Inspecting the relationship among e service quality, e trust, e customer satisfaction and behavioral intentions of online shopping customers in ho chi minh city, vietnam

BANKING UNIVERSITY OF HO CHI MINH CITY VU QUANG HUY INSPECTING THE RELATIONSHIP AMONG E-SERVICE QUALITY, E- TRUST, E-CUSTOMER SATISFACTION AND BEHAVIORAL INTENTIONS OF ONLINE SHOPPING C

BANKING UNIVERSITY OF HO CHI MINH CITY

VU QUANG HUY INSPECTING THE RELATIONSHIP AMONG E-SERVICE QUALITY, E-

TRUST, E-CUSTOMER SATISFACTION AND BEHAVIORAL INTENTIONS OF ONLINE SHOPPING CUSTOMERS IN HO CHI MINH CITY, VIETNAM

GRADUATION THESIS Major: BUSINESS ADMINISTRATION

Code: 7340101

Ho Chi Minh City, 2018

BANKING UNIVERSITY OF HO CHI MINH CITY

VU QUANG HUY INSPECTING THE RELATIONSHIP AMONG E-SERVICE QUALITY, E- TRUST, E-CUSTOMER SATISFACTION AND BEHAVIORAL INTENTIONS OF ONLINE SHOPPING CUSTOMERS IN HO CHI MINH CITY, VIETNAM

GRADUATION THESIS Major: BUSINESS ADMINISTRATION

Code: 7340101 ADVISOR: Ph.D TRAN VAN DAT

Ho Chi Minh City, 2018

INSPECTING THE RELATIONSHIP AMONG SERVICE QUALITY,

E-TRUST, E-CUSTOMER SATISFACTION AND BEHAVIORAL INTENTIONS OF

ONLINE SHOPPING CUSTOMERS IN HO CHI MINH CITY, VIETNAM

ACKNOWLEGEMENT This thesis is the author's own work, the research results are honest, in which no previously published content or content done by others except for cited quotes in the thesis

During my thesis time, I received lots of supports and encouragements from many individuals This thesis would not have been accomplished without those valuable input, support, counsel, and advice

First and foremost, I would like to express my deepest acknowledge to my advisor – PhD Tran Van Dat – lecturer at Banking University of Ho Chi Minh City – for his unbelievable and unreserved help, valuable advices and recommendation Thank for his effort and wide knowledge to make my topic possible, his recommendations, guidance and advices are always highly appreciated and greatly contributing to the success of this thesis

Next, I would like to express my earnest appreciation to the professors and lecturers for their guidance during my academic years at Banking University The knowledge and skills that I have learned, have assisted me in the completing of this thesis

Another one I would like to show my sincere gratitude is my brother and friend –

Mr Nguyen Minh Dung, Master of Business Administration During my hard times, he has been contributing great support such as providing useful experiences and willing to help me in data analysis process, and gave many useful advices without hesitation during the time of constructing my thesis

Last but not least, honestly the most supported ones are my family Words fail me to express my thankfulness for my parents for their endless love

To all the above, and so many more, I just simply want to say again “Thank you for all your encouragement, support, and love”

TABLE OF CONTENTS

ACKNOWLEGEMENT 4

TABLE OF CONTENTS 5

LIST OF FIGURES 8

LIST OF SHORTENED WORDS 10

CHAPTER I: INTRODUCTION 11

1.1 Background 11

1.2 Purpose and Aims of The Study 13

1.3 Research Question 13

1.4 Research Subject 13

1.5 Research Design 13

1.6 Significance 14

1.7 Proposed Thesis Structure 14

CHAPTER II: LITERATURE REVIEW 16

2.1 Terms and Definitions 16

2.1.1 E-Service Quality 16

2.1.2 E-Trust 17

2.1.3 E-Customer Satisfaction 20

2.1.4 Behavioral Intentions 24

2.2 Conceptual Framework 24

2.2.1 Dimensions of E-Service Quality, E-Trust and E-Customer Satisfaction 24

2.2.2 Dimensions of E-Service Quality, E-Customer Satisfaction and Behavioral Intentions 26

2.2.3 Dimensions of E-Service Quality, E-Trust and Behavioral Intention 28

2.3 Research Issues 29

CHAPTER III: RESEARCH METHOD 31

3.1 Research Context 31

3.2 Research Design 31

3.2.1 E-Service Quality Measurement 31

3.2.2 E-Trust Measurement 36

3.2.3 E-Customer Satisfaction Measurement 37

3.2.4 Behavioral Intentions Measurement 37

3.2.5 Questionnaire Development 37

3.3 Description of Population and Sample 40

3.4 Research Hypothesis 41

3.5 Research Model 41

3.6 Instruments Development 42

3.7 Analysis Procedures 42

CHAPTER IV: DATA ANALYSIS 45

4.1 Descriptive Statistics 45

4.1.1 E-Service Quality 45

4.1.2 E-Trust 46

4.1.3 E-Customer Satisfaction 47

4.1.4 Behavioral Intentions 48

4.2 Reliability Analysis 49

4.2.1 E-Service Quality 49

4.2.2 E-Trust 51

4.2.3 E-Customer Satisfaction 52

4.2.4 Behavioral Intentions 53

4.3 Exploratory Factor Analysis – EFA 54

4.4 Confirmatory Factor Analysis – CFA 58

4.5 Reliability and Validity 61

4.6 Structural Equation Modeling – SEM 67

CHAPTER V: CONCLUSION AND RECOMMENDATION 75

5.1 Conclusion 75

5.2 Managerial Implications and Theoretical Contributions 78

5.3 Limitations and Recommendation for Future Studies 80

REFERENCE 81

APPENDIX 93

APPENDIX 1: QUESTIONNAIRE 93

APPENDIX 2: DATA ANALYSIS RESULT 103

1 Descriptive Statistics 103

1.1 E-Service Quality 103

1.2 E-Trust 103

1.3 E-Customer Satisfaction 103

1.4 Behavioral Intentions 104

2 Reliability Analysis 104

2.1 E-Service Quality 104

2.2 E-Trust 105

2.3 E-Customer Satisfaction 105

2.4 Behavioral Intentions: 106

3 Exploratory Factor Analysis 107

4 Confirmatory Factor Analysis 109

5 Structural Equation Modeling 113

LIST OF FIGURES

Figure 2-1: Trust level during transaction phases (from Petrovic et al., 2003) 19

Figure 4-2: CFA Result 59

Figure 4-3: Revised Research Model 61

Figure 4-4: SEM Result 68

Figure 4-5: Standardized Direct Effect 71

Figure 4-6: Standardized Indirect Effect 72

Figure 4-7: Total Effect of Research Model 74

LIST OF TABLES

Table 2-1:Prior studies for determining drivers of e-customer satisfaction (from

Barutçu, Süleyman, 2010) 21

Table 3-2:Final Draft Questionnaire 38

Table 4-3: Descriptive Statistics of E-Customer Satisfaction 47

Table 4-5: Reliability Statistics of E-Service Quality 49

Table 4-6: Item-Total Statistics of E-Service Quality 50

Table 4-7: Reliability Statistics of E-Trust 51

Table 4-8: Item-Total Statistics of E-Trust 51

Table 4-9: Reliability Statistics of E-Customer Satisfaction 52

Table 4-10: Item-Total Statistics of E-Customer Satisfaction 52

Table 4-11: Reliability Statistics of Behavioral Intentions 53

Table 4-12: Item-Total Statistics of Behavioral Intentions 53

Table 4-13: Reliability tests result – Cronbach’s Alpha 54

Table 4-14: KMO and Bartlett's Test of dependents variables 55

Table 4-15: Total Variance Explained 56

Table 4-16: Pattern Matrix 57

Table 4-17: CFA Result – Standardized Regression Weights 60

Table 4-18: Calculated Composite Reliability 64

Table 4-19: Correlation Between Constructs 64

Table 4-20: AVE and Squared Correlations between the constructs 66

Table 4-21: Unstandardized Regression Weight 68

Table 4-22: Standardized Regression Weight 69

Table 4-23 Standardized Direct Effect 70

Table 4-24: Standardized Indirect Effect 71

Table 4-25:Standardized Total Effect 72

LIST OF SHORTENED WORDS

CFA : Confirmatory Factor Analysis

ECS : Electronic Customer Satisfaction

ESQ : Electronic Service Quality

RMSEA : Root Mean Square Error Approximation

RMSEA : Root Mean Square Error Approximation

SEM : Structural Equation Modeling

CHAPTER I: INTRODUCTION

1.1 Background

If we had to choose a single word to describe today’s consumers, “connected” would surely rise to the top of the list In fact, with 3.5 billion people using the internet, 7.4 billion mobile-phone subscriptions and 1.79 billion active Facebook users, connected might not even adequately describe the current marketplace Increasingly, everything and everyone is moving online, resulting in the breaking of old habits and establishment of new ones The way we shop is no exception Digital retailing gives consumers more ways

to shop and more access to products and services than ever before It’s clear that consumers are embracing the freedom of shopping whenever and wherever they please, as online sales are capturing a double-digit share of retail dollars in some markets In China-the world’s largest e-commerce market-online retail sales accounted for 12.9% of the total retail purchases in 2015; in South Korea, it was 11.6% In Great Britain, online accounted for an average of 12.5% of all retail spending through the first 10 months of 2016, and in the U.S., e-commerce represented an average 8.1% of total retail sales through the first three quarters of 2016, a rate that Nielsen projects will grow at a compound annual growth rate (CAGR) of 12.2% through 2020 (Nielsen Global Connected Commerce Report, 2017)

Vietnam is home to 92 million people with a total GDP of 194 billion USD GDP per capita is currently 2,327 USD and expected to reach 3,105 USD by 2021 The country

is also ranked 164th by the World Bank GDP per capita rankings There are currently 35.4 million e-Commerce users in Vietnam, with an additional 6.6 million users to be shopping online by 2021 The average user spends 62 USD online, which will grow to 96 USD by 2021 (WorldBank, OECD, Statista, eShopWorld) These statistics are significant signs, informing that Vietnam is a hotspot for e-businesses to prospect Indeed, recently, there is a trend that foreign companies come and buy companies in Vietnam, in order to expand their business operation and also set foot in Vietnam market, where is emerging as

a potential market of the area On April 12th 2016, the China’s giant technology group

named Alibaba Group announced that it has reached an agreement to acquire the control

of e-Commerce platform in Southeast Asia, which is Lazada with an amount of 1 billion USD, thereby officially set foot in Vietnam The retail giant – Amazon is officially penetrating the Vietnamese market by announcing a trade program at the Vietnam Online Business Forum (VOBF) in Hanoi on March 14th 2018 to support small and medium enterprises in commodity export

Service quality, customer satisfaction, trust and behavioral intentions have been proven to have significant impacts on traditional businesses since the dawn of service industry In the new era of the Fourth Industrial Revolution, with the burst of technological advancement in the late 1990s and the early 2000s allowing more and more people to gain access to the Internet, new forms of business were shaped in the online environment, which latter are well-known as electronic commerce activities (e-Commerce) Compared with traditional face-to-face commerce, e-Commerce, or more specific -online shopping- possesses a great deal of unique advantages for the customers, such as: incredible convenience, better prices, a great variety of products, infinite choice, easy access to consumer reviews, no pressure sales and so on

As e-Commerce grows, electronic service quality has been positively influenced the success of online businesses (Yang & Fang, 2004; Zeithaml, Parasuraman & Malhotra, 2002) This success also often includes the contribution in service of the following factors: electronic service quality of the businesses (1); electronic trust of the customers (Gustavsson & Johansson,2006; Windham & Orton,2000) (2); electronic satisfaction of the customers (Kim & Stoel,2004) (3); and behavioral intentions of customers (Chao Wen, 2012) (4) These literatures mainly propose and prove the relationships that occur between the dimensions of electronic service quality and its impact on separate factors of successful e-Commerce In spite of the provided literatures and proofs, there are few studies that have examined the relationships among dimensions of e-Service Quality (ESQ), e-Trust (ET), e-Customer Satisfaction (ECS) and Behavioral Intentions (BI) all together As Vietnam’s e-Commerce is rapidly developing, it is crucial to conduct, investigate and clarify this study so that digital marketers and e-business runners can have

a reliable basis and further understanding in the e-service market Therefore, author choose to inspect the relationship among E-Service Quality, E-Trust, E-Satisfaction and Behavioral Intentions of online shopping customers in Ho Chi Minh City, Vietnam

1.2 Purpose and Aims of The Study

The general objective of this research is to clarify whether there are relationships among the four key factors contributing to the success of e-business: ESQ, ET, ECS and

BI, thus make a conclusion and provide better understanding in the field of e-service and e-marketing

The specific objectives of this research are:

1 Inspect the relationship between ESQ, ET, ECS and BI

2 Evaluate the impact between the four constructs

3 Propose managerial implications and suggestions for future researches

1.3 Research Question

The research is based on the following question:

Is there a relationship among E-Service Quality, E-Trust, E-Customer Satisfaction and Behavioral Intentions of online shopping customers in Ho Chi Minh City, Vietnam?

1.4 Research Subject

The subject of this research is the relationships among E-Service Quality, E-Trust, E-Customer Satisfaction and Behavioral Intentions of online shopping customers in Ho Chi Minh City, Vietnam

Test subjects are online shopping customers above 18 years old in Ho Chi Minh City, Vietnam

1.5 Research Design

This research uses quantitative method, using SPSS and AMOS program to analyze data and identify factors in order to evaluate the relationship

Chapter 2: Literature Review

 A review of previous studies related to the problem under investigation

 Comments and statements of unsolved problems

 Descriptive statistics

 Reliability analysis

 Exploratory Factor Analysis (EFA)

 Confirmatory Factor Analysis (CFA)

 Reliability and validity

 Structural Equation Modeling (SEM)

Chapter 5: Conclusions and Recommendations

 Conclusion

 Managerial implications and theoretical contributions

 Limitations and recommendation for future research

CHAPTER II: LITERATURE REVIEW 2.1 Terms and Definitions

2.1.1 E-Service Quality

As technological advancements are forwarding, there has been a great variety of new products and services coming out in order to fulfill the needs and further improve human’s living standard The human race, to an extent, has surpassed the stage of filling the stomach and warming the body Living standard has upgraded to a point where people demand quality in every aspect, and quality has somewhat become a key factor in terms

of considering buying decision rather than price tags Therefore, it is outdated to consider pricing as a crucial competitive factor Reality shows that perceived quality of a product/service is now the most important competitive advantage in the field of business all over the world This is why the business world today named “The Quality Era” (Peelers, 1996) The term “service quality” began in the 80s as a trend happening around the globe, when marketers realized that only quality products can assure and maintain competitive advantage (Wal et al., 2002) There are various definitions of service quality, depends on each approach that service quality is defined differently, based on reliable scientific basis that aim to resolve specific problems in particular fields In this research, authors choose to define service quality as the level of fulfilling needs of customers A few typical definitions of service quality related to the authors approach are from Lewis and Boom (1983) defined service quality as a measure of how well the service level delivered matches customer expectations; Parasuraman et al., (1988, 1991), considered service quality as an overall judgment similar to attitude towards the service, or also the ability of the organization to meet or exceed customer expectations Feigenbaum (1991) indicated that service quality is customers decision based on their realistic experience with the product/service, measured by customer requests These requests, given or not, were aware of or simply perceived, totally subjective or professional, always represent changing targets in a competitive market According to Edvardsson, Thomasson and Ovretveit (1994), service quality can be defined as the relationship between the customer's expectations of a service and the perception of the service after it was

received

By emergence of e-money and possibility of conducting financial interactions through electronic and online tools, e-commerce increasingly spreads and penetrates into more and more areas of global economy and a new type of business i.e e-business has been founded on the basis of this technology (Kamal Ghalandari, 2012) As a consequence, wherever business grows, there will be customers and problems concerning both parties, e-commerce comes along with e-service quality For an organization to gain competitive advantage it must use technology to gather information on market demands and exchange it between organizations for the purpose of enhancing the service quality (Seth and Deshmukh et al., 2005) Rust & Lemon, (2001) defined e-service in a general concept as the role of service in an online environment More specific, e-service quality, according to Santos (2003), is the consumers’ overall evaluation and judgement of the delivery of service in a virtual market The Internet considered as a primary channel for delivering e-service (Lu et al., 2010; Sousa and Voss, 2006; Parasuraman et al., 2005) So far, several instruments have been developed to assess the e-service quality, such as E-S-QUAL (Zeithaml et al., 2005), SiteQUAL (Yoo and Donthu, 2001), UPWQ (user-perceived web quality: Aladwani and Palvia, 2002), and QES (Fassnacht and Koese, 2006)

2.1.2 E-Trust

“Trust is often understood as a relation between an agent (the trustor) and another agent or object (the trustee) The relation is supposed to be grounded on the trustor’s beliefs about the trustee’s capabilities and about the context in which the relation occurs” (Gambetta, 1988) In an online environment, trust is even more required as its complexity far exceed the traditional one Petrovic et al., (2003) addressed that online transactions and exchange relationships are not only characterized by uncertainty, but also by anonymity, lack of control and potential opportunism, making risk, and trust crucial elements of electronic commerce E-trust, as a causality, occurs in environments where do not present any sign of direct and physical contacts, interactions are only mediated through electronic devices E-Trust is an intangible tool that is effective in reducing

uncertainty and complexity of transactions and relationships in electronic markets

The emergence of trust requires three conditions, which cannot be fulfilled in electronic environments, those are:

1 Direct interactions between the agents;

2 The presence of shared norms and ethical values that regulate the interactions

in the environment;

3 The identification of the parts involved in the interactions

These are the basic differences between trust and e-trust Trust in digital environments is mostly associated with trust over the Internet and especially with that of e-commerce In these cases, e-trust is often reduced to a matter of security (Taddeo, 2011) However, recent innovations and developments of web developers and authorities have made it possible to fulfill the requirements of trust in the digital area Identity confirmations, chats, logs, IP addresses… all contributing to the foundation of electronic trust in such uncertain environments

Petrovic et al., (2003) demonstrated a figure explaining the phases of a transaction and the trust level of each phase There are three main phases during a transaction: information, agreement, and settlement

Figure 2-1: Trust level during transaction phases (from Petrovic et al., 2003)

In order to determine the most appropriate trust model for an e-business model, trust mechanisms are matched with the interaction between participants The behavior of a trust model may affect how users interact with each other, what kind of information (e.g user’ s identity, security policy) is available, how information can be validated or delivered, what kind of environment is used (e.g user-friendly interface, control mechanisms), and for which e-commerce model is suitable Trust mechanisms are used to assist in the development of the framework of a trust model for each e-commerce model

A few proposed trust models in different business context (Pittayachawan and Singh, 2004):

1 Close-Relationship Trust Model (B2E, B2C)

2 Casual Trust Model (B2C, B2B)

3 Community Trust Model (B2C, B2B, G2C, G2G)

4 Community with Casual Trust Model (B2C, B2B, G2C, G2G)

5 Organizational Trust Model (G2G)

6 Popularity-based Trust Model (C2C, P2P)

7 Integrated Trust Model

2.1.3 E-Customer Satisfaction

It was not until the mid-70s of the twentieth century that customer satisfaction and concerning parties became highly anticipated as organizations increasingly attempt to measure it Annual conferences have been held on customer satisfaction (e.g., Hunt, 1977) which led to the publishing of Journal of Customer Satisfaction, Dissatisfaction and Complaining Behavior since 1981 During the past two decades, more than 1200 articles have been published in the area of customer satisfaction research (Perkins, 1991; Wilkie,1990) Customer satisfaction can be experienced in variety of situations and connected to both goods and services It is a highly personal assessment that is greatly affected by customer expectations The most comprehensive definition of satisfaction has been offered by Kotler and Keller who defined satisfaction as “person’s feeling of pleasure or disappointment which resulted from comparing a product’s perceived performance or outcome against his/ her expectations” (Kotler and Keller, 2006, p.144)

In the customer service aspect, Oliver (1980) defined customer satisfaction as the customers’ post-purchase comparison between pre-purchase expectation and performance received According to Zeithaml et al., (1990), customer satisfaction is based on the balance between customers' expectations and customers' experiences with the products and services From both theoretical and empirical perspectives, customer satisfaction is the key to companies’ competitiveness and can be considered the essence of success in today’s highly competitive world of business (Bitner and Hubbert, 1994)

Although there are many convenient features of online shopping mentioned and the substantial increase in number of e-customers, plenty of e-stores and e-retailers are still going out of business or on the verge of bankruptcy It seems quite simple to change e-retailers because of having an unsatisfactory e-service quality, high price of products and e-store design and etc Moreover, there is no switching cost from one e-retailer to another one If managers of e-stores hope to attract and retain e-customers, they need to know what evaluative criteria e-customers use while selecting an e-store (Lim and Dubinsky, 2004) and which factors are driving e-customer satisfaction (Barutçu, Süleyman, 2010)

Prior studies in the field of e-customer satisfaction have indicated plenty of different drivers, based on different concepts or aspects viewed to examine

Based on the listed drivers of the prior studies in Table 1, it is possible to determine which proven and commonly used drivers have the significant impact on customer satisfaction in the examining area

Table 2-1:Prior studies for determining drivers of e-customer satisfaction (from Barutçu, Süleyman, 2010)

Authors Drivers of e-customer satisfaction

Donthu (2001) Site-related factors: ease of use, aesthetic design,

processing speed, security Vendor related factors: competitive value, clarity of ordering, corporate and brand equity, product uniqueness

Cho and Park

(2001)

Product information, site design, consumer service, purchase result and delivery, purchasing process, payment methods, additional information services, delivery time and charge,

Kim and Lim

(2001)

Width of information, update of information, depth of information, promptness of retrieval, speed of transmission, web design, customer service, ease of access, convenience of use, security of user’s information, reliability of the site, advertising, entertain

Francis and

White (2002)

E-store functionality, product attribute description, ownership conditions, delivered products, customer service, security

Loiancona et al

(2002)

Ease of use (ease of understanding, intuitive operations), usefulness (informational fit-to-task), interactivity (trust, response time), entertainment (visual appeal, innovativeness, flow emotional appeal), complementary relationship (consistent image, online completeness, better than other channels)

Janda et al

Dolen et al

(2007)

Perceived technology attributes (control, enjoyment, reliability, speed, ease of use) and chat group characteristics (group involvement, similarity, receptivity)

2.1.4 Behavioral Intentions

Studies about how service quality affect the success of businesses are undeniable However, the real value of service quality is based on its decision-making implications Date back in the late 80s and early 90s of the twentieth century, during the emergence of service industry and findings related to service quality, reseachers began to examine marketing strategies and distinguish them as defensive and offensive tactics (e.g Fornell and Wernerfelt, 1987; Rust and Zahorik, 1993) Offensive marketing strategies focus on capturing new customers whilst defensive refer to retaining existing customers At first, they thought it was service quality that take responsible for the purchase intention, soon after that they realized service quality is not the only factor manipulating it Therefore, investing on service quality alone does not guarantee winning new customers or keeping old ones No matter what strategies a company follows, customers’ reactions to service quality are consequential Those reactions are grouped and called “behavioral intentions”

by numerous researchers Intended behavior is closely related to actual behavior and has diagnostic value Thus, behavioral intentions are important indicators for management to understand whether customers would remain with or defect from the company (Parasuraman et al., 1996) Behavioral intentions in traditional setting and virtual setting are quite similar (Janda et al., 2002), which normally include repurchase intentions, positive word-of-mouth (Boulding et al., 1993; Parasuraman et al., 2005) Parasuraman et al., (1996) presented a more specific group of behavioral intentions in a deeper study, including five factors: loyalty, switch, pay more, external response, and internal response

2.2 Conceptual Framework

2.2.1 Dimensions of E-Service Quality, E-Trust and E-Customer Satisfaction

In order to establish further knowledge and better understanding in the field of service, many researchers have been conducting theses proving the relationship among the key factors influencing e-businesses’ success, mostly between e-service quality and others According to Zeithaml et al., (2000), service quality in online shopping is a significant strategy to achieve success, even more than low prices and web presence Service quality reflects the idea of customers comparing their expectations concerning the

e-performance of service (Gronroos, 1984)

Concerning the effects of e-service quality on consumer e-trust and e-satisfaction, Al-Nasser et al., (2013) conducted a study to clarify the relationships between e-service quality, culture, trust and risk A quantitative research design was adopted to collect data and multiple regression analysis method was used In this study, the researcher adopted Parasuraman et al., (2005) E-S-QUAL four dimensions and E-RecS-QUAL three dimensions as a scale for measuring e-service quality The result shows that e-service quality has significant positive direct impact on customer trust in virtual environments This leads to the first hypothesis:

H1: E-Service Quality has a direct positive impact on E-Trust

Shu-Chiung et al., (2011) tested the significance of relationships among e-service quality, satisfaction, trust, and purchase intention, the comparison effect of culture on e-service quality, satisfaction, trust and purchase intentions between online retailing websites of Taiwan and Malaysia His study found that e-service quality of Taiwan model has significant effects on satisfaction and trust While on the other hand, e-service quality

of Malaysia model has significant effects on satisfaction but not for trust Also, the effects

of e-service quality on e-trust and e-customer satisfaction were identified and reported by Ghalandari (2012) through a survey by collecting data from 382 online buyers A linear regression model was performed, the result indicated that e-service quality determined consumer trust and satisfaction, thereby directly influenced e-loyalty in the virtual concept From these results, the second hypothesis about e-service quality and e-customer satisfaction is formed as below:

H2: E-Service Quality has a direct positive impact on E-Customer Satisfaction

Chuang and Fan (2011) in a study, gathered a sample from 325 members of bookstore in Taiwan, found that service quality determined trust and service quality delivered by e-retailer which satisfied customer’s expectations encouraged trust belief Zhou et al., (2011) in a research to examine the critical success factors of mobile web site adoption, based on the valid responses collected from a questionnaire survey, the

e-structural equation modelling technique was employed to examine the research model The results indicate that system quality is the main factor affecting perceived ease of use, whereas information quality is the main factor affecting perceived usefulness Service quality has significant effects on trust and perceived ease of use Perceived usefulness, perceived ease of use and trust determine user satisfaction Alsajjan et al., (2006) found that e-service quality is a prominent variable in literature dedicated to trust According to Gounaris et al., (2010), examined the effects of service quality and satisfaction on three consumer behavioral intentions, namely word‐of‐mouth, site revisit, and purchase intentions in the context of internet shopping 240 online interviews were carried out from a randomly generated sample of 1,052 online shoppers using the database of a leading Internet provider in Greece as the sample frame The result revealed that e‐service quality has a positive effect on e‐satisfaction, while it also influences, both directly and indirectly through e‐satisfaction, the consumer's behavioral intentions, namely site revisit, word‐of‐mouth communication and repeat purchase Sysmanski and Hise (2000) summarized that convenience, product offerings and product information, site design and financial security are the antecedents of e-customer satisfaction by using focus-group interview The empirical results of the study found that convenience, site design and financial security have significant influences to e-customer satisfaction This indicates that some features of e-service quality and e-trust influence e-customer satisfaction in the online environment

Within the presented studies, the findings are consistent with prior findings concerning the positive relationship between e-service quality, e-trust and e-customer satisfaction The third hypothesis proposed to test the relationship among e-trust and e-customer satisfaction:

H3: E-Trust has a direct positive impact on E-Customer Satisfaction

2.2.2 Dimensions of E-Service Quality, E-Customer Satisfaction and

Behavioral Intentions

Customer satisfaction is viewed as a complex determinant with both cognitive and affective components (Oliver, 1997) In many studies, satisfaction has been proven to have correlation with service quality and behavioral intentions, both direct and indirect Assessing the effects of quality, value, and customer satisfaction on consumer behavioral intentions in service environments, Cronin et al., (2000) synthesizes and builds

on the efforts to conceptualize the effects of quality, satisfaction, and value on consumers’ behavioral intentions A number of notable findings are reported including the empirical verification that service quality, service value, and satisfaction may all be directly related

to behavioral intentions when all of these variables are considered collectively The results further suggest that the indirect effects of the service quality and value constructs enhanced their impact on behavioral intentions, specifically between service quality, customer satisfaction and behavioral intentions, in which customer satisfaction is an important mediator According to Hu et al., (2009) in today's world of intense competition, satisfying customers is only the base line and may not be sufficient for survival Management should focus on gaining customer loyalty by enhancing customer perceptions of service quality and increasing as perceived by the consumer value Examining relationships and impacts of service quality, perceived value, customer satisfaction, and image, the results found that that delivering high quality service and creating superior customer value can result in achieve high customer satisfaction, thus effecting the firm's corporate image, and ultimately leading to consumer retention In brief, Hu’s study partly indicates that customer satisfaction generated by great service quality significantly affect behavioral intentions Yu et al., (2006) also pointed out that service quality affects behavioral intentions through customer satisfaction in his study in Taiwanese leisure industry C.-H Lien et al., (2011) examined the relationships among e-service quality, perceived value, satisfaction, and behavioral intentions for Taiwanese online shoppers The testing results show that, for the direct path, electronic service quality has a significant, positive influence on perceived value, satisfaction, and behavioral intentions Also, perceived value directly influences customer satisfaction and behavioral intentions and satisfaction is an antecedent of behavioral intentions Indirectly, electronic service quality has a significant, positive influence on behavioral intentions

through satisfaction and perceived value

Based on the literatures above, the third hypothesis is proposed to examine the relationship among e-service quality, e-customer satisfaction and behavioral intentions:

H4: Service Quality impacts Behavioral Intentions indirectly through Customer Satisfaction

E-2.2.3 Dimensions of E-Service Quality, E-Trust and Behavioral Intentions

Trust is important for fostering successful relationships, reducing uncertainty and risk, and increasing willingness to purchase In spite of numerous studies being focused

on the critical role of trust in recent decades, the relationships between trust and other service factors, especially behavioral intentions in the online environment have yet to be deeply discussed However, there are several studies mentioned the effect of trust on some aspects of customer intentions, both in online and offline environment For example, Jarvenpaa and Tractinsky (1999) inspected consumer trust in an internet store Their findings indicated that consumers recognized differences in size and reputation among Internet stores, and those differences influenced their assessments of store trustworthiness and their perception of risk, as well as their willingness to patronize the store In general, the study claims that trust is significant for the success of online consumer purchasing – an important customer behavior Verhagen et al., (2006) examined the relationships between consumer perceptions of risk and trust and the attitude towards purchasing at a consumer-to-consumer electronic marketplace It was revealed in Verhagen study that e-trust has a positive effect on customer’s online shopping intentions Gefen (2002) conducted an empirical study to examine the effects of overall online customer trust in the web vendor on shopping intentions among online customers Trust in this study was referred to as perceptions regarding the ability, integrity and benevolence of the party being trusted Results showed that the overall trust consumers had on the online vendor maximized their inclination to purchase from the seller online In a different study, Lynch et al., (2001) investigated the key predictors of

e-consumers’ intention to shop online Results from the experiment showed that trust had a positive effect on buying intention The results suggested that trust positively led to purchase intention for the case of T-shirts

Therefore, e-service quality is expected to have adequate effect on behavioral intentions through e-trust This led to the final hypothesis:

H5: Service Quality impacts Behavioral Intentions indirectly through Trust

E-2.3 Research Issues

Former researches and past studies have shown that there have been remarkable correlations among e-service factors, impacting each other directly or as mediators, one way or another From the development of e-service quality which is a fundamental basis, researchers have been investigating on how to properly measure e-service quality, therefore lead to many other researches concerning e-service industry

Impact of e-service quality towards e-customer satisfaction, e-trust have been proven

to be positive (Al-Nasser et al., 2013; Shu-Chiung et al., 2011; Ghalandari, 2012; Chuang and Fan, 2011; Zhou et al., 2011; Alsajjan et al., 2006; Gounaris et al., 2010; Sysmanski and Hise, 2000), and e-trust together with e-satisfaction are generated by customer’s perceived value of e-service quality Also, e-trust sometimes contributes directly in building e-customer satisfaction along with e-service quality

Behavioral intentions are a group of behaviors demonstrated in the literature as a consequential and crucial factor in e-service context It depends on how customers perceive the online firm through their experiences Often when customers experience aspects of service quality or receive satisfaction during using the firm product/service, they show traits of behavioral intentions This has been indicated in the literature (Cronin

et al., 2000; Hu et al., 2009; Yu et al., 2006; C.-H Lien et al., 2011) Furthermore, service quality and e-customer satisfaction simultaneously impact behavioral intentions, directly or indirectly However, there are still blurred lines among the relationships

e-between e-service quality, e-trust and behavioral intentions The mentioned literature shows that there are significant connections between e-trust and e-service quality, but there are little evidence generally indicates the relationship between e-trust and behavioral intentions, or as a mediator between e-service quality and behavioral intentions (Jarvenpaa and Tractinsky, 1999; Verhagen et al., 2006; Gefen, 2002; Lynch et al., 2001)

In general, there are few studies that have examined the relationships among dimensions of e-Service Quality e-Trust, e-Satisfaction and Behavioral Intentions all together As Vietnam’s e-Commerce is rapidly developing, it is crucial to conduct, investigate and clarify this study so that digital marketers and e-business runners can have

a reliable basis and further understanding in the e-service market Therefore, author choose to inspect the relationship among E-Service Quality, E-Trust, E-Satisfaction and Behavioral Intentions of online shopping customers in Ho Chi Minh City, Vietnam

CHAPTER III: RESEARCH METHOD 3.1 Research Context

According to Vietnam online insight by Google (2016), 87% of Vietnamese users use the internet daily for personal internet usage It means that to reach customers, the most efficient way is through the internet To take good advantages of this, online firms must have either adequate marketing strategies or good customer perception The variety

of online retailers in Vietnam is wide, thus four famous online retailers (Lazada, Tiki, Shopee, and Sendo) in Vietnam were chosen for this study All participants have online shopping experience with the four online retailers and this research investigates their overall attitudes toward the four sites

3.2 Research Design

3.2.1 E-Service Quality Measurement

The most commonly used scale for measuring service quality is the SERVQUAL scale developed by Parasuraman et al., (1985, 1988) Parasuraman’s scale provided a general tool for measuring service quality, not just one specific field, but on a large scale and broad range of service aspects In the recent years, many researchers have been using SERVQUAL scale as the basis for developing e-service quality scale Therefore, a quick review of the SERVQUAL scale is necessary

The widely used SERVQUAL instrument is composed of five dimensions, which are based on the original ten dimensions also developed by Parasuraman et al., (1985, 1988):

1 Tangibles: The appearance of physical facilities, equipment, personnel and communication materials;

2 Reliability: The ability to perform the promised service dependably and accurately;

3 Responsiveness: The willingness to help customers and provide prompt services;

4 Assurance: The knowledge and courtesy of employees and their ability to convey trust and confidence;

5 Empathy: Care and individualized attention provided to customers

SERVQUAL scale is widely accepted and used as an efficient scale for measuring service quality indeed However, some researchers have tried to make use of the application of SERVQUAL scale in the e-service context, and it did not work well due to the three significant characteristics of e-service industry that differentiate between e-service and traditional face-to-face service: (Lee and Lin, 2005):

1 The absence of direct interaction between people and people In e-service, there is no service encounters between the customers and the sales staff as in the traditional service

2 The absence of traditional tangible element In e-service, service process is almost completed in the virtual environment with some intangible elements

3 Self-service of customers In e-service, customers conduct self-service in purchasing and realize control in business process

Apparently new modified scales are needed because of the gap created by the differences in traditional and virtual service context that SERVQUAL cannot cover There have been many modified scales introduced and measured to adapt to changes

in the service industry, especially in e-service Li and Suomi (2009) conducted a review

of listed dimensions of e-service quality proposed by different authors

Table 3-1: Dimensions of E-Service Quality (from Li and Suomi, 2009)

Dabholkar (1996) Website designs,

reliability, delivery, ease

of use, enjoyment and control

E-service

Zeithaml et al., (2000) Efficiency, reliability,

fulfillment, privacy, responsiveness, compensation, and contact

Online retailing

Yoo and Douthu (2001) Ease of use, aesthetic

design, processing speed, and security

Online retailing

Cox and Dale (2001) Website appearance,

communication, accessibility, credibility, understanding and availability

Online retailing

Jun and Cai (2001) Website design,

information, ease of use, access, courtesy,

responsiveness, and reliability

Online shopping sites

Zeithaml et al., (2002) Security, communication,

reliability, responsiveness and delivery

E-service

Madu and Madu (2002) Performance, features,

structure, aesthetics, reliability, serviceability, security and system integrity, trust, responsiveness, service differentiation and customization, Web store police, reputation,

assurance and empathy

E-service

Loiacono et al., (2002) Information, interactivity, Online retailing

trust, response time, website design, intuitiveness, flow, innovativeness, integrated communication, business process and

substitutability

Yang and Jun (2002) Website design, security,

reliability, responsiveness, accessibility and

customization

Online retailing

Surjadaja et al., (2003) Security, interaction,

responsiveness, information, reliability, delivery, and

customization

E-service

Santos (2003) Ease of use, appearance,

linkage, structure, content, efficiency, reliability, communication, security, incentive and customer support

E-service

Yang et al., (2003) Responsiveness,

credibility, ease of use, reliability, convenience, communication, access, competence, courtesy, personalization, collaboration, security and aesthetics

Online retailing

Yang et al., (2004) Reliability,

responsiveness, competence, ease of use,

Online shopping sites

security and product portfolio

Field et al., (2004) Website design,

reliability, security, and customer service

E-service

Kim and Stoel (2004) Web appearance,

entertainment, information, transaction capability, responsiveness and trust

Online retailing

Yang and Fang (2004) Responsiveness,

reliability, credibility, competence, access, courtesy, communication, information,

responsiveness and website design

E-service

Gounaris et al., (2005) Website design,

information, trust, responsiveness and reputation

Online retailing

Parasuraman et al.,

(2005)

Efficiency, availability, fulfillment, privacy, responsiveness, compensation and contact

E-service

Lee and Lin (2005) Website design,

reliability, responsiveness, trust and personalization

Online retailing

Kim et al., (2006) Efficiency, fulfillment,

system availability, privacy, responsiveness, compensation, contact,

Online retailing

information and graphic style

Fassnacht and Koese

(2006)

Graphic quality, layout, attractiveness of selection, information, ease of use, technical quality,

reliability, functional benefit and emotional benefit

E-service

Cristobal et al., (2007) Website design, customer

service, assurance and order management

communication, website content and functionality

Online Financial service

It has been more than two decades since researchers started developing e-service quality counter-measure for internet uncertainty Reliable scales have been accepted and adapted by marketers and scholars In this thesis, author also chooses to adapt the measurement scales from online retailing and online shopping sites e-service quality by former researchers (Wolfinbarger and Gilly (Website design, reliability, security, and customer service.), 2003; Lee and Lin (Website design, reliability, responsiveness, trust and personalization), 2005; Their scales represent the research context of the thesis, targeting e-service quality at online retailing sites

3.2.2 E-Trust Measurement

There is, in fact, no specific common measure of trust for all of the virtual context sites and online consumers Different types of websites (travel sites, information-oriented sites, shopping sites…) have different factors that impact customer characteristics, trust and behavioral intentions (Bart et al., 2005) In this thesis, e-trust is examined between

online retailing vendors and their customers (B2C) Previous studies indicated that by using purchase and dollar value as constructs affected by other factors as level of e-trust, Consumer Trust, Perceived Risk, Perceived Benefit, Perceived Performance, Willing to Purchase, Expectation, Satisfaction, Confirmation, Consumer e-loyalty, Disposition to trust, and, Familiarity between sites a respondent trusts and sites a respondent do not trust, have been proven to have positive impacts on e-trust (Kim, 2009) Scientific method of scale construction for future empirical studies has been the focus of study on the dimensions of ability, integrity and benevolence (Bhattacherjee, 2002) In an experimental study, the purchase intent of the respondent has been examined as a function

of attitude towards vendor, perceived trust in vendor and system trust (Pennington et al., 2004) Singh et al., (2015) investigated factors that can be used to analyze the issue of Trust in Online Marketplaces in the Indian Context Their findings indicate that Trust and its manifestation (1), Credibilty of the Vendor (2), Reliability of the Vendor (3), Honesty

of the Vendor (4), Information Quality (5), Reputation and Ability of the Vendor (6) are key determinants of e-trust

Adapting from the literatures, a scale for measuring e-trust in the thesis is constructed following the determinants listed above

3.2.3 E-Customer Satisfaction Measurement

Based on the literatures presented and the listed drivers of e-customer satisfaction in Table 1, a scale is adapted from Janda, Trocchia, and Gwinner, 2002 It is the overall perceived satisfaction a customer felt when experienced service quality from the vendor

3.2.4 Behavioral Intentions Measurement

Parasuraman et al., (1996; 2005) completed a scale for measuring customer behavioral intentions and it is considered the lodestar for researchers even till today The scale includes five factors: loyalty, switch, pay more, external response, and internal response

3.2.5 Questionnaire Development

The questionnaire is a regularly used method to collect empirical evidence to serve

the purpose of the research It is usually developed based on the factors of the research model, and the language is presented in a less formal way so as to provide better understanding The statements are clear and short to avoid confusion

The questionnaire includes two parts The first part contains demographic questions regarding basic personal information The second part consists of 26 questions measuring e-service quality, e-trust, e-customer satisfaction and behavioral intentions

The questionnaire is designed based on the Likert’s measurement scale According

to Likert Rensis (1932), it is a kind of question form that respondents rate the level of their agreement on statements or questions Likert’s scale has many different types of scales; among those, there are two scales which are the most common in quantitative analysis that are questions structured with five-point or seven-point response scale Likert surveys are quick, efficient and inexpensive methods for data collection Therefore, to be easier for collecting and having more accurate data, the questionnaire will be designed in the form of Likert 7-point-scale, which is a scale from 1 (Extremely Disagree) to 7 (Extremely Agree)

The final draft questionnaire includes 26 questions:

Table 3-2:Final Draft Questionnaire

Lee and Lin, 2005;

ESQ2 This online retailer provides in-depth

information of the product/service ESQ3 My order was delivered by the time

promised by this online retailer ESQ4 Transactions with this online retailer are

error-free

ESQ5 I feel safe in my transaction with this

E-Trust ET1 This online retailer has the skills and

expertise to perform transactions in an expected manner

Pennington

et al., (2004); Singh et al., (2015)

ET2 This online retailer has access to the

information needed to handle transactions appropriately

ET3 This online retailer is fair in its conduct

of customer transactions ET4 This online retailer is fair in its customer

service policies following a transaction ET5 This online retailer is open and receptive

to customer needs ET6 This online retailer keeps its customers’

best interests in mind during most transactions

ET7 This online retailer makes good-faith

efforts to address most customer concerns

ET8 Overall, this online retailer is

trustworthy

E-Customer

Satisfaction

ECS1 Based on all of my experience with this

online retailer, I feel very satisfied

Janda et al.,

2002 ECS2 Overall, I am satisfied with the decision

to purchase from this online retailer ECS3 My choice to do business with this

online retailer was a wise one ECS4 I feel very pleasant about my decision

concerning this online retailer Behavioral

Intentions

BI1 Say positive things about this online

retailer to other people

Parasuraman

et al., (1996;

2005) BI2 Recommend this online retailer to

someone who seeks my advice BI3 Encourage friends and relatives to do

business with this online retailer BI4 Consider this online retailer to be my

first choice if I buy the same product/service again

BI5 Do more business with this online

retailer in the next few years BI6 Continue to do business with this online

retailer if its prices increase somewhat

(Source: author)

3.3 Description of Population and Sample

An online survey using questionnaire in Ho Chi Minh City was conducted to collect the data 526 responds collected and 476 of them are valid The invalid responds are the ones with less than 50% of the questions answered Among the respondents, 35.6% of them are males and the same figure for females are 64.4% In terms of age, those who above 18 to under 25 years old accounted for 89.2% of the sample, ranked the highest The same figure for those aged 26 to under 35 and above 35 are 9.8% and 1%,