Affiliation:
1. NUS School of Computing, National University of Singapore, Singapore 117417;
2. Simon Business School, University of Rochester, Rochester, New York 14627
Abstract
Incentivizing reviewers to write product reviews is a widespread yet controversial practice. Whereas outright fake reviews are clearly unacceptable and should be removed from any review platform, reviews contributed by incentivized consumers with otherwise authentic product experiences fall in a gray area. This paper offers a fresh perspective for us to understand conceptually the relationship between incentivized reviews and its two counterparts (i.e., organic reviews and advertisements) on the two ends of the spectrum, and it studies whether incentivized reviews are of higher text quality. The authors argue that incentivized reviewers may shift their “writing mode” from back stage to front stage and may also “compensate” for their reduced impartiality through better text quality. Drawing on recent advancements in computational linguistics, the authors demonstrate that incentivized reviews tend to have more coherent writing and cover more details, suggesting higher review text quality. Their finding highlights the often-overlooked value of incentivized reviews, which can complement an organic review system and also alleviate the cold-start problem for new products, thereby promoting healthy competition in the e-commerce era. For review platforms, the authors suggest they explicitly group and label incentivized reviews without their numerical ratings and separate them from organic reviews. In this way, we can take the best of both worlds.
Publisher
Institute for Operations Research and the Management Sciences (INFORMS)
Subject
Library and Information Sciences,Information Systems and Management,Computer Networks and Communications,Information Systems,Management Information Systems
Cited by
9 articles.
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