Abstract
In striking a balance between attracting more product reviews versus maintaining review quality, online platforms have started to label reviews with whether they are associated with verifiable purchases. This paper examines the impact of such disclosure policy on the strategic behavior of review writers and the helpfulness of verified reviews (VRs) and non-verified reviews (NVRs) for review users. We propose that the introduction of the verified purchase tag induces two competing effects for VRs, increased credibility and concerns for acquisition bias, which in turn influence the behaviors of both writers and users. By exploiting the exogenous shock resulting from a policy change on Amazon, we find that, after the disclosure, NVRs became longer in length and VRs started to contain more unique information. Surprisingly, we find strong evidence that VRs receive fewer helpfulness votes than NVRs. We further explore the underlying mechanism, namely review users' concerns about acquisition bias associated with VRs, and identify conditions under which these unexpected effects can be mitigated. Our findings generate important implications for online platforms seeking to design a more effective review ecosystem and for review writers aiming to produce more helpful content.
Original language | English |
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Article number | 114367 |
Journal | Decision Support Systems |
Volume | 188 |
DOIs | |
Publication status | Published - Jan 2025 |
Keywords
- Acquisition bias
- Credibility
- Machine learning
- Product reviews
- Review helpfulness
- Verified purchase