Abstract
ABSTRACT Most existing studies of consumer search behaviour focus on page-level analysis, and some scholars start to examine the effect of refinement tools and characteristics in terms of products. However, it still remains undeveloped on the product-level. To fill this gap, we reproduced the consumer shopping process in accordance with the topology of the Taobao platform from where we collected the clickstream data. We modelled consumers’ sequential decision-making behaviour based on the taxonomy with Bayesian approach and found that not all the refinement tools are utilised for optimising decisions by users and it’s surprising that there exists no significant impact of all sorting tools. Besides, consumers are highly concerned with the characteristics of products. On the basis of the findings, platform function announcement and platform design suggestions were provided for improving platform functionality and optimising consumer decision-making, which also points out the direction of future research.
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