On the Effectiveness of Self-Contained Reward Systems to Incentivize User-Generated Content
Abstract
Many digital platforms rely on reward systems to incentivize the production of user-generated content. These platforms frequently resort to financial or peer-based reward systems. Both systems have drawbacks and limitations. Financial rewards such as vouchers can crowd out effort of the content contributor and induce a positivity bias to the user-generated content. Peer-based rewards, which are conditional on upvotes from peers, are used when crowds identify the best contribution or curation. Because online review platforms aim at incentivizing a variety of contributions at scale, they can hardly apply peer-based reward systems. It is undetermined whether gamification systems designed for self-contained rewards—where reviewers receive points and badges for their activities unconditional on upvotes from peers—can effectively circumvent these drawbacks and limitations. To empirically address this question, we draw on a data set of online reviews from Google Maps and Tripadvisor that we matched on a site level. Our identification strategy hinged on a natural experiment of Google’s self-contained reward system, Local Guides, being restructured such that particular reviewing activities were rewarded with more points. We found that self-contained reward systems avoid effort crowding out and positivity bias but do incentivize the production of user-generated content. Beyond that and in contrast to our expectation, we detected substantial positive spillover effect to the unincentivized task of submitting a rating without a textual review. Furthermore, we documented that the effectiveness of self-contained rewards differs across low- and high-expertise reviewers. Most importantly, our study shows that peer-based incentive mechanisms are no prerequisite for effective nonfinancial reward systems, and applying self-contained reward systems circumvents many negative side effects associated with financial rewards.
This seminar will take place in T09-67. To join online, find the details below:
https://eur-nl.zoom.us/j/96886971957