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NATIONAL BUREAU OF ECONOMIC RESEARCH
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Incentives Can Reduce Bias in Online Reviews

Ioana Marinescu, Nadav Klein, Andrew Chamberlain, Morgan Smart

NBER Working Paper No. 24372
Issued in March 2018
NBER Program(s):The Industrial Organization Program, The Labor Studies Program

Online reviews are a powerful means of propagating the reputations of products, services, and even employers. However, existing research suggests that online reviews often suffer from selection bias—people with extreme opinions are more motivated to share them than people with moderate opinions, resulting in biased distributions of reviews. Providing incentives for reviewing has the potential to reduce this selection bias, because incentives can mitigate the motivational deficit of people who hold moderate opinions. Using data from one of the leading employer review companies, Glassdoor, we show that voluntary reviews have a different distribution from incentivized reviews. The likely bias in the distribution of voluntary reviews can affect workers’ choice of employers, because it changes the ranking of industries by average employee satisfaction. Because observational data from Glassdoor are not able to provide a measure of the true distribution of employer reviews, we complement our investigation with a randomized controlled experiment on MTurk. We find that when participants’ decision to review their employer is voluntary, the resulting distribution of reviews differs from the distribution of forced reviews. Moreover, providing relatively high monetary rewards or a pro-social cue as incentives for reviewing reduces this bias. We conclude that while voluntary employer reviews often suffer from selection bias, incentives can significantly reduce bias and help workers make more informed employer choices.

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Document Object Identifier (DOI): 10.3386/w24372

Published: Ioana Marinescu & Nadav Klein & Andrew Chamberlain & Morgan Smart, 2018. "Incentives can reduce bias in online employer reviews," Academy of Management Proceedings, vol 2018(1).

 
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