image, attitude 
and behaviour of staff, core service delivery and technology-related factors as the major issues 
that influence consumers’ decision to open and maintain an account. Thus, management of banks 
should consider these key factors: image, attitude and behaviour of staff, core service delivery 
and technology-related factors in order to increase student customers as well as maintain existing 
ones.  
 
2.10 CRITIQUE OF STUDIES ON CUSTOMER SWITCHING BEHAVIOR 
Extant literature makes it emphatically clear that switching behaviours are as a result of 
unsatisfied needs by consumers (Boadu et al., 2014; Chadha & Bhandari, 2014; Nimako & 
Owusu, 2015) and it has been researched in various industries such as insurance industry (Boadu 
et al., 2014; Wen-Bao, 2010) health care industry (Ayimbillah et al., 2011; Ofori-Okyere & 
Kumadey, 2015) telecommunication industry (Arthur et al., 2012; Effah-Bediako et al., 2013; 
Chadha & Bhandari, 2014; Nimako & Nyame, 2015; Nimako & Owusu, 2015; Yeboah-Boateng, 
et al., 2014; Kouser, et al., 2012) banking industry (Abawiera et al., 2014; Asab et al., 2014; 
Boohene et al., 2013; Clemes et al., 2010; Cohen et al., 2007; Gurjeet & Mahajan, 2012; Kura et 
al., 2012; Narteh & Owusu-Frimpong, 2011; Okoe et al, 2013; Nimako & Mensah, 2014; 
Subramaniam & Ramachandran, 2012; Vishal, 2014) hospitality industry (Han et al., 2011; 
Nimako & Mensah, 2013) and real estate industry (Preko et al., 2014). 
 
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Even though most of the studies reported that there are factors which determine customer 
switching behavior  in different organizations (Boohene et al., 2013; Clemes et al., 2010; Narteh 
& Owusu-Frimpong, 2011; Nimako & Nyame, 2015; Nimako & Mensah, 2014) these factors 
ranged from demographic factors to organizational services. Most of these studies selected 
samples which are more than 400 (Clemes et al., 2010; Nimako & Nyame, 2015; Nimako & 
Mensah, 2014; Boohene et al., 2013) whilst other studies used sample size of 400 and below 
(Abawiera et al., 2014; Arthur et al., 2012; Asab et al., 2014; Ayimbillah et al., 2011; Effah-
Bediako et al., 2013,  Chadha & Bhandari, 2014; Boadu et al., 2014; Kura et al., 2012; Narteh & 
Owusu-Frimpong, 2011; Okoe et al., 2013; Preko et al., 2014; Vishal, 2014; Wen-Bao, 2010; 
Yeboah-Boateng et al., 2014).  
 
Also it is imperative to state that most of the studies reviewed used self-administered structured 
questionnaires (Boohene et al., 2013; Clemes et al., 2010; Nimako & Nyame, 2015; Nimako & 
Mensah, 2014; Narteh & Owusu-Frimpong, 2011) while only one study adopted focus group 
discursion (Clemes et al., 2010). 
 
The sampling technique used by many researchers suggests the proliferation use of convenience 
sampling (Asab et al., 2014; Effah-Bediako et al., 2013; Clemes et al., 2010; Kouser, et al., 2012; 
Nimako & Mensah, 2014; Narteh & Owusu-Frimpong, 2011; Subramaniam & Ramachandran, 
2012; Vishal, 2014; Yeboah-Boateng et al., 2014), whilst few studies have adopted simple 
random sampling to select respondents (Abawiera et al., 2014; Boadu et al., 2014; Boohene et al., 
2013; Preko et al., 2014). Other studies used one or more sampling techniques other than 
convenience sampling (Ayimbillah et al., 2011; Ofori-Okyere & Kumadey, 2015; Okoe et al., 
2013). 
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Moreover, most of the studies used customers and consumers as respondents (Abawiera et al., 
2014; Arthur et al., 2012; Asab et al., 2014; Ayimbillah et al., 2011; Boadu et al., 2014; Boohene 
et al., 2013; Chadha & Bhandari, 2014; Clemes et al., 2010; Effah-Bediako et al., 2013; Gurjeet 
& Mahajan, 2012; Kouser, et al., 2012; Nimako & Mensah, 2014; Okoe et al., 2013; Preko et al., 
2014; Subramaniam & Ramachandran, 2012; Vishal, 2014; Wen-Bao, 2010; Yeboah-Boateng et 
al., 2014) without segregating the types of customers and consumers available with exception of 
two studies. The first study (Narteh & Owusu-Frimpong, 2011) concentrated on the 
undergraduates and graduates and the other (Ofori-Okyere & Kumadey, 2015) on workers in 
hospital with emphasis on administrative staff. 
 
Furthermore most of the studies focused on customer switching behavior in either a particular 
bank or a number of banks (Boohene et al., 2013; Clemes et al., 2010; Nimako & Mensah, 2014; 
Narteh & Owusu-Frimpong, 2011). While others focused on the telecommunication and 
hospitality industry (Nimako & Nyame, 2015). Besides most of these used samples of customers 
in the locality where the study was being conducted instead of using only students or 
administrative workers (Boohene et al., 2013; Clemes et al., 2010; Nimako & Nyame, 2015; 
Nimako & Mensah, 2014). It is significant to note that some studies (Arthur et al., 2012; Chadha 
& Bhandari, 2014; Clemes et al., 2010; Kouser, et al., 2012; Subramaniam & Ramachandran, 
2012) agree to the fact that price and tariffs have a positive relation on switching behavior.  
 
There are also inconsistencies with literature that suggest that demographic variables do not 
influence switching behavior. Effah-Bediako et al., (2013) argues that age and gender do not 
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influence switching behavior however, Nimako & Nyame (2015), in a recent study concluded 
that there is a significant relationship between demographic variables (age, income) and 
switching behavior. These inconsistencies need to be tested to ascertain the facts, which can be 
used to either accept or reject the claims in literature. 
Finally, some of the studies were conducted in Ghana (Abawiera et al., 2014; Arthur et al., 2012; 
Ayimbillah et al., 2011; Boadu et al., 2014; Boateng et al., 2014; Boohene et al., 2013; Narteh & 
Owusu-Frimpong, 2011; Nimako & Owusu, 2015; Nimako & Mensah, 2014; Ofori-Okyere & 
Kumadey, 2015; Okoe et al., 2013; Effah-Bediako et al., 2013) Nigeria (Kura et al., 2012), whilst 
others were done in Asia and Europe (Chadha & Bhandari, 2014; Clemes et al., 2010; Cohen et 
al., 2007; Gurjeet & Mahajan, 2012; Subramaniam & Ramachandran, 2012; Vishal, 2014).  
 
2.11 CONCEPTUAL FRAMEWORK 
The framework was developed from Clemes et al. (2010) and hypothesized that the independent 
variables is significantly related to switching behaviour. However, the demographic variables as 
the moderator have the tendency to affect the relationship between the dependent and 
independent variable. The conceptual framework has been outlined as follows. 
 
2.11.1 Price and Switching Behaviour 
Price according to Zeithaml (1988) is what is given up for a service and in the context of this 
study; price connotes interest rates and bank charges, which in effect affect customers switching 
behaviour. When bank charges are high, customers consider alternative sources where the price is 
relatively low or moderately priced hence high bank charges can affect the bank’s operations by 
losing customers to other competitors (Nyarko, 2015). Keaveny (1995) reports that, almost thirty 
percent of customers switch due to poor pricing perceptions. In addition Gerrard and Cunningham 
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(2004) advocate that price is very vital in persuading consumers to switch. The study again posits 
that higher tariffs or fees charged can have effect on consumers’ decision to switch. Hence, 
following hypothesis is proposed: 
H1: There is a positive relationship between a disparaging perception of price and customers 
switching banks. 
 
2.11.2 Technology and Switching Behaviour 
The services offered by banks are very critical in retaining customers and attracting new ones and 
hence, the technology used by the bank can be a source of competitive advantage. Nartey and 
Owusu-Frimpong (2011), reports that technology can influence the selection criteria of a 
customer and this assertion is shared by Parasuraman et al, (2005). Ankrah (2013) in study 
concluded that technology significantly affect customers’ switching intentions. The study again 
revealed that internet banking and ATM services were crucial in influencing customers to switch.  
Therefore, the following hypothesis is proposed: 
H2: There is a positive relationship between technology and switching behavior. 
 
2.11.3 Service Quality and Switching Behaviour 
Extant literature (Clemes, et al., 2007; Safakli, 2007) argue that, there is there is a positive 
relationship between superior value and customer switching behaviour in the banking sector.  
Pirzada et al, (2014) also conclude that, there exists a significant relationship between service 
quality and customers’ switching behaviour. The study further argues that an increase in the 
quality of service will reduce customers’ intention to switch. Furthermore, Nyarko (2015) also 
concluded in a study that, there is a significant relationship between service quality and switching 
behaviour. Service quality exists when there is contentment of desire from service providers 
(Parasuraman & Zeithaml, 2006). The ability to provide quality service is essential to the survival 
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of firms as it serves as a competitive advantage and ensures profitability as well. Hence the 
following hypothesis is proposed: 
H3: There is a significant relationship between service quality and customer switching behaviour 
 
2.11.4 Advertisement and Switching Behaviour 
The promotion of company’s products and services to make existing customers and potential 
customers aware is what is termed as advertising (Cengiz et. al., 2007). According to Cengiz et. 
al., (2007) the basic essence of advertising is to inform potential customers about products and 
services the bank has to offer. Becker and Murphy (1993) developed a model and used 
advertising as a complementary good and proved that customers may derive more utility from 
consuming a more advertised good. Due to the nature of competition in the banking sector, it has 
become necessary for banks to promote its product to attract new customers. It is therefore 
important to note that customers of existing banks may want to switch to another because of an 
advertised product of the new bank. Hence, following hypothesis is proposed:  
H4: There is a negative relationship between ineffective advertising competition and customers’ 
switching banks.  
 
2.11.5 Involuntary Factors and Switching Behaviour 
Involuntary switching is defined as the factors that go beyond the customer or the service 
provider and extant literature has established. The authors argue that involuntary remains one of 
the cardinal factors that affects switching behaviour though in a study by Vishal (2014) reports 
that, involuntary switching remains the most common behaviour in switching due to some factors 
such as change of jobs, moving house or branches closed down in that area. Taylor, Roots and 
Hamer (2009) posit that despite the firms’ ability to provide superior services, customers can still 
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switch due to reasons beyond control of either party.  Therefore the following hypothesis is 
proposed:  
H5: Involuntary switching factors affect customers’ switching banks. 
 
2.11.6 Customer Satisfaction 
Wirtz (2003) say that firms can only measure satisfaction when there is positive word of mouth, 
repeat purchase and long term profitability. This assertion makes it profound on the basis that, 
customers get satisfied on the bases of prior experience with the bank (Aydin et. al., 2005). 
Cudjoe et al, (2015) report that customer satisfaction to a greater level is dependent on total 
service quality a firm delivers. Therefore the following hypothesis is proposed:  
H6: There is a positive relation between customer dissatisfaction and customers’ switching banks 
 
2.11.7 Responses to Service Failure 
These are as a result of issues that arise when the service is being delivered (Zikiene & 
Bakanauskas, 2009). Inseparability being one of the construct of service characteristics makes it 
possible for customers to interact with the bank’s employees, telephone or automatic teller 
machine (ATM). Johnston and Michel (2004) argues that service failures are unavoidable despite 
banks efforts to offer error-free services. Therefore the following hypothesis is proposed:  
H7: There is a positive relation between service failure and customers’ switching banks. 
 
2.11.8 Service Products 
Products offered by banks makes customers switch to another as a result of differences in product 
characteristics (Ogilvie, 1997; Kiser, 2002). Streital, Gupta, Raj and Wilemon (1999) advance 
that, technology driven environment requires offering variety of products for customer to choose 
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from and this ensures the survival of the company. Gerrard and Cunningham (2004) postulate that 
banks that do not innovate products with technology may cause switching to occur. Therefore the 
following hypothesis is proposed:  
H8: There is a negative relation between service products and customers’ switching banks. 
 
2.12 DEMOGRAPHIC VARIABLES 
2.12.1 Socio-Economic Status (SES) and Switching Behaviour 
Many researchers (Boohene et al., 2013; Clemes et al., 2010; Narteh & Owusu-Frimpong, 2011; 
Nimako & Nyame, 2015; Nimako & Mensah, 2014) have claimed that several factors affect 
customers’ switching behaviour and these includes demographic factors to organizational 
services. Block and Roering (1976) also adhere to the fact that, demographic factors give 
meaning to understanding consumer characteristics and behaviour. These factors according to 
(Antwi-Boateng et al., 2013; Mburu & Selapisa, 2012; Morgan, 2012; Tripathi & Singh, 2012; 
Karani, & Fraccastoro, 2010; Shin & Kim, 2008; Ranganathan et al., 2006; Teo et al., 2004; 
Gilbert et al., 2003; Carroll et al., 2002; Brosnan & Davidson, 1996) are moderated by socio-
demographic variables such as age, gender, income and education. Yoon and Cole (2008) assert 
that age is widely accepted in consumer behaviour and that, experiences of younger and older 
customers are not the same when comes to switching behaviour with service offering. Due to the 
differences in male and female characteristics, people behave differently when posed with same 
service offering which is rooted in the socialization theory (Fernandes, Proenca & Rambocas, 
2013). In addition, men are more calculative in solving problems whereas women pay attention to 
detail and these differences influences choices and behaviour (Spelke & Spinker, 2005). On the 
issue with education, customers with higher educational background tend to have detail cognitive 
processing of information which gives rise to alternatives thereby maximizing their utility 
(Fernandes et. al., 2013). In addition, educated customers are able to differentiate on service 
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offerings and thus reduce dissonance when it comes to switching (Burnham et. al., 2003). In view 
of this the following hypothesis is proposed: 
H9: There is a positive relationship between age and customers’ switching banks. 
H10: There is a positive relationship between income and customers’ switching banks. 
H11: There is a positive relationship between education levels and customers’ switching bank. 
H12: There is a positive relationship between gender and customers’ switching banks. 
 
Figure 1. A proposed conceptual framework of the hypothesized relationship between 
drivers of switching behaviour and its dimensions 
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CHAPTER THREE 
CONTEXT OF THE STUDY 
 
3.0 INTRODUCTION 
The chapter provides the setting of the study and starts with the description of Ghana territorial 
region as well as banking sector in Ghana. It also features the key developments in the sector over 
time and its major contribution to the growth of the sector. 
 
3.1 HISTORY OF BANKING IN GHANA 
The colonial era saw the use of money in exchange for services. Ghana, formerly called Gold 
Coast used cowries from shells as a legal tender to purchase goods and services. Up until the 
1880’s, the trading activities was centered at the coastal areas of the country and merchants used 
gold weight to determine price of items purchased. Between 1818 and 1825, the denomination 
that was used in the Gold Coast era was the British coins, the US dollars and the cowries which 
saw the boom in the economic activities of the country at the time. The dollars was used to fund 
the activities of soldiers on mission and later the British coin become acceptable by the people 
when the demonetization ordinance was passed. This passage saw the fall of the cowries in the 
history of Gold Coast. 
 
In the early years of 1894, the Bank of British West Africa was born and registered as a company 
which begun operations to formalize the banking system. This was done to take charge of 
monetary transactions that happened at the time and also took charge of accounts of the managers 
of the economy (Anin, 2000). 
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The era of monopoly ended in 1917 where the British government decided to introduce 
competition and it resulted in the introduction of Barclays Bank. By 1925, the colonial bank was 
merged and gave rise to Barlcays Bank DCO (Dominion, Colonial and Overseas). 
 
The evolution of banking activities in the post era was mainly discounting of bills and exchanges, 
documentary credits and remittances. These were the primary function of the banks and the 
customers comprised of civil servants, traders and workers of the British educationists. This era 
had no standardized technology for banking so most of the transactions were done in books the 
system required more hands to take care of the growing demand of the customers. 
 
3.2 GHANA (PHYSICAL SETTING) 
Ghana is situated along the west coast of Gulf of Guinea and it’s embodied by three countries 
namely; Cote d’Ivoire, Togo and Burkina Faso. The topography of Ghana is about 238,540 sq. 
km and its population is 24 million and still counting (GSS, 2010). Ghana has 10 regions with 
distinct characteristics in each region the growth of the country is expected to increase to 
27million by 2016 (GSS, 2012).  
 
3.3 BRIEF HISTORY OF THE GHANA CURRENCY  
The West African Currency Board (WACB) had the responsibility of the issuance of the currency 
before independence. The currency at the time was the West African Pound, Shillings and Pence 
which was a legal tender until July 1958 (BoG, 2011). 
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3.3.1 The Birth of the Cedi   
Ghana’s Independence marked the new era of issuing its own currency in the form of the Ghana 
Pounds, Shillings and Pence. As a result of the independence, the issuance of the currency notes 
was the sole responsibility of the Bank of Ghana. 
 
The Cedi notes and Pesewa coins were introduced to replace the British denomination. During the 
mid-1960’s the cedi was equal to eight shillings and four pence (8s.4p) and had. Cedi was derived 
from “sedie” which had a meaning in Ghanaian dialect as cowrie and gained acceptance in the 
later part of the 19th Century. The coin called “Pesewa” was used to change the British Colonial 
penny which was the smallest.  
 
3.4 OUTLINE OF PAYMENT SYSTEMS IN GHANA 
Since 1997, the payment systems in Ghana has improved significantly and this continue to 
change according to the requirements of the country. In 2014, the Bank of Ghana implemented a 
10-year National Payment System which sought to improve the strategy used in the early 2000. 
Presently, the demands of the country are driven by public policy factors, economic, financial and 
an increase in ICT and global trends in payment systems development.  
 
The following are the objectives underlying the payment and settlement systems. 
 To prevent and or contain risks in payment, clearing and settlement systems 
 To establish a robust oversight and regulatory regime for the payment and settlement 
systems; 
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 To bring efficiency to fiscal operations of the Ghana Government 
 To deepen financial intermediation; 
 To discourage the use of cash for transactions whilst encouraging the use of paper-based 
instruments for payments as part of the short-term development plan; 
 To promote financial inclusion without risking the safety and soundness of the banking 
system; and 
 To develop an integrated electronic payment infrastructure that will enhance 
interoperability of payment and securities infrastructures. 
Figure 2: The payment system in Ghana 
 
Source: Bank of Ghana, 2014 
The Central Bank has system operators who have other channels of transferring funds between 
two points. Then the commercial banks also take the data from the system operators who then 
retail the information to the public or customers. In some cases, there is collaboration between the 
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private sector and the commercial banks as well. The diagram shown in figure 2 presents the 
pictorial view of the payment systems in Ghana. 
 
3.5 RULES GOVERNING AUTOMATIC TELLER MACHINE (ATM) AND POINT OF 
SALE SYSTEMS IN GHANA 
The effective way of ensuring legal and regulatory environment towards the operation of ATM 
and Point of Sale Systems is dependent on Bank of Ghana. The mandate is to ensure that 
suppliers have the needed practical and fiscal muscle to deliver what is expected of them. The 
approval for the setting of these platforms require adherent to the following conditions: 
 
 Establishment of ATM’s and POS is restricted to the banks, its conglomerate and other 
stakeholders. 
 The ISO certification must be standard and the ATM must support other cards from other 
banks like VISA and Mastercard. 
 Local banks who are interested in this operation must meet the following requirements. 
(a) More than four banks, minimum of 20 ATMs and 50% of the branches of each    
bank networked. 
(b) four banks, minimum of 30 ATMs and 50% of the branches of each bank  
networked. 
(c) three banks, minimum of 50 ATMs and 50% of the branches of each bank   
networked. 
 Local banks must ensure that there is interconnectivity and interoperability with current 
platforms. 
 
 
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3.6 THE GHANAIAN BANKING INDUSTRY 
Ghana has a population over 27 million (GSS, 2014) and it is situated at the West Coast of Africa 
with a projected growth rate of 6.4percent (BoG 2014). The Ghanaian banking industry over the 
years has seen major reforms since the 1980’s as part of IMF-World Bank structural adjustment 
programme to help improve the performance of the industry (Owusu-Frimpong, 2008). As a 
result of these activities, the Bank of Ghana deregularised the banking sector in 2006 and it 
abolished the three tiered structure of commercial, development and merchant banks. This 
strategy ensured that banks were able to operate in all sectors of the economy with their universal 
license.  
 
As a result of the deregulation, the banking sector in Ghana currently has 28 licensed banks with 
the latest addition being GN Bank formerly First National Savings and Loans Limited. Out of this 
number 13 are locally owned whilst 15 are foreign with the Nigerian banks dominating the 
foreign scene (BoG, 2014). 
Some of the local banks includes; GCB Bank formerly Ghana Commercial Bank, Agricultural 
Development Bank (ADB) and National Investment Bank which are owned wholly or 
considerably by the state and the purely private local banks such us Prudential Bank, UniBank 
and UT Bank. Some of the foreign banks also include; Standard Chartered Bank, Barclays Bank 
(UK), SG-SSB Bank (France), Stanbic Bank (South Africa), Zenith Bank, United Bank for 
Africa, Bank of Africa formerly Amalgamated Bank (Nigeria) and Ecobank Ghana Limited. 
 
Apart from the banks, other financial institutions like the microfinance also contribute to the 
growth of the economy. According to the Bank of Ghana (2014), the total assets of microfinance 
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institutions increased by 203.2 percent to GH¢958.8 million in 2014. This hefty feat was as a 
result of increase in the number of licensed MFI in the course of the year. 
This significant development in the Ghanaian banking industry suggests that firms must develop 
strategies to stay in business in the highly competitive environment. Firms has to develop 
differentiated services to attract customers and retain existing ones however as long as 
alternatives exist, customers will always switch and this makes the banking sector interesting. 
Banks are looking for innovative ways to satisfy customers with the use of technology and 
superior offerings to prevent customers from switching.  
 
3.7 DEVELOPMENTS IN BANKS AND NON-BANK FINANCIAL INSTITUTIONS 
3.7.1 Overview 
According to the BoG (2014) annual report, the deposit money banks and the non-bank 
institutions performed well in the year under review. There was an increase in banks, non-banks 
and rural banks which made the banking sector viable. 
 
3.7.2 Assets and Liabilities 
Deposit Money Banks (DMB) and Rural Community Banks (RCB) and Non-Bank Financial 
Institution (NBFI) did well financially by 40% by the financial year of 2014. BoG (2014) reports 
that the performance in the banking sector was as a result of loans and advances which also 
increased by 40% and 69.2% respectively. This is comparable to 2013 where loans and advances 
were 35.2% and 20.8%. This shows that the differences were significant which had a positive 
impact on the banking sector. 
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It is evident to note that, the total assets of banks and non-banks, accounted for 85.2% as 
compared to 84.4% in 2013. This implies that the banking sector in Ghana is doing despite the 
challenges that it’s faced with. 
 
3.8 STABILITY OF THE FINANCIAL SYSTEM 
In 2014, the external threats that the banking sector faced got to its peak because of the foreign 
and local macro-financial development. The first half of the year under review was characterised 
by heavy risks compared to the other part of the year which showed weak risks.  
 
3.8.1 Macro-Financial Stress Tests 
Bank of Ghana conducted a test called the two stress tests and this was done to know the stability 
of the banking sector. The potential causes of threats were taken into considerations which are 
liquidity, concentration and credit. As a result of this, the banks’ balance sheet were not too good 
however, the tests done, proved and graded the following factors; 
 Exchange rate risk was relatively tamed on account of  existing regulation on net open 
position requirements 
 Credit risk shocks had a pronounced impact on the Ghanaian banking system 
 The banking system remained highly susceptible to single largest borrower risk 
 Ability to withstand interest rate shocks continued to worsen 
 Multi-factor shocks involving credit and exchange rate risk showed unchanged robustness 
of the banking system in 2014 form 2013.  
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CHAPTER FOUR 
METHODOLOGY 
 
4.0 INTRODUCTION 
The chapter outlines the methodology carried in the research. The plan of the research includes 
the method used to achieve the research objectives stated in chapter one. Hence the chapter 
discusses methodological issues such as philosophical perspectives, research purpose, research 
approach, research strategy and design, data collection methods and method of data analysis.  
 
4.1 PHILOSOPHICAL PERSPECTIVES AND PARADIGMS 
Philosophical perspectives can be described as the frameworks within which all academic 
researchers are captured (Holden & Lynch, 2004). In line with this view, it is believed that 
ignoring philosophical issues and paradigms can affect the quality of research (Amaratunga et al., 
2002). Paradigms are a set of beliefs, values and techniques which is shared by members of a 
scientific community, and which acts  as  a  guide  or  map,  dictating  the  kinds  of  problems  
scientists  should  address  and  the  types  of explanations  that  are  acceptable  to  them” 
(Kuhn,1970). The most commonly used paradigms in the arena of social research are realism, 
relativism, critical realism, interpretivist, and positivism (Downward &  Mearman,  2004;  
Beverland  & Lindgreen,  2010). 
 
However, this current study draws on the paradigms of relativism and positivism to examine 
some key factors of switching behaviour and adds to an existing theory (Keaveny, 1995). 
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Relativism owes to the belief that the construction of knowledge is influenced by the ideologies 
of a researcher. Thus, researchers should aim at focusing on innovating or developing new 
theories which will be effective in solving specific problems (Downward & Mearman, 2004).   
The positivists approach supports the view that there are interactions in the social world in that 
definite structures affect people in a reciprocal pattern (Proctor, 2005).Therefore these 
interactions should be measured objectively rather than from subjective inferences. Positivism 
seeks unbiased findings through value-free approach and ensures that the researcher is 
independent from the respondent (Malhotra & Birks, 2007).  
 
4.2 RESEARCH PURPOSE 
According to Robson (2002), there are three ways of conducting research which are descriptive, 
explanatory and exploratory. In social research Saunders et al., (2009) also agree that social 
research have three categories namely descriptive, explanatory and exploratory.  
Descriptive research systematically describes a phenomenon, situation or problem and usually 
asks the ‘what’ question (Rosenthal & Rosnow, 1991). McMillan and Schumacher (2014) argue 
that descriptive research describes what was observed and these vivid accounts can be expressed 
in words or numbers. 
 
Explanatory research emphasizes on studying and understanding specific situations or problems 
in order to explain the relationships among variables (Saunders et al., 2009).  This type of 
research aims at developing precise theory that can be used to explain the phenomena, which 
leads to generalization from the research. 
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Exploratory research is the discovery of ideas and insights and it is mostly useful when the 
subject of study is relatively new (Saunders et al., 2009). In the light this relatively new area, the 
likely sources of information is literature review which the current study has established and 
clarified. Hence the current study adopts explanatory or causal research to understand the 
switching behaviour of bank customers in Ghana. 
 
4.3 RESEARCH APPROACH 
Denzin and Lincoln (2000) claim that there are two main approaches used by researchers; 
quantitative and qualitative research. Quantitative research is primarily concerned with number 
and representativeness and has highly structured methods for data collection (Hair et al., 2009). 
Qualitative research on the other hand helps researchers to understand people, social and cultural 
contexts within their domain (Fielding, 2010). As a result of this approach, there is the need to 
have a close contact with small purposive sample over a period of time (Amaratunga et al., 2002; 
Reeves, et al., 2005). For the purposes of this study, quantitative approach is preferred as it 
involves large scale research containing large numbers and quantities.  
 
Quantitative Approach 
Dencombe (1998) postulate that, quantitative research aims to produce numerical data which is 
objective because they exist independently of the researcher and they are not results with too 
much involvement from the researcher. Quantitative research is the testing of objective theories 
by examining the relationship among variables (Creswell, 2014).  
 
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The quantitative approach has been related with the positivist or empiricist paradigm in the 
literature (Smith, 1983) and according to Rosenthal and Rosnow, (1991), quantitative research 
seeks to determine the extent of a problem or the existence of a relationship between aspects of a 
phenomenon by quantifying variations. Quantitative research often seeks to test to support or 
disprove a proposed relationship between two or more aspects of a phenomenon. Dencombe 
(1998) postulate that, quantitative research aims to produce numerical data which is objective 
because they exist independently of the researcher and they are not results with a lot of 
involvement from the researcher. 
 
In order to have a good quantitative study, the essential skills needed for the researcher as 
suggested by Saunders et al. (2009) are the ability to develop proper hypotheses, test them with 
proper statistical techniques, and interpret statistical information into descriptive information. 
 
4.4 RESEARCH DESIGN 
According to McGivern (2006), a research design essentially aims to structure the research to 
answer research problems as accurately and explicitly as possible. Kumar and Phrommathed 
(2005) also affirm that research design is adopted by researchers to answer questions validly, 
objectively and accurately. In view of this, the study used cross-sectional survey to seek 
responses from the population and Cooper and Schindler (2006) assert that cross-sectional are 
needed when the population is large. This approach is consistent with methodologies used in 
much of defection and complaint research (Nyarko, 2015; Rust & Zahonk, 1996; Singh & 
Howell, 1985; Zeithaml et al., 1996). 
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The study used the quantitative approach to enable the study test the extent to which the 
demographic variable influence customers’ ability to switch. The study used the structured 
questionnaire to elicit information from respondents in order to help the study identify and 
explain statistically, the demographic factors that either increase the relationship or otherwise the 
relationship between the independent and dependent variables. 
 
4.5 SOURCES OF DATA AND DATA COLLECTION METHODS  
According to Saunders et. al (2009), there are two sources of data for research; primary and 
secondary data sources. Malhotra (2007) explains that primary data consists of data that is 
originated by the researcher for the specific purpose of addressing the research problem whereas 
with secondary data is described as the collection of data for purposes other than problem a hand.  
The forms of data collection using primary sources are observations, experiments, surveys, and 
interviews and these are dependent on the research design adopted for the study (Ghauri & 
Grønhaug, 2005). On the other hand, secondary data encompasses data from sources such as 
government publications and censuses which provide information which may have been collected 
for other purposes (Malhotra, 2010). On the backdrop of the afore mention types of data, the 
study used primary sources of data as it was important to seeking responses directly from 
respondents of bank customers and how they switch. 
 
The study used structured questionnaire and it was self-administered to respondents. By this the 
researcher considered the survey method as an appropriate method because it gave opportunity to 
establish the relationship between the variables under consideration.  
 
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4.5.1 Questionnaire Design and Administration 
The developments of the questionnaire were based on the research objectives and questions 
which followed Malhotra and Birks (2007) outline for designing survey questionnaires. Pilot 
study was done to in order to ascertain the readability, and correct any ambiguity that might be 
present. The constructs were drawn based on literature which influenced the model in the current 
study. A draft of the questionnaire was developed following a pretest of fifteen (15) customers of 
different banks in Wisconsin University. Fink in Saunders et. al., (2007) recommends that a 
minimum of ten (10) members are for pre-test is ideal. Some merits of the pilot study are that it 
gives the researcher advance warnings of challenges that might arise from the research. 
  
A seven-point Likert scale was used to know the degree to which respondents agreed or otherwise 
to the statement posed. According to Schall (2003) adapted seven-point Likert scale is the ideal 
size compared to the five and ten-point scales. It ranged from 1 – strongly disagree to 7 – strongly 
agree. The questionnaire had different sections for the respondents which are; 
Section One (Price): This section establishes how pricing/tariff decisions affect customers of 
banks in their quest to wanting better services. It was adapted from Akwensivie et al, (2013), 
Narteh and Owusu-Frimpong (2011) and Clemes et al, (2007). 
Section Two (Technology): Every bank is supposed to have technology as part of its quest to 
delivering superior service experience, and the questions were meant to assess whether the 
presence of it or not can influence customers decision to switch. It was adapted from Narteh and 
Owusu-Frimpong (2011) and Almossawi, (2001)  
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Section Three (Service Quality): The quality of service a bank has on offer can make a 
customer decides to remain loyal or not and hence the questions were to make customers rate 
their level of agreement to the statement given. This scale was adapted from Clemes et al, (2007). 
Section Four (Advertisement): A lot of banks advertise their products and services but as to 
whether it influences decision by customers or not requires responses to the statements. This scale 
was adapted from Pirzada et al, (2014) and Clemes et al, (2007). 
Section Five (Involuntary Factors): The factors that move beyond the customer’s ability to 
transact business with a particular bank is what this section is focused on. Clemes et al, (2007). 
Section Six (Responses to Service Failure): The degree to which service firms like banks 
respond to complaints of customers and how concerns are addressed is the focus. Therefore 
customers are to rate their level agreement to the statements given. It was adapted from 
Akwensivie et al, (2013) and Clemes et al, (2007). 
Section Seven (Customer Satisfaction): This section provides statements to respondents on their 
level of satisfaction with the service experience of their respective banks. Therefore customers are 
to rate their level agreement to the statements given. It was adapted from Clemes et al, (2007). 
Section Eight (Service Product and Service Failure): The section looks at the products that 
banks have on offer. Therefore customers are to rate their level agreement to the statements 
given. It was adapted from Narteh and Owusu-Frimpong (2011) and Clemes et al, (2007). 
Section Nine (Degree of Switching):  Customers level of switching differs and this section seek 
to know what extent of switching behaviour amongst customers of banks. This scale was adapted 
from Clemes et al, (2007). 
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Section Ten (Demographic Data): This section sought to seek responses from customers based 
on their age, gender, income and educational status. This scale was adapted from Clemes et al, 
(2007). 
 
4.6 POPULATION, SAMPLE AND SAMPLING TECHNIQUE   
The population of the study refers to the elements that possess the information sought by the 
researcher which inferences are made (Malhotra, 2007). McDaniel and Gates (2008) explain 
sampling as “the process of obtaining information from a subset of a larger group” and by this 
sample population helps to focus the research and puts the findings into perspective. In view of 
this, the true population may not always be plausible hence Attewel and Rule (1991) suggest the 
use of theoretical sample. On the backdrop of this, the Ga East Municipal was chosen for the 
study because that is where most banks are found (Composite Budget, 2012). These locations 
include Taifa, Dome, Kwabenya, Haatso, Agbogba, Ashongman and Madina. According to the 
Housing and Population Census (2010) claim that there are 147,742 inhabitants in these said 
areas however the number is expected to increase in the next population census. The banks 
located in these areas include Ecobank, UT Bank, GT Bank, StanChart Bank, Barclays and 
Prudential Bank and customers of these banks were used for the study. Only one branch of the 
banks was used for the study despite UT Bank and Ecobank having more than one branch and the 
study sampled customers who were exiting from the banks only.  
 
The sample size used for the study is 329 Crouch (1984) recommends that “minimum sample 
sizes for quantitative consumer surveys are of the order of 300 to 500 respondents.” This makes 
the sample size ideal for the study. Again, Hair et al. (2006) consider sample sizes of 100 and 
above appropriate for quantitative studies. Malhotra and Birks (2007) are of the view that, large 
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sample sizes allow for the effect of randomness and reduce chances of errors as the sample size 
increases. 
 
For the purposes of the study, convenience sampling method was employed which is a non-
probability sampling technique. Malhotra (2010) asserts that non-probability sampling techniques 
are not necessarily representative of the entire population but generalizations may still be made 
about the population. An example of non-probability sample includes quota, purposive, snowball 
and convenience sampling. 
 
4.7 ETHICAL CONSIDERATION  
Confidentiality of responses is highly adhered to as well as the code of ethics that underpins the 
APA (2002) format. The researcher sought permission from the respondent’s which made it possible to 
conduct the research. Bank customers who were less than 18 years were excluded from the study because 
the researcher was not interested in that segment.  The principle of confidentiality which explains that 
information obtained from research participants should be kept secret was also adhered to. 
 
4.8 CHAPTER SUMMARY 
The discussions described above have adequately established the research design employed in the 
study. This section explained the methods such as questionnaire design, type of respondents, and 
analysis of data. The next chapter presents the analysis of the empirical data collected. 
 
 
 
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CHAPTER FIVE 
DATA ANALYSIS AND DISCUSSION OF FINDINGS 
 
5.1 PROFILE OF THE RESPONDENTS 
Table 1 presents the profile of the sampled respondents. They were profiled according to gender, 
age, educational and income level. The results reveal that there were 46.5% males and 53.5% 
females who took part in the study. Regarding age, the lowest numbers of respondents (3.6%) 
were above 55 years followed by 8.5% who were in the age range of 46-55 years. However, 
33.1%, 34.7% and 20.1% were within the age brackets of 18-25, 26-35 and 36-45 respectively; an 
indication that respondents within 26-35 years were the dominant age group within the sample. 
With respect to educational qualification, majority of the respondents (56.8%) had HND or 
Bachelor’s degree whereas 19.5% and 16.4% had professional and postgraduate qualifications 
respectively. What’s more, 6.4% had up to SHS qualification and 0.9 indicated other 
qualifications. These therefore signify the ability of the sampled respondents to comprehend and 
provide accurate responses to questions. Furthermore, the income levels signify 38% earn 
monthly incomes between GHC500-GHC999, 34% earn between GHC1000-GHC1,999, 12.5% 
earn between GHC2,000-GHC2,999 with 15.5% earning GHC3,000 and above. 
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Table 5. 1 Profile of Respondents 
Characteristics Measures Sample composition 
n Percentage 
Gender Male 153 46.5 
 Female 176 53.5 
    
Age (in years) 18-25 109 33.1 
 26-35 114 34.7 
 36-45 66 20.1 
 46-55 28 8.5 
 55+ 12 3.6 
    
Educational level JHS/SHS 21 6.4 
 Professional 64 19.5 
 HND/Bachelor's Degree 187 56.8 
 Post Graduate Degree 54 16.4 
 Others 3 .9 
    
Income level 100-999 125 38.0 
 1000-1999 112 34.0 
 2000-2999 41 12.5 
 3000-3999 26 7.9 
 3999+ 25 7.6 
n = 329 
 
5.2 DESCRIPTIVE STATISTICS 
This study heeded the suggestion of scholars (Malhotra and Birks, 2007; Hair et al., 2010; 
Pallant, 2011) to first subject research (involving human participants) data to descriptive analysis 
(such as mean, standard deviation, range of scores, skewness and kurtosis) before any further data 
validation and analysis. The table below displays the descriptive statistics of the variables used in 
the survey instrument mainly based on mean and standard deviation results of the scale variables. 
Since the questionnaire were scaled 1-7 (from strongly disagree to strongly agree with 3 being 
neutral), the mean values here indicate the extent to which the respondents disagreed or agreed 
with the statements in the questionnaire. From the table the highest mean was 5.88 shared by (The 
bank staff do not make any extra effort to solve problems) and (I am not satisfied) while the 
lowest was 3.50 (The design of the competing bank’s ATM card influences my decision). The 25 
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variables displayed in Table II below represented the components of the constructs depicted in the 
conceptual framework for the study. 
 
Table 5. 2 t test (descriptive statistics) 
Variables CODE Mean s.d 
The bank charges high fees PR1 5.78 1.74 
The bank charges high interest for loans PR2 5.59 1.78 
The bank charges high interest for mortgages PR3 5.30 1.85 
The bank provides high interest rates on savings accounts PR4 4.20 2.48 
The bank does not have ATM TECH1 5.13 2.25 
The bank does not have internet banking TECH2 4.70 2.10 
The bank does not have credit and debit cards TECH3 5.00 2.02 
The bank is not networked TECH4 5.57 1.92 
The bank does not offer a wide range of service products SQ1 5.35 1.85 
The service product offered do not satisfy my specific needs SQ2 5.47 1.93 
The bank’s consulting service does not satisfy my specific needs SQ3 5.37 1.92 
The competing bank’s advertising content influences my decision AD1 4.41 2.13 
The signs or billboards of the competing bank influences my AD2 3.56 2.07 
decision 
The design of the competing bank’s ATM card influences my AD3 3.50 2.17 
decision 
The principal bank branches in my area are closed IF1 4.61 2.10 
My principal bank is not in the new geographic location I moved to IF2 4.78 2.01 
My bank is not my employers’ salary bank IF3 3.95 2.29 
The bank does not respond to service failures SF1 5.77 1.68 
The Bank staff do not make any extra effort to solve problems SF2 5.88 3.97 
The bank is slow in rectifying the problem SF3 5.78 1.53 
I am not satisfied SC1 5.88 1.65 
The bank’s promise does not meet my expectation SC2 5.64 1.64 
The services provided by my bank does not meet my needs SC3 5.74 1.63 
The bank does not offer a wide range of service products SP1 5.16 1.76 
The service products offered does not satisfy my specific need SP2 5.57 1.72 
 
 
 
 
 
 
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5.3 CONFIRMATORY FACTOR ANALYSIS 
Granted that scale measures were adopted from literature, a confirmatory factor analysis (CFA) 
was conducted on the scale variables. Three variables (PR4, IF3 and SF2) were dropped during 
the CFA because their loadings were less than the threshold value of 0.5. Table 3 presents the 
standardized loadings and the t-value of each variable indicator. All indicators had significant 
standardized loadings of ρ ≤ 0.001, and t-values of the individual indicators ranged from 5.263 to 
13.721 (Gerbing and Anderson, 1988). The reliability and validity of the measures represent the 
constructs being evaluated and assess the psychometric properties of scaled measures (Fornell 
and Larcker, 1981). Composite reliabilities gave an indication of the internal consistency, which 
means that the measures consistently represent the same latent construct. The composite construct 
reliability of each construct ranged from 0.668 (Response to service failures) to 0.818 
(Satisfaction with services), which meets the acceptable criteria (Fornell and Larcker, 1981; Hair 
et al., 2006). The variance-extracted estimate measures the amount of variance captured by a 
construct in relation to the variance due to random measurement error. The variance extracted 
scores of the constructs ranged from 0.503 (Response to service failures) to 0.600 (Satisfaction 
with services), which suggests adequate convergent validity (Bagozzi and Yi, 1988; Fornell and 
Larcker, 1981). All eight constructs were tested for the goodness of fit and validation of scales of 
the measurement of the constructs by the CFA. The model fit indices in the measurement model 
exhibited good fit on the data (Χ2 = 420.024, df = 223, GFI = .905, CFI = .929, RMSEA = .052, 
PCLOSE = .332). These indices meet the acceptable criteria for the overall model fit of the 
sample group suggested by Kline (2005). 
 
 
 
 
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Table 5.3 Confirmatory factor analysis 
Constructs and Alphas Items Loading t-value AVE Composite 
reliability 
Price (α = 0.784) PR1 .588 9.985 .571 .796 
 PR2 .834 12.213   
 PR3 .819 Fixed   
Technology (α = 0.784) TECH .778 10.957 .508 .784 
1 
 TECH 9.825  
2 .663  
 TECH
3 .657 9.765  
 
 TECH
4 .659 Fixed  
 
Service Quality (α = 0.779) SQ1 .639 10.805 .557 .788 
 SQ2 .844 13.721   
 SQ3 .742 Fixed   
Advertisement (α = 0.742) AD1 .524 8.459 .518 .756 
 AD2 .875 10.063   
 AD3 .716 Fixed   
Involuntary factors (α = 0.647) IF1 .576 5.263 .513 .671 
 IF2 .833 Fixed   
Response to service failures (α = 0.655) SF1 .768 9.828 .503 .668 
 SF3 .645 Fixed   
Satisfaction with services (α = 0.818) SC1 .777 13.377 .600 .818 
 SC2 .775 Fixed   
 SC3 .772 13.309   
Service products (α = 0.719) SP1 .723 10.648 .563 .720 
 SP2 .777 Fixed   
Χ2 = 420.024, df = 223, GFI = .905, CFI = .929, RMSEA = .052 
 
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5.4 DISCRIMINANT VALIDITY 
To investigate the multicollinearity of constructs, an assessment of discriminant validity is 
conducted. Discriminant validity compares the variance-extracted estimates of the measurements 
with the square of the parameter estimate between the measurements. Table 4 shows the means, 
standard deviations, and correlation values among the eight independent constructs. The means 
ranged from 3.82 (Advertisement) to 5.77 (service failure), and the standard deviations from 1.39 
to 1.77. The correlations among the constructs ranged from 0.007 to 0.568. The lowest correlation 
was that between service failure and advertisement (r = 0.007), and the highest was that between 
satisfaction and service quality (r = 0.568). The results demonstrated the strength and direction of 
relationships among the factors. This was carried out to cater for multicollinearity and to confirm 
that the factors are distinct from each other and not measuring the same attributes. 
 
Table 5. 4 Descriptive statistics and correlations 
 Mean s.d 1 2 3 4 5 6 7 8 
Price 5.56 1.50 1        
Technology 5.10 1.62 0.325 1       
Service quality 5.39 1.58 0.343 0.546 1      
Advertisement 3.82 1.72 0.037 0.174 0.065 1     
Involuntary 4.69 1.77 0.185 0.303 0.302 0.137 1    
Service failure 5.77 1.39 0.298 0.356 0.480 0.007 0.327 1   
Satisfaction 5.76 1.40 0.280 0.371 0.568 0.021 0.320 0.511 1  
Service product 5.36 1.54 0.242 0.427 0.476 0.121 0.317 0.515 0.459 1 
 
 
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5.5 ANOVA 
A one-way analysis of variance (ANOVA) was performed to test if there were any differences in 
demographic characteristics and the likelihood to switch banks. The results from Table 5 indicate 
that there were no significant differences among the respondents in relation to their gender, 
education, income levels and the likelihood to switch. However, there were significant 
differences among the respondents in their likelihood to switch banks when age was controlled 
for (F = 5.854, p < 0.005). This suggests that age is a potential moderator of the relationship 
between the independent variables and the dependent variable. 
 
Table 5. 5 ANOVA results 
 F-value Significance 
Gender 0.093 .761 
Age 5.854 .001 
Education 2.684 .052 
Income  1.106 .354 
 
 
5.6 HYPOTHESES TESTING USING LOGISTIC REGRESSION 
To assess the impact of the switching factors on predicting the likelihood of a consumer’s actual 
switch, a logistic regression was estimated. The switching factors were used as the predictor 
variables while the dependent variable was likelihood to switch (a binary variable computed from 
the dependent variable “switching”). Since the rating scale was anchored 1 to 7, all responses 
from neutral and below were treated as a dummy of no switching while those above were 
recognized as evidence of switching. The full model containing all predictors was statistically 
significant, χ2 = 132.602, df = 6, P value < 0.001, indicating the model is able to distinguish 
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between the likelihood to switch services or not. On a whole, the model explained between 28.6% 
(Cox and Snell R2) and 41.7% (Nagelkerke R2) of the variance in switching effects, with an 
overall predictive accuracy of 81.3% on the cases in the data. 
 
As shown in Table 6, the Wald statistics reveal three out of the six switching factors – satisfaction 
(Wald = 17.511, p value < 0.001), price (Wald = 10.861, p value < 0.005) and service issues 
(Wald = 8.710, p value < 0.05) – made statistical significant contribution to the model. 
Controlling for the other switching factors, the odds ratio [Ex(B)] results in each of the significant 
cases show that for a unit increase in dissatisfaction with services provided, bank consumers are 
almost three times (2.874) more likely to switch their service providers. In a similar manner, a 
unit increase in bank charges (price) has a 1.759 times more likelihood to cause consumers to 
switch banks while from a unit increase in problems related to service delivery (failures, quality, 
products)  the bank customers are 1.916 times more likely to switch banks. Although technology 
issues could effect 1.445 times likelihood for customers to switch, it was statistically not 
significant (Wald = 3.415, p value > 0.05). 
 
  
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Table 5. 6 Logistic regression on bank service switching 
Switching factors Std. 
B Error Wald Sig. Ex(B) 
Constant -5.428 .663 16.756 .000 .001 
Price .630 .070 10.861 .001 1.759 
Technology .357 .088 3.415 .056 1.445 
Advertisement .082 .085 .931 .335 .085 
Involuntary .066 .072 .839 .360 .068 
Less satisfied 1.134 .109 17.511 .000 2.874 
Service issues .574 .142 8.710 .004 1.916 
 
5.7 MODERATING EFFECT OF CUSTOMER AGE 
With reference to Table 5.5 showing gender (.761), education (.052) and income (.354) not 
significant, there are possible variations on likelihood to switch with respect to age of the 
customers and a series of sorted models were examined to verify the group differences. 
Consumers were clustered into two groups – those within the ages of 18 to 35 years, and those 
above 35 years. The results of these assessments are illustrated in Table 7. Among the younger 
age group (18-35 years), three switching factors – Technology (Wald = 10.207, p value < 0.001), 
Advertisement (Wald = 9.056, p value < 0.005) and price/charges (Wald = 7.919, p value < 0.05) 
– made statistical significant contribution to the model. However, among the older age groups 
(above 35 years), three switching factors – service issues (Wald = 14.018, p value < 0.001), 
satisfaction (Wald = 11.046, p value < 0.05) and price (Wald = 7.133, p value < 0.05) – made 
statistical significant contribution to the model. The ongoing results present some interesting 
observations for discussions. 
 
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Table 5. 7 Logistic regression on bank service switching 
Switching factors Std. 
B Error Wald Sig. Ex(B) 
Age 18 – 35 years      
Price .437 .299 7.919 .016 1.147 
Technology .647 .103 10.207 .000 1.954 
Advertisement .280 .088 9.056 .002 1.322 
Involuntary .042 .084 .256 .613 .873 
Satisfaction .317 .124 2.889 .051 1.290 
Service issues .140 .164 .728 .394 .851 
      
Ages above 35 years      
Price 1.065 .177 7.133 .021 1.437 
Technology .006 .188 .001 .973 .994 
Advertisement .143 .123 1.349 .245 1.154 
Involuntary .007 .167 .002 .968 1.007 
Satisfaction .766 .260 11.046 .006 1.767 
Service issues 1.061 .330 14.018 .000 1.936 
 
 
 
 
 
 
 
 
 
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5.8 DISCUSSION OF FINDINGS 
The study was done to investigate the seven (7) predicted relationships between drivers of 
customer switching behavior and dimensions of switching behavior. Also, eight predicted 
relationships between demographic variables and dimension switching behavior. The hypotheses 
stated were tested and the data was analyzed using Logistic Regression analysis. 
 
Firstly, the study reported that demographic variable- age (young and old group) significantly 
accounted for the variation in the factors that influence an individual’s decision to switch from 
one bank to another. Among the younger age group (18-35 years), three switching factors – 
Technology, Advertisement, and price/charges significantly contributed to their decision to 
switch from one bank to another.  
 
Secondly, it is reported that the older age group (above 35 years) considered three factors – 
service issues, satisfaction and price to account for their decision to switch from one bank to 
another. It was reported that the participants of the young group and the older group considered 
the factor – price to significantly influence their decision to switch. On the contrary, none of the 
age groups considered involuntary switching to influence their decision to leave one bank for 
another. Additionally, factors such as advertisement, service issues and satisfaction did not 
influence the decision of the participants  in the young age group to switch whilst  factors such as 
drivers of switching- technology and advertisement didn’t influence the older participants 
decision to switch. 
 
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Finally, with the exception of age, other demographic variables gender, education and income did 
not significantly influence the participants’ decisions to switch. Therefore, it was reported that 
hypothesis one, two, three, four, five, six, seven and eight were supported whilst hypothesis nine, 
ten and eleven were not supported. The findings of this current study were supported by two 
theories reviewed in the literature (Social Exchange Theory and Demographic Transition Theory) 
and studies in the literature (Nyarko, 2015; Antwi-Boateng, et al., 2013; Nartey & Owusu-
Frimpong, 2011; Zhang, 2009; Zhang & Prybutok, 2005;  Keaveney, 1995; Kristensen et al., 
1992). 
 
The discussion of the findings commences with a relation of the theories stated to the findings of 
reported.  
The social exchange theory states that individuals have the freedom to make decisions by 
analyzing the costs and benefits attached to the choices they make. The theory further states that 
people are hedonistic and try to maximize rewards whilst minimizing costs. Thus it is expected 
that customers make decisions concerning banking services on the bases of choosing a service 
that offer superior value. Again, service firms like banks that do not improve and innovate on 
products are likely to lose customers because the customer has an insatiable quest to look for 
better and improved service delivery. 
The demographic transition theory was developed by Thompson (1929) and states that as people 
progress from one developmental stage to another their preferences, expectations and interests 
change with time. In view of this, the theory is the most suitable for understanding how people 
with demographic characteristics such age, education and income can display a switching attitude 
from one service to other when their preferences and expectations change over time. 
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In relating the findings of the study, both theories support the observed findings of the study in 
that, the social exchange theory justifies reasons why  both old and young group customers 
considered  factors such as price as a determinant of switching behavior in banking firms. The 
Social exchange theory also supported separate determinant factors of the individual age groups. 
That is technology and advertisement for the young age group and service issues and satisfaction 
of the older group. Therefore if both age groups consider these factors to more effective and 
rewarding in exchange for their loyalty and retention behavior to the banks then they will not 
switch to other banking firms. 
 
Additionally, the demographic transition theory supports the variation in the determinant factors 
that influence both the old and young age groups to switch. Thus as the young age group  
progress to an older age  the factors  that influence their decision to switch  changes from  
technology, advertisement  to service issues, satisfaction but  price remains a constant factor. 
 
5.9 RELATIONSHIP BETWEEN DRIVERS OF SWITCHING BEHAVIOR, 
DEMOGRAPHIC VARIABLES AND DIMENSIONS OF SWITCHING BEHAVIOR 
The hypothesized relationships between drivers of switching and revealed that the younger age 
group (18-35 years) considered three switching factors – Technology, Advertisement, and 
price/charges to significantly influence to their decision to switch whilst the older age group 
(above 35 years) considered three factors – service issues, satisfaction and price to account for 
their decision to switch from one bank to another.  
 
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In defining the drivers of switching reported from the study, firstly, price is what is given up or 
sacrificed to have a product or a service (Zeithaml, 1988). Secondly, advertising is also defined as 
the promotion of products or services of a brand or a company for the purposes of customers 
getting to know about the product (Nawaz, Javed & Asab, 2014). Thirdly, service issues as “the 
degree of discrepancy between customer’s normative expectation for the service and their 
perceptions for the service performance” and issues that arise when dealing with service failures 
or conflict situations (Vishal, 2014; Zikiene & Bakanauskas, 2009). Finally, customer satisfaction 
is a term that measures how products and services supplied by a company meet or exceed 
customer expectation (Kotler & Armstrong, 2012).   
 
Therefore, in respect of price, the report was consistent with previous findings by Keaveney 
(1995) who reported that customers switch services due to poor pricing perceptions and thus 
unfavourable pricing may have a direct impact on customer’s intention to switch. Similarly, 
Nyarko (2015) also concluded that, bank charges are very crucial in determining the switching 
patterns of customers. Studies by Nartey and Owusu-Frimpong (2011) also revealed that price has 
a weak relationship with switching behavior which means that to some extent there is a 
relationship between price and switching behavior. This claim is also shared by some researchers 
who reported that price is the most important factor in switching decisions and that customers 
consider the charges of the bank before patronising the service (Antwi-Boateng, et al., 2013; 
Chigamba & Fatoki, 2011; Colgate & Hedge, 2001).  
 
 In terms of Advertising, the report was consistent with previous findings of Zhang (2009) who 
found a significant relationship between advertising and switching behaviour, and supported the 
view that it remains one of the cardinal factors in predicting customers’ ability to switch. This is 
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also consistent with studies such as Dunn (1995) and Cengiz et. al., (2007). The study however, 
was not consistent with Clemes et al, (2010) which found a negative relationship between 
effective advertising competition and switching behaviour 
Next, is the observed relationship between technology and switching which is consistent with 
Nartey and Owusu-Frimpong (2011) who found out that there was a significant relationship 
between technology and customers intention to switch from one service to another.  
The finding was also consistent with previous studies who reported that service firms like banks 
that are not technologically innovative in products delivery may cause customers to switch 
(Zhang & Prybutok, 2005; Bauer et al., 2005).  
 
Additionally, the observed relationship between customer satisfaction and switching behavior 
was consistent with studies which reported that customer satisfaction is worthy of attention as it 
further enhances the long term benefits the firm gains as a result of having superior products 
tailored to consumers (Cudjoe, Anim & Nyanofio 2015; Kristensen et al., 1992; McColl-Kennedy 
& Schneider, 2000; Zeithaml et al., 2006).  
 
In terms of the observed relationship between services issues and switching behavior was 
consistent with studies by Ogilvie (1997) and Kiser (2002) who reported that products offered by 
banks influences customers’ ability to switch. Clemes et al. (2007) also reported that a high level 
of service quality is important in order to prevent bank customers from switching. Similarly, 
Safakli (2007) also reported that superior service quality has a positive relationship with customer 
switching behavior. 
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Furthermore, reports from previous studies reviewed in the literature were consistent with the 
observed relationship between service quality and switching behavior (Nyarko, 2015; 
Chakravarty, et al., 2004; Gerrard & Cunningham, 2004; Colgate & Hedge, 2001)  
 
In terms of the influence of the demographic variable on the determinants of switching behavior, 
it was reported that age significantly influenced the relationship between the drivers and 
dimensions of switching behavior. This finding was consistent with Nartey and Owusu-Frimpong 
(2011) who reported that age has the tendency to influence consumers switching behaviour, 
though the study didn’t emphatically confirm the extent to which it affects switching. Also, this 
finding is also supported by (Clemes et. al., 2007; Gautam & Chandhok, 2011; Morgan, 2012) 
who reported that younger customers are most likely to switch banks. 
On the contrary, the observed relationship between the demographic variable thus age on the 
determinants of switching behavior was inconsistent with other studies (Effah-Bediako, Deh & 
Asuamah, 2013; Nimako & Nyame, 2015), who have dissenting views that age does not 
significantly affect switching behaviour. Additionally, it was reported that both age groups 
significantly influenced some determinants of switching and this finding was inconsistent with 
Clemes, Gan, Zhang (2010) who reported that the young age group have higher propensity to 
switch banks compared to older ones. However no relationship was reported for variables such as 
involuntary switching and customer’s switching behavior and this finding is inconsistent with 
studies that observed a significant relationship between involuntary switching and switching 
behavior (Khan et. al., 2010, Taylor et al., 2009; Ganesh et. al., 2000; Fried & Smith, 1993). 
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CHAPTER SIX 
SUMMARY, CONCLUSION AND RECOMMENDATION 
 
6.0 INTRODUCTION 
The research aim was to assess the drivers of switching behavior on banks in Ghana and to know 
the extent to which these drivers influence consumers’ ability to switch from one service provider 
to another. This chapter focuses on the summary and conclusion of the findings presented in 
chapter five. Again, the study makes recommendations and gives direction for future research. 
 
6.1 SUMMARY OF STUDY 
The research was carried out to ascertain the potential factors that make customers to switch. Of 
the total 350 questionnaires, 329 responded to the various items on the scale which gave 94% 
recovery rate. The study used the convenience sampling method to solicit responses from the 
respondents on the drivers of switching behavior. The objectives of the study primarily were to 
assess the demographic characteristics and the factors that cause customers to move from one 
service provider to another. 
 
Theories and factors that affect consumer behavior were researched in the literature to know the 
potential causes and the reasons thereof. A lot of studies (Abawiera et al., 2014; Asab et al., 2014; 
Boohene et al., 2013; Clemes et al., 2010; Cohen et al., 2007; Gurjeet & Mahajan, 2012; Kura et 
al., 2012; Narteh & Owusu-Frimpong, 2011; Okoe et al, 2013; Nimako & Mensah, 2014; 
Subramaniam & Ramachandran, 2012; Vishal, 2014) were reviewed on the banking sector from 
both developing and developed countries. The study revealed seven factors that make customers 
to switch banks and they are; price, technology, service quality advertisement, involuntary 
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switching, customer satisfaction and service issues. These factors however were moderated by 
demographic factors such as age, gender, education and income. A conceptual framework was 
developed to fully understand the concepts and how switching occur holding some variables 
constant. 
The data was analysed with logistic regression to predict the likelihood of a consumer to switch. 
The switching factors were used as the predictor variables while the dependent variable was 
likelihood to switch.  
Confirmatory factor analysis was carried out and three of the variables were dropped during the 
CFA due to their loadings being less than 0.5. However, all the indicators had significant 
standardized loadings of ρ ≤ 0.001, and t-values of the individual indicators ranged from 5.263 to 
13.721 (Gerbing and Anderson, 1988). Again, the model fit indices exhibited good fit on the data 
(Χ2 = 420.024, df = 223, GFI = .905, CFI = .929, RMSEA = .052, PCLOSE = .332). These 
indices meet the acceptable criteria for the overall model fit of the sample group suggested by 
Kline (2005). 
 
Again, discriminant validity was conducted to investigate the multicollinearity among the 
relationships. It turned out that the factors were distinct from each other and that the items did not 
measure the same characteristics.  
To know whether there were differences in demographic characteristics, it was prudent to conduct 
a one-way analysis of variance (ANOVA). The result did not indicate any significant differences 
and the likelihood to switch banks. However, there were significant differences among the 
respondents ability to switch banks when age was controlled (F = 5.854, p < 0.005). This makes it 
known that age is a potential moderator between the independent and dependent variables. 
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It is important to note that, the study reported that demographic variable- age (young and old 
group) significantly accounted for the variation in the factors that influence an individual’s 
decision to switch from one bank to another.  
Among the younger age group (18-35 years), three switching factors – Technology, 
Advertisement, and price/charges significantly contributed to their decision to switch from one 
bank to another. Moreover, it is reported that the older age group (above 35 years) considered 
three factors – service issues, satisfaction and price to account for their decision to switch from 
one bank to another. 
 
6.2 REVISED CONCEPTUAL FRAMEWORK 
From the study, it is evident that the demographic factor that influences consumers’ ability to 
switch is only age. This means that income, education, and gender do not have any bearing on the 
relationship between the drivers of switching behavior and the intention to switch. The variable 
age was significant when it was held constant and hence the proposed model; 
 
Independent Variables      Moderator Variable        Dependent Variable 
 Price Age 
 
Technology 
 Switching Behaviour 
Advertisement *Likely 
 *Unlikely 
 Satisfaction 
 
Service Issues 
 
Figure 3. Revised framework 
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S6.3 CONCLUSION 
The study makes it clear that the factors that makes switching possible is age and that, as 
individual ages, preferences also change hence expectations also change. Price is a constant 
variable among the two sets of age groups thus the young and the old. It also implies that bank 
charges or tariffs plays a key role in customers switching intentions and that the lower bank 
charge, the higher the loyalty to the bank. Pricing decisions can greatly affect a firm’s marketing 
efforts when not properly controlled. Besides, younger and older customers are price sensitive 
hence pricing decisions of banks must be thoroughly addressed in order to ensure continuous 
patronage of services. Customers are rational beings and therefore would prefer to buy service 
products that offer fewer prices but utmost value.  
 
Moreover, addition, technology is also a key feature in ensuring that customers do not switch. 
The technology introduced by the bank like ATM, internet banking and other services can go a 
long way to improving the fortunes of the firm. From the study the millennials enjoy technology 
compared to the older segment of the customers. It is notable that factors that make customers to 
switch from one bank to another are dependent of individual’s experiences and this according to 
the study young customers between the ages of 18 to 35 years are interested in the technology 
advancement of the bank. Besides, these age groups are innovative and trendy and would like to 
bank on online platforms like internet banking and therefore banks that do not offer technological 
services are bond to lose the customers. 
 
Again, advertisement of service product is very crucial for millennials and therefore, service 
firms ought to devote resources to advertisement. To buttress this point, advertising products and 
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services makes potential customers know and understand what is on offer and failure to recognise 
the need can cause customers to switch. 
The older age group of 35years and above are primarily influenced by satisfaction and service 
issues. This implies that when there is a failed service, customers in this age group are most likely 
to switch t another bank. The older segments are influenced by the satisfaction that I derived out 
of the service rendered. 
 
From the study, a change in price will make customers switch 1.759 times which means that price 
is very volatile to the needs of the customer. A change in price or tariffs will result in customers 
switching and this similar to satisfaction. A customer who is dissatisfied will be 17.511 times 
likelihood to switch banks and this is evident from the study. Satisfaction is a key variable when 
customers are involved as it is the driving force behind the success of firms. Wald statistic 
showed that satisfaction was the highest when it comes to the variables that will make customers 
switch. This makes it insightful for firms to consider the satisfaction levels of customers a priority 
in order to ensure lifetime value of the customer. 
 
Marketing efforts by banks should ensure to take into cognisance the different age groups in order 
to offer tailored products at them. This is because the age differences of the customer determines 
the needs set which is vital to the service firm to know.  
 
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6.4 RECOMMENDATIONS 
The study discovered interesting findings that affect the way customers respond to changes in 
their expectation and that when services rendered go sour or fall below expectation, customers do 
react quickly hence the following recommendations. 
 
6.4.1 Practice 
The implication for practice is crucial as it forms the basis for the survival of firms in Ghana. 
Customers are rational beings and therefore would resort to best way of meeting their needs 
despite the challenges that may arise as a result of it. Banks in Ghana must recognize that 
customers switch as a result of a dissatisfied need and that the any negative change in the banks’ 
operations be it poor network or increase in price will result in switching. It is also evident that 
the study revealed the issue of age as a primary demographic construct as a force to reckon with 
when designing products for the banks. Younger customers’ expectation of service delivery is 
different from the older age group which implies that different marketing efforts are required in 
targeting them. Mass marketing may not yield the needed expectation as the issues of concern 
aren’t the same and that firms must note this to ensure maximum benefits from the customers. 
Again, when service firms advertise its products, other customers from other banks also see the 
offers available and may want to make a decision to switch. Despite the importance of advertising 
to service firms, not all customers are influenced by it and thus budget towards the creation of 
campaigns must be reconsidered so as to channel it into the other segment of the market.  
 
Technological advance is on the increase and service firms like banks that do not incorporate 
technology its operation will fizzle out. Bank products like internet banking and ATM service 
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require advancement in technology and therefore the increase investment in this area would result 
in satisfaction and also yield positive word of mouth.  
Managers and consultants may find this research useful in shaping their organizational aspirations 
by taking into consideration the key highlights of this study. It is interesting to note that switching 
only happens when alternatives are available and that when switching cost is increased customers 
defection will reduce.   
 
6.4.2 Theory and Future Research 
The drivers of switching behavior in developing countries have been considered over the period 
and the factors that make customers switch are based on demographic characteristics such as age, 
gender, income and education. This notwithstanding this, the study showed that only age has a 
propensity to make customers switch and this is very profound in extending the marketing 
literature on switching behaviour.  Besides, the study can conclude that younger and older age 
groups are affected by different drivers of switching behaviour with younger age groups being 
sensitive to price, technology and advertisement. The older age groups are also conscious of 
price, satisfaction and service issues which are vital for the survival of banks by offering service 
products tailored to targeting market segments.  
 
The current study has used theories in sociology into marketing that makes the literature rich and 
interesting; social exchange theory posits that individuals are rational beings and that decisions 
are made to reflect the circumstances available. In addition, demographic transition theory was 
also used to explain the preferences that age has on customers. By this, it implies that individual’s 
preferences do change as they grow which was evident in the current study. Little research has 
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been explored on these two theories in relation to switching behaviour and makes the current 
study contribute to literature by extending the knowledge frontiers.  
 
Future research could be done to consider a longitudinal study in order to ascertain the loyalty of 
customers who have switched service providers. This will be interesting to know how the 
customers who have already switched are faring with their current banks. Moreover, the drivers 
of switching could also be expanded to ascertain the most important factor or variables that 
greatly impacts on customers’ propensity to switch banks. Again, the sample size could also be 
increased to determine whether there will be variations in the demographic factors. Finally, the 
study must be conducted to in different geographical setting to ascertain if there will differences 
in the results. 
 
 
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APPENDIX 
 
 
 
 
 
 
 
 
 
 
UNIVERSITY OF GHANA BUSINESS SCHOOL, 
LEGON DEPARTMENT OF MARKETING AND 
ENTREPRENUERSHIP 
 
 
 Dear Respondent, 
This study is being conducted by an M.Phil. Marketing Student of the University of Ghana 
 Business School on the topic “Switching Behaviour among Bank Customers in Ghana”. 
I humbly request you to fill the questionnaire below by ticking the most suitable option that 
applies to you. Please be informed that all the information that would be obtained through 
this questionnaire administration is purely for academic purposes only. 
 
 
A. SWITCHING BEHAVIOUR  
 
 Please CIRCLE how strongly you agree or disagree with each of the following statements on a scale of 
1 to 7. 1-you strongly disagree, 7-you strongly agree. 
 
   Strongly     Strongly 
  Price Disagree     Agree 
             
  I will switch to another bank if...           
1. The bank charges high fees  1 2 3 4 5 6 7  
2. The bank charges high interest for loans  1 2 3 4 5 6 7  
             
3. The bank charges high interest for mortgages  1 2 3 4 5 6 7  
4. The bank provides high interest rates on savings accounts  1 2 3 4 5 6 7  
             
  Technology           
             
  I will switch to another bank if...           
5. The bank does not have ATM  1 2 3 4 5 6 7  
6. The bank does not have internet banking  1 2 3 4 5 6 7  
             
7. The bank does not have credit and debit cards  1 2 3 4 5 6 7  
 8. The bank is not networked  1 2 3 4 5 6 7  
 Strongly     Strongly 
 
 Service Quality Disagree     Agree 
 
              
 I will switch to another bank if...            
 
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9. The bank does not offer a wide range of service products            
 
 (e.g. loans, mortgages, credit cards, online and phone            
 
 banking, direct bills payment services)  1  2 3 4 5 6 7  
 
11. The service product offered do not satisfy my specific     
 
 needs  1  2 3 4 5 6 7  
 
12. The bank’s consulting service does not satisfy my specific     
 
 needs  1  2 3 4 5 6 7  
 
            
 Strongly    Strongly 
 
 Advertisement Disagree           Agree  
 
 I will switch to another bank if...            
 
13. The competing bank’s advertising content influences my            
 
 decision  1  2 3 4 5 6 7  
 
14. The signs or billboards of the competing bank influences            
 
 my decision  1  2 3 4 5 6 7  
 
15. The design of the competing bank’s ATM card influences my           
 
 decision  1  2 3 4 5 6 7  
 
 Strongly     Strongly 
 
 Involuntary Factors Disagree      Agree 
 
              
 I will switch to another bank if...            
 
16. The principal bank branches in my area are closed  1  2 3 4 5 6 7  
 
              
17. I move to a new geographic location and my principal            
 
 bank is not in the area  1  2 3 4 5 6 7  
 
18. My bank is not my employers’ salary bank  1  2 3 4 5 6 7  
 
 Strongly     Strongly 
 
 Responses to service failure Disagree      Agree 
 
              
 I will switch to another bank if...            
 
19. The bank does not respond to service failures  1  2 3 4 5 6 7  
 
              
20. The Bank staff do not make any extra effort to            
 
 solve problems  1  2 3 4 5 6 7  
 
21. The bank is slow in rectifying the problem  1  2 3 4 5 6 7  
 
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  Strongly     Strongly 
 
 Customer Satisfaction Disagree     Agree 
 
             
 I will switch to another bank if...           
 
22. I am not satisfied  1 2 3 4 5 6 7  
 
23. The bank’s promise does not meet my expectation  1 2 3 4 5 6 7  
 
24. The services provided by my bank does not meet my needs  1 2 3 4 5 6 7  
 
             
 Strongly     Strongly 
 
 Service Products Disagree     Agree 
 
             
 I will switch to another bank if...           
 
25. The bank does not offer a wide range of service products           
 
 (e.g. loans, mortgages, credit cards)  1 2 3 4 5 6 7  
 
26. The service products offered does not satisfy my           
 
 specific needs  1 2 3 4 5 6 7  
 
 
 
 
 
 
 27. In relation to the above factors, how likely are you to switch from your current bank? 
On a scale of 1-7, 1= extremely unlikely, 2= unlikely, 3= slightly unlikely, 4=neutral, 
5=slightly likely, 6=likely, 7=extremely likely. 
 
              
1 2 3 4 5 6 7 
PS           FS 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1 
 
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B. DEMOGRAPHIC DATA  
 
 Please provide the information required below 
 1. Gender  
  
Male  Female  
 
 2. Age (years)  
        
 18-25  26-35   36-45   46-55  56+      
3. Educational Level                
          
 JHS/SHS     Proffessional   HND/Bachelor’s Degree    
        
 Post Graduate Degree       Others - please specify_________________  
 
 4. Income level  
GH₵100 - GH₵999         GH₵1000 - GH₵1999      GH₵2000 - GH₵2999   
GH₵3000 - GH₵3999           GH₵4000 and above  
 
 
Thank You 
 
 
 
2