Unraveling dynamics of multi-goal pursuit in health behavior: evidence from an online fitness platform

Purpose Multi-goal setting has complex effects on individual behavior, which may be due to the changes in self-efficacy in the process of multi-goal pursuit. Most research focuses on the pursuit of a single goal, and a few discuss the static effects of multi-goal setting on behavior change. However, self-efficacy dynamically changes when individuals pursue diverse goals, which is a dynamic process. This study takes an online fitness platform as an example to explore how multi-goal pursuit dynamically influences users’ self-efficacy and then changes their fitness behavior. Design/methodology/approach We collect detailed goal pursuit and fitness information of 1,387 unique users from a popular online fitness platform. Hidden Markov model is used to reveal the real-time self-efficacy state of users and capture the varying effects of multiple goals across users and over time. Findings We demonstrate that multiple goals have a positive effect on the transition to higher self-efficacy. Furthermore, the difficulty of goals and the tenure of users play different roles in the effect of physical and mental goals. Higher-difficulty goals only boost the relationship between physical goals and maintaining high self-efficacy. However, the moderation effect of user tenure is completely opposite. Originality/value This is the first study using Hidden Markov model to explain the underlying mechanism between multiple goals and fitness behavior in online context. We also find heterogeneous effects of multiple goals for different goal difficulties, which extends the research on goal difficulty in goal-setting theory. Our study provides insights to managers on gearing interventions toward users in specific states.

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Publication Details

Journal
Industrial Management & Data Systems
Published
2025-05-19
DOI
https://doi.org/10.1108/imds-10-2024-1053
Primary Topic
Behavioral Health and Interventions
Type
article
Field-Weighted Citation Impact
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article

Unraveling dynamics of multi-goal pursuit in health behavior: evidence from an online fitness platform

Chenxi Guo, Qiuju Yin, Zhijun Yan
1 links
Industrial Management & Data Systems
Behavioral Health and Interventions
article

Unraveling dynamics of multi-goal pursuit in health behavior: evidence from an online fitness platform

Chenxi Guo, Qiuju Yin, Zhijun Yan
article en

Abstract

Purpose Multi-goal setting has complex effects on individual behavior, which may be due to the changes in self-efficacy in the process of multi-goal pursuit. Most research focuses on the pursuit of a single goal, and a few discuss the static effects of multi-goal setting on behavior change. However, self-efficacy dynamically changes when individuals pursue diverse goals, which is a dynamic process. This study takes an online fitness platform as an example to explore how multi-goal pursuit dynamically influences users’ self-efficacy and then changes their fitness behavior. Design/methodology/approach We collect detailed goal pursuit and fitness information of 1,387 unique users from a popular online fitness platform. Hidden Markov model is used to reveal the real-time self-efficacy state of users and capture the varying effects of multiple goals across users and over time. Findings We demonstrate that multiple goals have a positive effect on the transition to higher self-efficacy. Furthermore, the difficulty of goals and the tenure of users play different roles in the effect of physical and mental goals. Higher-difficulty goals only boost the relationship between physical goals and maintaining high self-efficacy. However, the moderation effect of user tenure is completely opposite. Originality/value This is the first study using Hidden Markov model to explain the underlying mechanism between multiple goals and fitness behavior in online context. We also find heterogeneous effects of multiple goals for different goal difficulties, which extends the research on goal difficulty in goal-setting theory. Our study provides insights to managers on gearing interventions toward users in specific states.

Industrial Management & Data SystemsVol. 125(7)
Openalex Percentile: Top 88%
Behavioral Health and Interventions
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Unraveling dynamics of multi-goal pursuit in health behavior: evidence from an online fitness platform — Chenxi Guo, Qiuju Yin, et al. · Industrial Management & Data Systems (2025) | TGRS Research Map | TGRS