The psychology of success in data science contest design

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In today’s data-driven world, running data science competitions is a popular way to solve real-world problems. Companies use solutions to crowd out these competitions and strategically attract potential employees. Recent research from the University of Waterloo highlights the importance of encouraging participants in these competitions with appropriate competition structures and incentives to achieve success.

Dr. Kihyung Kim, a professor of emerging technologies from the School of Accounting and Finance, strives to understand what data science does. Competition Really inspiring. “In our research, we examine the common design structures used in data science competitions and how the competition organizer maximizes the efforts of competitors,” says Kim.

“We want to know that the structure of the competition is important and especially that the competition should include one or two stages.” His research is one of the few studies that examines the psychological and behavioral dynamics of participants, one of the most frequently overlooked critical issues in the design of data science competitions.

The paper was titled “Designer Data Science Competitions: Number of Levels and Prize Structures”. Published On September 8, 2023 Production and operations management.

Kim uses deep-rooted principles in his research Behavioral economics To examine the conditions of one and two-stage competition design. Behavioral economics examines how psychological factors influence decision making. Interestingly, Kim’s findings show that competitors exert greater effort in both phases compared to single-phase competition.

“Our study uses a behavioral model that provides a psychological explanation behind these new findings,” explained Kim. “Competitors show a psychological aversion to being eliminated early. Having a second stage makes the ‘winner’ and ‘loser’ distinction more salient than in a one-stage competition. Therefore, to avoid falling behind, competitors in a two-stage competition will put more effort into the first stage.

Kim also decided to assign most of them Prize money The winner of the two-stage competition is more effective in motivating competitors. In contrast, the allocation of prizes in a single platform competition does not significantly change the level of competitor effort. These findings indicate Financial incentives It may not be enough to motivate competitors and that Psychological reasons It should be considered in competition design.

This study provides immediate implications that competition organizers can apply to data science competition design. “Organizers should make multilevel competitions as possible to encourage maximum effort,” says Kim. “Furthermore, contest organizers can highlight ‘winning’ and ‘losing’ more prominently, such as publicly announcing the contest’s results. In general, it is critical for organizers to tap into non-financial factors such as psychological motivation to maximize contestant behavior, decision-making, and results.”

This study examines each important aspect Competition It’s an organizer-forward approach to open competition design and offers a fresh perspective on how competition design can foster excellence and innovation.

Additional information:
Jialu Liu et al., Designing Contests for Data Science Competitions: Number of Levels and Prize Structures; Production and operations management (2023) DOI: 10.1111/poms.14061

QuotePsychology of Success in Data Science Contest Design (2023, November 27) Retrieved November 27, 2023 from

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