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Understanding sustained usage of health and fitness apps: Incorporating the technology acceptance model with the investment model

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  • Cho, Heetae
  • Chi, Christina
  • Chiu, Weisheng

Abstract

With the increasing popularity and adoption of health/fitness apps, more research attention is needed to examine users' behavior in order to promote sustained usage of the apps. The purpose of this study is to understand health and fitness app users' decision-making process by integrating the Technology Acceptance Model (TAM) and the Investment Model (IM). Three hundred forty-six responses were collected from health and fitness app users in China. A confirmatory factor analysis and a structural equation modeling analysis were conducted. Results show that continuance intention to use the apps is significantly affected by constructs included in the two models. Specifically, perceived ease of use of the apps has a positive effect on perceived usefulness, which further affects users' intention to continue using the apps. In addition, perceived usefulness and perceived ease of use of the apps have significant effects on users' satisfaction, investment size, and quality of available alternatives, and these three constructs affect users' relationship commitment to the apps, which, in turn, influences users' continuing intention. The integrated model provides new insights into the app users' decision-making process and suggests practical implications for app providers, such as developing strategies to evoke and maintain users’ interest in their apps, keeping users satisfied by personalizing their experience, and designing features that keep users invested in the apps.

Suggested Citation

  • Cho, Heetae & Chi, Christina & Chiu, Weisheng, 2020. "Understanding sustained usage of health and fitness apps: Incorporating the technology acceptance model with the investment model," Technology in Society, Elsevier, vol. 63(C).
    • Handle: RePEc:eee:teinso:v:63:y:2020:i:c:s0160791x2030422x
    DOI: 10.1016/j.techsoc.2020.101429
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    1. Belanche, Daniel & Casaló, Luis V. & Guinalíu, Miguel, 2012. "Website usability, consumer satisfaction and the intention to use a website: The moderating effect of perceived risk," Journal of Retailing and Consumer Services, Elsevier, vol. 19(1), pages 124-132.
    2. Viswanath Venkatesh, 2000. "Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model," Information Systems Research, INFORMS, vol. 11(4), pages 342-365, December.
    3. Claudia Iconaru, 2013. "The Moderating Role of Perceived Self-efficacy in the Context of Online Buying Adoption," BRAND. Broad Research in Accounting, Negotiation, and Distribution, EduSoft Publishing, vol. 4(1), pages 20-29, March.
    4. Hyun Byun & Weisheng Chiu & Jung-sup Bae, 2018. "Exploring the Adoption of Sports Brand Apps: An Application of the Modified Technology Acceptance Model," International Journal of Asian Business and Information Management (IJABIM), IGI Global, vol. 9(1), pages 52-65, January.
    5. Giovanis, Apostolos N. & Athanasopoulou, Pinelopi, 2018. "Consumer-brand relationships and brand loyalty in technology-mediated services," Journal of Retailing and Consumer Services, Elsevier, vol. 40(C), pages 287-294.
    6. P.A. Ratna & Saloni Mehra, 2015. "Exploring the acceptance for e-learning using technology acceptance model among university students in India," International Journal of Process Management and Benchmarking, Inderscience Enterprises Ltd, vol. 5(2), pages 194-210.
    7. Viswanath Venkatesh & Fred D. Davis, 2000. "A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies," Management Science, INFORMS, vol. 46(2), pages 186-204, February.
    8. Ruiying Cai & Christina Geng-Qing Chi, 2018. "The impacts of complaint efforts on customer satisfaction and loyalty," The Service Industries Journal, Taylor & Francis Journals, vol. 38(15-16), pages 1095-1115, December.
    9. Maute, Manfred F. & Forrester, William Jr., 1993. "The structure and determinants of consumer complaint intentions and behavior," Journal of Economic Psychology, Elsevier, vol. 14(2), pages 219-247, June.
    10. Pham, Thanh-Thao T. & Ho, Jonathan C., 2015. "The effects of product-related, personal-related factors and attractiveness of alternatives on consumer adoption of NFC-based mobile payments," Technology in Society, Elsevier, vol. 43(C), pages 159-172.
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    5. Ryan, Mark, 2022. "The ethics of dietary apps: Technology, health, and the capability approach," Technology in Society, Elsevier, vol. 68(C).
    6. Bellary, Sreevatsa & Bala, Pradip Kumar & Chakraborty, Shibashish, 2024. "Exploring cognitive-behavioral drivers impacting consumer continuance intention of fitness apps using a hybrid approach of text mining, SEM, and ANN," Journal of Retailing and Consumer Services, Elsevier, vol. 81(C).
    7. Perez-Aranda, Javier & González Robles, Eva M. & Alarcón Urbistondo, Pilar, 2023. "Understanding antecedents of continuance and revisit intentions: The case of sport apps," Journal of Retailing and Consumer Services, Elsevier, vol. 72(C).
    8. Jianfei Cao & Karin Kurata & Yeongjoo Lim & Shintaro Sengoku & Kota Kodama, 2022. "Social Acceptance of Mobile Health among Young Adults in Japan: An Extension of the UTAUT Model," IJERPH, MDPI, vol. 19(22), pages 1-16, November.
    9. Esmonde, Katelyn & Roth, Stephen & Walker, Alexis, 2023. "A social and ethical framework for providing health information obtained from combining genetics and fitness tracking data," Technology in Society, Elsevier, vol. 74(C).

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