Information asymmetry is an inevitable issue in e-commerce and largely hampers the development of online shopping. The purpose of this paper is to propose a model to investigate the emotional content of online customer reviews, which are considered an efficient way to reduce information asymmetry, as a potential signal of product quality. The moderating effects of perceived empathy and cognitive effort are also explored on the basis of signaling theory.
A laboratory experiment with 120 subjects was used to empirically test the proposed research hypotheses. The subjects were randomly assigned to two treatment groups, with 60 subjects in each group. ANOVA, linear regression and binary logistic regression were used.
The emotional content of online customer reviews positively influences perceived product quality, which subsequently and positively affects purchase decisions. The emotional content of online customer reviews greatly influences perceived product quality when perceived empathy or cognitive effort is high.
This study is the first to extend extrinsic cues to emotional content on the basis of signaling theory and reveals the important role of emotional content of reviews. Moreover, the mediating effect of perceived product quality and the moderating effect of perceived empathy and cognitive effort illustrate the mechanism of the influence of emotional content on purchase decision. Findings demonstrate the positive signal of emotional content and provide important practical implications for sellers and customers.
The authors wish to thank the Editor-in-Chief, Associate Editor and anonymous reviewers for their highly constructive comments. The authors gratefully acknowledge financial support for this research from the National Natural Science Foundation of China (Nos 71671121, 71802147) and Ministry of Education of Humanities and Social Science Fund (No. 17YJC630173).
Wang, X., Guo, J., Wu, Y. and Liu, N. (2019), "Emotion as signal of product quality: Its effect on purchase decision based on online customer reviews", Internet Research, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/INTR-09-2018-0415Download as .RIS
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