Black Generation Y Expectations of Their Banks' Customer Relationship

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Surname, Initial(s). (2012) Title of the thesis or dissertation. PhD. (Chemistry), M.Sc. (Physics), M.A. (Philosophy), M.Com. (Finance) etc. [Unpublished]: University of Johannesburg. Retrieved from: https://ujdigispace.uj.ac.za (Accessed: Date). Black Generation Y expectations of their banks’ customer relationship management

MARIUS BRESLER

A dissertation submitted in fulfilment for the Degree Of Magister Commercii in Marketing Management

Faculty of Management University of Johannesburg

Supervisor: Dr CF De Meyer

2013

DECLARATION

I certify that the dissertation submitted by me for the degree Master’s of Commerce (Marketing Management) at the University of Johannesburg is my independent work and has not been submitted by me for a degree at another university.

Marius Bresler

25/07/2013

DEDICATION

I would like to dedicate this work to my little nephew Darius. Your mere existence is a miracle and a blessing from above. Your presence lights up a room and brings joy to everyone in it. May your little light keep on shining and become even greater as you conquer your own mountains one day.

ACKNOWLEDGEMENTS

First and foremost, I would like to thank my Heavenly Father for His blessing, guidance and unconditional love throughout this process. Without Him, none of this would have been possible.

I would also like to thank the following people, without whom it would not have been possible to complete this project:

 My supervisor Dr. Christine De Meyer for all the valuable hours she spent on mentoring, guiding and encouraging me.  My parents, Marius and Suzette for their lifelong encouragement, love, support and mentorship.  My best friend Danniella Sebastiao for her constant motivation, never give up attitude, her positive influence and love.  Maralize and Louis for their constant interest in my progress and their love and support throughout the whole process.

ABSTRACT

As the South African banking industry is becoming more competitive due to new entrants and competitive offerings it is important to establish relationships with customers to maintain a competitive advantage. For South African banks to form relationships with customers, they need to understand their customers and what customers require from the relationship. For that reason, South African banks need to identify dimensions of customer relationship management (CRM) to build upon in strengthening their relationships with customers. As South Africa has experienced a rise in the spending power of black generation Y’s, this demographic requires further investigation. South African banks should realise that this market has significant potential in terms of profitability and it is important to determine which dimensions of customer relationship management this market prefers in order to build and further strengthen relationships.

The primary objective of the study was to determine black generation Y’s expectations of customer relationship management offered by their banks especially targeting generation Y adults within the Gauteng area. The study aimed at identifying customer relationship management dimensions and investigating black generation Y adults’ expectations toward those dimensions. The study further investigated whether black generation Y adults were satisfied with their banks and whether their satisfaction will lead to relationship intention and loyalty. The study focused on CRM dimensions identified from previous literature namely service quality, customisation, two-way communication, technology (the use of), commitment and convenience. Quantitative research methods were then used by means of a questionnaire that was distributed through convenience sampling to respondents throughout selected shopping malls in the Gauteng area. In order to measure expectations, satisfaction, relationship intention and loyalty constructs, only respondents who have banked with one of the four major banks (ABSA, FNB, Nedbank and Standard Bank) for a period of three or more years between the ages of 21-34 were asked to participate in the study. A total of 581 questionnaires were retained for data analysis.

Results indicated that respondents had high expectations for the customer relationship management dimensions offered by their banks but specifically with the dimensions of convenience and technology. Respondents also indicated that they are satisfied with their current banks and are willing to continue their relationships with their banks and remain loyal.

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These results could benefit the South African banking industry in that it provides insights into black generation Y adults as well as provide insights into possible CRM strategies banks could consider. The results of the study confirm that customer satisfaction influences relationship intention and retention. Banks therefore need to ensure that customers are satisfied to ensure loyal customers in the long-term.

In making recommendations for future studies, it was suggested that this study also be done on other cohorts such as Generation X as well as to conduct a follow up study which include new and upcoming banks such as Capitec Bank within the South African banking industry.

LIST OF KEY TERMS AND DEFINITIONS

Throughout this study, various key terms will be used. The following section outlines these key terms as well as a definition of each.

 Customer: A customer can be defined as any individual who consumes a product or service and has the ability to choose between different suppliers (BusinessDictionary, 2013). For the purpose of this study, customers will be referred to as any individual holding a bank account with one of the four major banks in South Africa (ABSA, FNB, Nedbank and Standard Bank).

 Customer Relationship Management: Payne (2008) defines CRM as a business approach that seeks to form, develop and enhance relationships with carefully chosen customers in order to improve customer value and corporate profitability with the goal of maximizing shareholder value.

 Customer Expectations: Leventhal (2008:51) define customer expectations as the standards customers use to evaluate the attractiveness and desirability of the service experience and outcome.

 Customer Satisfaction: A customer’s fulfilment response in that the service received provides a pleasurable level of experience (Zeithaml, Bitner & Gremler, 2009:104)

 Relationship Intention: Kruger and Mostert (2012:42) define relationship intention as the customers’ intention to form a relationship with an organisation after purchasing a product or using a service that the organisation offers.

 Customer Loyalty: Boshoff and Du Plessis (2009:319) define customer loyalty as the willingness of a customer to keep buying from the same service provider over the long term.

 The South African Banking Industry: The South African banking industry is a well developed and effectively regulated system which compares favourably with those of industrialised countries (The Banking Association South Africa, 2011). The banking industry in South Africa is dominated by four major role players which include; Amalgamated Banks of Southern Africa (ABSA), First National Bank (FNB), Standard bank and Nedbank.

TABLE OF CONTENTS

PAGE DEDICATION i ACKNOWLEDGEMENTS ii ABSTRACT iii LIST OF KEY TERMS AND DEFINITIONS v LIST OF FIGURES xiv LIST OF TABLES xv

CHAPTER 1: INTRODUCTION TO THE STUDY

1.1 INTRODUCTION TO THE RESEARCH 1 1.2 BACKGROUND OF THE STUDY 1 1.3 LITERATURE REVIEW 3 1.3.1 CUSTOMER EXPECTATIONS AND SATISFACTION 3 1.3.2 CUSTOMER RELATIONSHIP MANAGEMENT (CRM) 4 1.3.3 BLACK CONSUMERS IN SOUTH AFRICA 5 1.3.4 GENERATIONAL THEORY 6 1.3.4.1 GENERATION Y 7 1.4 PROBLEM STATEMENT 8 1.5 OBJECTIVES 9 1.5.1 PRIMARY OBJECTIVE 9 1.5.2 SECONDARY OBJECTIVE 9 1.6 HYPOTHESES 11 1.7 RESEARCH METHODOLOGY 13 1.7.1 RESEARCH DESIGN 13 1.7.2 POPULATION AND SAMPLE 14 1.7.3 DATA COLLECTION PROCEDURES 16 1.8 DATA ANALYSIS 16 1.9 CHAPTER LAYOUT 18 1.10 CONCLUSION 19

CHAPTER 2: THE SOUTH AFRICAN BANKING INDUSTRY

2.1 INTRODUCTION 20 2.2 THE FINANCIAL SECTOR 20

2.3 THE SOUTH AFRICAN BANKING INDUSTRY 20 2.4 REGULATORY BODIES AND LEGISLATION IN THE SOUTH 23 AFRICAN BANKING INDUSTRY 2.4.1 THE BANKS ACT 23 2.4.2 THE NATIONAL PAYMENT SYSTEM ACT 23 2.4.3 THE FINANCIAL INTELLIGENCE CENTRE ACT (FICA) 23 2.4.4 THE FINANCIAL ADVISORY AND INTERMEDIARY SERVICES ACT 24 (FAIS) 2.4.5 THE NATIONAL CREDIT ACT 24 2.4.6 THE CONSUMER PROTECTION ACT 24 2.4.7 THE HOMELOAN AND MORTGAGE DISCLOSURE ACT 25 2.4.8 THE COMPETITIONS ACT 25 2.5 BANKING CATEGORIES IN SOUTH AFRICA 26 2.6 THE MAJOR BANKS IN THE SOUTH AFRICAN BANKING 29 INDUSTRY 2.6.1 STANDARD BANK 29 2.6.2 ABSA (AMALGAMATED BANKS OF SOUTH AFRICA LIMITED) 30 2.6.3 FNB (FIRST NATIONAL BANK) 30 2.6.4 NEDBANK 31 2.6.5 CAPITEC BANK 32 2.7 CONCLUSION 33

CHAPTER 3: CUSTOMER EXPECTATIONS, SATISFACTION AND LOYALTY

3.1 INTRODUCTION 35 3.2 CUSTOMER EXPECTATIONS 35 3.2.1 DEFINING CUSTOMER EXPECTATIONS 36 3.2.2 FACTORS INFLUENCING CUSTOMER EXPECTATIONS 36 3.2.2.1 MARKETING COMMUNICATION OR ADVERTISING 37 3.2.2.2 THE IMAGE THE CUSTOMER HOLD OF THE ORGANISATION 37 3.2.2.3 WORD OF MOUTH SPREAD BY CUSTOMERS 37 3.2.2.4 SELF-EFFICACY 38 3.2.2.5 PARTICIPATION OF THE CUSTOMER IN THE SERVICE DELIVERY 38 PROCESS 3.2.3 THE GAPS MODEL OF SERVICE QUALITY 38 3.2.3.1 GAP 1: THE LISTENING GAP 40

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3.2.3.2 GAP 2: THE SERVICE DESIGN AND STANDARDS GAP 40 3.2.3.3 GAP 3: THE SERVICE PERFORMANCE GAP 40 3.2.3.4 GAP 4: THE COMMUNICATION GAP 41 3.2.3.5 GAP 5: THE CUSTOMER GAP 41 3.3 CUSTOMER SATISFACTION 41 3.3.1 LINK BETWEEN CUSTOMER EXPECTATIONS AND CUSTOMER 42 SATISFACTION 3.3.2 DEFINING CUSTOMER SATISFACTION 43 3.3.3 IMPORTANCE OF CUSTOMER SATISFACTION 44 3.3.4 FACTORS CONTRIBUTING TO CUSTOMER SATISFACTION AND 45 DISSATISFACTION 3.3.4.1 FACTORS CONTRIBUTING TO CUSTOMER SATISFACTION 46 3.3.4.2 FACTORS CONTRIBUTING TO CUSTOMER DISSATISFACTION 47 3.3.5 METHODS AND PROCEDURES OF IMPROVING CUSTOMER 48 SATISFACTION 3.3.5.1 HIRE THE RIGHT PEOPLE 48 3.3.5.2 DELIVER SERVICE QUALITY THROUGH TRAINING AND 48 EMPLOYEE DEVELOPMENT 3.3.5.3 EMPOWER PEOPLE TO MAKE DECISIONS AND ACT ON THE 49 SITUATION 3.3.5.4 ENCOURAGE TEAMWORK 49 3.3.5.5 PROVIDE THE NECESSARY SUPPORT SYSTEMS 49 3.3.6 MEASURING CUSTOMER SATISFACTION 51 3.3.6.1 PERIODIC SURVEYS 51 3.3.6.2 MONITORING CUSTOMER LOSS OR DEFECTION RATES 51 3.3.6.3 MYSTERY SHOPPERS 51 3.4 LOYALTY 52 3.4.1 LINK BETWEEN CUSTOMER SATISFACTION AND LOYALTY 52 3.4.2 DEFINING CUSTOMER LOYALTY 53 3.4.3 TYPES OF LOYALTY 53 3.4.3.1 PREMIUM LOYALTY 54 3.4.3.2 LATENT LOYALTY 55 3.4.3.3 SPURIOUS LOYALTY 55 3.4.3.4 NON-LOYALS 55 3.4.4 ADVANTAGES OF LOYALTY 55 3.4.4.1 REPEAT PURCHASES 56

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3.4.4.2 POSITIVE WORD OF MOUTH TO OTHERS 56 3.4.4.3 LOWER ACQUISITION COSTS 56 3.5 EXPECTATIONS, SATISFACTION AND LOYALTY IN THE SOUTH 56 AFRICAN BANKING INDUSTRY 3.5.1 EXPECTATIONS IN THE SOUTH AFRICAN BANKING INDUSTRY 57 3.5.2 SATISFACTION IN THE SOUTH AFRICAN BANKING INDUSTRY 57 3.5.3 LOYALTY IN THE SOUTH AFRICAN BANKING INDUSTRY 58 3.6 CONCLUSION 58

CHAPTER 4: CUSTOMER RELATIONSHIP MANAGEMENT

4.1 INTRODUCTION 59 4.2 RELATIONSHIP MARKETING 59 4.2.1 DEFINING RELATIONSHIP MARKETING 59 4.2.2 SIX MARKETS MODEL OF RELATIONSHIP MARKETING 60 4.2.2.1 INTERNAL MARKETS 61 4.2.2.2 REFERRAL MARKETS 61 4.2.2.3 INFLUENCE MARKETS 62 4.2.2.4 RECRUITMENT MARKETS 62 4.2.2.5 SUPPLIER MARKETS 62 4.2.2.6 CUSTOMER MARKETS 63 4.3 CUSTOMER RELATIONSHIP MANAGEMENT (CRM) 63 4.3.1 DEFINING CUSTOMER RELATIONSHIP MANAGEMENT 63 4.3.2 LEVELS OF CUSTOMER RELATIONSHIP MANAGEMENT 64 4.3.2.1 LEAD CUSTOMERS 65 4.3.2.2 IRON CUSTOMERS 65 4.3.2.3 GOLD CUSTOMERS 66 4.3.2.4 PLATINUM CUSTOMERS 66 4.3.3 THE CUSTOMER LOYALTY LADDER 66 4.3.3.1 STRANGERS 67 4.3.3.2 ACQUAINTANCES 67 4.3.3.3 FRIENDS 67 4.3.3.4 PARTNERS 67 4.3.4 THE IMPORTANCE OF CRM 68 4.3.4.1 CRM AND CUSTOMER SATISFACTION 68 4.3.4.2 CRM AND CUSTOMER LOYALTY 69

4.3.5 PROCEDURES IN DEVELOPING A CUSTOMER RELATIONSHIP 69 MANAGEMENT PROCESS 4.3.5.1 STEP 1: COLLECTING CUSTOMER DATA 70 4.3.5.2 STEP 2: ANALYSING DATA 70 4.3.5.3 STEP 3: DEVELOPING CRM PROGRAMMES 71 4.3.5.4 STEP 4: IMPLEMENTING THE CRM PROGRAMMES 71 4.4 CRM DIMENSIONS 71 4.4.1 SERVICE QUALITY 72 4.4.1.1 RELIABILITY 73 4.4.1.2 RESPONSIVENESS 73 4.4.1.3 ASSURANCE 73 4.4.1.4 EMPATHY 73 4.4.1.5 TANGIBLES 74 4.4.2 CUSTOMISATION 74 4.4.3 TWO-WAY COMMUNICATION 75 4.4.4 USE OF TECHNOLOGY 75 4.4.5 COMMITMENT 76 4.4.6 CONVENIENCE 77 4.5 DEVELOPMENT OF CRM INTO SERVICE DOMINANT LOGIC 78 4.6 CUSTOMER RELATIONSHIP MANAGEMENT AND THE SOUTH 79 AFRICAN BANKING INDUSTRY 4.7 CONCLUSION 81

CHAPTER 5: RESEARCH DESIGN AND METHODOLOGY

5.1 INTRODUCTION 82 5.2 THE MARKETING RESEARCH PROCESS 82 5.2.1 STEP 1: IDENTIFY AND FORMULATE THE RESEARCH PROBLEM 83 5.2.2 STEP 2: DETERMINE THE RESEARCH OBJECTIVES AND 84 HYPOTHESES 5.2.2.1 PRIMARY OBJECTIVE 84 5.2.2.2 SECONDARY OBJECTIVES 85 5.2.2.3 HYPOTHESES 86 5.2.3 STEP 3: THE RESEARCH DESIGN 90 5.2.3.1 QUANTITATIVE AND QUALITATIVE RESEARCH 90 5.2.3.2 RESEARCH DESIGNS 91

5.2.4 STEP 4: CONDUCT SECONDARY RESEARCH 92 5.2.5 STEP 5: SELECT A PRIMARY RESEARCH METHOD 92 5.2.5.1 DATA GATHERING TECHNIQUE AND THE SURVEY METHOD 93 CHOSEN 5.2.5.2 QUESTIONNAIRE 94 5.2.5.3 THE CHOICE OF SCALE 98 5.2.5.4 PRE-TESTING OF THE QUESTIONNAIRE 105 5.2.5.5 VALIDITY OF THE QUESTIONNAIRE 106 5.2.5.6 RELIABILITY OF THE QUESTIONNAIRE 107 5.2.6 STEP 6: DETERMINE THE RESEARCH FRAME 108 5.2.6.1 TARGET POPULATION 108 5.2.6.2 THE SAMPLING UNIT 109 5.2.6.3 SAMPLING FRAME 109 5.2.6.4 SAMPLING TECHNIQUE 109 5.2.6.5 TIME AND PERIOD 111 5.2.6.6 EXTENT 111 5.2.6.7 SAMPLING SIZE 111 5.2.6.8 SAMPLING ERRORS 112 5.2.7 STEP 7: DATA GATHERING 112 5.2.8 STEP 8: DATA ANALYSIS 113 5.2.8.1 CODING OF DATA 113 5.2.8.2 DATA CAPTURING 113 5.2.8.3 EDITING OF DATA 114 5.2.8.4 STATISTICAL ANALYSIS OF DATA 114 5.2.9 STEP 9: REPORTING AND RECOMMENDATIONS 116 5.3 CONCLUSION 116

CHAPTER 6: DATA ANALYSIS

6.1 INTRODUCTION 117 6.2 REALISATION RATE AND DISTRIBUTION OF RESULTS 117 6.3 DEMOGRAPHIC PROFILE 118 6.4 EXPECTATIONS, SATISFACTION, RELATIONSHIP INTENTION 120 AND LOYALTY DESCRIPTIVES 6.4.1 EXPECTATIONS OF RESPONDENTS 120 6.4.2 SATISFACTION OF RESPONDENTS 126

6.4.3 RELATIONSHIP INTENTION OF RESPONDENTS 128 6.4.4 LOYALTY OF RESPONDENTS 130 6.5 FACTOR ANALYSIS 132 6.5.1 RELIABILITY 134 6.6 HYPOTHESIS TESTING 134 6.6.1 HYPOTHESIS 1 135 6.6.2 HYPOTHESIS 2 138 6.6.3 HYPOTHESIS 3 140 6.6.4 HYPOTHESIS 4 141 6.6.5 HYPOTHESIS 5 142 6.6.6 HYPOTHESIS 6 143 6.6.7 HYPOTHESIS 7 145 6.6.8 HYPOTHESIS 8 145 6.6.9 HYPOTHESIS 9 147 6.6.10 HYPOTHESIS 10 149 6.6.11 HYPOTHESIS 11 152 6.7 CONCLUSION 155

CHAPTER 7: RESEARCH CONCLUSIONS AND RECOMMENDATIONS

7.1 INTRODUCTION 156 7.2 SECONDARY OBJECTIVES 156 7.2.1 SECONDARY OBJECTIVE 1 156 7.2.2 SECONDARY OBJECTIVE 2 157 7.2.3 SECONDARY OBJECTIVE 3 158 7.2.4 SECONDARY OBJECTIVE 4 159 7.2.5 SECONDARY OBJECTIVE 5 160 7.2.6 SECONDARY OBJECTIVE 6 160 7.2.7 SECONDARY OBJECTIVE 7 161 7.2.8 SECONDARY OBJECTIVE 8 162 7.2.9 SECONDARY OBJECTIVE 9 163 7.2.9.1 GENDER 163 7.2.9.2 EDUCATION 164 7.2.9.3 INCOME 164 7.2.9.4 CHOSEN BANK 165 7.2.9.5 LENGTH OF TIME WITH BANK 165

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7.2.10 SECONDARY OBJECTIVE 10 165 7.2.10.1 GENDER 165 7.2.10.2 EDUCATION 166 7.2.10.3 INCOME 166 7.2.10.4 CHOSEN BANK 166 7.2.10.5 LENGTH OF TIME WITH THE BANK 167 7.2.11 SECONDARY OBJECTIVE 11 167 7.2.11.1 GENDER 167 7.2.11.2 EDUCATION 168 7.2.11.3 INCOME 168 7.2.11.4 CHOSEN BANK 168 7.2.11.5 LENGTH OF TIME WITH THE BANK 169 7.2.12 SECONDARY OBJECTIVE 12 169 7.2.12.1 GENDER 169 7.2.12.2 EDUCATION 169 7.2.12.3 INCOME 169 7.2.12.4 CHOSEN BANK 170 7.2.12.5 LENGTH OF TIME WITH THE BANK 170 7.3 LINKING SECONDARY OBJECTIVES, MAIN FINDINGS AND 170 HYPOTHESES TO QUESTIONS IN THE QUESTIONNAIRE 7.4 LIMITATIONS OF THE STUDY 175 7.5 RECOMMENDATIONS FOR FURTHER RESEARCH 175 7.6 CONCLUSION 176

BIBLIOGRAPHY 177 ANNEXURE 1: QUESTIONNAIRE FOR PRE-TESTING 197 ANNEXURE 2: FINAL QUESTIONNAIRE 203 ANNEXURE 3: PAIRED SAMPLE T-TEST FOR INDIVIDUAL ITEMS 209

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LIST OF FIGURES

PAGE FIGURE 1.1: A presentation of the Hypotheses 12

FIGURE 2.1: Shareholding in the South African banking industry as in 22 December 2010 FIGURE 2.2: Number of registered banks in SA 28 FIGURE 2.3: Bank share of markets share based on 84% of the total market 28 share

FIGURE 3.1: Gaps model of service quality by combining the customer as 39 well as organisation gaps FIGURE 3.2: The disconfirmation paradigm 42 FIGURE 3.3: Sub categories of loyalty 54

FIGURE 4.1: Six markets model of Relationship Marketing 61 FIGURE 4.2: The Customer Pyramid 65 FIGURE 4.3: The steps in developing a CRM process 70

FIGURE 5.1: The Marketing research process 83

FIGURE 6.1: Correlation testing for satisfaction, relationship intention and 139 loyalty

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LIST OF TABLES PAGE TABLE 1.1: Previous studies and dimensions measured in CRM 4 TABLE 1.2: Number of questionnaires to be fielded 15 TABLE 1.3: Sampling plan 15

TABLE 2.1: List of banks in South Africa 26

TABLE 3.1: The benefits of customer satisfaction 44 TABLE 3.2: Procedures in attaining customer satisfaction 50

TABLE 4.1: CRM dimensions found in previous studies 72

TABLE 5.1: The advantages and disadvantages of person administered 93 questionnaires TABLE 5.2: Literature in developing items 96 TABLE 5.3: Dimensions, items and scales used 99 TABLE 5.4: Links between the secondary objectives and the sections in the 104 questionnaire TABLE 5.5: The research frame to be followed in obtaining a representative 108 sample TABLE 5.6: Number of questionnaires to be fielded based on quota sampling 110

TABLE 6.1: Frequency table indicating the demographic profile of 118 respondents TABLE 6.2: The expectations respondents have toward individual CRM 121 dimensions TABLE 6.3: Overall mean score for each CRM dimension (from highest to 126 lowest) TABLE 6.4: Respondent satisfaction with their banks 127 TABLE 6.5: Relationship intentions of respondents toward their banks 129 TABLE 6.6: Loyalty of respondents toward their banks 131 TABLE 6.7: KMO and Barlett’s test of Sphericity results 133 TABLE 6.8: Cronbach alpha of each individual dimension/construct 134 TABLE 6.9: CRM dimensions paired samples t-test 136 TABLE 6.10: Service quality and gender 141

TABLE 6.11: Technology and gender 143 TABLE 6.12: Analysis of variance: Technology 144 TABLE 6.13: Convenience and gender 146 TABLE 6.14: Analysis of variance: Satisfaction and Chosen Bank 148 TABLE 6.15: Analysis of variance: Relationship intention and Chosen Bank 151 TABLE 6.16: Analysis of variance: Loyalty and Chosen Bank 154

TABLE 7.1: Previous literature on CRM dimensions 157 TABLE 7.2: Overall mean values for each CRM dimension (from highest to 157 lowest) TABLE 7.3: Link between secondary objectives, hypotheses, questions and 171 the main findings and results

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CHAPTER 1 INTRODUCTION TO THE STUDY

1.1 INTRODUCTION

The primary reason that organisations strive to build relationships with customers is the economic benefit it provides the organisation (Abratt, Berndt, De Jager, Klopper, Petzer, Saunders, Tait & Viljoen, 2007:126). It also assists in identifying and satisfying the needs of their most profitable customers in order to retain these customers (Walsh & Gordon, 2010:219 & Abratt et al., 2007:126). According to Latham and Braun (2010:9), retaining current customers by engaging in relationships with them is crucial to establishing and maintaining a competitive advantage. Abratt et al. (2007:126) opines that the South African retail bank industry is characterised by ruthless competition and thus Customer Relationship Management (CRM) is needed in order to gain a competitive advantage. For this industry to attain a competitive advantage, it needs to determine what customers require as part of the CRM strategy in order to satisfy customer needs (Christensen, 2010:22).

This chapter includes a discussion of the background of the study (which provides insight into the financial services industry of South Africa), the literature review (used throughout the study), and the problem statement. The problem statement and formulation of research objectives (primary and secondary) are also discussed, as well as the hypotheses which form the basis of the study. The chapter then concludes with the research methodology, the data analysis and the chapter layout for the remainder of the document.

1.2 BACKGROUND OF THE STUDY

The financial crisis of 2007 placed pressure on the South African economy and the global financial system (National Treasury, 2011:11). As a result, South Africa’s economy declined by 1.8% in 2009, with consumers spending less and investment growth weakening (National Treasury, 2011:11). Therefore, the necessity for a strong and viable financial sector cannot be disputed as it enables growth, job creation, and the building of sustainable development (National Treasury, 2011:11). The South African financial sector is one of the largest and most deregulated of emerging economies; it accounts for 220 000 jobs in total and contributed to 20% of the GDP in 2004 (Financial Service Forecast, 2005:477). Between 2000 and 2010, the sector grew at an annual rate of 9.1% (National Treasury, 2011:13).

The financial sector includes institutions such as banks, pension funds, securities markets and regulators. But the focus of this study is on the retail banking industry. The South African retail banking industry is dominated by four major banks, namely: Amalgamated Banks of Southern Africa (ABSA), First National Bank (FNB), Nedbank (Nedcor) and Standard Bank. Combined, these comprise 84% of the total market share (The Banking Association South Africa, 2012a). Okeahalam (2007:670) posits that despite these major banks only serving half of the adult population in South Africa, they are more profitable than most of their foreign counterparts and levy higher service charges than the top 100 banks in the world. These charges are unique to South Africa with banks earning more than 25% on equity, whereas foreign banks earn around 15% (Mulholland, 2007:20). The South African government has sought to alleviate poverty and, as a result, the major banks in South Africa have undertaken to provide more effective and affordable services to black individuals (Financial Service Forecast, 2005:477). This led to the introduction of the Mzansi account in 2004 across all banks (Abratt et al., 2007:128). Needless to say the Mzansi account never became fully integrated into the banking system as it was an expensive exercise written off as a social obligation rather than a real acquisition strategy (Fisher-French, 2012).

The black Generation Y segment of South Africa is rising at a significant rate and many of these customers are becoming professionals in their industries (Smith, 2010). These “buppies” – black up and coming professional people – are strongly contributing to the profit margins of organisations (South Africa.info reporter, 2004). From a profit perspective, it would be advantageous for the banking sector to target these customers due to the significant increase within this segment as well as the prospect of these customers becoming business professionals (South Africa.info reporter, 2004).

From a marketing perspective, effective marketing requires that an organisation understand the marketplace as well as customer needs and desires so as to design a market-driven strategy (Kotler, Armstrong, Tait, Beneke, Bhowan, Blake, Botha, Cassim, de Jager, Frey, George, Golestaneh, Human, Rammile, Roberts-Lombard, Rootman, Rugimbana, van Zyl Vigar-Ellis & Wait, 2010:19). A market-driven strategy then allows an organisation to deliver superior value, build profitable relationships and create customer delight (Kotler et al., 2010:19). Due to the competitive nature of the banking industry and the changing needs of customers, banks have realised that they cannot only compete on product offerings alone, but need to integrate product offerings with customer service, pricing strategies, and promotional activities. They also need to satisfy customer needs and expectations through relationship building (Ganguly & Roy, 2010:183; Walsh & Gordon, 2010:219). Wang, Hu and Yu (2010:179) add that building relationships through CRM contributes to more

innovative service offerings, the expansion of new markets, the improvement of customer satisfaction, and the creation of core competencies, which establish grounds for loyalty.

The next section focuses on a shortened version of the literature review, which is the foundation of the study. The literature review includes a discussion of the main constructs used for the purposes of this study which are then further discussed in Chapter 3 and Chapter 4.

1.3 LITERATURE REVIEW

Based on the above, it is necessary to discuss the concepts considered in this study, namely: customer expectations and satisfaction, CRM, dimensions of CRM, generational theory, and insight into the black consumer market in South Africa.

1.3.1 CUSTOMER EXPECTATIONS AND SATISFACTION

Johnston and Marshall (2010:235) describe customer expectations as the performance gap between what organisations promise and what customers perceive organisations to deliver. Expectations can be very difficult to measure as they are formed by uncontrollable forces ranging from previous experiences to a customer’s psychological state at the time of service delivery (Bick, Abratt & Moller, 2010:14).

For banks to flourish in this competitive environment, both product and service offerings must be aligned with customer expectations so as to create customer satisfaction and loyalty (Bick et al., 2010:13). In order to ensure that customer expectations are met, organisations need to create customer delight. This can be done by under-promising and over-delivering (Johnston & Marshall, 2010:90). When organisations over-promise and under-deliver, customers become dissatisfied and will most likely not make use of the organisation’s services again. This may result in the loss of potential future business from that customer (Johnston & Marshall, 2010:90).

Zengh (2011:233-234) states that satisfied customers can hold various benefits for an organisation such as positive word of mouth, increased sales, the willingness to pay more for a service received, and loyalty. Furthermore, organisations employing high standards of customer satisfaction often insulate themselves from competitive pressures, especially when faced with price competition.

For organisations to ensure that customers achieve a level of satisfaction, a clear focus needs to be on building relationships with these customers through CRM.

1.3.2 CUSTOMER RELATIONSHIP MANAGEMENT (CRM)

CRM forms part of the Relationship Marketing concept which includes an integrated offering of superior service as well as a superior product to attain maximum profitability, customer retention, and customer loyalty while taking all the stakeholders into consideration (Egan, 2008:236). Kotler et al. (2010:27) define CRM as a process that includes building and maintaining profitable relationships with customers by providing superior satisfaction and customer value. Thus, CRM follows the principles of acquiring, keeping, and growing those customers to ensure maximum profitability because the costs of retaining customers are less than the costs of acquiring new ones. Ranjan and Bhatnagar (2011:137) list the following benefits that can be achieved when implementing CRM programmes: the possibility of cross- selling, the ability to target only certain segments, the ability to target market segments using fixed criteria, and the benefit of creating loyal customers.

Kotler et al. (2010:33) and Edward and Sahadev (2011:327) explain that losing a customer is more than just losing a single sale. Instead, it means losing the entire stream of income which that person would have generated for the organisation over his/her lifetime. Agrawal (2003:151) explains that CRM is based on information technology which businesses implement with the aim of identifying future profitable customers as well as establishing mutually beneficial and profitable relationships with customers that drive customer retention and loyalty.

To understand CRM, there must be a clear understanding of the dimensions that constitute it so that the effectiveness of CRM programmes can be measured. Different authors have conducted studies on CRM within multiple industries. Table 1.1 provides an exposition of the CRM dimensions identified by previous studies. These are used as the basis for this study.

Table 1.1: Previous studies and dimensions measured in CRM Dimension Literature Service quality Zeithaml, Bitner and Gremler (2009:152-153) Customisation Wong, Chan, Leung and Pae (2008:143) Two-way communication Hashem (2012:132) Use of technology Sangle and Awasthi (2011:907)

Commitment Dagger, David and Ng (2011:280) Convenience Foscht, Schloffer, Maloles and Chia (2009:230)

From Table 1.1 the following CRM dimensions are identified:  Service quality: this includes responsiveness (including providing prompt service), reliability (including efficiency), tangibles (including servicescape), assurance (including trust and the knowledgeability of employees), and empathy (Zeithaml et al., 2009:152- 153).  Customisation: the ability to meet individual customers’ needs (Wong et al., 2008:143).  Two-way communication: communication between customers and employees, as well as the interaction between employees (Hashem, 2012:132).  Use of technology: the use of and ease of use of technology to assist customers in their transactions (Sangle & Awasthi, 2011:907).  Commitment: the commitment of staff to building relationships and satisfying customer needs (Dagger et al., 2011:280).  Convenience: the availability of staff, tellers, as well as convenient operating hours and procedures (Foscht et al., 2009:230).

The dimensions identified above are used as the bases for the study. Customer expectations of these CRM dimensions are also identified in the study, as well as customers’ level of satisfaction, what their relationship intentions are, and how loyal they are to their banks.

Alhemoud (2010:333) defines “satisfaction” as the positive evaluation of a customer after buying or using an organisation’s services. “Relationship intention” can be defined as a customer’s intention to form a relationship with an organisation after purchasing a product or using a service that the organisation offers (Kruger & Mostert, 2012:42). Ndubisi, Wah and Ndubisi (2007:224) state that loyalty is a deeply held commitment by customers to re-use a preferred service in the future despite other influences and marketing efforts from competing organisations who aim to affect switching behaviour.

1.3.3 BLACK CONSUMERS IN SOUTH AFRICA

Da Silva (2011) states that during the last decade, black South Africans have entered the mainstream economy. However, many marketers still underestimate the power of this market even though the percentage income of black consumers, on lower and upper ends, has increased year on year. For example, Comins (2005) found that from 1999 to 2005

black households that earned more than R154 000 a year grew by more than 368%. In addition, da Silva (2011) explains that black individuals have a soaring spending power and that the changes in their spending power have supported growth in other industries including services, manufacturing, and retail (Chuphi, 2010). Chuphi (2010) predicts that over the next few years, banking and insurance institutions will become beneficiaries of black spending in South Africa. This emphasises the need for financial institutions to concentrate their marketing efforts on this group. According to some researchers, black South Africans comprise a very specific group Smith (2010). Although they may share certain characteristics with other ethnic groups, there are some characteristics that are particular to them. Smith (2010) opines that black South Africans born after 1994 are the born-free generation since most of them grew up in a new South Africa. He further states that the older members of this generation are already grown up or are just about to enter the workplace. This generation represents the largest group currently in South Africa and can be characterised and identified as entrepreneurial, determined, optimistic, techno-savvy, and connected (Smith, 2010). Lee and Lee (2010:364) make mention of the fact that black South Africans are much more likely to make use of mobile technology than they are the Internet. Their study further indicates that members of this group use their mobiles for financial and business purposes, as well as for payment and billing services more than any other ethnic group. This could be a lucrative segment for banks trying to target this generation.

1.3.4 GENERATIONAL THEORY

Haynes (2011:106) posits that customers from different age generations have different expectations, satisfaction levels, and loyalty levels; thus the need has arisen to understand the expectations, satisfaction and loyalty that these different customers have in terms of the CRM strategies of their banks.

The main generations that can be identified include veterans (also called seniors, born between 1922 and 1945), baby boomers (born between 1946 and 1964), Generation X (born between 1965 and 1976) and Generation Y (born between 1977 and 2000) (Haynes, 2011:99; Kotler et al., 2010:84-85; Lamb, Hair, McDaniel, Boshoff, Terblanche, Elliot & Klopper, 2010:48-49). According to Jorgensen (2003:42), the Generation Y group differs significantly from those in other age cohorts. For this reason, this study will focus specifically on the Generation Y cohort.

1.3.4.1 GENERATION Y

Due to the large age group in this generation, the Generation Y cohort is often further divided into three smaller sub-segments, namely: Generation Y adults, twixters/teenagers and tweens (Haynes, 2011:99).

 Generation Y adults Generation Y adults, according to Ma and Niehm (2006:621), include individuals born between 1977 and 1994. Jorgensen (2003:43), on the other hand, states that Generation Y adults consist of individuals born between 1977 and 1988, while Kumar and Lim (2006:569), opine that Generation Y adults are those individuals born between 1980 and 1994. As there is no consensus between researchers regarding the exact age group of Generation Y adults, this study will consider Generation Y adults as those individuals born between 1978 and 1991, which places them between the ages of 21 and 34 at the time of the study (2012).

Generation Y adults have a very high work ethic and tend to be well educated (Jorgensen, 2003:43). Smith (2011) characterises Generation Y adults as being entrepreneurial, determined, success-driven, independent, self-confident as well as optimistic about the future. In addition, due to the fact that Generation Y adults have always known and used the Internet, they are referred to as the “digital natives” and can be reached through media such as Facebook, Twitter and other electronic technologies (Lamb et al., 2010:49). Lamb et al. (2010:49) explain that, because the younger Generation Y adults are entering the workplace, organisations must take the opportunity to target them and build long term relationships with them.

 Twixters/Teenagers According to Lamb et al. (2010:48), Twixters include those segments with a higher disposable income due to the fact that they do not have to buy necessities or pay taxes. They include all individuals between the ages of 13 and 18. Furthermore, this age cohort has a significant influence on household spending as parents will purchase goods according to the needs and desires of this group

 Tweens Martensen (2007:108) defines individuals between the ages of eight and 12 years as tweens since they are too old to be considered children, too young to be twixters/teenagers, and rely mostly on spending money from their parents. According to Lamb et al. (2010:48-49),

tweens influence household spending in four ways: 1) influencing the buying decision when accompanying parents on shopping trips; 2) influencing the buying decision, even when they are not accompanying parents, by encouraging parents to purchase a preferred brand; 3) influencing decisions when parents seek counsel from them; and 4) influencing the buying decision when they ask parents for gifts.

Taking the above discussion into consideration, the focus of this study will be on the Generation Y adult cohort because this age group is entering the workplace and earning money (Lamb et al., 2010:49). They therefore have the need for financial services and are the ideal group with which banks should form relationships since these customers have a long lifetime value if they are loyal to the bank.

1.4 PROBLEM STATEMENT

Ganguli and Roy (2010:183) and Palmer (2008:252) mention that since the financial sector is dominated mainly by services, customer service, and CRM plays a pivotal role in ensuring satisfied and loyal customers, especially in times such as a financial crisis.

Saunders (2008:452) indicates that CRM is important in aiming to satisfy customers, which, in turn, can lead to customer loyalty and retention. Many banks are using CRM programmes, but these programmes are not focused on customer needs and expectations. Previous studies conducted on CRM within the banking industry such as Rootman (2006:128-153), Bick, Brown and Abratt (2004:300-318) and Abratt and Russell, (1999:15) did, however, yield interesting results. The study conducted by Bick et al. (2004:300) measured customer perceptions resulting from expectations of the value delivered by retail banks in South Africa and determined that customers were not satisfied with the products, services, and customer intimacy offered by their banks. The effect of this was that customers did not desire long-term relationships with their banks and this impacted the need for CRM. The study by Rootman (2006:128-153) proved that customers identified the knowledgeability of employees as well as the employees’ attitudes when dealing with customers as the most important CRM dimensions. In addition, Abratt and Russell (1999:11-16) found that trust and service quality were two dimensions which customers perceived as being important. These studies, however, focused on banking customers in general and did not focus on a specific generation or segment.

Even though the importance of conducting consumer research on the black Generation Y consumer cannot be disputed, very few studies have focused on this group (Sibiya, 2007).

According to Sibiya (2007), South Africa’s black Generation Y adults are a very complex group to understand. and marketers often do not know how to market to these customers because they misinterpret their cultural roots, traditions, and expectations. Furthermore, because this group forms part of the workforce and therefore earn a salary (Lamb et al., 2010:49) they are an important target market for financial institutions. Although studies have been done on the impact of CRM and Relationship Marketing on customer satisfaction in retail banking, none could be found that has been conducted on black Generation Y consumers.

The main reason for undertaking to complete this study is thus to determine the expectations and satisfaction that black Generation Y adults have in terms of the CRM dimensions offered by their banks. The study will therefore aid banks by indicating what the expectations of the lucrative black Generation Y adult market are. Furthermore, the study aims to determine whether the black Generation Y adults are satisfied with the CRM dimensions provided by their banks.

It is clear then that there is a need for this type of research in the banking industry as no previous studies have been conducted which focus on this specific demographic and the current banking industry. The following objectives will assist in answering the research question.

1.5 OBJECTIVES

The following section will include a discussion on the primary and secondary objectives identified for the purposes of the study.

1.5.1 PRIMARY OBJECTIVE

The primary objective of this study is to determine black Generation Y adults’ expectations of the CRM dimensions offered by their banks as well as to identify their overall levels of satisfaction, relationship intention, and loyalty to their banks.

1.5.2 SECONDARY OBJECTIVES

This section provides insights into the secondary objectives set for the study in order to achieve the primary objective. The secondary objectives that the researcher aims to investigate include:

 Conducting a literature review to identify the CRM dimensions that can be used in the banking industry;  Identifying the black Generation Y adults’ expectations of the CRM dimensions (service quality, customisation, two-way communication, technology, commitment and convenience) offered by their banks;  Determining the overall satisfaction levels that black Generation Y adults have with their banks;  Determining the overall relationship intention of black Generation Y adults with their banks;  Determining the overall loyalty levels that black Generation Y adults have to their banks;  Identifying whether significant differences can be observed between the means of black Generation Y adults’ expectations and the CRM dimensions offered by their banks;  Identifying whether black Generation Y adults’ satisfaction levels influence the relationship intention with and loyalty levels to their banks;  Identifying whether black Generation Y adults’ relationship intentions influence their loyalty levels to their banks;  Determining whether significant differences between means can be observed in terms of black Generation Y adults’ expectation levels of the CRM dimensions offered by their banks and demographic variables (gender, education, income, chosen bank, and length of time with the bank);  Determining whether significant differences between means can be observed in terms of black Generation Y adults’ satisfaction levels with the CRM dimensions offered by their banks and demographic variables;  Determining whether significant differences between means can be observed in terms of black Generation Y adults’ relationship intention levels with the CRM dimensions offered by their banks and demographic variables.  Determining whether significant differences between means can be observed in terms of black Generation Y adults’ loyalty to the CRM dimensions offered by their banks and demographic variables.

From these secondary objectives the researcher has formulated hypotheses which will be discussed in the next section.

1.6 HYPOTHESES

The following hypotheses have been formulated based on the secondary objectives (as illustrated in figure 1.1):

H1: There is a significant difference between the means of each CRM dimension and the expectations that black Generation Y adults have of their banks. H2: Black Generation Y adults’ satisfaction levels significantly and positively influence relationship intention with and loyalty to their banks. H3: There is a significant difference between the means of black Generation Y adults’ expectations of the service quality offered by their banks and demographic variables. H4: There is a significant difference between the means of black Generation Y adults’ expectations of the customisation offered by their banks and demographic variables. H5: There is a significant difference between the means of black Generation Y adults’ expectations of the two-way communication offered by their banks and demographic variables. H6: There is a significant difference between the means of black Generation Y adults’ expectations of the technology offered by their banks and demographic variables. H7: There is a significant difference between the means of black Generation Y adults’ expectations of the commitment offered by their banks and demographic variables. H8: There is a significant difference between the means of black Generation Y adults’ expectations of the convenience offered by their banks and demographic variables. H9: There is a significant difference between the means of black Generation Y adults’ overall satisfaction with their banks and demographic variables. H10: There is a significant difference between the means of black Generation Y adults’ overall relationship intention with their banks and demographic variables. H11: There is a significant difference between the means of black Generation Y adults’ overall loyalty to their banks and demographic variables.

Figure 1.1: A presentation of the hypotheses

Demographic Variables (gender, education, income, chosen bank

Expectations and time)

H3 H9

H1 Service Quality Satisfaction

H1 H4 H10 H2 Customisation Relationship H2 H1 H5 Intention Communication

H2 H1 H6 H11 Use of technology Loyalty

H1 H7 Commitment

H1 H8 Convenience

1.7 RESEARCH METHODOLOGY

The research methodology section discusses the methods used to obtain the data, which inform the abovementioned objectives and hypotheses and also provides insight into the research methodology used for the purpose of the research. Chapter 5 includes an in-depth discussion of the research methodology. In this section, aspects such as research design, population and sampling, and data collection procedures are discussed.

1.7.1 RESEARCH DESIGN

A research design is considered to be the master plan or blueprint used to achieve the research objectives (which, for this study, have been discussed) (Zikmund, Babin, Carr, & Griffin, 2010:66). There are three types of research design from which to choose. These include: exploratory research (which focuses on the discovery of ideas and insights), descriptive research (which focuses on the relationship between two variables), and causal research (which emphasises a cause-and-effect relationship) (Churchill & Iacobucci, 2005:74). For the purposes of this study, the researcher made use of descriptive research because Zikmund and Babin (2007:83) state that descriptive research is best suited to quantitative research. Descriptive research can be defined as type of research design that describes the characteristics of a given research problem (Zikmund & Babin, 2010:45). Descriptive research has been used for the purposes of this study since a clear statement of the problem exists together with specific hypotheses and detailed information needs (Zikmund et al., 2010).

As the aim of the study is to determine black Generation Y customers’ expectations of and satisfaction levels with the CRM dimensions, descriptive research will help make the demographic and behavioural information of customers comprehensible. Data was collected using a survey (intercept surveys in shopping malls around Gauteng). The reason for this is the high flexibility of data collection, the high diversity of questions, and the high control of the data collection environment together with a high response rate (Zikmund & Babin, 2010:160). It was important to have control of the data collection environment since quota sampling methods were used. This is discussed in Section 1.7.2 (Population and Sample).

Secondary data can be defined as data that has been previously collected and recorded by another person for purposes other than the current research project (Malhotra, 2007:106). This

data is said to be historical and requires no further access to research respondents as it is already assembled (Zikmund & Babin, 2010:123). Secondary data, according Zikmund and Babin (2010:123), is readily available, collected much faster than primary data, less expensive, and enhances the collection of primary data. The Internet, books, articles, databases, academic journals, company information, and theses and dissertations, among others, have been used as sources of secondary data for this study.

Churchill and Iacobucci (2005:167) define primary data as research that is originated by the researcher for the purposes of investigating the problem at hand. From the collection of primary data, meaningful insights can be gathered. For the purposes of this study, insights into black Generation Y adults’ expectations, satisfaction levels, relationship intentions, and loyalty were gained through the gathering of primary data.

1.7.2 POPULATION AND SAMPLE

The target population for this study includes all black Generation Y adults who were between the ages of 21 and 34 (1978-1991) at the time this study was conducted (Ma & Niehm, 2006:621). More specifically, the study includes those who have banked with one of the four major South African banks (Standard Bank, First National Bank [FNB], Amalgamated Banks of South Africa [ABSA] and Nedbank) for a period of three years or longer as such a period of involvement will have allowed enough time for a relationship between the customers and their respective banks (De Meyer & Petzer, 2012:29).

Probability sampling is a selection method whereby the sampling units are selected at random (Hair, Wolfinbarger, Ortinau, & Bush, 2010:135), while non-probability sampling is the sampling of members not selected randomly but rather according certain criteria (Hair et al., 2010:135). Non-probability sampling in the form of quota sampling has been used in this study to obtain respondents (Malhotra, 2007:344). Malhotra (2007:344) defines quota sampling as a two-stage judgemental sampling: the first stage consisting of developing quotas of population dimensions and the second stage selecting sample dimensions based on convenience. The researcher thus aimed to obtain a spread of respondents from the four main banks in South Africa according to their market share as shown in Table 1.2. Additionally, quotas were filled according to gender with an even spread between males and females. The sample size included 600 respondents.

Table 1.2: Number of questionnaires to be fielded Bank Market share of Number of questionnaires the four major to be fielded (without other banks (with other banks)* banks) ABSA 21.6% 155 FNB 18.8% 135 Nedbank 17.8% 127 Standard Bank 25.5% 183 Total 83.7% 600 Source: The Banking Association South Africa (2011:3). * Only the four major banks with 83.7% of the market share will be included in the study.

The study was conducted in Johannesburg and Pretoria (Gauteng Province) where the researcher aimed to obtain a spread of respondents for the four main banks (quotas) as well as a spread between males and females. The reason for choosing the Gauteng province is that it represents the economic hub of South Africa and the responses gathered in this area could be considered as representative of the South African population (Okeahalam, 2007:934).

Table 1.3 illustrates the sampling plan for the study. The sampling plan is the plan the researcher follows in gathering the data. It includes the criteria for conducting the research.

Table 1.3: Sampling plan Target population Black Generation Y adults Sampling units Black Generation Y adults who have banked with one of the four major banks for a period of three years or longer Sampling frame Sampling units at different shopping malls throughout Gauteng Sampling technique Non-probability, quota sampling (2 stages consisting of quota and convenience sampling) Time and period 10 September – 1 October 2012 Extent The Gauteng area Sampling size 600 Respondents (Standard Bank = 183, FNB = 135, ABSA = 155 and Nedbank = 127) Age cohort Generation Y adults between the ages of 21-34

1.7.3 DATA COLLECTION PROCEDURES

Data was obtained in the form of a questionnaire using a mall intercept method where respondents were intercepted by fieldworkers fielding the questionnaire at shopping malls. The questionnaire measured the expectations and satisfaction that black Generation Y adults have with the CRM efforts offered by their banks in the Gauteng area.

The questionnaire was anonymous, structured with closed- and open-ended questions. The questionnaire included three screening questions determining whether the respondent had a bank account with one of the four major banks, whether the respondents has had that account for at least three years, and whether the respondent fell within the age group measured. On- site screening was done by fieldworkers to ensure that only black respondents were included in the sample. Section A of the questionnaire included items measuring the expectations of respondents pertaining to the CRM dimensions. Section B determined the satisfaction, relationship intentions, and loyalty levels of respondents. Lastly, section C gathered data pertaining to respondents’ demographic variables. The scale items in Section A and B of the questionnaire were measured on a seven-point Likert scale in which the number 1 signalled strong agreement and number 7 strong disagreement. In the relationship intention and loyalty sections, however, the number 1 signalled “not likely at all” while number 7 signalled “very likely”. The questionnaire was adapted from previous studies (see section 5.2.5.2 in Chapter 5).

The measuring instrument was pretested on a small sample of the respondents so as to identify and eliminate possible problems. The questionnaire instructions, content, wording, question difficulty, sequence, form, and layout were all pretested (Zikmund & Babin, 2010:178). After pretesting the questionnaire, fieldworkers distributed the questionnaire at pre-chosen shopping malls around the Gauteng area. Upon completion of the questionnaires, all the responses were sent to the Statistical Consultation Service (STATKON) of the University of Johannesburg for coding and analysis in conjunction with the researcher.

1.8 DATA ANALYSIS

All data obtained was analysed by means of PASW 20 (also known as SPSS 20). The skewness, kurtosis, and frequencies were determined in order to identify whether the data was normally distributed since this influences whether parametric or non-parametric tests can be

used for data interpretation. The skewness provides an indication of the symmetry of distribution, whereas the kurtosis provides information on the “peakedness” of the distribution (see section 5.2.8.4 in Chapter 5) (Pallant, 2007:56).

The researcher also tested for reliability and validity. Reliability, according to Eiselen, Uys and Potgieter (2005:13-14), is when a measuring instrument demonstrates the consistency of the measurements. Thus, a measuring instrument will be consistent if it produces equivalent results for repeated measurements. Validity refers to the degree to which a measuring instrument measures what it is supposed to measure (Eiselen et al., 2005:14). In testing reliability, the Cronbach-alpha value was used. Questionnaires were pretested so as to ensure high quality data collection and to test for validity, both of which could contribute to the outcome of the study.

Furthermore, regression analysis, t-tests, ANOVAs and a factor analysis were conducted. Regression analysis was conducted to measure the strength of association between two variables that can be measured on interval and ratio scales (Pallant, 2007:145) such as satisfaction and relationship intention, relationship intention and loyalty, and satisfaction and loyalty. A t-test was used to compare means for a variable grouped into two categories based on some less-than-interval variable (Zikmund & Babin, 2007:351-352). The independent sample t-test, which tests the differences between means, was also used for this study. The independent sample t-test was used to compare two means, one being an independent variable such as gender, and the other a dependent variable such as a CRM dimension. The paired sample t-test, for example, when testing the expectations and satisfaction levels between genders were also used. An ANOVA is a statistical technique for examining the differences between means for two or more populations (Zikmund & Babin, 2007:355-357), such as comparing the means of the sample in terms of the different CRM dimensions and different age categories, or for different age categories and satisfaction. According to Eiselen et al., (2005:104-105), factor analysis helps to determine underlying dimensions in a set of questions, thus reducing the number of questions to a few interpretable dimensions. This, in turn, permits the researcher to describe the survey results. A confirmatory factor analysis was also conducted so as to confirm the CRM dimensions obtained from previous literature.

1.9 CHAPTER LAYOUT

The following section outlines the various chapters that will be included in the study.

Chapter 1: Introduction to the study

This chapter provides a background to the study, the literature review, as well as a detailed description of the problem investigated. Furthermore, the objectives and hypotheses for the study are stated, and a brief overview of the research methodology used to conduct the study is then presented.

Chapter 2: The South African banking industry

This chapter includes an in-depth discussion of the South African banking industry as well as the financial industry. As part of the industry, each of the four major banks in South Africa is discussed as well as the reasons for the exclusion of Capitec Bank.

Chapter 3: Customer expectations, satisfaction, and loyalty

Customer expectations, satisfaction, and loyalty is explained in this chapter by investigating how expectations can lead to customer satisfaction or dissatisfaction. An in-depth discussion of the benefits of customer satisfaction and the outcomes of dissatisfaction follows. The relationship between expectations and satisfaction is also discussed, as well as the relationship between satisfaction and loyalty. Furthermore, the chapter presents a discussion of customer expectations and satisfaction in the South African retail bank industry.

Chapter 4: Customer relationship management

This chapter begins with a discussion of Relationship Marketing and how CRM forms part of the Relationship Marketing concept. A discussion of CRM then follows. Each CRM dimension used for the purposes of this study is also discussed together with the importance of CRM for organisations. The chapter concludes with a discussion of CRM and the South African retail bank industry as well as the transition from CRM to service dominant logic.

Chapter 5: Research methodology

This chapter discusses the research methodology utilised for the study. The marketing research process forms the foundation of the discussion and is discussed in detail. This process consists of the following nine steps: identifying the research problem, determining the research objectives, developing the research design, conducting secondary research, selecting the primary research method, determining the research frame, gathering the data, analysing the data and reporting, and making recommendations.

Chapter 6: Data analysis

This chapter provides an analysis of the data using various statistical analyses such as frequencies, factor analysis, regression analysis, t-tests and ANOVAs. The main findings and results are also presented.

Chapter 7: Research conclusions and recommendations

From the results presented in Chapter 6, the conclusions for the study are then drawn and recommendations for the banking industry (pertaining to the CRM dimensions, satisfaction, relationship intention, and loyalty of black Generation Y adults) are made and are based on the findings of the secondary objectives. Finally, the limitations of the study and the recommendations for future research are discussed.

1.10 CONCLUSION

The current chapter provided a background to the research problem as well as the problem statement for the study. It also briefly discussed the industry background, the problem statement, and gave a short review of the literature which is discussed in the following chapters. A summary of the research methodology as well as the data analysis used for the purposes of this study are also provided. The next chapter will focus on the South African banking industry by outlining the four major banks in South Africa and their market dominance.

CHAPTER 2 THE SOUTH AFRICAN BANKING INDUSTRY

2.1 INTRODUCTION

The South African banking industry is a well regulated private industry dominated by the four major banks (ABSA, FNB, Nedbank and Standard Bank) and a few emerging banks (such as Capitec Bank). This chapter will look at the South African banking industry as part of the bigger financial sector. The different regulatory issues are discussed as well as the different categories of banks in South Africa. A brief overview of each of the four major banks is also provided and the chapter concludes with a discussion of Capitec Bank and the reasons for its exclusion from the study.

2.2 THE FINANCIAL SECTOR

The global financial sector is currently recovering from a financial crisis (Council on Foreign Relations, 2012). Although authors agree that the worst part of the financial sector has passed and the sector is improving, the after-effects are still being felt globally (Council on Foreign Relations, 2012). It is important for the global financial sector to be healthy as it has a significant influence on the South African economy.

The financial services sector plays an important role in the South African economy as it contributes about 10.5% to gross domestic product (GDP) with assets of more than R6 trillion (The Banking Association South Africa, 2011). According to the labour force survey, the financial services industry plays an important role in the country’s economy as it represents the third largest employer in the country with 13.3% of the total employment (Labour Force Survey, 2011). The next section expands on the South African banking industry as part of the greater global financial sector.

2.3 THE SOUTH AFRICAN BANKING INDUSTRY

The South African banking industry is a well-developed and effectively regulated system which compares favourably with those of industrialised countries (The Banking Association South

Africa, 2011). The industry is viewed as one of the world’s best, with adequate capital resources, infrastructure, technology, and a strong regulatory environment (The Banking Association South Africa, 2011). The South African banking industry comprises a central bank (South African Reserve Bank), a few large and financially strong banks, investment institutions, and a number of smaller banks (South Africa.info, 2012). It is also dominated by four major role players which include: Amalgamated Banks of Southern Africa (ABSA), First National Bank (FNB), Standard Bank, and Nedbank. Another role player, Capitec Bank, entered the market in March 2001 and could be considered a major role player in the future, showing positive gains year on year as well as gains at the lower end of the previously uncaptured banking market in South Africa (Pitman, 2011). These four major banks as well as other smaller banks and financial institutions are all governed by the South African Reserve Bank (SARB, 2012a).

Prior to 2009 the South African banking industry experienced good growth in Net Revenue as well as Net Profit with an average growth rate of 24% and 20% respectively (Innovation Agency, 2011). In 2009 the South African banking industry profits stood at R27.2 billion with Net Revenue estimated at R314.5 billion (Innovation Agency, 2011). Liabilities within the banking industry have increased by 3% in the last quarter of 2011 with the total liabilities amounting to R2.6 trillion at the end of 2011 (The South African Banking Association, 2011). However, the Return on Equity (RoE) increased from 14.64% in 2010 to 16.39% in 2011 and Return on Assets (RoA) increased for the whole industry from 0.97% in 2010 to 1.15% in 2011, and this still makes the banking industry highly profitable (SARB, 2011). Operating expenses during the same period increased from R83.8 billion in 2010 to R93.1 billion in 2011 (The South African Banking Association, 2011) and overall profits increased from 29.77% in 2010 to 36.78% in 2011 (SARB, 2011).

The South African banking industry is mainly privately owned by its shareholders. As indicated in Figure 2.1, shareholding by foreigner shareholders as of December 2010 represents 43% of the total shares, domestic shareholders represent about 30% and the remaining 27% can be attributed to minority shareholders with less than 1% (The South African Banking Association, 2011). The large amount of foreign shareholding is due to the large stake that Barclays Plc has in ABSA.

Figure 2.1: Shareholding in the South African banking industry in December 2010

Domestic Shareholding Foreign Shareholding Minority Shareholding

27% 30%

43%

Source: Adapted from The South African Banking Association (2011).

Despite the success of the South African banking industry (discussed in the previous sections), there are still customers who choose to not have a bank account. As of 2010, 63% of the South African population utilized banking products, which is a slight increase from previous years (Innovation Agency, 2011). The remainder of the population is either unbanked (24%), informally (money obtained or invested in home, friends or family) (9%) or formally non-banked (other money markets such as investment companies and insurance companies) (5%) (Innovation Agency, 2011; Mishra, 2012).

The South African banking industry offers the following products that customers or these unbanked customers can eventually make use of: cheque accounts, savings accounts, Mzansi accounts, investment accounts, home loans, vehicle finance and personal loans (Bankmonitor, 2012).

As stated at the beginning of this section, the South African banking industry is a well-developed and effectively regulated system which compares favourably with those of industrialised countries (The Banking Association South Africa, 2011). For this reason, it is necessary to consider the regulatory bodies involved in the South African banking industry.

2.4 REGULATORY BODIES AND LEGISLATION IN THE SOUTH AFRICAN BANKING INDUSTRY

Since the South African banking industry is privately owned by its shareholders (The Banking Association South Africa, 2012a) there are certain regulatory bodies and legislation that control its operations. These include:

2.4.1 THE BANKS ACT

The Banks Act is regulated by the South African Reserve Bank (Momentum, 2012) and aims “to provide for the regulation and supervision of the business of public companies taking deposits from the public; and to provide for matters connected therewith” (SARB, 2012b).

2.4.2 THE NATIONAL PAYMENT SYSTEM ACT

The National Payment System Act is regulated by the South African Reserve Bank (SARB, 2012c) and aims “to provide for the management, administration, operation, regulation and supervision of payment, clearing and settlement systems in the Republic of South Africa; and to provide for connected matters” (National Payment System Act 1998, 2012).

2.4.3 THE FINANCIAL INTELLIGENCE CENTRE ACT (FICA)

The Financial Intelligence Centre Act is regulated by the Financial Intelligence Centre (Bidvest Bank, 2012). FICA aims “to establish a Financial Intelligence Centre and a Money Laundering Advisory Council in order to combat money laundering activities and the financing of terrorist and related activities; to impose certain duties on institutions and other persons who might be used for money laundering purposes and the financing of terrorist and related activities; to amend the Prevention of Organized Crime Act, 1998, and the Promotion of Access to Information Act, 2000; and to provide for matters connected therewith” (Financial Intelligence Centre Act 38 of 2001, 2012).

2.4.4 THE FINANCIAL ADVISORY AND INTERMEDIARY SERVICES ACT (FAIS)

The Financial Advisory and Intermediary Services Act (FAIS) is regulated by the Financial Services Board (Momentum, 2012). FAIS aims “[t]o regulate the rendering of certain financial advisory and intermediary services to clients; to repeal or amend certain laws; and to provide for matters incidental thereto” (Government Gazette, 2012a).

2.4.5 THE NATIONAL CREDIT ACT

The National Credit Act is governed by the National Credit Regulator (NCR) (Momentum, 2012). It aims “to promote a fair and non-discriminatory marketplace for access to consumer credit and for that purpose to provide for the general regulation of consumer credit and improved standards of consumer information; to promote black economic empowerment and ownership within the consumer credit industry; to prohibit certain unfair credit and credit-marketing practices; to promote responsible credit granting and use and for that purpose to prohibit reckless credit granting; to provide for debt re-organization in cases of over indebtedness; to regulate credit information; to provide for registration of credit bureau, credit providers and debt counselling services; to establish national norms and standards relating to consumer credit; to promote a consistent enforcement framework relating to consumer credit; to establish the National Credit Regulator and the National Consumer Tribunal; to repeal the Usury Act, 1968, and the Credit Agreements Act, 1980; and to provide for related incidental matters” (Government Gazette, 2012b).

2.4.6 THE CONSUMER PROTECTION ACT

The Consumer Protection Act is regulated by the National Consumer Commission (National Consumer Commission, 2012). It aims “to promote a fair, accessible and sustainable marketplace for consumer products and services and for that purpose to establish national norms and standards relating to consumer protection, to provide for improved standards of consumer information, to prohibit certain unfair marketing and business practices, to promote responsible consumer behaviour, to promote a consistent legislative and enforcement framework relating to consumer transactions and agreements, to establish the National Consumer Commission, to repeal sections 2 to 13 and sections 16 to 17 of the Merchandise Marks Act, 1941 (Act No. 17 of 1941), the Business Names Act, 1960 (Act No. 27 of 1960), the

Price Control Act, 1964 (Act No. 25 of 1964), the Sales and Service Matters Act, 1964 (Act No. 25 of 1964), the Trade Practices Act, 1976 (Act No. 76 of 1976), the Consumer Affairs (Unfair Business Practices) Act, 1988 (Act No. 71 of 1988), and to make consequential amendments to various other Acts; and to provide for related incidental matters” (Government Gazette, 2012c).

2.4.7 THE HOME LOAN AND MORTGAGE DISCLOSURE ACT

The Home Loan and Mortgage Disclosure Act is regulated by the Department of Housing (PMG, 2012). It aims to promote fair lending practices, which require disclosure of information by financial institutions regarding the provision of home loans; to establish an office of Disclosure; and to provide for matters connected therewith” (Government Gazette, 2012d).

2.4.8 THE COMPETITIONS ACT

The Competitions Act is regulated by the Competition Commission (Competition Commission, 2012). The Competitions Act aims “to provide for the establishment of a Competition Commission responsible for the investigation, control and evaluation of restrictive practices, abuse of dominant position, and mergers; and for the establishment of a Competition Tribunal responsible to adjudicate such matters; and for the establishment of a Competition Appeal Court; and for related matters.” (Competition Commission, 2012).

Not all of these regulators and legislations directly influence the banking industry but still need to be taken into consideration when conducting business. The Competitions Act for example may only have an influence on the marketing and fair practise aspect of the bank, whereas the Banks Act influences the business dealings of the bank directly (Competition Commission, 2012; SARB, 2012b). There is also the Financial Services Act like FICA that has an influence on banks’ business dealings but is meant for the financial sector as a whole (Financial Intelligence Centre Act 38 of 2001, 2012). As part of the South African banking industry, banks are classified into different categories. Every category has to comply with the regulatory bodies. The different categories will be discussed in the next section.

2.5 BANKING CATEGORIES IN SOUTH AFRICA

The South African banking industry comprises a central bank (South African Reserve Bank), a few large and financially strong banks, and a number of smaller banks (South Africa.info, 2012). The industry consists of five categories, namely: registered banks which are locally controlled, registered banks which are foreign controlled, mutual banks, local branches of foreign banks, and foreign banks with approved local representative offices (The South African Banking Association, 2011). Locally controlled registered banks are those banks that are registered banks in terms of The Banks Act 1990 (SARB, 2012b). They are locally controlled and ownership can be either local or foreign. Foreign controlled registered banks are those banks that are registered banks in terms of The Banks Act 1990 (SARB, 2012b) and are foreign owned and controlled. Mutual banks are defined as “a juristic person by which the members qualify to being shareholders in that juristic person and are entitled to participate in the exercise of control in a general meeting of that juristic person and that is provisionally or finally registered as a mutual bank in terms of the Mutual Banks Act of 1993” (South African Government, 2012). These mutual banks focus mainly on bonds and mortgages, which explains their classification as mutual banks. Table 2.1 provides an overview of the banks currently operating in South Africa and the categories into which they fall.

Table 2.1: List of banks in South Africa. Category Bank Registered banks – ABSA Bank Limited; African Bank Limited; Bidvest Bank Limited; Capitec locally controlled Bank Limited; FirstRand Bank Limited; Grindrod Bank Limited; Investec Bank Limited; Nedbank Limited; Regal Treasury Private Bank Limited (in liquidation); Sasfin Bank Limited; Ubank Limited; The Standard Bank of South Africa Limited. Registered banks – Albaraka Bank Limited; Habib Overseas Bank Limited; HBZ Bank Limited; foreign controlled Islamic Bank Limited (in final liquidation); Mercantile Bank Limited; The South African Bank of Athens Limited. Mutual banks GBS Mutual Bank; VBS Mutual Bank

Table 2.1: Continued

Category Bank Local branches of Bank of Baroda; Bank Of China Limited (Johannesburg Branch – trading as foreign banks Bank Of China Johannesburg Branch); Bank of Taiwan (South Africa Branch); China Construction Bank Corporation (Johannesburg Branch); Citibank N.A.; Deutsche Bank AG; JP Morgan Chase Bank N.A. (Johannesburg Branch); Société Générale; Standard Chartered Bank (Johannesburg Branch); State Bank of India; The Hong Kong and Shanghai Banking Corporation. Foreign banks with AfrAsia Bank Limited; Banco BPI, SA; Banco Espirito Santo e Comercial de approved local Lisboa; Banco Privado Português, S.A.; Banco Santander Totta S.A.; Bank representative Leumi Le-Israel BM; Bank of Cyprus Group; Bank of India; Barclays Bank offices Plc; Barclays Private Clients International Limited; BNP Paribas Johannesburg; Commerzbank AG Johannesburg; Credit Suisse AG; Credit Suisse Securities (Europe) Limited; Ecobank; Export-Import Bank of India; Fairbairn Private Bank (Isle of Man) Limited; Fairbairn Private Bank (Jersey) Limited; First Bank of Nigeria; Fortis Bank (Nederland) N.V.; Hellenic Bank Public Company Limited; HSBC Bank International Limited; Icici Bank Limited; KfW Ipex-Bank GmbH; Lloyds TSB Offshore Limited; Millenium BCP; National Bank of Egypt; NATIXIS Southern Africa Representative Office; Royal Bank of Scotland International Limited; Société Générale Representative Office for Southern Africa; Sumitomo Mitsui Banking Corporation; The Bank of New York Mellon; The Bank of Tokyo Mitsubishi UFJ, Ltd; The Mauritius Commercial Bank Limited; The Rep. Off. for Southern and Eastern Africa of The Export-Import Bank of China; UBS AG; Unicredit Bank AG; Union Bank of Nigeria Plc; Vnesheconombank,; Wells Fargo Bank, National Association; Zenith Bank Plc Source: Adapted from The South African Banking Association (2011).

Since 2001, the banking industry has seen a decrease in the number of registered banks that remain in the industry (from 41 in 2001 to 17 in 2010). This could be attributed to global financial crises during that period (The South African Banking Association, 2011). Figure 2.2 indicates the changes that occurred between 2001 and 2010.

Figure 2.2: Number of registered banks in SA

22 20 19 19 19 19 18 17

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Source: Adapted from The South African Banking Association (2011).

The banks included in the study are registered banks which are locally controlled. They include: ABSA, FNB, Nedbank and Standard Bank, which, at the end of 2011, held 84% of the total market share. Figure 2.3 indicates the share of market assets that each of the four major banks holds based on the 84% of total market share.

Figure 2.3: Bank share of markets share based on 84% of the total market share

24% 31% R681.4 billion R880.6 billion Standard Bank

20% ABSA R568 billion Nedbank 25% R710 billion First National Bank

Source: Adapted from The South African Banking Association (2011).

2.6 THE MAJOR BANKS IN THE SOUTH AFRICAN BANKING INDUSTRY

The following section provides an exposition of the four major banks in South Africa. Although this study only looks at the four major banks, it will also briefly discuss Capitec Bank as it is gaining in market share even though it has only been in the market since 2001.

2.6.1 STANDARD BANK

The Standard Bank group is a registered bank which is locally controlled, as can be seen in Table 2.1 (The Banking Association South Africa, 2011). The Standard Bank of British South Africa was established in 1862. In 1962, when a subsidiary company was formed to conduct business dealings in South Africa and Namibia, the name Standard Bank Limited was adopted (Standard Bank, 2012a). A holding company in South Africa was established in 1969 and listed on the JSE in 1970 (Standard Bank, 2012a). Another milestone was reached in 1987 when Standard Chartered sold its remaining 39% stake in the Standard Bank Group, transferring complete ownership of the holding company to South Africa (Standard Bank, 2012a). Standard Bank offers private banking, corporate banking, investment banking, wealth management, insurance and other financial services as part of their repertoire (Standard Bank, 2012a).

In 1988 the bank re-established its links with Africa by opening up branches in Swaziland and Botswana (Standard Bank, 2012a). Since then the bank has grown and has interests in Kenya, Uganda, Zaire, Zambia, Zimbabwe, Ghana, Nigeria, Jersey, the Isle of Man, Hong Kong, Malawi, Uganda, Russia, Brazil, Mozambique, Angola, Argentina, and Turkey (Standard Bank, 2012a).

Standard Bank currently has 52 127 employees operating across 1 222 branches and service centres, and 6 770 automated teller machines (Standard Bank, 2012b). The bank is focusing on targeting individuals earning more than R100 000 per year (Kamhunga, 2011). In addition, Standard Bank has about R880.6 billion of the share in market assets, which relates to 31% of the total market share (The South African Banking Association, 2011). This effectively makes Standard Bank the largest bank in South Africa as well as in Africa.

2.6.2 ABSA (AMALGAMATED BANKS OF SOUTH AFRICA LIMITED)

ABSA Bank is classified as a registered bank which is locally controlled, as is evident in Table 2.1 (The Banking Association South Africa, 2011). In 1991 ABSA, which was then known as Amalgamated Banks of South Africa Limited, was established through the merger of UBS Holdings, the Allied and Volkskas Groups, and certain interests of the Sage Group (ABSA, 2012). In 1992, ABSA acquired TrustBank, Senbank, and Bankfin, which at the time fell under the Bankcorp Group (ABSA, 2012). In 1997 the name “Amalgamated Banks of South Africa Limited” was changed to ABSA Group Limited and hence the abbreviation ABSA (ABSA, 2012). A UK based bank, Barclays Bank, acquired a majority stake of 55.5% in ABSA in 2005 as part of their drive to expand into international markets (ABSA, 2012). Currently ABSA conducts the majority of its business in South Africa and also has equity holdings in banks in Tanzania and Mozambique, representative offices in Namibia and Nigeria, and bancassurance operations in Botswana and Mozambique (ABSA, 2012).

The ABSA Group Limited, which is listed on the JSE, is one of South Africa’s largest banks, offering an array of services including retail, business, corporate and investment banking, insurance, and wealth management solutions (ABSA, 2012). In December 2011 ABSA boasted 718.2 million shares in issue and a market capitalisation of R101.27 billion (ABSA, 2012). At the same time ABSA had assets in excess of R786.7 billion and 12.1 million customers (ABSA, 2012). This, according to a study by the South African Banking Association, equates to about 25% of the total market share, which, in terms of assets, makes ABSA the second largest bank in South Africa after Standard Bank (The Banking Association South Africa, 2011). The group’s 12.1 million customers are serviced by 9 541 automated teller machines and 35 200 employees across head office and all its branches (ABSA). Currently ABSA is targeting customers earning more than R100 000 per year (Kamhunga, 2011).

2.6.3 FNB (FIRST NATIONAL BANK)

FNB is a registered bank which is locally controlled, as is evident in Table 2.1 (The Banking Association South Africa, 2011). In 1987, FNB emerged as a wholly South African owned and controlled entity (FNB, 2012). Its origins, however, can be traced back to 1838 with the establishment of the Eastern Province Bank in Grahamstown (FNB, 2012). In 1998, when Rand Merchant Bank Holdings and Anglo-American merged to form FirstRand Limited, FNB became

a wholly owned subsidiary of FirstRand and is currently trading as a division of FirstRand Bank Limited (FNB, 2012). FNB is also well-established beyond the borders of South Africa. The three largest subsidiaries are FNB Swaziland, Botswana, Namibia, Mozambique, and Zambia (FNB, 2012). FNB also recently opened a retail bank in Mumbai (Kamhunga, 2012).

The FNB Group is listed on the JSE and offers services such as personal, commercial and corporate banking, insurance, and wealth and asset management solutions to more than 6 million customers through 734 branches, 6 311 automated teller machines, and 28 510 employees (FNB, 2012). FNB boasts R681.4 billion in assets, which gives them a relative market share of roughly 24% and makes them the third largest bank in South Africa (The Banking Association South Africa, 2011). FNB’s current marketing strategy is targeting customers earning over R100 000 per year with their gold account offerings (Kamhunga, 2011).

2.6.4 NEDBANK

The Nedbank group is classified as a registered bank which is locally controlled, as can be seen in Table 2.1 (The Banking Association South Africa, 2011). The origins of Nedbank can be traced back to the 1830’s, although in 1888 the NBCV (Nederlandsche Bank en Credietvereeniging voor Zuid-Afrika) was founded and later changed its name to the NBZA in 1903 (Nedbank, 2012a). In 1925, the NBZA merged with the then established Transvaalsche Bank en Handelsvereeniging, and another name change to NBSA (Netherlands Bank of South Africa) occurred in 1951 (Nedbank, 2012a). In 1971 the NBSA changed its name to Nedbank and in 1973 the Nedbank Group was formed as a result of the merger of Syfrets South Africa, Union Acceptances, and Nedbank (Nedbank, 2012a) The bank has been listed on the JSE since 1969 (The Banking Association South Africa, 2012b).

As part of their business dealings, Nedbank assists clients with everyday banking needs such as private banking, wealth and investment management, corporate and business banking, insurance, and other services (Nedbank, 2012a). Nedbank is not limited to the South African borders but has representative offices in Canada and subsidiaries in Europe, Namibia, Lesotho, Swaziland, and Malawi (Nedbank, 2012b). The group boasts a R568 billion share of the market assets, which effectively makes it the fourth largest bank in South Africa (The Banking Association South Africa, 2011). In 2011 Nedbank showed excellent growth with a 26.2% increase in headline earnings, a 25.4% increase in diluted headline earnings per share, and a

10.8% increase in tangible net-asset value per share (Nedbank, 2012b). Nedbank currently has 28 494 employees stretching across more than 1 000 branches (Nedbank, 2012c). The group changed their focus to targeting individuals earning more than a R100 000 per year (Kamhunga, 2011).

2.6.5 CAPITEC BANK

Although the four major banks in South Africa discussed above will be included in the study because they offer customer relationship efforts as part of their marketing (which will be further discussed in Chapter 4), Capitec Bank also warrants mention due to the strides made by this bank in the current market (Pitman, 2011). Capitec Bank is a relative newcomer to the South African banking industry with its inception in 2001. It is also a locally controlled registered bank (Capitec Bank, 2012; The Banking Association South Africa, 2011). Although this bank can be classified as a new entrant, it has certainly gained some market share over recent years and is increasingly putting pressure on the major banks to decrease their bank costs in order to retain lower income customers. Capitec Bank is attracting more than 25 000 new customers per month due to its low cost banking (Jones, 2006). Capitec Bank targets the lower- to middle- income groups focussing on LSM 3 – 7. That is, households earning between R1 200 and R6 700 per month (Jones, 2006). According to Jones (2006), the other four major banks declared that it was impossible to make profits on the lowest income segments in South Africa, and yet Capitec has proven them wrong by focussing on the majority of the population rather than on the minority. At the time, the target market included 19 million potential customers which comprised about 60% of the population.

In 2007, Capitec Bank illustrated that the bank is on a strong growth path. Headline earnings in that same year grew by 15% and the return on equity stood on a solid 21% (Whitfield, 2007). Client numbers jumped by 39% to around 1 million customers in 2007 and staff members grew by 25% (Bruce Whitfield, 2007). During the same period, Capitec’s transaction fee income rose by 239% year on year (Whitfield, 2007).

Capitec listed on the JSE in 2002 and shares were obtainable from just two R2 per share. At the end of 2011, shares could be obtained at R173 per share (Pitman, 2011). The bank currently holds 5 331 fulltime employees spread across its 400 branches (PWC, 2011). In June 2009,

Capitec revealed that it had 2 million customers that were served by 360 branches throughout South Africa (Finweek, 2009).

Capitec based its original business model on the four needs the target market required at the time which include: affordability (Capitec Bank makes use of an aggressive pricing strategy ensuring that all bank charges are less than half of those of its four major rivals); accessibility (this means staying open till seven o’clock at night at some branches and being open 24 hours a day at certain mines to accommodate shift workers); simplicity (Capitec makes use of open platform with Windows front end which allows for a paperless system); and personal/customer service (which includes being available when and where a customer requires, being polite, and so on) (Pitman, 2011; Jones, 2006). It can thus be noted that Capitec Bank focuses on providing basic banking services to the lower end of the market.

An investigation into the four major banks proves that all four banks provide relationship bankers as part of their service offering whereas Capitec Bank does not. These relationship bankers are, however, targeted at higher income groups, thus making it feasible for the banks to engage in relationships. Since Capitec Bank focuses on a lower income group it would not be sensible for them to engage in long-term personalised relationships with customers because profitability per customer would then be minimised (Jones, 2006). Based on an ABC analysis of customer profitability, this implies that Capitec Bank does not focus on customer relationships as intensively as the other four major banks and will therefore not be included in this study.

2.7 CONCLUSION

In conclusion, the South African financial sector is a very healthy and well-regulated sector which contributes significantly to the South African economy. The banking industry forms part of this bigger financial sector. Despite the economic recession in 2009 which resulted in consumer affordability being lower (The Banking Association South Africa, 2011), the banking industry has shown increasing profits year on year even in the midst of the financial crisis. This makes the banking industry very lucrative for investments, both for local as well as foreign investors.

The industry is dominated by the four major banks (Standard Bank, ABSA, FNB and Nedbank) which are the main focus of the study as they control 84% of the total market share. Capitec

bank will soon be considered a major role player in the South African banking industry but due to its lack of relationship building, it is not included in this study.

The next chapter considers how customer expectations can influence customer satisfaction and loyalty. The chapter will also place emphasis on the current situation in the South African banking industry in order to determine whether customers are satisfied with the current situation and whether they remain loyal to the banking institution.

CHAPTER 3 CUSTOMER EXPECTATIONS, SATISFACTION AND LOYALTY

3.1 INTRODUCTION

Organisations need to provide higher levels of customer service since customers have become more demanding in terms of their expectations of services rendered (Tsai & Su, 2009:1779). These demanding customers come with sets of expectations that they want met or even exceeded. This has led to the need for organisations to perform over and above their standard processes and procedures in order to keep customers satisfied and loyal (Awan, Bukhari & Iqbal, 2011:203-204). The importance of customer satisfaction stretches beyond profit in that it contributes to the long-term sustainability of organisations and increases customer loyalty and retention (Hariharan, Bezawada & Talukdar, 2012:77). In order to increase customer satisfaction and loyalty, organisations should thus place emphasis on exceeding customer expectations rather than just meeting them due to competitive threats and more demanding customers.

This chapter will look at customer expectations and the influence different factors have on these expectations. It will also consider the Gaps model of service quality which is influenced by customer and organisational expectations of service levels. The focus will then shift to customer satisfaction, the link between satisfaction and customer expectations, the advantages of customer satisfaction, and methods of improving customer satisfaction. The chapter will also describe customer loyalty, the links between loyalty and satisfaction, and the advantages and disadvantages of loyalty. Finally, customer expectations, satisfaction, and loyalty in the South African banking industry will be discussed. It should be noted that this chapter is presented from a services marketing perspective.

3.2 CUSTOMER EXPECTATIONS

Customer expectations can be identified as an influencing factor in determining whether a customer is satisfied or dissatisfied with a service offering (Zeithaml et al., 2009:76). This section will provide a discussion of what customer expectations are as well as the factors

influencing customer expectations. As part of the discussion, the Gaps model of service quality will be discussed since it influences the level of customer expectations.

3.2.1 DEFINING CUSTOMER EXPECTATIONS

Leventhal (2008:51) defines customer expectations as the standards customers use to evaluate the attractiveness and desirability of the service experience and outcome. Additionally, customer expectations can be defined as the beliefs about service delivery that serve as reference points for customers whereby organisational performance is measured (Zeithaml et al., 2009:76).

From the above definitions it can be noted that customer expectations include the standards that customers set for the service experience and how organisations can measure performance. According to Leventhal (2008:51), these standards include:  An ideal standard or subjective norm for the customer whereby customers have certain set service standards that they want to be met or exceeded by the organisation; and  A relationship standard based on the overall experience a customer had from previous service encounters with the organisation. Using these standards as a point of leverage, customers will then have an ideal level of expectation and a minimum level of expectation which is referred to as the zone of tolerance (Zeithaml et al., 2009:76).

For organisations to be able to identify customers’ levels of expectations, it is important that they identify the factors that will influence whether customer expectations are merely met or exceeded.

3.2.2 FACTORS INFLUENCING CUSTOMER EXPECTATIONS

Leventhal (2008:51) and Lankton and Wilson (2007:88-92) state that customer expectations can be formed by various factors, namely: marketing communication or advertising, the image the customer holds of the organisation, word of mouth spread by customers, self-efficacy, and the participation of customers in the service delivery process.

3.2.2.1 MARKETING COMMUNICATION OR ADVERTISING

Marketing communication is organisation-specific and focuses on all communications and advertising in which the organisation engages (Leventhal, 2008:51). An example would be a service organisation such as a bank placing an advertisement on radio about a new service offering. This advertisement would include certain promises like, “apply for a loan now and only start paying in three months’ time”. Based on these promises, customers then form certain expectations resulting in their unwillingness to settle for anything less (Leventhal, 2008:51).

3.2.2.2 THE IMAGE THE CUSTOMER HOLDS OF THE ORGANISATION

Balmer (2011:1336) defines organisational image as the perception customers hold of an organisation. These perceptions are formed by various factors such as the organisation’s reputation, the quality of the services offered by the organisation, and the organisation’s history (Minkiewicz, Evans, Bridson, & Mavondo, 2011:192). Based on the perceptions customers hold of these factors, they will form an image of the organisation which will then be the basis of the expectations customers have of the services they expect to receive from the organisation (Minkiewicz et al., 2011:192). The image customers hold could be positive, negative or neutral. An example would include the image customers form of a bank that has been investigated for fraud or for misleading customers. This would most likely result in customers having a negative image of the bank and thus the lowering of their expectations pertaining to services offered by the bank.

3.2.2.3 WORD OF MOUTH SPREAD BY CUSTOMERS

Padma, Rajendran and Sai (2009:168) state that word of mouth refers to the recommendation (positive word of mouth) or non-recommendation (negative word of mouth) that customers spread to others regarding their experiences of an organisation’s products or services. When customers engage in positive word of mouth with others, they form expectations of the organisation based on what other customers have stated about their experiences (Padma et al., 2009:167). For example, a customer who has had a good experience using a bank’s online Internet banking system would spread positive word of mouth to others about his/her experience. This would create a situation where others, who have heard about the positive experience, will generate higher expectation levels when they interface with the online Internet

banking system. This indicates that positive word of mouth generates higher expectation levels, while negative word of mouth creates lower expectation levels (Padma et al., 2009:167).

3.2.2.4 SELF-EFFICACY

Lankton and Wilson (2007:89) define self-efficacy as the ability of a customer to perform certain actions (withdrawing cash from an ATM versus applying for a home loan) in order to obtain a performance from an organisation (receiving cash from an ATM or being approved for a home loan). If a customer has the capability to perform the action required without assistance from staff at the organisation, customers will have lower expectation levels (Lankton & Wilson, 2007:89).

3.2.2.5 PARTICIPATION OF THE CUSTOMER IN THE SERVICE DELIVERY PROCESS

Participation, in this case, is defined as the joint contribution of the customer and the staff of the organisation to the service delivery process (Lankton & Wilson 2007:90). The level of participation will influence an individual’s level of expectations, where higher levels of participation or interaction between the customer and staff leads to a customer’s higher expectation levels (Lankton & Wilson 2007:90). An individual opening a bank account, for example, is not able to open the bank account on his/her own but rather requires the assistance of a banker. The customer then has certain expectations that are met if the banker manages to open the account for the customer.

The factors discussed above therefore influence the level of expectations that customers have pertaining to the services organisations provide. Zeithaml et al. (2009:32-33) state that the expectation levels of customers also influence their perception of the quality of services actually provided by organisations. For this reason, it is important to look at the Gaps model of service quality, which is influenced by customer expectations.

3.2.3 THE GAPS MODEL OF SERVICE QUALITY

Zeithaml et al. (2009:32-33) explain that the Gaps model of service quality provides insight into areas where possible gaps could occur (which influence the customers’ perception of the quality of services received) in the actual delivery of services. These gaps influence customer

expectations and in closing or minimising these gaps, organisations can obtain many benefits such as excellent service design, customers fulfilling their roles in service, increased market share and higher customer satisfaction (Zeithaml et al., 2009:32-33; Boshoff & Du Plessis, 2009:49-51). The Gaps model of service quality as illustrated in Figure 3.1, consists of five gaps divided into four gaps influenced by the organisation (namely, the listening gap, the service design and standards gap, the service performance gap, and the communication gap) as well as one gap influenced by the expectations and perceptions of the customer. When the four organisational gaps are minimised the result will be a decrease in the customer gap (Boshoff & Du Plessis, 2009:49-51).

Figure 3.1: Gaps model of service quality by combining the customer as well as organisation gaps

Expected Service

Gap 5: Customer Gap

Perceived Service

Organisational Gaps Communications Service Delivery to Customers

Gap 3: Performance Gap Gap 4: Communication Customer-driven Service Gap Designs and Standards

Gap1: Listening Gap Gap 2: Service Design and Standards Gap Company Perceptions of Customer Expectations

(Source: Adapted from Zeithaml et al. (2009:43).

3.2.3.1 GAP 1: THE LISTENING GAP

Cant, Strydom, Jooste and Du Plessis (2006:308) define the listening gap as the difference between the customer expectations of a service (which is dependent on a customer’s personal needs, past experiences, and word of mouth communication) and the organisation’s understanding of those expectations. Boshoff and Du Plessis (2009:48) state that to close this gap the most crucial element for an organisation is to know what the customer needs and expects rather than to predict what the customer might expect. This can be achieved by listening to the customer by, for example, conducting customer satisfaction surveys. The way in which organisations listen to customer needs will influence whether customer expectations are met after the service delivery process.

3.2.3.2 GAP 2: THE SERVICE DESIGN AND STANDARDS GAP

Boshoff and Du Plessis (2009:49) describe this gap as being the organisation’s understanding of customer needs and expectations and then designing services based on this understanding rather than on actual customer needs and expectations. This gap is increased if organisations do not close Gap 1 and determine actual customer needs and expectations (Zeithaml et al., 2009:36-37). In closing this gap, Boshoff and Du Plessis (2009:50) suggest that management and front-line employees must pursue the same standards of service delivery expected by the customer and not the standards determined by organisation.

3.2.3.3 GAP 3: THE SERVICE PERFORMANCE GAP

This gap is the difference between the service design standards (as set in Gap 2) and the actual delivery of the service (Sharabi & Davidow, 2010:191). In other words, this is the difference between what the service should and does look like. The larger the gap, the more negatively customer expectations will be influenced. Boshoff and Du Plessis (2009:50) state that this gap is often caused by unrealistic service standards being set and which cannot be met during actual service delivery. To close this gap, Boshoff and Du Plessis (2009:50) suggest that organisations should improve internal communications, develop more comprehensive solutions to problems, and empower employees to take action and make on-the-spot decisions. It is also necessary for front-line staff to report back to management and back-line staff about where and why service delivery problems are occurring (e.g. due to unrealistic standards being set).

3.2.3.4 GAP 4: THE COMMUNICATION GAP

The communication gap is the difference between the services that will be delivered (as communicated to the customer through external communications and media) and the quality of the actual services delivered (Sharabi & Davidow, 2010:191). The more promises made in external communications, the more the level of customers’ expectations will increase. Sharabi and Davidow (2010:191) thus suggest that organisations develop communications that reflect realistic expectations which can be delivered and implement strategies that deliver consistent messages to customers. Boshoff and Du Plessis (2009:51) suggest that to close the gap, organisations should refrain from over-promising. This would result in customers not forming higher expectations of the service than usual, which makes it easier for organisations to meet expectations.

3.2.3.5 GAP 5: THE CUSTOMER GAP

The fifth gap focuses on the customer and is referred to as the customer gap. Figure 3.1 indicates that the customer gap is the gap between that which the customer expects and the customer’s perception of what is actually delivered by the organisation. This gap is minimised or closed when the customer’s perception of the service delivered meets or exceeds their initial expectations, while the gap is increased when expectations are not met (Zeithaml et al., 2009:43). The smaller the gap, the greater the possibility of meeting customer expectations. The greater the gap, the greater the possibility of not meeting customer expectations.

By closing or minimising the gaps, as discussed above, customer expectations can be met or exceeded (Boshoff & Du Plessis, 2009:48). This leads to a level of customer satisfaction. The next section will provide a discussion of customer satisfaction.

3.3 CUSTOMER SATISFACTION

This section provides a discussion of the link between customer expectations and satisfaction. Thereafter, a description of customer satisfaction and its importance to the organisation will be discussed, and the factors influencing customer satisfaction will be provided. The methods of improving customer satisfaction as well as the steps in attaining and measuring satisfaction will be mentioned.

3.3.1 LINK BETWEEN CUSTOMER EXPECTATIONS AND CUSTOMER SATISFACTION

Before the link between customer expectations and satisfaction can be made, it is important to note the relationship between service quality (as suggested in the Gaps model of service quality) and customer satisfaction. Siddiqi (2011:17) states that many authors debate the relationship between service quality and customer satisfaction. Some state that the two variables are complete opposites while others say that service quality is the antecedent of customer satisfaction. Recent studies, however, confirm the latter to be true. Zeithaml et al. (2009:32) state that no matter which viewpoint is taken, it is clear that there is a relationship between customer expectations and this influences the level of service quality experienced as well as customer satisfaction. One way of indicating the link between customer expectations and satisfaction is by considering the disconfirmation paradigm as illustrated in Figure 3.2. The disconfirmation paradigm explains how customers’ expectations and actual service delivery performance influence customer satisfaction levels.

Figure 3.2: The disconfirmation paradigm

Performance (p) Expectations (e)

Comparison

p > e p = e p < e

Positive Confirmation Negative Confirmation Confirmation

Satisfaction Satisfaction Dissatisfaction

(Source: Adapted from Lamb et al., 2010:5).

From Figure 3.2 it can be seen that customers compare the performance (p) of the organisation (pertaining to the actual services delivered) to their expectations (e) in order to determine their levels of satisfaction. When performance (p) exceeds expectations (e), customers tend to be satisfied/very satisfied (Lamb et al., 2010:5). When performance (p) is equal to expectations (e), customers tend to be satisfied, which indicates that expectations have been met, but not exceeded. When performance (p) does not exceed expectations (e), dissatisfaction takes place, which indicates that customers are unhappy with the services provided by the organisation. The following section provides greater insight into the concept of customer satisfaction.

3.3.2 DEFINING CUSTOMER SATISFACTION

In its simplest form, as defined by Lamb et al. (2010:5), customer satisfaction occurs when a product or service exceeds or meets customers’ expectations.

Additionally, other authors define customer satisfaction as:  A customer’s fulfilment response in that the service received provides a pleasurable level of experience (Zeithaml et al., 2009:104);  The positive evaluation of a customer after buying an organisation’s services (Alhemoud, 2010:333); and  The perceived performance of the service rendered relative to the customer’s expectations. When these performance perceptions exceed expectations, the customer is said to be satisfied (Kotler et al., 2010:27).

Customer satisfaction, however, cannot always be guaranteed, and there will be instances where customer dissatisfaction occurs. Mahapatra, Kumar and Chauhan (2010:99) define customer dissatisfaction as a situation where customer experiences and organisational performance fall short of customers’ expectations. Lapre and Tsikriktsis (2006:352) define customer dissatisfaction as the situation in which customers’ expectations exceed their perceptions after the service has been delivered. These definitions therefore also indicate the link between customer expectations and dis/satisfaction.

Hume and Mort (2010:173-174) and Cant et al. (2006:315) opine that there are two basic approaches in attempting to define customer satisfaction. The first is that customer satisfaction is the end result of a single experience (transactional satisfaction). The second is that customer

satisfaction represents a process in terms of what the customer received for what he/she gave up during all his/her encounters with the organisation (overall satisfaction). In terms of transactional satisfaction, the focus is on the satisfaction levels that customers experience during a specific transaction. For example, a customer needing to collect a debit card from his/her bank (Hume & Mort, 2010:173-174). Overall satisfaction, however, focuses on the customer’s overall experience with all the encounters the customer has had with the organisation rather than just a single transaction. It can therefore be viewed as a process (Hume & Mort, 2010:173-174).

Throughout the rest of this study, it should be assumed that when customer satisfaction is mentioned, it refers to overall satisfaction and not just transactional satisfaction. The next section will include a discussion of why overall satisfaction is so important to the organisation.

3.3.3 IMPORTANCE OF CUSTOMER SATISFACTION

Yen, Chung and Tsai (2007:1) state that when organisations focus on meeting customer needs and expectations during service encounters, it could lead to certain levels of customer, satisfaction which has certain benefits. These benefits are indicated in Table 3.1.

Table 3.1: The benefits of customer satisfaction Authors Benefits Yen et al. (2007:1)  High levels of customer loyalty;  Good organisational reputation;  Market share increases;  Reductions in the number of complaints. Hoffman, Bateson, Wood  Positive word of mouth from existing customers which and Kenyon (2009:369-373) often translates into new customers;  Satisfied customers will make use of the organisation’s services more often and are less likely to consider competitor offerings;  Organisations with high satisfaction ratings often insulate themselves from competitive pressures;

Table 3.1: Continued

Authors Benefits Dimitriadis (2010:299)  Loyalty;  Long term profitability;  Sales growth.

Taking the benefits indicated in Table 3.1 into consideration, it should be noted that customer satisfaction is important as it influences customer loyalty, word of mouth recommendations and organisational profitability (Dimitriadis, 2010:299). The satisfaction-profitability link (i.e. high levels of customer satisfaction will lead to increased levels of organisational profitability and low levels of customer satisfaction will lead to decreased levels of profitability) is much greater for services than it is for products. The reason for this is that services are measured based on the service encounter which could affect the overall level of satisfaction. This indicates that customer satisfaction levels have an important and positive influence of organisational profitability (Srijumpa, Chiarakul & Speece, 2007:174).

The importance of customer satisfaction cannot be overstated because of these benefits and the fact that it ensures the longevity of organisations. Without customers, service organisations have no reason to exist (Hoffman et al., 2009). The next section will focus on the factors influencing customer satisfaction and dissatisfaction.

3.3.4 FACTORS CONTRIBUTING TO CUSTOMER SATISFACTION AND DISSATISFACTION

Different factors in service contexts can either lead to customers being satisfied or customers being dissatisfied. The following sections will include discussions of the factors contributing to customer satisfaction or dissatisfaction.

3.3.4.1 FACTORS CONTRIBUTING TO CUSTOMER SATISFACTION

Srijumpa et al. (2007:177) mention that certain factors contribute to customers being satisfied with a service offering. These factors are all from an organisational perspective and include:

 Employees responding to customer needs and requests: This includes employees’ willingness and ability to respond to customer needs and special requests in a time-considerate manner (Srijumpa et al., 2007:177). Since customers have certain levels of expectations, as previously mentioned, they expect service organisations to respond to their needs. Responding to these needs in a standard procedural manner may only be enough to meet customer expectations. However, if the organisation wishes to increase customer satisfaction, they need to go beyond merely responding to customer needs and requests, as explained in the next section (Srijumpa et al., 2007:177).

 Employees spontaneously delighting customers: This factor builds on the previous factor mentioned, but incorporates performing over and above the standard norm (Srijumpa et al., 2007:177). Employees spontaneously delighting customers include those actions or activities of employees that are not expected by customers but are perceived very positively by the customers (Srijumpa et al., 2007:177).

 Employees responding to service failures: In order to ensure customer satisfaction, employees need to rectify situations in which service failure occurs. Parasuraman, Zeithaml and Berry (1988) (in Suk et al., 2009:40) state that a service failure occurs when the outcome of a service does not meet customers’ expectations or zone of tolerance, with the outcome being dissatisfaction. Some organisations even consider service failure a means to better satisfy a customer. This is referred to as the service recovery paradox, according to Zeithaml et al. (2009:215). The service recovery paradox works on the principle that an organisation willingly or accidentally causes a service failure so that it can rectify the failure in such a significant way that the customer is even more satisfied than s/he would have been had the failure not occurred (Zeithaml et al., 2009:215).

3.3.4.2 FACTORS CONTRIBUTING TO CUSTOMER DISSATISFACTION

In terms of the factors contributing to dissatisfaction, Srijumpa et al. (2007:177-178) list the factors which oppose those discussed above, together with other factors that contribute to dissatisfaction. These factors, from an organisation’s perspective, include:

 Technology failure: Technology failure includes all technology-driven equipment not performing as it should (Srijumpa et al., 2007:177-178). In the context of this study this could include platforms such as online banking, mobile banking, defective ATMs, and all technology-driven aspects within the banking industry. Customers expect these technologies to work; however, when they encounter problems, customer expectations are not met and dissatisfaction occurs (Srijumpa et al., 2007:177-178).

 Service design failures: Services so designed that they do not create an efficient and effective flow contribute to service design failures (Srijumpa et al., 2007:177-178). In the banking context, an example would be a customer applying for a home loan at a bank and being constantly sent around to different departments. These design service failures result in dissatisfaction because customer expectations are not met.

 Process failures: Process failures include a breakdown in the follow-up process after interaction with a customer has taken place (Srijumpa et al., 2007:177-178). For example, a bank consultant may forget to follow up with a client. Organisations may lose customers due to customer dissatisfaction if customers experience service failure during the initial service (which could have been rectified had there been no process failure) (Srijumpa et al., 2007:177-178).

When organisations do not focus on customer satisfaction, they do not just forgo some of the benefits, but it could also involve certain risks for the organisation. These risks, according to Albrecht and Zwenke (1985) (in Hoffman et al., 2009:368-369) and Yen et al. (2007:1), include customer complaints, customer losses and a loss of market share. Casado, Nicolau and Mas (2010:32) state that many organisations direct their long-term strategies towards increasing

customer satisfaction and loyalty through increasing the service quality. However, even for the best of service organisations, failures and mistakes cannot be avoided completely.

To avoid the factors that contribute to dissatisfaction, methods of improvement should be considered. The next section will look at the methods of improving customer satisfaction or recovering from a service failure.

3.3.5 METHODS AND PROCEDURES OF IMPROVING CUSTOMER SATISFACTION

As customer dissatisfaction can negatively affect an organisation, it is important to consider methods and procedures to improve customer satisfaction levels. There are no set criteria for improving customer satisfaction. However, Nguyen and Leclerc (2011:356) and Boshoff and Du Plessis (2009:210-218) suggest that for organisations to contribute to overall customer satisfaction, management should to do the following:

3.3.5.1 HIRE THE RIGHT PEOPLE

It should be the responsibility of the Human Resource Department to hire employees who tend to provide good customer service and satisfy customer needs (Boshoff & Du Plessis, 2009:210- 218). Crain (2009:37) states that hiring the right people results in employees becoming one of the organisation’s main assets. Since frontline employees are basically the “face” of the organisation, it is very important for organisations to hire the right people because these employees deal directly with customers. These employees then serve as a competitive advantage for the organisation.

3.3.5.2 DELIVER SERVICE QUALITY THROUGH TRAINING AND EMPLOYEE DEVELOPMENT

The organisation should make provision for sending employees for training and development in delivering quality customer service (Boshoff & Du Plessis, 2009:211). Crain (2009:35) states that for organisations to implement successful strategies, employees require knowledge, training and development in providing excellent customer service. This is particularly valuable for new employees. However, it must also be noted that certain employees require training in

certain fields. For example, call-centre staff specifically require systems training (Crain, 2009:35).

3.3.5.3 EMPOWER PEOPLE TO MAKE DECISIONS AND ACT ON THE SITUATION

Nguyen and Leclerc (2011:356) suggest that managers of financial institutions should empower their employees to make on-the-spot decisions so as to enhance customer satisfaction and increase prompt service. Customers are likely to be more satisfied with employees and the organisation if decisions can be made immediately rather than having to wait for feedback from management time after time.

3.3.5.4 ENCOURAGE TEAM WORK

Boshoff and Du Plessis (2009:216) state that managers must encourage teamwork to ensure the synergy and integration of employees. Teamwork is an important part in the effective running of an organisation as it can contribute significantly to the overall success of the organisation (Cacioppe & Stace, 2009:220). Since teamwork also creates synergy between departments in a variety of ways, it can also contribute to the overall effectiveness and efficiency of the organisation. In effect, this can influence customer satisfaction because customers’ needs are then better met and higher levels of service quality are obtained (Cacioppe & Stace, 2009:220).

3.3.5.5 PROVIDE THE NECESSARY SUPPORT SYSTEMS

For organisations striving to improve customer satisfaction, the necessary support systems must be provided to bottom-line employees. As employees are the direct link between customers and the organisation, it is important for management to support these bottom-line employees in delivering quality service. Worley and Doolen (2006:231) suggest that management support is so crucial that the non-existence of it can, intentionally or unintentionally, be damaging for the organisation. These support systems might include access to client accounts, online access to perform tasks quicker, and management presence.

From these abovementioned methods, it is evident that in addition to customers, employees also have to be satisfied in order to provide services to customers that are satisfactory.

Hellawell (2012:3) states that satisfied employees ensure satisfied customers. In considering these methods, organisations should combine them with the right procedures in attaining customer satisfaction. Different authors suggest different procedures in attaining customer satisfaction, as indicated in Table 3.2.

Table 3.2: Procedures in attaining customer satisfaction Cant et al. (2006:315)  Communicate with customers;  Manage the overall experience;  Handle complicated situations in a dignified manner;  Cultivate a service culture throughout the whole organisation;  Learn how to implement and control service processes. Vaughn (2003:22-24)  Educate employees (on the importance of customer satisfaction and on their role in customer satisfaction);  Recognise the right factors (in terms of measuring and implementing efficient and effective customer satisfaction processes);  Focus rewards (rewarding those individuals who contribute to overall customer satisfaction). Mark and Zen  Participate in customer satisfaction committees to share information (2007:22-24) and ideas about satisfying customer needs;  Focus on customer complaints to determine what it is that they are not satisfied with;  Set achievable customer satisfaction goals;  Involve staff in implementing satisfaction strategies;  Identify key areas of performance in terms of high, medium and low performers;  Follow up on customer queries without fail.

From Table 3.2 it can be noted that although there are no set lists of procedures to follow to ensure customer satisfaction, there are certain elements that come to the fore. These include: communication, handling customer complaints, organisation-wide customer service culture, and providing customers with value that should be measured and evaluated (Cant et al., 2006:315; Vaughn, 2003:22-24; Mark & Zen, 2007:22-24).

In addition, having the necessary procedures to attain customer satisfaction requires quality measurement instruments (Kotler & Keller, 2006:146). The next section focuses on the

necessity for measurement instruments in enabling an organisation to measure satisfaction and to implement necessary changes where needed.

3.3.6 MEASURING CUSTOMER SATISFACTION

Kotler and Keller (2006:146) suggest there are various ways in which organisations can measure overall customer satisfaction. These measures include:

3.3.6.1 PERIODIC SURVEYS

Periodic surveys can be used both to track customer satisfaction directly and, with the use of additional questions, to determine repurchase intentions and the likelihood of customer recommendation. Yen et al. (2007:2), however, suggest that organisational surveys can be seen from the organisation’s point-of-view and not necessarily the customer’s point-of-view. An example of this is a service organisation that only focuses on their strong points in a survey and does not include areas in which they fall short. The customer will then only be able to comment on the strong points and this will indicate a false level of overall customer satisfaction.

3.3.6.2 MONITORING CUSTOMER LOSS OR DEFECTION RATES

The second method that organisations can use to measure customer satisfaction is the monitoring of the customer loss or defection rate. This is used to determine how many customers are lost per annum (Wright & Riebe, 2010:860). However, although these do indicate customer losses, they do not provide the organisation with the reasons behind customer loss. It is, however, important to note that although certain customers do not defect, it does not necessarily mean that they are satisfied with the organisation and its services (I-net Bridge, 2011).

3.3.6.3 MYSTERY SHOPPERS

Kotler and Keller (2006:146) suggest that organisations should employ mystery shoppers who pose as potential users of the services. Zeithaml et al. (2006) (in Pinar, Eser & Strasser, 2010:8) state that mystery shoppers are trained in the criteria important to the customers of the organisation. The authors mention that mystery shoppers deliver objective assessments about

the service they receive by completing questionnaires on service performance. Yen et al. (2007:2) suggest that managers can continuously improve and achieve customer satisfaction by systematically measuring customer satisfaction to identify certain areas of improvement. To receive the relevant information, a combination of more than one of the abovementioned measurements must be completed (as opposed to merely one).

Organisations can choose any or a combination of the abovementioned methods to measure customer satisfaction, but to include transactional and overall satisfaction measurements, organisations should make use of more than one of these measurements (Hume & Mort, 2010:173-174). The next section focuses on customer loyalty as one of the benefits or outcomes of customer satisfaction.

3.4 LOYALTY

Customer loyalty is one of the most important factors for every organisation to consider. This section begins by discussing the link between customer satisfaction and loyalty and then further defines customer loyalty as well as the different types of loyalty. A discussion then follows on the outcomes of customer loyalty.

3.4.1 LINK BETWEEN CUSTOMER SATISFACTION AND LOYALTY

Yen et al. (2007:1) suggest that one of the outcomes of customer satisfaction is customer loyalty. Based on this, it can be said that a clear connection exists between the two concepts in which satisfaction is the antecedent of loyalty. This, however, does not ensure that all satisfied customers will remain loyal. It also does not mean that dissatisfied customers will defect from the organisation. Johnston and Marshall (2010:74) opine that customers who describe themselves as satisfied are not necessarily loyal. This is based on estimation that 60% to 80% of customers who proclaim that they are satisfied with an organisation eventually become defectors (i.e. they move to a competing organisation). Although this is perhaps true for most organisations, it should be taken into account that customers who choose to become defectors do so not by random choice, but rather because of improved competitor offerings, a change in customer requirements, and/or other influential factors (Johnston & Marshall, 2010:74). It is important to note that satisfied customers do not necessarily stay with organisations forever, but

instead continuously evaluate the service offerings in terms of competitive offerings (Boshoff & Du Plessis, 2009:319-320).

3.4.2 DEFINING CUSTOMER LOYALTY

Cant et al. (2006:312-313) define customer loyalty as those customers who insist on a particular brand or service and will go to extreme lengths to acquire it. These customers should be retained as they hold great benefit for the organisation. Other definitions of loyalty are provided below.  Boshoff and Du Plessis (2009:319) define customer loyalty as the willingness of a customer to keep buying from the same service provider over the long term.  Oliver (1999) (in Ndubisi et al., 2007:224) states that loyalty is a deeply held commitment by customers to re-use a preferred service in the future despite other influences and marketing efforts from competing organisations which aim to affect switching behaviour.  Ball, Coelho and Vilares (2006:391-392) define loyalty as the customer’s affective end-state which leads to re-patronization, lower price sensitivity, and the willingness to expand buying beyond the initial purchase of goods or services.

Although the definitions above generalise the concept of loyalty, different types of loyalty exist.

3.4.3 TYPES OF LOYALTY

Boshoff and Du Plessis (2009:319) state that two types of loyalty can be identified, namely: attitudinal loyalty and behavioural loyalty. Attitudinal loyalty occurs when a customer has a certain attitude towards an organisation in his/her mind but it does not guarantee that the customer makes use of the organisation’s services. Behavioural loyalty, on the other hand, can be seen in the actions the customer displays. This behavioural loyalty refers to customers’ repurchasing of the same service from the same organisation or making use of the same service time after time (Ball et al., 2006:391).

Based on these attitudinal and behavioural loyalties, Bove and Johnson (2009:187-188) categorise loyalty into four sub-categories which can be seen in Figure 3.3.

Figure 3.3: Sub-categories of loyalty

H i Latent Premium A g h t t

t L u o Spurious d w i

a l Non- Loyals

0 Low High

Behavioural

Source: Adapted from Bove and Johnson (2009:187-188).

As can be seen in Figure 3.3, the following sub-categories of loyalty are depicted, namely: premium, latent, spurious and non-loyals.

3.4.3.1 PREMIUM LOYALTY

Premium (also known as true loyalty) refers to customers with a high level of both behavioural and attitudinal loyalty. This type of loyalty includes high levels of repurchase owing to preferences for the brand or service (Jensen, 2011:334; Jones & Farquhar, 2007:163). These types of customers are not easily influenced by situational factors or other alternatives and are likely to act as ambassadors in spreading positive word of mouth to other consumers (Jensen, 2011:334).

3.4.3.2 LATENT LOYALTY

These are customers with high attitudinal loyalty and low behavioural loyalty. This type of loyalty refers to customers with a strong attitude toward or preference for a certain brand (Jensen, 2011:334; Jones & Farquhar, 2007:163). These customers will, however, choose an alternative brand in situations where the preferable brand is not available (Jensen, 2011:334).

3.4.3.3 SPURIOUS LOYALTY

These are customers with lower attitudinal loyalty and high behavioural loyalty. This type of loyalty refers to customers who frequently purchase a brand without any true preference for that brand (Jensen, 2011:334; Jones & Farquhar, 2007:163). Since these customers have no true preference for the brand they are inclined to switch to other brands in certain situational circumstances such as when competitive offerings are on sale (Jensen, 2011:334).

3.4.3.4 NON-LOYALS

These are customers with no degree of attitudinal or behavioural loyalty. This type of loyalty refers to customers whose attitude towards the brand reveals no or limited intention to repurchase (Jensen, 2011:334; Jones & Farquhar, 2007:163). These customers see no distinct difference between brands and situational factors (such as stock outs) which would encourage customers to switch to alternative brands (Jensen, 2011:334).

Every organisation strives to attain premium or true loyal customers. This, however, is not always the case. Service organisations should try to upgrade latent and spurious loyals and not invest too much in non-loyals. The next section will focus on the advantages of having premium loyal customers.

3.4.4 ADVANTAGES OF LOYALTY

Customer loyalty is of significant importance to any organisation as it holds certain advantages for the organisation. Mandhachitara and Poolthong (2011:123), McMullan and Gilmore (2008:1084), and Ball et al. (2006:391) mention the following advantages:

3.4.4.1 REPEAT PURCHASES

Loyal customers repurchase from an organisation even in situations where competitive services might be better priced (Ball et al., 2006:391). As the services industry is very competitive, repeat purchases become very important to service organisations in ensuring longevity and productivity (Hariharan et al., 2012:77).

3.4.4.2 POSITIVE WORD OF MOUTH TO OTHERS

Loyal customers do not just recommend the organisation’s services to family and friends but also engage in positive word of mouth (Ball et al., 2006:391). Positive word of mouth creates a more concrete image in consumers’ minds about the organisation and it serves as an important tool in attracting new customers (Ball et al., 2006:391).

3.4.4.3 LOWER ACQUISITION COSTS

Due to positive word of mouth and recommendations, the costs of acquiring new customers decreases significantly as customers remain loyal and new customers respond to the recommendations of existing customers (McMullan & Gilmore, 2008:1084). This drives down marketing and advertising costs and contributes to overall profitability (McMullan & Gilmore, 2008:1084).

These benefits are crucial in ensuring an organisation’s competitive advantage. The next section will look at customer expectations, customer satisfaction, and customer loyalty within the South African banking industry to determine whether customers are satisfied and whether banks enjoy the previously discussed benefits.

3.5 EXPECTATIONS, SATISFACTION AND LOYALTY IN THE SOUTH AFRICAN BANKING INDUSTRY

The South African banking industry is a well-developed and well-regulated industry (The Banking Association South Africa, 2011). This section describes the South African banking industries in terms of what customers expect from banks, whether they are satisfied with what is being delivered and whether that satisfaction or dissatisfaction leads to customer loyalty.

3.5.1 EXPECTATIONS IN THE SOUTH AFRICAN BANKING INDUSTRY

Anani (2010:2) states that the South African banking industry is characterised by high levels of customer expectations. Green and Van Belle (2012:1) suggest that customers expect their banks to engage in more personalised attention and cost savings as well as to customise different products and services according to the specific needs of customers. Anani (2010:3) states that customers in the South African banking industry do not limit their expectations to a specific service offering but rather desire a comprehensive service offering pertaining to quality performance. To ensure customer satisfaction, then, banks in South Africa (especially the four major banks) should not lack in certain aspects and perform in others, since customers expect high levels of service in all aspects of their encounters.

3.5.2 SATISFACTION IN THE SOUTH AFRICAN BANKING INDUSTRY

Bick et al. (2004:300) mention that customer satisfaction is achieved with superior service levels, but then continue to state that for organisations to effectively compete in their respective industries, they need to have offerings that comprise certain benefits and value for the customers. Alhemoud (2010:335) suggests that satisfaction in retail banking is driven by various factors, including service quality and its underlying dimensions (see Chapter 4 section 4.4.1.1). As retail banks understand the importance of satisfaction, most of the banks set strategies for increasing customer satisfaction through the quality of their services (Siddiqi, 2011:17).

A study done by Bick et al. (2004:316) showed that customers were not satisfied with the service, products and level of customer intimacy delivered to them by the retail banks in South Africa. However, in a study completed by InnovationAgency (2010) on banking innovation in South Africa, it was shown that customer satisfaction levels have increased since 2005 because banks now realise the importance of customer satisfaction. The main reason for this increase in the levels of satisfaction is due to the fact that banks are meeting customer expectations (InnovationAgency, 2010). The aim for banks should thus be to maintain or increase levels of customer satisfaction. For banks to further guarantee customer satisfaction, they have to start delighting their customers. This means that banks should not only meet customer expectations, but rather exceed these expectations, which, in turn, could potentially lead to customer loyalty (Zeithaml et al., 2009:215).

3.5.3 LOYALTY IN THE SOUTH AFRICAN BANKING INDUSTRY

The previously mentioned study by InnovationAgency (2010) revealed that South Africans tend to have some degree of loyalty when it comes to their banking needs. The following section will provide insight into loyalty in the South African banking industry.

According to InnovationAgency (2010), the top reasons customers remain loyal to their banks include: good service levels, difficulties encountered with changing, satisfaction with the current bank services, and the lack of a reason to change. However, despite countless threats by South African customers to leave their banks (suggesting that customers in the banking industry in South Africa are not true loyals), only about 9% have done so over the 12 to 18 months of 2009 – 2011 (I-net Bridge, 2011). According to the study, however, this does not mean that the remaining 91% of customers are completely satisfied with the service offered to them by their respective banks. Rather, it could indicate that perhaps the inconvenience of and difficulty with switching banks is greater than the dissatisfaction (I-net Bridge, 2011). Okeahalam (2001) also mentions that South African banks are oligopolistic, which implies that the level of competition necessary to increase efficiency and service levels are non-existent, and thus customers are not willing to switch banks as they deem all banks to be similar.

3.6 CONCLUSION

Customer expectations play a vital role in customer satisfaction or dissatisfaction levels. Organisations have the ability to influence satisfaction levels by either meeting or exceeding customer expectations through their service offerings. Customer satisfaction could be a very important determinant in ensuring that an organisation survives and gains a competitive advantage. Customer satisfaction, however, is the responsibility of the whole organisation and does not just rest with one or two individuals. Although not all customers will remain loyal to an organisation, the aim should be to turn those satisfied customers into truly loyal customers by delivering high quality services that can lead to positive word of mouth and increased profitability. When aiming to satisfy customers and create loyal customers, organisations need to develop long-term relationships with their customers. For this reason, the next chapter will discuss the concept of CRM. Specific emphasis will be placed on the various CRM dimensions that should form part of an organisational CRM strategy.

CHAPTER 4 CUSTOMER RELATIONSHIP MANAGEMENT

4.1 INTRODUCTION

In Chapter 3, it was identified that by meeting and exceeding customer expectations, customer satisfaction can ensue, which contributes positively to organisational profitability. As overall customer satisfaction and organisational profitability occurs over an extended period of time, it stands to reason that during the process relationships should be built with customers. Therefore, this chapter will focus on CRM and its importance in ensuring customer satisfaction.

CRM has long been a topic of discussion since its formal introduction to marketing in the late 1990s. Its importance as a valuable tool in ensuring long term organisational profitability and customer loyalty cannot be underestimated. This chapter identifies how CRM fits into the Relationship Marketing concept. Its importance, process and context within the financial industry is addressed and this is then followed by a discussion on each CRM dimension that is used for the purposes of this study. CRM has made the transition to Service Dominant Logic (SDL) in certain developed economies and thus this chapter concludes with an investigation into the transition from CRM to SDL as well as a discussion of CRM within the South African banking industry.

4.2 RELATIONSHIP MARKETING

Before the concept of CRM can be discussed, it is important to understand where it fits into the marketing realm. CRM is one of the six markets that form part of the broader concept of Relationship Marketing (RM). The next section will focus on the broader concept of RM by defining Relationship Marketing and providing a brief discussion of each of the six markets.

4.2.1 DEFINING RELATIONSHIP MARKETING

Egan (2008:34) explains that RM has come a long way since its introduction in the 20th century and has been redefined and developed throughout its existence. The author states that some of RM’s earliest definitions included the concepts of “attracting, maintaining and enhancing

customer relationships” (Egan, 2008:34). These definitions, however, did not hold credibility as they only focussed on relationships with customers and made no room for relationships with other stakeholders such as shareholders and suppliers (Egan, 2008:34). It was only in later years that RM expanded its definition to include relationships with all stakeholders. Throughout the development of the RM concept, other authors have developed more comprehensive definitions. These are listed below:  RM is a type of marketing that establishes, maintains and enhances relationships with customers and other stakeholders at a profit level where all the objectives of the parties involved are met (Gronroos, 1994:9).  RM is the process of identifying and establishing, maintaining and enhancing, and, when necessary, terminating relationships with customers and other stakeholders in order to meet the objectives of all parties involved (Egan, 2008:37).  RM is the process of creating, maintaining and enhancing strong relationships with an organisation’s stakeholders with the emphasis on maintaining existing customers rather than attracting new ones (Gilaninia, Almani, Pournaserani, & Mousavian, 2011:787).

Gummeson (1994) (in Harwood & Garry, 2006:107) suggests that RM is a situation in which it is mutually beneficial for both parties to enter into a relationship and in which both these parties are willing to commit to adapting their behaviour so as to ensure the longevity of the mutually beneficial relationship. Roberts-Lombard (2009:63) suggests that the development of such a relationship is based on two principles, which include: o The degree of trust between the organisation and its customers; o The willingness of the customer to establish a relationship with the organisation. The definitions provided indicate that RM encompasses more than just the relationship with customers, but includes relationships with other stakeholders. These relationships are discussed in what is termed, the “six markets model” of RM.

4.2.2 SIX MARKETS MODEL OF RELATIONSHIP MARKETING

According to Payne, Ballantyne and Christopher (2005:858), the six markets model of RM include: internal markets, referral markets, influencer markets, recruitment markets, supplier markets, and customer markets. Figure 4.1 indicates the six markets model in which the internal, referral, influence, recruitment supplier markets, and customer markets are all part of the RM concept.

Figure 4.1: Six markets model of relationship marketing

Internal Market

Customer Referral Market Market

Relationship Marketing

Supplier Influence Market Market

Recruitment Market

Source: Adapted from Payne et al. (2005:860).

4.2.2.1 INTERNAL MARKETS

Internal markets, also known as internal partnerships or internal relationships, include all internal departments and staff of the organisation (Payne et al., 2005:858). It is important for any organisation to manage the relationships with their internal employees as these employees deal directly with customers (Egan, 2008:174) and management can gain feedback from these internal employees regarding current issues within the organisation.

4.2.2.2 REFERRAL MARKETS

Maritz and Nieman (2008:15) describe the referral market as the communication between groups, including the customer’s family and friends, the service provider, independent experts, and the actual or potential customer. Payne et al. (2005:858) state that referral markets include existing customers and multipliers (other organisations that refer customers to the organisation).

The organisation has limited control over the referral market and may thus find it difficult to establish relationships with these markets.

4.2.2.3 INFLUENCE MARKETS

Influence markets are all stakeholders that can directly or indirectly influence an organisation’s operations. They include: financial analysts and institutions, shareholders, the media, the government and consumer groups (Payne et al., 2005:858). Rivera-Camino (2007:1335) states that it is important for organisations to establish good relationships with these influence markets as they have the influence to unlock many opportunities for the organisation.

4.2.2.4 RECRUITMENT MARKETS

Payne et al. (2005:858) define the recruitment markets as those markets concerned with attracting the right employees to the organisation and are normally considered to be recruitment agencies or job portals. As organisations have to compete against one another to acquire the services of the right employees, it is important to establish firm relationships with recruitment markets that are able to provide those employees (Maringe, 2006:466).

4.2.2.5 SUPPLIER MARKETS

Payne et al. (2005:858) opine that supplier markets include traditional suppliers within the supply chain as well as other organisations with which the organisation has some form of strategic alliance. Palmer (2000:689) (in Egan, 2008:193) suggests that these supplier markets or strategic alliances have a vertical as well as horizontal dimension. The vertical dimension represents relationships with organisations that integrate all or part of the supply chain, whereas the horizontal dimension represents relationships with organisations that are at the same point in the distribution channel (for instance, competitors who seek to cooperate for mutual benefit). Payne et al. (2005:858) state that these relationships are mostly established by means of continuous business efforts with the suppliers or by contractual agreements. These relationships should be considered important for the organisation as they hold certain benefits such as the availability of credit, preferred supplier status, and purchasing discounts.

4.2.2.6 CUSTOMER MARKETS

Payne et al. (2005:858; 860) suggest that customer markets include existing and prospective customers as well as intermediaries, and that these form the core of RM. This customer market is influenced by all the other markets in different ways. For example, internal employees deal directly with customers and can thereby ensure customer satisfaction (Egan, 2008:174), while referral markets can refer a potential customer to the organisation (Maritz & Nieman, 2008:15). Influence markets make decisions that have the potential to change the outcome of services and products rendered to customers (Rivera-Camino, 2007:1335), while recruitment markets are necessary for organisations so that they can employ the right employees to serve their customers (Maringe, 2006:466). Without the right supplier markets, organisations would be unable to provide their customers with the right products or service levels they require (Payne et al., 2005:858). As can be seen from the above examples, the other markets influence the customer market and, for this reason, the customer market has received its own focus in the form of CRM.

Egan (2008:150) states that the aim of the customer market should be to treat customers as valuable partners. This serves to enhance customer satisfaction by establishing customer needs which, in turn, helps to develop customer loyalty through quality service. This is achieved by managing customer relationships through CRM.

4.3 CUSTOMER RELATIONSHIP MANAGEMENT

CRM forms the corner stone in an organisation striving to build, maintain and enhance relationships with its customers. The next section will focus on providing insights into: what CRM is, the levels of customer relationships and its integration with the customer loyalty ladder, the importance of CRM within service industries, the process involved in achieving successful CRM implementation, and a discussion of the CRM dimensions to be used for the purposes of this study.

4.3.1 DEFINING CUSTOMER RELATIONSHIP MANAGEMENT

The late 1990s and early 21st century saw the rise of CRM as the next wave of marketing (Payne, 2005:13). CRM is seen as a marketing tool which forms part of the six markets model

of Relationship Marketing which aims to enhance customer relations (Payne, 2005:1). The following are definitions of CRM as provided by various researchers.  Payne (2005:18-22) defines CRM as a business approach that seeks to form, develop and enhance relationships with carefully chosen customers. This is so as to improve customer value and corporate profitability with the goal of maximizing shareholder value.  Chen, Yen, Li and Ching (2009:294) state that CRM should not be seen as one dimensional, but rather as the integration and collaboration of IT as well as organisational and marketing elements.  Cant et al. (2006:211) define CRM as an organisation’s approach to better understand and influence customer behaviour through meaningful communications with the goal of improving customer acquisition, customer retention, loyalty, and profitability in the long-term.

As CRM is an organisation-wide endeavour that should involve relationships with carefully chosen customers, it is important to note that certain levels of relationships exist (Chen et al., 2009:294). The next section will provide a discussion of the levels of CRM, in which organisations can engage.

4.3.2 LEVELS OF CUSTOMER RELATIONSHIP MANAGEMENT

Different types of customers exist and not all customers are equally profitable. This leads to the need for understanding the different levels of relationships between customers and organisations. For most organisations, the Pareto rule applies where 20% of customers make up 80% of the profits (Harrigan, Ramsey & Ibbotson, 2012:55). It is therefore necessary for organisations to identify the different types of customers in terms of customer lifetime value (CLV) as well as which type of relationships should be formed with these customers based on the availability of organisational resources (Chang & Hong, 2011:183). Zeithaml, Rust and Lemon (2001:125) indicate that customers can be classified according to their profitability levels (lead, iron, gold and platinum), which may also indicate the levels of relationships which can be formed (Pitta, Franzak & Fowler, 2006:426). The various levels of relationships can be identified in what is coined the Customer Pyramid, as indicated in Figure 4.2.

Figure 4.2: The Customer Pyramid

Platinum Gold

Iron

Lead

Source: Zeithaml et al. (2001:125).

4.3.2.1 LEAD CUSTOMERS

Lead customers can be classified as those customers who cost the organisation more money than the profits they generate over their lifetime with the organisation (Pitta et al., 2006:426). These customers, according to Pitta et al. (2006:426), can pose a serious threat to the organisation as they demand higher service levels not substantiating their profits. In essence, they then spread negative word of mouth about the poor service received from the organisation (Pitta et al., 2006:426). Organisations should avoid offering these customers any special treatment (Zeithaml et al., 2001:125).

4.3.2.2 IRON CUSTOMERS

Pitta et al. (2006:426) state that iron customers are valuable to the organisation in the sense that they provide the organisation with the necessary volumes to utilize the organisation’s capacity and resources. Iron customers should be retained as customers without any extra or preferential treatment. Preferential treatment would increase costs and thus lower overall organisational profitability (Pitta et al., 2006:426).

4.3.2.3 GOLD CUSTOMERS

Gold customers should be seen as valuable to the organisation in that they provide the organisation with high levels of profits and tend to be committed to the organisation over their lifetime (Pitta et al., 2006:426). Organisations should engage more with these customers by offering them preferential treatment such as better rates and discounts on products or services (Zeithaml et al., 2001:125) with the aim of moving them up the pyramid to platinum status.

4.3.2.4 PLATINUM CUSTOMERS

Platinum customers are considered to be those customers with a customer lifetime value considerably higher than customers in the lead and iron tiers of the pyramid (Pitta, Guesalaga & Marshall, 2008:394). These are the most profitable customers for the organisation and require high levels of engagement such as constant communication, specially structured packages and preferential treatment (Zeithaml et al., 2001:125). Dealing with these types of customers requires a degree of professionalism, product differentiation and customisation (Pitta et al., 2008:394).

Organisations should consider all these profitability levels in determining which customers they want to form relationships with. It must, however, be noted that not all customers remain loyal throughout the relationship and it may be necessary for the organisation to terminate the relationship. By identifying which customers to form relationships with, and what these customers’ profitability levels will be, organisations can then identify the levels of loyalty these customers exhibit. The next section will look at the customer loyalty ladder.

4.3.3 THE CUSTOMER LOYALTY LADDER

The customer loyalty ladder, according to Zeithaml et al. (2009:177-181), is characterised by four levels. The lower levels indicate lower levels of customer loyalty while the higher levels indicate higher levels of customer loyalty. The four levels in the customer loyalty level include: customers as strangers, friends, and partners.

4.3.3.1 STRANGERS

These types of customers have not had any interaction with the organisation per se and/or might not even be aware that the organisation exists (Zeithaml et al., 2009:177). In order to upgrade these individuals to acquaintances, the organisation should create awareness rather than relationships at this point in time. Thus, in this stage, no CRM efforts are required because individuals are not yet customers of the organisation and no form of loyalty exists (Zeithaml et al., 2009:177).

4.3.3.2 ACQUAINTANCES

At this stage in the loyalty ladder, the customer has made use of or purchased the organisation’s products or services and is familiar with the organisation (Zeithaml et al., 2009:177). No form of customer loyalty has come to the fore yet, and so the main aim of the organisation should be to keep the customer satisfied (Zeithaml et al., 2009:177). If the customer proves to be profitable in the future (based on the customer pyramid discussed in the previous section), then the organisation should put in maximum CRM efforts to move the customer further up the loyalty ladder (Payne, 2005:12).

4.3.3.3 FRIENDS

The more regularly a customer makes use of the products or services offered by an organisation, the more knowledge of the customer the organisation is able to acquire, which allows for the customisation of the product or service offering so as to meet the customer’s direct needs (Harridge-March, 2009:194). Customers who are seen as friends of the organisation are profitable and warrant CRM efforts such as better rates and discounts on products or services (Zeithaml et al., 2009:179). Customers identified as “friends”, show some extent of loyalty and should be moved, through CRM initiatives, up the loyalty ladder to partner status (Harridge-March, 2009:194).

4.3.3.4 PARTNERS

The last stage of the customer loyalty ladder includes those customers who move from being strangers of the organisation to being partners (Zeithaml et al., 2009:179). These customers

continue to interact with the organisation on a regular basis, and trust and loyalty exist between the two parties (Harridge-March, 2009:194). This level is also associated with commitment between the organisation and its customers; at this level, greater time and effort are spent in the relationship (Zeithaml et al., 2009:179). These customers are very profitable for the organisation and the highest level of CRM efforts are required to maintain and further enhance the relationship. The organisation could, for example, focus on constant communication, specially structured packages, and preferential treatment (Harridge-March, 2009:194).

By focusing on the customer loyalty ladder it is evident that maximum efforts should be spent to retain the most profitable customers (gold and platinum). By discussing the importance of CRM and its contribution to customer satisfaction and customer loyalty, the next section considers why organisations should aim to develop relationships with customers.

4.3.4 THE IMPORTANCE OF CRM

The importance of CRM cannot be underestimated due to its influence on customer satisfaction and loyalty. The importance of both these constructs for organisational survival is discussed in Sections 3.3.3 and 3.4.4 of Chapter 3, as well as the relationship between these three constructs (CRM, customer satisfaction, and loyalty). The next section will focus on the relationship between CRM and customer satisfaction as well as CRM and customer loyalty to determine whether a relationship exists between these constructs.

4.3.4.1 CRM AND CUSTOMER SATISFACTION

Richards and Jones (2008) (in Őztaysi, Sezgin & Őzok, 2011:944) explain that research indicates that a decrease in customer satisfaction occurs when CRM systems are poorly implemented. Thus, when there is a lack of CRM implementation, customer satisfaction tends to decrease. Wang and Feng (2012:120) support this idea by suggesting that successful implementation of CRM leads to greater customer satisfaction and loyalty. Thus, from previous studies it can be determined that a correlation exists between CRM and customer satisfaction in that satisfied customers are willing to form relationships with organisations.

4.3.4.2 CRM AND CUSTOMER LOYALTY

Oliver (1999) (in Ndubisi et al., 2007:224) states that customer loyalty is a deeply held commitment by customers to re-use a preferred service in the future. This is despite other influences and marketing efforts from competing organisations who aim to affect switching behaviour. While organisations strive to actively build relationships with customers, it is crucial for them to realise that true loyalty as described in Section 3.4.3 of Chapter 3 can only be built by investing, actively communicating and managing relationships that form part of CRM (Dagger et al., 2011:274; Ndubisi et al., 2007:224).

Richards and Jones (2008) and Ribgy et al. (2002) (in Őztaysi et al., 2011:944) state that poor implementation of CRM elements may lead to a decrease in customer loyalty which, in turn, can lead to decreased profitability as well as damaging long standing customer relationships. This is confirmed by Ndubisi et al. (2007:22) who state that effective implementation of CRM dimensions (e.g. commitment and communication) lead to higher levels of customer loyalty. In order to ensure that CRM processes are effectively implemented, organisations can follow procedures in development.

4.3.5 PROCEDURES IN DEVELOPING A CUSTOMER RELATIONSHIP MANAGEMENT PROCESS

Lambert (2010:4) states that the steps or processes that an organisation uses to implement CRM dimensions provide a blueprint for how relationships with customers are formed, developed and maintained. Levy and Weitz (2012:277) suggest that the CRM process consists of four steps or processes, namely: collecting customer data, analyzing data, developing CRM programmes and implementing these CRM programmes. These are illustrated in Figure 4.3.

Figure 4.3: The steps in developing a CRM process

Step 1: Collecting Customer Data

Step 4: Implementing Step 2: CRM Programs Analyzing Data

Step 3: Developing CRM Programs

Source: Adapted from Levy and Weitz (2012:277).

4.3.5.1 STEP 1: COLLECTING CUSTOMER DATA

Customer data collection is defined as the collection of customer and market related data required by an organisation (Rababah, Mohd & Ibrahim, 2011:25). At this stage, customer data is collected through sales and registrations and entered into a database. The data can include: personal information, previous transactions and previous services used (Levy & Weitz, 2012:277). The organisation can use this information later in the process to formulate more customised offerings for the customer and thus enhance their relationships (Levy & Weitz, 2012:277).

4.3.5.2 STEP 2: ANALYZING DATA

Rababah et al. (2011:25) describe this step as the conversion of the captured data in the previous step into actionable intelligence. This is done through a statistical programme which enables the organisation to identify target customers according to certain information requested by the organisation (Levy & Weitz, 2012:277). For example, if the organisation requires the contact details of all customers with a profitability margin of 15% or higher, these analyses

would be able to provide that information. These analyses enable organisations to classify customers according to different profiles such as iron versus platinum and according to their demographics and purchasing habits (Rababah et al., 2011:25).

4.3.5.3 STEP 3: DEVELOPING CRM PROGRAMMES

From these analyses (profitability, demographics and purchase habits), CRM programmes are then developed to target the identified customers according to organisational goals (Levy & Weitz, 2012:277). Mishra and Mishra (2009:85) state that these programmes are the integration of technologies and business processes that are adopted to satisfy customer needs and include the CRM dimensions that the organisation wishes to focus on for implementation in the next step.

4.3.5.4 STEP 4: IMPLEMENTING THE CRM PROGRAMMES

As soon as these programmes have been developed, they are then implemented in order to reach the organisational goals (Levy & Weitz, 2012:277). During implementation, organisations focus specifically on the dimensions they identify as important to the customer (Mishra & Mishra, 2009:86). Where necessary, these implementations are then done manually. For instance, when organisations make use of call centres and staff or when organisations make use of an electronic database to capture, analyse and send information through (Mishra & Mishra, 2009:86).

Throughout the procedure discussed in this section, it is important to take into consideration the CRM dimensions that are used in the implementation of a CRM programme. For that reason, the next section focuses on the CRM dimensions used for the purposes of this study.

4.4 CRM DIMENSIONS

The CRM dimensions which are discussed in this section are those that have been used for the purposes of the study (as identified from previous studies on CRM). These CRM dimensions include: service quality, customisation, two-way communication, the use of technology, commitment, and convenience. Table 4.1 indicates the CRM dimension as identified in the

literature, the authors who identified the dimension, and in which industry the study was undertaken. Each of these dimensions is discussed in more detail in the following section.

Table 4.1: CRM dimensions found in previous studies CRM dimension Authors Industry 1. Service quality Bick, Abratt and Moller Banking (2010:20-23)

1. Customisation Sin, Tse and Yim Various industries with

2. Two-way (2005:1266) reference to business

communication executives

3. Use of technology

1. Commitment Richard, Thirkell and Various industries 2. Two-way Huff (2007:935) communication 1. Two – way Abratt and Russell Banking communication (1999:15) between staff and customers 2. Customisation

3. Service quality

4. Convenience

1. Two-way Rootman (2006:77-78) Banking

communication 2. Service quality

4.4.1 SERVICE QUALITY

Malik, Naeem and Arif (2011:647) define service quality as the customer’s perception of the overall excellence of the organisation and refer to how well the services received match customer expectations. Boshoff and Du Plessis (2009:38) define service quality in terms of three key variables, namely: technical quality, functional quality and quality image.  Technical quality describes the service provided by the organisation. For instance, opening an account or processing a home loan application.  Functional quality describes how the service is delivered. For instance, quickly and reliably processing a home loan application.

 Quality image refers to the outcome of both technical and functional quality. Customers receive the service and form an image about the organisation based on the service delivered (Boshoff & Du Plessis 2009:38).  Zeithaml et al. (2009:103) and Boshoff and Du Plessis (2009:38) further state that service quality includes the following elements: reliability, responsiveness, assurance, empathy and tangibles.

4.4.1.1 RELIABILITY

Al-Alak and Alnaser (2012:157) and Boshoff and Du Plessis (2009:38) define reliability as the consistency and dependability in which the organisation performs the service promised to the customer. This is the ability of the organisation to perform the service promised to the customer in an accurate and dependable manner (Chowdhary & Prakash, 2007:509).

4.4.1.2 RESPONSIVENESS

This is the willingness of the organisation and its employees to respond to customer queries and needs in a prompt manner (Boshoff & Du Plessis, 2009:38; Chowdhary & Prakash, 2007:509). Al-Alak and Alnaser (2012:157) state that responsiveness is the readiness of the organisation’s employees to perform a service in a given timeframe.

4.4.1.3 ASSURANCE

Boshoff and Du Plessis (2009:38) state that this element of service quality refers to the competence and knowledge that employees possess, and the ability of employees to help customers in such a way that it conveys trust and confidence (Al-Alak & Alnaser, 2012:157; Chowdhary & Prakash, 2007:509).

4.4.1.4 EMPATHY

Al-Alak and Alnaser, (2012:157) state that empathy is the caring attention provided by the employees of an organisation in understanding a customer’s specific needs. The personal and individualised attention of an organisation and its employees aims at better understanding the customer (Boshoff & Du Plessis, 2009:38; Chowdhary & Prakash, 2007:509).

4.4.1.5 TANGIBLES

Tangibles refer to the physical appearance of the organisation in terms of elements such as the buildings, parking space, employee appearance, equipment, and promotional or informative materials (Al-Alak & Alnaser, 2012:157; Chowdhary & Prakash, 2007:509). These tangibles play a big role in the perception customers have of the organisation. When these tangibles are visually appealing, customers have positive perceptions of the organisation (Chowdhary & Prakash, 2007:509).

Service quality can have a significant impact on the relationship that organisations build with their customers. When these elements are not present, it can influence the relationship negatively (Malik et al., 2011:647). When these elements are present, they have the ability to delight customers with the result of positively influencing the relationship (Malik et al., 2011:647). The study will therefore determine whether customers perceive service quality as an important dimension in building relationships with an organisation.

4.4.2 CUSTOMISATION

Stremersch, Wuyts and Frambach (in Nordin, Kindström, Kowalkowski and Rehme, 2011:391) define customisation as the comprehensive combinations of service offerings provided to target customers. Hart and Taylor (1996) (in Sigala, 2006:397) define customisation as the use of current organisational resources and processes to produce personalised services to individual customers with the aim of building long-term relationships.

Sigala (2006:395) explains that customers have become more aware of the design and quality of service processes and that demand is increasing for customers to be co-designers of those processes in order to achieve customised services to satisfy their needs. Additionally, intense rivalry between organisations and changing demand patterns for more customised services have caused customisation to become a competitive advantage for organisations. Wang and Head (2007) (in Li, Chang and Chang, 2010:5385) state that customisation has now become an important element within CRM globally and is regarded as one of the decisive factors affecting customer satisfaction and loyalty. Customers are no longer willing to sacrifice their preferences for standard quality services at lower prices but would much rather pay extra for customised services (Pine, 1993 in Bardakci & Whitelock, 2005:398). These customisations may, for

example, include customising repayment options, lowering interest rates, and customising certain accounts.

4.4.3 TWO-WAY COMMUNICATION

Choi, Hise, Bagozzi and Fadil (2010:13) define two-way communication (from a services marketing perspective) as the extent to which an employee of an organisation and a customer engage in the communication process with the aim of providing instantaneous feedback. The process should allow for participative communication where both parties (employee and customer) engage in joint decision-making, goal-setting and timely information exchanges. Berndt, Herbst and Roux (2004:34) state that this communication should be done in an understandable manner with the elimination of technical or ambiguous terms. This may, for example, include: the friendliness of staff together with the courtesy and respect they show their customers as well as non-customers. The abovementioned, however, only focuses on two-way communication from a customer-to-organisation perspective.

Birdthistle (2008:432) suggests that two-way communication in the organisation should also be formalized (between employees and management). This is between top, medium, lower level management, and front-line employees, and ensures team work, resource availability, and effective communication of information to employees (Birdthistle, 2008:432-433).

Choi et al. (2010:13) state that misunderstandings in the communication process caused by different cultural backgrounds, values, norms and goals, may hinder the flow of credible information between parties and should be addressed. Once these issues are addressed, the feedback obtained can give parties valuable insights into and an understanding of the needs and desires of both parties (Choi et al., 2010:13).

4.4.4 USE OF TECHNOLOGY

In recent years, technological advances have led to many opportunities in how organisations reach and build relationships with their customers (Chau & Ngai, 2010:43). Technology use has also increased significantly over the last decade. However, there are still certain obstacles preventing customers from adopting technological processes. These obstacles include: security and privacy issues, inseparability (separation between customers and employees), potential

transactional errors, limited technological services, lack of clear and understandable information provided in operating technologies, and the lack of technological competence when using technologies (Muñoz-Leiva, Luque-Martínez & Sánchez-Fernández, 2010:908).

In trying to overcome these obstacles, Chau and Ngai (2010:43) suggest that two perceptions about technology exist in enhancing customer acceptance of technology. The first focuses on the perceived usefulness of technology and the second focuses on the perceived ease of use. Perceived usefulness is described as the extent to which a customer believes a certain technology can enhance performance in terms of time risk, social risk, monetary risk, and physical risk (Chau & Ngai, 2010:43). Perceived ease of use refers to a situation in which a customer believes that a minimum amount of effort is spent on using the technology (Chau & Ngai, 2010:43). Ndubisi and Sinti (2006:19) state that it is of utmost importance to provide customers with understandable information concerning technology use in order to overcome these obstacles.

According to Sangle and Awasthi (2011:911), customers make use of technology when the benefits outweigh the costs. These costs include the time costs, effort costs, and money costs. In terms of technology, then, organisations must ensure that when using the technology the costs incurred are less than the perceived benefits gained. Sangle and Awasthi (2011:912) also list mobility as a significant factor in technology use and state that it can be described as the ability to use technology on the go through wireless networks on devices such as PDAs and mobile phones. This puts strain on service providers using technological touch points to enhance CRM since these touch points need to be designed and implemented in such a way as to eliminate effort and increase convenience.

4.4.5 COMMITMENT

Dash et al. (2009) (in Al-Hawari, 2011:350) define commitment as the desire of the customer and organisation to maintain and further develop a valued relationship. Άlvarez, Casielles and Martín (2009:144) define commitment as the process of identifying, developing and maintaining a relationship between customers and organisations while making short term sacrifices in order to ensure the longevity of the relationship. Shum, Bove and Auh (2008:1350) state that an employee must be committed to the organisation for successful implementation of CRM in the organisation. The authors further mention that when employees are committed to an

organisation, customer service and the task at hand, they achieve more constructive behaviours such as better job performance and more positive attitudes. Examples of this commitment include: employees taking customer needs and queries to heart, employees wanting to form a relationship with customers, employees wanting to establish win-win partnerships with customers, and employees willing to make short-term sacrifices in maintaining and enhancing the relationship (Άlvarez et al., 2009:144).

It must be noted that commitment can only be achieved if and when both parties (customers and employees of the organisation) are willing to be involved in the relationship (Berry & Parasuraman, 1991 in Dagger et al., 2011:276). Commitment should be an integral part of the strategy and formulation of any CRM implementation. Al-Hawari (2011:348) states that commitment is at a lower level than customer relationships and yet it is considered a prerequisite for customer loyalty.

4.4.6 CONVENIENCE

Convenience in its simplest from can be defined as anything that contributes to a customer’s value when making use of a service (Brown, 1990 in Thuy, 2011:475). Thuy (2011:475) states that the less time a customer spends in a service environment, the more convenient the service tends to be.

Berry et al. (2002) (in Chen, Chang, Hsu and Yang, 2011:389) further define convenience by emphasizing five constructs of convenience. These are: decision convenience (the time and effort a customer spends in deciding how to achieve a specific outcome), access convenience (the time and effort spent by a customer in initiating service delivery), transactional convenience (the time and effort it takes for a customer to initiate a transaction), benefit convenience (the time and effort spent in experiencing the service benefits), and post-benefit convenience (the time and effort spent in reconnecting with the organisation). Apart from these five constructs influencing customer convenience, Chen et al. (2011:389) also include factors such as the servicescape and service design which impact convenience for customers. Examples of convenience include: how conveniently organisations are located for customers, the convenience in the process flow of business, and the convenience of using the organisations technologies to eliminate hassle. Chen et al. (2011:389) mention that convenience is generally

considered to be one of the most important and decisive factors in influencing customer behaviour and thus requires sufficient attention.

From Sections 4.2 to 4.4 it can be determined that CRM developed from the RM perspective and includes various dimensions. In recent years though, researchers have been considering the evolution of CRM into new concepts such as SDL (Gummesson, 2008:144). The next section will look at the possible future developments of CRM.

4.5 DEVELOPMENT OF CRM INTO SERVICE DOMINANT LOGIC

As stated above, one of the recent developments of CRM includes the speculation of enhancing or replacing CRM with Service Dominant Logic (SDL). SDL is a relatively new concept in the minds of consumers and it has received much criticism (Gummesson, 2008:144). Kowalkowski (2011:277) defines SDL as the value obtained through the interaction and co-creation of propositions between organisations and its customers throughout the relational process. According to Gummesson (2008:143), SDL ensures that organisations depend on the co- creation of customers when creating value propositions. Vargo (2009:374) states that in SDL, organisations cannot simply create value for customers. Instead, they can only create propositions and then value in collaboration with customers. Thus, the whole premise of SDL is that the customer and the organisation must collaborate through an interactive set of exchange relationships, whether directly or indirectly, in the case where a service is provided through goods (Vargo, 2009:374).

Kasouf, Darroch, Hultman and Miles (2009:60) mention that SDL is a designed system that focuses on taking the responsibility off the marketing of products and shifting it to the marketing of services as the true foundations of value. The aim of this is to enhance customer relationships. This does not mean eliminating a product, but rather focussing on the service accompanying the product to add value (Vargo, 2009:374). Although SDL might add value to RM and CRM in the future (Vargo, 2009:378), it is not yet seen as a theoretical construct (Kasouf et al., 2009:60).

At present, most literature in the fields of services marketing, RM, and CRM do not mention SDL (Gummesson, Lusch & Vargo, 2010:19). Gummesson et al. (2010:10) made the first effort to integrate SDL with CRM and RM. Although this was a success, it still had to be extended to

multi-party networks. For this purpose, SDL will not be tested in this study as it is still a relatively new concept to academia. The study also does not focus on customer value within the relationship.

4.6 CUSTOMER RELATIONSHIP MANAGEMENT AND THE SOUTH AFRICAN BANKING INDUSTRY

The retail banking segment in South Africa is a very complex and competitive environment and for banks to flourish in such an environment they need to have a clear and concise understanding of CRM (Ravesteyn, 2005:1). However, when banks implement CRM dimensions, they often implement it from the organisation’s point-of-view and therefore neglect customer needs and expectations. This can actually result in higher costs, decreased customer loyalty, and lower profitability (Saunders, 2008:452; Roig, Garcia, Tena, & Monzonis, 2006:268). Ravesteyn (2005:6) further states that there is a clear lack of customer focus and understanding in the South African retail banking environment, which proves to be a major obstacle in achieving organisational success and successful CRM implementation. Banks have for too long now relied on their standardised product offerings and services without considering a comprehensive CRM strategy since customer needs are often neglected (Berndt et al., 2004:32).

A problem arising from the implementation of CRM programmes is that customer preferences for CRM efforts change, as is evident in the studies of Abratt and Russell (1999) and Rootman (2006). The study by Abratt and Russell in 1999 proved that customers regarded service quality and two-way communication as the most important CRM dimensions (Abratt & Russell, 1999:15). In the study conducted by Rootman (2006), it was indicated that customers regarded employee knowledgeability and positive employee attitudes towards customers (both elements of service quality) as the most important CRM dimensions.

This, in recent years, South African banks have needed to shift their focus to customer needs and incorporating CRM dimensions into their marketing strategies. Anani (2010:12) states that due to the competitiveness of the banking industry in South Africa, banks are placing more emphasis on service quality. This is due to the fact that banks offer mostly undifferentiated products and services, and this creates the need for greater service quality and customisation in order to retain and strengthen their relationships with customers. The banks focus on high profit

customers and are much more willing to customise services and offerings to these customers’ specific needs. Deloitte (2012) mentions that banks customise messages and smaller offerings to low profit customers while customising better offerings to high profit customers. This then becomes an obstacle to forming relationships with lower income customers and could result in lower income customers switching to competing banks (if competitors customise services according to their needs). Apart from customisation, Rootman (2006:82) suggests that two-way communication is very important and that bank employees are more often than not playing a counselling role in that they have to listen, align and match customer needs to banking products and services. South African banks offer a variety of two-way communication options whether telephonically, via personalised attention, or by email.

Recently, there has been a significant ‘shift in the services marketing field CRM’ (Chen et al., 2009:283), which impacts the South African banking industry because it is service driven. This shift has come about because CRM systems take advantage of new information technology (IT) which leads to marketers being able to gain greater knowledge of customers’ needs and expectations with the aim of satisfying customers through individualised relationships with the organisations (Chen et al., 2009:283). IT is rapidly changing the way personal and financial services are designed and delivered (Aldás-Manzano, Lassala-Navarré, Ruiz-Mafé & Sanz- Blas, 2009:672). This is evident in the South African banking industry as an increasing number of banks are encouraging their customers to make use of online and technological platforms such as the Internet and cellphone banking.

Commitment is another dimension evident in the South African banking industry (Rootman, 2006). Anani (2010:32) states that commitment must start with top level management and be incorporated throughout the whole organisation, which is not always the case in the South African banking industry. In committing to customers, banks can strengthen their relationships by providing customers with re-assurance that they are willing to work on the relationship and search for the best possible outcome in all situations. Rootman (2006:103) is of the opinion that convenience is also evident in the South African banking sector although different cohorts will have different meanings for the concept. Senior citizens may, for instance, find a bank that is closely situated to them as convenient. Generation Y see online banking as more convenient than standing in cues at a branch. South African banks, in general, focus on all these aspects by making processes more convenient as well as adapting technological infrastructure to serve different cohorts (Rootman, 2006:103)

4.7 CONCLUSION

CRM can be seen as part of the broader RM concept as one of the six markets and can prove to be an imperative competitive advantage for organisations when implemented successfully. Successful implementation of CRM dimensions can ensure the future existence and growth of an organisation. Implementing these CRM dimensions is not without obstacles, but following a clear set of steps should ensure successful implementation. Choosing the right combination of CRM dimensions is also of crucial importance and can be industry or organisation specific. From previous studies, dimensions such as service quality, customisation, two-way communication, technology, commitment, and convenience have been linked to CRM in the banking industry. In considering these dimensions, the next chapter will focus on the research design and methodology used in order to reach the objectives set for the study.

CHAPTER 5 RESEARCH DESIGN AND METHODOLOGY

5.1 INTRODUCTION

A research design is considered to be the master plan or blueprint that specifies the different methods and procedures that will be used in collecting and analysing the needed information when aiming to solve a research problem (Zikmund et al., 2010:66). Determining which research design to use will depend on the objectives of the study and the nature of the research problem. In this study, the research process suggested by Iacobucci and Churchill (2010:31) consists of nine steps, namely: identifying and formulating the research problem, determining the research objectives and hypotheses, determining the research design, conducting secondary research, selecting the primary research method, determining the research frame, gathering the data, analysing and interpreting the data, and preparing the research report. This chapter provides an exposition of the research process, design and methodology used to conduct the study.

5.2 THE MARKETING RESEARCH PROCESS

The marketing research process can be defined as the series of steps taken in designing a marketing research project and includes the research design and methodology used when conducting research (Churchill & Iacobucci, 2005:39). Various authors suggest different steps in the marketing research process. For the purpose of this study the steps suggested by Iacobucci and Churchill (2010:31) have been followed. The steps in the marketing research process used in the study include the following: identifying and formulating the research problem, determining the research objectives and hypotheses, determining the research design, conducting secondary research, selecting the primary research method, determining the research frame, gathering the data, analysing and interpreting the data, and preparing the research report (Iacobucci & Churchill, 2010:31). The marketing research process followed in this study is presented in Figure 5.1 and will be subsequently discussed.

Figure 5.1: The marketing research process

Step 1: Identify and formulate the research problem

Step 2: Determine the research objectives and hypotheses

Step 3: Determine the research design

Step 4: Conduct secondary research

Step 5: Select a primary research method

Step 6: Determine the research frame

Step 7: Gather data

Step 8: Analyse data

Step 9: Prepare report and reccomendations

Source: Adapted from Iacobucci and Churchill (2010:31).

Figure 5.1 lists the nine research steps which were followed. The discussion below explains each step and how it was applied to the study. The next section of the chapter will focus on the first step in this process, which is identifying and formulating the research problem.

5.2.1 STEP 1: IDENTIFY AND FORMULATE THE RESEARCH PROBLEM

The research problem can be defined as a statement which lends direction to the investigation (Zikmund et al., 2010:64). For the purpose of this study, an in-depth discussion on the research problem is provided in Chapter 1 (see Section 1.5). From the discussion in Section 1.5 four main problems arose:  Current CRM programmes do not focus on the customers’ needs. Many organisations are using CRM programmes, but these programmes are not focused on customer needs and expectations (Saunders, 2008:452).

 Very few studies pertaining to the banking industry have been conducted on black Generation Y adults in South Africa. Even though the importance of conducting consumer research on the black Generation Y adult consumer cannot be disputed, very few studies have been conducted on this particular group (Sibiya, 2007). Although Rootman (2006), Bick et al. (2004:300-318), and Abratt and Russell (1999:15) have done studies on the impact of CRM and Relationship Marketing on customer satisfaction in retail banking, no studies with a specific focus on black Generation Y consumers in South Africa pertaining to the banking industry could be found.  South Africa’s black Generation Y adults are a very complex group to understand and it is apparent that marketers do not always know how to market to these customers (Sibiya, 2007). Furthermore, as this group generally forms part of the workforce and therefore earns a salary (Lamb et al., 2010:49), they are an important target market for financial institutions.

The objectives for the study were thus guided by a consideration of these problems. Given that no studies have been done on black Generation Y adults and their views on the CRM efforts in the South African banking industry, the main purpose of the study is therefore to investigate the expectation of black Generation Y adults in Gauteng regarding the CRM dimensions offered by their banks. The next section will focus on the primary and secondary objectives as well as the hypothesis set to solve the research problem.

5.2.2 STEP 2: DETERMINE THE RESEARCH OBJECTIVES AND HYPOTHESES

From the research problem and purpose, research objectives can be developed. The research objectives are based on the research problem definition identified in Step 1 and provide the guidelines for the remainder of the steps in the marketing research process (Hair et al., 2010:35). The research problem led to the development of primary and secondary objectives.

5.2.2.1 PRIMARY OBJECTIVE

The primary objective of this study is to determine the expectations of black Generation Y adults regarding the CRM dimensions offered by their bank, as well as to identify their overall levels of satisfaction, relationship intention and loyalty toward their banks.

5.2.2.2 SECONDARY OBJECTIVES

This section will provide insights into the secondary objectives set for the study in order to achieve the primary objective. The secondary objectives that the researcher aims to investigate include:  Conducting a literature review to identify the CRM dimensions that can be used in the banking industry;  Identifying the black Generation Y adults’ expectations of the CRM dimensions (service quality, customisation, two-way communication, technology, commitment and convenience) offered by their banks;  Determining the overall satisfaction levels that black Generation Y adults have with their banks;  Determining the overall relationship intention of black Generation Y adults with their banks;  Determining the overall loyalty levels that black Generation Y adults have to their banks;  Determining whether significant differences can be observed between the means of black Generation Y adults’ expectations and the CRM dimensions (service quality, customisation, two-way communication, technology, commitment and convenience) offered by their banks;  Determining whether black Generation Y adults’ satisfaction levels influence the relationship intention with and loyalty levels to their banks;  Determining whether black Generation Y adults’ relationship intention influences their loyalty levels to their banks;  Determining whether significant differences between means can be observed in terms of black Generation Y adults’ expectation levels of the CRM dimensions offered by their banks and demographic variables (gender, education, income, chosen bank and length of time with the bank);  Determining whether significant differences between means can be observed in terms of black Generation Y adults’ satisfaction levels of the CRM dimensions offered by their banks and demographic variables (gender, education, income, chosen bank and length of time with the bank);  Determining whether significant differences between means can be observed in terms of black Generation Y adults’ relationship intention levels of the CRM dimensions offered by their banks and demographic variables (gender, education, income, chosen bank and length of time with the bank);

 Determining whether significant differences between means can be observed in terms of black Generation Y adults’ loyalty levels to the CRM dimensions offered by their banks and demographic variables (gender, education, income, chosen bank and length of time with the bank).

From these secondary objectives the researcher formulated hypotheses which will be discussed in the next section.

5.2.2.3 HYPOTHESES

The following hypotheses have been formulated based on the secondary objectives:

H2a: Black Generation Y adults’ satisfaction levels significantly and positively influence relationship intention with their banks.

H2b: Black Generation Y adults’ relationship intention levels significantly and positively influence loyalty to their banks.

H2c: Black Generation Y adults’ satisfaction levels significantly and positively influence loyalty to their banks. H3: There is a significant difference between the means of black Generation Y adults’ expectations of the service quality offered by their banks and demographic variables.

H3a: There is a significant difference between the means of black Generation Y adults’ expectations of the service quality offered by their banks and gender.

H3b: There is a significant difference between the means of black Generation Y adults’ expectations of the service quality offered by their banks and education.

H3c: There is a significant difference between the means of black Generation Y adults’ expectations of the service quality offered by their banks and income.

H3d: There is a significant difference between the means of black Generation Y adults’ expectations of the service quality offered by their chosen bank.

H3e: There is a significant difference between the means of black Generation Y adults’ expectations of the service quality offered by their banks and length of time with the bank. H4: There is a significant difference between the means of black Generation Y adults’ expectations of the customisation offered by their banks and demographic variables.

H4a: There is a significant difference between the means of black Generation Y adults’ expectations of the customisation offered by their banks and gender.

H4b: There is a significant difference between the means of black Generation Y adults’ expectations of the customisation offered by their banks and education.

H4c: There is a significant difference between the means of black Generation Y adults’ expectations of the customisation offered by their banks and income.

H4d: There is a significant difference between the means of black Generation Y adults’ expectations of the customisation offered by their chosen bank.

H4e: There is a significant difference between the means of black Generation Y adults’ expectations of the customisation offered by their banks and length of time with the bank. H5: There is a significant difference between the means of black Generation Y adults’ expectations of the two-way communication offered by their banks and demographic variables.

H5a: There is a significant difference between the means of black Generation Y adults’ expectations of the two-way communication offered by their banks and gender.

H5b: There is a significant difference between the means of black Generation Y adults’ expectations of the two-way communication offered by their banks and education.

H5c: There is a significant difference between the means of black Generation Y adults’ expectations of the two-way communication offered by their banks and income.

H5d: There is a significant difference between the means of black Generation Y adults’ expectations of the two-way communication offered by their chosen bank.

H5e: There is a significant difference between the means of black Generation Y adults’ expectations of the two-way communication offered by their banks and length of time with the bank. H6: There is a significant difference between the means of black Generation Y adults’ expectations of the technology offered by their banks and demographic variables.

H6a: There is a significant difference between the means of black Generation Y adults’ expectations of the technology offered by their banks and gender.

H6b: There is a significant difference between the means of black Generation Y adults’ expectations of the technology offered by their banks and education.

H6c: There is a significant difference between the means of black Generation Y adults’ expectations of the technology offered by their banks and income.

H6d: There is a significant difference between the means of black Generation Y adults’ expectations of the technology offered by their chosen bank.

H6e: There is a significant difference between the means of black Generation Y adults’ expectations of the technology offered by their banks and length of time with the bank. H7: There is a significant difference between the means of black Generation Y adults’ expectations of the commitment offered by their banks and demographic variables.

H7a: There is a significant difference between the means of black Generation Y adults’ expectations of the commitment offered by their banks and gender.

H7b: There is a significant difference between the means of black Generation Y adults’ expectations of the commitment offered by their banks and education.

H7c: There is a significant difference between the means of black Generation Y adults’ expectations of the commitment offered by their banks and income.

H7d: There is a significant difference between the means of black Generation Y adults’ expectations of the commitment offered by their chosen bank.

H7e: There is a significant difference between the means of black Generation Y adults’ expectations of the commitment offered by their banks and length of time with the bank. H8: There is a significant difference between the means of black Generation Y adults’ expectations of the convenience offered by their banks and demographic variables.

H8a: There is a significant difference between the means of black Generation Y adults’ expectations of the convenience offered by their banks and gender.

H8b: There is a significant difference between the means of black Generation Y adults’ expectations of the convenience offered by their banks and education.

H8c: There is a significant difference between the means of black Generation Y adults’ expectations of the convenience offered by their banks and income.

H8d: There is a significant difference between the means of black Generation Y adults’ expectations of the convenience offered by their chosen bank.

H8e: There is a significant difference between the means of black Generation Y adults’ expectations of the convenience offered by their banks and length of time with the bank. H9: There is a significant difference between the means of black Generation Y adults’ overall satisfaction with their banks and demographic variables.

H9a: There is a significant difference between the means of black Generation Y adults’ overall satisfaction with their banks and gender.

H9b: There is a significant difference between the means of black Generation Y adults’ overall satisfaction with their banks and education.

H9c: There is a significant difference between the means of black Generation Y adults’ overall satisfaction with their banks and income.

H9d: There is a significant difference between the means of black Generation Y adults’ overall satisfaction with their chosen bank.

H9e: There is a significant difference between the means of black Generation Y adults’ overall satisfaction with their banks and length of time with the bank. H10: There is a significant difference between the means of black Generation Y adults’ overall relationship intention with their banks and demographic variables.

H10a: There is a significant difference between the means of black Generation Y adults’ overall relationship intention with their banks and gender.

H10b: There is a significant difference between the means of black Generation Y adults’ overall relationship intention with their banks and education.

H10c: There is a significant difference between the means of black Generation Y adults’ overall relationship intention with their banks and income.

H10d: There is a significant difference between the means of black Generation Y adults’ overall relationship intention with their chosen bank.

H10e: There is a significant difference between the means of black Generation Y adults’ overall relationship intention with their banks and length of time with the bank. H11: There is a significant difference between the means of black Generation Y adults’ overall loyalty to their banks and demographic variables.

H11a: There is a significant difference between the means of black Generation Y adults’ overall loyalty to their banks and gender.

H11b: There is a significant difference between the means of black Generation Y adults’ overall loyalty to their banks and education.

H11c: There is a significant difference between the means of black Generation Y adults’ overall loyalty to their banks and income.

H11d: There is a significant difference between the means of black Generation Y adults’ overall loyalty to their chosen bank.

H11e: There is a significant difference between the means of black Generation Y adults’ overall loyalty to their banks and length of time with the bank.

The next section will look at the chosen research design for this study.

5.2.3 STEP 3: THE RESEARCH DESIGN

A research design is considered to be the master plan or blueprint used to achieve the research objectives, as previously discussed (Zikmund et al., 2010:66). In selecting the research design, the researcher first needs to determine whether use should be made of quantitative or qualitative research data.

5.2.3.1 QUANTITATIVE AND QUALITATIVE RESEARCH

Quantitative research can be defined as research which places significant emphasis on using formal questions with predetermined response options through questionnaires or surveys administered to large numbers of respondents (Hair et al., 2010:77). Zikmund et al. (2010:134) define quantitative research as research that addresses the research objectives through empirical assessments that involve numerical approaches and statistical analyses. Quantitative research enables the researcher to make accurate predictions about the relationships between market factors and behaviours, and gain insights into those relationships and validate them. Lastly, it allows researchers to test hypotheses (Hair et al., 2010:77-78).

Qualitative research can be defined as research addressing marketing objectives through techniques such as focus groups, observations and in-depth interviews that allow the researcher to interpret certain market phenomena without having to depend on numerical statistics (Zikmund & Babin, 2007:82).

Quantitative research is used for the purposes of this study for the following reasons as suggested by Zikmund et al. (2012:136 & 147) and Hair et al. (2010:78):

 The researcher is an uninvolved observer and thus results are objective;  Large samples will be used to produce generalisable results of the population;  Quantitative data can provide quick, inexpensive and efficient data;  The researcher can apply simple statistical tools to analyse the data.

The next phase in step 3 involves selecting the appropriate research design for the study.

5.2.3.2 RESEARCH DESIGNS

There are three types of research designs to choose from, which include: exploratory research (which focuses on the discovery of ideas and insights), descriptive research (which focuses on the relationship between two variables), and, causal research (which emphasises a cause-and- effect relationship) (Churchill & Iacobucci, 2005:74).

For the purposes of this study the researcher has made use of descriptive research since Zikmund and Babin (2007:83) state that descriptive research is best suited to quantitative research. Descriptive research can be defined as a type of research design that describes the characteristics of a given research problem (Zikmund & Babin, 2010:45). Iacobucci and Churchill (2010:84) state that descriptive research should be used to:  Describe the characteristics of certain groups of people;  Estimate the amount of individuals reacting and behaving in a certain way.

Descriptive research supplies prior knowledge on the phenomena studied, as is depicted in the literature and thus rests on one or more specific hypotheses (Churchill & Iaocobucci, 2005:107). These hypotheses guide the research in the right direction making descriptive research much more rigid in contrast to exploratory research, which is much more flexible (Churchill & Iaocobucci, 2005:107).

The reason for selecting a descriptive research design for the purposes of this study is that a clear understanding of the research problem exists, as can be seen in Section 5.2.1. Descriptive research has been used to describe the characteristics of the customers (black Generation Y adults) in terms of their expectations of the South African banking industry (Zikmund & Babin, 2010:45). The next section will focus on conducting secondary research as a step in providing background to the research.

5.2.4 STEP 4: CONDUCT SECONDARY RESEARCH

Secondary data can be defined as data that has been previously collected and recorded by another person for purposes other than the current research project (Malhotra, 2007:106). This data is said to be historical and requires no further access to research respondents as it is already assembled (Zikmund & Babin, 2010:123).

Secondary data holds advantages for a researcher such as availability and cost effectiveness (it is relatively inexpensive compared to primary data and can be obtained much more quickly than primary data). Secondary data provides input into the literature to better explain the industry as well as the background to the study. Researchers must be careful not to rely on secondary data too much (merely for its availability), but must rather make sure that the research is relevant, useful and reliable (Zikmund & Babin, 2010:124). For the purposes of this study, the researcher has made use of secondary information sources such as books, academic journals, websites, dissertations and theses.

Although secondary data can be useful in explaining similar situations, it will not able to explain the current existing situation and thus it is necessary to select a primary research method in order to collect primary data (Malhotra, 2007:106). This is discussed in the next section.

5.2.5 STEP 5: SELECT A PRIMARY RESEARCH METHOD

Bradley (2010:112) defines primary data as the collection of original information from the marketplace. Churchill and Iacobucci (2005:167) define primary data as research that is originated by the researcher for the purpose of investigating the current problem at hand. From the collection of primary data meaningful insights can be gathered. For the purposes of this study, insights into black Generation Y adults’ expectations, satisfaction levels, relationship intentions and loyalty were gained through the gathering of primary data.

This step includes a discussion of the following subsections: the data gathering technique and the survey method chosen, the questionnaire, the choice of scales selected with applicable reasons, the pretesting of the questionnaire, the validity of the questionnaire, and, lastly, the reliability of the questionnaire in gathering the data.

5.2.5.1 DATA GATHERING TECHNIQUE AND THE SURVEY METHOD CHOSEN

In selecting a data gathering technique, the researcher needs to consider whether the method will answer the questions that need to be answered, whether the technique will reach a representative sample as well as whether the technique will be cost effective, time efficient and consider the literacy levels of the sample population (Malhotra, 2007:338). Roberts (2007) states that choosing the best data gathering technique will inherently depend on the strengths and weaknesses of that technique (measured in terms of other techniques). The goal is then to choose a technique with the most strengths and the fewest weaknesses based on the needs of the study conducted. Malhotra (2007:184) recommends the following data gathering techniques: telephone interviewing, personal interviewing, mail interviewing, and electronic interviewing.

Based on the strengths and weaknesses of each method, it was decided that the researcher would make use of personal interviewing in the form of a person-administered questionnaire. According to Hair et al. (2010:107), there are two types of person-administered questionnaires: in-home interviews and mall intercepts. In-home interviews can be described as personal interviews conducted at respondents’ homes to increase participation rates (Zikmund & Babin, 2010:159). Mall intercepts can be defined as personal interviews conducted in a shopping mall. The latter has been used for the purposes of this study. This method was chosen for cost effectiveness since fieldworkers did not have to travel to respondents’ homes and since the researcher did not have residential addresses for respondents (Zikmund & Babin, 2010:160). Table 5.1 lists the advantages and disadvantages for person-administered questionnaires that were considered before choosing this method.

Table 5.1: The advantages and disadvantages of person-administered questionnaires Advantages Disadvantages Adaptability (fieldworkers can adapt to Fieldworkers may wrongly record responses to respondents’ differences) questions The fieldworkers can insure the quality of Expensive endeavour responses in screening respondents beforehand

Table 5.1: Continued Advantages Disadvantages The fieldworkers can provide feedback to Fieldworker-respondent interaction error (the respondents while the respondents are answering respondent might consider a fieldworkers’ body the questionnaire language as a clue to answer a question in a Fieldworkers can create a comfort zone for certain way) respondents by helping them through the process and making the process more interesting Can accommodate large samples Convenient to administer and record respondents’ answers Source: Hair et al. (2010:108).

Once a data gathering technique has been selected, a research instrument needs to be developed. In the case of this study, since a person-administered research method was selected where questionnaires were distributed, the following section provides insight into the questionnaire (measuring instrument) used in this study.

5.2.5.2 QUESTIONNAIRE

A questionnaire can be defined as a set of questions used to collect data for research purposes (Doyle, 2011:322). The research design directed the researcher in choosing to use a person- administered questionnaire as the primary research instrument in gathering data for the purposes of this study. Malhotra (2012) suggests that the most difficult aspect of the questionnaire is setting the wording so that respondents can understand it. For this purpose, the researcher had to consider the target respondents and whether they would understand each statement. To avoid problems in the wording, the researcher followed four guidelines proposed by Malhotra (2012) which include:  Defining the issue at hand (items needed to address the research at hand);  Using ordinary words;  Avoiding ambiguous words;  Avoiding leading questions.

In following these guidelines, the researcher was able to construct items that could be easily understood by respondents. Additionally, the questionnaire was pretested among the target population to ensure all items were understood correctly.

In setting up the questionnaire, the researcher was also confronted with a choice between two communication methods. The first includes the structure and the second includes the disguise. The structure is the degree of standardisation imposed on the questionnaire (Iacobucci & Churchill, 2010:188). This entails structured or close-ended questions where predetermined responses have been permitted and unstructured or open-ended questions where respondents are free to answer in their own words and highlight their own opinions (Iacobucci & Churchill, 2010:188). The disguise of the questionnaire refers to the amount of knowledge about the purpose of the study communicated to the respondent (Iacobucci & Churchill, 2010:188). Undisguised questions make the purpose of the study clear to respondents whereas disguised questions try to hide the purpose of the study as to eliminate respondent bias towards a certain product, industry or situation (Churchill & Iacobucci, 2005:215).

For the purposes of this study, structured-undisguised methods were chosen. Churchill and Iacobucci (2005:215) define structured-undisguised questionnaires as containing questions that are presented to all respondents in exactly the same order and wording in order to compare answers. The authors state that these questionnaires are the most commonly used in marketing practice due to their standardisation and ease of recording, which assists the researcher greatly.

The questionnaire used in the study (Annexure 2) opens with a cover letter. Zikmund et al. (2010:222) define a cover letter as a letter that accompanies the questionnaire with the aim of introducing the research and persuading the respondent to complete the questionnaire. Hair et al. (2010:192) suggest that clear identification of the organisation conducting the research is needed in order to generate trust with respondents. A University of Johannesburg letterhead was used (on which the university logo is displayed) as well as contact information for the university, the researcher, and the supervisor for the study. The cover letter must include items describing the nature of the study as well as its importance (Hair et al., 2006:462 in Burin, 2010:211). The cover letter provided a description of the nature of the study. It furthermore assured respondents of their anonymity and confidentiality and stated that participation in the study was voluntary. The cover letter also indicated the approximate amount of time that it

might take a respondent to answer the questionnaire. No compensation or incentives were offered to respondents due to possible cost increases. The researcher also wished to encourage respondents to complete the questionnaire truthfully. To make the process as simple and clear as possible, basic instructions were included in the cover letter. After the cover letter, screening questions were also included. A screening question can be defined as the preliminary research question or questions that are asked at the beginning of an interview or questionnaire to determine whether the respondent is suitable for the particular study (Doyle, 2011:341). The screening question was used to determine whether potential respondents qualified to answer the remainder of the questionnaire. The screening questions specifically focused on three aspects and aimed to determine whether the respondent i) had banked or was, at the time, banking with one of the four major banks (ABSA, FNB, Standard Bank or Nedbank) in South Africa, ii) had had that bank account for a period of three years or longer and iii) fell in the required age cohort at which the study was aimed. The second screening question was based on previous literature by De Meyer and Petzer (2012:29) which suggests that being a customer of an organisation for three years or longer is indicative of a relationship. If respondents satisfied all three criteria, they could continue with the remainder of the questionnaire. If they did not qualify, the fieldworker thanked them for their cooperation and ended the interview.

The questionnaire consisted of three sections. Section A aimed at gathering responses pertaining to CRM dimensions as found in the literature. Section B aimed at gathering responses pertaining to satisfaction, relationship intention and loyalty. Section C gathered responses pertaining to demographic variables. In developing Sections A and B of the questionnaire, the researcher adopted scales from previous studies and literature to determine possible dimensions of CRM, satisfaction, relationship intention and loyalty as indicated in Table 5.2.

Table 5.2: Literature in developing items Dimension/Construct Literature Service quality Zeithaml et al. (2009:152-153) Customisation Wong et al. (2008:143) Two-way communication Hashem (2012:132) Use of technology Sangle and Awasthi (2011:907) Commitment Dagger et al. (2011:280)

Table 5.2: Continued Dimension/Construct Literature Convenience Foscht et al. (2009:230) Satisfaction Dagger and Sweeney (2007:36) Relationship Intention Yi-Ming and Chin-Fu (2010) Loyalty Dagger et al. (2011:280)

Section A included thirty five items with which to measure customer expectations. The goal was to determine what customers expected from their banks regarding the seven CRM dimensions previously discussed. As stated in Table 5.2, the items used to measure each CRM dimension were adopted from previous studies. Respondents were requested to indicate their level of agreement (expectation) for each item on a seven-point Likert scale (see Section 5.2.5.3).

Section B aimed to determine respondents’ overall level of satisfaction, relationship intention, and loyalty to their banks. The items used in this section were adopted from previous studies as indicated in Table 5.2. Satisfaction was measured on a seven-point Likert scale where respondents indicated their level of agreement on each item. Relationship intention and loyalty were also measured on a seven-point Likert scale, but here respondents had to indicate their level of likeliness, where 1 is not likely at all and 7 is very likely (see Section 5.2.5.3).

Various demographic questions with predetermined answers were presented to respondents in Section C. This section consisted of seven questions. The first four questions asked basic demographic questions such as gender, highest level of education, marital status and income. As certain questions are personal in nature, such as respondent income, it was decided to place the demographic questions in the final section in the questionnaire. The last three demographic questions pertained to the banking industry with questions determining the types of accounts the respondents hold with the bank, the length of time respondents have been with the bank, and the medium which respondents felt will most likely enhance their relationship with the bank.

5.2.5.3 THE CHOICE OF SCALE

For the purposes of this study a seven-point Likert scale was used in the questionnaire. Bradley (2010:199) defines a Likert scale as a summated rating scale measuring individual attitudes. Burin (2010:214) states that the Likert scale normally consists of a two part process: the first is the item or statement part and the second is the assessment part where items are measured according to answer categories. In choosing the seven-point Likert scale, the researcher considered the different advantages that this scale holds. The following includes a list of those advantages:  The scale makes the study free from response bias (Bradley, 2010:200).  The seven-point scale allows for the detection of smaller differences compared to a five-point scale (Veldhuyzen van Zanten, Chiba, Armstrong, Barkun, Thomson, Mann, Escobedo, Chakraborty & Nevin, 2006:527).  The seven-point Likert scale is more likely to record a respondent’s true objective evaluation (Finstad, 2010:108).  The seven-point Likert scale is sensitive enough to record a more accurate evaluation (Finstad, 2010:109).  The Likert scale is easy for the researcher to construct and easy for the respondent to understand (Malhotra, 2012).

Based on these advantages, the researcher decided to make use of a seven-point Likert scale rather than a five-point Likert scale.

In Section A of the questionnaire (see Annexure 2), which consisted of 35 items measuring expectations, the researcher made use of a seven-point Likert scale, where 1 signalled strong disagreement and 7 strong agreement. In Section B, which consisted of 10 items measuring satisfaction, relationship intention and loyalty, the researcher made use of a seven-point Likert scale (where 1 signalled strong disagreement and 7 strong agreement). In measuring relationship intention and loyalty the researcher also made use of a seven-point Likert scale where 1 signalled a very small likelihood and 7 great likelihood. Section C of the questionnaire included nominal and ordinal scales. Table 5.3 indicates each dimension measured with the different items as well as the scale used.

Table 5.3: Dimensions, items and scales used Dimension No. Item Response Scale type format SECTION A Service Quality 1 My bank should have up-to-date equipment Scaled Likert (Interval) 2 My bank’s physical facilities should be visually appealing Scaled Likert (Interval) 3 My bank’s employees should be well dressed and appear neatly Scaled Likert (Interval) 4 When my bank promises to do something by a certain time, they should do it Scaled Likert (Interval) 5 When I have a problem my bank must be sympathetic Scaled Likert (Interval) 6 My bank should be dependable Scaled Likert (Interval) 7 My bank should keep accurate records of my accounts Scaled Likert (Interval) 8 My bank should inform me exactly when services I requested will be performed Scaled Likert (Interval) 9 The bank’s employees must always be willing to help me Scaled Likert (Interval) 10 Employees of the bank should be available to respond to my requests promptly Scaled Likert (Interval) 11 I should be able to trust the employees of my bank Scaled Likert (Interval) 12 My bank’s employees should be polite Scaled Likert (Interval) 13 I expect of my bank to give me individual attention Scaled Likert (Interval) 14 It is realistic to expect that my bank has my best interest at heart Scaled Likert (Interval) 15 My bank is expected to have operating hours that are convenient to me Scaled Likert (Interval) Customisation 16 I should be able to rely on my bank to customise services according to my needs Scaled Likert (Interval) 17 My bank and I should make changes to customise my relationship-specific Scaled Likert (Interval) investments 18 My bank should be flexible in serving my needs Scaled Likert (Interval) 19 My bank should make an effort to find out what my needs are Scaled Likert (Interval)

Table 5.3: Continued

Dimension No. Item Response Scale type format Two-way 20 My bank should provide me with complete information when there is a new product or Scaled Likert (Interval) communication service 21 My bank should provide me with timely information Scaled Likert (Interval) 22 My bank should provide me with trustworthy information Scaled Likert (Interval) 23 My bank should have the ability to openly discuss solutions to my problems Scaled Likert (Interval) Use of 24 Overall, my bank should have easy-to-use technology (e.g. ATMs, self-service kiosks, Scaled Likert (Interval) technology mobile applications, internet banking) 25 Learning to use my bank’s technologies should be easy Scaled Likert (Interval) 26 Using my bank’s technologies should make it easier for me to do my banking Scaled Likert (Interval) Commitment 27 My bank should be committed to forming relationships with me Scaled Likert (Interval) 28 My relationship with my bank should be very important to them Scaled Likert (Interval) 29 My relationship with my bank should deserve their maximum effort to maintain Scaled Likert (Interval) 30 My bank should be prepared to make short-term sacrifices to maintain our relationship Scaled Likert (Interval) 31 I believe my bank and I should view our relationship as a long-term partnership Scaled Likert (Interval) Convenience 32 My bank should be conveniently located Scaled Likert (Interval) 33 My bank’s ATMs should be conveniently located Scaled Likert (Interval) 34 My bank’s internet platform should be easy to use Scaled Likert (Interval) 35 My bank’s self-service kiosks need to be conveniently located Scaled Likert (Interval)

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Table 5.3: Continued

Dimension No. Item Response Scale type format SECTION B Satisfaction 36 My feelings toward my bank are positive Scaled Likert (Interval) 37 I feel good about using my bank as my service provider Scaled Likert (Interval) 38 I feel satisfied that the results from using my bank are the best that I can currently Scaled Likert (Interval) obtain 39 The extent to which I have been using my bank has produced the best possible Scaled Likert (Interval) outcome Relationship 40 I will continue doing business with my bank Scaled Likert (Interval) intention 41 I will recommend my bank to others as a result of my positive experience Scaled Likert (Interval) 42 If a competing bank offers me lower banking fees, I will still make use of my current Scaled Likert (Interval) bank Loyalty 43 I say positive things about my bank to other people Scaled Likert (Interval) 44 I consider my bank to be the first choice of bank Scaled Likert (Interval) 45 I will remain loyal to my bank Scaled Likert (Interval) SECTION C Gender 1 1. Male Dichotomous Nominal 2. Female

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Table 5.3: Continued

Dimension No. Item Response Scale type format Education 2 1. Primary school completed Multiple- Nominal 2. Matric / Grade 12 choice 3. Diploma / Certificate 4. Bachelor’s degree 5. Postgraduate degree / Qualification Marital Status 3 1. Single Multiple- Nominal 2. Married choice 3. Divorced 4. Widowed 5. Living together 6. Separated Personal monthly 4 1. R0 – R3 000 Multiple- Ordinal income (after tax) 2. R3 001 – R5 000 choice 3. R5 001 – R7 000 4. R7 001– R10 000 5. R10 001 – R15 000 6. R15 001 – R20 000 7. R20 001 –R25 000 8. R25 001 – R30 000 9. R30 001 – R35 000 10. R35 001 – R40 000

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Table 5.3: Continued

Dimension No. Item Response Scale type format 11. R40 001 – R45 000 12. R45 001 – R50 000 13. R50 001 and more Chosen account 5 1. Cheque Accounts Multiple- Nominal held with bank 2. Savings Account choice 3. Mzansi Account 4. Investment Account(s) 5. Bond/Home Loan 6. Vehicle Finance 7. Loan (Any other loan) 8. Other (Please specify): Years with the 6 1. 3 years or more, but less than 5 years Multiple- Ordinal bank 2. 5 years or more, but less than 7 years choice 3. 7 years or more, but less than 9 years 4. More than 9 years Platform that will 7 1. Mobile/Cellphone banking Multiple- Nominal enhance the 2. Telephone banking choice relationship with 3. Online/Internet banking the bank 4. A banking application 5. In branch banking

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Table 5.4 provides the links between the secondary objectives identified for the study and the sections in the questionnaire aiming to reach the objective.

Table 5.4: Link between the secondary objectives and sections in the questionnaire No Secondary objective Items in questionnaire 1 Conduct a literature review to identify the CRM dimensions that can be used in N/A the banking industry. 2 Identify the black Generation Y adults’ expectations of the CRM dimensions Section A offered by their banks. Q1-35 3 Determine the overall satisfaction levels that black Generation Y adults have Section B with their banks. Q36-39 4 Determine the overall relationship intention of black Generation Y with their Section B banks. Q40-42 5 Determine the overall loyalty levels that black Generation Y adults have to their Section B banks. Q43-45 6 Identify whether significant differences can be observed between black Section A Generation Y adults’ expectations and the CRM dimensions (service quality, Q1-35 customisation, two-way communication, technology, commitment and convenience) offered by their banks. 7 Identify whether black Generation Y adults’ satisfaction levels influence the Section B relationship intention with and loyalty levels to their banks. Q36-45 8 Identify whether black Generation Y adults’ relationship intention influences Section B their loyalty levels to their banks. Q40-45 9 Determine whether significant differences between means can be observed in Section A terms of black Generation Y adults’ expectation levels of the CRM dimensions Q1-35 offered by their banks and demographic variables (gender, education, income, Section C chosen bank, and length of time with the bank). Q1-6 10 Determine whether significant differences between means can be observed in Section B terms of black Generation Y adults’ satisfaction levels with the CRM Q36-39 dimensions offered by their banks and demographic variables (gender, Section C education, income, chosen bank, and length of time with the bank). Q1-6 11 Determine whether significant differences between means can be observed in Section B terms of black Generation Y adults’ relationship intention levels with the CRM Q40-42 dimensions offered by their banks and demographic variables (gender, Section C education, income, chosen bank, and length of time with the bank). Q1-6

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Table 5.4: Continued No Secondary objective Items in questionnaire 12 Determine whether significant differences between means can be observed in Section B terms of black Generation Y adults’ loyalty levels to the CRM dimensions Q43-45 offered by their banks and demographic variables (gender, education, income, Section C chosen bank and length of time with the bank). Q1-6

Since all the items in the questionnaire answer all the outlined objectives, the next section will look at the pretesting of the questionnaire.

5.2.5.4 PRETESTING OF THE QUESTIONNAIRE

Before the questionnaire was fielded it had to be pretested. Zikmund and Babin (2010:178) define pretesting of the questionnaire as a trial run with a group of respondents who represent the sample to determine whether there are any problems with the questionnaire. Burin (2010:220-221) suggests that these problems include: difficulty in understanding the questionnaire, the use of ambiguous or biased questions, the use of hard to understand wording, and the use of inadequate instructions for respondents to follow. Malhotra (2012) suggests that pretesting should be done on a small sample of respondents (between about 15 to 30) in order to eliminate problems that may occur.

Pretesting was done on a representative sample of individuals who had similar characteristics to this study’s ultimate sample. The pretesting was also conducted in a similar environment to that used for the primary study. Pretesting was conducted by the researcher in order to be able to communicate any possible problems to field workers that might occur during the fieldwork stage of the primary study. The researcher pretested 30 questionnaires in terms of question content, wording, sequence, form and layout, question difficulty, and the comprehensibility of the instructions as outlined by Malhotra (2012).

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5.2.5.5 VALIDITY OF THE QUESTIONNAIRE

Zikmund and Babin (2010:250) define validity as the precision of a measure to which a score truthfully represents a concept. In more basic terms, the authors refer to validity as the ability of a measure to indeed measure what it is supposed to measure. The importance of validity cannot be overstressed, since any lack in the validity of the measures will also result in faulty conclusions from those measures (Zikmund & Babin, 2010:250). In testing the validity of the study, three basic aspects were considered: content validity, criterion validity, and construct validity.

 Content validity Iacobucci and Churchill (2010:256) define content validity as the adequacy of the area in which characteristics are captured by the measure. Zikmund and Babin (2010:250) and Malhotra (2007:286) define the concept as the subjective agreement among experts that the scale reflects the concept being measured. Zikmund and Babin (2010:250) further state that when an inspection of these test items convinces professionals that the items match the definition, it is said to have content validity. In determining content validity the researcher adopted scales and scale items from previous studies such as Hashem (2012:132), Dagger et al. (2011:280), Sangle and Awasthi (2011:907), Foscht et al. (2009:230), Zeithaml et al. (2009:152-153), and Wong et al. (2008:143), as illustrated in Table 5.2.

 Criterion validity Criterion validity, according to Zikmund and Babin (2010:250), addresses whether the measure of this study correlates with the measures of similar concepts. Iacobucci and Churchill (2010:256) and Malhotra (2007:286) define criterion validity as the ability of a measure in predicting some other characteristic of the individual. Criterion validity operates on the basis of two classifications. The first is concurrent validity which is defined as a new measure taken at the same time as the criterion measure that is shown to be valid (Zikmund & Babin, 2010:251). The second classification is predictive validity which is established when a new measure predicts a future event (Zikmund & Babin, 2010:251; Malhotra, 2007:286). In measuring the expectations (Section A of the questionnaire), the researcher depends on concurrent validity to determine what respondents expect. In measuring satisfaction, relationship intention and loyalty (Section B of the questionnaire), the researcher relies on predictive validity to determine

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whether respondents are satisfied with their banks and also whether they are willing to remain loyal to their banks.

 Construct validity Iacobucci and Churchill (2010:257) and Malhotra (2007:287) define construct validity as the ability or the degree to which the instrument measures what it is supposed to measure. Zikmund and Babin (2010:251) state that construct validity exists when the measure reliably measures and truthfully represents a unique concept. In setting up the questionnaire, the researcher made use of previous studies that have all proven reliable. The questionnaire was also pretested to ensure construct validity.

5.2.5.6 RELIABILITY OF THE QUESTIONNAIRE

Hair et al. (2010:156) define reliability as the extent to which a scale can obtain consistent measurement results across repeated trials. In more basic terms, reliability is a measure of constancy in measurement that is alternatively referred to as internal consistency (Malhotra, 2007:284). To assess internal consistency, two popular techniques exist: split-half tests and coefficient alpha.

Hair et al. (2010:157) define split-half tests as the process where questions are divided into two halves and the resulting halves’ scores are correlated against one another. Low correlations between the halves indicate poor internal consistency whereas high correlations between halves indicate good internal consistency (Hair et al., 2010:157). The second technique, coefficient alpha (Cronbach alpha), is defined as a technique that calculates the average of all split-half measures that result from differences in the division of the scale questions. In establishing the extent to which these individual items correlate collectively with the scale, the reliability of the scale was determined by using the Cronbach alpha measurement technique. The coefficient value of the Cronbach alpha ranges from 0 (no reliability) to 1 (complete reliability), where 0.7 upwards is considered reliable (Malhotra, 2007:285). A Cronbach alpha value of between 0.6 and 0.7 can be viewed as fairly reliable within the social sciences, whereas any values below 0.6 can be viewed as unreliable (Malhotra, 2007:285). The reliability of the questionnaire will be further discussed in Chapter 6 (see section 6.5.1). The next section will include an in-depth discussion on the research frame that was used in gathering data.

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5.2.6 STEP 6: DETERMINE THE RESEARCH FRAME

Burin (2010:224) defines the research frame as the process followed in selecting the respondents to be surveyed for the purposes of the research. Since the researcher is not able to reach the whole population, it is important to obtain a representative sample of the population. This representative sample must possess the same or similar characteristics to the population and allow the researcher to make projections about the bigger population as a whole (Burin, 2010:224). The following table indicates the chosen research frame for the purposes of this study.

Table 5.5: The research frame to be followed in obtaining a representative sample Target population Black Generation Y adults Sampling units Black Generation Y adults who have been banking with one of the four major banks for a period of three years or longer Sampling frame Sampling units at different shopping malls throughout Gauteng Sampling technique Non-probability, quota sampling (2 stages consisting of quota and convenience sampling) Time period 10 September – 1 October 2012 Extent The Gauteng area Sampling size 600 respondents (Standard Bank = 183, First National Bank (FNB) = 135, Amalgamated Banks of South Africa (ABSA) = 155 and Nedbank = 127) Age cohort Generation Y adults between the ages of 21-34

For the purposes of the study the sampling plan suggested above was followed. Each element of the sampling plan is discussed in the following sections.

5.2.6.1 TARGET POPULATION

In setting up a sampling plan the first question to ask, according to Zikmund et al. (2010:69), is: “Who is to be sampled?” The primary answer to this question is the target population, which could be defined as the totality of cases conforming to some designated characteristics (Churchill & Iacobucci, 2005:680). Hair et al. (2010:131) define the target population as a complete group of individuals sharing similar characteristics which can be identified for the

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purpose of a research project. The target population for this study included all black Generation Y adults aged between 21 and 34 at the time the study was conducted.

5.2.6.2 THE SAMPLING UNIT

Hair et al. (2010:131) define the sampling unit as target population individuals who are available during the sampling process. Zikmund and Babin (2010:307) define it as a group of elements who are eligible for selection in the sample. The sampling units used for this study include all black Generation Y adults between the ages of 21 and 34 who had been banking with one of the four major banks (ABSA, FNB, Standard Bank and Nedbank) in South Africa for a period of three years or longer at the time of the study.

5.2.6.3 SAMPLING FRAME

A sampling frame can be defined as a list of elements from which the researcher will draw the sample for the research (Zikmund et al., 2010:391). The sampling frame was drawn from sampling units in shopping malls in Gauteng where bank branches and ATM’s were located

5.2.6.4 SAMPLING TECHNIQUE

The sampling technique refers to the method or technique used in approaching respondents. Malhotra (2007:340) suggests the existence of two techniques: probability and non-probability sampling. Probability sampling is defined as a procedure which aims to ensure that each element of the population has a fixed chance of being selected (Malhotra, 2007:341). Non- probability sampling can be defined as a technique that draws respondents based on a fieldworker’s personal judgement rather than on a formula for gathering respondents (Hair et al., 2010:135). The researcher made use of non-probability sampling techniques.

There are different types of non-probability methods (each with their own advantages and disadvantages), including: convenience sampling (a technique that attempts to obtain a sample of convenient elements), judgemental sampling (a technique where population elements are purposely selected based on the judgement of the researcher), quota sampling (a two-stage judgemental sampling), and snowball sampling (a technique where an initial group of

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respondents are randomly chosen and subsequent respondents are selected based on referrals from the initial group of respondents) (Malhotra, 2007:341-345).

The researcher made use of quota sampling for the purposes of this study. Quota sampling can be further defined as the selection of prospective respondents based on pre-specified quotas (Hair et al. 2010:139). Malhotra (2007:344) defines quota sampling as a two-stage judgmental sampling. The first stage consists of developing quotas of population elements and the second stage consists of selecting sample elements based on convenience. In the first stage of quota sampling for this study, the quotas selected were based on the market share of each of the four major banks. Thereafter, respondents were selected based on convenience within each quota. Table 5.6 illustrates the quotas used for the purposes of the study based on the market share of the four major banks in South Africa. From Table 5.6 it should be noted that the largest four banks have a total share of 83.7% of the market. The number of questionnaires fielded was determined solely on the basis of the four largest banks.

Table 5.6: Number of questionnaires to be fielded based on quota sampling Bank Market share of Number of the four major questionnaires to be banks (with fielded (without other other banks) banks) ABSA 21.6% 155 FNB 18.8% 135 Nedbank 17.8% 127 Standard Bank 25.5% 183 Total 83.7% 600

In determining these quotas the following formula was used:

where: n = the number of questionnaires fielded per bank; ms = the market share for each bank; tms = the total market share for the four major banks; tq = the total number of questionnaires fielded.

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Once potential respondents were identified on the basis of the screening questions, fieldworkers gathered data from respondents using convenience sampling based on the quotas provided in Table 5.7. Bradley (2010:167) defines convenience sampling as a technique that uses respondents who are easily and conveniently available.

5.2.6.5 TIME AND PERIOD

The time refers to the amount of time field workers will have to field and distribute the questionnaires. Field workers were given three weeks to gather data. The three-week period was not punctuated by any significant changes in the banking industry which could have changed the outcome of this study. Data gathering took place between 10 September and 1 October 2012.

5.2.6.6 EXTENT

The extent refers to the geographic reach of the data gathering process. In this case, the area covered includes regions of Gauteng, primarily Johannesburg and Pretoria. The reason for choosing the Gauteng province is that it represents the economic hub of South Africa and the responses gathered in this area could be considered as representative of the South African population (Okeahalam, 2007:934).

5.2.6.7 SAMPLING SIZE

It is very important to decide on a sampling size that is representative of the whole population of the study. In determining the sample size, the researcher had to consider the purpose of the study, the size of the population, the time, the budget and resources available, as well as the importance of the results of the study (Bradley, 2010:173). Hair et al. (2010:142) suggest that there are no sample size formulas that can be used in non-probability sampling and thus personal judgement by the researcher based on past studies, industry standards or the amounts of resources available is necessitated. In a previous study of the banking industry the researcher (Rootman 2006:113) made use of 264 respondents. For the purposes of this study, the researcher decided to field 600 questionnaires to ensure a spread that surpasses the number of respondents for previous studies. This was done as a precaution in case missing values occurred.

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5.2.6.8 SAMPLING ERRORS

In evaluating the quality of the research frame, the researcher needed to consider certain errors that might arise as a result of a poorly designed research frame. There are two major sources of errors: random sampling errors and systematic errors. Random sampling errors can be defined as statistical fluctuations that occur due to chance variation in the elements selected for a sample, which is usually unavoidable without very large samples (Zikmund et al., 2010:188). Because the study consisted of 600 respondents, the chances of encountering a random sampling error were minimised. The second major source of survey errors is systematic errors, which can be defined as an error occurring due to faulty research design or a mistake in research execution (Zikmund et al., 2010:189). Systematic errors include: non-response error and sample selection error.

 Non-response error A non-response error may occur when the researcher is unsuccessful in retrieving information from the elements of the population selected for the sample (Burin, 2010:242). This type of error may occur if respondents refuse to participate in the research or when a missing value occurs (Malhotra, 2007:437).

 Sample selection error A sample selection error can be defined as an error that results in an unrepresentative sample due to an error in the sampling plan or in the execution of data gathering (Zimund et al., 2010:194; Malhotra, 2007:95). This kind of error may occur for different reasons. For example, fieldworkers conducting fieldwork only during the morning may not encounter working people. In order to avoid sample selection error, fieldworkers were required to conduct fieldwork during morning and afternoon hours.

5.2.7 STEP 7: DATA GATHERING

Once the sampling plan has been formalised, data gathering can begin (Zikmund et al., 2010:69). Data gathering can be defined as the practise of gathering or collecting information by the researcher (Zikmund et al., 2010:69). In gathering the data, trained fieldworkers fielded questionnaires over a three-week time span (10 September – 1 October 2012) across shopping malls in the Gauteng area. To gain a fair distribution within the Gauteng province, this included

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shopping centres such as Cresta, The Glen, Rosebank Mall, Sandton Square, South Gate, Maponya Mall and East Rand Mall in the Johannesburg area, and The Kollonade, Menlyn, Brooklyn, Irene Lifestyle Village and Woodlands Mall in the Pretoria area. In gathering the data, fieldworkers adhered to the quota system prescribed by the researcher. Fieldworkers were trained and given the questionnaires with specific instructions to field the questionnaires during the shopping hours of the respective malls (weekdays as well as weekends). Section 6.2 in Chapter 6 describes the data realisation rate. A total of 600 questionnaires were fielded and 581 were retained for data analysis. This amounts to a realisation rate of 96.8%. After data gathering has taken place it is necessary to analyse the data. The next section will focus on the data analysis conducted.

5.2.8 STEP 8: DATA ANALYSIS

Zikmund and Babin (2010:59) define data analysis as the application of reasoning to understand the data that has been gathered by the researcher. Zikmund et al. (2010:70) state that in its basic form, data analysis may involve determining consistent patterns and drawing conclusions about the relevant details revealed in the study. This section will include a discussion on the coding, capturing, editing and statistical analysis of data.

5.2.8.1 CODING OF DATA

Coding is a procedure in which the researcher takes raw data and transforms it into symbols with the help of a statistical analysis program (Iacobucci & Churchill, 2010:351). The questionnaire was pre-coded so as to expedite the data capturing process. No open-ended questions were included in the questionnaire, so no post-coding was required.

5.2.8.2 DATA CAPTURING

Data has no value to a researcher if it is not converted into a format that answers the main research questions (Burin, 2010:230). For a researcher to explain this data it has to go through a process called data processing. Zikmund et al. (2010:477) describe data processing as the next stage in the research design in which data entry takes place. In basic terms, data processing includes the function of taking the data from the questionnaires and entering it into a

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statistical programme in order to make certain interpretations. Data was captured using SPSS 20.

5.2.8.3 EDITING OF DATA

Iacobucci and Churchill (2010:350) state that the editing of data is the process of imposing certain levels or standards on the raw data to maintain quality. This process, according to the authors, involves the inspection of each questionnaire and the correction or editing of the questionnaire. When questionnaires were received from the fieldworkers, the questionnaires were inspected by the researcher based on face value. As a large number of questionnaires were returned, the researcher removed all questionnaires with four or more missing values. All other data was left unchanged and no means were allocated to missing values due to the size of the sample.

5.2.8.4 STATISTICAL ANALYSIS OF DATA

The statistical analysis of data refers to the analysis that is conducted via some statistical program. All data received was analysed by the researcher using SPSS 20. For the purposes of this study, the following statistical analyses were performed.

 Means A mean refers to the arithmetic average and can be considered as the most common measure of central tendency (Zikmund et al., 2010:415).

 Frequency distribution Hair et al. (2010:160) describe the frequency distribution as the amount of times each possible response to a question was recorded by the respondents. The frequency distribution will be used to test whether the distribution is even across intervals.

 Standard deviation Hair et al. (2010:264) define the standard deviation as the average distance of the distribution values from the mean. In basic terms, the standard deviation refers to the extent to which the data lies away from the mean.

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 Skewness and kurtosis The skewness provides an indication of the symmetry of distribution (Pallant, 2007:56). For a symmetric distribution the values on either side of the centre of distribution are the same and the mean, mode and median are equal (Malhotra, 2007:462). The kurtosis provides information on the “peakedness” of the distribution (Pallant, 2007:56). The kurtosis for a normal distribution is equal to zero (Malhotra, 2007:462). When the kurtosis is positive then the distribution is more peaked than a normal distribution, whereas a negative kurtosis has a flatter peak than a normal distribution (Malhotra, 2007:462).

 T-tests A t-test is used to compare means for a variable grouped into two categories and based on some less-than-interval variables (Zikmund & Babin, 2007:351-352). o The independent sample t-test (which tests the differences between means) is used to compare two means, one being an independent variable such as gender, and the other a dependent variable such as a CRM dimension (service quality, customisation, two-way communication, use of technology, commitment, convenience and attitude of employees) (Zikmund & Babin, 2007:351-352). o The paired sample t-test is defined as a test for comparing the scores of two interval variables and is used, for example, when testing the expectations and satisfaction levels between genders (Zikmund et al., 2010:539).

Results will be considered significant when the p-value between the means of the pairs of items is ≤ 0.05.

 Analysis of variance (ANOVA) An ANOVA is a statistical technique used to determine the differences among means for two or more populations (Zikmund & Babin, 2007:355-357). For example, comparing the means of the sample in terms of the different CRM dimensions and different age categories or for different age categories and satisfaction.

 Factor analysis A factor analysis helps to determine underlying dimensions in a set of questions, thus reducing the number of questions to a few interpretable dimensions which, in turn, permit the researcher to describe the survey results (Eiselen et al., 2005:104-105). This analysis allows the

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researcher to focus on the factors, rather than on individual items (Eiselen et al., 2005:104-105). Since the items used in the questionnaire for each dimension were adopted from previous studies, the researcher aimed to identify whether any sub-dimensions were evident as well as confirm whether the items from the scales were relevant to the study. For this reason, a confirmatory factor analysis (CFA) was conducted (Pallant, 2007:179). The factor analysis process followed in this study is discussed in more detail in Chapter 6 (see Section 6.5).

 Regression analysis According to Pallant (2007:145), regression is based on the correlations observed between variables. It also allows the researcher to examine the interrelationships among these variables or dimensions. In this study, regression analysis was conducted to determine the influences of satisfaction, behavioural intent and loyalty.

5.2.9 STEP 9: REPORTING AND RECOMMENDATIONS

This step entails reporting and making recommendations based on the research findings. Chapter 6 reports the results of the study and presents the results of the hypothesis testing. Chapter 7 then provides recommendations to the banks serving black Generation Y adults (based on the CRM dimensions studied in this research and the results reported in Chapter 6)

5.3 CONCLUSION

The research for this study was conducted by following a nine-step process. The researcher made use of a non-probability sampling technique while using a person-administered questionnaire. The questionnaire items were formulated from previous literature. Fieldworkers were trained and given instructions, based on quota sampling methods (two-stage judgemental sampling), for distributing questionnaires. These methods were chosen to include a fair spread among the four major banks based on market share. After the questionnaires were gathered again, the data was cleaned, edited and analysed. Chapter 6 will provide the results obtained from the data analysis together with the main findings and hypotheses.

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CHAPTER 6

DATA ANALYSIS

6.1 INTRODUCTION

This chapter provides insights into the data analysis and interpretation of results based on the research methodology described in the previous chapter. The chapter commences with a discussion of the realisation rate and the distribution of data. A demographic profile of respondents is provided, followed by the results pertaining to the expectations, satisfaction, relationship intention and loyalty of respondents. Each hypothesis set for the study is tested and discussed in this chapter. When conducting hypothesis testing, both statistical and practical significance are determined. It should be noted that only results which were statistically significant (moderate or high practical significance) are presented and discussed. The main results obtained from the statistical analysis are presented as main findings in each section.

6.2 REALISATION RATE AND DISTRIBUTION OF RESULTS

As discussed in the research methodology in Chapter 5 (see Section 5.2.6.7), 600 questionnaires were distributed based on the quotas identified relative to each banks’ market share. Of the 600 questionnaires distributed, 581 were usable for analysis; thus there was a realisation rate of 96.8%.

In order to determine whether data was normally distributed, it was analysed for skewness and kurtosis. All items fell within the parameters of skewness (absolute value less than 2.00) and kurtosis (absolute value less than 7.00) (Pallant, 2007:56) and thus the data was considered to be normally distributed. Due to both the normal distribution and the large sample size, parametric tests were conducted for hypothesis testing as the assumptions for using parametric tests were met (Palant, 2007:109-110).

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6.3 DEMOGRAPHIC PROFILE

Table 6.1 provides a demographic profile of respondents in relation to their respective banks, gender, highest level of education, marital status, monthly income after tax, chosen bank account(s) held, length of time with particular bank and, lastly, their medium preference for enhancing their relationship with their bank. For each demographic variable, the frequency and percentage is provided in Table 6.1.

Table 6.1: Frequency table indicating the demographic profile of respondents Demographic Variables Frequency % Bank most frequently ABSA 150 25.8 banked with FNB 133 22.9 Standard Bank 176 30.3 Nedbank 122 21.0 Gender Male 282 48.6 Female 298 51.4 Highest level of Primary school completed 9 1.5 education Matric/Grade 12 222 38.3 Diploma/Certificate 124 21.3 Bachelor’s degree 165 28.4 Postgraduate 61 10.5 degree/Qualification Marital status Single 424 73.1 Married 91 15.7 Divorced 5 0.9 Widowed 2 0.3 Living together 54 9.3 Separated 4 0.7 Personal monthly R0 – R3 000 178 34.2 individual income level R3 001 – R5 000 70 13.5 after tax R5 001 – R7 000 47 9.0 R7 001– R10 000 60 11.5 R10 001 – R15 000 62 11.9 R15 001 – R20 000 31 6.0

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Table 6.1: Continued

Demographic Variables Frequency % R20 001 –R25 000 29 5.6 R25 001 – R30 000 15 2.9 R30 001 – R35 000 10 1.9 R35 001 – R40 000 9 1.7 R40 001 – R45 000 5 1.0 R45 001 – R50 000 1 0.2 R50 001 and more 3 0.6 Chosen bank account(s) Cheque Accounts 301 51.8 held at the bank (more Savings Account 356 61.3 than one option could Mzansi Account 9 1.5 be chosen) Investment Account(s) 67 11.5 Bond/Home Loan 40 6.9 Vehicle Finance 60 10.3 Loan (Any other loan) 30 5.2 Banking duration 3 years or more, but less than 268 46.1 5 years 5 years or more, but less than 192 33.0 7 years 7 years or more, but less than 78 13.4 9 years More than 9 years 43 7.5 Medium through which Mobile/Cellphone banking 276 47.7 the relationship with Telephone banking 22 3.8 bank can be enhanced Online/Internet banking 173 29.9 A banking application 31 5.3 In branch banking 77 13.3

From Table 6.1 it can be determined that the majority of respondents bank with Standard Bank (however, it should be noted that quota sampling was used based on the banks overall market share in South Africa – see Section 5.2.6.4 in Chapter 5). Table 6.1 indicates that more female respondents (51.4%) participated in the survey than male respondents (48.6%). The highest percentage of respondents hold at least a matric/grade 12 (38.3%) and are single (73.1%).

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The table also indicates that the highest percentage of these respondents earn between R0 – R3 000 per month (34.2%). The majority of the respondents, 80.1%, (34.2% + 13.5% + 9.0% + 11.5% + 11.9%) earn R15 000 or less per month after tax. Furthermore, respondents hold more than one account with the different banks and the two most common accounts were savings (61.3%) and cheque (51.8%) accounts. The majority of respondents (46.1% + 33.0% = 79.1%) have been banking with their bank for at least 3 years or more, but less than 7 years. Lastly the majority of respondents indicated that their relationship with their banks could be enhanced through the use of mobile/cellphone banking (47.7%), followed by online/Internet banking (29.9%).

6.4 EXPECTATIONS, SATISFACTION, RELATIONSHIP INTENTION, AND LOYALTY DESCRIPTIVES

The following sections provide a descriptive exposition of the expectations of respondents, as per items in the measurement set, pertaining to the CRM dimensions offered by their banks, their general satisfaction levels, relationship intention and loyalty levels. This section therefore aims to provide results pertaining to Secondary Objectives 2, 3, 4, and 5 as discussed in Section 5.2.2.2 in Chapter 5.

6.4.1 EXPECTATIONS OF RESPONDENTS

Section A of the questionnaire tested the expectations respondents have of the CRM dimensions offered by their respective banks. In analysing customer expectations, a series of 35 questions were presented to respondents based on the CRM dimensions identified in the literature review (see Chapter 5, Section 5.2.5.2). These dimensions included: service quality, customisation, two-way communication, technology, commitment, and convenience dimensions. Respondents were requested to rate their expectations of these items measuring each dimension on a seven-point Likert scale where 1 signalled strong disagreement and 7 signalled strong agreement. Table 6.2 indicates the frequency and percentage obtained for each scale item making up all CRM dimensions as well as the mean and standard deviation for each item.

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Table 6.2: The expectations respondents have toward individual CRM dimensions Strongly 2 3 4 5 6 Strongly Std. CRM items Disagree Agree Mean Dev. F % F % F % F % F % F % F %

My bank should have up to date equipment 1 0.2 4 0.7 15 2.6 43 7.4 78 13.4 88 15.1 352 60.6 6.21 1.175

My bank’s physical facilities should be visually 9 1.6 7 1.2 16 2.8 37 6.4 99 17.1 144 24.9 266 46.0 5.95 1.312 appealing My bank’s employees should be well dressed 4 0.7 2 0.3 8 1.4 33 5.7 80 13.8 126 21.8 326 56.3 6.22 1.111 and appear neat When my bank promises to do something by a 1 0.2 1 0.2 1 0.2 23 4.0 41 7.1 95 16.4 416 72.0 6.55 0,858 certain time, they should do it When I have a problem my bank must be 2 0.3 4 0.7 11 1.9 37 6.4 91 15.7 138 23.8 298 51.3 6.13 1.130 sympathetic My bank should be dependable 4 0.7 4 0.7 8 1.4 27 4.7 60 10.4 118 20.5 356 61.7 6.32 1.104 My bank should keep accurate records of my 2 0.3 3 0.5 5 0.9 6 1.0 42 7.3 69 12.0 450 78.0 6.62 0.870 accounts My bank should inform me exactly when services 0 0 0 0 8 1.4 22 3.8 65 11.3 125 21.7 357 61.9 6.39 0.927 I requested will be performed The bank’s employees must always be willing to 1 0.2 0 0 4 0.7 18 3.1 46 8.0 101 17.5 408 70.6 6.53 0.855 help me Employees of the bank should be available to 0 0 0 0 6 1.0 13 2.2 75 13.0 124 21.5 360 62.3 6.42 0.874 respond to my requests promptly I should be able to trust the employees of my 0 0 3 0.5 6 1.0 9 1.6 51 8.9 119 20.7 388 67.4 6.50 0.867 bank My bank’s employees should be polite 0 0 2 0.3 4 0.7 20 3.4 86 14.8 116 20.0 353 60.8 6.36 0.941

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Table 6.2: Continued

Strongly 2 3 4 5 6 Strongly Std. CRM items Disagree Agree Mean Dev. F % F % F % F % F % F % F %

I expect of my bank to give me individual 3 0.5 6 1.0 10 1.7 58 10.0 113 19.5 137 23.7 252 43.5 5.92 1.216 attention It is realistic to expect that my bank has my 7 1.2 9 1.6 21 3.6 56 9.7 86 14.9 137 23.7 263 45.4 5.88 1.362 best interests at heart My bank is expected to have operating hours 9 1.6 8 1.4 14 2.4 72 12.5 121 20.9 108 18.7 246 42.6 5.76 1.381 that are convenient to me I should be able to rely on my bank to 4 0.7 8 1.4 16 2.8 46 7.9 122 21.1 156 26.9 227 39.2 5.85 1.242 customise services according to my needs My bank and I should make changes to 4 0.7 5 0.9 15 2.6 56 9.6 130 22.4 165 28.4 206 35.5 5.79 1.210 customise my relationship-specific investments My bank should be flexible in serving my 4 0.7 5 0.9 12 2.1 29 5.0 107 18.5 161 27.9 259 44.9 6.03 1.156 needs My bank should make an effort to find out what 7 1.2 5 0.9 13 2.3 55 9.6 125 21.9 136 23.8 231 40.4 5.83 1.277 my needs are My bank should provide me with complete 1 0.2 4 0.7 21 3.6 38 6.6 97 16.8 118 20.4 300 51.8 6.07 1.194 information when there is a new product or service My bank should provide me with timely 5 0.9 1 0.2 10 1.7 26 4.5 75 13.0 151 26.1 311 53.7 6.22 1.096 information My bank should provide me with trustworthy 0 0 1 0.2 2 0.3 12 2.1 48 8.3 103 17.9 409 71.1 6.57 0.784 information

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Table 6.2: Continued

Strongly 2 3 4 5 6 Strongly Std. CRM items Disagree Agree Mean Dev. F % F % F % F % F % F % F % My bank should have the ability to openly 2 0.3 2 0.3 4 0.7 21 3.6 69 11.9 140 24.2 340 58.8 6.34 0.970 discuss solutions to my problems Overall, my bank should have easy-to-use 1 0.2 3 0.2 6 1.0 15 2.6 50 8.6 73 12.6 431 74.4 6.55 0.926 technology (e.g. ATMs, self-service kiosks, mobile applications, internet banking) Learning to use my bank’s technologies should 2 0.3 3 0.5 4 0.7 19 3.3 54 9.3 117 20.2 380 65.6 6.44 0.960 be easy Using my bank’s technologies should make it 2 0.3 2 0.3 4 0.7 14 2.4 56 9.7 123 21.4 374 65.0 6.45 0.921 easier for me to do my banking My bank should be committed to forming 3 0.5 4 0.7 14 2.4 24 7.3 92 15.9 151 26.2 271 47.0 6.04 1.175 relationships with me My relationship with my bank should be very 3 0.5 3 0.5 9 1.6 26 4.5 87 15.0 131 22.6 320 55.3 6.22 1.090 important to them My relationship with my bank should deserve 2 0.3 2 0.3 6 1.0 34 5.9 106 18.2 148 25.5 283 48.7 6.13 1.060 their maximum effort to maintain My bank should be prepared to make short- 8 1.4 7 1.2 22 3.8 64 11.0 110 18.9 148 25.5 222 38.2 5.74 1.351 term sacrifices to maintain our relationship I believe my bank and I should view our 4 0.7 5 0.9 12 2.1 55 9.5 108 18.6 142 24.4 255 43.9 5.93 1.224 relationship as a long-term partnership My bank should be conveniently located 1 0.2 3 0.5 2 0.3 15 2.6 67 11.5 127 21.9 366 63.0 6.42 0.910

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Table 6.2: Continued

Strongly 2 3 4 5 6 Strongly Std. CRM items Disagree Agree Mean Dev. F % F % F % F % F % F % F % My bank’s ATMs should be conveniently located 1 0.2 1 0.2 1 0.2 13 2.2 43 7.4 96 16.6 423 73.2 6.59 0.796 My bank’s internet platform should be easy to use 1 0.2 2 0.3 6 1.0 22 3.8 41 7.1 119 20.6 388 67.0 6.47 0.930 My bank’s self-service kiosks need to be 2 0.3 1 0.2 7 1.2 28 4.8 61 10.5 145 25.0 337 58.0 6.32 1.000 conveniently located

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In determining the expectations of each scale item in Section A of the questionnaire and measuring CRM dimensions as indicated in Table 6.2, the individual CRM items most respondents agreed with, include: “My bank should keep accurate records of my accounts” (78.0% of respondents strongly agreed, mean = 6.62, standard deviation = 0.870), “My bank’s ATMs should be conveniently located” (73.2% of respondents strongly agreed, mean = 6.59, standard deviation = 0.796), and lastly “My bank should provide me with trustworthy information” (71.1% of respondents strongly agreed, mean = 6.57, standard deviation = 0.784).

In rating the expectations in Table 6.2 in terms of the individual items, respondents were found to have the lowest levels of agreement pertaining to their expectations of the following individual items: “My bank should be prepared to make short-term sacrifices to maintain our relationship” (only 38.2% of respondents strongly agreed, mean = 5.74, standard deviation = 1.351), “My bank is expected to have operating hours that are convenient to me” (only 42.6% of respondents strongly agreed, mean = 5.76, standard deviation = 1.381), and “My bank and I should make changes to customise my relationship-specific investments” (only 35.5% of respondents strongly agreed, mean = 5.79, standard deviation = 1.210).

 Main Finding 1: Respondents indicated their highest levels of agreement pertaining to the following item: “My bank should keep accurate records of my accounts” (mean = 6.62, standard deviation = 0.870).  Main Finding 2: Respondents indicated their lowest level of agreement pertaining to the following item: “My bank should be prepared to make short-term sacrifices to maintain our relationship” (mean = 5.74, standard deviation = 1.351).

After identifying the level of agreement of expectations for each item as shown in Table 6.2, it is necessary to identify respondents’ overall level of expectations for each CRM dimension (service quality, customisation, two-way communication, technology, commitment, and convenience). This is indicated in Table 6.3. The table includes the overall mean score for each CRM dimension as well as the standard deviation.

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Table 6.3: Overall mean score for each CRM dimension (from highest to lowest) CRM Dimension Mean Standard Deviation Overall convenience 6.46 0.713 Overall technology 6.42 0.779 Overall service quality 6.36 0.642 Overall two-way communication 6.26 0.772 Overall commitment 6.00 0.863 Overall customisation 5.88 0.939

From Table 6.3 it is evident that respondents have the highest level of agreement pertaining to their expectations of the CRM dimension of convenience (mean = 6.46, standard deviation = 0.713), followed by technology (mean = 6.36, Standard deviation = 0.779). Respondents indicated the lowest level of agreement pertaining to their expectations of the CRM dimension of customisation (mean = 5.88, standard deviation = 0.939). It should be noted, however, that all these CRM dimensions still measured above the median of 3.5; this indicates that, although respondents have different levels of CRM dimensions, they still have high expectations of all CRM dimensions.

 Main Finding 3: Respondents indicated their highest levels of agreement pertaining to their expectations of CRM dimensions relating to convenience (mean = 6.46) and the use of technology (mean = 6.42).  Main Finding 4: Respondents indicated their lowest level of agreement pertaining to their expectations of CRM dimensions relating to customisation (mean = 5.88).

6.4.2 SATISFACTION OF RESPONDENTS

Section B in the questionnaire measured respondents’ overall level of customer satisfaction with their banks. This was measured on a seven-point Likert scale where 1 signalled strong disagreement and 7 strong agreement. Table 6.4 provides the frequency and percentages as well as the mean and standard deviation obtained for each item measured in the scale. The table also provides the overall mean and standard deviation for the overall satisfaction scale.

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Table 6.4: Respondent satisfaction with their banks Strongly 2 3 4 5 6 Strongly Std. Satisfaction items Disagree agree Mean Dev. F % F % F % F % F % F % F %

My feelings toward my 12 2.1 13 2.2 17 2.9 86 14.8 136 23.4 148 25.5 169 29.1 5.48 1.410 bank are positive I feel good about using 14 2.4 9 1.6 17 2.9 76 13.1 137 23.6 148 25.5 179 30.9 5.54 1.406 my bank as my service provider I feel satisfied that the 13 2.2 20 3.4 35 6.0 98 16.9 131 22.6 139 24.0 144 24.8 5.25 1.501 results from using my bank are the best that I can currently obtain The extent to which I 10 1.7 18 3.1 36 6.2 96 16.6 124 21.4 155 26.8 140 24.2 5.30 1.456 have been using my bank has produced the best possible outcome Overall satisfaction 5.39 1.321

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Table 6.4 demonstrates that respondents indicated that they strongly agreed with the statement “I feel good about using my bank as a service provider” (30.9% of respondents strongly agreed, mean = 5.54, standard deviation = 1.406). Based on all the scale items, respondents indicated their lowest level of agreement with the statement “I feel satisfied that the results from using my bank are the best that I can currently obtain” (only 24.8% of respondents strongly agreed, mean = 5.25, standard deviation = 1.501). The results also indicate that respondents have a high level of agreement pertaining to their overall level of satisfaction, with an overall mean score of 5.39 (standard deviation = 1.321).

 Main Finding 5: Respondents indicated their highest level of agreement in terms of satisfaction for the following statement: “I feel good about using my bank as a service provider” (mean = 5.54).  Main Finding 6: Respondents indicated their lowest level of agreement in terms of satisfaction for the following statement: “I feel satisfied that the results from using my bank are the best that I can currently obtain” (mean = 5.25).  Main Finding 7: Respondents agreed that they are overall satisfied with the services provided by their respective banks (mean = 5.39).

6.4.3 RELATIONSHIP INTENTION OF RESPONDENTS

Section B of the questionnaire also measured respondents’ relationship intention and loyalty levels. For the purposes of reporting the results these two sections were split. In measuring relationship intention a seven-point Likert scale was used where 1 signalled not likely at all and 7, very likely. Table 6.5 provides the frequency and percentages obtained for each item measured in the scale, as well as the mean and standard deviation in measuring overall relationship intention. The table also provides the overall mean and standard deviation for this scale.

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Table 6.5: Relationship intentions of respondents toward their banks Not likely at all 2 3 4 5 6 Very likely Std.

Relationship intention items F % F % F % F % F % F % F % Mean Dev.

I will continue doing business 16 2.8 9 1.5 24 4.1 74 12.7 127 21.9 133 22.9 198 34.1 5.54 1.474 with my bank I will recommend my bank to 22 3.8 16 2.8 47 8.1 82 14.2 120 20.7 126 21.8 166 28.7 5.25 1.621 others as a result of my positive experience If a competing bank offers me 71 12.2 55 9.5 57 9.8 80 13.8 94 16.2 106 18.3 117 20.2 4.48 2.017 lower banking fees I will still make use of my current bank Overall relationship intention 5.09 1.446

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Table 6.5 indicates that respondents had the highest mean score for the statement “I will continue doing business with my bank” (34.1% of respondents indicated very likely, mean = 5.54, standard deviation = 1.474). Table 6.5 also indicates that respondents had the lowest mean score for the statement “If a competing bank offers me lower banking fees I will still make use of my current bank” (only 20.2% of respondents indicated very likely, mean = 4.48, standard deviation = 2.017). Overall, a 5.09 mean score (standard deviation = 1.446) was observed in terms of respondents’ relationship intention, indicating that they have a high likeliness of having an intention to build relationships with the bank they currently use.

 Main Finding 8: Respondents indicated their highest level of likelihood for the following statement in the relationship intention scale: “I will continue doing business with my bank” (mean = 5.54).  Main Finding 9: Respondents indicated their lowest level of likelihood in the relationship intention scale for the following statement: “If a competing bank offers me lower banking fees I will still make use of my current bank” (mean = 4.48).  Main Finding 10: Overall, respondents indicated that they are likely to continue in their relationship with their current banks (mean = 5.09).

6.4.4 LOYALTY OF RESPONDENTS

In measuring loyalty a seven-point Likert scale was used where 1 signalled not likely at all and 7, very likely. Table 6.6 provides the frequency and percentages obtained for each item measured in the scale, as well as the mean score and standard deviation in measuring loyalty. The table also provides the overall mean score and standard deviation for this scale.

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Table 6.6: Loyalty of respondents to their banks Not likely at all 2 3 4 5 6 Very likely Std.

Loyalty items F % F % F % F % F % F % F % Mean Dev

I say positive things 23 4.0 26 4.5 45 7.7 97 16.7 112 19.3 118 20.3 160 27.5 5.14 1.674 about my bank to other people I consider my bank to 31 5.4 30 5.2 38 6.6 90 15.6 96 16.6 122 21.1 171 29.6 5.15 1.767 be the first choice of bank I will remain loyal to 28 4.8 25 4.3 48 8.3 87 15.0 120 20.7 113 19.5 159 27.4 5.11 1.711 my bank Overall loyalty 5.13 1.597

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Table 6.6 indicates that respondents had the highest mean score for “I consider my bank to be the first choice of bank” (29.6% of respondents indicated very likely, mean = 5.15, standard deviation = 1.767). The table also indicates that respondents had the lowest mean score for the statement “I will remain loyal to my bank”, with a mean score of 5.11 (only 27.4% of respondents indicated very likely, standard deviation = 1.711). Overall, respondents indicated that they would be likely to remain loyal to their particular banks with an overall mean score of 5.13 (standard deviation = 1.597).

 Main Finding 11: Respondents indicated their highest level of likelihood for the following statement in the loyalty scale: “I consider my bank to be the first choice of bank” (mean = 5.15)  Main Finding 12: Respondents indicated their highest level of likelihood for the following statement in the loyalty scale: “I will remain loyal to my bank” (mean = 5.11).  Main Finding 13: Overall respondents indicated that they are likely to remain loyal to their respective banks (mean = 5.13).

6.5 FACTOR ANALYSIS

In obtaining items for the CRM dimensions the researcher made use of dimensions found in previous studies. The items in each CRM dimension (service quality, customisation, two- way communication, technology, commitment and convenience) were adopted from previous studies (Zeithaml et al., 2009:152-153; Wong et al., 2008:143; Hashem, 2012:132; Sangle & Awasthi, 2011:907; Dagger et al., 2011:280; Foscht et al., 2009:230) as described in Section 5.2.8.4 of Chapter 5.

As these scale items were adopted from previous studies, the researcher aimed to confirm whether the items in each dimension were applicable to the current study. For this reason a confirmatory factor analysis was conducted (Pallant, 2007:179). Before the data was subjected to factor analysis, it was assessed for suitability. Pallant (2007:181) states that to assess whether data is suitable for factor analysis, Bartlett’s test of sphericity and the KMO measure of sampling adequacy should be used. Bartlett’s test of sphericity should be p < 0.05 and the KMO should be greater than 0.6. From Table 6.7 it can be observed that the data conforms to these requirements and, since a large sample size was obtained (n = 581), the data was suitable for factor analysis. As suggested by Pallant (2007:186), the maximum likelihood method with an orthogonal rotation was used for the confirmatory factor analysis. The following table includes results from the KMO and Barlett’s test of sphericity for the CRM

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dimensions as well as the KMO and Barlett’s test of sphericity results for satisfaction, relationship intention and loyalty.

Table 6.7: KMO and Barlett’s test of sphericity results Dimension KMO Test of sphericity Cumulative % sig. Service Quality (9 items) 0.902 .000 45.67 Customisation (4 items) 0.761 .000 59.75 Two-way communication (4 items) 0.755 .000 58.45 Technology (3 items) 0.700 .000 72.99 Commitment (5 items) 0.777 .000 54.84 Convenience (4 items) 0.757 .000 63.42 Satisfaction (4 items) 0.825 .000 83.84 Relationship intention (3 items) 0.639 .000 73.60 Loyalty (3 items) 0.755 .000 86.33

When conducting the confirmatory factor analysis for each dimension, only the dimension of service quality had to be adjusted due to low factor loadings. Items 1, 2, 3, 7, 14 and 15 needed to be removed indicating that the dimension of service quality had nine remaining items. From Table 6.7 it can observed that these nine items explain 45.67% of the variance for service quality. No other dimensions had to be adjusted and no further items were removed. Items 16-19 were grouped into one factor to form customisation. These four items explained 59.75% of the variance. Items 20-23 were grouped into one factor to form two-way communication. These four items explained 58.45% of the variance. Items 24-26 were grouped into one factor to form the use of technology. These three items explained 72.99% of the variance. Items 27-31 were grouped into one factor to form commitment. These five items explained 54.84% of the variance. Items 32-35 were grouped into one factor and formed convenience. These four items explained 63.42% of the variance. Table 6.7 also indicates that items 36-39 were grouped into one factor to form satisfaction. These four items explained 83.84% of the variance. Items 40-42 were grouped into one factor to form relationship intention. These three items explained 73.60% of the variance. Items 43- 45 were grouped into one factor and formed loyalty. These three items explained 86.33% of the variance.

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6.5.1 RELIABILITY

Although all the constructs were adopted from previous literature, it was still important to determine the reliability of the measuring scales for this study after the confirmatory factor analysis was conducted. In testing reliability, the researcher used the Cronbach alpha value, as suggested by Malhotra (2007:285), which should fall within the parameters of reliability (higher than 0.7). Table 6.8 indicates the results pertaining to each individual construct measured in the measuring instrument.

Table 6.8: Cronbach alpha of each individual dimension/construct Dimension/Construct Cronbach alpha Service quality 0.860 Customisation 0.771 Two-way communication 0.751 Technology 0.815 Commitment 0.778 Convenience 0.801 Satisfaction 0.936 Relationship intention 0.794 Loyalty 0.921

From Table 6.8 it is evident that all the constructs tested fall within the parameters of reliability (higher than 0.7) and can thus be considered reliable (Malhotra, 2007:285).

 Main Finding 14: All constructs used in the measuring instrument were found to be reliable.

6.6 HYPOTHESIS TESTING

This section provides the results pertaining to each hypothesis set for the study as discussed in Section 1.6 in Chapter 1 and Section 5.2.2.3 in Chapter 5. These hypotheses aim to provide the results for Secondary Objectives 6-12 as set out in Section 1.5 of Chapter 1 and Section 5.2.2.2 of Chapter 5. In this section, it should be noted that various statistical analyses were used, including: independent sample t-tests, paired sample t-tests, ANOVAs, and regression analysis as discussed in Section 5.2.8.4 of Chapter 5.

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For the t-tests and ANOVAs, the statistical significance (p-value) and practical significance (d-value) were obtained. Statistical significance can be defined as a state that demonstrates whether a result obtained is significant and indicates whether the result occurred by chance (Hardy & Bryman, 2004:180). A significance p-value of ≤ 0.05 is deemed to be statistically significant with a 95% confidence level (Pallant, 2007). The second component that the researcher had to consider was practical significance. Practical significance (d-value) is defined as the strength of the significance of values and allows the researcher to judge the practical importance of an effect (Bagozzi, 1994:248). For the purposes of this study only results that are statistically and practically significant will be discussed (All other statistics can be found on the CD provided).

 Effect sizes for difference between means: Cohen (1988:20-27) presents the following formula in determining the effect size for difference between means: ̅ ̅

where:  d = effect size;

 ̅ ̅ is the difference between means of the two compared groups;

 is the maximum standard deviation of the two groups.

In interpreting the effect sizes Cohen (1988:20-27) suggests the following:  d = 0.2 small effect with no significance;  d = 0.5 medium effect;  d = 0.8 large effect indicating practical significance.

The following section describes the statistical results obtained for each hypothesis set including whether the results are statistically and practically significant.

6.6.1 HYPOTHESIS 1: THERE IS A SIGNIFICANT DIFFERENCE BETWEEN THE MEANS OF EACH CRM DIMENSION AND THE EXPECTATIONS THAT BLACK GENERATION Y ADULTS HAVE OF THEIR BANKS.

Prior to conducting a paired sample t-test to measure Hypothesis 1, the researcher conducted a paired sample t-test for each individual item of each CRM dimension. The following statistically and practically significant results were obtained in measuring service

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quality (see Annexure 3 for statistical tables). Respondents indicated a higher level of agreement with the statement “When my bank promises to do something by a certain time, they should do it” (mean = 6.55) than with the statement “I expect of my bank to give me individual attention” (mean = 5.92, with a p-value of 0.000). Additionally, a practical significant result of 0.51 (which indicates a medium effect) was obtained. Respondents also indicated a higher level of agreement with the statement “The bank’s employees must always be willing to help me” than with the statement “I expect of my bank to give me individual attention” (mean = 5.92, with a p-value of 0.000). No other statistical and practical significance was found in testing individual items for the CRM dimensions (see Annexure 3). In testing H1 (whether a significant difference exists between the means of each CRM dimension and the expectations that black Generation Y adults have of their banks) the researcher made use of a paired sample t-test. Table 6.9 presents the results of the paired sample t-test for each CRM dimension followed by a discussion.

Table 6.9: CRM dimensions paired samples t-test Paired differences Pairs Mean Std. Dev. Mean Std. Dev. p-value d-value Service quality 6.36 0.633 0.475 0.784 0.000 0.50 Customisation 5.88 0.945 Service quality 6.36 0.643 0.094 0.643 0.001 0.12 Two-way communication 6.26 0.778 Service quality 6.36 0.638 0.070 0.613 0.007 0.07 Technology 6.42 0.771 Service quality 6.36 0.644 0.339 0.760 0.000 0.41 Commitment 6.00 0.864 Service quality 6.36 0.637 0.101 0.592 0.000 0.14 Convenience 6.46 0.709 Customisation 5.88 0.923 0.374 0.785 0.000 0.41 Two-way communication 6.26 0.763 Customisation 5.88 0.940 0.540 0.886 0.000 0.57 Technology 6.42 0.773 Customisation 5.88 0.942 0.129 0.823 0.000 0.12 Commitment 6.00 0.861 Customisation 5.88 0.935 0.571 0.885 0.000 0.62 Convenience 6.46 0.714 Two-way communication 6.26 0.771 0.159 0.715 0.000 0.20

Technology 6.42 0.779

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Table 6.9: Continued

Paired differences Pairs Mean Std. Dev. Mean Std. Dev. p-value d-value Two-way communication 6.26 0.772 0.237 0.711 0.000 0.30 Commitment 6.00 0.859 Two-way communication 6.26 0.772 0.202 0.696 0.000 0.25 Convenience 6.46 0.708 Technology 6.42 0.781 0.402 0.802 0.000 0.49 Commitment 6.00 0.854 Technology 6.42 0.772 0.037 0.634 0.160 0.05

Convenience 6.46 0.710 Commitment 6.00 0.856 0.439 0.781 0.000 0.53 Convenience 6.46 0.715

Table 6.9 indicates that: o Statistically significant results between the overall dimensions of convenience and all other CRM dimensions, except for technology, could be observed. Respondents indicated a higher level of agreement with their expectations of the dimension of convenience (mean = 6.46) than with all the other dimensions (mean = 6.42). o Statistically significant results between the overall dimensions of service quality (mean = 6.36), customisation (mean = 5.88), two-way communication (6.26), and commitment (mean = 6.00) were obtained. o Statistically significant results between the overall dimensions of two-way communication (mean = 6.26), commitment (mean = 6.00), and customisation (mean = 5.88) were observed. o Statistical significant results between the overall dimensions of commitment (mean = 6.00) and customisation (mean = 5.88) were noted. o A medium practical significance (d = 0.50) exists between service quality (mean = 6.36) and customisation (mean = 5.88). o A medium practical significance (d = 0.57) exists between customisation (mean = 5.88) and technology (mean = 6.42). o A medium practical significance (d = 0.62) exists between customisation (mean = 5.88) and convenience (mean = 6.46). o A medium practical significance (d = 0.53) exists between commitment (mean = 6.00) and convenience (mean = 6.46).

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 Main Finding 15: Statistically significant differences were observed between all CRM dimensions except for convenience (mean = 6.46) and technology (mean = 6.42).  Main Finding 16: A statistically and medium practically significant result (p = 0.000, d = 0.50) was observed between the CRM dimensions of service quality and customisation, where respondents indicated higher levels of agreement pertaining to their expectations of service quality than of customisation.  Main Finding 17: A statistically and medium practically significant result (p = 0.000, d = 0.57) was observed between the CRM dimensions of customisation and technology, where respondents indicated higher levels of agreement pertaining to their expectations of technology than of customisation.  Main Finding 18: A statistically and medium practically significant result (p = 0.000, d = 0.62) was observed between the CRM dimensions of customisation and convenience, where respondents indicated higher levels of agreement pertaining to their expectations of convenience than of customisation.  Main Finding 19: A statistically and medium practically significant result (p = 0.000, d = 0.53) was observed between the CRM dimensions of commitment and convenience, where respondents indicated higher levels of agreement pertaining to their expectations of convenience than commitment.

Table 6.9 indicates that significant differences exist between the majority of the CRM dimensions with the exception of technology and convenience. Hypothesis 1 can thus be accepted except for the difference between the means of convenience and technology.

6.6.2 HYPOTHESIS 2: BLACK GENERATION Y ADULTS’ SATISFACTION LEVELS SIGNIFICANTLY AND POSITIVELY INFLUENCE RELATIONSHIP INTENTION AND LOYALTY TO THEIR BANKS.

This hypothesis is further refined as:

H2a: Black Generation Y adults’ satisfaction levels significantly and positively influence relationship intention with their banks.

H2b: Black Generation Y adults’ relationship intention levels significantly and positively influence loyalty to their banks.

H2c: Black Generation Y adults’ satisfaction levels significantly and positively influence loyalty to their banks.

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In determining whether black Generation Y adults’ satisfaction levels significantly and positively influence relationship intention and loyalty to their banks the researcher made use of a linear regression analysis. In testing linear regression the researcher had to adhere to three assumptions, namely those of normality, linearity, and homoscedasticity (Eiselen et al., 2005:156-159).

In terms of the assumption of normality, the data should be distributed by a normal bell- shaped curved. As discussed in Section 6.2, skewness and kurtosis were used to determine the normality of distribution. All items fell within the parameters of skewness (absolute value less than 2.00) and kurtosis (absolute value less than 7.00) and thus the data was considered to be normally distributed (Pallant, 2007:56). The results also show that a straight-line relationship exists between the independent and dependent variables, indicating that the assumption of linearity was confirmed. Additionally, no residual value was smaller than -3 or larger than +3, indicating that homoscedasticity was assumed. The results therefore indicate that linear regression could be performed on the constructs of satisfaction, relationship intention, and loyalty (Eiselen et al., 2005:156-159).

In this section, it was tested whether a positive influence exists between satisfaction, relationship intention, and loyalty, as well as the strength of that influence. Figure 6.1 indicates the influence between the three constructs.

Figure 6.1: Correlation testing for satisfaction, relationship intention and loyalty

Sig. = 0.000 Sig. = 0.000

Satisfaction Relationship Loyalty Intention B = 0.785 B = 0.838

Sig. = 0.000

B = 0.795

In conducting linear regression to test whether a positive influence exists between satisfaction, relationship intention, and loyalty, the Pearson product moment correlations indicated significant linear relationships between satisfaction and relationship intention, relationship intention and loyalty, and satisfaction and loyalty, with the p value smaller than 0.05 for all three combinations of variables. In looking at the beta values for the

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combinations of variables the following results were obtained: satisfaction and relationship intention had a beta value of 0.785, relationship intention and loyalty had a beta value of 0.838, and satisfaction and loyalty had a beta value of 0.795. All three beta values (0.785, 0.838 and 0.795) are high and closer to one which indicates a large positive influence.

 Main Finding 20: A positive influence exists between satisfaction, relationship intention, and loyalty, with the strongest influence being between relationship intention and loyalty (beta value = 0.838).

Based on the results indicated in Figure 6.1, Hypothesis 2 (including H2a, H2b and H2c) can be accepted.

6.6.3 HYPOTHESIS 3: THERE IS A SIGNIFICANT DIFFERENCE BETWEEN THE MEANS OF BLACK GENERATION Y ADULTS’ EXPECTATIONS OF THE SERVICE QUALITY OFFERED BY THEIR BANKS AND DEMOGRAPHIC VARIABLES.

This hypothesis is further refined as:

H3a: There is a significant difference between the means of black Generation Y adults’ expectations of the service quality offered by their banks and gender.

H3b: There is a significant difference between the means of black Generation Y adults’ expectations of the service quality offered by their banks and education.

H3c: There is a significant difference between the means of black Generation Y adults’ expectations of the service quality offered by their banks and income.

H3d: There is a significant difference between the means of black Generation Y adults’ expectations of the service quality offered by their chosen bank.

H3e: There is a significant difference between the means of black Generation Y adults’ expectations of the service quality offered by their banks and length of time with the bank.

When testing whether any significant differences exist between the means of black Generation Y adults’ expectations of the service quality offered by their banks and demographic variables, independent sample t-tests (for the difference between the means of two groups) and ANOVAs (for the difference between the means of more than two groups) were conducted. From all the tests, only a statistically and practically significant result was obtained between service quality and gender, as can be seen in Table 6.10.

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Table 6.10: Service quality and gender CRM dimension Demographic Variable N Mean Std. Dev. p-value d-value Service quality Gender Male 272 6.25 0.677 0.000 0.29 Female 287 6.45 0.592

Table 6.10 indicates a statistically significant difference between male and female respondents in relation to service quality (p-value = 0.000). Female respondents (mean = 6.45) have a higher level of agreement with the dimension measuring the expectation of the service quality offered by their banks than male respondents (mean = 6.25). Only a small practically significant result (d = 0.29) was noted. As there is a significant difference between the means, only H3a can thus be accepted.

 Main Finding 21: A statistically significant difference with a small practically significant effect could be noted between gender and service quality, where female respondents (mean = 6.45) showed a higher level of agreement with the dimension service quality offered by their banks than male respondents (mean = 6.25).

Since no other significant differences were observed, H3b, H3c, H3d and H3e can be rejected.

6.6.4 HYPOTHESIS 4: THERE IS A SIGNIFICANT DIFFERENCE BETWEEN THE MEANS OF BLACK GENERATION Y ADULTS’ EXPECTATIONS OF THE CUSTOMISATION OFFERED BY THEIR BANKS AND DEMOGRAPHIC VARIABLES.

This hypothesis is further refined as:

H4a: There is a significant difference between the means of black Generation Y adults’ expectations of the customisation offered by their banks and gender.

H4b: There is a significant difference between the means of black Generation Y adults’ expectations of the customisation offered by their banks and education.

H4c: There is a significant difference between the means of black Generation Y adults’ expectations of the customisation offered by their banks and income.

H4d: There is a significant difference between the means of black Generation Y adults’ expectations of the customisation offered by their chosen bank.

H4e: There is a significant difference between the means of black Generation Y adults’ expectations of the customisation offered by their banks and length of time with the bank.

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In testing whether any significant differences exist between the means of black Generation Y adults’ expectations of the customisation offered by their banks and demographic variables, the researcher made use of independent sample t-tests and ANOVAs. No significant differences were found, indicating that Hypothesis 4 (H4a – H4e) can be rejected.

6.6.5 HYPOTHESIS 5: THERE IS A SIGNIFICANT DIFFERENCE BETWEEN THE MEANS OF BLACK GENERATION Y ADULTS’ EXPECTATIONS OF THE TWO-WAY COMMUNICATION OFFERED BY THEIR BANKS AND DEMOGRAPHIC VARIABLES.

This hypothesis is further refined as:

H5a: There is a significant difference between the means of black Generation Y adults’ expectations of the two-way communication offered by their banks and gender.

H5b: There is a significant difference between the means of black Generation Y adults’ expectations of the two-way communication offered by their banks and education.

H5c: There is a significant difference between the means of black Generation Y adults’ expectations of the two-way communication offered by their banks and income.

H5d: There is a significant difference between the means of black Generation Y adults’ expectations of the two-way communication offered by their chosen bank.

H5e: There is a significant difference between the means of black Generation Y adults’ expectations of the two-way communication offered by their banks and length of time with the bank.

In testing whether any significant differences exist between the means of black Generation Y adults’ expectations of the two-way communication offered by their banks and demographic variables, the researcher made use of independent sample t-tests and ANOVAs. Since no significant differences were obtained, Hypothesis 5 (H5a – H5e) can be rejected.

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6.6.6 HYPOTHESIS 6: THERE IS A SIGNIFICANT DIFFERENCE BETWEEN THE MEANS OF BLACK GENERATION Y ADULTS’ EXPECTATIONS OF THE TECHNOLOGY OFFERED BY THEIR BANKS AND DEMOGRAPHIC VARIABLES.

This hypothesis is further refined as:

H6a: There is a significant difference between the means of black Generation Y adults’ expectations of the technology offered by their banks and gender.

H6b: There is a significant difference between the means of black Generation Y adults’ expectations of the technology offered by their banks and education.

H6c: There is a significant difference between the means of black Generation Y adults’ expectations of the technology offered by their banks and income.

H6d: There is a significant difference between the means of black Generation Y adults’ expectations of the technology offered by their chosen bank.

H6e: There is a significant difference between the means of black Generation Y adults’ expectations of the technology offered by their banks and length of time with the bank.

When testing whether any significant differences exist between the means of black Generation Y adults’ expectations of the technology offered by their banks and demographic variables, independent sample t-tests (for the difference between the means of two groups) and ANOVAs (for the difference between the means of more than two groups) were conducted. From all the tests, only a statistically and practically significant result was obtained between the CRM dimension of technology and gender, as can be seen in Table 6.11.

Table 6.11: Technology and gender CRM dimension Demographic Variable N Mean Std. Dev. p-value d-value Technology Gender Male 278 6.31 0.842 0.019 0.23 Female 292 6.51 0.701

Table 6.11 indicates a statistically significant difference between the means of male and female respondents pertaining to technology (p-value = 0.019). Female respondents (mean = 6.51) have a higher level of agreement with the dimension measuring the expectation of the technology offered by their banks than male respondents (mean = 6.31). Only a small practically significant result (d = 0.23) was noted. As there is a significant difference between the means, only H6a can thus be accepted.

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 Main Finding 22: A statistically significant difference with a small practically significant effect was noted between gender and technology, where female respondents (mean = 6.51) showed a higher level of agreement with the dimension technology offered by their banks than male respondents (mean = 6.31).

The results also indicate a statistically significant difference between the level of education and technology offered by the respective banks. Due to the low frequencies in each category, the variable of “education” was grouped into three groups, namely “completed school”, “diploma” and “degree”. The following Table 6.12 indicates the results of the ANOVA.

Table 6.12: Analysis of variance: Technology Comparisons d-value CRM Mean Std. N Level of significant at School Diploma Degree dimension Dev. education the 0.05 level Overall 6.50 0.974 231 (1) - 0.26 0.09 technology School 2-1 6.23 1.006 124 (2) 0.26 - 0.17 Diploma 6.41 0.784 226 (3) 0.09 0.17 - Degree

From Table 6.12 it is evident that statistically significant differences between the means of diploma and school respondents in measuring the overall technology offered by their banks (p > 0.05). Respondents who have completed school (mean = 6.50) have a higher level of agreement with the expectation of the overall technology offered by their banks than respondents with a diploma (mean = 6.23). A practical significant effect of 0.26 was also recorded, suggesting a small practical significance.

 Main Finding 23: Respondents whose highest level of education is school (mean = 6.50) demonstrated higher expectations of technology as a CRM dimension than respondents whose highest level of education is a diploma (mean = 6.23). There was a statistical and small practical significance between means (d = 0.26).

The results above indicate that H6b, can only be partially accepted since a significant difference could only be observed between technology and the variables of “school” and “diploma” and not with other variables measuring the level of education.

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Since no other significant differences were observed, except for those discussed above, H6c,

H6d and H6e can be rejected.

6.6.7 HYPOTHESIS 7: THERE IS A SIGNIFICANT DIFFERENCE BETWEEN THE MEANS OF BLACK GENERATION Y ADULTS’ EXPECTATIONS OF THE COMMITMENT OFFERED BY THEIR BANKS AND DEMOGRAPHIC VARIABLES.

This hypothesis is further refined as:

H7a: There is a significant difference between the means of black Generation Y adults’ expectations of the commitment offered by their banks and gender.

H7b: There is a significant difference between the means of black Generation Y adults’ expectations of the commitment offered by their banks and education.

H7c: There is a significant difference between the means of black Generation Y adults’ expectations of the commitment offered by their banks and income.

H7d: There is a significant difference between the means of black Generation Y adults’ expectations of the commitment offered by their chosen bank.

H7e: There is a significant difference between the means of black Generation Y adults’ expectations of the commitment offered by their banks and length of time with the bank.

In testing whether any statistically and practically significant differences exist between the means of black Generation Y adults’ expectations of the CRM dimension of commitment offered by their banks and demographic variables, the researcher made use of independent sample t-tests and ANOVAs. However, no significant results were obtained. Thus H7a, H7b,

H7c, H7d and H7e can be rejected.

6.6.8 HYPOTHESIS 8: THERE IS A SIGNIFICANT DIFFERENCE BETWEEN THE MEANS OF BLACK GENERATION Y ADULTS’ EXPECTATIONS OF THE CONVENIENCE OFFERED BY THEIR BANKS AND DEMOGRAPHIC VARIABLES.

This hypothesis is further refined as:

H8a: There is a significant difference between the means of black Generation Y adults’ expectations of the convenience offered by their banks and gender.

H8b: There is a significant difference between the means of black Generation Y adults’ expectations of the convenience offered by their banks and education.

H8c: There is a significant difference between the means of black Generation Y adults’ expectations of the convenience offered by their banks and income.

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H8d: There is a significant difference between the means of black Generation Y adults’ expectations of the convenience offered by their chosen bank.

H8e: There is a significant difference between the means of black Generation Y adults’ expectations of the convenience offered by their banks and length of time with the bank.

When testing whether any significant differences exist between the means of black Generation Y adults’ expectations of the convenience offered by their banks and demographic variables, independent sample t-tests (for the difference between the means of two groups) and ANOVAs (for the difference between the means of more than two groups) were conducted. From all the tests, only a statistically and practically significant result was obtained between convenience and gender, as can be seen in Table 6.13.

Table 6.13: Convenience and gender CRM dimension Demographic Variable N Mean Std. Dev. p-value d-value Convenience Gender Male 278 6.39 0.774 0.027 0.16 Female 297 6.52 0.646

Table 6.13 indicates a statistically significant difference between the means of male and female respondents pertaining to convenience (p-value = 0.027). Female (mean = 6.52) respondents showed a higher level of agreement with the dimension measuring the expectation of convenience offered by their banks than male respondents (mean = 6.39). Only a small practically significant result (d = 0.16) was noted. As there is a significant difference between the means, only H8a can thus be accepted.

 Main Finding 24: A statistically significant difference between means with a small practically significant effect could be noted between gender and convenience, where female respondents (mean = 6.52) demonstrated a higher level of agreement with service quality offered by their banks than male respondents (mean = 6.39).

Since no other statistically or practically significant differences between means were obtained hypotheses, H8b, H8c, H8d and H8e can be rejected.

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6.6.9 HYPOTHESIS 9: THERE IS A SIGNIFICANT DIFFERENCE BETWEEN THE MEANS OF BLACK GENERATION Y ADULTS’ OVERALL SATISFACTION WITH THEIR BANKS AND DEMOGRAPHIC VARIABLES.

This hypothesis is further refined as:

H9a: There is a significant difference between the means of black Generation Y adults’ overall satisfaction with their banks and gender.

H9b: There is a significant difference between the means of black Generation Y adults’ overall satisfaction with their banks and education.

H9c: There is a significant difference between the means of black Generation Y adults’ overall satisfaction with their banks and income.

H9d: There is a significant difference between the means of black Generation Y adults’ overall satisfaction with their chosen bank.

H9e: There is a significant difference between the means of black Generation Y adults’ overall satisfaction with their banks and length of time with the bank.

When testing whether any significant differences exist between the means of black Generation Y adults’ overall satisfaction and the chosen bank, independent sample t-tests (for the difference between the means of two groups) and ANOVAs (for the difference between the means of more than two groups) were conducted. From all the tests, only a statistically and practically significant result was obtained between overall satisfaction and the chosen bank, as can be seen in Table 6.14.

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Table 6.14: Analysis of variance: Satisfaction and chosen bank Comparisons d-value Dimension Mean Std. N Level of significant at ABSA FNB Standard Nedbank Dev. education the 0.05 level Bank Overall 5.11 1.350 149 ABSA 1 – 2 - 0.48 0.19 0.21 satisfaction (1) 5.71 1.119 131 FNB 0.48 - 0.25 0.21 (2) 5.37 1.344 176 Standard 0.19 0.25 - 0.02 Bank (3) 5.41 1.388 122 Nedbank 0.21 0.21 0.02 - (4)

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Table 6.14 indicates a significant difference between means in the overall satisfaction respondents have with their banks. Dunnett’s T3 indicated that a significant difference between means exists between FNB respondents (mean = 5.71) and ABSA respondents (mean = 5.11), where FNB respondents have higher levels of overall satisfaction than ABSA respondents. In testing the practical significance between the means, a d-value of 0.48 was obtained which resulted in a medium practical significant effect. H9d can therefore be accepted.

 Main Finding 25: A statistically significant difference with a medium practically significant effect between means could be noted between FNB and ABSA respondents and overall satisfaction, where FNB respondents (mean = 5.71) have a higher level of agreement of the overall satisfaction offered by their bank than ABSA respondents (mean = 5.11).

Since no other significant differences were obtained, H9a, H9b, H9c and H9e can be rejected.

6.6.10 HYPOTHESIS 10: THERE IS A SIGNIFICANT DIFFERENCE BETWEEN THE MEANS OF BLACK GENERATION Y ADULTS’ OVERALL RELATIONSHIP INTENTION WITH THEIR BANKS AND DEMOGRAPHIC VARIABLES.

This hypothesis is further refined as:

H10a: There is a significant difference between the means of black Generation Y adults’ overall relationship intention with their banks and gender.

H10b: There is a significant difference between the means of black Generation Y adults’ overall relationship intention with their banks and education.

H10c: There is a significant difference between the means of black Generation Y adults’ overall relationship intention with their banks and income.

H10d: There is a significant difference between the means of black Generation Y adults’ overall relationship intention with their chosen bank.

H10e: There is a significant difference between the means of black Generation Y adults’ overall relationship intention with their banks and length of time with the bank.

When testing whether any significant differences exist between the means of black Generation Y adults’ overall relationship intention and the chosen bank, independent sample t-tests (for the difference between the means of two groups) and ANOVAs (for the difference between the means of more than two groups) were conducted. From all the tests, only a

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statistically and practically significant result was obtained between overall relationship intention and the chosen bank, as can be seen in Table 6.15.

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Table 6.15: Analysis of variance: Relationship intention and chosen bank Comparisons d-value Dimension Mean Std. N Level of significant at ABSA FNB Standard Nedbank Dev. education the 0.05 level Bank Overall 4.78 1.491 147 ABSA 1 - 2 - 0.42 0.20 0.22 relationship (1) intention 5.41 1.211 133 FNB 0.42 - 0.22 0.19 (2) 5.08 1.494 176 Standard 0.20 0.22 - 0.02 Bank (3) 5.12 1.492 122 Nedbank 0.22 0.19 0.02 - (4)

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Table 6.15 indicates a significant difference between the means in the overall relationship intention respondents have with their banks. Dunnett’s T3 indicated that a significant difference exists between the means of FNB respondents (mean = 5.41) and ABSA respondents (mean = 4.78), where FNB respondents have higher levels of overall relationship intention than ABSA respondents. In testing the practical significance between the means, a d-value of 0.42 was obtained which resulted in a medium practically significant effect. H10d can therefore be accepted.

 Main Finding 26: A statistically significant difference with a small practically significant effect could be noted between the means of FNB and ABSA respondents and overall relationship intention, where FNB respondents (mean = 5.41) showed a higher level of likeliness regarding overall relationship intention than ABSA respondents (mean = 4.78).

Since no other significant differences were obtained, H10a, H10b, H10c and H10e can be rejected.

6.6.11 HYPOTHESIS 11: THERE IS A SIGNIFICANT DIFFERENCE BETWEEN THE MEANS OF BLACK GENERATION Y ADULTS’ OVERALL LOYALTY TO THEIR BANKS AND DEMOGRAPHIC VARIABLES.

This hypothesis is further refined as:

H11a: There is a significant difference between the means of black Generation Y adults’ overall loyalty to their banks and gender.

H11b: There is a significant difference between the means of black Generation Y adults’ overall loyalty to their banks and education.

H11c: There is a significant difference between the means of black Generation Y adults’ overall loyalty to their banks and income.

H11d: There is a significant difference between the means of black Generation Y adults’ overall loyalty to their chosen bank.

H11e: There is a significant difference between the means of black Generation Y adults’ overall loyalty to their banks and length of time with the bank.

When testing whether any significant differences exist between the means of black Generation Y adults’ overall loyalty and the chosen bank, independent sample t-tests (for the difference between the means of two groups) and ANOVAs (for the difference between the means of more than two groups) were conducted. From all the tests, only a statistically and

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practically significant result was obtained between overall loyalty and the chosen bank as can be seen in Table 6.16.

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Table 6.16: Analysis of variance: Loyalty and chosen bank Comparisons d-value Dimension Mean Std. N Level of significant at ABSA FNB Standard Nedbank Dev. education the 0.05 level Bank Overall 4.70 1.693 149 ABSA 1 - 2 - 0.48 0.25 0.30 loyalty (1) 5.52 1.357 132 FNB 0.48 - 0.24 0.18 (2) 5.13 1.576 176 Standard 0.25 0.24 - 0.04 Bank (3) 5.21 1.640 121 Nedbank 0.30 0.18 0.04 - (4)

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Table 6.16 indicates a significant difference between the means in the overall loyalty respondents have to their banks. Dunnett’s T3 indicated that a significant difference exists between the means of FNB respondents (mean = 5.52) and ABSA respondents (mean = 4.70), where FNB respondents have a higher likeliness of loyalty than ABSA respondents. In testing the practical significance between the means, a d-value of 0.42 was obtained and thus resulted in a medium practical significant effect. H11d can therefore be accepted.

 Main Finding 27: A statistically significant difference with a medium practically significant effect could be noted between the means of FNB and ABSA respondents and overall loyalty, where FNB respondents (mean = 5.52) have a higher level of likeliness of overall loyalty than ABSA respondents (mean = 4.70).

Since no other significant differences were obtained, H11a, H11b, H11c and H11e can therefore be rejected.

6.7 CONCLUSION

The chapter provided the main research findings pertaining to the study. The chapter began by presenting the realisation rate of the study, followed by the demographic profile of respondents. Confirmatory factor analyses were conducted and the measuring instrument proved reliable. All the data in the questionnaire was analysed using frequency analysis, paired samples t-test, independent sample t-tests, ANOVAs, and regression analysis. These tests were conducted to determine whether hypotheses should be accepted or rejected. The next chapter focuses on the recommendations of the main findings and also provides the conclusion to the study.

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CHAPTER 7 RESEARCH CONCLUSIONS AND RECOMMENDATIONS

7.1 INTRODUCTION

This chapter provides an overview of the study and offers recommendations based on the results presented in the previous chapter. The chapter will include a discussion of the main findings based on the secondary objectives and will also provide recommendations on those findings. The aim of this chapter is to supply evidence of having achieved the primary objective which was to determine black Generation Y adults’ expectations of the CRM dimensions offered by their bank, as well as to identify their overall levels of satisfaction, relationship intention, and loyalty to their banks. Furthermore, the limitations of the research will be discussed and recommendations will be made for further research.

7.2 SECONDARY OBJECTIVES

This section will include each secondary objective together with the main findings and applicable hypothesis tested for the individual objective. The implications and recommendations will accompany each section.

7.2.1 SECONDARY OBJECTIVE 1: CONDUCT A LITERATURE REVIEW TO IDENTIFY THE CRM DIMENSIONS THAT CAN BE USED IN THE BANKING INDUSTRY

In order to reach the first secondary objective, a literature review was conducted on previous studies that also focused on the constructs measured in this study. The literature review was discussed in Chapters 3 and 4. Chapter 3 provided insights into customer expectations, satisfaction and loyalty, whereas Chapter 4 discussed CRM and the CRM dimensions. From the literature review conducted, many studies were identified that dealt with CRM dimensions. Table 7.1 indicates the CRM dimensions identified in the literature and the previous studies used to measure particular CRM dimensions (see Section 5.2.5.2 in Chapter 5).

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Table 7.1: Previous literature on CRM dimensions Dimension Literature Service quality Zeithaml et al. (2009:152-153) Customisation Wong et al. (2008:143) Two-way communication Hashem (2012:132) Use of technology Sangle and Awasthi (2011:907) Commitment Dagger et al. (2011:280) Convenience Foscht et al. (2009:230)

As can be seen from Table 7.1, the dimensions identified in the literature and used for the purposes of this study included: service quality, customisation, two-way communication, technology, commitment, and convenience. Further analysis of these dimensions showed them to be reliable in this study (Main Finding 14).

 Recommendation: It is recommended that for further research within the South African banking industry, the CRM dimensions of service quality, customisation, two-way communication, technology, commitment, and convenience be considered in measuring CRM.

7.2.2 SECONDARY OBJECTIVE 2: IDENTIFY THE BLACK GENERATION Y ADULTS’ EXPECTATIONS OF THE CRM DIMENSIONS OFFERED BY THEIR BANKS

In determining black Generation Y adults’ expectations of the CRM dimensions offered by their banks, the mean score for each CRM dimension was determined. Table 7.2 indicates the mean score for each CRM dimension from highest to lowest.

Table 7.2: Overall mean values for each CRM dimension (from highest to lowest) CRM Dimension Mean Overall convenience 6.46 Overall technology 6.42 Overall service quality 6.36 Overall two-way communication 6.26 Overall commitment 6.00 Overall customisation 5.88

Although respondents had high levels of agreement regarding expectations for all the CRM dimensions measured, they indicated the highest level of agreement regarding expectations

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for convenience (mean = 6.46) and the use of technology (mean = 6.42) (Main Finding 3). Respondents indicated that they have the lowest level of agreement regarding expectations for customisation (mean = 5.88) and commitment (mean = 6.00) (Main Finding 4). When looking at individual items, respondents indicated their highest level of agreement regarding the following item: “My bank should keep accurate records of my accounts” (mean = 6.62) (Main Finding 1). Respondents also indicated their lowest level of agreement pertaining to the following item: “My bank should be prepared to make short-term sacrifices to maintain our relationship” (mean = 5.74) (Main Finding 2).

 Recommendation: The four major banks in South Africa (ABSA, FNB, Nedbank and Standard Bank) need to focus on the CRM dimensions of which respondents have high expectations, namely convenience and technology. Although convenience and technology had the highest mean scores, the other CRM dimensions also delivered high levels of agreement, suggesting that banks should not ignore these in their marketing strategy. Banks should specifically focus on introducing new technologies such as more innovative ways of mobile banking and upgrade existing technologies such as their websites in order to facilitate ease of use as well as convenience.  In order to differentiate themselves from other banks, the four major banks in South Africa should also focus on the two least desirable dimensions (customisation and commitment) in order to offer overall better service. This can be done by giving customers options to structure deals such as home loans, credit card facilities, and other facilities that would suit the willingness of the bank to commit to customers and not make them feel like a “number”. This could also be done, for example, by allowing respondents to customise their own online banking site. When looking at individual items the banks should take great care in keeping accurate records of customers’ accounts.

7.2.3 SECONDARY OBJECTIVE 3: DETERMINE THE OVERALL SATISFACTION LEVELS THAT BLACK GENERATION Y ADULTS HAVE WITH THEIR BANKS

Although respondents indicated that they feel satisfied with their banks overall (mean = 5.39, Main Finding 7), they also indicated their highest level of agreement regarding the following statement about satisfaction: “I feel good about using my bank as a service provider” (mean = 5.54, Main Finding 5). Respondents indicated their lowest level of agreement with the following statement about satisfaction: “I feel satisfied that the results from using my bank are the best that I can currently obtain” (mean = 5.25, Main Finding 6).

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 Recommendation: For the four major banks in South Africa to keep on providing high levels of satisfaction, they need to focus on maintaining and improving the overall service provided. This could be done by looking at each individual item for each CRM dimension and improving on it. For example, banks should use more technological platforms and create a more convenient environment in which customers can conduct their banking. Banks should also view competitive offerings since respondents feel that the outcomes achieved in a service interaction is not necessarily the best possible outcome to be achieved. This could be for various reasons, such as: customers perceive other banks to have better service or offerings, or customers feel that the bank acted on behalf of its own interests and did not necessarily take the customers’ needs into consideration. Banks need to take cognisance of this since customers could consider defecting if they are offered better value at other banks.

7.2.4 SECONDARY OBJECTIVE 4: DETERMINE THE OVERALL RELATIONSHIP INTENTION OF BLACK GENERATION Y ADULTS WITH THEIR BANKS

Overall respondents indicated that they are likely to continue the relationship with their current banks (mean = 5.09, Main Finding 10). Respondents indicated their highest level of likelihood for the following statement about relationship intention: “I will continue doing business with my bank” (mean = 5.54, Main Finding 8). Respondents also indicated their lowest level of likelihood for the following statement about to relationship intention: “If a competing bank offers me lower banking fees I will still make use of my current bank” (mean = 4.48, Main Finding 9).

 Recommendation: The fact that respondents indicated that they are likely to remain with their banks should serve as some comfort for banks focusing on retention strategies. However, what should be of concern is that customers would switch to competing banks if prices were lower. Banks can avoid this by lowering their fees to be more competitive or increasing their service offering to justify the higher prices. Banks should thus offer service that creates value for money and market the value customers get by using the banks’ services. The results of the study suggest that respondents only have a latent level of loyalty since they indicated that they would move to a competing bank if other banks offered lower prices. Banks should therefore try to move customers to a level of true loyalty, which could be done by increasing satisfaction levels and offering customers greater value with the CRM dimensions as discussed in Section 7.2.2.

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7.2.5 SECONDARY OBJECTIVE 5: DETERMINE THE OVERALL LOYALTY LEVELS THAT BLACK GENERATION Y ADULTS HAVE TO THEIR BANKS

Overall respondents indicated that they are likely to remain loyal to their respective banks (mean = 5.13, Main Finding 13). Respondents indicated their highest level of likelihood for the following statement pertaining to loyalty: “I consider my bank to be the first choice of bank” (mean = 5.15, Main Finding 11). Respondents also indicated their lowest level of likelihood for the following statement about loyalty: “I will remain loyal to my bank” (mean = 5.11, Main Finding 12).

 Recommendation: Respondents indicated that they consider their respective banks as being their first choice bank. It is recommended to the four major banks in South Africa that they continue to satisfy customers in order to retain them. This could be done by delivering superior service, customising services to customer requirements, communicating more effectively with customers, using and integrating more technological platforms such as banking applications and more innovative mobile banking, and allowing customers to customise their own Internet banking to create a convenient environment in which customers can conduct their banking. For competing banks trying to gain market share it is recommended that they consider lowering introductory fees to attract more customers from other banks. They should also increase their marketing and communication endeavours to communicate these lower fees to potential customers, and also market all other value adding activities.

7.2.6 SECONDARY OBJECTIVE 6: IDENTIFY WHETHER SIGNIFICANT DIFFERENCES CAN BE OBSERVED BETWEEN THE MEANS OF BLACK GENERATION Y ADULTS’ EXPECTATIONS AND THE CRM DIMENSIONS OFFERED BY THEIR BANKS

As previously discussed, the results in Hypothesis 1 (which link to Secondary Objective 6 in measuring whether significant differences existed between the means of the CRM dimensions) show that all the means were statistically significant with the exception of convenience (mean = 6.46) and technology (mean = 6.42). The results indicated that respondents have the highest level of agreement with and the highest expectations for these two dimensions (convenience and technology, Main Finding 15). Respondents indicated higher levels of agreement pertaining to their expectations of service quality than of customisation (Main Finding 16). Respondents indicated higher levels of agreement regarding their expectations of technology than of customisation (Main Finding 17).

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Respondents indicated higher levels of agreement regarding their expectations of convenience than of customisation (Main Finding 18). Lastly, respondents indicated higher levels of agreement regarding their expectations of convenience than of commitment (Main Finding 19). Respondents also indicated having the lowest expectations of customisation (mean = 5.88).

 Recommendation: It is recommended that the four major banks in South Africa focus on those CRM dimensions of which respondents have high expectations. Respondents indicated that they have the highest expectations of convenience and the use of technology, and the four major banks should thus seek to focus on those dimensions by streamlining processes, introducing new technologies (mobile applications, banking applications, and the option for customers to customise Internet banking according to their needs), and upgrading existing technologies (such as mobile and fixed ATM facilities) in order to facilitate ease of use as well as convenience. Banks should look at the six CRM dimensions as different levels and focus on those levels of which customers have the highest expectations and then focus on the other CRM dimensions as to differentiate themselves from competitors, since the means indicated all dimensions had high levels of expectations. This could be done by focussing on service quality. Banks should increase service quality by employing well-trained staff who strive to delight customers and who can attend to customer queries in a timely and efficient manner. Lastly, banks should then focus on the dimensions such as customisation and commitment in order to offer a more comprehensive service. In order to achieve this, banks should give customers options to structure deals such as home loans, credit card facilities, and other facilities that would suit their needs. This will show customers that they are more than a “number”.

7.2.7 SECONDARY OBJECTIVE 7: IDENTIFY WHETHER BLACK GENERATION Y ADULTS’ SATISFACTION LEVELS INFLUENCE THE RELATIONSHIP INTENTION WITH AND LOYALTY LEVELS TO THEIR BANKS

The findings measuring Hypothesis 2, which links to Secondary Objective 7, suggest that a direct positive influence exists between satisfaction and relationship intention of black Generation Y adults with a Beta value of 0.785 (Main Finding 16). This means that satisfied customers are 78.5% inclined to remain with their banks and continue their relationship. The findings also suggest a direct positive influence between satisfaction and loyalty for black Generation Y adults with a B-value of 0.795 (Main Finding 16). This indicates that satisfied customers have a 79.5% inclination of remaining loyal to the organisation.

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 Recommendation: It is therefore recommended that the four major banks in South Africa shift their focus towards satisfying their customers. This could be done by improving on all the CRM dimensions currently offered. The research shows that by keeping the customers satisfied, the customers’ intentions will be to remain with the bank. The literature stated that customers who are not satisfied are not inclined to form relationships with organisations and have no intention of remaining loyal, and vice versa (Yen et al., 2007:1). This was supported in this study. This means that banks should really focus on customer satisfaction to ensure relationship intention and overall customer loyalty. As the literature indicated, the four major banks can increase their satisfaction by employing staff who respond to customer queries in a timely manner, who aim to delight their customers and who respond to service failures in a professional and timely manner (Boshoff & Du Plessis, 2009:210-218).

7.2.8 SECONDARY OBJECTIVE 8: IDENTIFY WHETHER BLACK GENERATION Y ADULTS’ RELATIONSHIP INTENTION INFLUENCES THEIR LOYALTY LEVELS TO THEIR BANKS

The findings for Hypothesis 2, which links to Secondary Objective 8, further show that, apart from the positive influence between satisfaction and relationship intention and satisfaction and loyalty, a direct positive influence also exists between relationship intention and loyalty, with a Beta value of 0.838, which suggests a very strong influence (Main Finding 16). This indicates that individuals with a strong intent of furthering their relationship are also 83.8% inclined to remain loyal to the specific organisation.

 Recommendation: It is recommended that the four major banks in South Africa focus on relationship intention strategies (such as following up with customers on a regular basis, customising services to relationship specific requirements, and maintaining contact with customers) to ensure customer loyalty. To look at these retention strategies the banks should focus on reassuring customers about their intent to maintain and enhance their relationship with customers. Banks should also keep constant communication with their customers and inform them of any new products or changes that could be mutually beneficial to both parties involved.

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7.2.9 SECONDARY OBJECTIVE 9: DETERMINE WHETHER SIGNIFICANT DIFFERENCES BETWEEN MEANS CAN BE OBSERVED IN TERMS OF BLACK GENERATION Y ADULTS’ EXPECTATION LEVELS OF THE CRM DIMENSIONS OFFERED BY THEIR BANKS AND DEMOGRAPHIC VARIABLES (GENDER, EDUCATION, INCOME, CHOSEN BANK AND LENGTH OF TIME WITH THE BANK)

The following section provides the results for each demographic variable (from the hypothesis tested, which links with secondary objective 9) as well as recommendations based on that variable.

7.2.9.1 GENDER

In testing whether any significant differences exist between the means of black Generation Y adults’ expectations of the service quality (H3a) offered by their banks and demographic variables, the only significant difference obtained was between service quality and gender. Female respondents (mean = 6.45) have a higher expectation of the service quality than male respondents (mean = 6.25) (Main Finding 17). In testing whether any significant differences exist between the means of black Generation Y adults’ expectations of the technology offered by their banks and demographic variables (H6a), a significant difference between technology and gender was obtained. Female respondents (mean = 6.51) have a higher expectation of the technology offered by their banks than male respondents (mean = 6.31, Main Finding 18). In testing whether any significant differences exist between the means of black Generation Y adults’ expectations of the convenience offered by their banks and demographic variables, the only significant difference obtained was between convenience and gender (H8a). Female respondents (mean = 6.52) have a higher expectation of the service quality offered by their banks than male respondents (mean = 6.39, Main Finding 20).

 Recommendations: Firstly, it is recommended that the four major banks in South Africa focus on the reason for differences in the expectations of service quality, technology and convenience between males and females. Secondly, the banks should address the issue. Banks therefore need to realise that females have higher levels of expectations than males, which should be recognised in the marketing strategy.  To manage the service quality aspect, banks could for instance have employees that are well-dressed and willing to help customers. The banks should have neat and clean facilities, and have employees who can respond to customer requests in a timely manner.

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 To manage the technology aspect banks could, for instance, penetrate untapped locations by using mobile ATMs, increasing the amount of self-service kiosks, increasing branches especially in untapped geographical areas, and including stores in geographical areas which focus on educating customers on mobile banking, applications and Internet banking.  To manage the convenience aspect, banks could for instance introduce more technological platforms (banking applications and Internet banking), provide easy to use technologies for different generations, and streamline technological platforms to make it more convenient for customers to bank.

7.2.9.2 EDUCATION

The results also indicated that, pertaining to the use of technology, a significant difference exists between respondents whose highest level of education is schooling and respondents with a diploma (H6b, Main Finding 19). Respondents with high school as their highest level of education (mean = 6.50) expect more from technology than respondents with a diploma (mean = 6.23).

 Recommendation: It is recommended that the four major banks in South Africa firstly focus on ways in which to meet higher technological expectations of consumers with different levels of education by for instance introducing more technological platforms or redesigning platforms to enhance ease of use. Secondly, banks should educate and train customers about the advantages of using technological platforms to promote convenience and security.

7.2.9.3 INCOME

No significant differences between means was observed in terms of black Generation Y adults’ expectation levels of the CRM dimensions offered by their banks and income.

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7.2.9.4 CHOSEN BANK

No other significant differences between means can be observed in terms of black Generation Y adults’ expectation levels of the CRM dimensions offered by their banks and their chosen banks.

 Recommendation: Since no statistically or practically significant differences could be observed in terms of black Generation Y adults’ expectations levels of the CRM dimensions offered by their banks and the respondents’ respective banks, it is suggested that banks therefore not change their CRM marketing strategies based on chosen bank for the Generation Y demographic. Rather, they should focus on all CRM dimensions to ensure that differences in expectations will not occur in the future.

7.2.9.5 LENGTH OF TIME WITH BANK

No other significant differences between means can be observed in terms of black Generation Y adults’ expectation levels of the CRM dimensions offered by their banks and length of time with the bank.

 Recommendation: Since no statistically or practically significant differences could be observed in terms of black Generation Y adults’ expectations levels of the CRM dimensions offered by their banks and respondents’ length of time with the bank, it is suggested that banks therefore not change their CRM marketing strategies based on the length of time with the bank. Banks should realise that customers who have been dealing with the bank for less than three years have the same level of expectations as those who have been dealing with the bank for more than three years.

7.2.10 SECONDARY OBJECTIVE 10: DETERMINE WHETHER SIGNIFICANT DIFFERENCES BETWEEN MEANS CAN BE OBSERVED IN TERMS OF BLACK GENERATION Y ADULTS’ SATISFACTION LEVELS WITH THE CRM DIMENSIONS OFFERED BY THEIR BANKS AND DEMOGRAPHIC VARIABLES

7.2.10.1 GENDER

No significant differences between means can be observed in terms of black Generation Y adults’ satisfaction levels of the CRM dimensions offered by their banks and gender.

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 Recommendation: Since no statistically or practically significant differences could be observed regarding this objective, it is therefore suggested that banks not change their CRM marketing strategies based on gender but aim to have the same strategies for satisfaction for both males and females.

7.2.10.2 EDUCATION

No significant differences between means can be observed in terms of black Generation Y adults’ satisfaction levels of the CRM dimensions offered by their banks and education.

 Recommendation: Since no statistically or practically significant differences could be observed regarding this aspect, it is suggested that banks therefore not change their CRM marketing strategies based on education, since education levels do not influence the level of satisfaction for Generation Y respondents.

7.2.10.3 INCOME

No significant differences between means can be observed in terms of black Generation Y adults’ satisfaction levels of the CRM dimensions offered by their banks and the respondents’ income.

 Recommendation: Since no statistically or practically significant differences could be observed in relation to this aspect, it is suggested that banks therefore not change their CRM marketing strategies based on income and should realise that all respondents have the same level of satisfaction despite their income levels.

7.2.10.4 CHOSEN BANK

The results indicated that a significant difference exists between FNB respondents (mean = 5.71) and ABSA respondents (mean = 5.11) in terms of satisfaction with their chosen banks

(H9, Main Finding 21). FNB respondents are more satisfied with the CRM dimensions they receive from their banks than ABSA respondents.

 Recommendation: For the other banks to increase their satisfaction it is recommended that they focus on aspects such as improving service quality. This will allow customers to

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customise offerings according to their needs and banks to communicate more effectively with customers and be more committed to customers.

7.2.10.5 LENGTH OF TIME WITH THE BANK

No significant differences between means can be observed in terms of black Generation Y adults’ satisfaction levels of the CRM dimensions offered by their banks and length of time with the bank.

 Recommendation: Since no statistically or practically significant differences could be observed in relation to this aspect, it is therefore suggested that banks not change their CRM marketing strategies based on the respondents’ length of time with the bank. Banks should realise that Generation Y respondents’ satisfaction levels do not change based on the length of time they have been dealing with their bank, and should therefore aim to satisfy all customers – those who are new to the bank as well as those who have been with the bank for longer than three years.

7.2.11 SECONDARY OBJECTIVE 11: DETERMINE WHETHER SIGNIFICANT DIFFERENCES BETWEEN MEANS CAN BE OBSERVED IN TERMS OF BLACK GENERATION Y ADULTS’ RELATIONSHIP INTENTION LEVELS OF THE CRM DIMENSIONS OFFERED BY THEIR BANKS AND DEMOGRAPHIC VARIABLES

7.2.11.1 GENDER

No significant differences between means can be observed in terms of black Generation Y adults’ relationship intention levels of the CRM dimensions offered by their banks and gender.

 Recommendation: Since no statistically or practically significant differences could be observed regarding this aspect, it is therefore suggested that banks not change their CRM marketing strategies based on gender. Banks can thus have a generic strategy to develop relationships with both male and female customers.

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7.2.11.2 EDUCATION

No significant differences between means can be observed in terms of black Generation Y adults’ relationship intention levels of the CRM dimensions offered by their banks and education.

7.2.11.3 INCOME

No significant differences between means can be observed in terms of black Generation Y adults’ relationship intention levels of the CRM dimensions offered by their banks and income.

 Recommendation: Since no statistically or practically significant differences could be observed regarding this aspect, it is therefore recommended that banks not change their CRM marketing strategies based on income.

7.2.11.4 CHOSEN BANK

The results indicated that a significant difference exists between FNB respondents (mean = 5.41) and ABSA respondents (mean = 4.78) in terms of their relationship intention with their respective banks (H10, Main Finding 22). FNB respondents are more inclined to continue their relationship with their bank than ABSA respondents.

 Recommendation: For the other banks to increase their relationship intention it is recommended that they increase their customer satisfaction, since a direct positive influence exists between customer satisfaction and relationship intention. This indicates that satisfied customers are inclined to continue their relationship with their banks. Banks can increase their relationship intention by focusing on aspects such as improving service quality, allowing customers to customise offerings according to their needs, communicating more effectively with customers, being more committed to customers, and enhancing customer convenience through the integration of technology.

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7.2.11.5 LENGTH OF TIME WITH THE BANK

No significant differences between means can be observed in terms of black Generation Y adults’ relationship intention levels of the CRM dimensions offered by their banks and the respondents’ length of time with the bank.

7.2.12 SECONDARY OBJECTIVE 12: DETERMINE WHETHER SIGNIFICANT DIFFERENCES BETWEEN MEANS CAN BE OBSERVED IN TERMS OF BLACK GENERATION Y ADULTS’ LOYALTY LEVELS OF THE CRM DIMENSIONS OFFERED BY THEIR BANKS AND DEMOGRAPHIC VARIABLES

7.2.12.1 GENDER

No significant differences between means can be observed in terms of black Generation Y adults’ loyalty levels of the CRM dimensions offered by their banks and gender.

7.2.12.2 EDUCATION

No significant differences between means can be observed in terms of black Generation Y adults’ loyalty levels of the CRM dimensions offered by their banks and education.

7.2.12.3 INCOME

No significant differences between means can be observed in terms of black Generation Y adults’ loyalty levels of the CRM dimensions offered by their banks and income.

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7.2.12.4 CHOSEN BANK

In testing whether significant differences exist between customers of the four major banks in

South Africa and their loyalty to their respective banks (H11d), it was found that FNB customers (mean = 5.52) are more likely to remain loyal to their bank than ABSA customers (mean = 4.70), indicating a statistically significant difference between the two banks (Main Finding 23).

 Recommendation: For the other banks to increase the loyalty of their customers it is recommended that they effect changes that will see customers move from being spurious and latent loyals to being true loyals. This could be done by offering a more personalised service to customers who have been with the bank for a period of three years or longer, offering them lower fees, and constantly communicating with them.

7.2.12.5 LENGTH OF TIME WITH THE BANK

No significant differences between means can be observed in terms of black Generation Y adults’ loyalty levels of the CRM dimensions offered by their banks and the respondents’ length of time with the bank.

7.3 LINKING SECONDARY OBJECTIVES, MAIN FINDINGS, AND HYPOTHESES TO QUESTIONS IN THE QUESTIONNAIRE.

Table 7.3 presented below presents the link between the secondary objectives, hypotheses, questions in the questionnaire, and the main findings/results.

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Table 7.3: Link between secondary objectives, hypotheses, questions, and the main findings and results No Secondary objectives Hypotheses Questions in Main finding / questionnaire results 1 Conduct a literature review to identify the CRM dimensions that can be used in the N/A Dimensions MF: 14 banking industry. used in questionnaire 2 Identify the black Generation Y adults’ expectations of the CRM dimensions (service N/A Section A MF: 1-4 quality, customisation, two-way communication, technology, commitment, and Q1-35 convenience) offered by their banks. 3 Determine the overall satisfaction levels that black Generation Y adults have with their N/A Section B MF: 5-7 banks. Q36-39 4 Determine the overall relationship intention of black Generation Y with their banks. N/A Section B MF: 8-10 Q40-42 5 Determine the overall loyalty levels that black Generation Y adults have to their banks. N/A Section B MF: 11-13 Q43-45 6 Identify whether significant differences can be observed between the means of black H1 Section A MF: 15-19 Generation Y adults’ expectations and the CRM dimensions. Q1-35 H1: Accepted

7 Identify whether black Generation Y adults’ satisfaction levels influence the relationship H2: Section B MF: 20

intention and loyalty levels to their banks. H2a Q36-45 H2a: Accepted 8 Identify whether black Generation Y adults’ relationship intention influence their loyalty H2: Section B MF: 20

levels to their banks. H2b Q40-45 H2b: Accepted

H2c H2c: Accepted

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Table 7.3: Continued

No Secondary objectives Hypotheses Questions in Main finding / questionnaire results

9 Determine whether significant differences between means can be observed in terms of H3: H3a, H3b, Section A MF: 21-24

black Generation Y adults’ expectation levels of the CRM dimensions offered by their H3c, H3d, H3e Q1-35 H3a: Accepted

banks and demographic variables (gender, education, income, chosen bank, and length Section C H3b: Rejected

of time with the bank). H4: H4a, H4b, Q1-6 H3c: Rejected

H4c, H4d, H4e H3d: Rejected

H3e: Rejected

H5: H5a, H5b,

H5c, H5d, H5e H4a: Rejected

H4b: Rejected

H6: H6a, H6b, H4c: Rejected

H6c, H6d, H6e H4d: Rejected

H4e: Rejected

H7: H7a, H7b,

H7c, H7d, H7e H5a: Rejected

H5b: Rejected

H8: H8a, H8b, H5c: Rejected

H8c, H8d, H8e H5d: Rejected

H5e: Rejected

H6a: Accepted

H6b: Accepted

H6c: Rejected

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H6d: Rejected

H6e: Rejected

H7a: Rejected

H7b: Rejected

H7c: Rejected

H7d: Rejected

H7e: Rejected

H8a: Accepted

H8b: Rejected

H8c: Rejected

H8d: Rejected

H8e: Rejected

10 Determine whether significant differences between means can be observed in terms of H9: H9a, H9b, Section B MF: 25

black Generation Y adults’ satisfaction levels with the CRM dimensions offered by their H9c, H9d, H9e Q36-39 H9a: Rejected

banks and demographic variables. Section C H9b: Rejected

Q1-6 H9c: Rejected

H9d: Accepted

H9e: Rejected

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Table 7.3: Continued

No Secondary objectives Hypotheses Questions in Main finding / questionnaire results

11 Determine whether significant differences between means can be observed in terms of H10: H10a, Section B MF: 26

black Generation Y adults’ relationship intention levels of the CRM dimensions offered H10b, H10c, Q40-42 H10a: Rejected

by their banks and demographic variables. H10d, H10e Section C H10b: Rejected

Q1-6 H10c: Rejected

H10d: Accepted

H10e: Rejected

12 Determine whether significant differences between means can be observed in terms of H11: H11a, Section B MF: 27

black Generation Y adults’ loyalty levels of the CRM dimensions offered by their banks H11b, H11c, H11d, Q43-45 H11a: Rejected

and demographic variables. H11e Section C H11b: Rejected

Q1-6 H11c: Rejected

H11d: Accepted

H11e: Rejected

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Table 7.3 indicates that the results of the study obtained through the questionnaire support the achievement of the secondary objectives set for the study. These secondary objectives all contributed to answering the following primary objective: determine black Generation Y adults’ expectations of the CRM dimensions offered by their bank, and identify their overall levels of satisfaction, relationship intention and loyalty to their banks. The next section will focus on the limitations the researcher was faced with when conducting the study.

7.4 LIMITATIONS OF THE STUDY

In conducting the study the researcher was faced with the following limitations:  There was a lack of available literature on black Generation Y adults, particularly in academic journals.  No previous literature could be found on black Generation Y adults and the South African banking industry.  Various studies indicated different CRM dimensions, with some items in the dimensions being classified in different CRM dimensions in various studies.  Problems were experienced in obtaining permission to conduct the research at the selected shopping malls around Gauteng. Fieldworkers had to follow strict policies set by the shopping malls.  Respondents were hesitant in answering demographical questions pertaining to income.  The length of the questionnaire also caused a lack of interest leading to incomplete questionnaires.  Since the questionnaire targeted respondents at shopping malls, it did not include respondents who use online banking.  The study only focused on the four major banks in South Africa (ABSA, FNB, Nedbank and Standard Bank) and left out banks such as Capitec Bank.

7.5 RECOMMENDATIONS FOR FURTHER RESEARCH

After conducting the study and considering its limitations, the following recommendations for further research on this topic can be made:  The research could benefit from including customers using online banking as their primary method of banking.  Similar studies need to be conducted with the inclusion of Capitec Bank as a new rival to the four major banks in South Africa.

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 The research could benefit from using different sampling techniques (such as probability sampling) to ensure more representative results of the whole population.  The study should also be done in other geographical areas so that comparisons can be drawn.  The research could also be conducted on different age cohorts and population groups since the results could vary based on these differences.

7.6 CONCLUSION

This chapter provided insight into the major findings of the study and provided recommendations for the four major banks in South Africa with respect to the CRM dimensions, satisfaction, relationship intention and loyalty of black Generation Y consumers. It also presented the link between the secondary objectives, the main findings, the hypotheses and the questions in the questionnaire. It further outlined the limitations of the study and concluded with recommendations for further research.

The study aimed to identify black Generation Y adults’ expectations of their banks’ customer relationship management. The six CRM dimensions that came to the fore were service quality, customisation, two-way communication, technology, commitment, and convenience. Respondents indicated their level of agreement regarding these dimensions according to their expectations of each one. The research further provided insight into respondents’ satisfaction, relationship intention, and loyalty to their banks. Overall, respondents have high expectations of their respective banks’ CRM efforts and are also satisfied with their particular banks, showing intent to continue their relationship and also indicating a high likelihood of remaining loyal to their particular banks. In conclusion, the study succeeded in identifying the expectations black Generation Y adults have of their banks’ CRM efforts and their satisfaction, relationship intention, and loyalty levels, since each secondary objective was achieved.

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BIBLIOGRAPHY

Abratt, R., Berndt, A., de Jager, J., Klopper, H.B., Petzer, D., Saunders, S., Tait, M. & Viljoen, K. (2007). Contemporary cases in Southern African marketing. 2nd Edition. Claremont: New Africa Books.

Abratt, R. & Russel, J. (1999). Relationship marketing in private banking in South Africa. International Journal of Bank Marketing, 17(1):5-19.

ABSA. (2012). Overview. [online] Available at: http://www.absa.co.za/Absacoza/About- Absa/Absa-Group/Absa-Overview [Accessed: 23 May 2012].

Agrawal, M.L. (2004). Customer relationship management (CRM) & corporate renaissance. Journal of Services Research, 3(2):149-171.

Al-Alak, B.A. & Alnaser. A.S.M. (2012). Assessing the relationship between higher education service quality dimensions and student satisfaction. Australian Journal of Basic and Applied Sciences, 6(1):156-164.

Aldás-Manzano, J., Lassala-Navarré, C., Ruiz-Mafé, C. & Sanz-Blas, S. (2009). Key drivers of internet banking services use. Online Information Review, 33(4):672-695.

Al-Hawari, M.A. (2011). Automated service quality as a predictor of customers' commitment: A practical study within the UAE retail banking context. Asia Pacific Journal of Marketing and Logistics, 23(3):346-366.

Alhemoud, A.M. (2010). Banking in Kuwait: a customer satisfaction case study. Competitiveness review: An International Business Journal, 20(4):333-342.

Άlvarez, L.S., Casielles, R.V. & Martín, A.M.D. (2009). The role of commitment received by the consumer in service industries. Management Research: The Journal of the Iberoamerican Academy of Management, 7(2):141-157.

Anani, A.O. (2010). Attracting and retaining customers in South Africa’s banking sector. Published MBA minor dissertation. NMMU.

177

Awan, H.M., Bukhari, K.S. & Iqbal, A. (2011). Service quality and customer satisfaction in the banking sector: A comparative study of conventional and Islamic Banks in Pakistan. Journal of Islamic Marketing, 2(3):203-224.

Bagozzi, R.P. (1994). Principles of Marketing research. Cambridge: Blackwell.

Ball, D., Coelho, P.S. & Vilares, M.J. (2006). Service personalization and loyalty. Journal of Services Marketing, 20(6):391-403.

Balmer, J.M.T. (2011). Corporate marketing myopia and the inexorable rise of a corporate marketing logic: Perspectives from identity-based views of the firm. European Journal of Marketing, 45(9):1329-1352.

Bankmonitor. (2012). Costs, fees, features revealed. [online] Available at: http://icgrowth.co.za/bankmonitor/ [Accessed: 6 July 2012].

Bardakci, A. & Whitelock, J. (2005). A comparison of customers’ readiness for mass customisation: Turkish vs British customers. European Business Review, 17(5):397-410.

Berndt, A.D., Herbst, F.J. & Roux, L. (2004). Customer relationship management implementation within a retail banking environment: a South African perspective. Southern African Business Review, 8(2):31-41.

Bick, G., Abratt, R., & Moller, D. (2010). Customer service expectations in retail banking in Africa. South African Journal of Business Management, 41(2):13-27.

Bick, G., Brown, B. & Abratt, R. (2004). Customer perceptions of the value delivered by retail banks in South Africa. The International Journal of Bank Marketing, 22(5):300-318.

Bidvest Bank. (2012). Financial Intelligence Centre Act. [online] Available at: http://www.bidvestbank.co.za/Legal-FICA.aspx [Accessed: 14 August 2012].

Birdthistle, N. (2008). Family SMEs in Ireland as learning organisations. The Learning Organisation, 15(5):421-436.

Boshoff, C. & Du Plessis, F. (2009). Services marketing: A contemporary approach. Cape Town: Juta.

178

Bove, L.L. & Johnson, L.W. (2009). Does ‘true’ personal or service loyalty last? A longitudinal study. Journal of Services Marketing, 23(3):187-194.

Bradley, N. (2010). Marketing research: tools and techniques. 2nd Edition. New York, New York: Oxford University Press.

Burin, C.N. (2010). The perceived influence of the elements of internal marketing on the brand image of staffing agencies in South Africa. Published Masters Dissertation (MCom): University of Johannesburg.

BusinessDictionary. (2013). Customer. [online] Available at: http://www.businessdictionary.com/definition/customer.html [Accessed: 9 March 2013].

Cacioppe, R. & Stace, R. (2009). Integral team effectiveness: validity analysis of a theory- based team measure. Team Performance Management, 15(5/6):220-234.

Cant, M., Gerber-Nel, C., Nel, D. & Kotze, T. (2003). Marketing Research. Claremont: New Africa Books.

Cant, M.C., Strydom, J.W., Jooste, C.J. & du Plessis, P.J. (2006). Marketing Management. 5thEdition. Cape Town: Juta.

Capitec Bank. (2012). About Us. [online] Available at: http://www.capitecbank.co.za/aboutus [Accessed: 23 May 2012].

Casado, A.B., Nicolau, J.L. & Mas, F.J. (2010). The harmful consequences of failed recoveries in the banking industry. International Journal of Bank Marketing, 29(1):32-49.

Chang, W. & Hong, Y. (2011). A mixture model to estimate customer value for e-services. Kybernetes, 40(1/2):182-199.

Chau, V.S. & Ngai, L.W.L.C. (2010). The youth market for internet banking services: perceptions, attitude and behaviour. Journal of Services Marketing, 24(1):42-60.

179

Chen, M., Chang, K., Hsu, C. & Yang, I. (2011). Understanding the relationship between service convenience and customer satisfaction in home delivery by Kano model. Asia Pacific Journal of Marketing and Logistics, 23(3):386-410.

Chen, J., Yen, H.J.R., Li, E.Y. & Ching, R.K.H. (2009). Measuring CRM effectiveness: Construct development, validation and application of a process-oriented model. Total Quality Management, 20(3):283-299.

Choi, Y., Hise, R.T., Bagozzi, R.P. & Fadil, P.A. (2010). Communication, utilization, and performance in international strategic alliances: An investigation of the post-formation process. International Journal of Commerce and Management, 20(1):8-25.

Chowdhary, N. & Prakash, M. (2007). Prioritizing service quality dimensions. Managing Service Quality, 17(5):493-509.

Christensen, H.K. (2010). Defining customer value as the driver of competitive advantage. Strategy and Leadership, 38(5):20-25.

Chupi, N. (2010). The South African story. [online] Available at: http://www.ethos.co.za/c/article/340/the-south-african-story/ [Accessed: 22 February 2011].

Churchill, G.A. & Iacobucci, D. (2005). Marketing research: Methodological foundations. 9th Edition. Mason, Ohio: Thomson South Western.

Cohen, J. (1988). Statistical power analysis for the behavioural sciences. 2nd Edition. Hillsdale (NJ): Erlbaum.

Comins, L. (2005). Black consumers will have major market impact. [online] Available at: http://www.iol.co.za/news/south-africa/black-consumers-will-have-major-market-impact- 1.253590 [Accessed: 22 February 2011].

Competition Commission. (2012). The Competition Act. [online] Available at: http://www.compcom.co.za/assets/Files/pocket-book-2005-R.pdf [Accessed: 14 August 2012].

180

Council on Foreign Relations. (2012). The Global Finance Regime. [online] Available at: http://www.cfr.org/us-strategy-and-politics/global-finance-regime/p20177 [Accessed 6 July 2012].

Crain, D.W. (2009). Only the right people are strategic assets of the firm. Strategy and Leadership, 37(6):33-38.

Dagger, T.S., David, M.E. & Ng, S. (2011). Do relationship benefits and maintenance drive commitment and loyalty? Journal of Services Marketing, 25(4):273-281.

Dagger, T.S. & Sweeney, J.C. (2007). Service quality attribute weights: how do novice and longer-term customers construct service quality perceptions? Journal of Service Research, 10(1):22-42.

Da Silva, I.S. (2011). The truth about the black consumer market. [online] Available at: http://www.biz-community.com/Article/196/423/13076.html [Accessed: 23 February 2011].

Deloitte. (2012). Pushing the real-time accelerator; greater competition calls for banking unusual. [online] Available at: https://www.deloitte.com/assets/Dcom- SouthAfrica/Local%20Assets/Documents/Pushing%20the%20real- time%20acceleratorcvr2%20%282%29.pdf [Accessed: 9 September 2012].

De Meyer, C.F. & Petzer, D.J. (2012). Differences between customer type and consumption stage in terms of service failure responses and preferred service recovery strategies in the cellphone industry. Southern African Business Review, 16(2):24-46.

Dimitriadis, S. (2010). Testing perceived relational benefits as satisfaction and behavioural outcomes drivers. International Journal of Bank Marketing, 28(4):297-313.

Doyle, C. (2011). Oxford dictionary of marketing. 3rd Edition. New York, New York: Oxford University Press.

Edward, M. & Sahadev, S. (2011). Role of switching cost in the service quality, perceived value, customer satisfaction and customer retention linkage. Asia Pacific Journal of Marketing and Logistics, 23(3):327-345.

181

Egan, J. (2008). Relationship marketing: exploring relational strategies in marketing. 3rd Edition. Essex: Pearson Prentice Hall.

Eiselen R., Uys, T. & Potgieter N. (2005). Analysing survey data using SPSS13: a workbook. 3rd Edition. Johannesburg: University of Johannesburg.

Financial Intelligence Centre Act 38 of 2001. (2012). Financial Intelligence Centre Act 38 of 2001. [online] Available at: http://www.ssa.gov.za/Legislation/FIC%20Act%202001.pdf [Accessed: 14 August 2012].

Financial Services Forecast. (2005). South Africa. The Economist Intelligence Unit Limited, 474- 486.

Finstad, K. (2010). Response interpolation and scale sensitivity: Evidence against 5-point scales. Journal of Usability Studies, 5(3):104-110.

Finweek. (2009). Doing something right – Formula finds support. Finweek, 23.

Fisher-French, M. (2012). Mzansi accounts reach dead end. [online] Available at: http://mg.co.za/article/2012-02-17-mzansi-accounts-reach-dead-end [Accessed: 10 July 2013].

FNB. (2012). The world of FNB. [online] Available at: https://www.fnb.co.za/about- fnb/about-us/history.html [Accessed: 23 May 2012].

Foscht, T., Schloffer, J., Maloles, C. & Chia, S.L. (2009). Assessing the outcomes of Generation-Y customers’ loyalty. International Journal of Bank Marketing, 27(3):218-241.

Ganguli, S. & Roy, S.K. (2010). Generic technology-based service quality dimensions in banking: Impact on customer satisfaction and loyalty. International Journal of Bank Marketing, 29(2):168-189.

Gilaninia, S., Almani, A.M., Pournaserani, A. & Mousavian, S.J. (2011). Relationship marketing: A new approach to marketing in the third millennium. Australian Journal of Basic and Applied Sciences, 5(5):787-799.

182

Government Gazette. (2012a). Financial Advisory and Intermediary Services Act, 2002. [online] Available at: http://www.info.gov.za/view/DownloadFileAction?id=68072 [Accessed: 14 August 2012].

Government Gazette. (2012b). National Credit Act, 2005. [online] Available at: http://www.thenct.org.za/NCTDocs/founding-legislation/9a669fbc-ef58-4bd2-8a5e- d12f37d018bf.pdf [Accessed: 14 August 2012].

Government Gazette. (2012c). The Consumer Protection Act, 2008. [online] Available at: http://www.info.gov.za/view/DownloadFileAction?id=99961 [Accessed: 14 August 2012].

Government Gazette. (2012d). Home loan and Mortgage Disclosure Act, 2000. [online] Available at: http://www.info.gov.za/view/DownloadFileAction?id=68232 [Accessed: 14 August 2012].

Green, S. & Van Belle, J. (2012). Customer expectations of internet banking in South Africa. [online] Available at: http://www.commerce.uct.ac.za/informationsystems/staff/personalpages/jvbelle/pubs/f- VanBelleJeanPaul2.pdf [Accessed: 22 October 2012].

Gronroos, C. (1994). From marketing mix to relationship marketing: Towards a paradigm shift in marketing. Management Decision, 32(2):4-20.

Gummesson, E. (2008). Quality, service-dominant logic and many-to-many marketing. The TQM Journal, 20(2):143-153.

Gummesson, E., Lusch, R.F. & Vargo, S.L. (2010). Transitioning from service management to service-dominant logic: Observations and recommendations. International Journal of Quality and Service Sciences, 2(1):8-22.

Hair, J.F., Wolfinbarger, M.F., Ortinau, D.J. & Bush, R.P. (2010). Essentials of marketing research. 2nd Edition. New York, New York: McGraw-Hill.

Hardy, M. & Bryman, A. (2004). Handbook of data analysis. London: Sage.

Hariharan, V.G., Bezawada, R. & Talukdar, D. (2012). Trial, repeat purchase and spillover effects of cobranded extensions”. Journal of Product & Brand Management, 21(2):76-88.

183

Harridge-March, S. (2009). Direct marketing and relationships: An opinion piece. Direct Marketing: An International Journal, 2(4):192-198.

Harrigan, P., Ramsey, E. & Ibbotson, P. (2012). Entrepreneurial marketing in SMEs: The key capabilities of e-CRM. Journal of Research in Marketing and Entrepreneurship, 14(1):40-64.

Harwood, T.G. & Garry, T. (2006). Relationship marketing: Why bother? Handbook of Business Strategy, 7(1):107-111.

Hashem, T.N. (2012). The impact of customer relationship marketing on costumers’ image for Jordanian five star hotels. International Journal of Business and Social Science, 3(2):129-134.

Haynes, B.P. (2011). The impact of generational differences on the workplace. Journal of Corporate Real Estate, 13(2):98-108.

Hellawell, M. (2012). How to create a thriving workplace: Reaping the benefits of employee satisfaction. Strategic Direction, 28(5):3-5.

Hoffman, K.D., Bateson, J.E.G., Wood, E.H. & Kenyon, A.J. (2009). Services marketing: Concepts, strategies and cases. 4th Edition. London: South-Western, Cengage Learning.

Hume, M. & Mort, G.S. (2010). The consequence of appraisal emotion, service quality, perceived value and customer satisfaction on repurchase intent in the performing arts. Journal of Services Marketing, 24(2):170-182.

Iacobucci, D. & Churchill, G.A. (2010). Marketing research: Methodological foundations. 10th Edition. Mason, Ohio: South Western, Cengage Learning.

I-net Bridge. (2011). Only 9% switch banks: Study. [online] Available at: http://www.fin24.com/Money/Money-Clinic/Only-9-switch-banks-study-20110225 [Accessed: 18 October 2011].

InnovationAgency. (2010). 2010 Banking Innovation Study South Africa. [online] Available at: http://www.innovationagency.com/wp-content/uploads/2011/01/2010-Banking-Innovation- study-Highlevel-overview-v1.2.pdf [Accessed: 27 October 2011].

184

Innovation Agency (2011). Banking Landscape Observations and Opportunities for Innovation in Banking 2011. [online] Available at: http://www.innovationagency.com/wp- content/uploads/2011/08/2011-Banking-Landscape-Observations-and-Opportunities-for- Innovation-in-Banking-v1.1.pdf [Accessed: 1 March 2012].

Jensen, J.M. (2011). Consumer loyalty on the grocery product market: An empirical application of Dick and Basu’s framework. Journal of Consumer Marketing, 28(5):333-343.

Johnston, M.W. & Marshall, G.W. (2010). Relationship selling. 3rd Edition. New York, New York: McGraw-Hill.

Jones, L. (2006). Showing up the big boys – Capitec offers lowest fees in banking sector by a long way. Finweek. 72-73.

Jones, H. & Farquhar, J.D. (2007). Putting it right: Service failure and customer loyalty in UK banks. International Journal of Bank Marketing, 25(3):161-172.

Jorgensen, B. (2003). Baby Boomers, Generation X and Generation Y: Policy implications for defence forces in the modern era. Foresight, 5(4):41-49.

Kamhunga, S. (2011). Battle of Banks will be about fees – FNB. [online] Available at: http://bankmonitorsa.blogspot.com/2011/09/battle-of-banks-will-be-about-fees-fnb.html [Accessed: 18 October 2011].

Kamhunga, S. (2012). FNB opens retail bank in Mumbai. [online] Available at: http://www.bdlive.co.za/articles/2012/04/13/fnb-opens-retail-bank-in-mumbai [Accessed: 22 March 2012].

Kasouf, C.J., Darroch, J., Hultman, C.M. & Miles, M.P. (2009). Service dominant logic: Implications at the marketing/entrepreneurship interface. Journal of Research in Marketing and Entrepreneurship, 10(1):57-69.

Kotler, P., Armstrong, G., Tait, M., Beneke, J., Bhowan, K., Blake, S., Botha, E., Cassim, S., de Jager, J,. Frey, N., George, R., Golestaneh, M., Human, D., Rammile, N., Roberts- Lombard, M., Rootman, C., Rugimbana, R., van Zyl, J., Vigar-Ellis, D., & Wait, M. (2010). Principles of marketing. Cape Town: Pearson Education.

185

Kotler, P. & Keller, K.L. (2006). Marketing management. 12th Edition. Upper Saddle River, New Jersey: Pearson Prentice Hall.

Kowalkowski, C. (2011). Dynamics of value propositions: Insights from service-dominant logic. European Journal of Marketing, 1(2):277-294.

Kruger, L. & Mostert, P.G. (2012). Young adults’ relationship intentions towards their cell phone network operators. South African Journal of Business Management, 43(2):41-49.

Kumar, A. & Lim, H. (2006). Age differences in mobile service perceptions: Comparison of Generation Y and baby boomers. Journal of Services Marketing, 22(7):568-577.

Labour Force Survey. (2011). Quarterly labor force survey quarter 1 2011. [online] Available at: http://www.statssa.gov.za/publications/P0211/P02111stQuarter2011.pdf [Accessed: 22 March 2012].

Lamb, C.W., Hair, J.F., McDaniel, C., Boshoff, C., Terblanche, N., Elliot, R. & Klopper, H.B. (2010). Marketing. 4th Edition. Cape Town: Oxford University Press.

Lambert, D.M. (2010). Customer relationship management as a business process. Journal of Business and Industrial Marketing, 25(1):4-17.

Lankton, N.K. & Wilson, E.V. (2007). Factors influencing expectations of e-health services within a direct-effects model of user satisfaction. e-Service Journal, 5(2)85-111.

Lapre, M.A. & Tsikriktsis, N. (2006). Organisational learning curves for customer dissatisfaction: Heterogeneity across airlines. Management Science, 52(3):352-366.

Latham, S.F. & Braun, M.R. (2010). Jilted? The manager’s little book for keeping customers in a recession. Journal of Business Strategy, 31(1):4-10.

Lee, H. & Lee, S. (2010). Internet versus mobile services: comparisons of gender and ethnicity. Journal of Research in Interactive Marketing, 4(4):346-375.

Leventhal, L. (2008). The role of understanding customer expectations in aged care. International Journal of Health Care Quality Assurance, 21(1):50-59.

186

Levy, M. & Weitz, B.A. (2012). Retailing Management. 8th Edition. New York, New York: McGraw-Hill.

Li, D., Chang, F.M. & Chang, S. (2010). The relationship between affecting factors and mass-customisation level: The case of a pigment company in Taiwan. International Journal of Production Research, 48(18):5385-5395.

Ma, Y.J. & Niehm, L.S. (2006). Service expectations of older Generation Y customers: An examination of apparel retail settings. Managing Service Quality, 16(6):620-640.

Mahapatra, S.N., Kumar, J. & Chauhan, A. (2010). Consumer satisfaction, dissatisfaction and post-purchase evaluation: An empirical study on small size passenger cars in India. International Journal of Business and Society, 11(2):97-108.

Malhotra, N.K. (2007). Marketing research. 5th Edition. Upper Saddle River, New Jersey: Pearson Prentice Hall.

Malhotra, N.K. (2012). Questionnaire design and scale development. [online] Available at: http://www.terry.uga.edu/~rgrover/chapter_5.pdf [Accessed: 20 September 2012].

Malik, M.E., Naeem, B. & Arif, Z. (2011). How do service quality perceptions contribute in satisfying banking customers. Interdisciplinary Journal of Contemporary Research in Business, 3(8):646-653.

Mandhachitara, R. & Poolthong, Y. (2011). A model of customer loyalty and corporate social responsibility. Journal of Services Marketing, 25(2):122-133.

Maringe, F. (2006). University and course choice: Implications for positioning, recruitment and marketing. International Journal of Educational Management, 20(6):466-479.

Maritz, A. & Nieman, G. (2008). Implementation of service profit chain initiatives in a franchise system. Journal of Services Marketing, 22(1):13-23.

Mark, A. & Zen, R. (2007). 10 Steps to improve patient satisfaction. Nursing, 37(5):22-24.

Martensen, A. (2007). Tweens satisfaction and brand loyalty in the mobile phone market. Young Consumers, 8(2):108-116.

187

McMullan, R. & Gilmore, A. (2008). Customer loyalty: An empirical study. European Journal of Marketing, 42(9/10):1084-1094.

Minkiewicz, J., Evans, J., Bridson, K. & Mavondo, F. (2011). Corporate image in the leisure services sector. Journal of Services Marketing, 25(3):190-201.

Mishra, A. & Mishra D. (2009). Customer relationship management: Implementation process perspective. Acta Polytechnica Hungarica, 6(4):83-99.

Mishra, J. (2012). On finance & non-formal ways: Growth patterns of different types of firms. [online] Available at: http://articles.economictimes.indiatimes.com/2012-05- 12/news/31679744_1_bank-finance-firms-total-financing [Accessed: 14 August 2012].

Momentum. (2012). Regulatory and representative bodies. [online] Available at: http://www.momentum.co.za/wps/portal/Home/mom-pre- home/?1dmy¤t=true&urile=wcm%3Apath%3A/momentum/corporate/about- momentum/client-protection/regulatory-bodies/ [Accessed: 14 August 2012].

Mulholland, S. (2007). Convicted as charged. [online] Available at: http://www.fin24.com/Finweek/Nothing-sacred/Convicted-as-charged-20070624 [Accessed: 22 February 2011].

Muñoz-Leiva, F., Luque-Martínez, T. & Sánchez-Fernández, J. (2010). How to improve trust toward electronic banking. Online Information Review, 34(6):907-934.

National Consumer Commission. (2012). Consumer protection act. [online] Available at: http://www.nccsa.org.za/index.php/The-Act/The-Act/Consumer-Protection-Act.html [Accessed: 14 August 2012].

National Treasury. (2011). National Treasury policy document. [online] Available at: http://www.treasury.gov.za/documents/national%20budget/2011/A%20safer%20financial%2 0sector%20to%20serve%20South%20Africa%20better.pdf [Accessed: 22 February 2011].

National Payment System Act 1998. (2012). Republic of South Africa government gazette. [online] Available at: http://www.info.gov.za/view/DownloadFileAction?id=70735 [Accessed: 14 August 2012].

188

Ndubisi, N.O., Wah, C.K. & Ndubisi, G.C. (2007). Supplier-customer relationship management and customer loyalty: The banking industry perspective. Journal of Enterprise Information Management, 20(2):222-236.

Ndubisi, N.O. & Sinti, Q. (2006). Consumer attitudes, system's characteristics and internet banking adoption in Malaysia. Management Research News, 29(1):16-27.

Nedbank. (2012a). Nedbank group history. [online] Available at: http://www.nedbankgroup.co.za/abouthistory.asp [Accessed: 23 May 2012].

Nedbank. (2012b). Company Structure. [online] Available at: http://www.nedbankgroup.co.za/financial/Nedbank_ar2011/overview/company_structure.asp [Accessed: 24 May 2012].

Nedbank. (2012c). Consolidated statement of comprehensive income. [online] Available at: http://www.nedbankgroup.co.za/financial/Nedbank_ar2011/downloads/financial.pdf [Accessed: 24 May 2012].

Nguyen, N. & Leclerc, A. (2011). The effect of service employees' competence on financial institutions' image: benevolence as a moderator variable. Journal of Services Marketing, 25(5):349-360.

Nordin, F., Kindström, D., Kowalkowski, C. & Rehme, J. (2011). The risks of providing services: Differential risk affects of the service-development strategies of customisation, bundling and range. Journal of Services Management, 22(3):390-408.

Okeahalam, C. (2001). Structure and conduct in the commercial banking sector of South Africa. [online] Available at: http://www.tips.org.za/files/499.pdf [Accessed 10 July 2013].

Okeahalam, C. (2007). Estimating market power in the South African banking sector. International Review of Applied Economics, 21(5):669-685.

Okeahalam, C. (2007). Economics of access in a developing country: an analysis of firm- conduct in financial services. International Journal of Social Economics, 34(12):923-942.

Őztaysi, B., Sezgin, S. & Őzok, A.F. (2011). A measurement tool for customer relationship management processes. Industrial Management and Data Systems, 111(6):943-960.

189

Padma, P., Rajendran, C. & Sai, L.P. (2009). A conceptual framework of service quality in healthcare: Perspectives of Indian patients and their attendants. Benchmarking: An International Journal, 16(2):157-191.

Pallant, J. (2007). SPSS survival manual: A step-by-step guide to data analysis using SPSS version 15. 3rd Edition. Berkshire: McGraw-Hill Education.

Palmer, A. (2008). Principles of services marketing. 5th Edition. New York, New York: Mc- Graw Hill.

Payne, A. (2005). Handbook of CRM: achieving excellence in customer management. Oxford: Butterworth-Heinemann.

Payne, A., Ballantyne, D. & Christopher, M. (2005). A stakeholder approach to relationship marketing strategy: the development and use of the ‘six markets’ model. European Journal of Marketing, 39(7/8): 855-871.

Pinar, M., Eser, Z. & Strasser, S. (2010). Using mystery shopping to compare the service quality of banks in Turkey. Services Marketing Quarterly, 31:1-26.

Pitman, J. (2011). How Capitec gave the established banking industry a run for its money. [online] Available at: file:///C:/Users/Marius/Desktop/Capitec%20%20Riaan%20Stassen%20_%20Entrepreneur% 20Magazine.htm [Accessed: 13 April 2012].

Pitta, D., Franzak, F. & Fowler, D. (2006). A strategic approach to building online customer loyalty: Integrating customer profitability tiers. Journal of Consumer Marketing, 23(7):421- 429.

Pitta, D.A., Guesalaga, R. & Marshall, P. (2008). The quest for the fortune at the bottom of the pyramid: potential and challenges. Journal of Consumer Marketing, 25(7):393-401.

PMG. (2012). Home Loan and Mortgage Disclosure Bill: Briefing. [online] Available at: http://www.pmg.org.za/minutes/20000912-home-loan-mortgage-disclosure-bill-briefing [Accessed: 14 August 2012].

190

PWC. (2011). Unlocking opportunities Strategic and emerging issues in South African banking 2011 [online] Available at: http://www.pwc.co.za/en_ZA/za/assets/pdf/SA-Banking- 2011.pdf [Accessed: 22 March 2012].

Rababah, K., Mohd, H. & Ibrahim, H. (2011). Customer relationship management (CRM) processes from theory to practice: The pre-implementation plan of CRM system. International Journal of e-Education, e-Business, e-Management and e-Learning, 1(1):22-27.

Ranjan, J. & Bhatnagar, V. (2011). Role of knowledge management and analytical CRM in business: Data mining based framework. The Learning Organisation, 18(2):131-148.

Ravesteyn, L.J. (2005). The effect of relationship banking on customer loyalty in the retail business banking industry. Published Masters dissertation, (MCom): University of South Africa.

Richard, J.E., Thirkell, P.C. & Huff, S.L. (2007). An Examination of customer relationship management (CRM) technology adoption and its impact on Business-to-Business customer relationships. Total Quality Management, 18(8):927-945.

Rivera-Camino, J. (2007). Re-evaluating green marketing strategy: A stakeholder perspective. European Journal of Marketing, 41(11/12):1328-1358.

Roberts, C. (2007). Mixing modes of data collection in surveys: A methodological review. [online] Available at: http://eprints.ncrm.ac.uk/418/1/MethodsReviewPaperNCRM-008.pdf [Accessed: 13 September 2012].

Roberts-Lombard, M. (2009). A supply chain perspective on the supplier relationship practices on travel agencies in Gauteng. Journal of Transport and Supply Chain Management, 3(1):59-79.

Roig, J.C.F., Garcia, J.S., Tena, M.A.M. & Monzonis, J.L. (2006). Customer perceived value in banking services. International Journal of Bank Marketing, 24(5):266-283.

Rootman, C. (2006). The influence of customer relationship management on the service quality of banks. Published Masters Dissertation: Nelson Mandela Metropolitan University.

191

Sangle, P.S. & Awasthi, P. (2011). Consumer’s expectations from mobile CRM services: A banking context. Business Process Management Journal, 17(6):898-918.

SARB. (2011). Selected South African banking sector trends. [online] Available at: http://www.resbank.co.za/Lists/News%20and%20Publications/Attachments/3778/12%20Dec ember%202011.pdf [Accessed: 1 March 2012].

SARB. (2012a). South African Reserve Bank history [online] Available at: (http://www.resbank.co.za/AboutUs/History/Background/Pages/Background-Home.aspx) [Accessed: 01 March 2012].

SARB. (2012b). The Banks Act 1990. [online] Available at: http://www2.resbank.co.za/internet/Publication.nsf/LADV/0B2DBBD25565FE0242256D8D00 341E9D/$File/Banks+Act+1990.pdf [Accessed: 23 May 2012].

SARB. (2012c). The National Payment System in South Africa: 1995 to 2005. [online] Available at: http://www.resbank.co.za/RegulationAndSupervision/NationalPaymentSystem%28NPS%29/ Documents/Overview/NPS95to05.pdf [Accessed: 14 August 2012].

Saunders, S.G. (2008). Measuring and applying the PAKSERV service quality construct: Evidence from a South African cultural context. Managing Service Quality, 18(5):442-456.

Sharabi, M. & Davidow, M. (2010). Service quality implementation: Problems and solutions. International Journal of Quality and Service Sciences, 2(2):189-205.

Shum, P., Bove, L. & Auh, S. (2008). Employees' affective commitment to change: The key to successful CRM implementation. European Journal of Marketing, 42(11):1346-1371.

Sibiya, S. (2007). Black consumers aren’t white. [online] Available at: http://www.bizcommunity.com/Article/196/11/17229.html [Accessed: 22 February 2011].

Siddiqi, K.O. (2011). Interrelations between service quality attributes, customer satisfaction and customer loyalty in the retail banking sector in Bangladesh. International Journal of Business and Management, 6(3):12-36.

192

Sigala, M. (2006). Mass customisation implementation models and customer value in mobile phones services: Preliminary findings from Greece. Managing Service Quality, 16(4):395-420.

Sin, L.Y.M., Tse, A.C.B. & Yim, F.H.K. (2005). CRM: Conceptualization and scale development. European Journal of Marketing, 39(11):1264-1290.

Smith, C. (2010). Black to the future – South Africa’s Gen Y. [online] Available at: http://www.tomorrowtoday.co.za/2010/03/02/%E2%80%9Cblack-to-the-future%E2%80%9D- south-africa%E2%80%99s-gen-y/ [Accessed: 22 February 2011].

Smith, C. (2011). Black South African Graduate Numbers Rise Fourfold in 20 years. [online] Available at: http://www.guardian.co.uk/world/2011/jan/19/black-south-african- university-graduates [Accessed 22: February 2011].

South Africa.info. (2012). South Africa.info [online] Available at: (http://www.southafrica.info/business/economy/sectors/financial.htm) [Accessed: 01 March 2012].

South Africa Info Reporter. (2004). Black spending power on the up. [online] Available at: http://www.southafrica.info/doing_business/trends/empowerment/buppie.htm [Accessed: 22 February 2011].

South African Government. (2012). The Mutual Banks Act 1993. [online] Available at: http://www.info.gov.za/acts/1993/a124-93.htm [Accessed: 23 May 2012].

Srijumpa, R., Chiarakul, T. & Speece, M. (2007). Satisfaction and dissatisfaction in service encounters: Retail stockbrokerage and corporate banking in Thailand. International Journal of Bank Marketing, 25(3):173-194.

Standard Bank. (2012a). History. [online] Available at: http://www.standardbank.co.za/site/investor/corp_history01.html [Accessed: 24 May 2012].

Standard Bank. (2012b). Annual integrated report 2011. [online] Available at: http://annualreport2011.standardbank.com/downloads/Book-I-Business-Review.pdf [Accessed: 24 May 2012].

193

Suk, J.B., Chung, S.H., Choi, K. & Park, J. (2009). The causal relationship on quality- centered organizational culture and its impact on service failure and service recovery. The Asian Journal on Quality, 10(1):37-51.

The Banking Association South Africa. (2011). South African Banking Sector Overview. [online] Available at: http://www.banking.org.za/getdoc/getdoc.aspx?docid=1130 [Accessed: 15 June 2011].

The Banking Association South Africa. (2012a). South African Banking Sector Overview November 2011. [online] Available at: www.banking.org.za/getdoc/getdoc.aspx?docid=1175 [Accessed: 01 March 2012].

The Banking Association South Africa. (2012b). Nedbank – Case study. [online] Available at: http://www.nihilent.com/casestudies/Nedbank(CFS).pdf [Accessed: 6 July 2012].

Thuy, P.N. (2011). Using service convenience to reduce perceived cost. Marketing Intelligence and Planning, 29(5):473-487.

Tsai, C. & Su, C. (2009). Service failures and recovery strategies of chain restaurants in Taiwan. The Service Industries Journal, 29(12):1779-1796.

Vargo, S.L. (2009). Toward a transcending conceptualization of relationship: A service- dominant logic perspective. Journal of Business and Industrial Marketing, 24(5):373-379.

Vaughn, G. (2003). Simple steps to satisfaction. Nursing Management, 2003:20-24.

Veldhuyzen van Zanten, S.J.O., Chiba, N., Armstrong, D., Barkun, A.N., Thomson, A.B.R., Mann, V., Escobedo, S., Chakraborty, B. & Nevin, K. (2006). Validation of a 7-point Global Overall Symptom scale to measure the severity of dyspepsia symptoms in clinical trials. Journal Compilation: Aliment Pharmacol Ther, 23:521-529.

Walsh, K. & Gordon, J.R. (2010). Understanding professional service delivery. International Journal of Quality and Service Sciences, 2(2):217-238.

Wang, F., Hu, F. & Yu, L. (2010). The application of customer relationship management in investment banks. Asian Social Science, 6(10):178-183.

194

Wang, Y. & Feng, H. (2012). Customer relationship management capabilities: Measurements, antecedents and consequences. Management Decision, 50(1):115-129.

Whitfield, B. (2007). Loan arrangers – Its Abil versus Capitec, but investors increasingly have more choice. Finweek, 26-27.

Wong, Y.H., Chan, R.Y.K., Leung, T.K.P. & Pae, J.H. (2008). Commitment and vulnerability in B2B relationship selling in the Hong Kong institutional insurance service industry. Journal of Services Marketing, 22(2):136-148.

Worley, J.M. & Doolen, T.L. (2006). The role of communication and management support in a lean manufacturing implementation. Management Decision, 44(2):228-245.

Wright, M. & Riebe, E. (2010). Double jeopardy in brand defection. European Journal of Marketing, 44(6):860-873.

Yen, T., Chung, Y. & Tsai, C. (2007). Business opportunity algorithm for ISO 9001: 2000 customer satisfaction management structure. Research Journal of Business Management, 1(1):1-10.

Yik-Chee, L., Meredith, G.G. & Marchant, T. (2010). Singapore stock broking service quality: Fifteen percent gap. Journal of Services Marketing, 24(4):305-313.

Yi-Ming, T. & Chin-Fu. Ho. (2010). Effects of information sharing on customer relationship intention. Industrial Management and Data Systems, 110(9):1385-1401.

Zeithaml, V.A., Bitner, M.J. & Gremler, D.D. (2009). Services marketing: Integrating customer focus across the firm. 5th Edition. New York, New York: McGraw-Hill.

Zeithaml, V.A., Rust, R.T. & Lemon, K.N. (2001). The customer pyramid: Creating and serving profitable customers. California Management Review, 43(4):118-142.

Zengh, V. (2011). The value proposition of adopting mCRM strategy in UK SME’s. Journal of Systems and Information Technology, 13(2):223-245.

Zikmund, W.G. & Babin, B.J. (2007). Essentials of marketing research. 3rd Edition. Mason, Ohio: South Western, Cengage Learning.

195

Zikmund, W.G. & Babin, B.J. (2010). Essentials of marketing research. 4th Edition. Mason, Ohio: South Western, Cengage Learning.

Zikmund, W.G., Babin. B.J., Carr, J.C. & Griffin, M. (2010). Business research methods. 8th Edition. Mason, Ohio: South Western, Cengage Learning.

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ANNEXURES ANNEXURE 1: QUESTIONNAIRE FOR PRE-TESTING

Expectations, Satisfaction and Loyalty – The South African Banking Industry

______This questionnaire is designed to obtain feedback from you on the expectations and levels of satisfaction you experience with your current bank (ABSA, FNB, Nedbank and Standard Bank). The outcome of this survey will be used to determine the expectations and satisfaction of Black Generation Y adults towards the Customer Relationship Management efforts offered by their banks in the Gauteng area. The questionnaire will be completely anonymous and taking part is voluntary. The questionnaire consists of four sections and should take no longer than 15 minutes to complete. Your cooperation is valued. In answering questions please do so from your own perspective. Indicate all answers with an X in the appropriate box.

Thank you for taking the time to complete this survey. Should you have any questions, please feel free to contact: Mr. Marius Bresler: 011 559 3261 or [email protected] (Master’s Student) Dr. Christine De Meyer: 011 559 2455 or [email protected] (Supervisor)

Screening questions Which one of the following banks do you bank with most frequently?

ABSA 1 FNB 2 Standard Bank 3 Nedbank 4 None of the above 5

If your answer to the above question is “none of the above” then you do not need to continue with the rest of the questionnaire. If you chose any of the other banks, please continue.

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Have you had an account at this bank for a period of three years or longer?

Yes 1 No 2

Are you between the ages of 21 and 34?

Yes 1 No 2

If you answered “Yes” to both the previous questions, please continue with Section A, B and C. If your answer to any of the questions were “No”, then you do NOT have to complete the questionnaire.

SECTION A – Expectations Please rate you bank and your willingness to form a relationship with it with regard to the following statements, where 1 is “Strongly disagree” and 7 is “Strongly agree”. Strongly Strongly Disagree Agree 1 My bank should have up-to-date equipment 1 2 3 4 5 6 7 2 My bank’s physical facilities should be visually appealing 1 2 3 4 5 6 7 3 My bank’s employees should be well dressed and appear neatly 1 2 3 4 5 6 7 4 When my bank promises to do something by a certain time, they 1 2 3 4 5 6 7 should do it 5 When I have a problem my bank must be sympathetic 1 2 3 4 5 6 7 6 My bank should be dependable 1 2 3 4 5 6 7 7 My bank should keep accurate records of my accounts 1 2 3 4 5 6 7 8 My bank should inform me exactly when services I requested will be 1 2 3 4 5 6 7 performed 9 The bank’s employees must always be willing to help me 1 2 3 4 5 6 7 10 Employees of the bank should be available to respond to my requests 1 2 3 4 5 6 7 promptly 11 I should be able to trust the employees of my bank 1 2 3 4 5 6 7 12 My bank’s employees should be polite 1 2 3 4 5 6 7 13 I expect of my bank to give me individual attention 1 2 3 4 5 6 7 14 It is realistic to expect that my bank has my best interest at heart 1 2 3 4 5 6 7 15 My bank is expected to have operating hours that are convenient to 1 2 3 4 5 6 7

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me 16 I should be able to rely on my bank to customise services according to 1 2 3 4 5 6 7 my needs 17 My bank and I should make changes to customise my relationship- 1 2 3 4 5 6 7 specific investments 18 My bank should be flexible in serving my needs 1 2 3 4 5 6 7 19 My bank should make an effort to find out what my needs are 1 2 3 4 5 6 7 20 When my bank realises that I would like to modify a service, the 1 2 3 4 5 6 7 departments involved should make a coordinated effort to do so 21 The more extensively I communicate with my bank, the better 1 2 3 4 5 6 7 relationship I develop with my bank 22 My relationship with my bank will depend on the variety of services 1 2 3 4 5 6 7 offered 23 My bank should provide me with complete information when there is a 1 2 3 4 5 6 7 new product or service 24 My bank should provide me with timely information 1 2 3 4 5 6 7 25 My bank should provide me with trustworthy information 1 2 3 4 5 6 7 26 My bank should have the ability to openly discuss solutions to my 1 2 3 4 5 6 7 problems 27 My bank and I should talk openly with one another 1 2 3 4 5 6 7 28 Overall my bank should have easy-to-use technology (Eg. ATMs, self- 1 2 3 4 5 6 7 service kiosks, mobile applications, internet banking) 29 Learning to use my bank’s technologies should be easy 1 2 3 4 5 6 7 30 Using my bank’s technologies should make it easier for me to do my 1 2 3 4 5 6 7 banking 31 My bank’s employees should be available to assist me when using the 1 2 3 4 5 6 7 bank’s technologies 32 My bank should meet its obligations towards me 1 2 3 4 5 6 7 33 I want to remain a customer with my bank because I enjoy my 1 2 3 4 5 6 7 relationship with them 34 My bank should be committed to forming relationships with me 1 2 3 4 5 6 7 35 My relationship with my bank should be very important to them 1 2 3 4 5 6 7 36 My relationship with my bank should deserve their maximum effort to 1 2 3 4 5 6 7 maintain 37 My bank should be prepared to make short-term sacrifices to maintain 1 2 3 4 5 6 7 our relationship

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38 I believe my bank and I should view our relationship as a long-term 1 2 3 4 5 6 7 partnership 39 My bank should be conveniently located 1 2 3 4 5 6 7 40 My bank’s ATMs should be conveniently located 1 2 3 4 5 6 7 41 My bank’s internet platform should be easy to use 1 2 3 4 5 6 7 42 My bank’s self-service kiosks need to be conveniently located 1 2 3 4 5 6 7 43 Employees should go out of their way to reduce inconveniences for me 1 2 3 4 5 6 7

SECTION B – Satisfaction, Relationship Intention and Loyalty

Overall Satisfaction Please rate the following statements pertaining to your overall satisfaction levels with your bank, where 1 is “Strongly disagree” and 7 is “Strongly agree”. Strongly Strongly Disagree Agree 44 My feelings toward my bank are positive 1 2 3 4 5 6 7 45 I feel good about using my bank as my service provider 1 2 3 4 5 6 7 46 I feel satisfied that the results from using my bank are the best that I can 1 2 3 4 5 6 7 currently obtain 47 The extent to which I have been using my bank, has produced the best 1 2 3 4 5 6 7 possible outcome

Please rate the following statements pertaining to your willingness to form relationships and loyalty levels towards your bank, 1 is “Not likely at all” and 7 is “Very likely”. Not likely Very at all likely 48 I will continue doing business with my bank 1 2 3 4 5 6 7 49 I will recommend my bank to others as a result of my positive experience 1 2 3 4 5 6 7 50 If a competing bank offers me lower banking fees I will still make use of my 1 2 3 4 5 6 7 current bank 51 I expect my relationship with my bank to continue for a long time 1 2 3 4 5 6 7 52 I say positive things about my bank to other people 1 2 3 4 5 6 7 53 I consider my bank to be the first choice of bank 1 2 3 4 5 6 7 54 I will remain loyal to my bank 1 2 3 4 5 6 7

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SECTION C – Demographics Please mark the following statements that apply to you with an X. 1. What is your Gender? Male 1 Female 2

2. What is your highest level of education? Primary school completed 1 Matric/Grade 12 2 Diploma/Certificate 3 Bachelors degree 4 Postgraduate degree/Qualification 5

3. What is your marital status? Single 1 Married 2 Divorced 3 Widowed 4 Living together 5 Separated 6

4. What is your personal monthly income level after tax? R0 – R3 000 1 R3 001 – R5 000 2 R5 001 – R7 000 3 R7 001– R10 000 4 R10 001 – R15 000 5 R15 001 – R20 000 6 R20 001 –R25 000 7 R25 001 – R30 000 8 R30 001 – R35 000 9 R35 001 – R40 000 10 R40 001 – R45 000 11 R45 001 – R50 000 12 R50 001 and more 13

5. What type of account(s) do you hold with the bank selected at the beginning of the questionnaire? Mark all accounts that apply. Cheque Accounts 1 Savings Account 2 Mzansi Account 3 Investment Account(s) 4 Bond/Home Loan 5 Vehicle Finance 6 Loan (Any other loan) 7 Other (Please specify): 8

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6. How long have you been banking with the bank identified at the beginning of the questionnaire? 3 years or more, but less than 5 years 1 5 years or more, but less than 7 years 2 7 years or more, but less than 9 years 3 More than 9 years 4

7. Indicate through which ONE of the following your relationship with your bank will be enhanced? Mobile/Cellphone banking 1 Telephone banking 2 Online/Internet banking 3 A banking application 4 In branch banking 5

Thank you for taking time to answer this questionnaire.

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ANNEXURE 2: FINAL QUESTIONNAIRE

Expectations, Satisfaction and Loyalty – The South African Banking Industry ______

This questionnaire is designed to obtain feedback from you on the expectations and levels of satisfaction you experience with your current bank (ABSA, FNB, Nedbank and Standard Bank). The outcome of this survey will be used to determine the expectations and satisfaction of Black Generation Y adults towards the Customer Relationship Management efforts offered by their banks in the Gauteng area. The questionnaire will be completely anonymous and taking part is voluntary. The questionnaire consists of four sections and should take no longer than 15 minutes to complete. Your cooperation is valued. In answering questions please do so from your own perspective. Indicate all answers with an X in the appropriate box.

Screening questions Which one of the following banks do you bank with most frequently?

ABSA 1 FNB 2 Standard Bank 3 Nedbank 4 None of the above 5

If your answer to the above question is “none of the above” then you do not need to continue with the rest of the questionnaire. If you chose any of the other banks, please continue.

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Have you had an account at this bank for a period of three years or longer?

Yes 1 No 2

Are you between the ages of 21 and 34?

Yes 1 No 2

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15 My bank is expected to have operating hours that are convenient to 1 2 3 4 5 6 7 me 16 I should be able to rely on my bank to customise services according to 1 2 3 4 5 6 7 my needs 17 My bank and I should make changes to customise my relationship- 1 2 3 4 5 6 7 specific investments 18 My bank should be flexible in serving my needs 1 2 3 4 5 6 7 19 My bank should make an effort to find out what my needs are 1 2 3 4 5 6 7 20 My bank should provide me with complete information when there is a 1 2 3 4 5 6 7 new product or service 21 My bank should provide me with timely information 1 2 3 4 5 6 7 22 My bank should provide me with trustworthy information 1 2 3 4 5 6 7 23 My bank should have the ability to openly discuss solutions to my 1 2 3 4 5 6 7 problems 24 Overall my bank should have easy-to-use technology (Eg. ATMs, self- 1 2 3 4 5 6 7 service kiosks, mobile applications, internet banking) 25 Learning to use my bank’s technologies should be easy 1 2 3 4 5 6 7 26 Using my bank’s technologies should make it easier for me to do my 1 2 3 4 5 6 7 banking 27 My bank should be committed to forming relationships with me 1 2 3 4 5 6 7 28 My relationship with my bank should be very important to them 1 2 3 4 5 6 7 29 My relationship with my bank should deserve their maximum effort to 1 2 3 4 5 6 7 maintain 30 My bank should be prepared to make short-term sacrifices to maintain 1 2 3 4 5 6 7 our relationship 31 I believe my bank and I should view our relationship as a long-term 1 2 3 4 5 6 7 partnership 32 My bank should be conveniently located 1 2 3 4 5 6 7 33 My bank’s ATMs should be conveniently located 1 2 3 4 5 6 7 34 My bank’s internet platform should be easy to use 1 2 3 4 5 6 7 35 My bank’s self-service kiosks need to be conveniently located 1 2 3 4 5 6 7

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SECTION B – Satisfaction, Relationship Intention and Loyalty

Overall Satisfaction Please rate the following statements pertaining to your overall satisfaction levels with your bank, where 1 is “Strongly disagree” and 7 is “Strongly agree”. Strongly Strongly Disagree Agree 36 My feelings toward my bank are positive 1 2 3 4 5 6 7 37 I feel good about using my bank as my service provider 1 2 3 4 5 6 7 38 I feel satisfied that the results from using my bank are the best that I can 1 2 3 4 5 6 7 currently obtain 39 The extent to which I have been using my bank, has produced the best 1 2 3 4 5 6 7 possible outcome

Please rate the following statements pertaining to your willingness to form relationships and loyalty levels towards your bank, 1 is “Not likely at all” and 7 is “Very likely”. Not likely Very at all likely 40 I will continue doing business with my bank 1 2 3 4 5 6 7 41 I will recommend my bank to others as a result of my positive experience 1 2 3 4 5 6 7 42 If a competing bank offers me lower banking fees I will still make use of my 1 2 3 4 5 6 7 current bank 43 I say positive things about my bank to other people 1 2 3 4 5 6 7 44 I consider my bank to be the first choice of bank 1 2 3 4 5 6 7 45 I will remain loyal to my bank 1 2 3 4 5 6 7

SECTION C – Demographics Please mark the following statements that apply to you with an X. 1. What is your Gender? Male 1 Female 2

2. What is your highest level of education? Primary school completed 1 Matric/Grade 12 2 Diploma/Certificate 3 Bachelors degree 4 Postgraduate degree/Qualification 5

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3. What is your marital status? Single 1 Married 2 Divorced 3 Widowed 4 Living together 5 Separated 6

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Thank you for taking time to answer this questionnaire.

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ANNEXURE 3: PAIRED SAMPLE T-TEST FOR INDIVIDUAL ITEMS

The following sections will provide insight into the results for the paired sample T-tests conducted for individual items. Only items with statistical as well as practical significance will be discussed.

Expectations The following tables with discussions will provide insight into the paired samples t-test for each individual item for each CRM dimension. Respondents were requested to indicate their agreement with each item in the questionnaire pertaining to their expectations.

 Service quality

Table AN3.1: Service quality paired samples t-test Paired differences Pairs Mean Std. Dev. Mean Std. p- d- Dev. value value When my bank promises to do something 6.55 0.858 0.415 1.124 0.000 0.37 by a certain time, they should do it When I have a problem my bank must be 6.13 1.128 sympathetic When my bank promises to do something 6.55 0.848 0.230 1.121 0.000 0.20 by a certain time, they should do it 6.32 1.102 My bank should be dependable When my bank promises to do something 6.55 0.860 0.150 0.905 0.000 0.16 by a certain time, they should do it My bank should inform me exactly when 6.40 0.919 services I requested will be performed When my bank promises to do something 6.55 0.860 0.010 0.841 0.766 0.01 by a certain time, they should do it 6.54 0.854 The bank’s employees must always be willing to help me When my bank promises to do something 6.55 0.858 0.136 0.877 0.000 0.14 by a certain time, they should do it Employees of the bank should be 6.42 0.875 available to respond to my requests promptly

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When my bank promises to do something 6.55 0.859 0.045 0.884 0.220 0.05 by a certain time, they should do it I should be able to trust the employees of 6.50 0.868 my bank When my bank promises to do something 6.55 0.858 0.190 1.002 0.000 0.20 by a certain time, they should do it 6.36 0.941 My bank’s employees should be polite When my bank promises to do something 6.55 0.859 0.623 1.279 0.000 0.51 by a certain time, they should do it I expect of my bank to give me individual 5.92 1.218 attention When I have a problem my bank must be 6.13 1.131 0.187 1.319 0.001 0.16 sympathetic 6.32 1.104 My bank should be dependable When I have a problem my bank must be 6.13 1.132 0.265 1.214 0.000 0.23 sympathetic 6.40 0.927 My bank should inform me exactly when services I requested will be performed When I have a problem my bank must be 6.13 1.128 0.403 1.155 0.000 0.36 sympathetic 6.54 0.855 The bank’s employees must always be willing to help me When I have a problem my bank must be 6.13 1.132 0.291 1.196 0.000 0.25 sympathetic 6.42 0.874 Employees of the bank should be available to respond to my requests promptly When I have a problem my bank must be 6.13 1.131 0.375 1.242 0.000 0.32 sympathetic 6.50 0.867 I should be able to trust the employees of my bank When I have a problem my bank must be 6.13 1.130 0.229 1.197 0.000 0.20 sympathetic 6.36 0.941 My bank’s employees should be polite When I have a problem my bank must be 6.13 1.131 0.209 1.407 0.000 0.17 sympathetic 5.92 1.216 I expect of my bank to give me individual attention My bank should be dependable 6.32 1.107 0.080 1.141 0.093 0.07

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My bank should inform me exactly when 6.40 0.918 services I requested will be performed My bank should be dependable 6.32 1.092 0.211 1.165 0.000 0.20 The bank’s employees must always be 6.54 0.855 willing to help me My bank should be dependable 6.32 1.107 0.113 1.163 0.020 0.09 Employees of the bank should be 6.42 0.859 available to respond to my requests promptly My bank should be dependable 6.32 1.088 0.180 1.196 0.000 0.16 I should be able to trust the employees of 6.50 0.866 my bank My bank should be dependable 6.32 1.104 0.054 1.287 0.316 0.03 My bank’s employees should be polite 6.36 0.919 My bank should be dependable 6.32 1.106 0.386 1.422 0.000 0.32 I expect of my bank to give me individual 5.92 1.213 attention My bank should inform me exactly when 6.40 0.929 0.148 0.900 0.000 0.15 services I requested will be performed The bank’s employees must always be 6.54 0.857 willing to help me My bank should inform me exactly when 6.40 0.927 0.023 0.881 0.538 0.02 services I requested will be performed Employees of the bank should be 6.42 0.875 available to respond to my requests promptly My bank should inform me exactly when 6.40 0.927 0.112 0.981 0.007 0.10 services I requested will be performed I should be able to trust the employees of 6.50 0.868 my bank My bank should inform me exactly when 6.40 0.927 0.035 1.042 0.425 0.04 services I requested will be performed 6.36 0.943 My bank’s employees should be polite My bank should inform me exactly when 6.40 0.928 0.466 1.221 0.000 0.39 services I requested will be performed 5.92 1.219 I expect of my bank to give me individual attention The bank’s employees must always be 6.54 0.854 0.115 0.781 0.000 0.13 willing to help me 6.42 0.868 Employees of the bank should be

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available to respond to my requests promptly The bank’s employees must always be 6.54 0.857 0.031 0.913 0.411 0.04 willing to help me 6.50 0.868 I should be able to trust the employees of my bank The bank’s employees must always be 6.54 0.855 0.178 0.970 0.000 0.19 willing to help me 6.36 0.941 My bank’s employees should be polite The bank’s employees must always be 6.54 0.856 0.611 1.204 0.000 0.50 willing to help me 5.92 1.216 I expect of my bank to give me individual attention Employees of the bank should be 6.42 0.869 0.084 0.859 0.020 0.13 available to respond to my requests promptly 6.50 0.866 I should be able to trust the employees of my bank Employees of the bank should be 6.42 0.874 0.061 0.937 0.121 0.06 available to respond to my requests 6.36 0.943 promptly My bank’s employees should be polite Employees of the bank should be 6.42 0.875 0.498 1.174 0.000 0.41 available to respond to my requests promptly 5.92 1.217 I expect of my bank to give me individual attention I should be able to trust the employees of 6.50 0.867 0.132 0.938 0.001 0.15 my bank 6.36 0.925 My bank’s employees should be polite I should be able to trust the employees of 6.50 0.868 0.584 1.272 0.000 0.47 my bank 5.92 1.219 I expect of my bank to give me individual attention My bank’s employees should be polite 6.36 0.942 0.434 1.227 0.000 0.36 I expect of my bank to give me individual 5.92 1.216 attention * indicates significant differences between the means of the pairs of items (p-value ≤ 0.05) Table AN3.1 indicates that:

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o Respondents strongly agreed that the following item “When my bank promises to do something by a certain time, they should do it” (mean = 6.55) is significantly higher than all the other items except for “The bank’s employees must always be willing to help me” (mean = 6.54) and “I should be able to trust the employees of my bank” (mean = 6.50) o Respondents strongly agreed that the following item “The bank’s employees must always be willing to help me” (mean = 6.54) is significantly higher than all the other items except for “When my bank promises to do something by a certain time, they should do it” (mean = 6.55) and “I should be able to trust the employees of my bank” (mean = 6.50). o Respondents strongly agreed that the following item “I should be able to trust the employees of my bank” (mean = 6.50) is significantly higher than all the other items except for “When my bank promises to do something by a certain time, they should do it” (mean = 6.55) and “The bank’s employees must always be willing to help me” (mean 6.54). o Respondents strongly agreed that the following item “Employees of the bank should be available to respond to my requests promptly” (mean = 6.42) is significantly higher than “When I have a problem my bank must be sympathetic” (mean = 6.13), “My bank should be dependable” (mean = 6.32) and “I expect of my bank to give me individual attention” (mean = 5.92). o Respondents strongly agreed that the following item “My bank should inform me exactly when services I requested will be performed” (mean = 6.40) is significantly higher than “When I have a problem my bank must be sympathetic” (mean = 6.13) and “I expect of my bank to give me individual attention” (mean = 5.92) o Respondents strongly agreed that the following item “My bank’s employees should be polite” (mean = 6.36) is significantly higher than “When I have a problem my bank must be sympathetic” (mean = 6.13) and “I expect of my bank to give me individual attention” (mean = 5.92). o Respondents strongly agreed that the following item “My bank should be dependable” (mean = 6.32) is significantly higher than “When I have a problem my bank must be sympathetic” (mean = 6.13) and “I expect of my bank to give me individual attention” (mean = 5.92). o Respondents strongly agreed that the following item “When I have a problem my bank must be sympathetic” (mean = 6.13) is only significantly higher than “I expect of my bank to give me individual attention” (mean = 5.92).

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 Customisation

Table AN3.2: Customisation paired samples t-test Paired differences Pairs Mean Std. Mean Std. p- d- Dev. Dev. value value I should be able to rely on my bank to 5.85 1.242 0.057 1.168 0.241 0.04 customise services according to my needs 5.80 1.212 My bank and I should make changes to customise my relationship-specific investments I should be able to rely on my bank to 5.85 1.245 0.183 1.114 0.000 0.14 customise services according to my needs 6.03 1.157 My bank should be flexible in serving my needs I should be able to rely on my bank to 5.85 1.239 0.021 1.429 0.725 0.01 customise services according to my needs 5.83 1.277 My bank should make an effort to find out what my needs are My bank and I should make changes to 5.80 1.209 0.236 1.205 0.000 0.19 customise my relationship-specific 6.03 1.156 investments My bank should be flexible in serving my needs My bank and I should make changes to 5.80 1.211 0.038 1.365 0.501 0.02 customise my relationship-specific 5.83 1.277 investments My bank should make an effort to find out what my needs are My bank should be flexible in serving my 6.03 1.143 0.210 1.325 0.000 0.15 needs 5.83 1.280 My bank should make an effort to find out what my needs are * indicates significant differences between the means of the pairs of items (p-value ≤ 0.05)

Table AN3.2 indicates that: o Respondents strongly agreed that the following item “My bank should be flexible in serving my needs” (mean = 6.03) is significantly higher than all the other items.

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 Two-way communication

Table AN3.3: Two-way communication paired samples t-test Paired differences Pairs Mean Std. Mean Std. p- d- Dev. Dev. value value My bank should provide me with complete 6.07 1.194 0.144 1.158 0.003 0.12 information when there is a new product or 6.22 1.097 service My bank should provide me with timely information My bank should provide me with complete 6.07 1.196 0.497 1.135 0.000 0.41 information when there is a new product or 6.57 0.785 service My bank should provide me with trustworthy information My bank should provide me with complete 6.07 1.194 0.269 1.270 0.000 0.22 information when there is a new product or service 6.34 0.970 My bank should have the ability to openly discuss solutions to my problems My bank should provide me with timely 6.22 1.097 0.347 0.970 0.000 0.31 information 6.57 0.785 My bank should provide me with trustworthy information My bank should provide me with timely 6.22 1.096 0.128 1.108 0.006 0.10 information 6.34 0.970 My bank should have the ability to openly discuss solutions to my problems My bank should provide me with trustworthy 6.57 0.783 0.220 0.886 0.000 0.23 information 6.34 0.967 My bank should have the ability to openly discuss solutions to my problems * indicates significant differences between the means of the pairs of items (p-value ≤ 0.05) Table AN3.3 indicates that: o Respondents strongly agreed that the following item “My bank should provide me with trustworthy information” (mean = 6.57) is significantly higher than all the other items.

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o Respondents strongly agreed that the following item “My bank should provide me with timely information” (mean = 6.22) is significantly higher than “My bank should provide me with complete information when there is a new product or service” (mean = 6.07)

 Technology

Table AN3.4: Technology paired samples t-test Paired differences Pairs Mean Std. Mean Std. p- d- Dev. Dev. value value Overall my bank should have easy-to-use 6.54 0.927 0.107 0.859 0.003 0.10 technology (Eg. ATMs, self-service kiosks, mobile applications, internet banking) 6.44 0.961 Learning to use my bank’s technologies should be easy Overall my bank should have easy-to-use 6.54 0.916 0.103 0.892 0.006 0.09 technology (Eg. ATMs, self-service kiosks, mobile applications, internet banking) 6.45 0.922 Using my bank’s technologies should make it easier for me to do my banking Learning to use my bank’s technologies 6.44 0.958 0.016 0.765 0.623 0.01 should be easy 6.45 0.914 Using my bank’s technologies should make it easier for me to do my banking * indicates significant differences between the means of the pairs of items (p-value ≤ 0.05)

Table AN3.4 indicates that: o Respondents strongly agreed that the following item “Overall my bank should have easy- to-use technology (Eg. ATMs, self-service kiosks, mobile applications, internet banking)” (mean = 6.54) is significantly higher than all the other items.

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 Commitment

Table AN3.5: Commitment paired samples t-test Paired differences Pairs Mean Std. Mean Std. p- d- Dev. Dev. value value My bank should be committed to forming 6.04 1.176 0.179 0.930 0.000 0.15 relationships with me 6.22 1.093 My relationship with my bank should be very important to them My bank should be committed to forming 6.04 1.175 0.090 1.136 0.057 0.07 relationships with me 6.13 1.061 My relationship with my bank should deserve their maximum effort to maintain My bank should be committed to forming 6.04 1.175 0.298 1.447 0.000 0.22 relationships with me 5.74 1.352 My bank should be prepared to make short- term sacrifices to maintain our relationship My bank should be committed to forming 6.04 1.175 0.109 1.320 0.047 0.08 relationships with me 5.93 1.226 I believe my bank and I should view our relationship as a long-term partnership My relationship with my bank should be very 6.22 1.090 0.090 0.941 0.022 0.08 important to them 6.13 1.060 My relationship with my bank should deserve their maximum effort to maintain My relationship with my bank should be very 6.22 1.090 0.478 1.305 0.000 0.35 important to them 5.74 1.352 My bank should be prepared to make short- term sacrifices to maintain our relationship My relationship with my bank should be very 6.22 1.090 0.290 1.365 0.000 0.23 important to them 5.93 1.224 I believe my bank and I should view our relationship as a long-term partnership My relationship with my bank should deserve 6.13 1.060 0.384 1.281 0.000 0.28 their maximum effort to maintain 5.74 1.351 My bank should be prepared to make short- term sacrifices to maintain our relationship

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My relationship with my bank should deserve 6.13 1.060 0.193 1.365 0.001 0.16 their maximum effort to maintain 5.93 1.224 I believe my bank and I should view our relationship as a long-term partnership My bank should be prepared to make short- 5.74 1.351 0.191 1.616 0.005 0.14 term sacrifices to maintain our relationship 5.93 1.224 I believe my bank and I should view our relationship as a long-term partnership * indicates significant differences between the means of the pairs of items (p-value ≤ 0.05)

Table AN3.5 indicates that: o Respondents strongly agreed that the following item “My relationship with my bank should be very important to them” (mean = 6.22) is significantly higher than all the other items. o Respondents strongly agreed that the following item “My relationship with my bank should deserve their maximum effort to maintain” (mean = 6.13) is significantly higher than all the other items except for “My relationship with my bank should be very important to them” (mean = 6.22)” o Respondents strongly agreed that the following item “My relationship with my bank should deserve their maximum effort to maintain” (mean = 6.13) is significantly higher than “I believe my bank and I should view our relationship as a long-term partnership” (mean = 5.93) and “My bank should be prepared to make short-term sacrifices to maintain our relationship” (mean = 5.74). o Respondents strongly agreed that the following item “My bank should be committed to forming relationships with me” (mean = 6.04) is significantly higher than “I believe my bank and I should view our relationship as a long-term partnership” (mean = 5.93) and “My bank should be prepared to make short-term sacrifices to maintain our relationship” (mean = 5.74). o Respondents strongly agreed that the following item “I believe my bank and I should view our relationship as a long-term partnership” (mean = 5.93) is only significantly higher than “My bank should be prepared to make short-term sacrifices to maintain our relationship” (mean = 5.74).

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 Convenience

Table AN3.6: Convenience paired samples t-test Paired differences Pairs Mean Std. Dev. Mean Std. p- d- Dev. value value My bank should be conveniently located 6.43 0.899 0.157 0.697 0.000 0.17 My bank’s ATMs should be conveniently 6.59 0.796 located My bank should be conveniently located 6.43 0.911 0.047 0.954 0.240 0.04

My bank’s internet platform should be 6.47 0.930 easy to use My bank should be conveniently located 6.43 0.910 0.105 0.983 0.010 0.11

My bank’s self-service kiosks need to be 6.32 1.000 conveniently located My bank’s ATMs should be conveniently 6.59 0.790 0.113 0.870 0.002 0.13 located 6.47 0.913 My bank’s internet platform should be easy to use My bank’s ATMs should be conveniently 6.59 0.796 0.265 0.942 0.000 0.27 located 6.32 0.988 My bank’s self-service kiosks need to be conveniently located My bank’s internet platform should be 6.47 0.930 0.150 0.948 0.000 0.14 easy to use 6.32 1.002 My bank’s self-service kiosks need to be conveniently located * indicates significant differences between the means of the pairs of items (p-value ≤ 0.05) Table AN3.6 indicates that: o Respondents strongly agreed that the following item “My bank’s ATMs should be conveniently located” (mean = 6.59) is significantly higher than all the other items. o Respondents strongly agreed that the following item “My bank’s internet platform should be easy to use” (mean = 6.47) is significantly higher than all the other items except for “My bank’s ATMs should be conveniently located” (mean = 6.59). o Respondents strongly agreed that the following item “My bank should be conveniently located” (mean = 6.43) is only significantly higher than “My bank’s self-service kiosks need to be conveniently located” (mean = 6.32)

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Satisfaction

Table AN3.7: Satisfaction paired samples t-test Paired differences Pairs Mean Std. Mean Std. p- d- Dev. Dev. value value My feelings toward my bank are positive 5.48 1.410 0.062 0.801 0.063 0.04 I feel good about using my bank as my 5.54 1.406 service provider

My feelings toward my bank are positive 5.48 1.410 0.229 1.081 0.000 0.15 I feel satisfied that the results from using my 5.25 1.501 bank are the best that I can currently obtain My feelings toward my bank are positive 5.48 1.410 0.187 1.057 0.000 0.12 The extent to which I have been using my 5.30 1.456 bank, has produced the best possible outcome I feel good about using my bank as my 5.54 1.407 0.285 0.890 0.000 0.19 service provider 5.25 1.502 I feel satisfied that the results from using my bank are the best that I can currently obtain I feel good about using my bank as my 5.54 1.408 0.244 0.955 0.000 0.16 service provider 5.30 1.456 The extent to which I have been using my bank, has produced the best possible outcome I feel satisfied that the results from using my 5.25 1.499 0.041 0.883 0.259 0.03 bank are the best that I can currently obtain The extent to which I have been using my 5.30 1.456 bank, has produced the best possible outcome * indicates significant differences between the means of the pairs of items (p-value ≤ 0.05)

Table AN3.7 indicates that: o Respondents strongly agreed that the following item “I feel good about using my bank as my service provider” (mean = 5.54) is significantly higher than all the other items except for “My feelings toward my bank are positive” (mean = 5.48).

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o Respondents strongly agreed that the following item “My feelings toward my bank are positive” (mean = 5.48) is significantly higher than all the other items except for “I feel good about using my bank as my service provider” (mean = 5.54).

Relationship intention

Table AN3.8: Relationship intention paired samples t-test Paired differences Pairs Mean Std. Mean Std. p- d- Dev. Dev. value value I will continue doing business with my bank 5.55 1.468 0.259 0.951 0.000 0.18 I will recommend my bank to others as a 5.25 1.621 result of my positive experience I will continue doing business with my bank 5.55 1.475 1.066 1.852 0.000 0.53 If a competing bank offers me lower banking 4.48 2.017 fees I will still make use of my current bank I will recommend my bank to others as a 5.25 1.622 0.773 1.849 0.000 0.38 result of my positive experience 4.48 2.018 If a competing bank offers me lower banking fees I will still make use of my current bank * indicates significant differences between the means of the pairs of items (p-value ≤ 0.05) Table AN3.8 indicates that: o Respondents indicated their highest level likelihood for the following item “I will continue doing business with my bank” (mean = 5.55) as being significantly higher than all the other items. o Respondents indicated their highest level likelihood for the following item “I will recommend my bank to others as a result of my positive experience” (mean = 5.25) as being only significantly higher than “If a competing bank offers me lower banking fees I will still make use of my current bank” (mean = 4.48).

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Loyalty

Table AN3.9: Loyalty paired samples t-test Paired differences Pairs Mean Std. Dev. Mean Std. Dev. p- d- value value I say positive things about my bank to 5.14 1.678 0.009 1.119 0.853 0.00 other people 5.15 1.767 I consider my bank to be the first choice of bank I say positive things about my bank to 5.14 1.675 0.033 1.161 0.497 0.01 other people 5.11 1.711 I will remain loyal to my bank I consider my bank to be the first 5.15 1.767 0.036 1.017 0.391 0.02 choice of bank 5.11 1.711 I will remain loyal to my bank * indicates significant differences between the means of the pairs of items (p-value ≤ 0.05) Table AN3.9 indicates that: o No significant differences exist.

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