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    Artificial Intelligence-based Public Healthcare Systems: G2G Knowledge-based Exchange to Enhance the Decision-making Process

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    Publication date
    2021
    End of Embargo
    2023-02-09
    Author
    Nasseef, O.A.
    Baabdullah, A.M.
    Alalwan, A.A.
    Lal, Banita
    Dwivedi, Y.K.
    Keyword
    Artificial Intelligence
    AI
    Public healthcare
    Cognitive fit model
    G2G knowledge-based exchange
    Experience-based decision-making
    Decision-making
    Rights
    © 2021 Elsevier. Reproduced in accordance with the publisher's self-archiving policy. This manuscript version is made available under the CC-BY-NC-ND 4.0 license (https://creativecommons.org/licenses/by-nc-nd/4.0/)
    Peer-Reviewed
    Yes
    Open Access status
    Green
    
    Metadata
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    Abstract
    With the rapid evolution of data over the last few years, many new technologies have arisen with artificial intelligent (AI) technologies at the top. Artificial intelligence (AI), with its infinite power, holds the potential to transform patient healthcare. Given the gaps revealed by the 2020 COVID-19 pandemic in healthcare systems, this research investigates the effects of using an artificial intelligence-driven public healthcare framework to enhance the decision-making process using an extended model of Shaft and Vessey (2006) cognitive fit model in healthcare organizations in Saudi Arabia. The model was validated based on empirical data collected using an online questionnaire distributed to healthcare organizations in Saudi Arabia. The main sample participants were healthcare CEOs, senior managers/managers, doctors, nurses, and other relevant healthcare practitioners under the MoH involved in the decision-making process relating to COVID-19. The measurement model was validated using SEM analyses. Empirical results largely supported the conceptual model proposed as all research hypotheses are significantly approved. This study makes several theoretical contributions. For example, it expands the theoretical horizon of Shaft and Vessey's (2006) CFT by considering new mechanisms, such as the inclusion of G2G Knowledge-based Exchange in addition to the moderation effect of Experience-based decision-making (EDBM) for enhancing the decision-making process related to the COVID-19 pandemic. More discussion regarding research limitations and future research directions are provided as well at the end of this study.
    URI
    http://hdl.handle.net/10454/18594
    Version
    Accepted manuscript
    Citation
    Nasseef OA, Baabdullah AM, Alalwan AA et al (2021) Artificial Intelligence-based Public Healthcare Systems: G2G Knowledge-based Exchange to Enhance the Decision-making Process. Government Information Quarterly. xx(xx): 101618. Accepted for publication.
    Link to publisher’s version
    https://doi.org/10.1016/j.giq.2021.101618
    Type
    Article
    Notes
    The full-text of this article will be released for public view at the end of the publisher embargo on 9 Feb 2023.
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    Management and Law Publications

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