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An Exploratory Study of Home Healthcare Robots Adoption Applying the UTAUT Model

Author

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  • Ahmad Alaiad

    (Department of Information Systems, University of Maryland Baltimore County, Baltimore, MD, USA)

  • Lina Zhou

    (Department of Information Systems, University of Maryland Baltimore County, Baltimore, MD, USA)

  • Gunes Koru

    (Department of Information Systems, University of Maryland Baltimore County, Baltimore, MD, USA)

Abstract

The home healthcare initiative is aimed to reduce readmission costs, transportation costs, and hospital medical errors, and to improve post hospitalization healthcare quality, and enhance patient home independency. Today, it is almost unimaginable to consider this initiative without information technology. Home healthcare robots are one of such emerging technologies. Several robots have been developed to facilitate home healthcare such as remote presence robots (e.g., RP2) and Paro. Most previous research in this area has focused on technology and implementation issues of home healthcare robots, but ignored the factors that influence their adoption. To address the limitation, the current research applied and extended the UTAUT model to the home healthcare domain. The model was tested using survey questionnaire. The empirical results not only confirmed the effects of some constructs from the original UTAUT model but also identified perceived security as a new factor that directly affects usage intention of home healthcare robots. In addition, effort expectancy did not show a direct effect but an indirect effect through performance expectancy on usage intention. Several practical and theoretical implications are also discussed.

Suggested Citation

  • Ahmad Alaiad & Lina Zhou & Gunes Koru, 2014. "An Exploratory Study of Home Healthcare Robots Adoption Applying the UTAUT Model," International Journal of Healthcare Information Systems and Informatics (IJHISI), IGI Global, vol. 9(4), pages 44-59, October.
    • Handle: RePEc:igg:jhisi0:v:9:y:2014:i:4:p:44-59
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    Cited by:

    1. Haili Yang & Yueyue Luo & Yunhua Qiu & Jiantao Zou & Mohammad Masukujjaman & Abdullah Mohammed Ibrahim, 2023. "Modeling the Enablers of Consumers’ E-Shopping Behavior: A Multi-Analytic Approach," Sustainability, MDPI, vol. 15(8), pages 1-28, April.
    2. Pham, Phuoc & Zhang, Huilan & Gao, Wenlian & Zhu, Xiaowei, 2024. "Determinants and performance outcomes of artificial intelligence adoption: Evidence from U.S. Hospitals," Journal of Business Research, Elsevier, vol. 172(C).
    3. Yan Shi & Abu Bakkar Siddik & Mohammad Masukujjaman & Guangwen Zheng & Muhammad Hamayun & Abdullah Mohammed Ibrahim, 2022. "The Antecedents of Willingness to Adopt and Pay for the IoT in the Agricultural Industry: An Application of the UTAUT 2 Theory," Sustainability, MDPI, vol. 14(11), pages 1-23, May.
    4. Arfi, Wissal Ben & Nasr, Imed Ben & Kondrateva, Galina & Hikkerova, Lubica, 2021. "The role of trust in intention to use the IoT in eHealth: Application of the modified UTAUT in a consumer context," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    5. Yu-Ping Lee & Hsin-Yeh Tsai & Athapol Ruangkanjanases, 2020. "The Determinants for Food Safety Push Notifications on Continuance Intention in an E-Appointment System for Public Health Medical Services: The Perspectives of UTAUT and Information System Quality," IJERPH, MDPI, vol. 17(21), pages 1-15, November.
    6. Pinghao Ye & Liqiong Liu, 2021. "Factors Affecting User Intention to Pay via Online Medical Service Platform: Role of Misdiagnosis Risk and Timeliness of Response," International Journal of Healthcare Information Systems and Informatics (IJHISI), IGI Global, vol. 16(4), pages 1-26, October.

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