Advancing public sector knowledge management: towards an understanding of knowledge formation in public administration
Harri Laihonen,
Anna-Aurora Kork and
Lotta-Maria Sinervo
Knowledge Management Research & Practice, 2024, vol. 22, issue 3, 223-233
Abstract:
The article proposes a novel way of conceptualising knowledge management in public sector by highlighting the social process of knowledge formation, where knowledge for public policies emerges and takes shape. This approach aims to overcome three main criticisms levelled at knowledge management, namely its excessive internal focus, solving tame organisational problems, and focusing on data over meanings. We take knowledge formation to be a social process in which information is collected, interpreted, and shared. We expand and contribute to the ongoing debate on KM in public sector by integrating insights from administrative sciences, organisation studies, and political science. The suggested approach provides an opportunity to understand the diverse conceptions regarding the role of information and the nature of knowledge in organisational decision-making and policy-making that complements the organisation-centric and instrumentalist approach to KM.
Date: 2024
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/14778238.2023.2187719 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:tkmrxx:v:22:y:2024:i:3:p:223-233
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tkmr20
DOI: 10.1080/14778238.2023.2187719
Access Statistics for this article
Knowledge Management Research & Practice is currently edited by Giovanni Schiuma
More articles in Knowledge Management Research & Practice from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().