antencedents and mediators of consumer’s online purchase intention

Technology characteristics, trust, and social influence are three factors that influence purchase intention indirectly via mediator perceived ease of use.. The results of this study prov

UNIVERSITY OF ECONOMICS HO CHI MINH CITY

International School of Business

-

Nguyen Thi Thanh Tuyen

ANTENCEDENTS AND MEDIATORS OF CONSUMER’S ONLINE PURCHASE

INTENTION

MASTER OF BUSINESS (Honours)

Ho Chi Minh City – Year 2015

UNIVERSITY OF ECONOMICS HO CHI MINH CITY

International School of Business

-

Nguyen Thi Thanh Tuyen

ANTENCEDENTS AND MEDIATORS OF CONSUMER’S ONLINE PURCHASE

INTENTION

ID: 22120036

SUPERVISOR: Nguyen Quynh Mai

Ho Chi Minh City – Year 2015

ANTENCEDENTS AND MEDIATORS OF CONSUMER’S ONLINE PURCHASE

INTENTION

Nguyen Thi Thanh Tuyen

UNIVERSITY OF ECONOMICS HO CHI MINH CITY

International School of Business

ACKNOWLEDGEMENTS

I am deeply grateful to my advisors, Dr Nguyen Quynh Mai for the guidance and comments through the process of completing this thesis Without the support and encouragement from Dr Nguyen Quynh Mai, the thesis might not be completed in meeting the requirements and

expectation of the research I also want to say thanks to my classmates and others who

complete the surveys and share knowledge with me

Nguyen Thi Thanh Tuyen

July 4th, 2015

ABSTRACT

Many e-vendors have been investigated in Vietnam but not all of them are successful In order

to be successes, e-vendors need to know how to attract consumers by understanding consumers’ purchase intention In this study, five factors that were proposed to have influence on purchase intention Those were technology characteristics, trust, social influence, perceived ease of use, perceived usefulness A survey was launched in August, 2014 and 180 responses was collected

in Ho Chi Minh City, Vietnam for analyzing The findings showed that perceived usefulness is not a factor that influences purchase intention Perceived ease of use is found to be a key factor that influence purchase intention directly Technology characteristics, trust, and social influence are three factors that influence purchase intention indirectly via mediator perceived ease of use

To gain consumers online purchase intention, e-vendors should provide products and services that gain consumers’ perceived ease of use Besides that, their websites need to be easy to read and easy to understand by improving technology characteristics E-vendors also need to gain trust and social influence to increase consumers’ purchase intention The results of this study provide a valuable insight on the direct impact of perceived ease of use and the indirect impact

of trust, social influence, and technology characteristics towards online purchase intention

TABLE OF CONTENTS

ACKNOWLEDGEMENTS II ABSTRACT III

CHAPTER 1: INTRODUCTION 1

1.1 BACKGROUND 1

1.2 PROBLEM STATEMENT 2

1.3 RESEARCH OBJECTIVES 4

1.4 RESEARCH QUESTIONS 4

1.5 RESEARCH SCOPE AND LEMITATION 4

1.6 THESIS STRUCTURE 4

CHAPTER 2: LITERATURE REVIEW 5

2.1 CONCEPTS 5

2.1.1 E-Retailing 5

2.1.2 Online Purchase Intention 6

2.1.3 Consumer Behavior 6

2.2 THEORIES OF CONSUMER BEHAVIOR 7

2.2.1 Theory of Reason Action - TRA 7

2.2.2 Theory of Planned Behavior – TPB 8

2.2.3 Theory of Acceptance Model – TAM 9

2.3 ATTENCEDENTS OF ONLINE PURCHASE INTENTION .11

2.3.1 Perceived Usefulness 11

2.3.2 Perceived Ease of Use 13

2.3.3 Trust 14

2.3.4 Social Influence 16

2.3.5 Technology Characteristics 17

2.4 CONCEPTUAL MODEL 18

2.5 CHAPTER SUMMARY 19

CHAPTER 3: REASECH METHODOLOGY 20

3.1 RESEARCH PROCESS .20

3.2 MEASUREMENT SCALES .22

3.3 DATA COLLECTION METHOD 25

3.3.1 Sample and Sample Size 25

3.3.2 Data Collection Process 25

3.4 DATA ANALYSIS METHOD 25

3.4.1 Descriptive Analysis 26

3.4.2 Reliability Analysis 26

3.4.3 Exploratory Factor Analysis 26

3.4.4 Multiple Regression Analysis 27

3.4.5 Testing Mediation with Regression Analysis 28

3.5 CHAPTER SUMMARY 28

CHAPTER 4: DATA ANALYSIS 29

4.1 DESCRIPTIVE ANALYSIS 29

4.1.1 Gender 31

4.1.2 Age 31

4.1.3 Education 31

4.1.4 Income 31

4.1.5 Career 32

4.1.6 Frequency of Online Purchasing 32

4.1.7 Most Recent Purchase 32

4.2 RELIABILITY ANALYSIS 32

4.3 EXPLORATORY FACTOR ANALYSIS 35

4.4 HYPOTHESES TESTING 39

4.4.1 Assumption Test .39

4.4.2 Testing Mediation with Regression Analysis 42

4.5 CHAPTER SUMMARY 49

CHAPTER 5: CONCLUSION AND IMPLICATION 50

5.1 DISCUSSION 50

5.2 MANAGERIAL IMPLICATIONS 52

5.3 LIMITATION OF STUDY AND FUTURE RESEARCH 53

5.4 CONCLUSION 54

REFERENCES 56

APPENDICES 61

LIST OF FIGURES 8

Figure 2.1: Theory of Reasoned Action model 8

Figure 2.2: Theory of Planned Behavior – TPB 9

Figure 2.3: Original TAM 10

Figure 2.4: Final version of TAM 11

Figure 2.5: E-retailing purchase intention model 18

Figure 3.1: Research Process 21

Figure 4.1: Revised e-retailing purchase intention model 38

Figure 4.2: Histogram 40

Figure 4.3: P-P Plot 41

Figure 4.4: Scatter Plot 41

Figure 4.5: Diagram of description step 1-3 44

Figure 4.6: Diagram of description step 4 45

Figure 4.5: Model Tested Result 46

LIST OF TABLES

Table 3.1: Results of the Reliability Test (Pilot) 24

Table 4.1: Descriptive Analysis 29

Table 4.2: Results of Reliability Test 33

Table 4.3: KMO and Bartlelt’s Test 35

Table 4.4: Total Variance Explained 36

Table 4.5: Rotated Factor Matrix 37

Table 4.6: Collinearity Statistics 39

Table 4.7: Coefficients of TC, T, and SI Predicting PI 42

Table 4.8: Coefficients of TC, T, and SI Predicting TB 43

Table 4.9: Coefficients of TB Predicting PI 43

Table 4.10: Coefficients of TC, T, SI, and TB Predicting PI 44

Table 4.11: Testing with Regression Analysis Result 48

on e-retailing websites by making transaction via virtual interface It’s more convenient than traditional shopping which usually causes anxious crowded, traffic jam, limited time, and parking space However, web shopping is perceived to be more risky than traditional way, so trust play a crucial role for consumers making online transaction (Pavlou, 2003)

E-retailing has arisen in Vietnam from 2001 Together with the event joining WTO in

2006, Vietnam becomes a promising environment for e-retailing in next five years A recent study Irwin and Nguyen (2013) showed that Vietnam’s e-retailing market value achieved approximately $300 million in 2011 and is expected to gain $2.8 billion by 2015 with growth rate at 75% from 2011 to 2015 (Irwin and Nguyen, 2013)

In 2013, German Rocket Internet invested $250 million in Lazada Group, an online retailing group, to five countries in Southeast Asia including Vietnam Observers commented that it is the right time for foreign investors to gear up their investment plans in Vietnam Many market reports have predicted that an online boom will happen in near future Tran

e-TrongTuyen, the director of DKT, forecasted that the Vietnamese e-commerce market in

2014-2015 will be doubled that of 2013 In 2013, Epinion, a market survey firm reported that 50% of Vietnamese internet users use online shopping Lazada’s CEO, Alexandre Dardy, believes that shopping online through smartphones will be the tendency in near furure which will be favored

by young consumers Vietnam Net Bridge, a market survey firm, has reported that Vietnam

ranks second in the world in using smartphone It is the reason for traditional retailers such as FPT Shop, Nguyen Kim, and The Gioi Di Dong last year began to expand their investments to develop online retailing (VietNamNet Bridge)

In order to be successful, e-retailers need to learn about Vietnamese consumer’s

characteristics to understand consumers’ purchase intention Purchase intention refers to

willingness of consumers when buying products and services online (Kimery and McCord, 2002) The purchase intention is the key element that leads to make the final decision on

buying products Purchase intention is evaluated base on the consumers’ willingness to

purchase and their willingness to purchase again within a period of time Furthermore, prior studies have showed that purchase intention is a key factor that influences consumers’ buying behavior and their shopping activities in the future (Pi et al., 2011; Pavlou and Gefen, 2004)

Different from consumers in developed countries, people search products, play orders, and make payment online, Vietnamese often search on the internet and place order online but making payment by cash in person Nguyen Ngoc Dung, chief representative of VECOM’s HCM City Branch, the Vietnam e-commerce association, pointed out that shopping online barrier does not lie in technology solutions but in consumer’s habits (VietNamNet Bridge, 2014) Vietnamese wants to see products in person before buying, so Vietnamese want to make payment after delivery of goods E-retailing firms now have to accept that It’s caused a lot of pain for e-retailing firms when many orders are cancelled upon delivery and the companies have to incur the cost of delivery This problems need to be solved for e-retailing firms don’t have to bear the pain of canceled order upon delivery

1.2 Problem Statement

Vietnamese doesn’t believe in the quality of products until they physically touch them, so they prefer to buy products in store after reviewing on the web It’s critical for companies to win Vietnamese consumers’ trust to against skepticism While online payment via the bank is a mainly method in developed countries, the kind of method is not widely used in Vietnam Online shoppers still pay in cash upon delivery Payments via bank accounts and intermediate

payments are accounted for 41% to 8% respectively (Vecita, 2014) It’s because some people don’t have bank account and the others don’t trust banking system This issue is a great pain for companies since some people cancel order on delivery If people trust banking system and product qualities, then they will think making payment online is useful and their perceived usefulness will influence their purchase intention If social influence such as social media, friends, relative, colleagues, etc pays online for their shopping cart, then people will think payment online is useful and their perceived usefulness will influence their purchase intention

TAM model has been applied in many technology fields and e-retailing field is not exceptional In 1996, Venkatesh and Davis introduced final version of TAM model When investigating information system using behavioral, they recognized that perceived usefulness and perceived ease of use influence behavioral intention directly Following pervious studies such as Ramayah and Ignatius (2005), Koufaris (2002), Garwal and Prasad (1999), Chau and

Hu (2001), Moon and Kim (2001), Ngo (2013), Ho and Chen (2013), Jun et al (2004), and Honarbakhsh et al (2013), this study will also use TAM as a main theory to develop research framework In this study, perceived ease of use and perceived usefulness are two keys factors that influence purchase intention directly External factors that influence purchase intention indirectly via those two key factors that are technology characteristics, social influence, and trust

Trust and social influence are another problem that influence consumers on perceived usefulness which influence purchase intention according to TAM Model Besides that,

technology characteristics are the problem that influence purchase intention via perceived ease

of use Overall, trust, social influence, technology characteristics, perceived ease of use,

perceived usefulness are all problems that preventing consumers from online purchasing

There are many e-retailing studies have been done in Vietnam but e-vendors still have to deal with online transaction problem Most consumers still use cash payment upon delivery which cause a lot of pain for e-vendor when orders are canceled upon delivery This study will investigate indepth about consumers’ purchase intention to help e-vendors solve the problem

1.3 Research Objectives

This study aims to apply TAM model to identify if perceived usefulness, perceived ease of use, trust, social influence, and technology characteristics influence consumers’ online purchase intention

1.4 Research Questions

The research is to answer the following question

How do perceived usefulness, perceived ease of use, trust, social influence, and

technology characteristics influence purchase intention?

1.5 Research Scope and Limitation

Research scope: the research takes place in HCMC and data is collected from August 12th,

2014 until September 12th, 2014

Limitation: Most of people I know work in high tech industries, so they are more

familiar with internet than the others Ho Chi Minh City is the biggest city, people live in HCMC will shop online more than people from other cities Therefore, the result may

overestimate Vietnamese consumers purchase intention

1.6 Thesis Structure

This thesis have five chapter The first chapter is introduction which introduces about research background, research problems, research questions, research objectives, research scope and limitation, and thesis structure The second chapter does the literature review, proposed

hypothesis, and then proposed research model The third chapter introduces about methodology

to be conducted The chapter fourth represents research results After having the result, chapter five makes conclusion and gives recommendation

CHAPTER 2 LITERATURE REVIEW

This chapter will review previous studies to understand main concepts of this studies and

identify key factors that influence online purchase intention Hypotheses are proposed after reviewing key concepts and theories foundation

2.1 Concepts

2.1.1 E-retailing

According to Awais and Samin (2012), e-retailing has looping process In looping process, a company or a consumer uses internet to browse products that his/her want and compare with others products to see its advantages When he/she completely satisfies with the products, he/she will place an order The order will then be in the virtual shopping cart for online

transaction option When he/she completes payment, the seller will notify his/her about the fulfillment of the order The order will be soon shipped and delivered to the consumers If the consumers are satisfy with the services, then they will repurchase from that e-retailer

Awais and Samin (2012) pointed out the strength, weakness, opportunity, and threat of e-retailing The major strengths of e-retailing are no boundary, no physical company setup, time saving The major weaknesses are security, fraud, fake websites, and long delivery timing Changing trends, new technologies, and global expansion are considered as opportunities for e-retailing to be grown Privacy concern, risk, and fraud are thread for e-retailing

Popularity of internet connectivity together with developing new powerful tools for using internet related devices have created a new era of retail which is called e-retailing E-retailing is a type of business that operates by selling and buying of goods and services through computer by using internet The developing of e-retailing has led businesses to online market E-retailing gives opportunities for sellers and potential buyers to interact with each other

fromdistance by just one click Saving time and money are a key success for e-retailing (Awais and Samin, 2012)

2.1.2 Online Purchase Intention

Customer purchase intention is considered as an important signal to determine the strength of a consumer’s intention to carry out a specified purchasing behavior via Internet in the online shopping environment (Salisbury, et al., 2001) Furthermore, the theory of reasoned action (TRA) also proposed that consumer behavior can be predicted from intention Intention

influences consumer behavior in terms of action, target, and context (Ajzen and Fishbein, 1980) According to Day (1969), consumer intention can be measured more effective than consumer behavior because consumer may make a purchase due to constraints rather than real preference when purchase is considered

Purchase intention is one of the components of consumer behavior on how individuals want to purchase a specific brand Laroche, Kim, and Zhou (1996) suggested that purchase intention can be measured by variables which influence consideration or expectation in buying

a specific brand According to Pavlou (2003), he defined online purchase intention as a

situation when consumers are willing and intend to involve in an online transaction The online transaction is defined as an activity in which information retrieval, information transfer, and product purchase are processed (Pavlou, 2003) Information retrieval and information transfer are considered as intentions to use a website When consumers use a website and want to buy products, then the online transactions occur (Pavlou, 2003) Therefore, it’s very important to study consumer purchase intention to encourage individuals make purchase on web shopping environment

2.1.3 Consumer Behavior

Consumer behavior is influenced by external and internal factors External factors are

considered as the environmental condition, and internal factors are related to the consumer’s mind (Mitta, 2013) Consumer behavior of every individual is different from another because

of buying habits and choices which are influenced by psychological and social drivers

(Brassington and Pettitt, 2000) People often change their mind but they usually don’t realize that Most people after changinh their mind and reconstructing their past opinion, they believe that they always thought like that (Keys, 2011) So consumer behavior is difficult to predict Mitta (2013) suggested that the external factors have five sectors which are demographics, socio-economoics, technology and public policy, culture, and sub-culture He also suggested that internal factors are influenced by variety of psychological processes which is attitudes, learning, perception, motivation, self-image, and semiotics

In addition, Seth (1983) also proposed that the consumer’s behavior has two type of motives while shopping They are functional and non-functional The functional motives are time, shopping place, and consumer’s needs The consumers will be motivated if they can save time when shopping in an environment where they don’t have to pay parking fee and lower cost with widely range of products to choose The non-functional behavior motives are related

to culture or social values such as the brand name of the store

2.2 Theories of Consumer Behavior

TAM is the Theory of Technology Acceptance model that has been used for many prior studies

in e-retailing field, so this study will use TAM as a main theory to develop the research model TAM was develop based on TRA, Theory of Reason Action, byAjzen and Fishbein (1980) and TPB, Theory of Planned Behavior by Ajzen (1985), so TRA, TPB will also be introduced to for reader to understand how TAM to be developed

2.2.1 Theory of Reason Action – TRA

Theory of Reasoned Action (TRA) was proposed Ajzen and Fishbein(1980) They suggested that a person actual behavior is influenced by their prior behavioral intention along with beliefs that the person would have for the given behavior They also proposed that behavioral intention

is determined by a person attitude towards the actual behavior and the subjective norm

associated with the behavior The person attitude is defined as a person’s positive or negative feelings about performing actual behavior The attitude of a person can be measured by the sum

of the product of all salient beliefs about consequences of performing that behavior and the evaluation of those sequences The subjective norm is the person’s perception that most people who are important to him or her think he or she should or should not perform the behavior The subjective norm is the sum of product of person’s normative beliefs and his or her motivation

to comply The normative beliefs are perceived expectations of other individuals or groups Thus, Theory of Reasoned Action is an appropriate model for explaining and predicting

personal behavioral intention or consumers’ purchase intentions

Figure 2.1: Theory of Reasoned Action model (Davis, Bagozzi, and Warshaw, 1989)

2.2.2 Theory of Planned Behavior – TPB

The Theory of Planned Behavior (TPB) was proposed by Ajzen (1985) TPB is very similar to the TRA, except that it takes into account the perceived behavioral control (PBC) PBC is the perception of control over performance of a given behavior PBC is determined by two beliefs which are control beliefs and perceived facilitation Control beliefs include perceived

availability of skills, resources, and opportunities Perceived facilitation belief is the

individual’s assessment of available resources to the achievement of a given set of outcomes The perceived behavioral control construct could help identify specific barriers to system use such as limitations in users kills

Belief and

Evaluations

Attitude toward Behaviors (A)

Normative beliefs and

Motivation to comply

Behavioral Intention (BI)

Actual Behavior Subjective

Norm (SN)

Figure 2.2 Theory of Planned Behavior – TPB (Ajzen, 1985)

2.2.3 Theory of Technology Acceptance Model – TAM

Fred Davis proposed the Technology Acceptance Model (TAM) in 1985 when he worked on his doctoral thesis at the MIT Sloan School of Management He suggested that actual system use is directly influenced by user’s motivation to use the system The user’s motivation

depends on system features and capabilities (Davis, 1985)

Relying on TRA (Fishbein and Ajzen, 1975), Davis further refined his conceptual framework to propose the theory of Technology Acceptance Model (TAM) In this model, Davis suggested that users’ motivation is influenced by perceived ease of use, perceived usefulness, and attitude toward using the system A person’s attitude toward using the system was considered to be the major determinant of the person actually using the system The attitude was then influence by perceived ease of use, and perceived usefulness Davis adapted TRA to develop his model and made two main changes Firstly, he did not take subjective norm into account in predicting the actual behavior of a person Secondly, he only defined two

Behavioral beliefs

and

Outcome

Perceived Behavioral Control

Intention Behavior

beliefs which are perceived usefulness and perceived ease of use, instead of several individual salient beliefs to determine the attitude towards a given behavior Davis defined perceived usefulness as individual perspective about using a particular system would enhance his or her job performance Perceived ease of use was defined as individual perspective about using a particular system would be free of physical and mental effort He thinks those two beliefs was enough for predicting individual attitude toward the use of a system Both of these beliefs were influenced by system design characteristics which are X1, X2, and X3 in the figure below

Figure 2.3: Original TAM proposed by Fred Davis(Davis,1985,p.24)

Davis, Bagozzi, and Warshaw (1989) tested the model above and they recognized that perceived usefulness had great influence on people’s intention and perceived ease of use had a small but significant influence on people’s intention The most important finding is that both perceived usefulness and perceived ease of use influenced behavioral intention directly Thus the final version of TAM model eliminated the need for the attitude construct from the model

User Motivation

X1

Perceived Usefulness

Perceived Ease of Use

Attitude Toward Using

Actual System Use X2

X3

Figure 2.4: Final version of TAM(Venkatesh&Davis,1996,p.453)

2.3 Antecedents of Online Purchase Intention

Based on TRA, TPB, TAM, and prior studies, this study propose that perceived usefulness and perceived ease of use influence purchase intention directly Social influence and trust influence purchase intention indirectly via mediator perceived usefulness Technology characteristics influence purchase intention indirectly via mediator perceived ease of use Following section will discuss about why those factors should be chosen to be the main antecedents of online purchase intention

2.3.1 Perceived Usefulness

Perceived usefulness refers to the individual’s beliefs about the usefulness of purchasing on retail websites (Guritno and Siringiringo, 2013) They also proved that perceived usefulness has a direct influence on intention to use Internet and it has stronger effect on shopping

intention than perceived ease of use Perceived usefulness is the degree to which a person believes that using internet system will enhance his/her purchasing performance In case of e-retailing, perceived usefulness is a consumer’s subjective probability thinking that Internet usage will efficiently smoothen the progress of purchase (Koufaris and Sosa, 2004) Potential consumers would want to engage in retail websites which are practical and capable to enhance their purchasing performance in searching desired products or services (Chui et al., 2005) The

External

Variables

Perceived Usefulness

Behavioral Intention

Actual System Use Perceived

Ease of Use

potential consumer can like or dislike engaging in online purchasing based on whether the tradeoff is beneficial to the potential consumer as opposed to other types of retailing (Ramayah and Ignatius, 2005) Ramayah and Ignatius (2005) believes that usefulness will attract online consumers The belief is in line with Davis (1989) who defines perceived usefulness as

consumers’ perspective about increasing their performance In e-retailing context, the

performance would be the benefits of purchasing a product through a retailing website minus the tradeoff of a physical retailing In the past, Koufaris (2002) also have validated that

perceived usefulness influence the intention of potential online consumers directly

Additionally, Agarwal and Prasad (1999), Chau and Hu (2001), Moon and Kim (2001) also proved that perceived usefulness influence behavioral intention positively and significantly

In Vietnamese e-retailing market, it indicates that perceived usefulness has strong

impact on purchase intension (Ngo, 2013; Ho and Chen, 2013) Ngo (2013) prove that

perceived usefulness influences purchase intention directly studying about factors influencing consumer online purchase intention of fashion in Vietnam – the case of Zalora In another study, Ho and Chen (2014) proved that technology beliefs, which are represented by perceived usefulness affect purchase intention indirectly through technology attitudes when studied about Vietnamese consumers’ intention to use online shopping Their research result shows that perceived usefulness is the strongest predictor for Vietnamese consumers’ intention to shop online Ho and Chen (2014) believes that Vietnamese consumers’ intention to adopt online shopping as a shopping medium is firstly explained by perceived usefulness of their own using

In another word, the higher consumer’s perceived usefulness of online shopping is, the stronger their technology attitudes are, then they become ready to adopt online shopping as a shopping medium In the first phase of being contact with online shopping, shoppers prefer to something new If they see immediate benefits of this shopping channel, they will accept it as a shopping channel

Following previous studies, it’s reasonable to propose that:

H1: Perceived usefulness has a positive relationship with consumers’ online purchase intention

2.3.2 Perceived Ease of Use

According to Davis (1989), perceived ease of use refers as the degree to which and individual believes that using a particular system would be free of effort He stated definition about

perceived ease of use in broad context which can be understood in any fields Chiu et al (2005) provided specific definition in e-retailing field as the degree of how consumers believe that retail websites can help them to search information with less effort Thus, purchasing goods via internet should not take much effort The process of purchasing should be done by just a click for online shoppers to engage in online shopping In the e-retailing context, the dimensions ease of use refers to the ease of ordering, functionality, navigation of website, and accessibility

of information (Reibstein, 2002) Consumers will prefer to visit a website with good quality web design rather than a complicated and ambiguous websites A good quality web design will increase customer satisfaction which leads to a higher online purchase intention (Lee & Lin, 2005) On the other hand, if users perceive that a website is difficult to use or complicated and ambiguous, they will show a lower intention on purchasing (Green, Pearson, & Pearson, 2007) Poorly designed forms would cause consumers to lose focus on their shopping carts In another words, it will reduce perception on the ease of use of online shopping and the consumers will develop a negative attitude In turn, it will make potential consumers do not want to engage in internet shopping (Ramayah and Ignatius, 2005)

Conventional shopping usually causes anxious, crowded, traffic jam, limited time, and parking space (Yulihasri, Islam, and Daud, 2011) Purchasing via retail websites is surmised to have beneficial outcomes, but the hassle of engaging in the interaction medium lead to daunt for some consumers (Ramayah and Ignatius, 2005) If the hassle is outweigh the benefit of purchasing online, then the consumers will prefer to purchase in conventional way If a website has a well-designed user interface, consumers are likely to believe that online shopping is easy

According to Jun et al (2004) and Honarbakhsh et al (2013), perceived ease of use influences the consumers’ purchase intention in e-retailing context

E-retailing purchase intention has been studied in Vietnam Ho and Chen (2013), Ngo (2013) explore that perceived ease of use has great influence on purchase intention Ngo (2013) studies about factors influencing consumer online purchase intention of fashion in Vietnam – the case of Zalora and found out that perceived ease of use is the strongest factors influence purchase intention directly among product and company attributes, and perceived usefulness factors Ho and Chen (2013) considers perceived ease of use as a component of technology belief which influence purchase intention indirectly via mediator technology attributes They believe that once online buyers have good understanding and knowledge about Internet, they will be more actively applying such knowledge to their online shopping Generally, with a simple performance and implementation without any obstacles, consumers will have a positive attitude towards online shopping Then, they will be confidence to use that technology to make online transaction After reviewing international research and Vietnamese e-retailing studies, it’s reasonable to propose that:

H2: Perceived ease of use has a positive relationship with consumers’ online purchase intention

2.3.3 Trust

Trust is considered as a set of specific beliefs about the benevolence, competence, and integrity

of another party Benevolence is the belief that the trustee will not act against the trustor even

in case of given the opportunity Competence is the belief in the trustee’s ability to fulfill the obligations as the trustor expected Integrity is the belief that the trustee will be honest and will honor its commitments (Mcknight et al 2002) In additional, Gefen (2003) proposed that trust refers to an expectation that trustee will not behave opportunistically and/or will take advantage

of trustor in any situation If an e-retailing vendor can’t be trusted in accordance with the

consumers’ expectation, then there is no reason for consumers should expect to gain any

benefit from that vendor (Pavlou, 2003; Gefen, 2004; Chiu, 2009) According to Hoffman et al (1999), a lack of trust will prevent buyers from engaging in e-retailing because they are

implausible to transact with a vendor who fails to convey a sense of credibility It’s mainly because of fears of seller opportunism If consumers initially trust an e-vendor and observe that adopting online shopping is beneficial to shopping effective and performance, then they come

to believe that online shopping is useful for them (Gefen et al., 2003) Indeed, many previous researches shows that trust play a crucial role in driving perceived usefulness (Gefen et al., 2003; Pavlou, 2003)

Ho and Chen (2013) point out that consumers’ trust in online shopping plays a critical role and prerequisite influencing on consumers’ intention to participate in online shopping when studying about Vietnamese consumer’s intention to online shopping adoption The

research result shows that the higher the reputation, the higher gain in case of favorable

behavior and the more certain online consumers about the e-vendor will not act

opportunistically Especially, when consumers do not have personal experience with an vendor, the word of mouth about the reputation of a merchant is a key to attract them to make transaction with that business The shared information from ones who interact with the online providers positively can help in reducing perception of risk and security issue of online buyers when they make transactions with those providers The reputation of online provider is the basis to form the initial trust of an e-commerce purchase Moreover, when buyers actually have experience in online shopping, their faith will be created base on their experience or their

e-familiarity with the purchased goods The experience and e-familiarity are two factors that help buyers to reduce the uncertainty in transactions When making online transaction, usually the buyers cannot sure if the transaction can be risky and it is possible for damages to be recovered Hence, while making online transaction with e-vendors, the buyers are interested in ones who are competence, benevolence, and integrity Lee and Ngoc (2010) also find out that trust exerts significant influence on online shopping behaviorand online shopping intention

wheninvestigating about the online shopping intention of Vietnamese students Following previous studies, it’s reasonable to propose that:

H3: Trust has a positive relationship with perceived usefulness

2.3.4 Social Influence

The circle of individual social life comprises his or her peers who are siblings, friends and acquaintances (Pilgrim, 2001) The concept of reference groups is very important in

understanding consumer purchasing behavior as an individual adapts his/her habits according

to his/her belonging groups He/she complies intentionally or unintentionally with the dominant traits of the peers and forms his/her own traits (Clasen and Brown, 1985) According to

Ventakesh and Davis (2000), consumers usually take their family or peer’s opinion with initial experience to evaluate information to judge online shopping sites An individual is more like to make online purchase more if his/her social groups desire to do online shopping

Besides social groups, social media also contribute a strong impact on consumers online purchasing through attractive advertisements and social networking sites Social networking sites provide a platform for people to connect with friends, family, and acquaintances On social networking sites, individual can conduct online social networking activities and send products’ recommendation to their social network groups It also allows retailers to leverage consumers’ connections for commerce purposes, advertise, and promote their brands/products E-retailing can also manage interaction with consumers directly in an open environment and sharing economy (Ng, 2012) This kind of social networking can understand as social influence

in this study

Social recommendation gives advises for individual, so it makes social commerce to be

a trusted environment of which prospective consumers make buying decision based on the advice of a network friends and family (Lietsala&Sirkkumen, 2008) Peers’ opinions make significant impact on technology usefulness as Lin et al (2003) studied about digital

government system The result of their study proved that social influence affect perceived usefulness directly on technology acceptance

A recent study about Vietnamese consumer’s intention to online shopping adoption, Ho and Chen (2013) explored that consumers tend to rely on opinions of reliable people such as relatives, friends, colleagues as well as the previous online buyers for searching information and select goods for making a transaction Research results indicate that most consumers

participate and get certain understanding about online shopping through their friends and

relatives The assessment of previous buyers is a valuable reference for consumers to make an appropriate decision on a product selection and implementation of online transactions From analyses above, it can be seen that social influence is a key factor having significant influence one participation of consumers in e-retailing

In e-retailing field, it’s reasonable to propose that:

H4: Social influence has a positive relationship with perceived usefulness

2.3.5 Technology Characteristics

Because of the important of perceived ease of use, many e-vendors have been trying to improve website graphical user interfaces to be user-friendly (Venkatesh, 2000) Lederer et al (2000) pointed out that factors relating with the quality of information can be found on a website, and the quality of information can be understood influence website perceived ease of use They consequently identified those two factors influence perceived ease of use directly

Quality of information finding is the notion about a website should be easy to navigate and easy to return to previous display pages Individual can determine his/her location on a website without effort For individual without prior internet experience, navigating through a website should not be a daunting task if the website is considered as ease of use (Brown, 2002)

Quality of information understanding reflects a need for a website to be understandable and consistent graphics and terms Content of a website includes text, pictures, layout, sound, and motion which is a main factor that contribute to repeat consumers visit (Rosen &Purinton, 2004) The website should be visually readable, consistent in graphics and terms It should provide a link for more information for subject at hand (Brown, 2002)

The purpose of an e-retailing website is to attract potential consumers’ attention to visit products and services on the web (Smith, 2004) Website representation will get potential

consumers to be initially drawn in, but the website content is still the critical issue in online purchase Fancy design and representation can only draw potential consumer at initial stage but without good valuable content, consumers might likely to browse somewhere else (Sam et al., 2009) Generally, good technology characteristics provide a richer media influencing user’s involvement

Hence, it’s reasonable to propose that:

H5: Technology characteristics has a positive relationship with perceived ease of use

2.4 Conceptual Framework

This study adapted literature review of Technology Acceptance Model (TAM) and develop it to fit with e-retailing context Based on TAM model, this study considers perceived ease of use and perceived usefulness as main factors that influences purchase intention directly By

reviewing TRA, TPB, and other prior studies, this research proposes that trust and social

influence are two main factors that influence perceived usefulness Technology characteristics influence perceived ease of use

Figure 2.5: Online purchase intention model

Purchase intention H1

H2

H5

H3

H4

H1: Perceived usefulness has a positive relationship with consumers’ online purchase intention H2: Perceived ease of use has a positive relationship with consumers’ online purchase intention H3: Trust has a positive relationship with perceived usefulness

H4: Social influence has a positive relationship with perceived usefulness

H5: Technology characteristics has a positive relationship with perceived ease of use

2.5 Chapter Summary

This chapter reviews foundation theoretical model TRA, TPB, TAM and other studies to figure out which factors play crucial role in influencing consumers’ purchase intention Based on TAM, this studies suggest that perceived usefulness and perceived ease of use are two main factors that influence consumer purchase intention directly Reviewing other prior studies, TRA, and TPB, this studies propose that trust and social influence are two main factors that influence purchase intention indirectly via perceived usefulness Technology characteristics influence purchase intention indirectly via perceived ease of use

In order to verify proposed hypotheses, questionnaires were constructed based on prior studies and modified to fit with research context After having questionnaires, research design was performed to collect data for analyzing Questionnaires were sent out to 52 people via email who were really committed to take the survey to test the reliability of the questionnaires After analyzing the reliability and exploratory factor analysis, questionnaires were modified to develop main survey The main survey was then conducted via email and in person in order to get enough data for analyzing The main survey was designed in Google form and sent out for friends, colleagues, relatives, classmates to take the survey, but the data still was not enough The main survey then was conducted in person by printing out and handing out to ISB students

in UEH Ho Chi Minh City After having enough data, the data was analyze its reliability, exploratory factor, and multiple regression by using SPSS software The analyzing result was then drawn conclusion and recommendation

Figure 3.1: Research Process

Introduction

Research Problem Research Objective Research Scope

Literature Review

Research Model Hypotheses

Instruments design and Data Collection

Questionnaires design Quantitative pilot (n = 52) Main survey

Data Analysis

Descriptive Reliability (Cronbach’s alpha) Validity (EFA)

Hypothesis testing

Conclusion and Recommendation

3.2 Measurement Scales

The questionnaire part consisted of 30 multiple choice questions in which five personal

questions, two general questions, and 23 online shopping experience related questions The questionnaires were developed from prior studies for consistency All measurements in the questionnaire adopted the five Likert-scales, where 1="strongly disagree" and 5 = "strongly agree" for all online shopping related questions See more detail in Appendix A

Purchase intention is taken from Chengetal.(2012)

1 I would use online purchasing for my needs

2 I will return to online purchasing site in the future

3 I will suggest others to make online purchasing

Perceived usefulness is taken from Chengetal.(2012)

1 The online purchasing (OP) enables me to save money

2 The OP makes it easier for me to obtain goods

3 In find OP useful in conducting purchase transactions

4 Overall, I find OP to be advantageous

Perceived ease of use is taken from Chengetal.(2012)

1 Using the OP service is easy for me

2 I find my interaction with the OP service clear and understandable

3 It is easy for me to become skillful in the use of the OP services

4 Overall, I find the use of the OP service easy

E-trust is taken from ShiauandLuo (2012)

1 The OP gives me a feeling of trust

2 I have trust in OP vendors

3 The OP gives me a trustworthy impression

Social influence is taken from Chengetal.(2012)

1 Most of my friends and colleagues believe that shopping online is good and convenient

2 I’m influenced by social media when making decision

Technology characteristics are taken from Brown (2002)

1 Web allows easy to return to previous display pages

2 I can determine my position within Web

3 Web is easy to navigate

4 Web uses consistent terms

5 Web uses understandable terms

6 Web display page provide links to more detailed information

7 The Web displays pages are easy to read

Pilot test:

The pilot was sent out to 52 people who are friends, relatives, classmates, and colleagues via email and in person After having the data, reliability analysis was conducted to test the data reliability Table 3.1 indicated that the result was quite good since all Corrected Item values were above 0.5 and all Cronbach’s alpha values were above 0.7 except social influence had Cronbach’s alpha value of 699 which was not bad According to Pallant (2005), the

measurements were reliable if Cronbach’s alpha coefficient of each measurements is equal to

or greater than 0.7 and those items with the value of Corrected Item-to-total Correlation should

be greater than 0.3 After analyzing the pilot data and having good result, questionaires then sent out to the target group

Construct Items Corrected Item Cronbach’s alpha

Technology

Characteristics

TC1 TC2 TC3 TC4

0.550 0.557 0.647 0.627

0.853

TC5 TC6 TC7

0.712 0.603 0.628 Social Influence SI1

0.679 0.710 0.594

0.791 0.784 0.750 0.763

0.895

Perceived

Usefulness (PU)

PU1 PU2 PU3 PU4

0.627 0.557 0.511 0.555

.758

Purchase

Intention (PI)

PI1 PI2 PI3

.675 544 589

.764

Table 3.1: The Results of the Reliability Test (Pilot)

3.3 Data Collection Method

3.3.1 Sample & Sample size

The target population of this study is students and professional According to Hair et al (1995), the minimum sample size should be greater than five time of independent variable and not less than 100 Hence, the sample size for this study should be at least 115 (5*23) Tabachnick and Fidell (2001) required to have minimum sample size for the multiple Regression is n = 50 +8m where m is number of independent variables In this study, there are 5 independent variables, so the sample size should be 90 Overall, the sample size should be at least 115

3.3.2 Data Collection Process

The main survey was launched on August 12th, 2014 and completed on September 12th, 2014 Survey invitation was sent out to 431 people by email and hard copies

I sent out to 86 participants on the web and just got only 52 feedbacks Data from 52 people was not large enough for the analysis, so I have to do offline survey I printed out the survey and hnded out for students at University of Economic Ho Chi Minh to fill it out By using this method, I got 138 completed responds and but 10 uncompleted responds which were not

qualified for analyzing Therefore, I have 180 questionnaires were valid data, where visitor volume was 270 and the number of respondent answers was 180 with the filling-in rate of 67.41%

3.4 Data Analysis Method

The collected data was analyzed by using Statistical Package for Social Science (SPSS)

software which could enable to do descriptive analysis, Cronbach Alpha Reliability Analysis, Exploratory Factor Analysis (EFA), and Multiple Regression Analysis

3.4.1 Descriptive Analysis

Descriptive analysis was used to describe general view of the data in this study In this study, there were lots of measures and a large number of people on a measure Descriptive analysis generated simple summaries about the sample and the measures Each descriptive statistic reduced lots of data into a simpler summary Together with simple graphics analysis, it formed the basis of virtually every quantitative analysis of the data

3.4.2 Reliability Analysis

Cronbach’s alpha reliability analysis method was used to test the reliability of the

measurements The measurements were reliable if Cronbach’s alpha coefficient of each

measurements is equal to or greater than 0.7 (Pallant, 2005) Besides, those items with the value of Corrected Item-to-total Correlation less than 0.3 should be discarded to improve reliability level of the measurements

3.4.3 Exploratory Factor Analysis

Exploratory factor analysis was used to explore the interrelationship among a set of variable to identify the number of underlying factors Principle Axis Factoring and Promax rotation

technique were used to extract the factors The data was strong if it met following conditions (Pallant, 2005):

- The sample size should be enough In this study, it should be at least 115

- Factor analysis was appropriate if:

 The Kaiser-Meyer-Olkin value (KMO) should be 0.5 or above

 The Bartlett’s test of sphericity should be statistically significant: p < 0.05

- The number of factors were determined if:

 The components have an eigenvalue of 1 or more

 The total variance explained by these component should be above 50%

 Factor loading criteria should be 0.5 or more to ensure practical significant

3.4.4 Multiple Regression Analysis

Multiple linear regression was used to test the research model and hypothesis According to Pallant (2005), the assumptions of multiple regression are:

- The sample size should be enough: n > 50 + 8m (m: number of independent variables)

- No multi-collinearity is found

- No outliers are found or in case there are, no significant impact of outlier is found

- Normality and linearity should exist

The assumptions should be test before conducting multiple regression analysis

R-square explained how much of a variance in the dependent variable was explained by the model

3.4.5 Testing Mediation with Regression Analysis

Mediation is a hypothesized causal chain in which one variable affects a second variable that,

in turn, affects a third variable as Figure 3.2 below The intervening variable, M, is the

mediator It “mediates” the relationship between predictor X and an outcome Y Path a and path b are direct effects Path c’ is indirect effect between X and Y through mediator M

X M Y

Figure 3.2: Mediation Relation

Testing mediation with regression analysis was performed by four steps in which several regression analyses conducting and significance of coefficients examining (Baron and Kenny, 1986)

Step 1: Conduct a simple regression analysis with X predicting Y to test for path c alone Sept 2: Conduct a simple regression analysis with X predicting M to test for path a Step 3: Conduct a simple regression analysis with M predicting Y to test for path b alone

Step 4: Conduct a multiple regression analysis with X and M predicting Y

The purpose of Steps 1-3 is to establish that zero-order relationships among the variables exits If one or more of these relationships are not significant, then mediation is not possible are likely If these relationships are significant, the Step 4 is processed In the Step 4, some form of mediation is supported if the effect of M (path b) remains significant after controlling for X If

X is no longer significant when M is controlled, the finding supports full mediation If X is still significant, the finding supports partial mediation

In this study, the coefficient of indirect effect is calculated by multiplying two

regression coefficients (Sobel, 1982) The first coefficients is the partial regression effect for M predicting Y, B2, and the second coefficient is the simple coefficient for X predicting M

After the regression coefficient for the indirect effect was calculated, significance

needed to be tested Statistic test for mediation effect was calculated by dividing the products

of paths a and b by a standard error term (Barron & Kenny, 1986)

+ Where a and b were unstandardized regression coefficients and sa and sb were their standard errors