77
Moreover, the extant literature demonstrates little about how TCs vary between online and
traditional shopping environments (Wirtz and Lihotzky 2003, Kim and Li 2009b). As such,
the conceptualization and operationalization of TCs associated with online shopping need to
be re-considered so that a valid instrument can be developed for measuring costs-related
variables and offer a better understanding of their roles in online shopping behaviour.
Table 2.1 Summary of the Findings of the Effect of Online TCs on Behaviour-Related
Consequences
Dependent variables
Independent variables
Result
Studies
Customer acceptance of
online purchase
TCs
Negative correlation
(Liang
and Huang
1998)
Consumers’
willingness to buy
online
TCs Negative
correlation
(Teo
et al.
2004);
(Teo and Yu 2005)
Customer satisfaction
TCs
Negative correlation
(Kim and Li 2009b);
(Kim
et al.
2011)
Customer loyalty
TCs
Negative correlation
(Kim and Li 2009b)
E-shopping value
TCs
(Wu
et al.
2014)
--Information
searching cost Negative
correlation
--Moral hazard cost
Negative correlation
--Specific
asset investment
Negative correlation
Repurchase intention
TCs
Negative correlation
(Yen
et al.
2013)
--Information searching cost
Negative correlation
(Wu
et al.
2014)
--Moral hazard cost
Negative correlation
--Specific asset investment
Negative correlation
Trust TCs
0
(Kim
et al.
2011)
--Transaction security
Positive correlation
(Kim
et al.
2013b)
--Navigation functionality
Positive correlation
--Cost effectiveness
Positive correlation
78
As described earlier and shown in Table 2.2, many attempts have been
made to identify the
antecedents of TCs. However, there is no agreement in the literature as to what factors may
lead to TCs of consumers in online shopping. The study conducted by Liang and Huang
(1998) found that uncertainty and asset specificity increase the perceived TCs for the
consumers in online shopping while Teo et al. (2004) observed that product
uncertainty,
behavioural uncertainty, asset specificity, convenience, economic utility, and dependability
significantly affect TCs. This implies that there is a lack of consensus on this issue. In
addition, the identified antecedents can only account for a relatively small
percentage of the
total variance in TCs in the studies, which suggests that there might be some other potential
antecedents that have been overlooked in prior studies. Scholars (Sholtz 2001, Teo
et al.
2004,
Wu
et al.
2014) have called for more research on exploring antecedents of TCs of online
shopping. A comprehensive list of antecedent factors affecting TCs associated with online
shopping should be explored and tested simultaneously in an integrated framework.