Cited by 346Technology Adoption and User BehaviourArtificial Intelligence in Healthcare and EducationElectronic Health Records Systems

Investigating the impacting factors for the healthcare professionals to adopt artificial intelligence-based medical diagnosis support system (AIMDSS)

Fan, Wenjuan, Liu, Jingnan, Zhu, Shuwan, Pardalos, Panos M.·2020·Annals of Operations Research

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Crossref · 10.1007/s10479-018-2818-y

Cites

78 of 78 references verified0 citation errors · 0 not checkable

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  • Higher levels of Personal innovativeness in technology adoption will be positively related to HRM (AI) extension.

    “Research Proposition 9 (a-d): Higher levels of Personal innovativeness in technology adoption will be positively related to HRM (AI) a) initiation, b) adoption, c) routinisation, and d) extension.”

    From AI-augmented HRM: Antecedents, assimilation and multilevel consequences (2023) · cites this paper as Fan et al., 2020

  • Higher levels of Personal innovativeness in technology adoption will be positively related to HRM (AI) adoption.

    “Research Proposition 9 (a-d): Higher levels of Personal innovativeness in technology adoption will be positively related to HRM (AI) a) initiation, b) adoption, c) routinisation, and d) extension.”

    From AI-augmented HRM: Antecedents, assimilation and multilevel consequences (2023) · cites this paper as Fan et al., 2020

  • Higher levels of Personal innovativeness in technology adoption will be positively related to HRM (AI) routinisation.

    “Research Proposition 9 (a-d): Higher levels of Personal innovativeness in technology adoption will be positively related to HRM (AI) a) initiation, b) adoption, c) routinisation, and d) extension.”

    From AI-augmented HRM: Antecedents, assimilation and multilevel consequences (2023) · cites this paper as Fan et al., 2020

  • Higher levels of Personal innovativeness in technology adoption will be positively related to HRM (AI) initiation.

    “Research Proposition 9 (a-d): Higher levels of Personal innovativeness in technology adoption will be positively related to HRM (AI) a) initiation, b) adoption, c) routinisation, and d) extension.”

    From AI-augmented HRM: Antecedents, assimilation and multilevel consequences (2023) · cites this paper as Fan et al., 2020

  • Trust is associated with increased intent to adopt machine learning-based CDSSs.

    “whereas trust is associated with increased intent to adopt machine learning–based CDSSs [11].”

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Authors
Fan, W., Liu, J., Zhu, S., & Pardalos, P. M.
Affiliations
Hefei University of Technology (CN)
Corresponding author
Fan, Wenjuan
Venue
Annals of Operations Research
Published
2018-03-19
Volume
294
Issue
1-2
Pages
567-592
ISSN
  • 0254-5330 (ISSN-L)
  • 1572-9338
OpenAlex
W2791915030
Cited by
346
References
78
Citations by year
2026: 40 · 2025: 73 · 2024: 71 · 2023: 48 · 2022: 62 · 2021: 25 · 2020: 20 · 2019: 6 · 2018: 1
FWCI
18.46
Type
journal article
Language
en
Open access
closed
Locations
  • Annals of Operations Research (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Funders
nature sciences foundation of china (71501058)
Topics
  • Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
Keywords
technology adoption, healthcare workers, UTAUT, trust theory, task complexity, technology acceptance, artificial intelligence in healthcare

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