Reducing online consumer uncertainty perception in e-commerce

Abstract

With the rapid growth of e-commerce, uncertainty has been widely viewed as a primary barrier. A significant challenge faced with online customers is the inability to predict the consequences of online transactions. As e-commerce proliferates, understanding consumers' uncertainty becomes increasingly important. However, Information Systems (IS) academic community's interest in studying this phenomenon is still developing. This study aims to explore effective mitigators to reduce uncertainty in e-commerce. Drawing upon Uncertainty Reduction Theory (URT), the research model depicts three sets of uncertainty mitigating factors: (1) Consumer characteristics; (2) IT-enabled factors; and (3) Seller-buyer relationship factors. The first set of antecedents is online consumer characteristics, which focus on consumers' product knowledge and goal specificity. The second set of antecedents is IT-enabled factors that include content relevance and information consistency. Finally, seller-buyer relationship factors include fears of seller opportunism and privacy concerns. A survey is used to collect data from the users of Taobao.com in China. The results reveal the direct effects of three groups of antecedents on consumers' perceived uncertainty. The higher an online consumer's level of product knowledge, the lower the consumer's degree of perceived uncertainty. IT-enabled factors (i.e., content relevance and information consistency) are negatively related to perceived uncertainty. Specifically, the higher a consumer's exposure is to a content relevance and information consistency website, the lower the consumer's degree of perceived uncertainty is. Furthermore, the results also indicate that consumer's fears of seller opportunism and privacy concerns are positively related to perceived uncertainty. The findings also show that the mitigating effect of content relevance on perceived uncertainty can be strengthened by both consumer product knowledge and goal specificity. Finally, the theoretical and practical implications of this research are discussed.

Date of Award	15 Jul 2013
Original language	English
Awarding Institution	City University of Hong Kong
Supervisor	Paul Benjamin LOWRY (Supervisor) & Kai H. LIM (Supervisor)