Understanding consumer online shopping behaviour from the perspective of transaction costs

2.4 APPLICATION OF TCS IN ONLINE CONSUMER BEHAVIOUR 
2.4.1 Introduction 
Studies of TCs have attracted growing interest from scholars in economics (Verbeke and 
Kano 2013), sociology (Granovetter 2005), political science (Moe 1991), organization theory 
(Barney and Hesterly 2006, Steenkamp and Geyskens 2012), contract law (Palay 1984) and 
marketing (Anderson 1996, 2008, Williamson and Ghani 2012) in their attempts to explain a 
broad range of exchange-related issue, such as strategic impact of information systems 

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(Hennart 2006, Lacity
 et al.
2011), resource allocation (Masten 1984, Levy 1985, Lieberman 
1991, Masten
 et al.
1991, Balakrishnan and Wernerfelt 2006, Yang
 et al.
2012, Castano and 
Mills 2013), sourcing decisions (Walker and Weber 1987, Masten
 et al.
1989, Schneider
 et al.
2013) and location decisions (Mcivor 2013). However, it has only received limited attention 
in the research regarding transactions of individual consumers in an online environment (Yen
 
et al.
2013). The majority of past studies on online TCs focused on using TCs to explain the 
rise of e-commerce and cost savings (Malone
 et al.
1987, Morton 2006). Only a limited 
number of studies empirically examined impacts of TCs on online shopping behaviour (Wu
 
et al.
2014). 
TCs appear to be a critical and relevant issue for consumer behaviour theory and practice 
because TC reduction has been found to lead to purchase/repeat purchase intention and revisit 
the website to re-experience the service performance (Liang and Huang 1998, Teo and Yu 
2005, Yen
 et al.
2013). Moreover, an understanding of TCs is also crucial for online vendors 
if they are to counteract the negative impacts these costs might have on consumers’ shopping 
choices. It will help online vendors effectively allocate their resources to reduce consumer’s 
TCs perceptions. In this sense, understanding TCs associated with the online transactions of 
individual consumers should be an important research domain for online shopping 
researchers as it is crucial to both online vendors and consumers.
In terms of the level of analyses, TCT has been applied to explain issues at the firm level, 
such as development of web strategy (Steinfield and Whitten 1999), strategic alliance 
structuring (Parkhe 1993), industry value chain (Benjamin and Wigand 1995), product 
adaption (Long
 et al.
2014) and alignment of electronic governance form (Hannas
 et al.

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2010). In contrast, there have been little studies which apply TCT at the individual consumer 
level (Liang and Huang 1998, Teo and Yu 2005, Morton 2006).
In an online setting, Jones and Leonard (2007) indicated that the amount of information 
provided to eliminate uncertainty, the additional avenues provided for buying and selling, and 
the time saved in accomplishing an online purchase predict buyer satisfaction. Liang and 
Huang (1998) and Teo and Yu (2005) stated that the online market with lower TCs could be 
accepted as a preferred channel by the consumer. Lee and colleagues (2000) argued that the 
fewer the competing online vendors, the greater the possibility of opportunistic behaviour on 
the part of existing vendors so as to maximize profits. This would increase TCs for the 
consumer, leading to a decrease in the intention to revisit a specific online store. The extant 
studies on TCs and TCT have acknowledged that e-commerce has become an increasingly 
popular alternative to traditional forms of commerce for consumers due to its relatively lower 
TCs as compared with the offline shopping channel.