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How Online Reviews Become Helpful: A Dynamic Perspective

Shuya Lu, Jianan Wu and Tseng, Shih-Lun (Allen)

Journal of Interactive Marketing, 2018, vol. 44, issue C, 17-28

Abstract: Online product reviews aid consumer decision making. Although many studies show that review characteristics have salient effects on review helpfulness, little research has investigated whether such effects change temporally. To bridge this research gap, we study the dynamic formation of review helpfulness by considering the behaviors of three major players in a typical review system: consumers, the review hosting firm, and reviewers. This study uses both dynamic and static drivers of review helpfulness to examine temporal changes in their effects on review helpfulness, along two time characteristics of a post: its lifespan and its timing. Daily data collected from Amazon show that for long post lifespans or late post timing, the effects of static drivers and the spillover effect of dynamic drivers weaken, but the carryover effect of dynamic drivers strengthens. For vendors to leverage user reviews of a product, high-quality reviews posted early are extremely important and should be cultivated diligently. Sorting by review quality attributes, such as review length, also can effectively prolong the time window for reviewers to write high-quality detailed reviews.

Keywords: Online reviews; Dynamics; Helpfulness depth; Helpfulness breadth; Helpfulness rank (search for similar items in EconPapers)
Date: 2018
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