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Abstract
Many small businesses have started to use
eBay as their electronic commerce platform.
Such a strategy increases their reach to
global customers without high financial and
technical costs in building their own e-
commerce infrastructure or in intense
advertising. How can these e-stores conduct
successful international business on eBay?
This paper addresses this complex issue by
discussing how online customers’ percep-
tions of an e-store’s culture, size, and
history affect the e-store’s feedback rating
and successful sales. We analyze data of the
completed transactions of 400+e-stores on
eBay across twenty-two countries. The
results suggest that feedback rating is a
significant determinant of the success of an
e-store, and that an e-store’s culture, size,
and history significantly affect the e-store’s
feedback rating.
Keywords: electronic commerce,international
business, culture, feedback rating, trust
Authors
Paul Komiak
(pjkomiak@students.tamiu.edu) is a PhD
Student in International Business and
Strategy at Texas A&M International
University. His research focuses on the
strategy and policy implications of IB.
Sherrie Y. X. Komiak
(skomiak@mun.ca) is an Assistant
Professor of Information Systems at
Memorial University of Newfoundland,
Canada. Her research focuses on
electronic commerce, human computer
interaction and trust.
Michael Imhof
(michaelimhof@students.tamiu.edu) is a
PhD.Student in International Business
and Finance at Texas A&M International
University.
Conducting International Business at eBay:
The Determinants of Success of e-Stores
PAUL KOMIAK, SHERRIE Y. X. KOMIAK AND MICHAEL IMHOF
INTRODUCTION
The growing use of the Internet as a
medium for conducting business is
one the most significant factors
shaping the world economy (Gibbs
et al. 2003). However, cost signifi-
cantly deters electronic commerce
adoption in small to medium-Sized
Enterprises (SMEs) (Al-Qirim
2005). To overcome this constraint,
many SMEs have started to use a
well-known electronic market like
eBay as their electronic commerce
platform. Such a strategy increases
their reach to global customers
without high financial and technical
costs in building their own e-com-
merce infrastructure or in intense
advertising. Since its inception in
1995, eBay has grown to be a huge
and best-known electronic market.
Online retailers can use eBay to
launch e-stores, listing their items
under specific product headings for a
small monthly fee. For a larger fee,
sellers can list their e-store as an
anchor store, with premium place-
ment opportunities. Sellers some-
times use eBay as their only online
sales effort because they do not have
the cost and expertise in-house to
handle online payment, website
development and maintenance, and
other necessities that come with
being an independent online mer-
chant. Other companies use eBay as
another online channel in addition
to their own websites or promote
the items they are selling on eBay on
their own websites. Though using
eBay as a platform for operating
their own e-stores may provide
businesses with a potentially vast
number of international and domes-
tic customers without broad and
intense advertising, the benefits can
only occur when international and
domestic customers actually patron-
ize their eBay-based websites.
How can e-stores on eBay con-
duct successful international busi-
ness? While a large quantity of
research addresses the determinants
for success of traditional multina-
tional corporations (MNCs)
(Ahlstrom et al. 2005,
D’Annunzio-Green 2002, Darling
and Box 1999, Dow 2006, Elenkov
and Fileva 2006, Fey and Bjo
¨rkman
2001, Galan et al.1999, Goodbody
2005, Gorg and Strobl 2003,
Holtbrugge 2004, Jennex et al.
2004, McLarney and Dastrala
2001, Reid 1995, Robson et al.
2002, Tixier 1995, Tudor and
Trumble 1996, Yang and Lee
2002, Yang 1998), few scholarly
works address the determinants of
success for companies engaging in
international electronic commerce.
Among the studies on electronic
markets, most emphasize a direct
Internet-based exchange. For
Copyright ß2008 Electronic Markets
Volume 18 (2): 187-204. www.electronicmarkets.org DOI: 10.1080/10196780802045120
RESEARCH
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example, the transaction cost perspective focuses on the
effect of the Internet on the efficiency of the transaction
process (Rotondaro 2002). Another perspective exam-
ines the nature of the product, called the product fitness
theory (Liang et al. 2004). Only recently has research
focused on the electronic intermediary and on external
variables such as consumer demographics (Black 2005,
Kshetri 2002). Even if the use of the Internet can lower
costs and speed up activities in the value chain,
differences that drive purchasing behaviour, i.e., con-
sumer perceptions, beliefs, preferences, and attitudes,
may remain (Lynch et al. 2001). Many academics have
included consumer trust and intended behaviour, e.g.,
intention to purchase, in their research (Gefen et al.
2003a). Other academics have introduced culture into
their research on e-commerce behaviour (Johnston and
Johal 1999, Kacen and Lee 2002, Lynch and Beck
2001). However, culture has usually been left out of
research on trust and trust beliefs in e-commerce (Gefen
and Heart 2006).
This paper addresses the complex issue of e-commerce
success by examining the roles that culture, store size,
store temporal history and feedback score (i.e. custo-
mers’ perceptions and beliefs about an e-store) play in
the success of international online retailers in a real-life
environment, in which actual buyers selected e-stores
and completed their purchase transactions. This paper
extends the research on beliefs, attitudes and intentions
to actual behaviour. We propose and test the central role
of feedback score in the success of e-stores on eBay.
Since customer’s perceptions and beliefs can be
influenced by e-store design, the results of this study
will generate some useful suggestions for electronic
market researchers, practitioners and policymakers. First,
researchers may find such knowledge helpful in addres-
sing the growing international presence of Internet
stores and the central role of feedback scores in e-store
success. Second, for web design and online seller
practitioners, knowing what attracts buyers, and what
does not, may enable the development of better e-
commerce strategies. Finally, knowing the determinants
of e-commerce performance may help policymakers
enhance the effectiveness of consumer protection laws
by helping them to understand better the purchasing
behaviour and legal demands of online consumers.
The rest of the paper is structured as follows: the next
section establishes the theoretical grounds underlying
the feedback rating of e-stores on eBay, and the
relationship between the feedback-rating and success of
e-stores. This is followed by a section that explores
several factors (e-store’s culture, size, and history)
hypothesized to have an impact on the e-store’s
Feedback Rating. Then the research methodology is
presented. We analyze data of the completed transac-
tions of 84 e-stores on eBay across 14 countries. We
controlled the factor of product types by selecting
these 84 e-stores who sold the same products. We
cross-validate our findings with a second sample of 346
e-stores from a different product type and a more recent
sample timeframe. The results are then presented and are
followed by a discussion on the theoretical, managerial,
and policy implications of this study. The final section
concludes the paper.
FEEDBACK SCORES OF E-STORES AT EBAY
The concept of feedback scores
eBay’s feedback rating system is a very well known
reputation system in electronic markets. On every e-
store’s main webpage, on every item selling, and on
every bid, a Feedback Rating score will show up beside
the name of that eBay member (e-store, buyer or seller).
As explained by eBay at: http://pages.ebay.com/
services/forum/feedback.html, for each completed
transaction, only the buyer and seller can rate each
other by leaving feedback. Each feedback consists of a
positive, negative, or neutral rating and a short
comment. Once it is entered, the feedback becomes a
permanent part of the member’s profile. Feedback
ratings are used to determine each member’s feedback
score. The feedback score represents the number of eBay
members that are satisfied doing business with a
particular member. It is usually the difference between
the number of members who left a positive rating and
the number of members who left a negative rating. A
member can increase or decrease another member’s
score by only 1 no matter how many transactions they
share. Feedback score can be conceptualized as a proxy
of trust (Ba and Pavlou 2002). Therefore, it is likely that
feedback scores can serve as the proxy of customer trust
in an eBay e-store.
Although the importance of trust as a foundation for
buyer-seller relationships in traditional commerce
(Morgan and Hunt 1994, Swan et al. 1999) and in
electronic commerce (Gefen et al. 2003a, Komiak and
Benbasat 2006, McKnight et al. 2002a) is widely
accepted, trust has been conceptualized in various ways
and in different disciplines. McKnight et al.’s trust
model (2002a) consists of disposition to trust (from
psychology), institution-based trust (from sociology),
trusting beliefs, and trusting intentions (from social
psychology). Blomqvist (1997) analyzes the various
levels and dimensions of trust in the fields of social
psychology, philosophy, economics and marketing.
Blomqvist proposes that trust is an actor’s expectation
of the other party’s competence and goodwill. Dwyer
and Lagace (1986) proposes that trust can be con-
ceptualized in one of three ways: (1) trust as a
personality trait or generalized expectancy about the
trustee’s competence and reliability (Anderson and
Narus 1990, Anderson and Weitz 1989, Magrath and
Hardy 1989), (2) trust as a predisposition toward
188 Paul Komiak, Sherrie Y. X. Komiak and Michael Imhof &International Business at eBay
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another or belief that another will behave in a
matter beneficial to the other party (Morgan and
Hunt 1994), and (3) trust from the standpoint of
risking behaviours, that reflects a willingness on the
part of the buyer to accept the possibility of vulnerability
on her part in the transaction (Hawes et al. 1993,
Mayer et al. 1995, Moorman et al. 1993, Swan et al.
1985).
Many researchers conceptualize trust as a truster’s
trusting beliefs, in other words, a truster’s beliefs in a
trustee’s multi-dimensions (Mayer et al. 1995). Trusting
beliefs means the confident truster perception that
the trustee has attributes that are beneficial to the
truster (McKnight et al. 2002a). Many types of
trusting beliefs exist in the trust literature, while three
are utilized most often: competence (ability of the
trustee to do what the truster needs), benevolence
(trustee caring and motivation to act in the truster’s
interests), and integrity (trustee honesty and promise
keeping) (Mayer et al. 1995, McKnight et al. 2002a). It
is worthy noting that predictability is also used in at
least nine prior studies on trust (Gabarro 1978,
Rempel et al. 1985), as summarized by McKnight et
al. (2002a) and by Chopra and Wallace. (2003).
Predictability is defined as the degree to which the
trustee’s behaviour conforms to expectations (Chopra
and Wallace 2003). Expectations can be based on the
trustee’s history or role. It is suggested to be the
fourth trusting belief (Chopra and Wallace 2003,
McKnight et al. 1998).
Based on the information about the eBay feedback
score and prior research on trust and reputation, we
conceptualize the feedback score of an e-store on eBay as
a proxy of online customers’ trusting belief in the e-
store’s trustworthiness. While online customers’ short
comments on an eBay member (a part of feedback
ratings) contain their assessments on the eBay member’s
various dimensions of trustworthiness (competence,
benevolence and integrity), feedback score, as a single
number calculated from the accumulated feedback
ratings, represents online customers’ overall trusting
belief in that eBay member’s trustworthiness. It is a
summary of the total number of satisfied trading
partners minus dissatisfied trading partners for a member
on eBay.
Particularly, feedback score is related to the predict-
ability trusting belief. Feedback score represents an eBay
member’s trading history, i.e. how well this eBay
member behaved in prior transactions. Such a history
is revealed to the new customers through the presenta-
tion of feedback score. New customers can develop
an understanding of the eBay member’s (an e-store in
this paper) behaviours in the past, based on which the
new customers can develop expectations or predictions
on this eBay member’s future behaviours (Luhmann
1979).
Feedback score affects the success of e-stores
Our research model is shown in Figure 1. Based on prior
literature on trust and culture in electronic commerce,
the current study examines the central role of feedback
score in the success of e-stores on eBay, defined as the
number of successful sales conducted by an e-store
within a certain period of time. It also predicts that
customers’ perceptions of e-stores (i.e. culture, history
and size) will significantly affect feedback score. Our
research model does not examine the impact of product
types. To control the impact of product types, we
examine the sales within a single product category (a first
sample for consumer electronics, and a second sample
for health and beauty products) across different e-stores.
Trust theories provide the conceptual foundations to
understand the effect of feedback score on the success of
e-stores. When a new customer is considering whether
to buy from an e-store at eBay, the feedback score is
clearly shown besides the name of this eBay member.
The higher this feedback score, the higher prior
customers’ trust in this e-store is. The new customer
will transfer trust from prior customers through the
feedback score, based on the theory of transferred trust.
Transferred trust means ‘‘trust in trust’’, which asserts
that the level of trust that others place in a trustee (an e-
store in this case) can serve as a rational basis for trust
(Chopra and Wallace 2003, Doney and Cannon 1997,
Luhmann 1979). Similarly, a new customer can develop
a high level of trust in an e-store based through the
reputation categorization process (McKnight et al.
1998). A higher feedback score indicates a higher
reputation for an e-store. According to the reputation
categorization process, those with good reputations are
categorized as trustworthy individuals; thus new custo-
mers will quickly develop a higher level of initial trusting
beliefs about that individual (the e-store in this case),
even without first-hand knowledge.
A customer can also develop a higher level of trust in
an e-store with higher feedback scores through calcula-
tive-based trust (Doney and Cannon 1997, Gefen et al.
2003a). According to the calculative-based trust para-
digm, trust can be shaped by rational assessments of the
costs and benefits of another party cheating or cooperat-
ing in the relationship; Trust in this view is derived from
an economic analysis occurring in ongoing relationships,
namely that it is not worthwhile for the trustee to engage
in opportunistic behaviour if the costs of being caught
outweigh the benefits of cheating, then trust is
warranted since cheating is not in the best interest of
the trustee (Coleman 1990, Gefen et al. 2003a).
According to this theory, an e-store with a higher
feedback score has a higher cost for cheating than an e-
store with a lower feedback score, thus the e-store with a
higher feedback score is more trustworthy than the e-
store with a lower feedback score.
Electronic Markets Vol. 18 No 2 189
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Particularly, feedback score is related to the predict-
ability trusting belief, as we discussed above. A new
customer will develop trust in an e-store with high
feedback score through prediction process (Doney and
Cannon 1997), also called knowledge-based trust
(Gefen et al. 2003a). Trust is created in this process
when the truster’s knowledge about the other party
allows it to predict the behaviour of the other
party (Doney and Cannon 1997). A new customer
can learn from an e-store’s high feedback score
that the store behaved well in prior trading; thus the
new customer can develop trust in this store based on
the prediction that that the e-store will continue to
operate in the same fashion as it has previously.
In addition, prediction is related to consistency
(McKnight et al. 2002a). eBay also show the percentage
of positive feedback ratings in all the feedback
ratings. When this percentage is higher, and when
the feedback score is higher, the new customer can
perceive a higher consistency of the e-store’s past
behaviour, thus the new customer’s confidence in his
or her expectation in the e-store will be higher, leading
to higher level of trusting belief.
When a higher feedback score elicits higher trusting
beliefs from a new customer, higher trusting beliefs will
lead to higher success of the e-store, because the
customer’s buying from the e-store is a trusting
behaviour. Online customers’ trusting beliefs are sig-
nificantly and positively associated with trusting beha-
viours or trusting behaviour intentions (e.g. buying from
an e-store), according to the ‘Theory of reasoned action’
(Fishbein and Ajzen 1975) and many empirical studies
(Ba and Pavlou 2002, Gefen et al. 2003b, McKnight et
al. 2002b). Therefore, we expect:
Hypothesis 1: Higher feedback score will generate higher sales for
an e-store.
CULTURE, HISTORY AND SIZE AFFECT FEEDBACK
SCORES
Each eBay customer can easily learn about an eBay e-
store through the e-store’s website and member profile.
From the e-store’s website and its owner’s member
Figure 1. Research model - conceptual
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profile, the customer can learn the e-store’s culture, size
and history. On each e-store’s website, a customer can
perceive the size of the e-store (e.g. 2367 items found in
all categories), in addition to a list of products for sale.
Each e-store’s member profile displays the e-store’s
location (e.g. United States) and history (e.g. Member
since: Dec-26-98), and detailed feedback ratings. The
customer can perceive the e-store’s culture based on the
location of the e-store.
Culture (individualism and uncertainty avoidance)
affects feedback scores
Most definitions of culture currently used are modifica-
tions of Tylor’s (1871) definition of the concept as that
including knowledge, belief, morals, law, customs and
any other habits imbedded as a social member. The
term, however, has been criticized as being conceptually
weak (Child 1981). More recently, culture has been
conceptualized as the shared attitudes and values of the
members of a country (O’Grady and Lane 1996) and
these attitudes and values may be more helpful in
understanding behaviours than sociodemographic vari-
ables such as age, education and income (Deng et al.
2006). In continuing research, the definition and
usability of national culture, is under debate and open
for redefinition (House 2004: 266, Srite and Karahanna
2006: 265). Culture is an important factor in buyer-
seller relationships in international markets because
cultural values and norms can significantly impact
consumer preferences (Johnson-Page and Thatcher
2001). Culture is an important variable adding to the
complexity of international business but can also be a
source of conflict rather than synergy (Hofstede et al.
1990). Understanding the impact of culture can give a
seller or a buyer an advantage which may translate into
more successful results.
Hofstede’s seminal works (1980, 1983) develop a
well-defined, empirically based, and widely cited typol-
ogy to describe cultures. Hofstede’s model of national
cultural differences includes five cultural dimensions
(see: http://www.geert-hofstede.com/). (1) Power
Distance Index (PDI) is the extent to which the less
powerful members of organizations and institutions (like
the family) accept and expect that power is distributed
unequally. (2) Individualism (IDV) on the one side,
versus its opposite, collectivism, is the degree to which
individuals are integrated into groups. Individualism-
Collectivism is the extent to which the self-concept of
individuals in a country revolve around that of an
individual or that of a member of a group (Hofstede
1980). (3) Masculinity (MAS) versus its opposite;
Femininity, refers to the distribution of roles between
the genders. (4) Uncertainty Avoidance Index (UAI)
deals with a society’s tolerance for uncertainty and
ambiguity; it ultimately refers to man’s search for truth.
(5) Long-Term Orientation (LTO) versus Short-Term
Orientation: values associated with Long Term
Orientation are thrift and perseverance; values associated
with Short Term Orientation are respect for tradition,
fulfilling social obligations and protecting one’s ‘face’.
The current study uses Hofstede’s index scores for the
Individualism-Collectivism and Uncertainty Avoidance
dimensions to represent an eBay e-store’s culture.
Individualism-Collectivism and Uncertainty Avoidance
are considered to be important predictors of Internet
shopping rates (Lim et al. 2004). There also appears to
be a strong positive correlation between Individualism
and Internet usage, and a strong negative correlation
between high Uncertainty Avoidance and Internet usage
(Ess and Sudweeks 2005). These correlations have been
noted in numerous earlier studies conducted on a global
scale (cf. Barnett and Sung 2005; Maitland and Bauer
2001). We choose the Individualism-Collectivism
dimension because it is the most significant cultural
dimension explaining differences historically and cross-
culturally (Triandis 2001). Individualism-Collectivism as
a cultural typology has been extensively replicated and
supported in prior research focused on cultural differ-
ences (Triandis and Suh 2002). In addition, we choose
the Uncertainty Avoidance dimension because we
believe that it is the most trust-relevant dimension
among Hofstede’s five dimensions of culture.
Uncertainty avoidance is directly related to people’s
beliefs and attitude on risk and trust.
Individualism affects feedback scores. eBay customers
and eBay e-stores are viewed as out-group members,
because eBay customers are anonymous and new to an e-
store, and an e-store is generally unknown and
anonymous to the customers. These entities potentially
come from different cultures worldwide. The customer
who gives feedback to the e-store has one and only one
transaction with the store, because an eBay store’s
feedback score only includes a customer’s first feedback,
even though this customer may be a repeat customer.
Thus when a customer gives an e-store feedback, there is
a very short transaction history between them.
In dealing with out-members, collectivists differenti-
ate between in-group and out-group members more
than individualists (Iyengar et al. 1999, Triandis 1972).
Individualists are more cooperative with out-group
members than collectivists (Yamagishi 1988, Yamagishi
et al. 1998). Thus individualist cultures exhibit higher
Internet shopping rates than collectivist cultures (Lim et
al. 2004). Individualists emphasize efficiency and
directness (Grimm et al. 1999, Triandis 2001), and
tend to stress consistency and stability of attitudes
(Iyengar et al. 1999). In contrast, collectivists behave
more favourably towards in-group members rather than
out-group members (Elahee et al. 2002). It is some-
times considered acceptable in collectivistic societies to
exploit and deceive out-group members, whereas it
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would not be socially appropriate to do so to in-group
members (Triandis and Suh 2002). Therefore, we expect
that e-stores in individualist cultures will behave more
fair and efficiently towards the anonymous eBay
customers (out-group members), which will lead to
higher feedback scores, than e-stores in collectivism
culture.
In addition, customers give a feedback score based on
their first transaction with an e-store. With only one
transaction, it is easier for customers in individualism
cultures to develop trust (thus higher feedback scores)
than customers in collectivism cultures. Relative to
counterparts in collective cultures, people in individualist
cultures are more likely to form trust via a calculative
process (trusting based on cost/reward calculation) or a
capability process (assessing a target’s ability to fulfil his
or her promises); however, relative to counterparts in
individualist cultures, people in collectivism cultures are
more likely to form trust via a prediction process
(predicting a target’s behaviours based on a history),
an intentionality process (evaluating a target’s motiva-
tions) (Doney et al. 1998). One transaction may be
enough to enable a capability process and a calculative
process for individualist people, but multiple transac-
tions are generally needed to enable a prediction process
and an intentionality process for collectivism people.
Therefore:
Hypothesis 2:The feedback score of an e-store in an
individualism culture will be higher than the feedback score in
collectivism culture.
Uncertainty avoidance affects feedback scores. Un-
certainty Avoidance Index (UAI) deals with a society’s
tolerance for uncertainty and ambiguity (Hofstede 2001).
It indicates to what extent a culture programmes its
members to feel either uncomfortable or comfortable in
unstructured situations. Uncertainty avoiding cultures (i.e.
high uncertainty avoidance) try to minimize the possibility
of unstructured situations by strict laws and rules, etc. In
contrast, uncertainty accepting cultures (i.e. low uncer-
tainty avoidance) are more tolerant for unstructured,
unclear or unpredictable situations. Uncertainty is a
necessary condition of trust (Doney and Cannon 1997,
Luhmann 1979), and uncertainty avoidance reflects
people’s attitude to uncertainty and risk, thus uncertainty
avoidance will affect the perceived trustworthiness of e-
stores on eBay in different cultures.
An e-store in uncertainty accepting cultures may gain
higher feedback scores than an e-store in uncertainty
avoiding cultures, because compared to people in
uncertainty avoiding culture, the people in uncertainty
accepting cultures are more likely to hold an overall
higher regard of other people, and they are more willing
to accept not only familiar but also unfamiliar risks
(Hofstede 2001). Thus they are more likely to have
higher trust (giving higher feedback scores) in these e-
stores in eBay, which are new, unknown and unstruc-
tured, compared to traditionally branded and physically
existing stores.
In addition, eBay customers give an e-store feedback
scores based on only one transaction. It is easier for
customers in uncertainty accepting cultures to develop
trust (giving higher feedback scores) than customers in
uncertainty avoiding cultures. Relative to counterparts in
uncertainty avoiding cultures, customers in uncertainty
accepting cultures are more likely to form trust via
calculative process, because the level of uncertainty (or
risk) a culture considers tolerable influences economic
rationality and consequently, relative to counterparts in
uncertainty accepting cultures, people in uncertainty
avoiding cultures are more likely to form trust via a
prediction process and an intentionality process (Doney
et al. 1998). However, it usually takes multiple
transactions before people in uncertainty avoiding
cultures are able to develop trust through prediction
processes or intentionality processes. Therefore, the
feedback score of an e-store in uncertainty accepting
cultures can be higher because the people in uncertainty
avoiding cultures do not have enough time and
opportunities to fully develop their trust in an e-store.
Therefore:
Hypothesis 3
:
The feedback score of an e-store in uncertainty
avoiding culture will be lower than the feedback score in
uncertainty accepting culture.
Size affects feedback scores
Prior research finds that non-price cues are important in
the formation of store images (Kshetri 2002).
Prospective buyers are willing to pay higher prices when
non-price cues such as extra services, late hours,
expensive interiors, etc. are present in a store (Brown
1969). Literature suggests that consumers evaluate e-
store alternatives on a number of attributes which are
defined differently from those used to evaluate brick-
and-mortar stores (Lim and Dubinsky 2004).
One cue about an eBay store is its size. On every eBay
e-store’s website, customers can easily see a line at the
top of product lists and pictures: ‘‘[number of] items
found in All Categories.’’ The number can be as large as
thousands or as small as a single digit. This number
refers to the numbers of items available from an e-store,
thus representing the size of the e-store.
As discussed above, the underlying concept of feed-
back score is online customer’s trusting belief in an e-
store. The trust literature suggests that buyers use size as
a signal that a seller can be trusted. In a traditional
market, a store’s size assists consumers in forming their
impressions regarding the store’s trustworthiness as well
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as their willingness to patronize the store (Andersen
2001, Chow and Holden 1997). In electronic markets,
consumers recognize differences in size among Internet
stores; perceived size significantly influences consumers’
assessments of an e-store’s trustworthiness and their
perceptions of risk regarding doing business with that e-
store (Jarvenpaa et al. 2000).
Our research model predicts that an e-store’s size will
influence the e-store’s feedback score (customer trust in
the e-store) for several reasons. First, the perception of
large organizational size implies that other buyers trust
the organization and conduct business successfully with
it. Second, large size also signals that the firm should
have the necessary expertise and resources for support
systems such as customer and technical services; the
existence of these systems encourages trust (Doney and
Cannon 1997). Third, large sellers have more resources
invested in their businesses and hence are perceived by a
buyer to have more to lose than smaller firms by acting
in an untrustworthy way. According to the calculative-
based trust prospective (Coleman 1990, Gefen et al.
2003a), more to lose means higher possibility of not-
cheating. Therefore, a bigger size e-store is more
trustworthy than a smaller-size e-store.
Hypothesis 4: An e-store’s perceived size will increase its
feedback score.
HISTORY AFFECTS FEEDBACK SCORES
In every eBay member’s profile, customers can see a line
such as ‘‘Member since: Mar-11-03,’’ thus customers
know how long this member has operated on eBay.
Customer can also see the ID history of the member.
It is possible that the temporal history will affect an e-
store’s feedback score since temporal history may affect
customer trust in that e-store. It takes time for an e-store
to accumulate a trading history. Such a history contains
trust-related knowledge based on which a customer can
understand an e-store and its owner, thus judging its
competence, integrity, benevolence and predictability
(i.e. trustworthiness). With a long history, customers can
judge whether an e-store’s particular behaviour is
attributed to the store’s internal characteristics or is a
temporary trick. Second, a long history of an e-store
signals competence in e-commerce. It is relatively easy to
start a new Internet retail web space but it takes effort to
become an e-store with a history. Thus a store’s long
history is more valuable than a short history. From the
perspective of calculative-based trust (Coleman 1990,
Gefen et al. 2003a), the more valuable the history is, the
less likely that an e-store will engage in a distrust
behaviour. In addition, store reputation, including
company history, contributes to a customer’s comfort
level in dealing with a firm through the Internet (Lohse
and Spiller 1998). Therefore,
Hypothesis 5
:
An e-store’s temporal history will increase its
feedback score.
METHODOLOGY
Data collection and analysis
Our study uses field data to examine whether a good
feedback profile leads to success, as measured by sales
volume, in real auction settings. As antecedents, the
effects of culture, store size and store temporal history
are evaluated. Table 1 displays the measures used to
operationalize our constructs.
As there is no direct measure of trust or success in the
eBay data, the research model had to be modified.
Instead of testing the relationship between trust and
success, we tested a direct relationship between feedback
profiles and sales volume and the antecedent effects of
location of seller, store size and store history on that
relationship.
Several strategies exist to increase Internet sales for
online stores: such strategies include displaying custo-
mer endorsements (e.g., eBay.com’s Feedback Forum),
website endorsements (e.g., the Yahoo portal), and
incorporating seals of approval (e.g., WebTrust). eBay’s
Feedback Forum is one implementation of the strategy
inviting existing customers to provide comments about
their buying and selling experiences to other potential
customers. The forum is a way an e-store can provide
information, or signals, to differentiate it from other
sellers. The incentive to the e-store is that by collecting
and disseminating information about the store’s transac-
tion history, the feedback profile provides proof of the e-
store’s reputation. Within eBay, buyers can assess the
past behaviour of all available sellers, and they are able to
choose. Buyers will trust sellers who have good feedback
profiles and this not only provides a signal of trust-
worthiness to buyers, but also indicates that sellers have
incentives to maintain good feedback profiles (Ba and
Pavlou 2002).
The relationship between trust, i.e., the analysis of the
seller’s feedback profile, and intention, i.e., a buyer’s
confidence in the seller, has been characterized as one of
diminishing marginal utility (Thaler 1985). In other
words, the incremental impact of a given increase in
reputation on intention to buy decreases as the
reputation goes up. The relationship is not linear.
Hence our empirical dependent variable is the logarithm
of the net number of positive and negative ratings,
similar to that used by Ba and Pavlou (2002).
Determining the number of successful auctions within
a 30-day period developed the measure of success of the
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e-stores. Given the insufficiency of empirical assessment
of e-store performance measures and because most
Internet retailers were not profitable from an accounting
point of view (Mahajan and Srinivasan 2002), we were
precluded from using traditional performance metrics,
such as return on assets, return on sales, and so on,
which are used to examine relative business performance
(Palepu et al. 1996). We find further support in that the
differences among industries suggest that the character-
istics of the industry in which the firm operates be taken
into consideration when measuring performance
(Chrisman et al. 1998). Moreover, it is purported that
within e-commerce industries, such as on-line auctions,
there are particular goals that stem from the conditions
and characteristics unique to the industry (Mahajan and
Srinivasan 2002). For example, using revenues or the
number of employees as performance measures is
especially relevant to small and new businesses that
frequently do not have profit histories and are not
expected to show profitability during the first years of
existence. Moreover, revenues are considered a valid
measure for presenting overall performance, especially in
relatively homogenous samples, when firms from a
particular industry operate under very similar cost
structures (Haber and Reichel 2005). Thus we modified
the hypotheses and use the numbers of e-store
completed sales as a proxy for success.
In addition, it is appropriate to stress that feedback
score is different and independent from success (i.e., the
number of successful transactions in a given time
period). Feedback score is determined from the time
the e-store became an eBay member, while success refers
to the number of transactions within a one month
period – the first sample in 2005, the second in 2007.
Feedback scores exist before the success metric is
determined. Additionally, feedback score is calculated
as the number of satisfied eBay members minus the
number of dissatisfied eBay members; it does not include
repeated transactions from the same member – each
member can only contribute to a feedback score once.
However, success (i.e., the number of transactions) can
contain repeated transactions from the same eBay
members and not every one who participated in
transactions will give feedback ratings. In reality, less
than 50% buyers and sellers gives feedback as evidence
by seller forums such as: http://www.amazonseller-
community.com/forums/thread.jspa?messageID51143431
and#1143431.
Table 1. Measures and metrics were developed for our constructs based on prior research and publications
Construct Measure Metric References
Culture Location of seller Located in an individualistic versus
collectivistic culture per Hofstede’s
cultural dimensions
Hofstede (1980, 2001)
Hofstede et al. (1990)
Lim et al. (2004)
Triandis (1995)
Triandis and Suh (2002)
Located in an low uncertainty avoidance
culture versus a high uncertainty
avoidance culture per Hofstede’s
cultural dimensions
Korgaonkar and Wolin (1999)
Donthu and Garcia (1999)
De Mooij and Hofstede (2002)
Straughan and Albers-Miler (2001)
Doney et al. (1998)
e-store History How long has the Internet
merchant been an eBay e-store
Number of days as an eBay e-store –
at the end of the sample period
Kshetri (2002)
Lim and Dubinsky (2004)
Lohse and Spillar (1998)
e-store Size What is the number of items for
sale in the product category
Number of items for sale in the product
category at the end of the sample period
Jarvenpaa et al. (2000)
Andersen (2001)
Chow and Holden (1997)
Doney and Cannon (1997)
Trust eBay Feedback Rating Overall number of positive ratings minus
the number of negative ratings
Ba and Pavlou (2002)
McKnight et al. (2002)
Gefen et al. (2003)
Jarvenpaa et al. (2000)
Macintosh and Lockshin (1997)
Thaler (1985)
Success Sales transactions Number of successful transactions during
the 30-day sample period
Mahajan and Srinivasan (2002)
Haber and Reichel (2005)
Westhead et al. (2001)
Chrisman et al. (1998)
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Data were collected from eBay, which encompasses
transactions on local, national, and international bases.
Its feedback forum allows buyers to leave comments
about sellers with whom they have transacted, rating
them as positive, negative, or neutral and is readily
available to any prospective buyer. For the period from 3
November 2005 to 2 December 2005 we collected data
from 84 eBay e-store affiliates consisting of 65,067
completed auctions for the category of consumer
electronics. Data included the location of the seller,
seller history in days, the number of items for sale, the
feedback profile of each seller, and the number of
successfully completed transactions during the sample
period. Sellers were located in fourteen countries. The
country location of the Internet portal was also
collected. Figures 2 to 5 contain Internet print screens
relevant to the collection of the data. Data collection was
facilitated by the uniformity of eBay’s webpages across
all portals. We accessed eBay’s international websites
from hyperlinks at the bottom of most eBay main web
pages, e.g., www.ebay.com. From these main pages, we
selected Consumer Electronics as the product category
and collected the data from the ‘‘eBay Stores’’ presented
in this category. eBay e-stores were deemed to be
international if 1) worldwide shipping was available from
the e-store, and 2) at least one transaction during the
sample time frame was conducted by a buyer whose eBay
identification located him(her) outside of the eBay
seller’s country.
In marketing research as in the behavioural sciences,
there is growing concern of the degree to which the
research can be validated and its findings generalized
(Permut 1976). Validation, in this sense, is concerned
with the ability of a study to bear replication. The
concern for replicability also involves consideration of
reliability, and reliability is defended most rigorously by
cross-validation (Smith 1970). Pertinent to this study,
we collect a second sample for the product category of
health and beauty products for the period 1 – 31 March
2007. This sample represented 148,273 completed
auctions from 346 eBay e-stores across 22 countries
(including the 14 countries covered in the first sample).
The second sample allows for cross-validation in this
study to determine the reliability of data for the model –
by examining a different product type, to determine
whether socio-cultural changes over time have occurred
in the dynamic electronic marketplace – by obtaining a
more recent sample, and to aid in the determination of
the generality of obtained findings.
Tables 2 and 3 show the descriptive statistics of the
location, history and feedback ratings of the two
samples.
Data analysis
We use OLS regression to analyze the data. Prior to
performing the analyses, we ensured that the basic
assumptions of regression analysis were satisfied. To test
the relationships between size of the store, store
history and culture, as independent variables, and trust
in the e-store, as the dependent variable, multivariate
Figure 2. eBay e-stores listed as a selection in the left margin of eBay’s Ireland portal for the category of Consumer Electronics. eBay’s
uniformity across its portals facilitated ease of data collection
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regression analysis was performed. To test the relation-
ship between feedback ratings and e-store success,
multivariate regression analysis was again used, with
the independent variable being the logarithm of the net
number of positive and negative ratings. The dependent
variable was the success of the e-store as measured by the
volume of store sales. All regressions have high tolerance
and low values for VIF.
RESULTS
Table 4 presents the regression results between trust
(feedback profile) and culture (individualism versus
collectivism and uncertainty avoidance), size (number
of items for sale), and history (number of days as an eBay
e-store). Regression analysis found significant correla-
tion between culture, size, and history and trust. This
Figure 4. eBay Brazilian portal. Note consistency in Web site presentation with eBay US
Figure 3. eBay seller feedback profile for an e-store located in Hong Kong and featured in the eBay Ireland portal. eBay member profiles are
also uniform throughout all eBay portals
196 Paul Komiak, Sherrie Y. X. Komiak and Michael Imhof &International Business at eBay
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provides evidence that a positive buyer feedback profile
will exist and have a greater positive impact in cultures
with higher individualism versus in cultures with higher
collectivism and that buyers do take into account
reputation indicators such as a seller’s size and history.
Therefore field data provide support for our theoretical
arguments that culture may account for buyer trust in an
Internet store and that positive indicators of size and
history may induce higher trust, confirming Hypothesis
1, Hypothesis 2, Hypothesis 3 and Hypothesis 4 in the
research model. It was expected that higher relative
feedback ratings would lead to higher sales volume. The
regression results indicate that store sales are significantly
influenced by trust in that store, confirming Hypothesis
5 in our research model. Table 5 summarizes the key
findings of the study. The data, cross-validating the
feedback score and its antecedents in both product
categories, generally support the proposition that trust
and trust beliefs differ across cultures, and thus may be a
variable aspect of e-commerce.
DISCUSSION
Theoretical implications
This study was carried out in a real-life environment, in
which actual buyers selected e-stores and completed
purchase transactions. Comments provided by previous
buyers, contained in the e-stores’ feedback profiles, and
the locations of sellers were readily available for all
prospective buyers to examine. This study examined the
number of completed purchase transactions as compared
to previous studies (Ba and Pavlou 2002; Gefen et al.,
2003b; Jarvenpaa et al. 2000), where buyer intention or
belief was studied. Moreover, our study attempts to
make theoretical inferences about the role of culture in
the global competitiveness of Internet businesses.
Our results confirm and extend previous research
findings. The factors of individualism-collectivism and
uncertainty avoidance were shown to be significant in
explaining differences across cultures. Previous literature
suggests that consumers evaluate e-store alternatives on
a number of attributes that are defined differently from
those used to evaluate brick-and-mortar stores. This
study shows that store reputation, including company
history, contributes to a customer’s comfort level in
dealing with a firm through the Internet. This study also
confirms the importance of store size and its ability to
evoke consumer trust.
Practical and policy implications
Our results clearly point to a number of practical
implications for successful Internet marketing strategies
using eBay as the electronic market platform. First, our
study has implications for the structure and operation of
eBay.com’s Feedback Forum. It seems better to separate
a member’s feedback score as a buyer versus his or her
feedback score when this eBay member participates as a
seller. The two feedback scores are different in their
nature. For a seller, the buyer’s feedback score as a buyer
is not very important, because the risk for the seller is
small. For example, the seller can wait to get payment
before the seller sends the goods to the buyer. However,
Figure 5. eBay seller feedback profile from Brazilian portal
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for a buyer, the seller’s feedback score as a seller is very
important. Although mediated, the buyer still has to pay
before he or she receives the goods. In addition, if an
eBay member wants to fabricate a more positive feed-
back score, it is much easier for this member to create (in
other words, purchase) a feedback score as a buyer by
buying multiple cheap items. However, it is much more
difficult to earn feedback score as a seller by successfully
selling many goods.
Overall, the Feedback Ratings are numerically highly
positive. Some members may be afraid to give negative
feedback for fear that the recipient member will give
negative feedback ratings as revenge – this negative
exchange of feedback was observed in both samples.
Cultures differ in their relationship between conflict and
satisfaction (Griffith et al. 2000). As a result, the level of
conflict reported by a business partner may be reduced.
This is supported by earlier research which finds that
members of a cultural group (i.e., collectivist, large
power distance, strong uncertainty avoidance) will often
avoid conflict in order to preserve a relationship
(Moghaddan et al. 1993). It may be as simple as
adopting a policy to not post one transacting member’s
feedback until both transacting members have com-
pleted their feedback ratings, or until a deadline of
giving feedback rating has past for both transacting
members. In sum, eBay may be able to improve its
electronic market efficiency (e.g., overcome information
asymmetry, lack of trust) by implementing culturally
cognizant procedures.
Second, our results make evident several tactics for
eBay e-stores. It appears that e-stores in individualistic
cultures can earn higher feedback scores. It seems to
behove an e-store to open a branch (i.e., become a
member and e-store) in a county with individualistic
culture. Of course, high feedback scores and cultural
dimensions can have alternative implications: collectivis-
tic e-stores should learn from individualistic e-stores
about how to treat anonymous buyers (out-group
members). Equally as important as culture in assessing
and predicting buyer behaviour in eBay e-stores are store
attributes. It has been shown here that store size and the
amount of time an e-store has been in business may
affect the level of trust a buyer will have in that store.
Customers, it appears, equate size and store history with
trustworthiness. This has practical implications for
online retailers using or planning to use web portals
such as eBay to launch their own e-stores. Following our
results, maintaining an accessible store history and
increasing perceived size might be advantageous strate-
gies for e-store success. In terms of size, e-stores may
consider combining with other e-stores or listing
individual items separately, rather than in groups. As
history is also valuable, these stores should consider
combining with long tenured e-stores.
Results of the study highlight the need for managers
to systematically develop the appeal and trustworthiness
of their websites. Because they engender trust in buyers,
adding culturally specific features such as localizing the
feedback mechanism may be the most important
improvements an e-store can make. The study’s findings
underline the importance for managers to maintain a
competitive advantage by evoking positive feelings
during the shopping experience. To compete globally
on the Internet, merchants designing for only one
market are going to have to change their way of doing
Table 2. Descriptive statistics of the location of the 84 e-stores in
Sample 1 and the 346 e-stores in Sample 2. Sellers were located
in 22 countries
Location of Seller Frequency %
Sample 1
Australia 4 4.8
Brazil 5 6.0
Canada 4 4.8
China 8 9.5
France 5 6.0
Germany 3 3.6
Hong Kong 5 6.0
India 5 6.0
Italy 10 11.9
Mexico 4 4.8
Spain 5 6.0
Taiwan 2 2.4
UK 5 6.0
US 19 22.6
Total 84 100
Sample 2
Argentina 7 2.0
Australia 14 4.0
Austria 10 2.9
Belgium 13 3.8
Brazil 5 1.4
Canada 4 1.2
France 16 4.6
Germany 38 11.0
Hong Kong 44 12.7
India 1 0.3
Italy 23 6.6
Japan 2 0.6
Mexico 9 2.6
Netherlands 17 4.9
Poland 4 1.2
Singapore 4 1.2
Spain 16 4.6
Switzerland 2 0.6
Taiwan 1 0.3
Thailand 1 0.3
UK 46 13.3
US 69 19.9
Total 346 100
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business; adopting strategies that capitalize on the
unique cultural preferences for particular markets
appears to be a better approach.
Finally, the results of this study may give policymakers
a better understanding of the role culture, store size and
store history play in shaping online consumer behaviour.
Differences in pre- and post-purchase behaviour, secur-
ity and privacy concerns, and methods of dispute
resolution as well as values, norms, and traditions may
impact the needs and demands of increasingly divergent
online consumer markets. For those responsible for the
protection of online businesses and consumers as well as
the facilitation of information technology, understand-
ing the determinants of eBay e-store success may provide
a clearer picture of those factors affecting the success of
online retailers in general.
Government initiatives, suited to the local culture, can
be used in promoting electronic commerce. The
geographic landscape of e-commerce is changing.
Foreign consumers are increasingly demanding local
content (Gibbs et al. 2003), customized websites,
information, and products particular to their individual
interests (Ha 2004). Once lacking the necessary
technological infrastructure needed to connect their
Table 3. Data included the location of the seller in terms of Hofstede I-C and UA indices, seller history in days, the number of items for
sale, the feedback profile of each seller, and the number of successfully completed transactions during the sample period
A. Descriptive statistics of the individualism-collectivism, uncertainty avoidance, size, history, feedback ratings, and items sold of the 84 e-
stores in Sample 1.
N Minimum Maximum Mean Std. deviation
I-C cultural index 84 17 91 63.02 26.881
UAI cultural index 84 29 86 55.73 19.844
Size 84 43 6889 1018.49 1339.339
History 84 160 2932 1069.92 568.371
Feedback 84 67 197085 13679.11 32284.047
Items Sold 84 14 8593 774.61 1511.078
Correlations
Pearson Correlation Size History I-C cultural index UA cultural index
Size 1.0
History .069 1.0
I-C cultural index .043 .361 1.0
UA cultural index 2.324 2.176 .022 1.0
B. Descriptive statistics of the individualism-collectivism, uncertainty avoidance, size, history, feedback ratings, and items sold of the 346 e-
stores in Sample 2.
N Minimum Maximum Mean Std. deviation
I-C cultural index 346 17 91 67.82 24.055
UAI cultural index 346 8 94 55.82 20.970
Size 346 2 32409 1005.65 2550.444
History 346 7 3371 1032.02 651.828
Feedback 346 3 113098 4802.26 11071.640
Items sold 346 0 17847 428.53 1139.488
Correlations
Pearson Correlation Size History I-C cultural index UA cultural index
Size 1.0
History .087 1.0
I-C cultural index .157 .289 1.0
UA cultural index 2.205 2.176 2.025 1.0
Electronic Markets Vol. 18 No 2 199
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economies to the World Wide Web, developing coun-
tries are making structural improvements, often bypass-
ing obsolete technologies still heavily used in countries
like the United States and Canada (Johnson-Page and
Thatcher 2001). The policy key for increasing the
diffusion and acceptance of electronic markets as a way
of doing business is to include culture in a significant
way. For example, in high uncertainty avoidance
cultures, perceived uncertainty may be the impediment
to e-commerce. Policies aimed at protecting the interests
of transacting parties or the creation of secure transac-
tion infrastructures would be effective. Similarly, for
collectivist cultures, creating an aura of in-group
acceptance of e-commerce, may increase its adoption
in both developed and developing countries.
Limitations and future research
First, this study examines the effect of culture as
determined by the location of the seller, i.e., the e-store.
A relationship between the seller’s culture and trust in
that seller was hypothesized and supported in this study.
Alternative approaches could examine the relation
between buyer’s culture and trust in the seller or the
effects of cultural alignment between both buyer and
seller. Replicating the study using different and larger
groups of subjects could only assess whether the results
are applicable to other Internet users.
Second, as in Ba and Pavlou’s (2002) study, a
limitation was the use of secondary data, which did not
allow for the measurement of trust perceptions.
Although elements of the written comments that
accompanied sellers’ ratings were collected, e.g., loca-
tion of buyer, dispute resolution, etc., the written
comments were not evaluated and used in assessing
the degree of buyer trust. Buyers’ comments offer
notable information that cannot be captured by
simple ratings (Ba and Pavlou 2002). Analysis of
written comments may reveal new information about
the role of feedback mechanisms. Future research could
analyze the role of written comments in determining
trust and the relative importance of buyer and seller
locations.
Future studies can extend this research in additional
ways. For example, research that compares the relative
effectiveness of different web strategies across cultures is
important because each trust-building mechanism, such
as a web strategy, can come with a cost to the user
organizations. Results of such research could thus
inform organizations operating in different cultures of
how their websites could be customized for maximum
Table 4. Regression results (1) between trust (feedback profile) and cultural dimensions (IC, UA), size (number of items for sale), and
history (number of days as a registered eBay e-store) and regression results (2) between trust (feedback profile) and sales
Sample 1 Sample 2
Regression 1 R
2
(adjusted) F-value B
i
tR
2
(adjusted) F-value B
i
t
DV IV
Log(P-N) .403 15.325
a
.488 83.236
a
LS-IC .259 2.847
a
.290 7.454
a
LS-UA 2.191 22.113
b
2.338 28.519
a
HistDay .381 4.122
a
.335 8.282
a
SizeNoAll .193 2.169
b
.256 5.816
a
Regression 2
ItmSld1M
Log(P-N) .488 81.975
a
.363 172.318
a
Collinearity Statistics
Sample 1 Sample 2
Model 2 Tolerance VIF Tolerance VIF
LS-IC .849 1.178 .969 1.032
LS-UA .859 1.165 .906 1.103
HistDay .822 1.216 .886 1.128
SizeNoAll .888 1.126 .878 1.139
P-N5positive ratings – negative ratings;
a
p,0.01,
b
p,0.05
200 Paul Komiak, Sherrie Y. X. Komiak and Michael Imhof &International Business at eBay
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effectiveness, while due consideration could be given to
minimize the associated costs.
While our research examined the success of e-stores,
measured by the number of successful transactions
completed on eBay, many relevant refinements and
extensions beckon. Success can be measured by a high
percentage of international transactions or high price
premiums. Furthermore, what antecedents influence the
success of these e-stores? The antecedents examined in
this research include a store’s feedback profile, size and
location. Extensions include the examination of product
type, product price, payment method and delivery speed.
An alternative approach would study the effects of the
new or modified trust-building methods available on
eBay: the PayPal Buyer Protection Policy, the Buyer
Compliant Policy, and eBay’s Standard Purchase
Protection Program, together with the Feedback
Forum mechanism.
CONCLUSION
This research has empirically investigated the impact of
culture on the propensity for shopping on the Internet.
It demonstrates the need to consider specific cultural
dimensions, such as individualism versus collectivism and
uncertainty avoidance, as well as to maintain and
disseminate positive store attributes, in the design of
websites and web strategies to build trust. This may be
particularly important for new or relatively new Internet
stores, but in such a competitive environment as the e-
business market, well-established stores should also
recognize the importance of being culturally sensitive.
This research shows that the seller feedback profile
strategy is particularly effective for collectivistic con-
sumers. This research highlights the importance of being
culturally sensitive. Only by addressing the cultural
needs of consumers can Internet merchants achieve their
aims of participating in an increasingly global market-
place.
References
Ahlstrom, D., Foley, S., Young, M. N. and Chan, E. S. (2005)
‘Human Resource Strategies in Post-WTO China’,
Thunderbird International Business Review 47(3): 263–85.
Al-Qirim, N. (2005) ‘An Empirical Investigation of an e-
Commerce Adoption–Capability Model in Small Businesses
in New Zealand’, Electronic Markets 15(4): 418–37.
Table 5. The key findings of the study vis-a
`-vis hypotheses
Construct Measure Hypothesis
Expected
Relationship Findings Discussion
Culture Location of seller:
individualism versus
collectivism
Positive customer endorsements
will have a greater impact on
trust in cultures higher on
collectivism versus in cultures
higher on individualism.
Positive Supported
Location of seller: Low
versus high uncertainty
avoidance
Positive customer endorsements
will have a greater impact on
trust in cultures lower on
uncertainty avoidance versus in
cultures higher on uncertainty
avoidance.
Negative Supported
e-store Size Number of items for sale An e-store’s perceived size will
significantly and positively
affect consumer’s trust in
an Internet store.
Positive Supported
e-store History Number of days as an
eBay e-store
An e-store’s temporal history
will significantly and positively
affect consumer’s trust.
Positive Supported
Trust Net feedback rating:
Number of positive
ratings – number of
negative ratings
Higher consumer trust toward
an Internet store will generate
higher sales from the store.
Positive Supported Trust not explicitly measured
– eBay feedback profile
used as a proxy for trust.
Success Sales: Number of
successful transactions
Relative success measured
by the number of
successful transactions
Electronic Markets Vol. 18 No 2 201
Downloaded By: [Schmelich, Volker] At: 14:35 24 March 2010
Andersen, R. H. (2001) ‘Relationship Development and
Marketing Communication: An Integrative Model’, Journal
of Business and Industrial Marketing 16(3): 167–82.
Anderson, E. and Weitz, B. (1989) ‘Determinants of
Continuity in Conventional Industrial Channel Dyads’,
Marketing Science 8: 310–23.
Anderson, J. C. and Narus, J. A. (1990) ‘A Model of
Distributor Firm and Manufacturer Firm Working
Partnerships’, Journal of Marketing 54: 42–58.
Ba, S. and Pavlou, P. (2002) ‘Evidence of the Effect of Trust
Building Technology in Electronic Markets: Price
Premiums and Buyer Behavior’, MIS Quarterly 26(3):
243–68.
Barnett, G. A. and Sung, E. (2005) ‘Culture and the Structure
of the International Hyperlink Network’, Journal of
Computer-Mediated Communication 11(1): 217–38.
Black, G. S. (2005) ‘Is eBay for Everyone? An Assessment of
Consumer Demogaphics’, S.A.M. Advanced Management
Journal 70(1): 50.
Blomqvist, K. (1997) ‘The Many Faces of Trust’,
Scandinavian Journal of Management 13(3): 271–86.
Brown, E. (1969) ‘Price Image versus Price Reality’, Journal of
Marketing Research 6(2): 185–91.
Child, J. (1981) ‘Culture, Contingency and Capitalism in the
Cross National Study of Organizations’, in: L. L.
Cummings and B. M. Staw (eds) Research in
Organizational Behavior, (Vol. 3), Greenwich, CT: JAI
Press.
Chopra, K. and Wallace, W. A. (2003) ‘In Trust in Electronic
Environments’, paper presented at the Proceedings of the
36th Hawaii International Conference on System Sciences
(HICSS 2003), Hawaii: IEEE.
Chow, S. and Holden, R. (1997) ‘Toward an Understanding
of Loyalty: The Moderating Role of Trust’, Journal of
Managerial Issues 9(3): 275–98.
Chrisman, J. J., Bauerschmidt, A. and Hofer, C. W. (1998)
‘The Determinants of New Venture Performance: An
Extended Model’, Entrepreneurship Theory and Practice
23(1): 5–29.
Coleman, J. C. (1990) Foundations of Social Theory,
Cambridge, MA: Harvard University Press.
D’Annunzio-Green, N. (2002) ‘An Examination of the
Organizational and Cross-cultural Challenges Facing
International Hotel Managers in Russia’, International
Journal of Contemporary Hospitality Management 14(6):
266–73.
Darling, J. R. and Box, T. M. (1999) ‘Keys for Success in the
Leadership of Multinational Corporations, 1990 through
1997’, S.A.M. Advanced Management Journal 64(4):
16–21.
Deng, J., Walker, G., Swinnerton, G., Walker, G. J. and
Vilet, V. (2006) ‘A Comparison of Environmental Values
and Attitudes between Chinese in Canada and Anglo-
Canadians’, Environment and Behavior 38(1): 22–47.
Doney, P.-M. and Cannon, J.-P. (1997) ‘An Examination of
the Nature of Trust in Buyer-seller Relationships’, Journal
of Marketing 61(2): 35–51.
Doney, P. M., Cannon, J. P. and Mullen, M. R. (1998)
‘Understanding the Influence of National Culture on the
Development of Trust’, Academy of Management Review
23(3): 601–20.
Dow, D. (2006) ‘Adaptation and Performance in Foreign
Markets: Evidence of Systematic Under-adaptation’,
Journal of International Business Studies 37(2): 212–26.
Dwyer, F. R. and Lagace, R. R. (1986) ‘On the Nature and
Role of Buyer-Seller Trust’, AMA Summer Educators
Conference Proceedings, Chicago.
Elahee, M. N., Kirby, S. L. and Nasif, E. (2002) ‘National
Culture, Trust and Perceptions about Ethical Behavior in
Intra- and Cross–cultural Negotiations: An Analysis of
NAFTA Countries’, Thunderbird International Business
Review 44(6): 799–818.
Elenkov, D. and Fileva, T. (2006) ‘Anatomy of a Business
Failure: Accepting the ‘‘Bad Luck’’ Explanation vs
Proactively Learning in International Business’, Cross
Cultural Management 13(2): 132–41.
Ess, C. and Sudweeks, F. (2005) ‘Culture and Computer-
mediated Communication: Toward New Understandings’,
Journal of Computer-Mediated Communication 11(1):
179–91.
Fey, C. F. and Bjorkman, I. (2001) ‘The Effect of Human
Resource Management Practices on MNC Subsidiary
Performance in Russia’, Journal of International Business
Studies 32(1): 59–75.
Fishbein, M. and Ajzen, I. (1975) ‘Belief, Attitude, Intention
and Behavior: An Introduction to Theory and Research’
Reading, MA: Addison-Wesley.
Gabarro, J. J. (1978) ‘The Development of Trust, Influence
and Expectations’, in: A. G. Athos and J. J. Gabarro (eds)
Interpersonal Behavior: Communication and Understanding
in Relationships, Englewood Cliffs, NJ: Prentice
Hall. pp. 290–303.
Galan, J. I., Galende, J. and Gonzalez-Benito, J. (1999)
‘Determinant Factors of International Development: Some
Empirical Evidence’, Management Decision 37(10):
778–85.
Gefen, D. and Heart, T. (2006) ‘On the Need to Include
National Culture as a Central Issue in e-Commerce Trust
Beliefs’, Journal of Global Information Management 14(4):
1–30.
Gefen, D., Karahanna, E. and Straub, D. (2003a) ‘Trust and
TAM in Online Shopping: An Integrated Model’, MIS
Quarterly 27(1): 51–90.
Gibbs, J., Kraemer, K. L. and Dedrick, J. (2003) ‘Environment
and Policy Factors Shaping Global e–Commerce Diffusion:
A Cross-country Comparison’, Information Society 19(1):
5–18.
Goodbody, J. (2005) ‘Critical Success Factors for Global
Virtual Teams’, Strategic Communication Management
9(2): 18–22.
Gorg, H. and Strobl, E. (2003) ‘Multinational Companies,
Technology Spillovers and Plant Survival’, The
Scandinavian Journal of Economics 105(4): 581–95.
202 Paul Komiak, Sherrie Y. X. Komiak and Michael Imhof &International Business at eBay
Downloaded By: [Schmelich, Volker] At: 14:35 24 March 2010
Griffith, D. A., Hu, M. Y. and Ryans, J. K. J. (2000) ‘Process
Standardization across Intra- and Inter-cultural
Relationships’, Journal of International Business Studies
31(2): 303–24.
Grimm, S. D., Church, A. T., Katigbak, M. S. and Reyes, J. A.
S. (1999) ‘Self-Described Traits, Values and Moods
Associated With Individualism and Collectivism: Testing I-
C Theory in an Individualistic (U.S.) and Collectivistic
(Philippine) Culture’, Journal of Cross Cultural Psychology
30(4): 466–500.
Ha, H.-Y. (2004) ‘Factors Influencing Consumer Perceptions
of Brand Trust Online’, The Journal of Product and Brand
Management 14(4/5): 329–42.
Haber, S. and Reichel, A. (2005) ‘Identifying Performance
Measures of Small Ventures – The Case of the Tourism
Industry,’ Journal of Small Business Management 43(3):
257–86.
Hawes, J. M., Rao, C. P. and Baker, T. L. (1993) ‘Retail
Salesperson Attributes and the Role of Dependability in the
Selection of Durable Goods’, Journal of Personal Selling
and Sales Management 13(Fall): 61–71.
Hofstede, G. (1980) Culture’s Consequences, Beverly Hills:
Sage.
Hofstede, G. (1983) ‘The Cultural Relativity of Organizational
Practices and Theories’, Journal of International Business
Studies 14: 75–89.
Hofstede, G. (2001) Culture’s Consequences: Comparing
Values, Behaviors, Institutions and Organizations across
Nations, (2nd ed.), Thousand Oaks, CA: Sage Publications.
Hofstede, G., Neujen, B., Ohayv, D. D. and Sanders, G.
(1990) ‘Measuring Organizational Cultures: A Qualitative
and Quantitative Study Across Twenty Cases’,
Administrative Science Quarterly 35: 286–316.
Holtbrugge, D. (2004) ‘Management of International
Strategic Business Cooperation: Situational Conditions,
Performance Criteria and Success Factors’, Thunderbird
International Business Review 46(3): 255–74.
Iyengar, S. S., Lepper, M. R. and Ross, L. (1999)
‘Independence from Whom? Interdependence with Whom?
Cultural Perspectives on Ingroups versus Outgroups’, in:
D. Miller and D. Prentice (eds) Cultural Divides:
Understanding and Overcoming Group Conflict, New York:
Sage, pp. 273–301.
Jarvenpaa, S. L., Tractinsky, N. and Vitale, M. (2000)
‘Consumer Trust in an Internet Store’, Information
Technology and Management 1: 45–71.
Jennex, M. E., Amoroso, D. and Adelakun, O. (2004) ‘e-
Commerce Infrastructure Success Factors for Small
Companies in Developing Economies’, Electronic
Commerce Research 4(3): 263–86.
Johnson-Page, G. F. and Thatcher, R. S. (2001) ‘B2C Data
Privacy Policies: Current Trends’, Management Decision
39(4): 262–71.
Johnston, K. and Johal, P. (1999) ‘The Internet as a ‘‘Virtual
Cultural Region’’: Are Extant Cultural Classification
Schemes Appropriate?’, Internet Research 9(3): 178–86.
Kacen, J. J. and Lee, J. A. (2002) ‘The Influence of Culture on
Consumer Impulsive Buying Behavior’, Journal of
Consumer Psychology 12(2): 163–76.
Komiak, S. Y. X. and Benbasat, I. (2006) ‘The Impact of
Internalization and Familiarity on Trust and Adoption of
Recommendation Agents’, MIS Quarterly 30(4): 941–60.
Kshetri, N. (2002) ‘In Factors Influencing Consumers’
Reaction to a Price and Intention to Bid in a C-to-C
Internet Auction’, (Vol. 13), paper presented at the
American Marketing Association, Austin, TX, pp. 44–50.
Liang, T. P., Lin, C. Y. and Chen, D. N. (2004) ‘Effects of
Electronic Commerce Models and Industrial Characteristics
on Firm Performance,’ Industrial Management and Data
Systems 104(7): 538–45.
Lim, H. and Dubinsky, A. J. (2004) ‘Consumers’ Perceptions
of e-shopping Characteristics: An Expectancy-value
Approach’, The Journal of Services Marketing 18(6/7): 500.
Lim, K. H., Leung, K., Sia, C. L. and Lee, M. K. O. (2004) ‘Is
e-Commerce Boundary-less? Effects of Individualism-
Collectivism and Uncertainty Avoidance on Internet
Shopping’, Journal of International Business Studies 35(6):
545–59.
Lohse, G. L. and Spiller, P. (1998) ‘Electronic shopping: How
Do Customer Interfaces Produce Sales on the
INTERNET?’ Communications of the ACM 41(7): 81–7.
Luhmann, N. (1979) Trust and Power, Chichester, UK: Wiley.
Lynch, P. D. and Beck, J. C. (2001) ‘Profiles of Internet
Buyers in 20 Countries: Evidence of Region Specific
Strategies’, Journal of International Business Studies 32(4):
725–48.
Lynch, P. D., Kent, R. J. and Srinivasan, S. S. (2001) ‘The
Global Internet Shopper: Evidence from Shopping Tasks
in Twelve Countries’, Journal of Advertising Research
(May–June): 15–23.
Magrath, A. J. and Hardy, K. G. (1989) ‘A Conceptual
Framework for Assessing the Level of Mutual Trust
Between Manufacturers and Their Resellers’, paper
presented at the Proceedings of the 5th IMP Conference,
State College/University Park, Pennsylvania.
Mahajan, V. and Srinivasan, R. (2002) ‘The Dot.com Retail
Failures of 2000: Were There Any Winners?’ Journal of the
Academy of Marketing Science 30(4): 474–86.
Maitland, C. and Bauer, J. (2001) ‘National Level Culture and
Global Diffusion: The Case of the Internet’, in: C. Ess (ed.)
Culture, Technology, Communication: Towards an
Intercultural Global Village, Albany, NY: State University
of New York Press, pp. 87–120.
Mayer, R. C., Davis, J. H. and Schoorman, F. D. (1995) ‘An
Integrative Model of Organizational Trust’, Academy of
Management Review 20(3): 709–34.
McKnight, D. H., Choudhury, V. and Kacmar, C. (2002a)
‘Developing and Validating Trust Measures for e-
Commerce: An Integrative Typology’, Information Systems
Research 13(3): 334–59.
McKnight, D. H., Choudhury, V. and Kacmar, C. (2002b)
‘The Impact of Initial Consumer Trust on Intentions to
Electronic Markets Vol. 18 No 2 203
Downloaded By: [Schmelich, Volker] At: 14:35 24 March 2010
Transact With a Web Site: A Trust Building Model’,
Journal of Strategic Information Systems 11(3–4): 297–323.
McKnight, D. H., Cummings, L. L. and Chervany, N. L. (1998)
‘Initial Trust Formation in New Organizational Relationships’,
Academy of Management Review 23(3): 473–90.
McLarney, C. and Dastrala, R. (2001) ‘Socio-political
Structures as Determinants of Global Success. The Case of
Enron Corporation’, International Journal of Social
Economics 28(4): 349–68.
Moghaddan, F. M., Taylor, D. M. and Wright, S. C. (1993)
Social Psychology in Cross-cultural Perspective, New York:
Freeman.
Moorman, C., Deshpande, R. and Zaltman, G. (1993) ‘Factors
Affecting Trust in Market-research Relationships’, Journal
of Marketing 57(1): 81–101.
Morgan, R.-M. and Hunt, S.-D. (1994) ‘The Commitment-
trust Theory of Relationship Marketing’, Journal of
Marketing 58(3): 20–38.
O’Grady, S. and Lane, H. (1996) ‘The Psychic Distance
Paradox’, Journal of International Business Studies 27(2):
309–33.
Palepu, K. G., Bernard, V. L. and Healy, P. M. (1996) Business
Analysis and Valuation: Using Financial Statements,
Cincinnati: South-Western.
Permut, S. E. (1976) ‘The Researcher’s Sample: A Review of
the Choice of Respondents in Marketing Research’, Journal
of Marketing 13: 278–83.
Reid, D. M. (1995) ‘Critical Success Factors in Japanese
Consumer Products Market: Guidance for Foreign MNCs’,
International Executive 37(6): 555–82.
Rempel, J. K., Holmes, J. G. and Zanna, M. P. (1985) ‘Trust
in Close Relationships’, Journal of Personality and Social
Psychology 49(1): 95–112.
Robson, M. J., Leonidou, L. C. and Katsikeas, C. S. (2002)
‘Factors Influencing International Joint Venture
Performance: Theoretical Perspectives, Assessment and
Future Directions’, Management International Review
42(4): 385–418.
Rotondaro, R. G. (2002) ‘Defining the Customer’s
Expectations in e-Business’, Industrial Management and
Data Systems 102(9): 476–82.
Smith, N. C. (1970) ‘Replication Studies: A Neglected Aspect of
Psychological Research’, American Psychologist 25: 970–97.
Srite, M. and Karahanna, E. (2006) ‘The Role of Espoused
National Cultural Values in Technology Acceptance’, MIS
Quarterly 30(3): 679–704.
Swan, J. E., Bowers, M. R. and Richardson, L. D. (1999)
‘Customer Trust In The Salesperson: An Integrative Review
And Meta-analysis of the Empirical Literature’, Journal of
Business Research 44(2): 93–107.
Swan, J. E., Trawick, F. I. and Silva, D. W. (1985) ‘How
Industrial Salespeople Gain Customer Trust’, Industrial
Marketing Management 14: 203–11.
Thaler, R. H. (1985) ‘Mental Accounting and Consumer
Choice’, Marketing Science 4(Summer): 199–214.
Tixier, M. (1995) ‘Trends in International Business Thought
and Literature: Mixed Management Teams: How West
European Businesses Approach Central and Eastern
Europe’, International Executive 37(6): 631–44.
Triandis, H. (2001) ‘Individualism-Collectivism and
Personality’, Journal of Personality 69(9): 907–24.
Triandis, H. and Suh, E. M. (2002) ‘Cultural Influences on
Personality’, Annual Review of Psychology 53: 133–60.
Triandis, H. C. (1972) The Analysis of Subjective Culture,
New York: John Wiley.
Tudor, T. R. and Trumble, R. R. (1996) ‘Cultural Integration:
An Examination of Success for United States and Japanese
Business Mergers’, International Journal of Management
13(1): 52–9.
Tylor, E. B. (1871) Primitive Culture: Researches into the
Development of Mythology, Philosopy, Religion, Language,
Art and Custom, New York: Holt, Reinhart and Winston.
Yamagishi, T. (1988) ‘Exit from the Group as an
Individualistic Solution to the Free Rider Problem in the
United States and Japan’, Journal of Experimental Social
Psychology 24: 530–42.
Yamagishi, T., Cook, K. S. and Watabe, M. (1998)
‘Uncertainty, Trust and Commitment Formation in the
United States and Japan’, American Journal of Sociology
104(1): 165–94.
Yang, J. and Lee, H. (2002) ‘Identifying Key Factors for
Successful Joint Venture in China’, Industrial Management
and Data Systems 102(1/2): 98–109.
Yang, J. Z. (1998) ‘Key Success Factors of Multinational Firms
in China’, Thunderbird International Business Review
40(6): 633–68.
204 Paul Komiak, Sherrie Y. X. Komiak and Michael Imhof &International Business at eBay
Downloaded By: [Schmelich, Volker] At: 14:35 24 March 2010
