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Journal of Data and Information Science  2019, Vol. 4 Issue (2): 36-55    DOI: 10.2478/jdis-2019-0008
Research Paper     
Evolution of the Socio-cognitive Structure of Knowledge Management (1986-2015): An Author Co-citation Analysis
Carlos Luis González-Valiente1†(),Magda León Santos2,Ricardo Arencibia-Jorge3
1Biblioteca Nacional de Cuba “José Martí”, ave. Independencia, # 257 e/ 20 de Mayo y Aranguren, Plaza de la Revolución, La Habana, Cuba;
2Facultad de Comunicación, Universidad de la Habana, San Pedro entre Ermita y Avenida Independencia, Plaza de la Revolución, Cuba;
3Empresa de Tecnologías de la Información, Calle 18 # 4310, Miramar, Playa. La Habana, Cuba
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Abstract  

Purpose: The evolution of the socio-cognitive structure of the field of knowledge management (KM) during the period 1986-2015 is described.

Design/methodology/approach: Records retrieved from Web of Science were submitted to author co-citation analysis (ACA) following a longitudinal perspective as of the following time slices: 1986-1996, 1997-2006, and 2007-2015. The top 10% of most cited first authors by sub-periods were mapped in bibliometric networks in order to interpret the communities formed and their relationships.

Findings: KM is a homogeneous field as indicated by networks results. Nine classical authors are identified since they are highly co-cited in each sub-period, highlighting Ikujiro Nonaka as the most influential authors in the field. The most significant communities in KM are devoted to strategic management, KM foundations, organisational learning and behaviour, and organisational theories. Major trends in the evolution of the intellectual structure of KM evidence a technological influence in 1986-1996, a strategic influence in 1997-2006, and finally a sociological influence in 2007-2015.

Research limitations: Describing a field from a single database can offer biases in terms of output coverage. Likewise, the conference proceedings and books were not used and the analysis was only based on first authors. However, the results obtained can be very useful to understand the evolution of KM research.

Practical implications: These results might be useful for managers and academicians to understand the evolution of KM field and to (re)define research activities and organisational projects.

Originality/value: The novelty of this paper lies in considering ACA as a bibliometric technique to study KM research. In addition, our investigation has a wider time coverage than earlier articles.



Key wordsKnowledge management      Bibliometrics      Author co-citation analysis      Knowledge domain visualization      Social network analysis      Intellectual structure     
Received: 14 February 2019      Published: 30 May 2019
Cite this article:

Carlos Luis González-Valiente, Magda León Santos, Ricardo Arencibia-Jorge. Evolution of the Socio-cognitive Structure of Knowledge Management (1986-2015): An Author Co-citation Analysis. Journal of Data and Information Science, 2019, 4(2): 36-55.

URL:

http://manu47.magtech.com.cn/Jwk3_jdis/10.2478/jdis-2019-0008     OR     http://manu47.magtech.com.cn/Jwk3_jdis/Y2019/V4/I2/36

Figure 1. Co-citation map of authors, 1986-1996.

Note. Colors indicate different clusters and node size indicates citation weights.

Figure 2. Co-citation map of authors, 1997-2006.

Note. Colors indicate different clusters and node size indicates citation weights.

Figure 3. Co-citation map of authors, 2007-2015.

Note. Colors indicate different clusters and node size indicates citation weights.

Network measures 1986-1996 1997-2006 2007-2015
Nodes 20 39 152
Edges 79 741 11,186
Average degree 4 19 74
Diameter 3 1 2
Density 0.2 0.5 0.5
Average clustering coefficient 0.5 0.5 0.5
Table 1 Statistical description of the KM network.
Figure 4. Relations among KM communities using network-shrinking operation in Pajek; (a): 1986-1996, (b): 1997-2006; and (c): 2007-2015.
Sub-period Cluster name Size (colour) Top author ACC
1986-1996 (1) K-based theory 6 (red) Spender, JC 8
(2) K-based systems 6 (green) Skuce, D 9
(3) Technology-based strategy 5 (blue) Sanchez, R 7
(4) Decision support systems 3 (yellow) Holsapple, CW 11
1997-2006 (5) Strategic management 11 (red) Grant, RM 156
(6) K-based theory 10 (green) Nonaka, I 286
(7) Organizational learning and behaviour 9 (blue) Senge, PM 134
(8) KM foundations 9 (yellow) Davenport, TH 229
2007-2015 (9) Strategic management 41 (red) Grant, RM 229
(10) Marketing strategy 26 (green) Hair, JFJ 168
(11) KM foundations 23 (blue) Nonaka, I 382
(12) KM systems and technology 22 (yellow) Alavi, M 202
(13) Organizational theories 19 (purple) Wenger, EC 275
(14) Networks and knowledge transfer 12 (cyan) Hansen, MT 251
(15) Organizational leaning and behaviour 9 (light blue) Pfeffer, J 174
Table 7 Appendix 1. Cluster descriptions by sub-periods.
Author Discipline Affiliation RCFq*
1986-1996 Skuce, D Computer science Ottawa Univ 0.165
Holsapple, CW Management science Univ Kentuchy 0.094
Spender, J-C Management Kozminski Univ 0.076
Nonaka, I Business administration Hitotsubashi Univ 0.065
Bonczek, RH Computer science Illinois Univ 0.065
Sanchez, R Technology Strategy Copenhagen Bus Sch 0.053
Nelson, RR Economics Univ Manchester 0.047
Hedlund, G Economics Stockholm Sch Econ 0.047
Von Hippel, E Economics MIT Sloan Sch Manag 0.047
Kogut, B Management Univ Penn 0.047
1997-2006 Nonaka, I Business administration Hitotsubashi Univ 0.144
Davenport, TH Management; Business Harvard Univ 0.091
Polanyi, M Physical chemistry Manchester Univ 0.041
Grant, RM Economics Georgetown Univ 0.038
Leonard-Barton, D Business administration Harvard Univ 0.035
Brown, JS Computer and Communication Sciences Xerox Corp 0.034
Alavi, M Information systems; Computer Science Emory Univ-Atlanta 0.031
Hansen, MT Business administration Univ Calif Berkeley and Berkeley National Lab 0.029
Teece, DJ Economics Univ Calif 0.028
Wenger, EC Artificial inteligence Social Capital Grp 0.027
2007-2015 Nonaka, I Business administration Hitotsubashi Univ 0.074
Davenport, TH Management; Business Harvard Univ 0.037
Grant, RM Economics Georgetown Univ 0.025
Alavi, M Information systems; Computer Science Emory Univ-Atlanta 0.024
Teece, DJ Economics Univ Calif 0.018
Hansen, MT Business administration Univ Calif Berkeley and Berkeley National Lab 0.017
Wenger, EC Artificial inteligence Social Capital Grp 0.016
Polanyi, M Physical chemistry Manchester Univ 0.015
Kogut, B Management Univ Penn 0.014
Barney, JB Sociology; Administrative Sciences Ohio State Univ 0.014
Table 8 Appendix 2. Top 10 authors by sub-periods.
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