User Behaviors, Engagement, and Consequences

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Paper Number

2207

Paper Type

short

Description

User engagement has been widely discussed as a critical factor for the success of digital platforms. Among various mechanisms for increasing user engagement, of particular interest are gamification techniques. In this study we focus on competition and use a behavioral economics lens to investigate how competitive structures presented to users in the form of leaderboards affect user engagement. We construct a novel leaderboard design, which we refer to as “local leaderboards”, to create competitive structures unique to each user by showing the competitors around them and compare this design against the traditional “global leaderboards”, which typically show only the top ranked users. Our randomized field experiment suggests that the localized leaderboards may be more effective than the traditional leaderboards in influencing the level of user engagement on digital platforms. Our data analysis using generalized linear regression models with fixed effects reinforces our findings and provides additional insights.

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Dec 12th, 12:00 AM

How Am I Doing? The Impact of Localized Leaderboards in Digital Platforms

User engagement has been widely discussed as a critical factor for the success of digital platforms. Among various mechanisms for increasing user engagement, of particular interest are gamification techniques. In this study we focus on competition and use a behavioral economics lens to investigate how competitive structures presented to users in the form of leaderboards affect user engagement. We construct a novel leaderboard design, which we refer to as “local leaderboards”, to create competitive structures unique to each user by showing the competitors around them and compare this design against the traditional “global leaderboards”, which typically show only the top ranked users. Our randomized field experiment suggests that the localized leaderboards may be more effective than the traditional leaderboards in influencing the level of user engagement on digital platforms. Our data analysis using generalized linear regression models with fixed effects reinforces our findings and provides additional insights.

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