Bank choice behavior, customer participation: a study in the retail banking sector

search, experience and credence influence customer loyalty; b and through which mechanism customer participation influence the relationships between attributes of bank choice behavior an

ACKNOWLEDGEMENT

At the first, I would like to thank all those people who made this thesis possible and an unforgettable experience for my studying Foremost, I would like to express my sincere gratitude to my supervisor, Dr Ngo Viet Liem, for his intensive support, valuable suggestions, instructions and encouragement during the time of doing my research His guidance helped me

in all the time of research and writing of this thesis

Besides my supervisor, I would like to thank the rest of my thesis committee: Prof Nguyen Dong Phong, Prof Nguyen Dinh Tho, and Dr Tran Ha Minh Quan … for their encouragement, insightful comments, and hard questions

I thank my classmates in ISB MBUS 2011 (specially members in my group: Ms Hanh,

Ms Hang, Mr Chuong and Ms Hien) and my colleagues at Shinhan Bank for their encouraging and supporting to me complete this thesis Besides that, my sincere thanks are given to all of my teachers at International Business School – University of Economics Ho Chi Minh City for their teaching and guidance during my MBUS course

Last but not the least, I would like to thank my family I must express my gratitude to Phan Thi Hoi, my older sister, for her continued support and encouragement I also wish thank all those people who spent through their time and generous support made this thesis project

Ho Chi Minh City, October, 2014

PHAN DANH HOANG

ABSTRACT

This study integrates bank choice behavior and customer participation into a theoretical framework to explain variation in customer loyalty Specifically, the purpose of this study is twofold: (a) to examine the extent to which attributes of bank choice behavior (e.g search, experience and credence) influence customer loyalty; (b) and through which mechanism customer participation influence the relationships between attributes of bank choice behavior and customer loyalty The empirical setting of this study is the retail banking sector A survey

of 466 customers using personal loan services in some domestic banks is conducted

The findings indicate that bank choice behavior and customer participation play important role in predicting the loyal of customer who use personal loan services The results also support that customer participation is biggest impact to customer loyalty, followed by credence attributes and experience attributes Whereby, the banking managers need to consider creating all of experience attributes, credence attributes and customer participation to make their customer loyalty to the bank The research results are limited in the power of measurement scale, sampling approach as well as the fitness of the research model and data It results in the valuable directions for further researches in future

Keywords

Retail banking, personal loan, bank choice behavior, customer participation, customer loyalty

TABLE OF CONTENTS

ACKNOWLEDGEMENT 1

ABSTRACT 2

TABLE OF CONTENTS 3

CHAPTER 1 - INTRODUCTION 7

1.1 Background to the research 7

1.2 Statement of the problem 8

1.3 Research questions 8

1.4 Significance of the Study 9

1.5 Research scope and delimitation 9

1.6 Organization of the thesis 10

CHAPTER 2 11

THEORETICAL MODEL AND HYPOTHESES 11

2.1 Bank choice behavior 11

2.2 Customer participation: 12

2.3 Customer Loyalty 15

2.4 Research model and hypotheses development 16

Building upon prior research, Figure 2.2 integrates the focal constructs of the thesis with hypothesized relationships 16

2.4.1 Bank choice behavior and customer loyalty 17

2.4.2 Bank choice behavior and customer participation 18

2.4.3 Customer participation and customer loyalty 20

CHAPTER 3 22

RESEARCH METHODS 22

3.1 Research design 22

3.2 Development of questionnaire 23

3.2.1 Measurement scales 23

3.2.1.1 Measure of search, experience and credence 23

3.2.1.2 Measure of customer participation 25

3.2.1.3 Measure of customer loyalty 26

3.2.2 Draft questionnaire 26

3.3 Pilot study 27

3.4 Sample method 28

3.5 Questionnaire administration 30

3.6 Data analysis methods 31

CHAPTER 4 32

DATA ANALYSIS AND FINDINGS 32

4.1 Descriptive analysis 32

4.2 Reliability analysis 33

4.3 Exploratory Factor Analysis (EFA) 36

4.4 Confirmatory Factor Analysis 39

4.4.1 Composite reliability and variance extracted 41

4.4.2 Unidimensional analysis 42

4.4.3 Convergent validity analysis 42

4.4.4 Discriminant validity analysis 43

4.5 Research model test 43

4.5.1 Theoretical model test by using SEM approach 43

4.5.2 Theoretical model estimation by BOOTSTRAP 46

CHAPTER 5 48

DISCUSSION, IMPLICATIONS AND LIMITATION 48

5.1 Discussion 48

5.2 Implications of the research 49

5.3 Limitations and directions for further research 51

REFERENCES 53

APPENDICES 61

APPENDICES APPENDIX 1 - Questionnaire 61 

APPENDIX 2 - The results of population census 2009 in Ho Chi Minh City 67 

APPENDIX 3 - The result of EFA analysis – Eigenvalues for variables (the first test) 67 

APPENDIX 4 - CFA test result 72 

LIST OF FIGURES Figure 2.1 - Totally disaggregated second-order model of bank choice behavior 12

Figure 2.2 - The proposed research model with hypotheses 21

Figure 3.1 - Research process 23

Figure 4.1 - CFA result in the second time (Standardized estimates) 40

Figure 4.2 - Result of hypothesis test in the second time 45

Figure 4.3 - The result of CFA in the first time (Standardized) 72

LIST OF TABLES Table 3.1 - Measurement scales of bank choice behavior 24

Table 3.2 - Measurement scales of customer participation 25

Table 3.3 - Measurement scales of customer loyalty 26

Table 3.4 - calculating sample with quota sampling method 29

Table 4.1 - Descriptive statistic of respondent’s characteristics 32

Table 4.2 - Descriptive statistic of respondent’s characteristics 33

Table 4.3 - Cronbach’s alpha reliability coefficient 34

Table 4.4 - Cronbach’s Alpha coefficients for each measurement scale 34

Table 4.5 - The EFA analysis result 37

Table 4.6 - Cronbach’ Alpha results after excluding unsatisfactory items 38

Table 4.7 - Modification indices 39

Table 4.9 - Discriminant validity of concept 43

Table 4.10 - Regression Weights 44

Table 4.11 - Regression Weights: (Group number 1 - Default model) 45

Table 4.12 - The results for Bootstrap estimation 47

CHAPTER 1 - INTRODUCTION 1.1 Background to the research

The Vietnamese banking sector is transforming at a rapid pace and is expected to show a higher growth rate than most of its counterparts in neighboring Asian countries in the upcoming years (Ho and Baxter, 2011) This tendency has been mainly shaped by state-headed economic reconstructions since the end of the 1980s and the creation of several State-Owned Commercial Banks (SOCB) It has accelerated recently with the country’s accession to the World Trade Organization in 2007, heading to a dynamic liberalization of the banking sector These reforms and the tremendous economic development of the country during the last two decades (Breu and Dobbs, 2012) are making important chances for both national and foreign banks operating in Vietnam, mainly in retail banking sector

Since early 2014, although interest rates for enterprises were fall down in the lowest level since the stimulus package in 2009 of Government, but the credit growth is still difficult

to increase Many enterprises still hesitate to get loans So many banks shift their emphasis to personal loans services to grow credit outstanding balance In particular, personal loan services attracted attention from many individual customers by simple and convenient procedures The success of retail banking sector depends on the type of relationship maintained with its customer and an understanding of customer needs In the commercial banking industry there is

a growing recognition that individual customers not only represent a viable market segment but that their needs are different and frequently changed

One strategic tool that banks can use to attract new customers, retain current customers and develop strong relationships is the customer loyalty Customer loyalty is one of key concerns for researchers and marketers who are interested in understanding its predictors and causal structure Previous research on this concept also showed that customer participation leading to loyalty (Auh, Bell, McLeod& Shih, 2007; Ngo &O'Cass, 2013) It gives the notion that customer participation is very important concept for marketers and managers

Besides the customer loyalty, bank choice behavior attributes (search, experience, credence) also attract many of researchers (Mitra, Reiss, and Capella, 1999; Babakus, Eroglu&Yavas (2004) However, few empirical studies investigate the relationship between bank choice behavior contributes, customer participation and customer loyalty This study therefore develops a model examining the role of bank choice behavior, customer participation

on customer loyalty Empirically, it tests the impact of bank choice behavior attributes on customer participation Then, it investigates the impact of bank choice behavior contributes and customer participation on customer loyalty Following this introduction, the next section presents statement of the problem

1.2 Statement of the problem

The demand for personal loan products has been increasing dramatically However, banks still do not have an optimal recipe for attracting new customers, retaining and selling more services to existing customers A study on the effects of bank choice behavior and customer participation on customer loyalty will allow bank managers to have an appropriate marketing strategy to attract new customers It can help bank managers give out methods which help to increases the level of customer loyalty, thereby maintaining the existing customers Through studying the relationship between customer participation and customer loyalty, it also allows bank managers find out ways to strengthen the participation of the customer in the transaction process through which banks can increase the level of customer loyalty

1.3 Research questions

The purpose of this research is to empirically investigate the impact of bank choice behavior and customer participation on customer loyalty The empirical setting in this particular research is the retail banking sector in the transitional economy in Vietnam Contrary

to the past, many customers are trying to use personal banking services and have a lot of products to choose Given this situation, a study of bank choice behavior, customer

participation and customer loyalty would be very useful This study attempts to answer the following research questions

 To what extent, do attributes of bank choice behavior (e.g search, experience and credence) and customer participation influence customer loyalty?

 Between bank choice behavior and customer participation, which factor will most influence to customer loyalty?

1.4 Significance of the Study

This study has important implications for both practitioners (leaders of commercial banks, marketing managers) and academic (researchers, students of the business administration department) as follow:

 The findings of this study contribute to research on bank choice behavior and customer participation by investigating the contribution of both bank choice behavior and customer participation to enhancing customer loyalty Based on it, managers of commercial banks will make an effective strategy to enhance customer loyalty and improve operational efficiency

 Marketing managers will consider the factors of bank choice behavior which affect customer loyalty in personal loan market sector to set up an appropriate communicate strategy The results of this study also are a basis for researchers, students for developing further research to practical applications

1.5 Research scope and delimitation

This study is conducted in Ho Chi Minh City, one of the biggest economic centers of Viet Nam Respondents are customers who are using personal loan services at banks Due to limited time and cost, the research surveyed about 500 customers of large domestic commercial banks in HCMC The result of research in this city, in some level can represent for Viet Nam in general and can be use as reference for further purposes

The research will assess the effect of bank choice behavior attributes and customer participation to customer loyalty In this, the quota sampling method is used to collect research data It is a type of the non-probability sampling Althought selected-sample is not generalized

to population, if we choose the right controlled characteristic (distinguishing attributes of studied objects), in theoretically, sample cannot represent for population but in practice it may represent for population

1.6 Organization of the thesis

This thesis is organized in five chapters The first chapter is the introduction that describes the overview of research background, research problem, and objective, followed by the scope of research, implications, and structure of thesis

Chapter 2 reviews previous research on customer loyalty and customer participation Specifically, the chapter reviews the mediating role of customer participation model and theory

of bank choice behavior and, how they are used in various contexts This chapter concentrates

on explaining each variable in the model, and reasons for choosing them to be included in the research model

Chapter 3 introduces research methodology used to validate the research model in previous session It presents the research design, development of survey questionnaire, qualitative study, and main survey This chapter also presents how to collect data and analyze the data collected to test the research hypotheses proposed in chapter 2

Chapter 4 analyses data as well as discusses the result finding in connection with research model This chapter explains the empirical part of the study This part discusses the analyses of the data received, psychometric properties of focal constructs, and hypothesis testing

The last chapter, chapter 5 discusses implications and research limitations Finally, this thesis makes suggestions for further research on the topic area

References and appendixes are included in the end of thesis

CHAPTER 2 THEORETICAL MODEL AND HYPOTHESES

This chapter provides a theoretical background about bank choice behaviour, customer participation, customer loyalty, upon which a conceptual research model and hypotheses are constructed

2.1 Bank choice behavior

The underlying theory of the bank choice behavior model was first developed within the economics of information literature (Darby and Karni, 1973; Nelson, 1970) and later refined within the services context (Bloom and Pailin, 1995; Lynch and Schuler, 1990) Three sets of attributes are hypothesized to be manifestations of a consumer’s choice decisions: search, experience and credence (Mitra et al., 1999) as shown in Figure 1 Search attributes are those that are accurately evaluated before making a choice decision (Srinivasan and Till, 2002) According to Babakus at al., (2004), search, experience and credence can defined as follows:

 Search attributes – which may be accurately evaluated before making a choice Within the banking context, these include interest rates on deposits or loans, overdraft privileges, fees and charges, working hours and new bank services

 Experience attributes – which may be accurately assessed only when the service has been purchased and used Within the banking context, these include the helpfulness of tellers, the supply of services with a timely manner, the attentiveness of bank employees, their temperament to pay attention to the client, their friendliness and expertise, and the speed of decision made by the bank authorized person

 Credence attributes – which can or might not be evaluated even when a sale is created, simply because the client might lack the technical experience needed to create the assessment or there may be without delay accessible indicators of the attributes Within the banking context, credence attributes consist keeping the client’s banking information

confidential, the integrity of the bank, and adoption of bank in receiving of the most recent technology, its management and its overall ability inside the business of banking

Figure 2.1 - Totally disaggregated second-order model of bank choice behavior

2.2 Customer participation:

Many different theories focus on how to increase customer actively engaged in services production and distribution (Auh at al., 2007; Yi at al., 2011) The study of Firat at al., (1995) pointed out that customer participation in the company can contribute to create new services in accordance with their own needs In addition, the involvement of customers allows the company to create long-term relationships between companies and customers (Bendapudi & Leone, 2003; Payne at al., 2009) In fact, companies tend to focus on encouraging customers to take part in spreading positive word of mouth The reason is when companies invite customers

to share their views with managers; this activity will make them become brand evangelists

Most managers grasp that paying attention to customers makes sensible business sense Banks have abundant to achieve from actively seeking and inspiring client participation, that banks have a tendency to outline as obtaining customers to supply constructive suggestions and share their concepts on the way to form product and repair offerings Nonetheless whereas the thought that soliciting and listening rigorously to customers is recent, several corporations solely pay lip service to it The return on customer participation is higher than several managers suppose

Dabholkar (1990) considered customer participation as involved level of customers in the production and supply of services Integrating customers into the innovation process of companies will help companies improve and enhance the quality of service and success in the market Dagger & Sweeney (2007) also claimed that improving service quality in the service industry is the top priority because high quality services not only increases the positive intention of customers behavior but also contribute to improved market share, revenue and greater profitability

Lengnick-Hall et al., (2000) suggested that customer participation is the involving of customer as an active participant in the work of the organization This view has two main benefits First, the integrated clients in customer engagement can help organizations reduce costs (e.g after customers use banking services, they discovered the irrational in the process transactions, they raised these issues with bank managers, to collect opinions and adjustment processes transactions of banks will help to reduce transaction errors and transaction time, this obviously helps banks to cut staff costs, reduce transaction time, increased customer satisfaction) Besides that, customer participation can help reduce the price of products and services (e.g cost and price are both normal covariates, the customer participation help banks cut costs as well means helping organizations improve profitability, and the considering service discounts will be considered in order to increase competitiveness, attract customers of the bank) In line with this view, Mills et al., (1983) also said that customer participation lead to increase productivity for organizations Second, customer participation facilitates the bank to

customize its offerings to customers’ desires The private interaction between the consumer and the bank consequently represents a vital part of a service delivery method within which the client has direct input into the assembly of the ultimate service High-contact services, like money, legal, and medical services, are outlined by a high degree of coupling (i.e., continuous, immediate impact of contact), interdependence (i.e., service quality is conditional inputs from every party), and knowledge richness (i.e the worth of knowledge passed between parties) (Kellogg and Chase, 1995) The advantages of client participation do not seem to be restricted entirely to high-involvement services though; even in low- and moderate-involvement services, clients could notice customer participation enticing because they fancy magnified perceived management over the service delivery method (Bateson, 1985) and extra opportunities to create selections that offers them higher levels of customization (Schneider and Bowen, 1995).

Bendapudi& Leone (2003) and Ravald&Gronroos (1996) said that customer participation represent for things which the company could do with clients to co-create value Customers can search and see the benefits of it to make their impact on different parts of the worked system to build shopping and consumer experience of his own personal (Prahalad&Ramaswamy, 2004) Besides, customer participation not only helps the company consume products or services but also help companies change and improve products/services quality Therefore, customers are increasingly encouraged to actively cooperate with the company to create better value on the basis of mutual benefit

According to Krajewski at al., (2010), the involvement of the customer is not always the best option, but is accompanied by the disadvantages Allowing customers play an active role

in the service process may create trouble and makes the process less efficient The management

of time and volume of customer needs can be difficult and challenging Measuring service quality also becomes more difficult Costs for businesses could rise due to the layout of skilled personnel to better interact with customers However, the benefits of active participation in the process can increase customer value for themselves Some clients seek active participation and control services process, especially if this participation saving both time and cost More client

involvement will mean higher quality, quicker delivery, bigger flexibility, and even lower price Self-service is that the selection for several retailers, like supermarkets, gas stations and bank services

Encouraging customer participation will make the most customer competencies throughout the course of their innovation activities (Blazevic&Lievens, 2008) To inspire customers’ participation, enterprises may set-up and on-going relationship and work closely with customers to confirm meet customer needs During this sense, customer is thought as active partners within the creation of innovative offerings Consequently, to amass superior service quality for the client, corporations ought to be ready to develop new strategies (e.g social control and promoting innovations) to encourage customers to participate, in addition as strategies to success monitor and manage the process along the way

2.3 Customer Loyalty

Customer loyalty refers to the trend to hold favorable attitudes to the services / products and undertaking to acquisition and / or use of services / products (Bowen and Chen, 2001) Marketing researchers agree that in most of situation customer loyalty for a brand is more important than customer satisfaction (Cooil et al, 2007; Pleshco and Baqer, 2008) In the other hand, loyalty can make customers easy to forgive in a disappointing situation associated with a certain brand or to a store (Shankar et al., 2003)

In the opinion of Bendapudi & Berry (1997), even though the research literature of customer loyalty is done with the different aspects, the two most popular views are the behavior and attitudes In particular, the first approach of loyal is to meaning as repeat purchase behavior However, there is also the idea that customers can eliminate repeat purchase behavior out of their habit because a number of barriers prevent them from changing suppliers or because of a lack of attractive options or services instead In this respect, customers can maintain loyalty as obligations, developed a type of faked loyalty without any good feelings

with their suppliers The second approach is the considering of loyalty as a psychological state (emotional and or cognitive) that customers can achieve as a result of supplier’s relational strategies Customers may voluntarily maintain relationships based on the benefits they receive

in this relationship (Caruana, 2004) This approach supports the view that the foundation of loyalty is actually a positive attitude to the supplier and ensures repeat purchasing behavior in the future With the benefits that customers receive loyalty of customers to suppliers is derived from themselves to maintain this relationship (Oliver, 1999)

In order to generalize the two approaches as Gremler at al., (2001) suggested, this study considers loyalty to a particular supplier as a multidimensional concept In which, loyalty refers

to the extent to which customers expressed their intention to purchase again in the future (intention future behavioural), showing a positive attitude to suppliers (affective loyalty) and see vendors as an unique option for the needs arising in the future (cognitive loyalty) Derived from two perspectives on loyalty, managers were given two main strategies to enhance customer loyalty The first strategy is to satisfy customers and provide them with the products and services which make they feel satisfied so that their desire to maintain this satisfaction The second strategy is to establish barriers to prevent conversion process of customer to a new provider (Balabanis, Reynolds, and Simintiras, 2006) If the customer is aware that the provision of products and services on the market are homogeneous, there is little difference, they will not be combined with any benefits to changing providers The result is the tendency

to abandon the relationship will be reduce and increase the level of loyalty (Balabanis et al., 2006)

2.4 Research model and hypotheses development

Building upon prior research, Figure 2.2 integrates the focal constructs of the thesis with hypothesized relationships

2.4.1 Bank choice behavior and customer loyalty

Nelson (1970, 1974) and Darby and Karni (1973) extended the concept of search, experience and belief in the economic information theory of Stigler (1961) by questioning how the various types of attributes interact with the customer search and experience Accordingly, there is a distinction between search and experience attributes Search attributes is something that customers can confirm before purchase via directly check or based on the source of available information While experience attributes are things that customer can only get after using the product (Ford et al., 1990) On the other hand, according to Darby and Karni (1973), credence attributes are things that very difficult for customer to verify even after using A product or service can have one, two or three types of attributes For example, in the case of personal loan services: search attribute is interest rates, experience attribute is a professional in service, and credence attribute will be integrity of staff Three types of properties are very useful in checking customer disbelief (Ford et al., 1990, Smith, 1990), marketing information contents (Norton and Norton, 1988), trust evaluation and confidence (Wright and Lynch, 1995), and the important role of price in making choice services (Ostrom and Iacobucci, 1995)

Customer loyalty usually is created after customers feel satisfied with the services that banks provide Therefore, customer loyalty will be not established before they experience the product In the case of search attributes (such as interest rate, overdraft privileges), consumers are able to inspect the services and draw inferences about the attribute before actually purchasing the service, and consumers are least skeptical of search claims (Ford et al., 1990) Hoch and Ha (1986) showed that search attributes are relatively unambiguous in the theory of information diagnosticity and ambiguity Therefore customers are most likely to review their cognitive framework that services quality of this bank is better or worse than that bank to generic products while evaluating search attributes Therefore, this study hypothesizes that the change of search attributes effect on customer loyalty

Hypothesis 1: There is a positive effect of search attributes on customer loyalty

As discussed above, in opposition to aspects of search attributes, experience and credence attributes are not easily confirmed before customers use a product or service that (Darby and Karni, 1973; Nelson, 1974) Also in the opinion of Kirmani and Wright (1989); Shapiro (1983); Wernerfelt (1988), customers must use a specific product / service to assess attributes and draw their own experience If customers want to evaluate the product before use, they will have to rely on other features to draw conclusions about the quality of products/services Another problem is that customers can not clearly evaluate credence attribute even after using products/services So, in the absence of any other indication, customers tend to evaluate credence attributes based on the customer perception Before using the service, customers often evaluate it based primarily on their basis perception of the service However, after the customer has got the opportunity to try the service, they have extra information to associate with their inference perception of its quality If a same services and differing only in name of bank, trial would be expected to reduce the attitudinal loyalty for the service of bank have a low quality and increase the attitudinal loyalty for the service of bank have higher quality Therefore, the study hypothesizes that experience and credence attributes will have a positive effect on customer loyalty

Hypothesis 2: There is a positive effect of experience attributes on customer loyalty Hypothesis 3: There is a positive effect of credence attributes on customer loyalty

2.4.2 Bank choice behavior and customer participation

Experience represents a customer’s accrued knowledge about how a service should perform and general understanding of the average value of similar services in a different provider Experience likely increases client involvement of the customer for several reasons First, as customers gain more experience in the type of product, they can better evaluate where they would make a contribution Moorthy et al (1997) similarly argue that as customers gain experience, they are better able to evaluate the various attributes of different service offerings

In other words, customers who have a high level of experience are better equipped to make

valuable contributions to the production of a service and hence more likely to do so Second, inexperienced customers typically perceive higher decision-making risk (Heilman et al 2000) These customers are less likely to involve themselves because they fear producing a suboptimal outcome Third, experienced customers likely have a greater need for control in the service delivery process (O’Connor and Siomkos, 1994) Therefore, the need to control or influence the outcome of a service will increase expert customers’ likelihood of getting involved in production

In the chain of bank choice behavior, customer joins all of the process from search, experience, to credence The interactive process creates the communication between client and bank staff Sharma and Patterson’s (1999) define communication as the formal and informal sharing of meaningful and timely information between a client and advisor in an empathetic manner The content of communication, in the financial context of our study, focuses on encourage clients participate in the loan process, interacting with bank staff to search services information, response their understanding about the products and the responding of bank staff

to client for requesting information Communication flow is central to the establishment of strong relationships; it builds trust by resolving clients’ queries and concerns and managing their expectations (Sharma and Patterson, 1999) Accordingly, author expects bank choice behavior chain between the advisor and the client will increase the incidence of customer participation because of their greater willingness to share (potentially sensitive) information Accordingly, the study hypothesizes:

Hypothesis 4: There is a positive effect of search attributes on customer participation Hypothesis 5: There is a positive effect of experience attributes on customer

participation

Hypothesis 6: There is a positive effect of credence attributes on customer participation

2.4.3 Customer participation and customer loyalty

Customer participation is defined as constructive customer participation in the service creation and delivery process and clarify that it requires meaningful, cooperative contributions

to the service process In the delivery of financial services, such contributions might involve client preparation prior to meetings with advisors, client provision of input to decision making processes, and timely and accurate responses to advisor requests for information

Customer participation likely yields several benefits for customers, including lower prices, more opportunities to make purchasing, and larger discretion about the configuration of the ultimate product Moreover, clients likely experience shorter waiting times and enjoy a greater likelihood of customization The relationship between customer participation and perceived value, however, may not be unequivocally positive (Lengnick-Hall, 1996) Enterprises have less control over the training of customers to participate effectively in the production process than they do with service employees In turn, customer involvement may raise the overall level of uncertainty in the transaction and thereby affect outputs Furthermore, customers may dislike the level of effort required to co produce a service and therefore abdicate their role in the service process (Solomon, 1986) On balance, however, customers likely consider being involved in a service creation process as a source of value, especially in the emerging era of connected, informed, empowered, active consumers (Prahalad and Ramaswamy, 2004) Dellande et al (2004) recently demonstrated that customer compliance-one facet of customer participation-relates significantly to customer satisfaction, and efforts by organizations to involve clients in customer participation lead to increased mutual understanding (Mohr and Bitner 1991) Such mutual understanding results in positive emotional responses to the service (Price et al., 1995) Moreover, according to the view that satisfaction results from both cognitive and affective assessments of service experiences (Westbrook, 1987), repeated positive emotional experiences ultimately contribute to the sort of customer satisfaction that underpins customers’ decisions to be loyal to an organization (Lam

et al., 2004) Therefore, the study incorporate measures of attitudinal and behavioral loyalty

(Dick and Basu, 1994; Wallace et al., 2004) Attitudinal loyalty refers to a measure of clients’ intentions to stay with and level of commitment to the organization, whereas behavioral loyalty, in the financial services context, is an objective measure of the amount of brokerage the client paid to the firm in the year following the administration of the questionnaire Taking these measures of loyalty into consideration and on the idea of the preceding arguments, the study hypothesizes:

Hypothesis 7: There is a positive effect of customer participation on customer loyalty

Figure 2.2 - The proposed research model with hypotheses

CHAPTER 3 RESEARCH METHODS

This chapter discusses research methodology and methods for data collection and data analyses It presents the research design, development of survey questionnaires, qualitative study, and main survey This chapter also presents the data collection procedure and data analysis methods for testing the research hypotheses proposed in chapter 2

3.1 Research design

The research design of this study includes two phases The first phase, qualitative research identifies the models, factors, suitable measurement variables for research in HCMC Through the previous relevant researches, the questionnaire was built then running the pilot test for checking the efficiency and the meaning of the questions The pilot test was purposed to explore and define the relevant items and building a completed questionnaire The second phase, quantitative survey was the main approach of this study The goal is to examine the effect of bank choice behavior and customer participation on customer loyalty in the personal loan services of retail banking sector

Research process includes the steps as illustrated in Figure 3 (Steiger, 1990; Albright, 2006; Schumacker at all, 2006)

Figure 3.1 - Research process 3.2 Development of questionnaire

3.2.1 Measurement scales

The measurement scales used in this study is multi-item five point Likert scales, which were well-established in the extant literature

3.2.1.1 Measure of search, experience and credence

Bank choice behavior consists of twenty-one items capturing three components (eight items for search, seven items for experience and six items for credence) These items refer to the application of knowledge in bank choice behavior generating from the literature (Babakus

at al., 2004; Devlin, 2002) This construct will be measured on a five-point Likert scale with

scale poles ranging from strong disagree to strong agree

Table 3.1 - Measurement scales of bank choice behavior

Construct Coding of

Search

attributes

SA1 1 I always search interest rates on loans information of

banks before I make decision of using services Interest rate SA2 2 I usually ask banks what is the type of collateral the

bank will accept to secure my loan? Collateral requirements SA3 3 I usually ask banks whether they willing offer me an

overdraft privileges account (unsecured) Overdraft privileges SA4 4 I usually compare fee structure between banks when I

SA5 5 I always consider bank transaction hour whether it

fixes with my times to do transaction at banks Banking hour SA6 6 I usually make a research if banks have got new

services which have advantages for me New bank services

SA7

7 I consider whether branch location near my house or

SA8

8 I consider the bank that I use personal loan services is

Experience

attributes

EA1 1 Bank X’s staffs serve me with friendliness and

EA2 2 Bank X provides services in a timely manner Timely manner of service

provision EA3 3 Bank X’s staffsare always willing to listen to me Willingness to listen

EA4 4 Bank X’s staffs present their professional in all

EA5 5 Bank X gives me a specific period for my application approval period for application

EA6 6 Bank X serves me quickly and efficiently Speed of dicision

EA7 7 Bank X does not require me so much un-need

CRE2 2 I feel that bank staff always show their integrity when

I take transaction at bank Integrity of loan officer CRE3 3 I see that bank staff has got knowledge of the market

when they converse with me Knowledge about the market CRE4 4 I believe that bank staff always keeping my private

information in safely status Information confidential CRE5 5 When I use services at my bank, bank staff usually

introduces to me new technological advancements

Help customer up date new technological advancements CR6 6 I believe that my bank has enough competence in the

business

Competence in the business of banking

3.2.1.2 Measure of customer participation

Customer participation consists of six items These items refer to the application of

knowledge in customer participation from the literature (Ngo & O'cass, 2013; Auh at al., 2007;

Chan at al., 2010) This construct will be measured on a five-point Likert scale with scale poles

ranging from strong disagree to strong agree

Table 3.2 - Measurement scales of customer participation

Sharing information

CP2

2 I put a lot of effort into expressing my personal needs to the staff of bank X during the service process

Showing needs

CP3 3 I always provide suggestions to the staff of Bank

X for improving the service outcome Suggestions for improving CP4 4 I have a high level of participation in the service

using process of bank X Level of participation

CP5

5 I am very much involved in deciding how the services should be provided when dealing with bank X

Affect to providing services

3.2.1.3 Measure of customer loyalty

Customer loyalty consists of four items These items refer to the application of

knowledge in customer loyalty generating from the literature (Auh at al., 2007) This construct

will be measured on a five-point Likert scale with scale poles ranging from strong disagree to

CL1 1 I will apply more loan amount at bank Xin the

CL2 2 I will continue to use bank X for my needs in the

future

Willing to continue using services

CL3 3 The likelihood of me trying other services from

CL4 4 I try to use bank X for most of transaction needs Willing to use services

In summary, based on the previous research and after refinement, 30 variables are select

and group in fours indenpent variables and a dependent variable

3.2.2 Draft questionnaire

The questionnaire using a five-point Likert scale was employed to collect the data for

factors of the research model Items selects for the factors are mostly adapted from previous

research in order to ensure content validity Items measuring search, experience, credence,

customer participation and customer loyalty was take from previous research (see in 3.2.1

Measurement scales)

Structure of questionnaire consists of three main parts:

 Part 1: General information of customers who have used personal loan services This information helps select the target respondent to study

 Part 2: The main information includes statements (questions) are based on

a scale of measurement was proposed for the research The items were measured

on the Likert 5-point scale from 1 to 5 (strongly disagree, disagree, neutral, agree, and strongly agree)

 Part 3: Questions on demographics characteristics are included at the end

The pilot test was conducted at Ho Chi Minh branch of Shinhan bank in Ho Chi Minh city The 10 questionaires (translated to Vietnamese language) were sent to 03 banking experts and 07 customers for answering All of them had much knowledge and many experience years in retail banking services After that, the forms have been return for the pilot test Some small changes on the questionnaire fits with understand of respondents and make clear for the questions (in Vietnamsese language)

Finally, after adjusting the first questionnaire table, a small sample size of fifteen convenient respondents was delivered the questionnaires to recognize whether any parts of its unclear to understand or misunderstand However all of them understood meaning of

questionnaires quite well and knew the way to answer The last version of questionnaire was established to survey in the massive areas After that, a main survey was conducted

3.4 Sample method

The target population are the banking customers who are using personal loan of different banks in Ho Chi Minh City, the biggest city in Vietnam Due to limited time and cost, the target respondents are about 500 customers

Researcher will use the quota sampling method to collect research data It is a type of the non-probability sampling It is mean that selected sample is not generalized to population However, if we choose the right controlled characteristic (distinguishing attributes of studied objects), in theoretically, sample cannot represent for population but in practice it may represent for population The reason is when we divide the population according to controlled characteristics; the elements in the same group will usually have high homogeneity So, the elements involve in sample of selected groups although are selected in non-probability method, but because they have high homogeneity, so in some level, they can represent for population Thus, the quota sampling method is a popular method which is usually used in scientific theories testing Even in applied research (collecting data to make business decisions), this method is also commonly used, especially when the researcher do not know sampling frame (Nguyen Dinh Tho, 2012)

In this research, control characteristics including: location - Ho Chi Minh City; used to/ are using personal loans services, gender, ages In which, the location characteristic was controlled by sending emails for person who has bank account in Ho Chi Minh city Used to/ are using personal loans services characteristic was controlled in question form Yes/No Gender and ages characteristics were used to calculate exactly sample rate Researcher used the results of population census 2009 in Ho Chi Minh City and the theoretical basis of quota sampling method to calculate the sample rate The results are as follows:

Table 3.4 - calculating sample with quota sampling method

Sample was divided in 14 groups with age from 25 to 59 and gender (man/women) Data analysis methods used for this research is the Exploratory factor analysis (EFA), Confirmatory factor analysis (CFA) and Structural equation modeling (SEM) Although many researchers in this field agree that this method requires a large sample size because it is based

on a large sample distribution theory (Raykov & Widaman 1995), how large of sample size is not yet to be clearly defined Moreover, the sample size depends on the estimation method used (eg, ML, GLS or ADF)

Some researchers particularly considered with sample size can compute the desired N required for a given model (e.g., some determined number of variables, constructs, and therefore degrees of freedom) and desired level of power, or conversely, an estimate of power for a given N (Kim, 2005; MacCallum, Browne, & Cai 2006) While others researchers found the added benefit that with three or more indicators per factor, a sample size of 100 respondents will usually be sufficient for convergent validity, and a sample size of 150 will usually be sufficient for a convergent and proper solution” (Anderson & Gerbing, 1984)

In EFA analysis, the sample size is usually determined based on (1) the minimum size and (2) number of variables Hair et al (2006) suggested that in order to use EFA, the sample size must be at least 50 and preferably 100 and the rate observations/ items should be 5:1 It means that 01 measured variables need minimum of 5 observations (with 30 original observed variables measuring customer loyalty, so to conduct EFA, the sample size of the study is at least 30x5 = 150) If the method used to estimate is ML (Maximum Likelihood), the minimum sample size from 100 to 150 (Hair et al., 1998) Thus, the sample sizes of the study should be at least 150 Using sample size n = 466 in this research is satisfy above conditions

3.5 Questionnaire administration

The respondents will submit questions through the online survey and direct survey The researcher sent 100,000 individual electric mails to whom have an account at Vietcombank/ Shinhanbank and are living in Ho Chi Minh City and direct survey 50 persons at Vietcombank

Ho Chi Minh Branch After eleven day from 10/08/2014 to 21/08/2014, there are 550 customers answered through online survey and 31 customers answered through direct survey However, to fix with the rate of gender and age from quota sampling method, the researcher only selected 466 respondents to conduct data analysis

3.6 Data analysis methods

All responded questionnaires were reviewed for completion, coded and input as raw data in IBM SPSS Statistic The reliability and validity of measurement scales were evaluated

by using reliability analysis (Cronbach’s alpha test), exploratory factor analysis (EFA) and Confirmatory Factor Analysis (CFA) Then, analized method SEM is used to provide for interpreting the results of its application from a managerial and statistical viewpoint The list of codified variables is shown in Appendix 1

CHAPTER 4 DATA ANALYSIS AND FINDINGS

The purpose of this chapter is to present finding which were collected from the actual questionnaire survey Beside, the researcher proposed an official assessment of measures and also carried out the analysis to give the accurate answers for the research questions, hypotheses proposing in the chapter 2

4.1 Descriptive analysis

The sample with 466 respondents included 48 men with year olds from 25 to 29, and others as details in table below The percent is suitable with the selected sample rate of quota sampling method as describe in Section 3.4

Table 4.1 - Descriptive statistic of respondent’s characteristics

According to income variable, there were 70 persons have income equal or higher VND

20 million/month, counted 15%; 51 persons had income from 15 to lower VND 20 million/month, counted 10.9%; 104 persons had income from 10 to lower VND 15 million/month, counted 22.3%; 241 person had income from 5 to lower VND 10 million/month

There were 128 persons had postgraduate degrees, counted 27.5%; 324 persons had bachelor’s degree, counted highest with 69.5%; 14 persons had finished high school level, counted 3.0% Most of respondent had high education level, it means that they easily understand the questionnaires and answer it with high accuracy

Of 466 respondents, 136 persons in single status, counted 29.2%; 317 persons in married status, counted highest 68% and 13 persons in other status, counted 2.8%

Table 4.2 - Descriptive statistic of respondent’s characteristics

determine if they are measuring attribute Therefore, scales also should be judged on their content and construct validity George and Malley (2003) also provided the following techniques:

Table 4.3 - Cronbach’s alpha reliability coefficient

In testing of Cronbach's alpha, the observed variables have item-total correlation less than 0.3 will be disqualified and criteria scale Cronbach's alpha coefficient to 0.6 or higher (Nunnally & Burnstein, 1994) However, it should be noted that if the Cronbach's Alpha is too high (> 0.95), it may appears redundant items in the scales

Table 8 depicts a summary of the beta scores of all the response ranking of the factors that affect to customer loyalty of person who use personal loan service The results indicated that all scales satisfied the requirement for reliability All Cronbach‘s Alpha of the scales were higher than 0.60 Among factors, “Experience attributes” factor has the highest ranking of Cronbach’s Alpha with valued 0.901 The lowest value of Cronbach‘s Alpha is 0.846 in factor

“Customer loyalty”, the next valued is 0.866 in “Search attributes” and “Customer participation”, and 0.879 in Credence attributes In addition, the corrected item – total correlation in all scales satisfied the criterion (> 50)

Table 4.4 - Cronbach’s Alpha coefficients for each measurement scale

Scale Mean if

Item Deleted

Scale Variance if Item Deleted

Corrected Item-Total Correlation

Squared Multiple Correlation

Cronbach's Alpha if Item Deleted

4.3 Exploratory Factor Analysis (EFA)

Norris and Lecavalier (2010, p.9) indicated that “EFA is based upon a testable model and can be evaluated in terms of its fit to the hypothesized population model; fit indices can be generated to help with model interpretation” The purpose of EFA test is to identify latent constructs underlying a set of manifest variables”

According to Gerbing & Anderson (1988), Principal Axis Factoring Method with Promax rotation (Oblique) will reflect data structure more accurately compare to Principal Components method with Varimax rotation (Orthogonal)

Hair at all (1998, 111) also suggested that Factor loading is the criteria of ensuring practical significance Factor loading >0.3 are considered to reach a minimum, Factor loading

>0.4 are considered important, ≥0.5 were considered to have practical significance Hair at all (1998, 111) also advised that if selected standards Factor loading > 0.3, then sample size must

be at least 350, if sample size is about 100, the Factor loading should be > 0.55, if sample size

is about 50, the Factor loading should be >0.75

Moreover, factors with a total eigenvalue of 1 or greater will take into account; hence any factors with an eigenvalue of less than 1 are discounted (Lee & Hooley, 2005, p.376).Based on these studies, any factors with eigenvalues greater than 1 would be retained And any factor loadings of 0.3 or higher on a factor are counted

KMO is a criteria used to consider the appropriateness of EFA, if 0.5≤KMO≤1 the factor analysis is appropriate Bartlett testing considers the correlation between the observed variables to zero in population If this testing is statistically significant (Sig <0.05), the observed variables are correlated with each other in population

So, researcher should be EFA with the following condistions:

- Using Principal Axis Factoring method with Promax rotation

- Factor Loading of every item must be > = 0.5

- In each item, the difference between | Factor Loading |'s largest and | Factor Loading | any should be > = 0.3 (Jabnoun & Al-Tamimi, 2003)

- Cumulative % of Extraction Sums of Squared Loadings > = 50% (Gerbing & Anderson, 1988)

- KMO> = 0.5, Bartlett testing had statistically significant (Sig <0.05)

After testing Cronbach‘s Alpha coefficient, the measures were continued to be analyzed

by EFA analysis method (extraction method: Principal Axis Factoring and rotation method: Promax) After two time running EFA, the result indicated that there were five factors extracted and total variance extracted was 55.28% (greater than requirement of 50%) Thus, variance extracted matched requirement However, there was 01 item (SA8) that not satisfied the requirements for factor loadings due to loadings < 50 So it was eliminated from the measurement scales Factor Loading of all items were > = 0.50, the difference between largest Factor Loading and any Factor Loading was >= 0.30, KMO= 0.948>0.5, Bartlett testing had statistically significant (Sig = 0.000 <0.05)

Table 4.5 - The EFA analysis result

Extraction Method: Principal Axis Factoring

Rotation Method: Promax with Kaiser Normalization

a Rotation converged in 6 iterations

Accordingly, EFA analysis modified the measurement scale with 05 factors, including: Search attributes (7 items); Experience attributes (7 items); Credence attributes (6 items); Customer participation (5 items), Customer loyalty (4 items) The scales had deleted-items from EFA results, their Cronbach‘s Alpha were calculated again Consequently, the Cronbach‘s Alpha test and EFA results eliminated the unsatisfactory items in measurement scales The modified scales, which matched the requirements, were used to be tested by Confirmatory Factor Analysis (CFA) method

Table 4.6 - Cronbach’ Alpha results after excluding unsatisfactory items

Scale Mean if Item Deleted

Scale Variance

if Item Deleted

Corrected Total Correlation

Item-Squared Multiple Correlation

Cronbach's Alpha if Item Deleted

4.4 Confirmatory Factor Analysis

To measure the degree of model fit to market information, people often use the square (CMIN); Chi-square adjusted for degrees of freedom (CMIN/df); Comparative Fit Index (CFI) Tucker & Lewis index (TLI); Root Mean Square Error Approximation (RMSEA) The model is considered appropriate for market data when tested with Chi-square P-value> 0.05 However, the weak point of Chi-square is dependent on sample size If a model receives values GFI, TLI, CFI ≥ 0.9 (Bentler & Bonett, 1980); CMIN/df ≤ 2, in some cases CMIN/df can be ≤

Chi-3 (Carmines & McIver, 1981); RMSEA ≤ 0:08, RMSEA ≤ 0.05 are considered very good (Steiger, 1990); so the model is considered to be consistent with market data or compatible with market data

Tho & Trang (2008) suggested that if the models get the value of TLI, CFI ≥ 0.9, CMIN/df ≤ 2, RMSEA ≤ 0.08, the model fit (compatible) with market data This rule is also used to assess the suitability of SEM model

In the first time run saturated model including 05 constructs (Search – Search attributes, Experience – Experience attributes, Credence – Credence attributes, CusPart – Customer participation, Cusloy - Customer loyalty), the results was pretty good with Chisquare/df = 2.153, GFI= 892, TLI= 936, CFI= 942, RMSEA= 05 Because Chi-square/df > 2, we would find the way to improve this index Based on the suggestions of Modification indices table, we would draw new variances between errors and run the model again

Table 4.7 - Modification indices

The result of second time running saturated model for 05 scale (standardized estimates) (Figure 4) Chisquare/df = 1.793, p = 000, GFI = 0.913, TLI = 956, CFI = 96, RMSEA =

.041 It demonstrated that these scales received an acceptable fit to the data (Figure 4) All the standardized regression weights λ were substantial, greater than 50 (the minimum is standardized λ SA3= 523 – Appendix 5) and significant (p < 05) The researcher will examine some criteria before has official conclusions about the appropriate level of scale and research model

Figure 4.1 - CFA result in the second time (Standardized estimates)