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An Exploration and Confirmation of the Factors Influencing Adoption of IoT-Based Wearable Fitness Trackers

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  • Yu-Sheng Kao

    (Department of Technology Management for Innovation, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan)

  • Kazumitsu Nawata

    (Department of Technology Management for Innovation, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan)

  • Chi-Yo Huang

    (Department of Industrial Education, National Taiwan Normal University, Taipei 106, Taiwan)

Abstract

In recent years, IoT (Internet of Things)-based smart devices have penetrated a wide range of markets, including connected health, smart home, and wearable devices. Among the IoT-based smart devices, wearable fitness trackers are the most widely diffused and adopted IoT based devices. Such devices can monitor or track the physical activity of the person wearing them. Although society has benefitted from the conveniences provided by IoT-based wearable fitness trackers, few studies have explored the factors influencing the adoption of such technology. Furthermore, one of the most prevalent issues nowadays is the large attrition rate of consumers no longer wearing their device. Consequently, this article aims to define an analytic framework that can be used to explore the factors that influence the adoption of IoT-based wearable fitness trackers. In this article, the constructs for evaluating these factors will be explored by reviewing extant studies and theories. Then, these constructs are further evaluated based on experts’ consensus using the modified Delphi method. Based on the opinions of experts, the analytic framework for deriving an influence relationship map (IRM) is derived using the decision-making trial and evaluation laboratory (DEMATEL). Finally, based on the IRM, the behaviors adopted by mass customers toward IoT-based wearable fitness trackers are confirmed using the partial least squares (PLS) structural equation model (SEM) approach. The proposed analytic framework that integrates the DEMATEL and PLS-SEM was verified as being a feasible research area by empirical validation that was based on opinions provided by both Taiwanese experts and mass customers. The proposed analytic method can be used in future studies of technology marketing and consumer behaviors.

Suggested Citation

  • Yu-Sheng Kao & Kazumitsu Nawata & Chi-Yo Huang, 2019. "An Exploration and Confirmation of the Factors Influencing Adoption of IoT-Based Wearable Fitness Trackers," IJERPH, MDPI, vol. 16(18), pages 1-31, September.
    • Handle: RePEc:gam:jijerp:v:16:y:2019:i:18:p:3227-:d:263911
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    Cited by:

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    3. Sanjit Thapa & Abubakar Bello & Alana Maurushat & Farnaz Farid, 2023. "Security Risks and User Perception towards Adopting Wearable Internet of Medical Things," IJERPH, MDPI, vol. 20(8), pages 1-22, April.
    4. Na Yu & Yi-Ting Huang, 2020. "Important Factors Affecting User Experience Design and Satisfaction of a Mobile Health App—A Case Study of Daily Yoga App," IJERPH, MDPI, vol. 17(19), pages 1-16, September.
    5. Liqian Gao & Ziyang Liu, 2023. "Unraveling the Multifaceted Nexus of Artificial Intelligence Sports and User Willingness: A Focus on Technology Readiness, Perceived Usefulness, and Green Consciousness," Sustainability, MDPI, vol. 15(18), pages 1-16, September.
    6. Ming Xing Wang & Ki Su Kim & Jeoung Kun Kim, 2023. "Investigating the Determinants of IoT Device Continuance Intentions: An Empirical Study of Smart Speakers Through the Lens of Expectation-Confirmation Theory," SAGE Open, , vol. 13(3), pages 21582440231, September.
    7. Sonia Chien-I. Chen & Chenglian Liu, 2020. "Factors Influencing the Application of Connected Health in Remote Areas, Taiwan: A Qualitative Pilot Study," IJERPH, MDPI, vol. 17(4), pages 1-20, February.

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