Authors:
(1) Muhammad Zia Hydari, Katz Graduate School of Business, University of Pittsburgh and Corresponding author;
(2) Idris Adjerid, Pamplin College of Business;
(3) AAaron D. Striegel, Department of Computer Science and Engineering, University of Notre Dame. Table of Links Abstract and 1 Introduction 2. Background and 2.1. Leaderboards 3. Effect of Leaderboards on Healthful Physical Activity and 3.1. Competition 3.2. Social Influence 3.3. Moderating Effects of Prior Activity Levels and Leaderboard Size 4. Data and Model 4.1. Data 4.2. Model 5. Estimation and Robustness of the Main Effects of Leaderboards 5.2. Robustness Check for Leaderboard Initiation 5.3. Fitbit Compliance 5.4. Fitbit Attrition, Leaderboard De-Adoption, and Additional Robustness Checks 6. Heterogeneous Effect of Leaderboards 6.1. Heterogeneity by Prior Activity Levels 6.2. Interaction of Leaderboard Size, Rank, and Prior Activity Levels 6.3. Summary of Findings from Heterogeneous Effect Analysis 7. Conclusions and Discussion, Endnotes, and References 2. Background Physical activity is a key element of healthful living and is known to have significant health benefits (Penedo and Dahn 2005, Warburton et al. 2006). Our main outcome variable is Fitbit step counts and includes a variety of these healthful physical activities, such as jogging, running, walking, playing sports, climbing stairs, and so on. Moreover, daily step counts are key to Fitbit leaderboards, as rankings on leaderboards are determined exclusively by differences in the step counts of the participants of the leaderboard. 2.1. Leaderboards A leaderboard is “a large board for displaying the ranking of the leaders in a competitive event.”[7] In a digital setting, the leaderboard may be displayed on a mobile application or an online dashboard. In this study, we utilize health wearables made by Fitbit Inc., which is a pioneering firm in this market.[8] Using Fitbit’s online dashboard or the mobile application, a Fitbit user can invite another user (or receive an invitation) to join a leaderboard. If there is mutual agreement between the users to participate, both users will appear on each other’s leaderboards. Each leaderboard ranks participating users based on seven-day running tallies of their steps.[9] The step counts shown on the leaderboard are directly captured by the Fitbit device and are not manually entered by the users, thus avoiding the measurement errors that may result from self-reported activity data. Figure 1 shows four leaderboards, with the focal user labeled at the lower left corner. Each leaderboard can have the same or different user composition. For instance, Ash and Todd are connected to Mary and to each other. Dave is only connected to Mary, and Mary is connected to all other users. The leaderboards also show the seven-day-step count of each participating user. Users are assigned ranks on participating leaderboards based on their sevenday step count relative to other users on that leaderboard. For instance, Mary is ranked second on her own leaderboard, but she is ranked first on Ash’s and Todd’s leaderboards. Thus, Ash and Todd may be motivated to do better by seeing their lower rank on the leaderboard relative to Mary. Users get feedback according to their rank on their own leaderboard. Although Mary dominates the highest number of leaderboards, the feedback she gets is that she is ranked second on her own leaderboard and must strive harder to achieve a first rank. Leaderboard adoption is “sticky” on the Fitbit platform. To de-adopt, users have to go through cumbersome steps and hide themselves via privacy settings. Notes. This figure shows leaderboards for Ash, Dave, Mary, and Todd. Ash and Todd are connected to each other and Mary, Dave is only connected to Mary, and Mary is connected to all other participants. This paper is available on arxiv under CC BY 4.0 DEED license. Authors: (1) Muhammad Zia Hydari, Katz Graduate School of Business, University of Pittsburgh and Corresponding author; (2) Idris Adjerid, Pamplin College of Business; (3) AAaron D. Striegel, Department of Computer Science and Engineering, University of Notre Dame. Authors: Authors: (1) Muhammad Zia Hydari, Katz Graduate School of Business, University of Pittsburgh and Corresponding author; (2) Idris Adjerid, Pamplin College of Business; (3) AAaron D. Striegel, Department of Computer Science and Engineering, University of Notre Dame. Table of Links Abstract and 1 Introduction Abstract and 1 Introduction 2. Background and 2.1. Leaderboards 2. Background and 2.1. Leaderboards 3. Effect of Leaderboards on Healthful Physical Activity and 3.1. Competition 3. Effect of Leaderboards on Healthful Physical Activity and 3.1. Competition 3.2. Social Influence 3.2. Social Influence 3.3. Moderating Effects of Prior Activity Levels and Leaderboard Size 3.3. Moderating Effects of Prior Activity Levels and Leaderboard Size 4. Data and Model 4.1. Data 4.1. Data 4.2. Model 4.2. Model 5. Estimation and Robustness of the Main Effects of Leaderboards 5. Estimation and Robustness of the Main Effects of Leaderboards 5.2. Robustness Check for Leaderboard Initiation 5.2. Robustness Check for Leaderboard Initiation 5.3. Fitbit Compliance 5.3. Fitbit Compliance 5.4. Fitbit Attrition, Leaderboard De-Adoption, and Additional Robustness Checks 5.4. Fitbit Attrition, Leaderboard De-Adoption, and Additional Robustness Checks 6. Heterogeneous Effect of Leaderboards 6. Heterogeneous Effect of Leaderboards 6.1. Heterogeneity by Prior Activity Levels 6.1. Heterogeneity by Prior Activity Levels 6.2. Interaction of Leaderboard Size, Rank, and Prior Activity Levels 6.2. Interaction of Leaderboard Size, Rank, and Prior Activity Levels 6.3. Summary of Findings from Heterogeneous Effect Analysis 6.3. Summary of Findings from Heterogeneous Effect Analysis 7. Conclusions and Discussion, Endnotes, and References 7. Conclusions and Discussion, Endnotes, and References 2. Background Physical activity is a key element of healthful living and is known to have significant health benefits (Penedo and Dahn 2005, Warburton et al. 2006). Our main outcome variable is Fitbit step counts and includes a variety of these healthful physical activities, such as jogging, running, walking, playing sports, climbing stairs, and so on. Moreover, daily step counts are key to Fitbit leaderboards, as rankings on leaderboards are determined exclusively by differences in the step counts of the participants of the leaderboard. 2.1. Leaderboards A leaderboard is “a large board for displaying the ranking of the leaders in a competitive event.”[7] In a digital setting, the leaderboard may be displayed on a mobile application or an online dashboard. In this study, we utilize health wearables made by Fitbit Inc., which is a pioneering firm in this market.[8] Using Fitbit’s online dashboard or the mobile application, a Fitbit user can invite another user (or receive an invitation) to join a leaderboard. If there is mutual agreement between the users to participate, both users will appear on each other’s leaderboards. Each leaderboard ranks participating users based on seven-day running tallies of their steps.[9] The step counts shown on the leaderboard are directly captured by the Fitbit device and are not manually entered by the users, thus avoiding the measurement errors that may result from self-reported activity data. Figure 1 shows four leaderboards, with the focal user labeled at the lower left corner. Each leaderboard can have the same or different user composition. For instance, Ash and Todd are connected to Mary and to each other. Dave is only connected to Mary, and Mary is connected to all other users. The leaderboards also show the seven-day-step count of each participating user. Users are assigned ranks on participating leaderboards based on their sevenday step count relative to other users on that leaderboard. For instance, Mary is ranked second on her own leaderboard, but she is ranked first on Ash’s and Todd’s leaderboards. Thus, Ash and Todd may be motivated to do better by seeing their lower rank on the leaderboard relative to Mary. Users get feedback according to their rank on their own leaderboard. Although Mary dominates the highest number of leaderboards, the feedback she gets is that she is ranked second on her own leaderboard and must strive harder to achieve a first rank. Leaderboard adoption is “sticky” on the Fitbit platform. To de-adopt, users have to go through cumbersome steps and hide themselves via privacy settings. Notes . This figure shows leaderboards for Ash, Dave, Mary, and Todd. Ash and Todd are connected to each other and Mary, Dave is only connected to Mary, and Mary is connected to all other participants. Notes This paper is available on arxiv under CC BY 4.0 DEED license. This paper is available on arxiv under CC BY 4.0 DEED license. available on arxiv

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