IDEAS home Printed from https://ideas.repec.org/a/eee/teinso/v63y2020ics0160791x2030422x.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0160791X2030422X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.techsoc.2020.101429?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Salvador Angosto & Jerónimo García-Fernández & Moisés Grimaldi-Puyana, 2023. "A systematic review of intention to use fitness apps (2020–2023)," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-11, December.
    2. 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).
    3. Pal, Shounak & Biswas, Baidyanath & Gupta, Rohit & Kumar, Ajay & Gupta, Shivam, 2023. "Exploring the factors that affect user experience in mobile-health applications: A text-mining and machine-learning approach," Journal of Business Research, Elsevier, vol. 156(C).
    4. Souha Al-Geitany & Hasan Yousef Aljuhmani & Okechukwu Lawrence Emeagwali & Elsie Nasr, 2023. "Consumer Behavior in the Post-COVID-19 Era: The Impact of Perceived Interactivity on Behavioral Intention in the Context of Virtual Conferences," Sustainability, MDPI, vol. 15(11), pages 1-23, May.
    5. Poonyawat Kusonwattana & Yogi Tri Prasetyo & Stefanus Vincent & Jefferson Christofelix & Aryadaksa Amudra & Hazel Juan Montgomery & Michael Nayat Young & Reny Nadlifatin & Satria Fadil Persada, 2022. "Determining Factors Affecting Behavioral Intention to Organize an Online Event during the COVID-19 Pandemic," Sustainability, MDPI, vol. 14(20), pages 1-15, October.
    6. Ryan, Mark, 2022. "The ethics of dietary apps: Technology, health, and the capability approach," Technology in Society, Elsevier, vol. 68(C).
    7. 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.
    8. 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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Liébana-Cabanillas, Francisco & Marinkovic, Veljko & Ramos de Luna, Iviane & Kalinic, Zoran, 2018. "Predicting the determinants of mobile payment acceptance: A hybrid SEM-neural network approach," Technological Forecasting and Social Change, Elsevier, vol. 129(C), pages 117-130.
    2. Schmidthuber, Lisa & Maresch, Daniela & Ginner, Michael, 2020. "Disruptive technologies and abundance in the service sector - toward a refined technology acceptance model," Technological Forecasting and Social Change, Elsevier, vol. 155(C).
    3. Salvador Angosto & Jerónimo García-Fernández & Moisés Grimaldi-Puyana, 2023. "A systematic review of intention to use fitness apps (2020–2023)," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-11, December.
    4. Türker, Cansu & Altay, Burak Can & Okumuş, Abdullah, 2022. "Understanding user acceptance of QR code mobile payment systems in Turkey: An extended TAM," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    5. Mäntymäki, Matti & Salo, Jari, 2013. "Purchasing behavior in social virtual worlds: An examination of Habbo Hotel," International Journal of Information Management, Elsevier, vol. 33(2), pages 282-290.
    6. Globisch, Joachim & Dütschke, Elisabeth & Schleich, Joachim, 2018. "Acceptance of electric passenger cars in commercial fleets," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 122-129.
    7. Michael Addotey-Delove & Richard E. Scott & Maurice Mars, 2023. "Healthcare Workers’ Perspectives of mHealth Adoption Factors in the Developing World: Scoping Review," IJERPH, MDPI, vol. 20(2), pages 1-27, January.
    8. Nistor, Cristian, 2013. "A conceptual model for the use of social media in companies," MPRA Paper 44224, University Library of Munich, Germany.
    9. Peter Bou Saba & Régis Meissonier, 2016. "Conflict contagion effects from previous IT projects: action research during preliminary phases of a DST implementation project [Effets de contagion de conflits de projets TI antérieurs:Une recherc," Post-Print hal-02161336, HAL.
    10. Sarv Devaraj & Ming Fan & Rajiv Kohli, 2002. "Antecedents of B2C Channel Satisfaction and Preference: Validating e-Commerce Metrics," Information Systems Research, INFORMS, vol. 13(3), pages 316-333, September.
    11. Youngcheoul Kang & Nakbum Choi & Seoyong Kim, 2021. "Searching for New Model of Digital Informatics for Human–Computer Interaction: Testing the Institution-Based Technology Acceptance Model (ITAM)," IJERPH, MDPI, vol. 18(11), pages 1-36, May.
    12. Shafiqul Islam & Mohammad Fakhrul Islam & Noor-E- Zannat, 2023. "Behavioral Intention to Use Online for Shopping in Bangladesh: A Technology Acceptance Model Analysis," SAGE Open, , vol. 13(3), pages 21582440231, September.
    13. Han-Jen Niu & Fei-Hsu Sun Hung & Po-Ching Lee & Yensen Ni & Yuhsin Chen, 2023. "Eco-Friendly Transactions: Exploring Mobile Payment Adoption as a Sustainable Consumer Choice in Taiwan and the Philippines," Sustainability, MDPI, vol. 15(24), pages 1-18, December.
    14. Xin Xu & Viswanath Venkatesh & Kar Yan Tam & Se-Joon Hong, 2010. "Model of Migration and Use of Platforms: Role of Hierarchy, Current Generation, and Complementarities in Consumer Settings," Management Science, INFORMS, vol. 56(8), pages 1304-1323, August.
    15. Sharath Sasidharan & Radhika Santhanam & Daniel J. Brass & Vallabh Sambamurthy, 2012. "The Effects of Social Network Structure on Enterprise Systems Success: A Longitudinal Multilevel Analysis," Information Systems Research, INFORMS, vol. 23(3-part-1), pages 658-678, September.
    16. Juan F. Tavera Mesías & Juan C. Sánchez Giraldo & Bernardo Ballesteros Díaz, 2011. "Aceptación del E-Commerce en Colombia: un estudio para la ciudad de Medellín," Revista Facultad de Ciencias Económicas, Universidad Militar Nueva Granada, December.
    17. BHINDER Hardaman Singh & NAYAK Kamakshya Prasad & KUMAR Vineet, 2021. "The Technology Acceptance Model and Learning Management System: A Study on Undergraduate Tourism and Hospitality Students," European Journal of Interdisciplinary Studies, Bucharest Economic Academy, issue 02, June.
    18. Zhiqiang Yuan & Jing Liu & Xi Deng & Tianzi Ding & Tommy Tanu Wijaya, 2023. "Facilitating Conditions as the Biggest Factor Influencing Elementary School Teachers’ Usage Behavior of Dynamic Mathematics Software in China," Mathematics, MDPI, vol. 11(6), pages 1-18, March.
    19. Driediger, Fabian & Bhatiasevi, Veera, 2019. "Online grocery shopping in Thailand: Consumer acceptance and usage behavior," Journal of Retailing and Consumer Services, Elsevier, vol. 48(C), pages 224-237.
    20. Yadgar Taha M. Hamakhan, 2020. "The effect of individual factors on user behaviour and the moderating role of trust: an empirical investigation of consumers’ acceptance of electronic banking in the Kurdistan Region of Iraq," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-29, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:teinso:v:63:y:2020:i:c:s0160791x2030422x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/technology-in-society .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.