To Cooperate or to Compete in the Gig Economy? Endorsements and the Performance of Freelancers in Online Labor Markets

Date
2023-01-03
Authors
Tripathi, Sambit
Deokar, Amit
Karhade, Prasanna
Li, Xiaobai
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617
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Abstract
Online labor markets connect buyers with gig workers across several task categories. A buyer evaluates workers’ quality based on their past performance encapsulated in ratings and reviews. However, these ratings can be inflated and arguably fail to assess workers’ true quality. Literature shows that worker characteristics like skills, experience, and heuristic cues can measure worker quality. In this study, we explore how gig workers’ personality traits in terms of Social Value Orientation (SVO) affects their performance on an online labor platform. We measure SVO from peer endorsements among workers on an online labor platform. Our results show that a cooperative SVO, where gig workers endorse each other, is more beneficial to the stakeholders of online labor platforms than competitive and individualistic SVO. We also explore how such cooperative behavior evolves by leveraging social network analysis methods to examine the endorsements generated among gig workers. We observe that reciprocity, homophily and worker popularity induces such cooperative behavior.
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The Sharing Economy, competition, cooperation, gig economy, social network analysis, social value orientation
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9
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Related To
Proceedings of the 56th Hawaii International Conference on System Sciences
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Attribution-NonCommercial-NoDerivatives 4.0 International
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