Evolution of Knowledge Management Towards Wisdom Management

Maria Jakubik
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Maria Jakubik: Ronin Institute, 127 Haddon Pl, Montclair, New Jersey 07043, USA2Department of Leadership and Organizational Sciences, Faculty of Business and Economics, University of Pécs, Pécs, Rákóczi út 80, 7622, Hungary

Journal of Information & Knowledge Management (JIKM), 2023, vol. 22, issue 06, 1-18

Abstract: To provide solutions to the world’s global challenges, there is an urgent demand for wise organisations, wise leadership, wise workers, and most importantly, for wise actions. Since the mid-1990s, Knowledge Management (KM) as a discipline and practice has emerged internationally, and it has passed through several phases of development. Simultaneously, in the last four decades we have experienced a growth of wisdom research and intensified discourses about Wisdom Management (WM) as a possible venue for dealing with wicked problems. The dilemma is whether the current sixth phase of KM is able to address the global problems of the world. Therefore, this conceptual paper seeks to answer the question if WM will complement or replace KM. This paper explores the evolutionary phases of KM; it presents the discourses about WM, and it discovers the presence of wisdom in the KM literature (1995–2022). The research approach is explorative and inductive. Methods of Computational Social Sciences and RStudio as an Integrated Development Environment (IDE) are utilised for analysing, visualising, and interpreting the data. This paper analyses 255 wisdom-related keywords that emerged from 39 sources written by 50 authors. The three data analyses methods are: word cloud data analysis; dictionary-based data analysis, and bipartite network analysis. The findings are presented in word clouds; keywords frequency; bipartite network, and in a synthesised framework to show the similar and different concepts of KM and WM. The novelty value of this paper is the result of the bipartite network analysis that allows to identify how authors and wisdom-related keywords are connected with the same word nodes. This paper contributes to KM because it is the first study to explore and illustrate the presence of wisdom attributes in the KM literature.

Keywords: Knowledge Management (KM); wisdom management (WM); evolution of KM; Computational Social Sciences (CSS); RStudio; bipartite network analysis; dictionary-based data analysis (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1142/S021964922350051X

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