Understanding consumer online shopping behaviour from the perspective of transaction costs



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6.6 OVERALL CONCLUSIONS 
TCs are advocated as an important factor for organizations choosing governance structure 
(market, hybrid and hierarchy). Recently, there is a growing call for a paradigm shift in 
marketing from market focus to customer focus and cost reduction. Marketing is thus headed 
towards interaction and customer focus. In line with this transformation from current 
generation of market-focused marketing to next generation of customer-focused marketing, 
this study examines individual customers’ TCs and argues that not only organizations bear 
TCs, but individual consumers also incur TCs for almost all of the products they consume. 
Further, building on the TCT and extending it to the online shopping environment at the 
individual consumer level, the study proposes and empirically tests the integrative TC model 
utilizing data from China’s online shopping industry. The findings highlight that TCs are 
affected by three-category antecedent factors, namely consumer-related characteristics, online 
vendor- and product-related characteristics, and online channel-related characteristics. The 
results show that TCs negatively influence online purchase behaviour, customer satisfaction 
and loyalty. Consumer’s risk-bearing propensity is found to moderate the effect of TCs on 
loyalty, and perceived enjoyment moderates the effect of TCs on online purchase behaviour. 
The model is further tested in two product categories and reveals the significant difference in 
the aforementioned relationships across product categories.


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Overall, the study provides new insights into TCT within the domain of online shopping. It 
contributes to a more comprehensive understanding of the online shoppers’ decision making 
process by taking TCs into account. It also enhances the online consumer behaviour literature 
by identifying three categories of antecedent factors affecting consumer TCs and further 
examines the linkage between TCs and behavioural consequences. This study is responsive to 
the call for greater understanding of online consumer behaviour from the perspective of TCs 
by Teo (2004) and Wu et al. (2014). The researcher hopes this study can provide some further 
insight and contributions to the on-going discussion of cost challenges facing both theorists 
and practitioners in the online shopping discipline. 
From managerial perspective, this study highlights important implications for online vendors 
in relation to the TC reduction activities. The results call on online vendors to realize that to 
minimize TCs, they should endeavour to provide superior e-service, eliminate consumers’ 
concerns over product quality, enhance convenience of online shopping, improve their store 
reputation and increase online transaction frequency with exiting consumers. Importantly by 
showing the dimensions of TCs, the measures provide guideline for management practices in 
online firms seeking to identify the dimensions in which they perform poorly. By allocating 
more resources in the underperforming areas, online vendors would be able to reduce the 
overall TCs. The lowering of TCs will, subsequently, encourage the online purchase 
behaviour of customers, enhance customer satisfaction with the online vendors and improve 
their loyalty towards the online vendors. The researcher hopes through this study that the TC 
reduction will be recognized as a key driver of online purchase, acting as a driver of 
satisfaction and loyalty formation.


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Although this study has been conducted with methodological rigour, the findings should be 
interpreted with caution. Since this study examined online consumer behaviour in China, the 
findings may not be generalizable to other geographic areas. Future research could include 
online shoppers representing different countries and cultures. Such research could help 
academicians uncover country and cultural specific relationships that were not exposed with 
this initial study. The study only conducted cross-sectional research by capturing data at one 
time point. It does not provide as much insight as does a longitudinal research design while 
studying the dynamics of TCs, their antecedent variables and behavioural consequences. 
Thus, a longitudinal design could be used in future reearch to identify the changing roles of 
online TCs in affecting their decision-making process. 


352

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