Developing an Integrated HMSAM-FoMO Model and Its Instrument Testing for Social Live Streaming
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Context: The rapid growth of social live streaming platforms has transformed how individuals interact and experience digital entertainment. Despite this expansion, prior studies have largely focused on commercial or gaming-related live streaming, leaving the social and hedonic aspects underexplored. Furthermore, psychological mechanisms such as the Fear of Missing Out (FoMO) have received limited attention in explaining behavioral intention in live streaming environments. Objective: This study aims to develop and validate an integrated model combining the Hedonic-Motivation System Adoption Model (HMSAM) with FoMO to explain users’ behavioral intention in social live streaming contexts. Method: A quantitative approach was employed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with data from 57 Indonesian social media users. The research process consisted of three stages: conceptual integration, instrument operationalization, and empirical validation, supported by expert qualitative evaluation to enhance construct clarity and theoretical consistency. Results: The findings show that hedonic motivations such as joy, curiosity, and immersion strongly influence behavioral intention, while FoMO acts both as a direct determinant and as a mediator linking hedonic motivations to user engagement. Two indicators (CTR2 and CTR4) were removed for weak conceptual fit, and constructs with AVE values slightly below 0.50 (Control and Perceived Usefulness) were retained for theoretical reasons. The integrated HMSAM–FoMO model explained 64.4% of the variance in behavioral intention, demonstrating strong explanatory power. Conclusions: The study contributes theoretically by extending HMSAM with FoMO to capture both emotional enjoyment and psychological tension in digital engagement. It also provides practical guidance for designing psychologically balanced live streaming experiences that enhance enjoyment while minimizing FoMO-induced anxiety. These findings offer a foundation for future research and policy development toward healthier digital participation.
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[1] A. Thompson, “Digital 2025: The essential guide to the global state of digital,” We Are Social. 2025. [Online]. Available: https://wearesocial.com/uk/blog/2025/02/digital-2025-the-essential-guide-to-the-global-state-of-digital/
[2] S. Kemp, “Digital 2025: Indonesia,” DataReportal. 2025. [Online]. Available: https://datareportal.com/reports/digital-2025-indonesia
[3] Surjandy, Sherleen, M. R. Alhakim, J. Kenaz, and Kelly, “Factors Influencing the Use of Sports Live Streaming Video Services Based on the Hedonism Model,” in 2023 10th International Conference on Information Technology, Computer, and Electrical Engineering, ICITACEE 2023, IEEE, 2023, pp. 65–70. https://doi.org/10.1109/ICITACEE58587.2023.10276668
[4] A. Subiyakto et al., “Reviewing Factors of Audience Engagement in Live Streaming,” J. CoreIT J. Has. Penelit. Ilmu Komput. dan Teknol. Inf., vol. 11, no. 1, pp. 85–92, 2025. https://doi.org/10.24014/coreit.v11i1.36039
[5] Y. Tian and B. Frank, “Optimizing live streaming features to enhance customer immersion and engagement: A comparative study of live streaming genres in China,” J. Retail. Consum. Serv., vol. 81, p. 103974, 2024. https://doi.org/ 10.1016/j.jretconser.2024.103974
[6] S. Salimah and P. Rufaidah, “Influence of Live Streaming on Virtual Experiential Marketing Mediated By Fomo: a Bibliometric Analysis Using Vosviewer,” Bus. Financ. J., vol. 10, no. 1, pp. 46–63, 2025. https://doi.org/10.33086/bfj.v10i1.6765
[7] A. Rachman, Y. Efawati, and J. T. Anmoel, “Understanding the Role of Fomo (Fear of Missing Out) in Impulse Purchase for Smes,” Riset, vol. 6, no. 2, pp. 117–134, 2024. https://doi.org/10.37641/riset.v6i2.2109
[8] A. K. Przybylski, K. Murayama, C. R. Dehaan, and V. Gladwell, “Motivational, emotional, and behavioral correlates of fear of missing out,” Comput. Human Behav., vol. 29, no. 4, pp. 1841–1848, 2013. https://doi.org/10.1016/j.chb.2013.02.014
[9] M. Chandraa, D. W. Sukmaningsih, and E. Sriwardiningsih, “The Impact of Live Streaming On Purchase Intention In Social Commerce In Indonesia,” Procedia Comput. Sci., vol. 234, pp. 987–995, 2024. https://doi.org/10.1016/j.procs.2024.03.088
[10] F. Fayola, V. Graciela, V. Chandra, and D. W. Sukmaningsih, “Impact of Gamification Elements on Live Streaming ECommerce (Live Commerce),” Procedia Comput. Sci., vol. 245, pp. 1065–1074, 2024. https://doi.org/ 10.1016/j.procs.2024.10.335
[11] T. Y. Qian, B. Yu, R. Matz, L. Luo, and C. Xu, “Gamification for consumer loyalty: An exploration of unobserved heterogeneity in gamified esports social live streaming,” Telemat. Informatics, vol. 85, p. 102062, 2023. https://doi.org/ 10.1016/j.tele.2023.102062
[12] S. L. Buglass, J. F. Binder, L. R. Betts, and J. D. M. Underwood, “Motivators of online vulnerability: The impact of social network site use and FOMO,” Comput. Human Behav., vol. 66, pp. 248–255, 2017. https://doi.org/10.1016/j.chb.2016.09.055
[13] E. Wegmann, U. Oberst, B. Stodt, and M. Brand, “Online-specific fear of missing out and Internet-use expectancies contribute to symptoms of Internet-communication disorder,” Addict. Behav. Reports, vol. 5, no. April, pp. 33–42, 2017. https://doi.org/10.1016/j.abrep.2017.04.001
[14] J. D. Elhai, H. Yang, and C. Montag, “Fear of missing out (Fomo): Overview, theoretical underpinnings, and literature review on relations with severity of negative affectivity and problematic technology use,” Brazilian J. Psychiatry, vol. 43, no. 2, pp. 203–209, 2021. https://doi.org/10.1590/1516-4446-2020-0870
[15] P. Lowry, J. Gaskin, N. Twyman, B. Hammer, and T. Roberts, “Taking ‘Fun and Games’ Seriously: Proposing the Hedonic-Motivation System Adoption Model (HMSAM),” J. Assoc. Inf. Syst., vol. 14, pp. 617–671, Apr. 2013. https://doi.org/ 10.17705/1jais.00347
[16] C. Ji, K. Li, and Q. He, “Understanding user’s continuance intention of mobile social media apps: fear of missing out (FoMO) and users’ desired value,” Curr. Psychol., vol. 43, no. 21, pp. 19330–19343, 2024. https://doi.org/10.1007/s12144-024-05753-8
[17] R. Agarwal and E. Karahanna, “Time Flies When You’re Having Fun: Cognitive Absorption and Beliefs About Information Technology Usage,” MIS Q. Manag. Inf. Syst., vol. 24, no. 4, pp. 665–694, 2000. https://doi.org/10.2307/3250951
[18] G. F. Khan, M. Sarstedt, W.-L. Shiau, J. F. Hair, C. M. Ringle, and M. P. Fritze, “Methodological research on partial least squares structural equation modeling (PLS-SEM) An analysis based on social network approaches,” Internet Res., vol. 29, no. 3, pp. 407–429, 2019. https://doi.org/10.1108/IntR-12-2017-0509
[19] J. F. Hair, G. T. Hult, C. Ringle, and M. Sarstedt, A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM), 2nd ed. SAGE Publications, 2017.
[20] L. S. Lambert and D. A. Newman, “Construct Development and Validation in Three Practical Steps: Recommendations for Reviewers, Editors, and Authors*,” Organ. Res. Methods, vol. 26, no. 4, pp. 574–607, 2023. htps://doi.org/10.1177/10944281221115374
[21] F. Davis and F. Davis, “Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology,” MIS Q., vol. 13, p. 319, Sep. 1989. https://doi.org/10.2307/249008
[22] M. Brod, L. E. Tesler, and T. L. Christensen, “Qualitative research and content validity: Developing best practices based on science and experience,” Qual. Life Res., vol. 18, no. 9, pp. 1263–1278, 2009. https://doi.org/10.1007/s11136-009-9540-9
[23] V. Venkatesh and F. D. Davis, “Theoretical extension of the Technology Acceptance Model: Four longitudinal field studies,” Manage. Sci., vol. 46, no. 2, pp. 186–204, Feb. 2000. https://doi.org/10.1287/mnsc.46.2.186.11926