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Enhancing online fitness course participation: the impact of social support in reviews

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  • Zhou, Ruoxin
  • Zhou, Jialu
  • Ma, Xuejing

Abstract

Online reviews play a critical role in shaping user decisions. However, the content of these reviews, particularly the social support they offer, has been underexplored. This study investigates the impacts of two social support (i.e., informational and emotional) on user participation in online fitness communities, as well as the moderating effect of review visibility. Empirical analyses are conducted using a dataset from an online fitness platform, including 187 newly launched courses over a 16-week period. Social support variables are extracted and quantified through manual annotation and BERT-based analysis. The results indicate that courses with more informational and emotional support attract more user participation. Moreover, these positive impacts are more pronounced when the reviews are highly visible. Our study contributes to the field of online review by highlighting the role of social support and sheds light on the optimization of review management strategies.

Suggested Citation

  • Zhou, Ruoxin & Zhou, Jialu & Ma, Xuejing, 2026. "Enhancing online fitness course participation: the impact of social support in reviews," Journal of Business Research, Elsevier, vol. 203(C).
    • Handle: RePEc:eee:jbrese:v:203:y:2026:i:c:s0148296325006368
    DOI: 10.1016/j.jbusres.2025.115813
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    1. Banita Lal & Yogesh K. Dwivedi & Markus Haag, 2023. "Working from Home During Covid-19: Doing and Managing Technology-enabled Social Interaction With Colleagues at a Distance," Information Systems Frontiers, Springer, vol. 25(4), pages 1333-1350, August.
    2. R. Filieri & Fraser Mcleay & Bruce Tsui & Zhibin Lin, 2018. "Consumer perceptions of information helpfulness and determinants of purchase intention in online consumer reviews of services," Post-Print hal-04779103, HAL.
    3. Jonah Berger & Alan T. Sorensen & Scott J. Rasmussen, 2010. "Positive Effects of Negative Publicity: When Negative Reviews Increase Sales," Marketing Science, INFORMS, vol. 29(5), pages 815-827, 09-10.
    4. Melanie Swan, 2009. "Emerging Patient-Driven Health Care Models: An Examination of Health Social Networks, Consumer Personalized Medicine and Quantified Self-Tracking," IJERPH, MDPI, vol. 6(2), pages 1-34, February.
    5. Sungsik Park & Woochoel Shin & Jinhong Xie, 2021. "The Fateful First Consumer Review," Decision Analysis, INFORMS, vol. 40(3), pages 481-507, May-June.
    6. Chaoqun Deng & T. Ravichandran, 2024. "Managerial Response to Online Positive Reviews: Helpful or Harmful?," Information Systems Research, INFORMS, vol. 35(4), pages 1802-1823, December.
    7. Ni Huang & Yili Hong & Gordon Burtch, 2015. "Digital Social Visibility, Anonymity and User Content Generation: Evidence from Natural Experiments," Working Papers 15-04, NET Institute.
    8. David Godes & Dina Mayzlin, 2004. "Using Online Conversations to Study Word-of-Mouth Communication," Marketing Science, INFORMS, vol. 23(4), pages 545-560, June.
    9. Françoise Simon & Claire Roederer, 2019. "When social intrusiveness depletes customer value: A balanced perspective on the agency of simultaneous sharers in a commercial sharing experience," Post-Print hal-02319727, HAL.
    10. Lucia-Palacios, Laura & Pérez-López, Raúl & Polo-Redondo, Yolanda, 2018. "Can social support alleviate stress while shopping in crowded retail environments?," Journal of Business Research, Elsevier, vol. 90(C), pages 141-150.
    11. Yang (Alison) Liu & Zhenhui (Jack) Jiang & Ben C. F. Choi, 2023. "Pushing Yourself Harder: The Effects of Mobile Touch Modes on Users’ Self-Regulation," Information Systems Research, INFORMS, vol. 34(3), pages 996-1016, September.
    12. Lu Yan & Yong Tan, 2014. "Feeling Blue? Go Online: An Empirical Study of Social Support Among Patients," Information Systems Research, INFORMS, vol. 25(4), pages 690-709, December.
    13. Behnaz Bojd & Xiaolong Song & Yong Tan & Xiangbin Yan, 2022. "Gamified Challenges in Online Weight-Loss Communities," Information Systems Research, INFORMS, vol. 33(2), pages 718-736, June.
    14. Sungsik Park & Woochoel Shin & Jinhong Xie, 2021. "The Fateful First Consumer Review," Marketing Science, INFORMS, vol. 40(3), pages 481-507, May.
    15. Jeroen Stragier & Mariek Vanden Abeele & Lieven De Marez, 2018. "Recreational athletes’ running motivations as predictors of their use of online fitness community features," Behaviour and Information Technology, Taylor & Francis Journals, vol. 37(8), pages 815-827, August.
    16. Filieri, Raffaele, 2015. "What makes online reviews helpful? A diagnosticity-adoption framework to explain informational and normative influences in e-WOM," Journal of Business Research, Elsevier, vol. 68(6), pages 1261-1270.
    17. Baojun Gao & Jing Wang & Xiaojie Ding & Yue Guo, 2025. "The Pitfalls of Review Solicitation: Evidence from a Natural Experiment on TripAdvisor," Management Science, INFORMS, vol. 71(2), pages 1671-1691, February.
    18. Theodoros Lappas & Gaurav Sabnis & Georgios Valkanas, 2016. "The Impact of Fake Reviews on Online Visibility: A Vulnerability Assessment of the Hotel Industry," Information Systems Research, INFORMS, vol. 27(4), pages 940-961, December.
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