1

Repurchase intention in C2C e-commerce –

A Taobao experience

BY

Chan Ka Leung, Donald

11001631

Information Systems and e-Business Management

An Honours Degree Project Submitted to the

School of Business in Partial Fulfillment

of the Graduation Requirement for the Degree of

Bachelor of Business Administration (Honours)

Hong Kong Baptist University

Hong Kong

April 2013

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Acknowledgment

I would like to take this opportunity to express my sincere gratitude to my supervisor, Dr.

CHOW, Vincent W S, for his supervision and guidance. During our meetings each time,

his priceless opinions and supports provide me practical insights to this project, his point

of view always broadens my thinking and his encouragement makes me feel confident to

overcome different challenges.

Furthermore, I would like to express my thankfulness to all the people who have helped

me to fill in the questionnaires. Without their help, I may not have enough sample size to

continue my research analysis.

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Abstract

Online shopping becomes more and more popular nowadays and Taobao is one of the

popular websites that provides C2C e-commerce service. The entry barrier of online

business is low and there are thousands of new shops opened in Taobao every day. To

face this intense competition, sellers in Taobao should perform well in relationship

quality in order to survive in this e-marketplace. Previous research has discussed the

relationship between online relationship quality and online repurchase intention, however,

the study only focused in B2C context. In this study, C2C e-commerce will be examined

in this topic.

The research model is comprised with 3 groups of factors that many influence customer

online relationship quality. They are seller characteristics, seller behavior and consumer

personality. For the seller characteristics, perceived website usability, perceived expertise

in order fulfillment and perceived reputation are examined. For the seller behavior,

distrust in seller behavior is studied. For the consumer personality, it includes consumer

disposition to trust. To test the model this study developed, online research were

conducted and 131 usable questionnaires are successfully collected through the Internet.

The result findings have suggested that online relationship quality is the significant factor

of online repurchase intention in Taobao. Moreover, perceived reputation is the only

significant factor of online relationship quality in C2C context. Perceived website

usability, perceived expertise in order fulfillment and consumer disposition to trust are

not viewed as a significant predicator to online relationship quality. The results also

showed there is a negative relationship between distrust in seller behavior and online

relationship quality.

Based on these research results, implications of these findings are discussed. After that,

some practical suggestions and recommendations for the sellers in Taobao are provided.

Sellers in Taobao are recommended to work hard in building high reputation. In addition,

the study provides some suggestions for further research on the relationship between

online relationship quality and online repurchase intention.

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Contents

1. Introduction………………………………………………………………..……………6

1.1 Background……………………..………………………………6

1.2 Objective………………………………………………………..7

2. Literature Review……………………………………………………………………….9

2.1 Relationship quality…………………………………………….9

2.1.1 Website usability………………………………….…….………9

2.1.2 Expertise in order fulfillment………………...…………………9

2.1.3 Reputation………………………………………………..……10

2.1.4 Distrust………………………………………………...………10

2.1.5 Consumer disposition to trust…………………………………10

2.2 Online repurchase intention………………….…….…….……10

3. Research Model and Hypotheses……………………………………………………...12

3.1 Online relationship quality…………………………………….14

3.2 Seller characteristics………………………………….……….14

3.2.1 Perceived seller’s website usability…………………….……..14

3.2.2 Perceived seller expertise in order fulfillment…….......………15

3.2.3 Perceived seller reputation…………………………………….15

3.3 Seller behavior……………………………………...…………16

3.3.1 Distrust in seller behavior……………………………………..16

3.4 Consumer personality………………………………………....16

3.4.1 Consumer disposition to trust…………………………………16

4. Research Methodology…………………………………………………………….….18

4.1 Measurement…………………………………………………..18

4.2 Design of questionnaire……………………………………….22

4.3 Data collection………………………………………………...22

4.4 Survey response………………………………………….……23

5. Data Analysis and Results……………………………………………………………..25

5.1 Measurement model……………………………………...……25

5.1.1 Convergent validity………………………………………...….25

5.1.2 Discriminant validity…………………………………….……28

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5.2 Structural model……………………………………………….29

6. Discussion and Implications…………………………………………………….…….33

6.1 Discussion………………………………………..……………33

6.1.1 Online relationship quality………………………………….....33

6.1.2 Seller characteristics………………………………….……….33

6.1.3 Seller behavior……………………………………………..….35

6.1.4 Consumer personality………………………………………....35

6.2 Implications…………………………………………………....36

6.2.1 Implications for research……………………………………....36

6.2.2 Implications for sellers in Taobao……………………..………37

7. Limitation and Future Research……………………………………………………….39

8. Conclusion………………………………………………………………………….....40

9. Reference…………………………………………………………………………...…41

10. Appendix…………………………………………………………………..…………47

10.1 Appendix A: Questionnaire…………………………………....47

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1. Introduction

1.1 Background

E-commerce refers to a wide range of online business activities, there are three

basic types of e-commerce including B2B, B2C and C2C. B2B e-commerce

describes the business activities between companies; B2C e-commerce describes the

business activities between companies and consumers; C2C e-commerce describes

the business activities between consumers and private individuals, a third party

always involved to facilitate the transactions (Turban et al., 2012).

Basically, to strike for long term success, no matter in which types of

e-commerce, online shop owners not only require encouraging people to purchase

online, but also need to encourage them to repurchase in next time. As a result,

repurchase behavior is essential for online shops to survive on the Internet. It is

more costly and time consuming for online shop to acquire new customers than

retaining current customers. Customer retention is also important in developing

competitive advantage (Tsai & Huang, 2007). Many virtual shop owners understand

that customer retention is a key determinant for success; however, there are only

about 1% of online buyers that are willing to purchase in the previous shop again

(Gupta & Hee-Woong, 2007). Therefore, it is critical to find out what are those

drivers affecting the online customer repurchase intention (Qureshi et al., 2009).

Repurchase intention is a reflection of customer loyalty toward a particular

shop (Harris & Goode, 2004) and this behavior affects the seller’s profit directly.

According to Khalifa & Liu (2007), studies on online customer repurchase behavior

is only developed a short period of time. And there are only few studies had

investigated the customer repurchase behavior in a relationship quality perspective.

As a result, this research is going to examine how relationship quality influences

customer online repurchase intention in C2C context.

Traditionally, different relationship marketing literature suggested that

satisfaction of buyer and trust in the seller are the two key elements in determining

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relationship quality (Zhang et al., 2011). It is suggested that satisfaction is measured

by the buyer evaluation on the seller past performance and trust is the buyer

evaluation on the seller performance in the future. Therefore, to sustain a good and

long term relationship quality, the seller should perform well in the past and also in

future. Research also found that there is a significant relationship between

relationship quality, retaining buyers and increasing buyer loyalty (Palmatier et al.,

2006).

1.2 Objective

Prior researches had studied repurchase intention in C2C auction (Yen et al.,

2008; Xu et al., 2010). However, it seems that there is no previous research studying

repurchase intention in Taobao which is a fast-growing C2C platform. As a result,

this study aims to investigate in this area and focus in online relationship quality

perspective. Previous research had examined the repurchase intention in relationship

quality perspective in B2C context and found that there is a strong relationship

between online customers repurchase and online relationship quality (Zhang et al.,

2011). This study wants to extend the topic from B2C to C2C context and find out

how the formation of customer online relationship quality influences repurchase

intention.

In the recent years, online C2C markets have become extremely popular and

successfully attract many Internet users around the world. The online C2C markets

grow rapidly in many countries especially in China. According to iResearch which is

an Internet market research company in Shanghai, the China online C2C market

sales have increased from $51 million in 2001 to $434 million in 2004. In 2008, the

figures stepped up to $16 billion and it is expected that the sales will reach $55

billion in 2011 (Xu, 2010).

Taobao, one of the leading trading C2C platforms in China, has the highest

number of product listings, volume transactions, registered users and penetration

rate. The C2C market share of Taobao in China is 83.9% (Carol, 2009). In this study,

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the research will focus on Taobao platform to investigate how the online relationship

quality can be contributed to online repurchase intention. To provide some practical

insights to C2C online sellers in Taobao, the study propose to examine different key

antecedents of online relationship quality in order to have a more clear

understanding of why customers intent to repurchase and find out how online

relationship quality affects customer online repurchase behavior in C2C context.

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2. Literature Review

2.1 Relationship quality

There are many prior researches discussing the relationship marketing in

traditional business (Harker & Egan, 2006). Relationship marketing is all the

activities including establish, develop, and maintain relational exchange for the

purpose of generating long term relationship with customers. Previous research has

found that the relationship quality between service providers and customers has

influenced the loyalty of the customers perceived toward the service provider

(Sanchez-Franco et al., 2009). To estimate the relationship quality in the export

market, Lages et al. (2005) had developed a new measurement method called

RELQUAL. Prior research also found that there is a significant relationship between

relationship quality and business customer loyalty in B2B context (Rauyruen &

Miller, 2007). Salesperson characteristics and behavior are considered as two

categories of factors of antecedents of relationship quality (Zhang et al., 2011). The

current study try to focus in C2C e-commerce, therefore, in the online environment

the salesperson is referred to the online seller in Taobao. The following are some

literature reviews of 5 possible influencing factors of online relationship quality:

2.1.1 Website usability

Prior research studied about the usefulness of website usability. According

to the study by Cyr (2008), the design of a website can influence trust and

satisfaction, there is a positive relationship between website usability and

consumer loyalty. Casalo et al. (2008) also suggested that if a consumer is

familiar a website, a relationship between website usability and loyalty is

established to the consumer.

2.1.2 Expertise in order fulfillment

Zhang et al. (2011) suggested that expertise in order fulfillment is

important in establishing long term relationship between buyer and seller.

Moreover, Cao et al. (2003) found that the performance of seller in order

fulfillment influence the customer satisfaction significantly.

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2.1.3 Reputation

Prior research found that reputation is important in reducing risk (Antony

et al., 2006). It is because high reputation can provide evidence that the seller

provided sufficient and trustworthy services for the customers in the past (Kim

et al., 2008). Building reputation is a social process related to past interactions

between buyer and seller (Zacharia & Maes, 2000).

2.1.4 Distrust

For the seller behavior, most of the previous researches about relationship

quality only concerned some positive factors including trust and service level,

to draw a more comprehensive picture of customer relationship quality, Zhang

et al. (2011) included distrust of the vendor behavior as one of the factors that

may influence online relationship quality. Distrust is a significant factor in

influencing online customers’ behavior (Dimoka, 2010).

2.1.5 Consumer disposition to trust

Consumer disposition to trust is a consumer specific antecedent of trust. It

is the customer’s individual trait leading to expectations about trustworthiness

and this trait had a positive effect on consumer trust. (Kim et al., 2008).

Furthermore, Rotter (1971) found that different human has distinct propensity

of trust based their unique past experiences.

2.2 Online repurchase intention

Customer repurchase intention is an important factor for online shops to

success in long term. And some studies found that customer intention to come back

online is positively related to customer loyalty (Jiang & Rosenbllom, 2005). Loyal

customers carry many advantages for the seller as they are willing to spend and buy

more, motivate to search for company news, more resist to opponent actions and

more willing to generate positive WOM (Jiang & Rosenbllom, 2005). The research

result from Jiang & Rosenbllom found that the profit of the seller will increase

25-95% if the customer retention rate increased 5%. They also suggested that

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customer retention is much more important in online context than offline context. It

is because online sellers are more costly to acquire new customers on the Internet

than the traditional channels.

According to the theory of reasoned action, intention is the best immediate

factor in the relationship between attitude and behavior and it is also appropriate to

test the consumers’ behavior (Ajzen & Fishbein, 1980). Many prior researches

studied the customer retention in online context. For example, study of online

consumer retention on the perspective of buying habit and shopping experience on

the Internet (Khalifa & Liu, 2007), study about intention to continue shopping online

by applying technology acceptance model (Koufaris, 2002; Mouakket, 2009) and

study of website stickiness in relationship perspective (Li, et al., 2006). Customer

online repurchase intention is a construct of combination of information system

theory and marketing theory, the customer is both the e-commercial website user

and a consumer (Wen et al., 2006). Therefore, this study aims to examine the

customer repurchase intention in C2C platform comprehensively in relationship

aspect; the study will focus the information system itself (website usability), other

online seller characteristics (perceived expertise in order fulfillment, perceived

reputation), seller behavior (distrust) and consumer personality (consumer

disposition to trust).

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3. Research Model and Hypotheses

In this section, the research model and the related hypothesis will be further

illustrated (Figure 1). The research aims to explain the relationship between customer

repurchase intention and online relationship quality in Taobao – a famous C2C platform.

The model is comprised with 3 groups of factors, including seller characteristics, seller

behavior and consumer personality. For the seller characteristics, it includes perceived

website usability, perceived expertise in order fulfillment and perceived reputation. For

the seller behavior, it includes distrust in seller behavior. For the consumer personality, it

includes consumer disposition to trust. The main predictors of this model are the online

relationship quality and the perceived website usability.

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Figure 1 Research model

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3.1 Online relationship quality

The relationship between buyer and seller can be regarded as good quality

when buyers feel satisfied and trustworthy in the past communication between the

buyer and seller (Zhang et al., 2011). And it is expected that the further

communication between the buyer and seller is also positive because the previous

positive interaction. Thus, the research purposes that:

H1. Online relationship quality is positively related to customer online repurchase

intention.

3.2 Seller characteristics

3.2.1 Perceived seller’s website usability

When people conduct online shopping, they find the product information

and make payments by accessing a website, therefore, a good website should

contain sufficient information of products for consumers (Yoon, 2002).

Moreover, research found that online buying experience can be improved by

providing a website with good usability to consumers and there was a positive

relationship between consumer loyalty and website usability design

(Chakraborty et al., 2002; Flavian et al., 2006). Thus, the research purposes

that:

H2. Perceived website usability is positively related to online repurchase

intention.

The customers’ perception towards the shopping website is better when

the perceived website usability is high (Zhang et al., 2011). Prior research

suggested that there is a significant relationship between perceived website

usability, customer satisfaction and trust (Zviran et al., 2006). Casalo et al.

(2008) also conducted the study of the role of perceive usability on the

formation process of website loyalty. The result of the research found that the

perceived website usability is positively related to customer satisfaction. As a

result, the research purposes that:

H3. Perceived website usability is positively related to online relationship

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quality.

3.2.2 Perceived seller expertise in order fulfillment

Previous research found that order fulfillment is one of the critical

characteristic of the online vendor (Cao et al., 2003). However, this research is

focused in B2C context, but not in C2C e-commerce. The current study aims to

examine the customer perception in online order fulfillment process in C2C

context in order to see whether there is a positively relationship between

perceived expertise in order fulfillment of C2C seller and online relationship

quality. In addition, Prior research stated that if you want to be successful in

e-commerce, it is vital for the vendor to show the expertise in order fulfillment

to customers (Torkzadeh & Dhillon, 2002). Zhang et al. (2011) suggested that

when the online vendor performs well in order fulfillment process, the

customers probably believe that the vendor has the ability and expertise in

order fulfillment and the customers is confident that he can receive the product

required on schedule. Therefore, it is important for the online seller to ensure

that he/she can provide the products to buyer in expertise after the online buyer

has paid. The consequence is that it can help the seller to build a long term

relationship with the buyer if the online seller can provide high quality service

in order fulfillment. As a result, the research purposes that:

H4. Perceived seller expertise in order fulfillment is positively related to

online relationship quality.

3.2.3 Perceived seller reputation

In Koufaris & Hampton-Sosa (2004) previous study, they suggested that

there are different elements in vendor reputation including customers

perceptions of the vendor’s public image, innovativeness, quality of product

and service and commitment to customer satisfaction. Customers can therefore

evaluate the online seller reputation based on the above elements. Reputation is

comprised with equity and credibility. Equity is the value of the seller website

and credibility is the perceived trustworthiness of the seller. It is difficult for the

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seller to maintain trustworthiness and many researches had already shown that

reputation is a critical factor of establishing trust for online sellers (Zhang et al.,

2011). Moreover, customers are more willing to trust a seller with a good

reputation because the seller probably would not risk their reputation and

provide insufficient services to the buyer. All in all, the research purposes that:

H5. Perceived seller reputation is positively related to online relationship

quality.

3.3 Seller behavior

3.3.1 Distrust in seller behavior

Trust in seller behavior is a hit research topic; however, the research on

distrust is also becoming more popular in the recent years (Dimoka, 2010). The

implication of distrust in seller behavior is that the seller cannot meet the

expectation of the buyer (Zhang et al., 2011). For example, the product

delivered to the customers is in poor quality or the seller failed to satisfy the

need of the buyer in order fulfillment process. In the current research, the

relationship between distrust in seller behavior and online relationship quality

is being assessed. Thus, the research purposes that:

H6. Distrust in seller behavior is negatively related to online repurchase

quality.

3.4 Consumer personality

3.4.1 Consumer disposition to trust

Consumer disposition to trust is used to display faith in humanity and to

adopt trusting with others (Gefen, 2000). If a consumer is high in disposition to

trust, it means that he/she is probable to trust others and this disposition is also

likely applicable in buyer and seller relationship (McKnight et al., 1998; Rotter,

1971). On the other hand, if a consumer is low in disposition to trust, it means

that he/she has low tendency in trusting others (McKnight et al., 1998; Rotter,

1971). This tendency is probable to include the online seller when conducting

transaction in Internet and eventually affect the relationship quality negatively.

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Previous research mentioned that each individual has different personal

experiences, personality and also cultural background, so every person has

different attitude toward disposition to trust, this tendency or individual traits is

the result of the ongoing lifelong experiences and socialization but not the

experience of a particular party (Fukuyama, 1995; McKnight et al., 1998;

Rotter, 1971). As a result, the research purposes that:

H7. Consumer disposition to trust is positively related to online repurchase

quality.

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4. Research Methodology

4.1 Measurement

To investigate the customer repurchase intention in C2C platform in

relationship perspective, a structured questionnaire will be used for data collection

and the majority of the constructs have been adopted in previous literature so that

the validity of the study can be enhanced. In the study, the model contains 8

constructs (Table 1). Multi-item measures are used that the constructs are measured

by few number of items so that to ensure the reliability and also the validity.

Previous research suggested that online relationship quality was conceptualized

as a second-order factor containing satisfaction and trust (Zhang et al., 2011).

However, as second-order model is quite complicated and difficult for an

undergraduate student to handle, so the project supervisor suggested that first order

factor is used in this study. The constructs “Trust” and “Satisfaction” are comprised

with number of questions. And the mean value of thus questions is calculated

correspondingly and used in measuring online relationship quality.

A 7-point Likert scale will be used in the study, (1) is represented to “strongly

disagree” while (7) is represented to “strongly agree”. A clear guideline is included

in the questionnaire. Before answering the question, the participants were asked to

first think of a seller in Taobao (not including Tmall) that they had purchased online

recently and then participants can rate the questions accordingly based their

preference.

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Table 1 Model measurement items

Construct Original Question Reference Designed Question Item

Online

relationship

quality

(Satisfaction)

1. Overall extremely

dissatisfied/overall extremely

satisfied

2. Overall extremely

displeased/overall extremely

pleased

3. My expectations were not met at

all/my expectations were exceeded

Qureshi et

al. (2009)

1. My shopping experience with

this seller is extremely satisfied.

2. My shopping experience with

this seller is extremely pleased.

3. My expectations were exceeded

in the purchase process.

S1

S2

S3

Online

relationship

quality

(Trust)

1. I believe that this vendor is

consistent in quality and service

2. I believe that this vendor is keen

to fulfill my needs and wants

3. I believe that this vendor is

honest

4. I believe that this vendor wants

to be known as one that keeps

promises and commitments

5. I believe that this vendor has my

best interests in mind

6. I believe that this vendor is

trustworthy

7. I believe that this vendor has

high integrity

8. I believe that this vendor is

dependable

Qureshi et

al. (2009)

1. This seller is consistent in quality

and service.

2. This seller is keen to fulfill my

needs and wants.

3. This seller is honest.

4. This seller wants to be known as

one that keeps promises and

commitments.

5. This seller has my best interests

in mind.

6. This seller is trustworthy.

7. This seller has high integrity.

8. This seller is dependable.

T1

T2

T3

T4

T5

T6

T7

T8

Online 1. Likelihood/probability that you Qureshi et 1. I will likely purchase online from ORI1

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repurchase

intention

will purchase online from the same

vendor in the medium term

2. Likelihood/probability that you

will purchase online from the same

vendor in the long term

3. I will never purchase from the

same vendor again

al. (2009) the same seller in the medium term.

2. I will likely purchase online from

the same seller in the long term.

3. I will never purchase from the

same seller again.

ORI2

ORI3

Perceived

website

usability

1. Extremely difficult/easy to use

2. Extremely

unprofessional/professional

3. Extremely poorly organised/well

organised

4. Extremely poor/excellent breadth

of product/service selection

5. Extremely poor/excellent

description of product/service

selection

6. Extremely difficult/easy to

navigate

7. Extremely difficult/easy to find

information that I want

8. Extremely difficult/easy to

conduct online shopping

Balabanis &

Reynolds

(2001)

Chakraborty

et al. (2002)

Yoon (2002)

1. This seller’s website is extremely

easy to use.

2. This seller’s website is extremely

professional.

3. This seller’s website is extremely

well organized.

4. This seller’s website has

extremely excellent breadth of

product selection.

5. This seller’s website has

extremely excellent description of

product selection.

6. This seller’s website is extremely

easy to navigate.

7. This seller’s website is extremely

easy to find information that I want.

8. This seller’s website is extremely

easy to conduct online shopping.

PWU1

PWU2

PWU3

PWU4

PWU5

PWU6

PWU7

PWU8

Perceived

expertise in

order

fulfillment

1. I believe that this vendor has

knowledge and expertise in

distribution (i.e. how to deliver

products/services)

2. I believe that this vendor has

efficiently integrated all necessary

Qureshi et

al. (2009)

1. This seller has knowledge and

expertise in distribution. (i.e. how to

deliver products)

2. This seller has efficiently

integrated all necessary processes

that are needed to deliver products.

PEOF1

PEOF2

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departments/systems that are

needed to deliver products or

services

3. I believe that this vendor has an

efficient system for processing

orders received

3. This seller has an efficient system

for processing orders received.

PEOF3

Perceived

reputation

1. Poor/excellent public image

2. Not/extremely committed to

customer satisfaction

3. Not innovative at all/extremely

innovative

4. Products and/or services are

extremely poor/excellent

5. Has an extremely poor/excellent

reputation.

6. Extremely unreliable/reliable

Qureshi et

al. (2009)

1. This seller has excellent public

image.

2. This seller is extremely

committed to customer satisfaction.

3. This seller is extremely

innovative.

4. Products and/or services provided

by the seller are extremely

excellent.

5. This seller has an extremely

excellent reputation.

6. This seller is extremely reliable.

PR1

PR2

PR3

PR4

PR5

PR6

Distrust in

seller

behavior

1. I believe that this vendor could

sometimes fail to deliver

product/service as and when

promised

2. I believe this vendor is

sometimes unable to deliver what

they promise to

3. I believe that this vendor is

sometimes unable to meet

expectations

4. I believe that this vendor

sometimes promises more than they

can deliver

Gefen

(2002)

Torkzadeh &

Dhillon

(2002)

1. This seller could sometimes fail

to deliver product/service as

promised.

2. This seller is sometimes unable to

deliver what they promise to.

3. This seller is sometimes unable to

meet expectations.

4. This seller always promises more

than they can deliver.

DIST1

DIST2

DIST3

DIST4

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Consumer

disposition

to trust

1. I generally trust other people.

2. I generally have faith in

humanity.

3. I feel that people are generally

reliable.

4. I generally trust other people

unless they give me reasons not to.

Gefen

(2002)

1. I generally trust other people.

2. I generally have faith in

humanity.

3. I feel that people are generally

reliable.

4. I generally trust other people

unless they give me reasons not to.

CDT1

CDT2

CDT3

CDT4

4.2 Design of questionnaire

The questionnaire is divided into four parts. The first part is asking the

respondent whether he/she had online shopping experience or not. If the respondent

had no experience in using Taobao for online shopping, the questionnaire will end.

The second part of the questionnaire consist of question that how the respondents

perceive the online C2C purchase process in the past. The 8 constructs are online

repurchase intention, satisfaction, trust, perceived website usability, perceived

expertise in order fulfillment, perceived reputation, distrust in seller behavior and

the consumer disposition to trust. For the third part, it is used to collect the

demographic data of respondents. The last part is optional for the respondents. It is

asking the personal contact of the respondents. A lucky draw is provided for those

who are interested after filling the contact information at the end of this survey.

4.3 Data collection

Web-based questionnaire is used in this study. English version of the

questionnaire is presented on the qualtrics.com for collecting the data. The

questionnaire is delivered on online channel through social networking - Facebook.

Facebook is a popular website for users to share information and photos. A

Facebook event is opened to invite people to participate the web-based research. In

the data collection process, 131 completed responses are successfully collected.

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4.4 Survey response

Out of this 131 completed responses, 17 of them did not have experience in

conducting online shopping in Taobao. As a result, there are 114 responses are

useful for the study including 52% were female and 48% were male. 1% of the

respondents were aged < 18, 71% were aged 18 - 25, 24% were aged 26 - 35 and 4%

were aged 36 - 45. Table 2 summarizes the details of the demographic information.

Table 2 Demographic details of respondents

Measure Items Frequency Percent

Gender Male 55 48%

Female 59 52%

Age < 18 1 1%

18 - 25 81 71%

26 - 35 27 24%

36 - 45 5 4%

Occupation Student 76 67%

Professional 23 20%

Others 15 13%

Monthly Income HK$<5,000 63 55%

HK$5,000 - 10,000 20 18%

HK$10,001 - 15,000 19 17%

HK$15,001 - 20,000 9 8%

HK$>20,000 3 3%

Using Frequency of online shopping in one month 0 - 1 53 46%

2 - 4 47 41%

5 - 7 9 8%

8 - 10 4 4%

>10 1 1%

Using Frequency of Taobao in one month 0 - 1 71 62%

2 - 4 36 32%

24

5 - 7 5 4%

8 - 10 2 2%

>10 0 0%

Year Experience of shopping online <6 months 31 27%

6 - 12 months 34 30%

13 - 24 months 28 25%

25 - 36 months 12 11%

>36 months 9 8%

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5. Data Analysis and Results

The purpose of this part is to test the model and the hypothesis. The current study

follows the measurement model of Zhang et al. (2011), different measurements and

techniques will be used to perform the statistics analysis. This study used Partial Least

Squares (PLS) to perform the testing which is a structural modeling technique to examine

the measurement model and then the structural model.

5.1 Measurement model

For the measurement model, convergent validity and discriminant validity are

examined. Descriptive statistics (mean and SD value) and the loading of different

items were presented in Table 3. Moreover, Table 4 reported the result of

confirmatory factor analysis which was used to examine the composite reliability

(CR) and the average variance extracted (AVE). The measurement model was

examined to ensure the quality of the research data.

5.1.1 Convergent validity

Convergent validity refers to all items measuring a construct actually

loading on a single construct (Campbell and Fiske, 1959). It indicates the

degree to which the items of a scale that are theoretically related to each other

are related in reality. The study first checked the construct loading which was

summarized in Table 3.The loadings lower than 0.7 were being dropped and

only the loadings with value greater than 0.7 were retained and re-examined.

The questions PEOF2, PR1, DIST4 and ORI3 were being dropped. After this

process, all of the items loaded sufficiently and met the recommended value.

26

Table 3 Descriptive statistics

Construct Item Loading t-value Mean SD

Online

relationship

quality

(ORQ)

S 0.96 117.1 5.05 1.03

T 0.96 144.0 5.12 0.89

Online

repurchase

intention

(ORI)

ORI1 0.96 84.29 5.06

1.18

ORI2 0.94 51.89 4.81 1.27

Perceived

website

usability

(PWU)

PWU1 0.79 16.72 5.52

0.83

PWU2 0.77 17.19 5.19 0.90

PWU3 0.76 17.83 5.29 0.89

PWU4 0.73 12.00 5.25 0.88

PWU5 0.70 13.28 5.32 0.83

PWU6 0.79 21.16 5.24 0.80

PWU7 0.80 21.15 5.37 0.77

PWU8 0.73 14.59 5.44 0.78

Perceived

expertise in

order

fulfillment

(PEOF)

PEOF1 0.76 7.606 5.49

0.82

PEOF3 0.93 29.09 5.38 0.70

Perceived PR2 0.86 30.95 5.15

0.93

27

reputation

(PR)

PR3 0.78 20.22 5.11 0.93

PR4 0.84 32.78 5.23 0.87

PR5 0.87 35.31 5.11 0.79

PR6 0.87 22.80 5.14 1.26

Distrust in

seller behavior

(DIST)

DIST1 0.94 52.71 3.87 1.37

DIST2 0.95 58.27 3.74 1.36

DIST3 0.95 111.7 3.85 1.33

Consumer

disposition to

trust

(CDT)

CDT1 0.92 50.99 5.16

1.08

CDT2 0.89 31.24 5.19 0.95

CDT3 0.91 51.58 4.98 0.98

CDT4 0.83 17.27 5.19 0.85

Convergent validity was then assessed by CR and AVE from the measures.

CR is the measure of reliability and internal consistency of the measured

variables representing the latent constructs. If a scale has high reliability, it is

suggested that the scale is homogeneous (Kerlinger, 1986). AVE is a summary

measure of convergence among a set of items representing the latent construct.

The recommended value of CR is 0.70 whether the recommended value of AVE

is 0.50 (Fornell and Larcker, 1981). For the CR, as summarized in Table 4, it

ranged from 0.84 to 0.96 which was above the recommended value. And the

AVE also showed the convergent validity as all the values were ranged from

0.58 to 0.93.

28

Table 4 Result of confirmatory factor analysis

Construct Number of

items

Composite reliability (CR) Average variance extracted (AVE)

ORQ 2 0.96 0.93

ORI 2 0.94 0.89

PWU 8 0.92 0.58

PEOF 2 0.84 0.73

PR 5 0.92 0.71

DIST 3 0.96 0.89

CDT 4 0.94 0.78

5.1.2 Discriminant validity

Discriminant validity is the extent of a constructs that is distinct from

other constructs. It is indicated by low corrections between the measure of

interest and the measure of other constructs (Fornell and Larcker, 1981). From

Table 5, the square root of AVE for each construct was larger than the

correlations between it and any of other constructs. As a result, it showed

adequate discriminant validity.

Table 5 Correlation between constructs

Construct ORQ ORI PWU PEOF PR DIST CDT

ORQ 0.96

ORI 0.75 0.96

PWU 0.70 0.56 0.76

PEOF 0.39 0.22 0.44 0.85

PR 0.85 0.72 0.76 0.38 0.84

DIST -0.50 -0.28 -0.36 -0.19 -0.47 0.94

CDT 0.52 0.37 0.54 0.35 0.53 -0.20 0.88

.

29

5.2 Structural model

After examined the measurement model, structural model were then assessed.

By performing the bootstrapping in PLS, tests of significance for all paths were

showed. Figure 2 showed the full result of bootstrapping including their significance,

the path coefficient and the R2. R

2 is the value indicates the percentage of total

variation of the dependent variable explained by the regression model consisting of

the corresponding independent variable. Result showed that the model explained

74% of the variance of online relationship quality and 57% of the variance of online

repurchase intention.

30

Note: *p<0.10, **p<0.05, ***p<0.01

Figure 2 Result of structural model

31

After that, t-statics of the structural model was examined. H1 (t=5.02) showd

that online relationship quality is positively influenced to online repurchase intention

with 0.70 path coefficient. However, the path between perceived website usability

and online repurchase intention is not significant, therefore, H2 (t=0.70) is not

supported. For H3 (t=1.06), it is not significant for the path between perceived

website usability and online relationship quality. Result also showed that the path

between perceived expertise in order fulfillment and online relationship quality is

not significant, confirmed that H4 (t=0.74) is not supported. H5 (t=7.83) showed

that perceived reputation is positively influenced online relationship quality with

0.65 path coefficient. Moreover, distrust in seller behavior has a negative impact to

online relationship quality with -0.13 path coefficient, therefore, H6 (t=2.00) is

supported. For H7 (t=1.07), it is not significant for the path between consumer

disposition to trust and online relationship quality.

32

Table 6 Summary of the result

Hypothesis Path Path

Coefficient

Conclusion

H1 Online relationship quality -> Online

repurchase intention

0.70

(t=5.02)

H1 is supported

H2 Perceived website usability -> Online

repurchase intention

Not

significant

H2 is not supported

H3 Perceived website usability -> Online

relationship quality

Not

significant

H3 is not supported

H4 Perceived expertise in order fulfillment

-> Online relationship quality

Not

significant

H4 is not supported

H5 Perceived reputation -> Online

relationship quality

0.65

(t=7.83)

H5 is supported

H6 Distrust in seller behavior -> Online

relationship quality

-0.13

(t=2.00)

H6 is supported

H7 Consumer disposition to trust -> Online

relationship quality

Not

significant

H7 is not supported

Table 6 summarized the result of PLS analysis. H1, H5 and H6 are supported in

this study while H2, H3, H4 and H7 are not supported.

33

6. Discussion and Implications

The purpose of this study is to extend the research of repurchase intention in B2C

platform in a relationship quality perspective and the current study want to focus on C2C

e-commerce instead of B2C e-commerce. In current research findings that mentioned in

previous section, the result found that there is a significant difference between B2C

e-commerce and C2C e-commerce in online repurchase intention in terms of online

relationship quality.

6.1 Discussion

6.1.1 Online relationship quality

The result found that online relationship quality is a significant predictor

of online repurchase intention while Zhang et al. (2011) research finding also

got the significant result in this relationship and stated that a buyer-seller

relationship is considered high quality only when previous interaction with the

vendor has been positive and future interactions with the seller are expected.

The online relationship between the seller and buyer affects how much

customers will repurchase for the same seller in the future. Therefore, it was a

significant predictor of online repurchase intention in current research and

previous study.

6.1.2 Seller characteristics

In terms of the seller characteristics, the current research result showed

that perceived website usability is not a significant factor of online repurchase

intention and online relationship quality, which is different from the result of

previous research model. In the research of Zhang et al. (2011), it found that

perceived website usability is a significant factor of online repurchase intention

and online relationship quality. The respondents of Zhang et al. (2011) research

can choose the website in their own preference by thinking of a vendor that the

respondents have purchased from recently via the Internet. As a result, the

research findings were comprised with different B2C website that respondents

always used and preferred to use. Because different B2C e-commerce platforms

34

may have various layouts and website designs, it is important to provide a

website to customer with high usability and perceived website usability is one

of the critical factors for developing online relationship quality, therefore

previous research found that perceived website usability is positively related to

online repurchase intention and eventually the online relationship quality. Back

to the current research, respondents were restricted to answer the questions in

reference of shopping experience in C2C Taobao platform only and the target

respondents are people who used Taobao for online shopping before. Although

there are many different shops in Taobao, the layouts and the designs of the

website are quite similar as Taobao has provided some website templates for

online seller (Taobao, n.d.). As a result, there is not much difference of the

websites in Taobao in terms of website usability. Customers may not view

perceived website usability in Taobao as important as other B2C online

shopping platforms as the differences of website usability in Taobao are not

significant. Therefore, this may explain why perceived website usability is not

a significant factor of online repurchase intention and online relationship

quality in current study.

For the perceived expertise in order fulfillment, result found that perceived

expertise in order fulfillment is an insignificant predictor with online

relationship quality while Zhang et al. (2011) research found that perceived

expertise in order fulfillment was significant predictor with online relationship

quality. As the business operation of B2C and C2C is quite different, the order

fulfillment service in C2C e-commerce is so standardized and many online

shops in Taobao can provide sufficient order fulfillment service to the buyers.

The consequence is that customers do not feel more satisfied and trustworthy if

a buyer in Taobao provided great order fulfillment service and they may even

switch to purchase in other websites that also have similar order fulfillment

service just like the previous experience. As a result, this may be a possible

explanation of why perceived expertise in order fulfillment is not a significant

predictor with online relationship quality. It is not an important factor for

35

sellers to enhance the online relationship quality with buyers. The seller in C2C

e-commerce can only increase online relationship quality by other factors.

Result also found that perceived reputation of seller is a significant

predictor with online relationship quality. The research finding of the current

study is matched with the result with Zhang et al. (2011). Customers believe

that the sellers with high reputation are probable to meet its obligations in the

current transactions (Sharif et al., 2005). The current study extends the research

from B2C context to C2C context and found that buyer in both e-commerce

platform consider reputation is a very important characteristic of seller in

building online relationship quality. When the perceive reputation of the seller

is good, buyer will feel more satisfied and trustworthy, therefore, people are

more willing to buy for the same seller in the long term. Thus, perceived

reputation of seller is a significant predictor with online relationship quality.

6.1.3 Seller behavior

In terms of the seller behavior, the result of current research suggested that

there is a significant relationship between distrust in seller behavior and online

relationship quality and the result is similar to Zhang et al. (2011) research in

B2C context. Previous research finding suggested that distrust is one of a

distinct factors influencing online customer’s behavior (Dimoka, 2010). The

current result confirms that the distrust in seller behavior is a stumbling block

for establishing good online relationship quality between buyer and seller.

Therefore, distrust in seller behavior is negatively related to online repurchase

quality.

6.1.4 Consumer personality

Consumer disposition to trust is a new factor that this study contributes to

the Zhang et al. (2011) research model. This study found that consumer

disposition to trust does not have a significant effect on online relationship

quality. The research result is quite surprise to the study. Many researches had

36

already studied the relationship between trust and consumer disposition to trust

(Gefen, 2000; McKnight et al., 1998; Pavlou & Gefen, 2004) and the findings

from Kim et al. (2008) suggested that consumer disposition to trust had a

significant effect on consumer trust. As online relationship quality is mainly

comprised with trust and satisfaction (Zhang et al., 2011), thus in setting the

hypothesis, this study purposed that consumer disposition to trust may

contribute to trust in seller and then also contribute to online relationship

quality. However, the current research finding do not support this hypothesis

and show that consumer disposition to trust does not have a significant direct

effect on online relationship quality. One possible reason for this insignificant

effect is that the seller can only maintain high online relationship quality when

buyers felt both satisfied and trustworthy after the buying process. Only

fulfilling the trust element cannot sufficiently contribute to high online

relationship quality. Thus, consumer disposition to trust is not a significant

predictor with online relationship quality in this study.

6.2 Implications

6.2.1 Implications for research

This research attempts to examine how online relationship quality affects

customer online repurchase intention in C2C platform Taobao and see whether

the research in this study is similar to Zhang et al. (2011) study in B2C context.

The current study found that there are some differences between C2C

e-commerce and B2C e-commerce in maintaining online relationship quality.

The research studied online relationship quality in 3 groups of factors including

seller characteristics, seller behavior and consumer personality. In terms of

seller characteristics, only perceived reputation is viewed as a significant

predicator to online relationship quality. For the perceived website usability and

perceived expertise in order fulfillment, this study found that it is not applicable

in C2C context as the website usability and order fulfillment in C2C platform

are quite standardized, seller in C2C platform cannot obtain online relationship

quality successfully by only performing well in these two areas. For the seller

37

behavior, the current study verified the research finding of Zhang et al. (2011)

study and confirmed that there is a negative relationship between distrust in

seller behavior and online relationship quality. Moreover, this study added one

more dimension which is consumer personally in investigating the formation of

online relationship quality. Although result found that consumer disposition to

trust is not a significant predictor of online relationship quality, this study has

already enriched the model of Zhang et al. (2011). In the future, researchers can

further examine online relationship quality in terms of consumer personality in

order to have a more comprehensive study in this topic.

6.2.2 Implications for sellers in Taobao

From the research findings of this study, developing high online

relationship quality can help to achieve online repurchase intention in Taobao.

And perceived reputation is the only factor positively related to online

relationship quality. As a result, this implies that customers would conduct

online shopping with those sellers that are high in reputation. Generally,

shopping online has higher risk than offline. To reduce the risk level, customers

are more willing to purchase in a shop with high reputation. Therefore, this

give a clear direction to the sellers in Taobao that the seller can only enhancing

the online relationship quality by increasing the perceived reputation.

The rating system in Taobao is the most important indicator of sellers’

reputation. People are more willing to purchase in a shop with high rating as

high rating implicated that the seller has high reputation within the Taobao

platform. To maintain a long term relationship with their customers and

facilitating online repurchase intention, seller in Taobao should try their best to

perform better in the rating system. This can be achieved by providing better

customer services especially seller should put more focus on after-sale service.

It is because the buyer can only rate the seller after the buyer received the

products and confirmed the transaction. By providing better after-sale service,

buyers are more willing to give a high rating to the seller.

38

Moreover, this research also reminds the sellers in Taobao about the

potential drawback of distrust. Sellers should not do anything that may create

distrust from the buyer toward the seller as the study have found that there is a

negative relationship between distrust in seller behavior and online relationship

quality. As a result, seller should try to deliver products as promised, meet the

customers’ expectation and should not promises more than they can deliver to

ensure online relationship quality would not be affected by this factor.

39

7. Limitation and Future Research

Although this study provides some practical insights of online repurchase intention

in online relationship quality perspective, there are still some limitations which can be

improved in the future research.

Firstly, there is only 131 samples were collected for this study. It is not large enough

to represent the whole population of people using Taobao in online shopping. To improve

the measurement of the model, future research should increase the sample size so that the

result can become more representative.

Secondly, because of the time constraints, the research questionnaire was only

distributed through the Facebook platform and result found that 67% of the respondents

are students. Therefore, it cannot reflect the views of all age groups representatively. In

future research, paper questionnaire may be distributed to increase the participation of

different age groups.

Thirdly, the study pre-set the C2C e-commerce websites to Taobao only. However,

in reality, there are many different C2C online shopping platforms in the Internet.

Although Taobao is relatively popular in Hong Kong, some respondents are still not so

familiar with Taobao. In future research, it may be better if the respondents can choose

the website that they had repurchase experience before.

Fourth, this study aims to examine Taobao in terms of the relationship between

online repurchase intention and online relationship quality. The research has considered 5

factors that may influence customer online relationship quality. However, more

dimensions like security or privacy problems maybe added into the model to enhance the

comprehensiveness.

40

8. Conclusion

C2C online shopping platform has become more and more popular nowadays

especially for Taobao. This study aims to investigate different key antecedents of online

relationship quality in order to examine the online repurchase intention of customers in

Taobao. The research findings confirm that online relationship quality is the significant

factors of online repurchase intention in C2C context. Also, unlike the previous research

result in B2C context, perceived reputation is the only significant factors of online

relationship quality in C2C platform. The results also demonstrate how distrust in seller

behavior can influence online relationship quality negatively.

With these findings, this research provides some practical insights in studying online

repurchase intention in relationship quality perspective in C2C context. Sellers in Taobao

can therefore understand what they can improve in order to increase customer repurchase

intention in the future.

41

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10. Appendeix

10.1 Appendix A: Questionnaire

48

Hong Kong Baptist University

Department of Finance and Decision Sciences

The study of HK people using TaoBao for e-shopping

I am a BBA student at the HKBU and now conducting my final year project entitled “The

study of HK people using TaoBao for e-shopping”. I am very much appreciated if you

could help me to fill out the following questionnaire.

This project cannot be completed without your participation. I however ensure you that

all information provided in this survey will be kept straightly confidential.

This questionnaire will take about 10 minutes for completion. We will provide a lucky

draw for those who are interested after filling the contact information at the end of this

survey. However, this part of information is an optional.

Thank you again for your kind participation.

49

Have you ever used the website — TaoBao (not including Tmall) to do online shopping? Yes

No (End of questionnaire)

Please rate the following questions accordingly. (1- Strongly Disagree, 7- Strongly Agree)

To answer the following questions, please think of a seller in Taobao (not including Tmall)

that you have purchased online recently.

Section 1/10 (Online repurchase intention)

Strongly

Disagree

(1)

(2)

(3)

Neutral

(4)

(5)

(6)

Strongly

Agree

(7)

I will likely

purchase

online from the

same seller in

the medium

term.

I will likely

purchase

online from the

same seller in

the long term.

I will never

purchase from

the same seller

again.

Section 2/10 (Satisfaction)

Strongly

Disagree

(1)

(2)

(3)

Neutral

(4)

(5)

(6)

Strongly

Agree

(7)

My shopping

experience with

this seller is

extremely

satisfied.

My shopping

experience with

this seller is

extremely

pleased.

My expectations

were exceeded in

50

the purchase

process.

Section 3/10 (Trust)

Strongly

Disagree

(1)

(2)

(3)

Neutral

(4)

(5)

(6)

Strongly

Agree

(7)

This seller is

consistent in

quality and

service.

This seller is keen

to fulfill my needs

and wants.

This seller is

honest.

This seller wants

to be known as one

that keeps

promises and

commitments.

This seller has my

best interests in

mind.

This seller is

trustworthy.

This seller has

high integrity.

This seller is

dependable.

51

Please rate the following questions accordingly. (1- Strongly Disagree, 7- Strongly Agree)

To answer the following questions, please think of a seller in Taobao (not including Tmall)

that you have purchased online recently.

Section 4/10 (Perceived website usability)

Strongly

Disagree

(1)

(2)

(3)

Neutral

(4)

(5)

(6)

Strongly

Agree

(7)

This seller's

website is

extremely easy to

use.

This seller's

website is

extremely

professional.

This seller's

website is

extremely well

organized.

This seller's

website has

extremely

excellent breadth

of product

selection.

This seller's

website has

extremely

excellent

description of

product selection.

This seller's

website is

extremely easy to

navigate.

This seller's

website is

extremely easy to

find information

that I want.

This seller's

website is

extremely easy to

52

conduct online

shopping.

Section 5/10 (Perceived expertise in order fulfillment)

Strongly

Disagree

(1)

(2)

(3)

Neutral

(4)

(5)

(6)

Strongly

Agree

(7)

This seller has

knowledge and

expertise in

distribution. (i.e.

how to deliver

products)

This seller has

efficiently

integrated all

necessary

processes that

are needed to

deliver products.

This seller has

an efficient

system for

processing

orders received.

Section 6/10 (Perceived reputation)

Strongly

Disagree

(1)

(2)

(3)

Neutral

(4)

(5)

(6)

Strongly

Agree

(7)

This seller has

excellent public

image.

This seller is

extremely

committed to

customer

satisfaction.

This seller is

extremely

innovative.

Products and/or

services

provided by the

seller are

extremely

excellent.

53

This seller has

an extremely

excellent

reputation.

This seller is

extremely

reliable.

Section 7/10 (Distrust in seller behavior)

Strongly

Disagree

(1)

(2)

(3)

Neutral

(4)

(5)

(6)

Strongly

Agree

(7)

This seller could

sometimes fail to

deliver

product/service as

promised.

This seller is

sometimes unable to

deliver what they

promise to.

This seller is

sometimes unable to

meet expectations.

This seller always

promises more than

they can deliver.

54

Please rate the following questions accordingly. (1- Strongly Disagree, 7- Strongly Agree)

Section 8/10 (Expertise in using Internet to conduct transactions)

Strongly

Disagree

(1)

(2)

(3)

Neutral

(4)

(5)

(6)

Strongly

Agree

(7)

I know a lot about

conducting purchases

via the Internet.

I am experienced in

conducting purchases

via the Internet.

I am informed about

conducting purchases

via the Internet.

I am an expert buyer

of products/services

via the Internet.

Section 9/10 (General issue)

Strongly

Disagree

(1)

(2)

(3)

Neutral

(4)

(5)

(6)

Strongly

Agree

(7)

I generally

trust other

people.

I generally

have faith in

humanity.

I feel that

people are

generally

reliable.

I generally

trust other

people unless

they give me

reasons not to.

55

Section 10/10 (Personal Information)

What is your gender? Male

Female

What is your age? < 18

18 - 25

26 - 35

36 - 45

46 - 55

> 55

What is your occupation? Student

Professional

Researcher

Others

What is your highest education? High school

Undergraduate Degree

Master Degree

PhD

In last month, how many times have you done online shopping? 0 - 1

2 - 4

5 - 7

8 - 10

>10

In last month, how many times have you done online shopping with TaoBao (not

including Tmall)? 0 - 1

2 - 4

5 - 7

8 - 10

>10

So far, how many months have you had online shopping experience with TaoBao (not

56

including Tmall)? <6

6 - 12

13 - 24

25 - 36

>36

What is your monthly income? HK$<5,000

HK$5,000 - 10,000

HK$10,001 - 15,000

HK$15,001 - 20,000

HK$>20,000

On average, how much do you spend on online shopping each time? HK$<250

HK$250 - 500

HK$501 - 750

HK$751 - 1,000

HK$>1,000

Please provide your contact information for Lucky Draw (Optional). Name: ______________________________________

Phone Number: _______________________________

Email Address: _______________________________