Adopting Artificial Intelligence in Healthcare in the Digital Age: Perceived Challenges, Frame Incongruence, and Social Power

Research output: Book/ReportPh.D. thesisResearch

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Abstract

Rapidly developing emerging technologies such as Artificial Intelligence (AI) have been transforming business and service practices. In the digital age, not only managers but also government policymakers and users must pay attention to adoption of technologies. There is still limited knowledge and understanding of the uniqueness of AI and its adoption, since the features of AI are new to users and policymakers and the specific context of healthcare. In particular, use of AI has been moving forward rather slowly in this sector compared with other
sectors such as finance and consulting. The factors behind the reluctance regarding AI adoption need to be further explored by scholars in Information Systems (IS).
To explore these influencing factors of adopting AI in healthcare, this paper-based dissertation draws on the theoretical lens of technological frames of reference (TFR) and social power to analyze the influencing factors and how these affect AI adoption in healthcare. Based on four Chinese hospitals, this dissertation uses case studies to exemplify different AI technologies adopted in each of the four hospitals. An framework of influencing factors of technology is proposed, which is inductively explored based on the literature review on
information technology (IT) adoption, and used to map the three papers in this dissertation.
This dissertation uses case studies and semi-structure interviews, participant observation and document analysis to collect data. Collected data were analyzed with NVivo version 11 following an abductive approach. Thus, in different papers, I used either an inductive approach or a combined inductive/deductive approach.
Original languageEnglish
Place of PublicationFrederiksberg
PublisherCopenhagen Business School [Phd]
Number of pages294
ISBN (Print)9788793956032
ISBN (Electronic)9788793956025
Publication statusPublished - 2019
SeriesPh.d. Serie
Number30.2019
ISSN0906-6934

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