Opinion evolution of online consumer reviews in the e-commerce environment

Abstract

Online consumer reviews play an important role in shaping potential customers’ purchase decisions in e-commerce. Previous studies have analyzed the influence of online consumer reviews on sales, mainly considering factors such as reviewers’ and viewers’ profiles, information provided, and product features. However, there are relatively few studies that discuss how online consumer reviews interact with each other and how consumers’ opinions evolve over time. This paper proposes an opinion evolution dynamics model that is applicable to online consumer reviews in the e-commerce environment by taking into account influencing factors such as viewer reading limits, review sorting and releasing strategies, convergence parameters, review posting possibilities, and confidence thresholds. Using multi-agent simulation based on the proposed opinion evolution dynamics model, the paper discusses how these factors affect viewers’ opinions, and the opinion evolution process itself. Finally, conclusions and managerial implications of the simulation results are discussed.