Review First or Rate First: How the Review Process and Device Choice Shape Online Reviewing Behavior

• 成果类型: Article
• 署名作者: Qahri-Saremi, Hamed; Kordzadeh, Nima; Turel, Ofir
• 署名单位: Colorado State University System; Colorado State University Fort Collins; Worcester Polytechnic Institute; University of Melbourne
• 刊物名称: JOURNAL OF MANAGEMENT INFORMATION SYSTEMS
• ISSN/ISSBN: 0742-1222; 1557-928X
• DOI: 10.1080/07421222.2026.2692281
• 发表日期: 2026-07-03
• 页码: 958-991
• 关键词: Composition effects; online deliberation; online reviews; star ratings; rating ambivalence; rating confidence; decisiveness; attitudinal ambivalence; decision-making; INFORMATION; COMMITMENT; persuasion; disclosure; MESSAGE; culture; systems; MODEL

摘要

The quality of online review content is a central factor in its perceived helpfulness to consumers. Yet platforms' efforts to enhance the quality of online reviews through extrinsic incentives have shown mixed results. In this paper, we address this issue by showing that a subtle change in the design of the review generation process can improve review quality. Via four randomized controlled experiments (n = 1,101), we specifically examine whether the task order in which platforms solicit numerical ratings and textual reviews can shape reviewers' reasoning processes and, in turn, the deliberativeness of textual reviews and the characteristics of subsequent numerical ratings. Results show that changing the task order in the online review generation process, from the current rating first to a review first task order, enhances reviewers' deliberation in their textual reviews, reduces their ambivalence toward the product/service, and improves their decisiveness and confidence in numerical ratings. Moreover, we show that these effects are contingent on the device (PC vs. mobile) used to generate textual reviews, as a situational boundary condition. In response to calls for research on the design of review systems, these findings offer actionable insights for online review platforms by presenting novel ways to elicit more deliberative textual reviews and more decisive, confident numerical ratings. They also clarify the important distinction between PC reviews and mobile reviews.