Factors affecting consumers online puchase intention the moderrating role of product category an empirical study in ho chi minh city

International School of Business --- Trinh Minh Long FACTORS AFFECTING CONSUMER’S ONLINE PURCHASE INTENTION: THE MODERATING ROLE OF PRODUCT CATEGORY - AN EMPIRICAL STUDY IN HO CHI MIN

International School of Business -

Trinh Minh Long

FACTORS AFFECTING CONSUMER’S ONLINE

PURCHASE INTENTION: THE MODERATING ROLE OF PRODUCT CATEGORY - AN EMPIRICAL STUDY IN HO

CHI MINH CITY

MASTER OF BUSINESS (Honors)

Ho Chi Minh City – Year 2014

International School of Business -

Trinh Minh Long

FACTORS AFFECTING CONSUMER’S ONLINE

PURCHASE INTENTION: THE MODERATING ROLE OF PRODUCT CATEGORY - AN EMPIRICAL STUDY IN HO

CHI MINH CITY

Factors Affecting Consumer’s Online Purchase Intention: The Moderating Role of

Product Category - An Empirical Study in Ho Chi Minh City

Trinh Minh Long

long.minh.trinh@gmail.com

0938727169

Dr Nguyen Quynh Mai

MBUS 3 Dec, 08th, 2014

ACKNOWLEDGEMENTS

I would like to express my deepest gratitude to my advisor, Dr Mai Nguyen, for her excellent guidance, caring, patience, and providing me with a great atmosphere for doing research Her guidance helped me in all the time of research and writing of this thesis I could not have imagined having a better advisor and mentor for my Master thesis

Besides my advisor, I would like to thank my friends, and other workers in the

Engineering Service Department, Software Center of Excellence Department at LogiGear Corporation in Ho Chi Minh City for helping me to collect mussel samples from the field

My research would not have been possible without their helps

My sincere thanks go to my mom, two elder brothers, and younger sister They were always supporting me and encouraging me with their best wishes

Last but not the least, I would like to thank my girlfriend, Dao Ninh She was always there cheering me up and stood by me through the good times and bad

Table of Contents

Chapter 1: Introduction 1

1.1.Background of the Study 1

1.2.Problem Statement 4

1.3.Research Objective 7

1.4.Research Question 7

1.5.Research contributions 8

1.5.1 Theoretical contributions 8

1.5.2 Practical contributions 8

1.6.Scope of the study 9

1.7.Organization of the Study 11

Chapter 2: Literature Review 12

2.1.Introduction 12

2.2.Behavioral Intention Models 12

2.2.1 Theory of Reasoned Action (TRA) 12

2.2.2 Theory of Planned Behavior (TPB) 14

2.2.3 Technology Acceptance Model (TAM) 15

2.3.Overview of the Preliminary Model 16

2.4.Conceptual Framework and Proposed Hypotheses 18

2.4.1 Perceived usefulness (PU) 19

2.4.2 Perceived ease of use (PEOU) 19

2.4.3 Perceived risk (PR) 20

2.4.4 Brand orientation (BO) 21

2.4.5 Prior online purchase experience (POPE) 22

2.4.6 Product category 23

2.5.Chapter summary 26

Chapter 3: Research Method 27

3.1.Introduction 27

3.2.Research design 27

3.3.Measurement and Questionnaire Design 27

3.3.1 Measurement 27

3.3.2 Questionnaire design 29

3.4.Data Collection Method 30

3.5.Data Analysis Method 31

3.5.1 Descriptive statistics 31

3.5.2 Exploratory factor analysis (EFA) 31

Correlation matrix analysis 32

Kaiser-Meyer-Olkin (KMO) Measure of Sampling Adequacy/Bartlett's Test of Sphericity 32

Factor extraction analysis 32

Rotation analysis 33

3.5.3 Reliability analysis 33

3.5.4 Correlation Analysis 33

3.5.5 Multiple Regression 33

(1) Normality 34

(2) Linearity 34

(3) Independence of error term 34

(4) Absence of multicollinearity 34

(5) Absence of heteroscedasticity 34

(6) Absence of outlier and influential observations 34

3.6.Chapter summary 35

Chapter 4: Research Results 36

4.1.Introduction 36

4.2.Profile of Respondents 36

4.3.Descriptive statistics 38

Perceived usefulness (PU) 39

Perceived ease of use (PEOU) 39

Perceived risk (PR) 40

Brand orientation (BO) 40

Prior online purchase experience (POPE) 41

Online purchase intention (OPI) 41

4.4.Factor analysis 42

4.5.Reliability Test 45

4.6.Correlation Analysis 47

4.7.Multiple Regression 47

4.7.1 Assumption for Multiple Regression 47

4.7.2 Hypotheses Test 48

4.7.3 The Moderating Effect 51

4.7.4 Summary of Model Analysis 54

4.8.Chapter summary 56

Chapter 5: Discussion and Conclusion 57

5.1.Introduction 57

5.2.Discussion 57

5.2.1 Relationship between perceived usefulness and consumer’s online purchase intention 58

5.2.2 Relationship between perceived ease of use and consumer’s online purchase intention 59

5.2.3 Relationship between perceived risk and consumer’s online purchase intention 60

5.2.4 Relationship between brand orientation and consumer’s online purchase intention 62

5.2.5 Relationship between prior online purchase experience and consumer’s online purchase intention 63

5.2.6 The moderating effect of product category 64

5.3.Implications 65

5.3.1 Theoretical 65

5.3.2 Practical 66

5.4.Limitations 68

5.5.Recommendations 69

5.6.Conclusion 70

References 72

APPENDIX A1 i

APPENDIX A2 v

APPENDIX B ix

APPENDIX C x

APPENDIX D xi

APPENDIX E xiii

APPENDIX F xv

APPENDIX G xviii

APPENDIX H xxi

List of tables

Table 3.1: Measurements and Sources 28

Table 4.1: Respondents’ Demographic Profile 37

Table 4.2: Online purchasing characteristics 38

Table 4.3: Means and standard deviations of items measuring perceived usefulness 39

Table 4.4: Means and standard deviations of items measuring perceived ease of use 40

Table 4.5: Means and standard deviations of items measuring perceived risk 40

Table 4.6: Means and standard deviations of items measuring brand orientation 41

Table 4.7: Means and standard deviations of items measuring prior online purchase experience 41

Table 4.8: Means and standard deviations of items measuring online purchase intention 42

Table 4.9: KMO and Bartlett's Test 43

Table 4.10: Rotated Component Matrix a 44

Table 4.11: Total Variance Explained 45

Table 4.12: Reliability Statistics 46

Table 4.13: Pearson Correlation Coefficient 47

Table 4.14: Model Summary 49

Table 4.15: ANOVAa 49

Table 4.16: Result of Multiple Regression Analysisa 50

Table 4.17: Correlation between Moderator, Dependent and Independent Variables 52

Table 4.18: Model Summaryc with Moderator 52

Table 4.19: Result of Regression Analysisa with Moderator 53

Table 4.20: Product category differences in online shopping (books: n=89; electronics: n = 106; clothing: n=124) 54

Table 5.1: Summary of Hypotheses Results 58

List of figures

Figure 1.1: Trends of revenue from electronic means 2

Figure 1.2: Purposes of accessing Internet 3

Figure 1.3: Popular online products on e-commerce website purchased 10

Figure 1.4: The types of products or services introducing on e-commerce websites 10

Figure 2.1: Theory of reasoned action model 13

Figure 2.2: Theory of planned behavior 14

Figure 2.3: Technology acceptance model 15

Figure 2.4: Conceptual Model 26

Figure 4.1: Final Research Model 55

experience, and brand orientation and the moderator of product category The data was collected using web-based and fill in on-the-spot questionnaire surveys of Internet users aged between 16 and 45 including both online visitors (non-shoppers) and purchasers

(shoppers) with a response rate of 77 percent at sample size of 319 Multiple regression analysis is employed in this study to analyze the data and test the developed hypotheses by using SPSS The findings showed that all of five factors have a significant impact on

consumers’ online purchase intention Accordingly, perceived usefulness is found as the most important determinant, followed by prior online purchase experience In addition, the study confirmed the product type differences in consumers’ online shopping experience, perceptions risks and usefulness, brand orientation associated with online shopping This research will be not only benefit to e-retailers’ marketers who wish to propose the good marketing strategies in relation to increasingly market of its product, but will be useful to web developers as an input in their design process for websites’ interface, search product engine and payment transactions in various product type In addition, the findings may help the Vietnamese government a view to facilitate and support this new emerging technology

to catch up with world trends, which will ultimately be beneficial to the country as a whole

Keywords: online purchase intention, perceived usefulness, perceived ease of use,

perceived risk, brand orientation, prior online purchase experience, and product category

Chapter 1: Introduction

1.1 Background of the Study

The advent of the Internet, along with the development of related technologies, has created a significant impact on the lives of people around the globe Accordingly, online shopping has grown tremendously all over the world This has opened a window and

business opportunity for all businesses because of its ability to make viable the conduct of business in cyberspace, or by connecting people worldwide without geographical limitations (Singh, Jayashankar, & Singh, 2001) Meanwhile, consumers can purchase goods and

services virtually anywhere, 24 hours a day, 7 days a week without worrying about store hours, time zones, or traffic jams (Li & Gery, 2000)

The use of the Internet as a shopping or purchasing medium has been growing with an impressive pace in the past decade According to ACNielsen (2008), 875 million of the world population had made an online purchase in 2008 compare to 627 million in 2006 Among internet users, the highest percentage shopping online is found in South Korea, where 99 percent of those with internet access have used it to shop, followed by the United Kingdom (97%), Germany (97%), Japan (97%) with the United States eight, at 94 percent

A study by Indvik (2013) reported that e-commerce market would grow from $857 billion

in 2011 to $1,860 billion in 2016 and the online retail sales in US amounted to $308 billion

in 2011, and this would likely reach $546 billion in 2016

Online shopping in Vietnam is still a new technology breakthrough since it has just begun to assault the Vietnamese retailing sector with online shopping services The Vietnam E-commerce Report 2013 published by Vietnam E-Commerce and Information Technology Agency (VECITA) showed that in term of the business sectors, the rate of enterprises in wholesale, retail sector joining e-marketplaces stayed in the moderate rate of 15%

(VECITA, 2014) The finance, estate and industry sectors were in the highest rate to

participate in e-marketplace with 28% and 20% respectively 85% of surveyed enterprises answered the efficiencies of participating e-marketplaces were moderate or good levels,

15% respondents evaluated these efficiencies in low levels According to 2013 VECITA’s survey results, 41% of businesses said their revenue increased throughout e-commerce channel, 13% decreased and 46% almost unchanged Particularly, the effectiveness of e-commerce review is relatively stable in the past few years (VECITA, 2014)

Source: Survey of Vecita in 2013

Figure 1.1: Trends of revenue from electronic means

As reported by Vietnam E-commerce and Information Technology Agency, in 2013, the numbers of internet users in Vietnam, accounted for 36% of the population and 57% of them have done online transactions In particular, the e-commerce sales per online buyer are approximately $120 and the most popular items purchased on the internet are clothes, shoes and cosmetics, followed by technology, air ticket, food and book (Quantrimang, 2013) The e-commerce market in Vietnam amounted to $2.2 billion in 2013 Forecasting by 2015, Vietnam will have 40-45% of Internet users Goes along with the increase of Internet user in

2015 as well as the economic growth rate, the e-commerce legal framework will be

completed; the development trend of logistic infrastructure and payments will increasingly

be concerned Pursuant to the findings, the rate of Internet users purchasing items online is predicted to increase by 2015 Based on the above-mentioned figures and an estimated increase of 30 USD in each online consumer’s spending in 2015 in comparison with 2013, Vietnam B2C e-commerce sales will reach around 4 billion USD (VECITA, 2014) In

comparison with the major powers in the world of e-commerce as the U.S ($343 billion), Japan ($127 billion), UK ($124 billion) and China ($110 billion), the e-commerce market is still quite small (PwC, 2013)

Appropriately, although sales of products from the Internet account for only a small percentage of total retail sales, millions of consumers shop and buy on the Internet

Therefore, many companies in Vietnam are also rushing to establish an Internet presence despite a great deal of confusion about the actual impact of this new medium on their

businesses To increase online shopping in Vietnam, the understanding of consumer’s

online shopping behavior and the factors that influence this behavior when shopping online should be given priority Researches indicate that majority of Vietnamese especially young people were using internet for non-shopping activities such as seeking for information (87%), using social network or forum (73%) or accessing e-mail (71%); and only 20% for shopping online (VECITA, 2014)

Source: Survey of E-commerce and Information Technology Agency 2013

Figure 1.2: Purposes of accessing Internet

Depending on Levin, Levin, and Weller (2005), consumers tend to rely on different information sources to confirm product quality and enhance the likelihood of satisfaction when purchasing different types of products They differ in their preferences for online and

traditional outlets based on the varied importance associated with different product

attributes (Levin, Levin, & Weller, 2005) Thus, researchers propose that online products can be categorized by whether their dominant product attributes are digital or non-digital (Biswas & Biswas, 2004; Lal & Sarvary, 1999) Digital products, defined as “all product attributes can be communicated through the Internet” (Lal & Sarvary, 1999, p 487), have less inherent product risk in the online channel than non-digital products that may require physical inspection of the product (Lal & Sarvary, 1999) Levin et al (2005) find that

consumers place greater value on the ability to touch and inspect apparel products and thus prefer traditional stores for apparel shopping In contrast, consumers place greater value on immediate access to product related information when purchasing product such as books and therefore, prefer shopping online for digital products

In order to understand the factors that affects consumer’s online purchase intention, a lots of studies have been conducted using traditional behavioral intention models and

theories, such as Theory of Reasoned Action (TRA) (Fishbein & Ajzen, 1975), Technology Acceptance Model (TAM) (Davis, 1989) and Theory of Planned Behavior (TPB) (Ajzen, 1991) In this research, TAM is used as the foundation of the research It is believed to be the most appropriate model, which can explain Information Technology (IT) or Information System (IS) behavioral intention well and operate in valid and reliable instruments

(Mathieson, 1991)

1.2 Problem Statement

The role of a shopper’s personal attitudes has been widely acknowledged in the consumer decision-making and behavioral intentions In particular, service attitude is a bridge between consumer characteristics and consumer satisfy their needs (Ajzen, 1991) Furthermore, the behavior of consumers’ online shopping have also been influenced by their characteristics, such as personality, demographics and perception of the online shopping benefits (Goldsmith & Flynn, 2004) Therefore, identifying the relative importance of each choice’s determinant for a certain action can be a useful step in understanding why such

behavior happens Meanwhile, behavioral intention is determined by an individual 's attitude towards the implementation of the act Awareness of an individual on the behavior’s

benefits, as well as the individual's self-efficacy and the ability to control both internal and external resources on the behavior in implementing the intended behavior, leading to the development of the Theory of Reasoned Action (TRA), Theory of Planned Behaviour

(TPB) and Technology Acceptance Model (TAM) Based on the perspective of e-business, knowledge of TRA, TPB, and TAM could provide a reasonable basis for explaining and predicting consumers' intention towards adopting online shopping behavior (Choi &

Geistfeld, 2004) Choi and Geistfeld (2004) argue that online shopping is perceived to be more risky than brick-or-mortar retailing transaction Additionally, since consumer behavior

is cultural-specific, it is unclear whether the results reported by consumers intend to

purchase online in Western countries can be directly applied in an Eastern country as in Vietnam

Dann and Dann (2001) argue that the rise of online shopping phenomenon of

consumers is due to the easy accessibility to information online, so consumers are becoming more knowledgeable and efficient by shopping online Although a lots of studies have concentrated on online shopping in the world, there is still a necessity for a closer

examination of the consumers’ online shopping intention in specific countries (Salisbury, Pearson, Pearson, & Miller, 2001) Internet in Vietnam is still considered as a new medium between retailers and consumers, and retaining consumers on e-retail is the most

problematic for any e-retail store (Dai, Forsythe, & Kwon, 2014) To increase understanding

in this area, the questions need an accurate answer

In 2013, Vietnam had a big progress of the online transaction types in both business

to business (B2B) and business to consumer (B2C) (Ha, 2014) Considering the general aspects of the market, the selection of business models for e-commerce plays a very

important role in increasing the awareness level of customers as well as the revenue In the end 2010, the advent of groupon web pages as muachung.vn, hotdeal.vn, nhommua.vn has changed completely electronic commercial in Vietnam The economic benefits are brought

in by these sites have encouraged customers to participate in the e-commerce strongly and created a very large spillovers (Ha, 2014) Currently, e-commerce in Vietnam is still highly fragmented in both consumer to consumer (C2C) and business to consumer (B2C) segments (Ha, 2014) The notable sites work on this model include in vatgia.com, enbac.vn, 5giay.vn while typical e-retailers are solo.vn, tiki.vn, yes24.vn, lazada.vn, zalora.vn, etc Besides, thegioididong.com and nguyenkim.com of the leading retail companies were known as most popular online sales channels with Vietnamese consumers (Quantrimang, 2013) The

expectation of this study is to provide relevant results to the e-retail company to engage the consumers to shop online E-retailer can be more attractive to encourage consumers

shopping on the Internet in Vietnam

In addition, the dependence on different sources of information (e.g., search vs experience) for different product categories in traditional shopping channels also exists in the online shopping context Past researches have established that, depending on the type of products being purchased, shoppers tend to rely on different information sources to make purchasing decisions in traditional shopping environment (e.g brick-and-mortar stores) (Nelson, 1970) However, many extant researches on online shopping have ignored the effect of different product category on shoppers’ intention in Vietnam (Dai et al., 2014) More importantly, eligible product categorization scheme (e.g., search vs experience) in traditional retail setting may not readily apply to the online setting Although some products (e.g., apparel) have inherent risks when purchasing online, published researches have failed

to, with the exception of Biswas and Biswas (2004), provide a compelling evidence for recognition knowledge of how online shoppers’ risk perceptions vary by product category

or how specific risk perceptions influence online purchase intentions for various product types

Despite the potential in Vietnamese consumers, there is still lack of understanding towards online shopping in Vietnam Online retailers will be successful only if they provide value to the consumers; hence, Internet marketers should understand the customers’

expectations and intentions regarding Internet shopping The research can help these online

retailers to understand their customers, satisfy their needs and wants, and create value for them

1.3 Research Objective

The purpose of this research is to identify the determinants affecting consumer’s online purchase intention, using product category as moderating factor in Ho Chi Minh City, Vietnam More specifically, the research mainly seeks to achieve the following

- Does perceived ease of use contribute towards consumer’s online purchase intention?

- Does perceived risk contribute towards consumer’s online purchase intention?

- Does brand orientation contribute towards consumer’s online purchase intention?

- Does prior online purchase experience contribute towards consumer’s online

purchase intention?

- Are there differences above impacts among various product categories?

Above factors (perceived usefulness, perceived ease of use, perceived risk, brand orientation, and prior online purchase experience) are further discussed in the second

chapter under conceptual framework

1.5 Research contributions

1.5.1 Theoretical contributions

The explanatory model has been examined through the existing literature to find a suitable model to explain consumers' behavioral intentions in purchasing products online Further, we use product category as the important control variable for studying the

relationship between factors and intention to purchase online TAM is chosen for this study due to its consistent ability to explain a significant portion of the difference from behavioral intentions and actual behavior deriving mainly from the research into buying products

relating to technology (Adam, Nelson, & Todd, 1992; Mathieson, 1991; Davis, Bagozzi, & Warshaw, 1989) This model seems to be a good model capable of explaining purchase intention of consumers when shopping online and the moderating role of kinds of products

on which there has currently a little literature Therefore, this research contributes to the body of knowledge in this field

1.5.2 Practical contributions

In addition to the theoretical contributions mentioned as above, the findings of this study also affect many applications in business management The main practical

contributions can be summarized as follows:

- This study provides useful information for the business management to prioritize their resources for time, budget allocation, human resources, and investment

- Help marketers to better understand the customer’s intentions concerning Internet shopping It is hoped that the study will indicate the behavioral intentions of

consumers toward Internet shopping and also identify the variables that affect

behavioral intentions of consumers in the product category The marketing manager may be able to plan marketing mix to cater to the needs of online consumers and increase consumer satisfaction by finding appropriate strategies and tactics to deal with the underpinning factors explored in this research

- It provides useful input so that Web developers can design sites and pages of which content and layout is more compelling and effective to attract more business from consumers

- Policy makers or government can use this information to promote online business by improving infrastructure and regulations regarding as Internet, fraud prevention, security and privacy issues to facilitate and encourage larger participation of

consumers in buying and selling products online

1.6 Scope of the study

Due to the nature of this research, a number of delimitation of scope had to be set for the study as below:

- This research is delimited to only Ho Chi Minh citizens, over 15 years of age Ho Chi Minh City is selected due to the highest Internet penetration rate As stated in a

Cimigo’s report, more than 50% of the population has used the internet already in urban Vietnam (Cimigo, 2011) The report also shows that HCMC is higher than the average rate of 50% of the population with the rate 62% in 2011

- Survey is conducted in this research to gather information among people who has browsed online shopping pages (visitors) as well as those who has experience in online shopping (purchasers)

- ACNielsen (2008) reported that, across the globe, the most popular items purchased

on the internet are books (41%), followed by clothing/accessories/shoes (36%), video/DVD/games and airline ticket reservations (24%) In Vietnam, the popular online products purchased are clothes, shoes and cosmetics accounted for 62% The second most popular categories were technology products (35%), followed by

household products (32%), air tickets (25%) and books, stationery (20%), and etc

Source: Survey of E-commerce and Information Technology Agency 2013

Figure 1.3: Popular online products on e-commerce website purchased

Similarly, clothing and footwear, electronics, books and stationery were the top commonly sold products on the e-commerce websites, accounted for 79% of

surveyed sites This proportion represented a correspondence between the supply and demand, of which 62% of people chose to purchase this kind of product online Based on above discussion, the study selected clothing, electronics and books as objects of product category

Source: Data gathered by E-commerce and Information Technology Agency 2013

Figure 1.4: The types of products or services introducing on e-commerce websites

1.7 Organization of the Study

This research is organized as five chapters

Chapter 1 offers an introduction to the study, including background to the study, statement of the problem, research objectives, research questions, the significance of the study, and scope of the study

Chapter 2 makes a brief reference to the theories that have been used These

literatures summarize briefly the knowledge of recent studies, describes the conceptual model, and hypotheses

Chapter 3 presents research methodology, including the research design, population and sampling plan, the instruments, procedures and methods of data analysis

Chapter 4 presents the description and analysis of the data collected

Finally, Chapter 5 reports in detail research findings and implications Further, this chapter concludes with discussion on the results derived, limitations and future research

Chapter 2: Literature Review

2.1 Introduction

The purpose of this chapter is to review the relevant literature to determine the

overview of the field of inquiry, thus allowing the researcher to build a conceptual model for testing and determining the factors that affect consumers' purchase intention to buy online

2.2 Behavioral Intention Models

The most popular theories which have been used to study behavioral intention in technological products are the Theory of Reasoned Action (TRA), the Theory of Planned Behavior (TPB), the Technology Acceptance Model (TAM) and the Diffusion of

Innovation Most of these theories have been developed from the Theory of Reasoned

Action originally proposed by Fishbein and Ajzen (1975) The Diffusion of Innovation Theory was focused more on the adoption of the Internet and determined the likelihood that the innovation will be adopted rather than focusing on purchasing or shopping online As a result, the researcher examines only the other three frequently used theories namely, TAM, TPB, and TRA in order to gain a better understanding on the relationships between belief, attitude, and behavioral intention of consumers when buying products online

2.2.1 Theory of Reasoned Action (TRA)

The theory of reasoned action (TRA), developed by Fishbein and Ajzen (1975,

1980), posits that individual behavior is driven by behavioral intentions TRA is a model for the prediction of behavioral intention, spanning predictions of attitude and predictions of behavior The subsequent separation of behavioral intention from behavior allows for

explanation of limiting factors on attitudinal influence (Ajzen, 1980) With Ajzen and

Fishbein (1980), starting from the behavioral intentions, these include the functions of an individual’s attitude towards the behavior and the subjective norm surrounding the

performance of the behavior Accordingly, the actual use of an innovation is determined by the individual’s behavioral intention to use it The attitude towards an act or a behavior is the individual’s positive or negative feelings about performing a behavior Subjective norm

is defined as an individual’s perception of whether people important to the individual think the behaviors should be performed (see Figure 2.1)

To put the definition into simple terms: a person’s volitional (voluntary) behavior is predicted by his/her attitude toward that behavior and how he/she thinks other people would view them if they performed the behavior A person’s attitude, combined with subjective norms, forms his/her behavioral intention (Fishbein & Ajzen, 1975)

Source: Fishbein and Ajzen, 1975

Figure 2.1: Theory of reasoned action model

However, the TRA has some limitations on explaining all mechanisms of the actual use of an innovation and the role of the individual’s behavioral intent In addition, TRA was criticized for neglecting the importance of social factors that in real life could be a

determinant for individual behavior (Grandon & Peter, 2004) Nevertheless, the advantage

of TRA is the inclusion of subjective norms that can play an important role in certain

situations TRA has been shown to have strong predictive power of consumer’s behavioral intention formation for a variety of consumer products such as fashion, beer, toothpaste, dog food, mineral water and facial tissue (Grandon & Peter, 2004)

2.2.2 Theory of Planned Behavior (TPB)

The theory of planned behavior is a theory about the link between beliefs and

behavior The concept was proposed by Ajzen to improve on the predictive power of the theory of reasoned action by including perceived behavioral control (Ajzen, 1991) It has been applied to studies of the relations among beliefs, attitudes, behavioral intentions and behaviors in various fields such as advertising, public relations, and healthcare Perceived behavior control the importance of behavior control is self-evident and refers to people's perception of the ease or difficulty implementing the interest behavior (Ajzen & Madden, 1985) Under TPB that the behavior is a joint function with intention and perceived control behavioral Ajzen (1991) mentioned that the central factor in the TBP is the person’s

intention to perform a behavior The intention is assumed to capture the motivational

variables affecting behavior They are signs of how people are willing to perform the

behavior (see Figure 2.2)

Source : Azjen (1991)

Figure 2.2: Theory of planned behavior

The Theory of Planned Behavior has been used in many studies, such as weight loss behavior, sexual behavior, waste-recycling behavior, student’s class attendance, spreadsheet

software, and information technology (Richard & Joop de Vries, 2000; Taylor & Todd, 1995) Nevertheless, the Theory of Planned Behavior lacks sufficient scale development for studying online shopping behavior

2.2.3 Technology Acceptance Model (TAM)

Technology Acceptance Model (TAM) is considered an extension of the theoretical effects of TRA, according to Ajzen and Fishbein (1980) Davis (1989); and Davis, Bagozzi, and Warshaw (1989) proposed TAM to explain why users accept or reject information technology by adapting TRA TAM provides a facility that traces how external variables influence the beliefs, attitudes, and intentions to use Two cognitive beliefs adopted by TAM: perceived usefulness and perceived ease of use Perceived usefulness was defined as

"the degree to which a person believes that using a particular system would enhance his or her job performance" (Davis, 1989) Perceived ease-of-use was defined as "the degree to which a person believes that using a particular system would be free from effort" (Davis, 1989) TAM also suggests that the external factors affecting intention and actual use

through mediated effects on perceived usefulness and perceived ease of use (see Figure 2.3)

Source: Davis, Bagozzi, & Warshaw (1989)

Figure 2.3: Technology acceptance model

TAM has proven to be a theoretical model in helping to explain and predict user behavior of information technology (Legris, Ingham, & Collerette, 2003) The scales of

measurement are used in the TAM which are perceived ease of use and perceived usefulness also constantly show to have both high reliability and validity (Adam, Nelson, & Todd, 1992) Additionally, TAM has been found to be the most popular theory used by most

researchers to study the behavioral intention to use technological products from the

literature review Likewise, the robustness of the TAM has been proven in many studies, experiments, organizational surveys, as well as researches in the fields of microcomputer, software, spreadsheet, e-mail, and the World Wide Web (Igbaria, Guimaraes, & Gordon, 1995; Taylor & Todd, 1995) In addition, TAM has been tested and proven in various

countries such as US, Canada, Taiwan, China, India, Thailand, Malaysia, Iran and

Singapore (Jayawardhena, Wright, & Dennis, 2007) Hence, TAM seems to be a suitable model to develop a conceptual model to examine the factors affecting online purchase

intention in Vietnam

In summary, the preliminary theoretical model to test factors affecting online

purchase in this study is based on TAM Previous empirical studies repeatedly confirm that TAM explains a significant portion of the difference from behavioral intentions and actual behaviors of a wide range of information technology This model is considered robust, powerful, and parsimonious In the next section, a preliminary study model, unique to this study, is proposed In addition, constructs and scale measurements is determined to measure the theoretical model of the factors influencing online purchase

2.3 Overview of the Preliminary Model

The Technology Acceptance Model has been used in different contexts with

numerous supporting empirical studies Although attitudes are structured in TAM initially proposed, many researchers have eliminated these constructs from their models (Venkatesh

& Morris, 2000; Davis, Bagozzi, & Warshaw, 1989) There are three main reasons that accounted for the removal of attitudes from the TAM Firstly, previous experimental studies showed a non-significant effect on behavioral intention (Davis et al., 1989) Perceived usefulness was found to be an important determinant of behavioral intention while attitudes

showed a non-significant impact toward behavioral intention Although perceived

usefulness has an important influence on the formation of attitudes, attitudes might not play

a strong role in predicting behavioral intention after an individual is exposed long enough to technology Secondly, some researchers have chosen to move attitudes out of the TAM could be in the advantage of the revised model has fewer indicators, which do not

significantly lower its predictive capability (Mathieson, 1991; Davis, 1989) Thirdly, the TAM based on the premise that the attitudes are comprehensively existed in the constructs

of perceived usefulness People may use a technology even if they do not have a positive attitudinal affect towards its influence as long as it is useful or provides productivity

enhancement (Davis et al., 1989) So, attitudes are excluded from the structural model

proposed for this study

In TAM, perceived usefulness is the major determinant of behavioral intention and the effect of perceived ease of use on behavioral intention is largely indirect through the construct of perceived usefulness (Davis et al., 1989) Besides, PU and PEOU had

consistently been proven to have both high reliability and validity (Adam et al., 1992) It also explains a substantial proportion of variances between behavioral intentions and actual behaviors (Kamarulzaman, 2007) Thus, perceived usefulness and perceived ease of use in original TAM will be kept on this study

Although TAM has been applied and adopted by most researchers, Lee, Kozar, and Larsen (2003) argued that original TAM should be integrated and extended in order to obtain a better understanding of IT adoption According Amin (2007), there are three

approaches to extend TAM, which are “by introducing factors from related models” (Dai, Forsythe, & Kwon, 2014), “by introducing additional or alternative belief factors” (Moon & Kim, 2001), and “by examining antecedents and moderators of perceived usefulness and perceived ease of use” (Kamarulzaman, 2007) Some studies might use any two approaches

or all the three approaches to extend the original TAM (Amin, 2007; Chang, 2004)

Accordingly, TAM has evolved over time Moreover, TAM2 extended the original model to explain perceived usefulness and intentions to use, including social influence (subjective

norm, image, and voluntariness), cognitive instrumental processes (result demonstrability, job relevance, and output quality) and experience The new model was tested in both

voluntary and mandatory settings The results have strongly supported TAM2 which

explained 60 percent of user’s adoption (Venkatesh & Davis, 2000)

Accordingly, TAM has been used in numerous studies to explain the online purchase intention of consumer in many countries In those studies, the TAM has been extended to include constructs such as gender (Brown, Pope, & Voges, 2003; Gefen & Straub, 1997), product category (Dai, Forsythe, & Kwon, 2014; Wen, Prybutok, & Xu, 2011), brand

orientation (Kwek, Tan, & Lau, 2010; Ling, Chai, & Piew, 2010), perceived risk (Dai et al., 2014; Broekhuizen & Huizingh, 2009), online trust (Thamizhvanan & Xavier, 2013; Wen et al., 2011; Ling et al., 2010), prior online purchase experience (Dai et al., 2014;

Thamizhvanan & Xavier, 2013; Brown et al., 2003), social influence (Zamri & Idris, 2013; Abadi, Hafshejani, & Zadeh, 2011)

There are many studies supporting that behavioral intention has a significant impact

on usage and this variable can predict actual behavior in real world (Igbaria et al., 1995; Taylor & Todd, 1995; Mathieson, 1991) As a result, this study measures purchase intention

as a predictor of actual purchase A detailed explanation of the preliminary model, its

constructs and hypotheses are next

2.4 Conceptual Framework and Proposed Hypotheses

The Technology Acceptance Model is chosen as a basic model in this study to

develop a framework of conceptual model to test and investigate the factors that influence consumers’ online purchase intention The study is aimed to take advantage of the reliability and validity of perceived usefulness (PU) and perceived ease of use (PEOU) in TAM by adding other constructs to achieve explanation better and increase the predictive power of online consumer behavior scale (Igbaria et al., 1995; Taylor & Todd, 1995) in Ho Chi Minh City Additional constructs include in brand orientation, perceived risk, and prior online purchase experience

2.4.1 Perceived usefulness (PU)

Perceived usefulness is the degree to which an individual believes that using a

particular system would enhance his or her job performance (Davis, 1989) Since behavioral intention depends on cognitive choice, a potential Internet shopper can either respond

favorably or unfavorably towards engaging in online purchasing Partly, this study believes that the power to attract online shoppers lies in the technology’s usability and usefulness This is in line with Davis (1989) who defines the latter as perceived usefulness (PU), i.e the belief that using the application would increase one’s performance In this context, the performance would be centered in the benefits of purchasing a product through Internet retailing minus the tradeoff of a physical retailing (Davis, 1989) Although study on Internet retailing from the TAM perspective is limited, the PU construct still garnered tremendous support from many other technological applications For instance, Dai et al (2014) asserted the existence of a positive influence of PU on intention in Intranet media Plus, Amin

(2007); Moon and Kim (2001); Venkatesh and Davis (2000); Igbaria et al (1995);

Mathieson (1991); Davis et al (1989) reported that perceived usefulness is significant and positively influences the behavioral intention Hence, it is expected that:

H1: Perceived usefulness has a significant positive impact on the consumer’s online purchase intention

2.4.2 Perceived ease of use (PEOU)

According to Davis (1989), perceived ease of use refers as the degree to which an individual believes that using a particular system would be free of effort This shows that online shopping provides convenience to consumers while traditional shopping often

attributes limited time, anxious, parking space, crowded, traffic jam, and etc (Yulihasri, Islam, & Daud, 2011) A study by Amin (2007) used TAM to evaluate the acceptance of e-commerce and found that “ease of use has a direct effect on consumer’s intention towards purchasing via online” Peng, Wang, and Cai (2008) believe that perceived ease of use is one of the factors that influence consumers’ willingness to purchase online The result

indicates consumer believes that online shopping is useful when it is easy for them to use Further, the dimension of perceived ease of use included characteristics such as controllable, flexible, easy to learn, clear and understandable, easy to become skillful, and easy to use According to Yulihasri et al (2011), ease of use will influence the consumers’ intention to purchase online As such, it could be hypothesized that:

H2: Perceived ease of use has a significant positive impact on the consumer’s online purchase intention

2.4.3 Perceived risk (PR)

The concept of perceived risk was first introduced by Bauer (1960) Based on the theory of risk perception of consumers, any time customers consider purchasing a new product or signing up for a new service, they also face a set of uncertainties about the

product or service collectively referred to as perceived risk (Taylor, 1974; Bauer, 1960) In the context of online shopping, the perceived risk level might be exaggerated due to the physical limitation in accessing to products and sales personnel from online consumers (Kwek et al., 2010)

In the online retailing environment, customers may face some common types of the risk which are security risk, privacy risk, and product risk (Chen & Barnes, 2007) Security

is one of the factors that affect customer trust in online retailing which refers to the safety of the information technology system and financial information or credit card as well (Bart, Shankar, Sultan, & Urban, 2005) Perceived privacy is defined as the ability of consumers to control the informational dissemination provided in the online transactions (Dai et al.,

2014) Goldsmith and Goldsmith (2002) found that, in online apparel shopping, consumers perceived higher level of product risk as opposed to in a traditional store It has also been documented that risks associated with product uncertainty could negatively affect online shopping intention (Bhatnagar, Misra, & Rao, 2000) Prior studies such as Dai et al., 2014; Lee et al., 2003; Miyazaki & Fernandez, 2000; Warrington, Abgrab, & Caldwell, 2000

found that the perceived risk exhibits a significant negative influence on intention to

purchase online So, it could be hypothesized that:

H3: Perceived risk has a significant negative impact on the consumer’s online purchase intention

2.4.4 Brand orientation (BO)

A brand is defined as a name, term, design, symbol, or any other feature that

uniquely identifies one seller's products or services, and distinguishes them from those of its competitors (Aaker, 1991) In the online market, a brand identity is a cognitive anchor and a point of recognition where customers perceive a great deal of uncertainty (Julie, Anthony, & Dena, 2006) Trusted corporate and brand names are used by customers as substitutes for product information when they intent to purchase online (Julie et al., 2006) Orientation of a product towards its brand is called brand orientation Brand orientation develops in response

to market intelligence (Aaker, 1991)

Kamins and Marks (1991) indicated that high familiarity to brand and a good brand image would help improving the consumer's brand attitude and willingness to buy Subodn and Srinivas (1998) suggested that brand image creates within the minds of consumers, consisting of all the information and expectations associated with a product, service or the company providing them and directly affects to the consumers’ purchase decision process, from which consumers inferred the quality of products and formed the behavior of

consumption Moreover, several studies have found that brand loyalty exhibits a strong positive impact on purchase intention in the traditional online retailing marketplace

(Thamizhvanan & Xavier, 2013; Kwek et al., 2010) Studies carried out by Ling et al

(2010); Jayawardhena et al (2007) conclude that brand orientation is positively related to the customer online purchase intention Thus, we propose:

H4: Brand orientation has a significant positive impact on the consumer’s online purchase intention

2.4.5 Prior online purchase experience (POPE)

Helson (1964) argued that an individual’s response to a judgmental task is based on three aspects, which are sum of the individual’s past experiences, context or background, and stimulus Web shopping is a relatively new activity for a wide range of consumers, online shopping is still perceived as riskier than those on traditional ones (Laroche, Yang, McDougall, & Bergeron, 2005) Therefore, web-shopping consumers depend heavily on experience quality in which can be obtained only through prior purchase experience

Experience shows that the more times an action has been performed, the less time is required on each of the subsequent iteration Prior experiences strongly affect future

behaviors In the online shopping context, customers evaluate their online purchase

experiences in terms of perceptions regarding as service offered, risk involved, payment, product information, visual appeal, privacy, personalization, security, navigation, delivery terms, entertainment, and enjoyment (Burke, 2002)

As reported by Elliot and Fowell (2000), customer experience with the Internet

drives the growth of Internet shopping Consumers care deeply about the overall experience

of the buying process Kwek et al (2010) argue that customers intend to purchase product from the Internet after they have already experienced them In the other hand, customers who have prior online purchase experience will be more likely to purchase through online than those who lack such experience Seckler (2000) explains this phenomenon that as individual gain experience with web-shopping, perhaps with small purchases at first, they will be more likely to develop confidence and skills that facilitate more ambitious buying through the Internet After that, consumers respond to the marketing message, the

advertising, the sales approach, the website, the interaction with brand, and more

Customers who are strong interested in online purchase usually have prior purchase experiences since they are assisted in reducing their uncertainties (Solomon, Dann, Dann, and Russell-Bennett, 2007) Therefore, shoppers who have never done an online purchase before are more risk-averse than who have bought products through online means (Lee et al., 2003) If prior online purchase experiences resulted in satisfactory outcomes, this will

lead customers to continue to shop on the Internet in the future (Shim, Eastlick, Lotz, & Warrington, 2001) Unfortunately, if these past experiences are evaluated negatively,

customers will be reluctant to engage in online shopping in the future

Based on the vast extant literature, it can be concluded that customers’ online

purchase experience will have a significant positive effect on their future online purchase intention (Solomon et al., 2007; Laroche et al., 2005; Shim et al., 2001)

H5: Prior online purchase experience has a significant positive impact on the consumer’s online purchase intention

2.4.6 Product category

Previous studies on information asymmetry have suggested that products or services have search, experience, and credence qualities (Brush & Artz, 1999) Search goods are those products or services with features and characteristics easily evaluated before purchase Experience goods are dominated by those products or services where characteristics, such as quality or price are difficult to observe in advance, but these characteristics can be

ascertained upon consumption Credence goods are those whose utility impacts are difficult

or impossible for the consumer to ascertain All goods/services can be placed on a

continuum ranging from “easy to evaluate” (search goods) to “difficult to evaluate”

(credence goods) (Nelson, 1970)

Dimoka, Hong, and Pavlou (2012) described how information signals reduce product uncertainty The information signals are most successful when people can be trusted with a brand/product without being explicitly exposed to the company's name, but rather through diagnostic product descriptions and third-party product assurances A higher price is usually taken as an indication of higher quality, even though the significance of such perceived correction may vary across product categories (Lichtenstein & Burton, 1989) The quality of search goods/services can be learned at almost zero cost in the internet, hence high

surcharges will decrease purchase intention While the purchase of experience

goods/services is required to assess their quality and credence qualities require additional

information for their values to be assessed For experience and credence goods/services, however, a somewhat personalized approach by the provider is required, which will lower the opportunity for customers to compare offerings on the basis of price (Brush & Artz, 1999) Books, clothing and electronics, used in the study, represented three product types—search, experience and credence qualities goods

Perceptions may vary when they shop online for different products depending on the availability of various product information sources on the Internet Thus, the classification

of products into search versus experience and credence may not adequately describe the significant specialties of products because in the online configuration, certain tangible

attributes of search products become intangible (Lichtenstein & Burton, 1989) For

example, consumers are not able to feel the texture or try on a garment when shopping on the Internet This may increase the uncertainty of product performance and change the categorization of products depending on the availability of information sources

Levin et al (2005) found that consumers place greater value on the touching and feeling products in person as a fundamental part of shopping apparel products When they are buying clothes, they would like to see that it fits correctly or how the fabric feels against their skin before purchasing As the result, they prefer traditional stores for apparel

shopping In contrast, consumers place greater value on ability to immediately access

products that do not require any kind of those interactions such as books, DVDs, music, hardware, toys and furniture Thus, they prefer to buy them online Purchasers may perceive

a relatively high level of product risk associated with purchasing non-digital products (e.g., apparel), as opposed to digital products (e.g., MP3 files) online Purchasers feel greater product risk for buying apparel products online due to: (1) the inability to fully examine apparel products’ attributes online, and (2) substantial variations in the characteristics of apparel products (e.g., sizing, color, style, fabric) The result is the same as reports of

Biswas and Biswas (2004)

Furthermore, Bhatnagar et al (2000) found that the risk related to product category and financial aspects, as prominent influencers of consumers’ online shopping intention

Product category contributes to perceived risk in terms of uncertainty associated with the product itself and related aspects like whether product would function as expected

Perceived risk is increased considerably if a product is technologically complex or satisfies ego-related needs or is sold at high price (Bhatnagar et al., 2000) For example, while risk may not be high for buying book, it may be higher for buying computers, refrigerators, or electronics which are technically more complex From this standpoint, product category may contribute significantly to risks associated with Internet purchases In this research, we use product category as the important control variable for studying the relationship between independent factors and consumers’ intention to purchase online Thus, we have the

framework is generated to test the influence of each independent variable on online

purchase intention The TAM developed by Davis (1989) as the basis for the development

of this framework Further, the extended TAM which integrates five constructs altogether is adopted to help understand the role of users’ risk perception, firm reputation, as well as customer experience in online purchase process In this study, we argue for the facilitating role of perceived risk, perceived ease of use, perceived usefulness, brand orientation and prior online purchase experience in online purchase intentions of consumers

Source: Abadi, Hafshejani, &Zadeh (2011); Davis (1989)

Figure 2.4: Conceptual Model

2.5 Chapter summary

This chapter provides a context for understanding the background, used constructs,

the importance of examining factors influencing consumers’ online purchase intention and

the moderating role of product category by reviewing previous literatures Results from the

literature review indicate that the TAM is suitable to use as a basis model for this study

because of its solid theoretical foundation, high reliability and validity of the constructs, and

wide acceptance Perceived usefulness and perceived ease of use are two original TAM

constructs which play important roles in explaining a substantial proportion of variances

between behavioral intentions Therefore, the preliminary research model is developed from

combination these constructs with three additional constructs namely prior online purchase

experience, perceived risk and brand orientation to build a unique model for testing with

consumers in HCMC, Vietnam Extraordinarily, researcher concerns the product category is

as a moderate variable on the relationship between the factors and consumers' online

purchase intention The concerns have been postulated to six hypotheses are tested

Chapter 3: Research Method

3.1 Introduction

This chapter describes the research design of this study Measurement and

questionnaire design, instruments used in data collection, data collection method and data analysis method are also explained in this section

3.2 Research design

The research design method was used in this research is quantitative research Based

on the purpose of this study, the survey method was chosen due to its widespread use in social, business and information science, as well as its ability to collect data on human attitude, behavior and characteristics (Gray, 2009) Besides, the survey provides a mean of rapid, inexpensive, effective and precise in assessing information on the population and producing large amount of data in a short time (Zikmund, Babin, Carr, & Griffin, 2010)

To conduct this survey research, a review of literature was conducted to provide the conceptual foundation Then a self-administered questionnaire was designed and pre-tested before being distributed to the public This is to enhance the clarity and readability of the questionnaire and to reduce the incidence of non-response to the questionnaire (Gray, 2009) The final questionnaire was distributed to the people in the defined population via face-to face and web-based after the pilot testing Afterward, data was collected and imported into SPSS software for several testing and analysis included in: exploratory factor analysis, reliability analysis, correlation analysis, and multiple regression Finally, the finding and implementations were presented and discussed based on the derived results

3.3 Measurement and Questionnaire Design

3.3.1 Measurement

In constructing the instrument, measures were selected from validated questionnaires used in prior researches The multi-scaled items used to measure the constructs were