Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4942537 | Electronic Commerce Research and Applications | 2017 | 23 Pages |
Abstract
Online reputation systems provide consumers important references before their purchase decisions. So designing a mechanism to encourage consumers to leave honest online reviews becomes very important for e-commerce platforms. We establish a Bayesian model to simulate the formation of consumers' perceptions of sellers' reputations in a C2C e-commerce platform. We find that both truthfulness of reviews and number of reviews influence consumers' perceptions of sellers' reputation, and they are mutually substitutable. Consumers may have no faith in the truthfulness of the reviews if sellers offer rebates for more online reviews. To obtain honest reputation information, the platform should encourage consumers to provide honest opinions about experiences and feelings consistent with of social-exchange theory. In addition, to obtain a certain level of perceived reputation, the system does not need all consumers to submit their opinions. We also provide upper and lower bounds for rebates offered by the platform.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Lirong Chen, Tao Jiang, Wenli Li, Shidao Geng, Shahbaz Hussain,