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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%
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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: _______________________________