Author:
Zhang Zhiguo,Zhang Jun,Zheng Bowen,Zhang Jingzhi, , ,
Abstract
Due to the importance of employees’ physical well-being, organizations have long been conducting wellness programs to motivate their employees to exercise. The wide use of wearable devices (e.g., smart bands and smartphones) and fitness applications (e.g., fitness mobile applications) enable organizations to shift from offline to online fitness programs where participants use physical activity records tracked by wearable devices to complete fitness tasks and challenges. To better motivate employees’ exercise behavior, online fitness programs widely offer monetary or social incentives strategies. However, little is known about the interaction effects of the two types of incentives when they are jointly offered. Besides, organizers lack knowledge of how to set an optimal fitness challenge for the incentives in online fitness programs. In this study, we obtained a rich panel dataset from a university-wide online fitness program, which includes the daily exercise records of 2578 participants during a 100-day period, to empirically investigate the joint effects of monetary and social incentives on individuals’ exercise behavior. Most interestingly, we found that there is a crowd-out effect between monetary and social incentives—the influences of social incentives (i.e., social support and social contagion) are relatively weaker when there exists an unachieved monetary goal; once the monetary goal has been achieved, the influences of social incentives become stronger. In addition, we found that participants’ exercise behavior can be maximized when the dynamic goal is set at an optimal level. Our findings can help practitioners better design the online fitness programs and the associated fitness technologies.
Publisher
Journal of University of Science and Technology of China
Reference63 articles.
1. Joo S Y, Lee C B, Joo N Y, et al. Feasibility and effectiveness of a motion tracking-based online fitness program for office workers. Healthcare, 2021, 9 (5): 584.
2. Walsh J C, Corbett T, Hogan M, et al. An mHealth intervention using a smartphone app to increase walking behavior in young adults: A pilot study. JMIR mHealth and uHealth, 2016, 4 (3): 1–8.
3. Sullivan A N, Lachman M E. Behavior change with fitness technology in sedentary adults: A review of the evidence for increasing physical activity. Frontiers in Public Health, 2017, 4: 1–16.
4. Wilson C, Boe B, Sala A, et al. User interactions in social networks and their implications. In: Proceedings of the 4th ACM European Conference on Computer Systems. New York: ACM, 2009.
5. Woldaregay A Z, Issom D Z, Henriksen A, et al. Motivational factors for user engagement with mHealth apps. In: pHealth 2018. Amsterdam: IOS Press, 2018.
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