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Healthcare wearable devices: an analysis of key factors for continuous use intention

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  • Sang M. Lee

    (University of Nebraska-Lincoln)

  • DonHee Lee

    (Inha University)

Abstract

This study empirically examined the effects of internal and external factors on actual use behavior, health improvement expectancy, and continuous use intention of healthcare wearable devices. The study proposed a research model with its associated hypotheses that were tested using structural equation modeling. We also performed a comparative analysis of the two sample groups (medical personnel and general public), based on data collected from 288 healthcare wearable devices/apps users. The findings of the study indicated that internal and external factors have positive effects on actual use behavior, and health improvement expectancy and continuous use intention of healthcare wearable devices can be promoted through actual use behavior. The comparative analysis of the two groups showed that medical personnel had higher relationships among the study factors than general public. The study results shed theoretical and practical implications regarding how healthcare wearable devices or apps can be effectively used for disease prevention and health management for the users.

Suggested Citation

  • Sang M. Lee & DonHee Lee, 2020. "Healthcare wearable devices: an analysis of key factors for continuous use intention," Service Business, Springer;Pan-Pacific Business Association, vol. 14(4), pages 503-531, December.
    • Handle: RePEc:spr:svcbiz:v:14:y:2020:i:4:d:10.1007_s11628-020-00428-3
    DOI: 10.1007/s11628-020-00428-3
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    Cited by:

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    6. Roberto De Fazio & Roberta Proto & Carolina Del-Valle-Soto & Ramiro Velázquez & Paolo Visconti, 2022. "New Wearable Technologies and Devices to Efficiently Scavenge Energy from the Human Body: State of the Art and Future Trends," Energies, MDPI, vol. 15(18), pages 1-37, September.
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    8. Hayat, Naeem & Salameh, Anas A. & Malik, Haider Ali & Yaacob, Mohd Rafi, 2022. "Exploring the adoption of wearable healthcare devices among the Pakistani adults with dual analysis techniques," Technology in Society, Elsevier, vol. 70(C).
    9. Uzir, Md Uzir Hossain & Al Halbusi, Hussam & Lim, Rodney & Jerin, Ishraq & Abdul Hamid, Abu Bakar & Ramayah, Thurasamy & Haque, Ahasanul, 2021. "Applied Artificial Intelligence and user satisfaction: Smartwatch usage for healthcare in Bangladesh during COVID-19," Technology in Society, Elsevier, vol. 67(C).
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    11. Yuhyung Shin & Won-Moo Hur & Hansol Hwang, 2022. "Impacts of customer incivility and abusive supervision on employee performance: a comparative study of the pre- and post-COVID-19 periods," Service Business, Springer;Pan-Pacific Business Association, vol. 16(2), pages 309-330, June.
    12. Jennifer Eymann & Werner Vach & Luis Fischer & Marcel Jakob & Andreas Gösele, 2022. "Comparing a Sensor for Movement Assessment with Traditional Physiotherapeutic Assessment Methods in Patients after Knee Surgery—A Method Comparison and Reproducibility Study," IJERPH, MDPI, vol. 19(24), pages 1-19, December.
    13. Jesús J. Cambra-Fierro & María Fuentes-Blasco & Rocío Huerta-Álvarez & Ana Olavarría, 2021. "Customer-based brand equity and customer engagement in experiential services: insights from an emerging economy," Service Business, Springer;Pan-Pacific Business Association, vol. 15(3), pages 467-491, September.
    14. DonHee Lee & Seong No Yoon, 2021. "Application of Artificial Intelligence-Based Technologies in the Healthcare Industry: Opportunities and Challenges," IJERPH, MDPI, vol. 18(1), pages 1-18, January.
    15. Marinko Skare & Domingo Riberio Soriano, 2022. "Explaining COVID-19 shock wave mechanism in the European service industry using convergence clubs analysis," Service Business, Springer;Pan-Pacific Business Association, vol. 16(2), pages 283-307, June.

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