JOURNAL ARTICLE

Knowledge Sharing in Health Community of Practice (CoP) and Online Health Communities (OHCs): A Bibliometric Analysis.

  • Published In: Journal of Information & Knowledge Management, 2023, v. 22, n. 3. P. 1 1 of 3

  • Database: The Belt and Road Initiative Reference Source 2 of 3

  • Authored By: Fauzi, Muhammad Ashraf 3 of 3

Abstract

This study aims to provide a scientific mapping based on a bibliographic database of knowledge sharing in the health community of practice (CoP) and online health communities (OHCs). These online platforms have provided an efficient means for members to share best practices, expertise, and information on health-related matters and acquire knowledge in the fast-moving health and medical field. Applying a bibliometric method, this study contributes to the body of knowledge concerning health CoP function, capacity, and contribution. This study tends to uncover past themes (citation analysis), current themes (co-citation analysis), and predict trends (co-word analysis) on health CoP and OHCs perspectives. Findings indicate the imperative role of CoP in the field, mainly due to the rapid development of sophisticated tacit knowledge on complicated health issues and unpredictable diseases affecting public health. Implications on theory and managerial aspect to strengthen the function of CoP in providing optimum health service to the public is discussed. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Journal of Information & Knowledge Management. 2023/06, Vol. 22, Issue 3, p1
  • Document Type:Article
  • Subject Area:Social Sciences and Humanities
  • Publication Date:2023
  • ISSN:0219-6492
  • DOI:10.1142/S0219649223500065
  • Accession Number:164629587
  • Copyright Statement:Copyright of Journal of Information & Knowledge Management is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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