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 3.2. Social Influence Leaderboards involve connecting individuals around health and the revelation of previously private levels of physical activity between individuals. These connections and disclosures introduce the potential of social influence to impact motivation and behavior. We consider two potential effects in the realm of social influence: individual accountability and reference points for exercise.[10] 3.2.1. Individual Accountability. Joining a leaderboard involves the revelation of one’s previously private levels of physical activity to other users. This self-revelation allows other leaderboard members to hold the focal user accountable for lackluster levels of physical activity and nudge them to do better. In fact, the Fitbit app has a mechanism for messaging, cheering, and taunting other users directly from the platform. Some of these interactions may also happen off the Fitbit platform (and are thus unobserved by us as researchers)—for example, discussions between family members over dinner. The potential of group-based interventions to increase mutual accountability and increase physical activity has been explored in the literature: Patel et al. (2016) uncover benefits of incentive schemes for exercise that are tied to group versus individual performance targets. 3.2.1. Individual Accountability. 3.2.2. Exercise Reference Points. In addition to the potential impacts of self-revelation, the revelation by others of their previously private levels of physical activity can result in changes to individuals’ reference points for exercise. Specifically, social comparison theory suggests that such revelations can lead to an updated perception of one’s own ability to exercise and the appropriateness of one’s own level of exercise (Garcia et al. 2013). However, how these comparisons impact reference points depends on whether individuals engage in upward comparisons (i.e., comparisons with those more active than themselves) or downward comparisons (i.e., comparisons with those less active than themselves) (Festinger 1954). In both cases, the literature suggests that individuals will take action to reduce discrepancies between themselves and similar others (Festinger 1954, Garcia et al. 2013). Thus, if individuals compare upward, the revelation of this information between members of a leaderboard may have a positive impact on an individual’s reference point for healthful activity and increase exercise. For instance, a mother with two young children may aim for a higher level of healthful activity if she observes another mother with two young children consistently doing more healthful activity. Given that these two users may have similar schedule constraints, the focal user may find the leaderboard information more relatable. If individuals compare downward, the revelation of physical activity information by others may have unintended negative impacts on an individual’s reference point for physical activity. In particular, this informational signal can work in the opposite direction—that is, focal users may decrease activity if they see other relatable individuals on their leaderboards who are less active than themselves. Related to this point, Schultz et al. (2007) found that a nudge intended to decrease electricity consumption by revealing the consumption levels of others in one’s neighborhood had the (opposite) boomerang effect for those who were underusing electricity (relative to their neighbors) prior to the intervention. 3.2.2. Exercise Reference Points. 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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