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Exploring Patients’ AI Adoption Intention in the Context of Healthcare

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Digital Health and Medical Analytics (DHA 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1412))

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Abstract

Artificial intelligence (AI) produces positive effects on the productivity and efficiency for organizations and is widely adopted in various contexts. Although individuals’ adoption of new technology has been studied widely, very few studies has been devoted to the adoption of AI in the context of healthcare. Based on technology adoption related theories, the study explains how the proposed factors impact patients’ trust toward AI technology and in turn their adoption attention. Using 304 patients’ sample, we built the conceptual model and conclude that trust toward AI technology, perceived ease of use, relative advantage, and perceived risk in the healthcare background significantly affect AI adoption intention. Our study thus extends the understanding of AI use in the healthcare industry.

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Authors and Affiliations

  1. School of Economics and Management, Beijing Institute of Technology, Beijing, 100081, China

    Yiwei Zhu & Shiwei Sun

Authors
  1. Yiwei Zhu
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  2. Shiwei Sun
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Correspondence to Shiwei Sun .

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Editors and Affiliations

  1. The University of Sheffield, Sheffield, UK

    Yichuan Wang

  2. University of Waikato, Hamilton, New Zealand

    William Yu Chung Wang

  3. Beijing Institute of Technology, Beijing, China

    Zhijun Yan

  4. University of North Carolina at Charlotte, Charlotte, NC, USA

    Dongsong Zhang

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Zhu, Y., Sun, S. (2021). Exploring Patients’ AI Adoption Intention in the Context of Healthcare. In: Wang, Y., Wang, W.Y.C., Yan, Z., Zhang, D. (eds) Digital Health and Medical Analytics. DHA 2020. Communications in Computer and Information Science, vol 1412. Springer, Singapore. https://doi.org/10.1007/978-981-16-3631-8_4

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  • DOI: https://doi.org/10.1007/978-981-16-3631-8_4

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-3630-1

  • Online ISBN: 978-981-16-3631-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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