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The Curse of Experience in Creative Crowdsourcing Contests and Contest Searches as a Remedy

众包 竞赛 诅咒 背景(考古学) 质量(理念) 公共关系 数据科学 营销 心理学 探索者 知识管理 激励 政治学 计算机科学
作者
Yuan Jin,Ho Cheung Brian Lee,Xinxin Li
出处
期刊:Management Information Systems Quarterly [MIS Quarterly]
卷期号:50 (1): 351-378 被引量:2
标识
DOI:10.25300/misq/2025/17751
摘要

In creative crowdsourcing contests that seek novel ideas and solutions, experience can help solvers use relevant knowledge to generate solutions, but may also cause solvers to fixate on familiar solution paths, which we call the “curse of experience.” This study examines how experience affects solvers’ performance in such contests and how contest searches (searching descriptive information about other contests), as a type of external information-seeking activity, moderate the effects of experience. Our analyses show that both the benefit and the curse of experience coexist. Solvers’ experience contributes to a higher likelihood of generating acceptable submissions (solutions meeting basic quality standards) but reduces the chance of creating winning solutions (extreme-value solutions selected as contest winners). Contest searches prior to participation in a contest provide solvers with contest choices, strengthening the beneficial effects of experience on creating both acceptable and winning solutions. Contest searches that occur during participation in a contest, although potentially triggering an overload effect that decreases the beneficial effect of experience on solution acceptance, also bring new ideas and inspiration to solvers’ solution search processes, reducing the impedimental effect of experience on creating winning solutions. Searches of contests that differ in skill or context from the focal contest are beneficial for both prior and parallel contest search processes but are not always fully utilized by solvers. These findings delineate a comprehensive picture of how contest search activities can remedy the curse of experience and inform the effective design and use of search features for crowdsourcing platforms and solution seekers to help improve solvers’ performance.
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