IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v18y2021i23p12682-d692863.html
   My bibliography  Save this article

Adopting Artificial Intelligence in Public Healthcare: The Effect of Social Power and Learning Algorithms

Author

Listed:
  • Tara Qian Sun

    (Department of Digitalization, Copenhagen Business School, 2000 Frederiksberg, Denmark)

Abstract

Although the use of artificial intelligence (AI) in healthcare is still in its early stages, it is important to understand the factors influencing its adoption. Using a qualitative multi-case study of three hospitals in China, we explored the research of factors affecting AI adoption from a social power perspective with consideration of the learning algorithm abilities of AI systems. Data were collected through semi-structured interviews, participative observations, and document analysis, and analyzed using NVivo 11. We classified six social powers into knowledge-based and non-knowledge-based power structures, revealing a social power pattern related to the learning algorithm ability of AI.

Suggested Citation

  • Tara Qian Sun, 2021. "Adopting Artificial Intelligence in Public Healthcare: The Effect of Social Power and Learning Algorithms," IJERPH, MDPI, vol. 18(23), pages 1-20, December.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:23:p:12682-:d:692863
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/18/23/12682/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/18/23/12682/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yu Tong & Chuan-Hoo Tan & Hock-Hai Teo, 2017. "Direct and Indirect Information System Use: A Multimethod Exploration of Social Power Antecedents in Healthcare," Information Systems Research, INFORMS, vol. 28(4), pages 690-710, December.
    2. L. G. Pee & Shan L. Pan & Lili Cui, 2019. "Artificial intelligence in healthcare robots: A social informatics study of knowledge embodiment," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 70(4), pages 351-369, April.
    3. Gerald C. Kane & Giuseppe (Joe) Labianca, 2011. "IS Avoidance in Health-Care Groups: A Multilevel Investigation," Information Systems Research, INFORMS, vol. 22(3), pages 504-522, September.
    4. Eivor Oborn & Michael Barrett & Elizabeth Davidson, 2011. "Unity in Diversity: Electronic Patient Record Use in Multidisciplinary Practice," Information Systems Research, INFORMS, vol. 22(3), pages 547-564, September.
    5. Abhay Nath Mishra & Catherine Anderson & Corey M. Angst & Ritu Agarwal, 2012. "Electronic Health Records Assimilation and Physician Identity Evolution: An Identity Theory Perspective," Information Systems Research, INFORMS, vol. 23(3-part-1), pages 738-760, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ortiz-Barrios, Miguel & Arias-Fonseca, Sebastián & Ishizaka, Alessio & Barbati, Maria & Avendaño-Collante, Betty & Navarro-Jiménez, Eduardo, 2023. "Artificial intelligence and discrete-event simulation for capacity management of intensive care units during the Covid-19 pandemic: A case study," Journal of Business Research, Elsevier, vol. 160(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yu-Kai Lin & Mingfeng Lin & Hsinchun Chen, 2019. "Do Electronic Health Records Affect Quality of Care? Evidence from the HITECH Act," Service Science, INFORMS, vol. 30(1), pages 306-318, March.
    2. Petrakaki, Dimitra & Klecun, Ela, 2015. "Hybridity as a process of technology's ‘translation’: customizing a national Electronic Patient Record," LSE Research Online Documents on Economics 60437, London School of Economics and Political Science, LSE Library.
    3. Oliver Thomas & Simon Hagen & Ulrich Frank & Jan Recker & Lauri Wessel & Friedemann Kammler & Novica Zarvic & Ingo Timm, 2020. "Global Crises and the Role of BISE," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 62(4), pages 385-396, August.
    4. Dan Zhang & Loo G. Pee & Shan L. Pan & Jingyuan Wang, 2024. "Information practices in data analytics for supporting public health surveillance," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 75(1), pages 79-93, January.
    5. Daniel Beverungen, 2014. "Exploring the Interplay of the Design and Emergence of Business Processes as Organizational Routines," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 6(4), pages 191-202, August.
    6. H. Colleen Stuart, 2017. "Structural Disruption, Relational Experimentation, and Performance in Professional Hockey Teams: A Network Perspective on Member Change," Organization Science, INFORMS, vol. 28(2), pages 283-300, April.
    7. Verstegen, Luuk & Houkes, Wybo & Reymen, Isabelle, 2019. "Configuring collective digital-technology usage in dynamic and complex design practices," Research Policy, Elsevier, vol. 48(8), pages 1-1.
    8. Meizi Zhou & Xuelin Li & Gordon Burtch, 2024. "Healthcare Across Boundaries: Urban-Rural Differences in the Consequences of Telehealth Adoption," Information Systems Research, INFORMS, vol. 35(3), pages 1092-1113, September.
    9. Petrakaki, Dimitra & Klecun, Ela & Cornford, Tony, 2016. "Changes in healthcare professional work afforded by technology: the introduction of a national electronic patient record in an English hospital," LSE Research Online Documents on Economics 59475, London School of Economics and Political Science, LSE Library.
    10. Xu, Zhuo, 2019. "An empirical study of patients' privacy concerns for health informatics as a service," Technological Forecasting and Social Change, Elsevier, vol. 143(C), pages 297-306.
    11. Carsten Østerlund & Mohammad Hossein Jarrahi & Matthew Willis & Karen Boyd & Christine T. Wolf, 2021. "Artificial intelligence and the world of work, a co‐constitutive relationship," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(1), pages 128-135, January.
    12. Andy Weeger & Heinz-Theo Wagner & Heiko Gewald & Tim Weitzel, 2021. "Contradictions and Interventions in Health IS," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 63(6), pages 689-710, December.
    13. Haijing Hao & Rema Padman & Baohong Sun & Rahul Telang, 2018. "Quantifying the Impact of Social Influence on the Information Technology Implementation Process by Physicians: A Hierarchical Bayesian Learning Approach," Information Systems Research, INFORMS, vol. 29(1), pages 25-41, March.
    14. Zahlan, Ahmed & Ranjan, Ravi Prakash & Hayes, David, 2023. "Artificial intelligence innovation in healthcare: Literature review, exploratory analysis, and future research," Technology in Society, Elsevier, vol. 74(C).
    15. Sangseok You & Lionel P. Robert, 2023. "Subgroup formation in human–robot teams: A multi‐study mixed‐method approach with implications for theory and practice," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 74(3), pages 323-338, March.
    16. Daniel Fürstenau & Martin Gersch & Stefanie Schreiter, 2023. "Digital Therapeutics (DTx)," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 65(3), pages 349-360, June.
    17. Huigang Liang & Yajiong Xue, 2022. "Save Face or Save Life: Physicians’ Dilemma in Using Clinical Decision Support Systems," Information Systems Research, INFORMS, vol. 33(2), pages 737-758, June.
    18. Michael A. Stanko, 2016. "Toward a Theory of Remixing in Online Innovation Communities," Information Systems Research, INFORMS, vol. 27(4), pages 773-791, December.
    19. Sebastian Hermes & Tobias Riasanow & Eric K. Clemons & Markus Böhm & Helmut Krcmar, 2020. "The digital transformation of the healthcare industry: exploring the rise of emerging platform ecosystems and their influence on the role of patients," Business Research, Springer;German Academic Association for Business Research, vol. 13(3), pages 1033-1069, November.
    20. Grace Fox & Tabitha L. James, 2021. "Toward an Understanding of the Antecedents to Health Information Privacy Concern: A Mixed Methods Study," Information Systems Frontiers, Springer, vol. 23(6), pages 1537-1562, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:18:y:2021:i:23:p:12682-:d:692863. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.