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environments, the predictive power of the theories varies from one study to another. These
theories to some extent lack the elasticity to predict online purchase behaviour due to their
inherent limitations and the complexities of online transaction environments. Therefore, it
can be concluded that both theories do not appear capable of investigating the complexities of
online shopping behaviour. In this regard, conceptual and
empirical extensions seem
necessary and an integration of these theories may be needed.
The second section reviewed the major antecedents of online shopping adoption, especially
focusing on consumer intention to purchase online and actual online purchase behaviour.
Synthesizing a large number of studies while integrating their similar factors, this study
grouped the antecedents into three major categories, including consumer characteristics,
online vendor/store and product characteristics, and perceived channel characteristics. The
review showed that different studies have different ways of identifying the antecedents. Some
antecedents, such
as online store design, relative advantages and trust receive a lot of
attention. They seem to constitute the main streams of research in this area that is, focusing
on the benefits of online shopping. However, academic inquiry on the effects of other
antecedents, particularly the cost-relevant variables is largely neglected. Perceived costs have
been suggested as the important inhibitors to online purchase intention (Teo
et al.
2004, Teo
and Yu 2005). Despite this, far less attention has been focused on online inhibitors (e.g., costs)
than online motivators (e.g., benefits). However, an understanding of these constraints is
crucial to researchers and practitioners if they are to counteract the
negative impacts of these
inhibitors on consumers’ online shopping decision-making. Accordingly, more studies
concerning the roles the costs play in predicting online behaviour are warranted.
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In the last section, eight studies pertaining to the TCs of online shopping were carefully
reviewed. A closer look at the research shows that to date studies on the effects of TCs on
online purchase behaviour and post-purchase behaviour such as customer loyalty are lacking.
The main problem unsolved in this area is that TCs associated with online shopping do not
have a consistent conceptualization. The issue of taking different approaches to measure TCs
has been discussed very rarely in the literature. Little measurement
attention has been
attempted and the issue merits further investigation into the epistemic structure of the
measures. In this sense, it becomes evident that researchers need to be aware of the measures
of TCs. Accordingly, one of the purposes of this research is to identify and measure online
TCs. Despite an improved understanding on the antecedents of TCs, the careful assessment of
the extant studies indicates that that
little effort has been made, either theoretically or
empirically, to examine a comprehensive list of antecedent variables that affect TCs in the
online shopping context. On this issue, there is still a need for thorough investigations into
the antecedents of TCs by taking into account the consumers, vendors, and online channel-
related characteristics. Furthermore, little is currently known
about the mediators and
moderators between TCs and online behavioural
consequences, and the difference in the
relationships between antecedents and TCs, and between TCs and online behavioural
consequences across product categories.
In light of the above discussions, there currently exists no empirical research concerning the
explanation of online purchase behaviour and customer loyalty from the perspective of TCs
in which their antecedents, consequences, mediators, and moderators are combined and
studied in an integrated framework with testing the framework across product categories. In
an attempt to address the significant gaps in the literature and contribute to current knowledge,
the present study aims to examine the antecedents of consumer TCs and their impacts on the
87
behaviour-related consequences including online purchase behaviour and customer loyalty,
test the mediators and moderators between TCs and behavioural consequences, and compare
all aforementioned relationships
across two product categories, i.e., search products and
experiences products in the context of a developing country, China. Specifically, building on
previous discussions, the following research questions are proposed and will be addressed in
this study:
1.
To what extent do the antecedents affect TCs of consumers in online shopping?
2.
To what extent do TCs determine online behavioural consequences?
3.
Whether and to what extent are the relationships
between TCs and behavioural
consequences mediated by customer satisfaction?
4.
Whether and to what extent are the relationships between TCs and behavioural
consequences moderated by consumers’ risk-bearing propensity and perceived
enjoyment of online shopping?
5.
To what extent do the relationships between antecedents and TCs differ across
product categories?
6.
To what extent do the relationships between TCs and behavioural consequences differ
across product categories?
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