Inspiration from the “Biggest Loser”: Social Interactions in a Weight Loss Program

Abstract

We investigate the role of heterogeneous peer effects in encouraging healthy lifestyles. Our analysis revolves around one of the largest and most extensive databases about weight loss that track individual participants’ meeting attendance and progress in a large national weight loss program. The main finding is that, although weight loss among average-performing peers has a negative effect on an individual’s weight loss, the corresponding effect for the top performer among peers is positive. Furthermore, we show that our results are robust to potential issues related to selection into meetings, endogenous peer outcomes, individual unobserved heterogeneity, lagged dependent variables, and contextual effects. Ultimately, these results provide guidance about how the weight loss program should identify role models.

Consumer susceptibility to social influence in new product diffusion networks: how does network location matter?

“…Marketers have been increasingly interested in leveraging peer influence in online brand communities to maximize the effort toward a specific goal, such as preserving energy (Yildirim et al, 2020). Our results suggest that the optimal community design could consider not only the heterogeneity in peer performance (Uetake and Yang, 2020) and network structural EJM 55,5 conditions such as density (Yildirim et al, 2020), but also the network location characteristics of members in online brand communities.…”

Testing Theories of Goal Progress in Online Learning

“…In addition, although there was little social interaction among learners within the courses in our sample, an emerging area within MOOCs is understanding learner behaviors within online forums, student–teaching assistant interactions, and peer grading (Ramesh et al 2013; Sinha et al 2014). Learners may also be motivated by weekly subgoals (Fishbach, Dhar, and Zhang 2006; Morgan 1985) or the behavior of others (Huang 2018; Uetake and Yang 2020).…”

“…Consistent with this, actions at the beginning and end of a sequence are perceived to be more diagnostic of personal standards compared with actions in the middle (Touré-Tillery and Fishbach 2012). The stuck-in-the-middle pattern suggests that individuals are vulnerable to dropout in the middle of a course and may stop paying attention to motivating reference points such as the performance of others (Huang 2018; Uetake and Yang 2020). Content creators may anticipate and combat the “lull” in the middle by reframing activities or subgoals within a sequence.…”

Online Training of Salespeople: Impact, Heterogeneity, and Spillover Effects

“…Competitive pressure among peers may reduce coworkers’ well-being, hurt profits, and lead to higher employee attrition (Cornelissen 2016) (i.e., negative spillover effects). In the weight loss domain, Uetake and Yang (2020) find that average weight loss by peers discourages their own future weight loss (a negative effect), and the top performer's weight loss encourages their own future weight loss (a positive effect). In the sales training literature, Chan, Li, and Pierce (2014a) study team versus individual commissions in the same context as Chan, Li, and Pierce (2014b).…”

“…Literature on the spillover effect is rich and spread across many domains such as advertising (Shi, Grewal, and Sridhar 2021), research and development (Bloom, Schankerman, and Van Reenen 2013), branding (Balachander and Ghose 2003), entrepreneurship (Aarstad, Haugland, and Greve 2010), product diffusion (Bollinger and Gillingham 2012), human capital (Battu, Belfield, and Sloane 2003; Mas and Moretti 2009; Moretti 2004; Rosenthal and Strange 2008), education and training (Atefi et al 2018), gambling (Park and Manchanda 2015), and weight loss (Uetake and Yang 2020). Summarizing the extant literature on peer effects, Hickman and Metz (2018) find two broad reasons for peer effects: learning and motivation.…”