商家自我刷好评行为的触发机理及电商平台的应对策略研究

Abstract

This paper studies the price competition and potential review brushing behavior between a high-quality online seller and a low-quality online seller. The e-commerce platform detects fake positive reviews with a certain detection rate and penalizes dishonest sellers by hiding all their reviews. We develop game-theoretic models for the cases where only one seller chooses to brush and both sellers choose to brush, and reveal the following findings by analyzing the equilibrium results. (1) If the rival chooses not to brush, the seller chooses to brush if and only if the unit brushing cost coefficient is below a threshold and the detection rate is below a specific threshold; if the rival chooses to brush, besides the above conditions, the seller chooses to brush when the unit brushing cost coefficient is slightly higher than a threshold and the detection rate takes extreme values. (2) When only one seller chooses to brush, the impact of his brushing behavior on the e-commerce platform's expected profit depends on the volume of fake reviews, the fake review detection rate, and consumers' average evaluated quality of the product after its reviews are hidden. (3) When both sellers choose to brush, there exists an inverted U-shaped relationship between the e-commerce platform's expected profit and the detection rate.