Designing Effective Performance Feedback Notification Systems to Stimulate Content Contribution: Evidence from a Crowdsourcing Recipe Platform

Date
2017-01-04
Authors
Huang, Ni
Gu, Bin
Burtch, Gord
Hong, Yili
Chen, Liang
Wang, Kanliang
Fu, Dongpu
Yang, Bo
Lan, Wei
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Abstract
This study investigates whether and how a platform’s provision of performance feedback to users about their prior content contributions can help to stimulate users’ subsequent contributions. We draw on social value orientation theory to hypothesize how different framings may impact users’ likelihood of producing additional content. We partnered with a major mobile crowdsourcing recipe platform based in China to conduct a randomized field experiment involving the delivery of feedback messages with randomly determined framings, via mobile push notifications. We find that feedback framed either pro-socially or pro-self has a positive effect on content contributions, whereas feedback framed competitively has no such effect. Additionally, we observe differences across genders, such that the positive effects of pro-socially framed feedback are significantly stronger for female users. In contrast, competitively framed feedback is only effective for male users. Our findings provide implications for the design of platform-provided performance feedback to stimulate users' content contribution.
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Notification system design, User-generated content, performance feedback, mobile, crowdsourcing
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10 pages
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Proceedings of the 50th Hawaii International Conference on System Sciences
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Attribution-NonCommercial-NoDerivatives 4.0 International
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