Fake online reviews: Literature review, synthesis, and directions for future research

By Yuanyuan Wu, Eric Wai Ting Ngai, Pengkun Wu, Chong Wu. Decision Support Systems, 2020

327 citations recorded by the source corpus.

Abstract Fake online reviews in e-commerce significantly affect online consumers, merchants, and, as a result, market efficiency. Despite scholarly efforts to examine fake reviews, there still lacks a survey that can systematically analyze and summarize its antecedents and consequences. This study proposes an antecedent–consequence–intervention conceptual framework to develop an initial research agenda for investigating fake reviews. Based on a review of the extant literature on this issue, we identify 20 future research questions and suggest 18 propositions. Notably, research on fake reviews is often limited by lack of high-quality datasets. To alleviate this problem, we comprehensively compile and summarize the existing fake reviews-related public datasets. We conclude by presenting the theoretical and practical implications of the current research.

Subfields: Artificial Intelligence, Information Systems, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/67f874e15ff1d435aec4b1007fd24f8b1b33d084