The Wisdom of Crowds: The Impact of Negative Upward Social Comparison on Premature Quitting in Kaggle Crowdsourcing Competitions
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2024-07-08
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en
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This study investigates how gamified elements that allow Social Comparison with high-tier participants influence premature quitting behavior. Additionally, the moderating role of different reward levels on this relationship was examined. The objective of this analysis is to gain insights into the psychological triggers of premature quitting behavior in crowdsourcing contests and how incentives (rewards) shape this relationship. Hierarchical regression (using OLS) provides an analysis to examine these relationships. Three models were developed to assess these relationships: a baseline model containing only the control variables, a main effect model containing the control variables and main effect and an interaction effect model containing all the variables and the interaction term.
The hierarchical regression results reveal that the presence of high-tier participants significantly increases participants’ decision to prematurely quit, supporting the hypothesis that high-tier participants positively influence the number of premature quitters because they discourage other participants. Additionally, this study explored the role of different levels of rewards on this relationship. The interaction effect model revealed that higher rewards weaken the effect between high-tier participants and premature quitters. This partially supports the second hypothesis that rewards moderate the relationship between high-tier participants and premature quitting, though it was not in the expected direction. Rewards weaken this relationship instead of strengthening this relationship, as proposed in the second hypothesis.
The research highlights the complex relationship between high-tier participants and rewards. While showing the presence of high-tier participants on leaderboards tends to increase quitting rates, high rewards can mitigate this effect. Strategic use of gamification elements such as leaderboards, tier systems and reward structures could potentially be used to stimulate continued participation in crowdsourcing competitions.
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Faculteit der Managementwetenschappen