Researcher from the School of Accounting and Finance explores how nonmonetary factors impact contestant behavior and effort levels
In today's data-driven world, holding data science competitions is a popular way to address real-world problems. Companies leverage these competitions to crowdsource solutions and strategically attract potential employees. Recent research from the University of Waterloo highlights the importance of motivating participants in these competitions through the appropriate contest structure and incentives to achieve success.
Dr. Keehyung Kim, a professor of Emerging Technologies from the School of Accounting and Finance, has endeavoured to understand what makes a data science competition truly motivating. “In our study, we investigate the common design structures used in data science competitions and examine how a contest organizer can maximize the effort level exerted by contestants,” says Kim. “We want to know if the contest structure matters, and more specifically, if the contest should include one or two stages.” His research stands out as one of the few studies examining a crucial aspect frequently ignored in the design of data science contests: the psychological and behavioral dynamics of participants.
To learn more, read the full story on Waterloo News.