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The Market for Reviews: Strategic Behavior of Online Product Reviewers with Monetary Incentives

Verena Dorner et al.

Schmalenbach Business Review2020https://doi.org/10.1007/s41464-020-00094-yarticle
AJG 2
Weight
0.55

What the paper says

Customer reviews reduce search cost and uncertainty about a product’s quality. Hence, the quantity and quality of reviews has positive impacts on purchase intentions, sales, and customer satisfaction. In order to increase review quality, retailers and online platforms employ different monetary incentives. We experimentally compare two different incentive schemes: an incentive scheme in which reviewers receive a flat salary, which is independent of review quality, and a tournament incentive scheme in which the reviewer who wrote the most helpful review receives a bonus payment. Helpfulness ratings are assigned by the other reviewers. In our experiment, adverse consequences arise under the tournament incentive scheme. Strategic considerations give rise to strategic downvoting, so that reviewers assign low helpfulness ratings to others’ reviews in order to maximize their expected payoffs. Review writing behavior remains unaffected: the tournament incentive scheme does not affect review quality. However, it does destroy the signaling power of helpfulness ratings.

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https://doi.org/https://doi.org/10.1007/s41464-020-00094-y

Or copy a formatted citation

@article{verena2020,
  title        = {{The Market for Reviews: Strategic Behavior of Online Product Reviewers with Monetary Incentives}},
  author       = {Verena Dorner et al.},
  journal      = {Schmalenbach Business Review},
  year         = {2020},
  doi          = {https://doi.org/https://doi.org/10.1007/s41464-020-00094-y},
}

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The Market for Reviews: Strategic Behavior of Online Product Reviewers with Monetary Incentives

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Evidence weight

0.55

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.53 × 0.4 = 0.21
M · momentum0.74 × 0.15 = 0.11
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.