Social Network Analysis of Knowledge and Actor Relations: A Case Study in KLG IT Department

Evelline Kristiani, Tubagus Ahmad Marzuqi, Dana Indra Sensuse, Sofian Lusa, Nadya Safitri, Damayanti Elisabeth

Abstract


IT department is often relied on as business activities enabler. To be able to do that task efficiently while also continuing to innovate, knowledge is necessary. KLG is one of the retail business players in Indonesia; currently their IT department is in effort to capture various types of important knowledge. Unfortunately, it experiences stagnation. What the IT department have now is a file repository, so where to start to implement a more comprehensive solution like Knowledge Management? To better understand the current pattern of communication influenced by its unique culture and structure of the organization, this research uses Social Network Analysis (SNA) one-mode network and bipartite graph. The visualization and analysis of the social network were performed using tools called Cytoscape. From total of 10 IT-side actor nodes and 5 business-side actor nodes, it was found connection value between actors. FA and PM get identical results due to being indistinguishable by other actors. FA/PM got the highest score followed by IT Ops & Support at betweenness (1.0993, 1.0369) and stress centrality (796, 698). At closeness centrality, Ops & Support (0.8750) took the lead, followed by FA/PM (0.7778) and developers (0.7778). In addition to the analysis of the actors’ relationships, potential knowledge contributors and actors’ interest in different types of knowledge are also identified. Further research will describe how knowledge management strategies are shaped based on these findings.

Keywords


social network analysis, one-mode network, bipartite network, knowledge management, project management

Full Text:

PDF

References


I. Becerra-Fernandez and R. Sabherwal, Knowledge Management Systems and Processes, Second Edi. Library of Congress Cataloging in Publication Data, 2015.

A. Barão, J. B. de Vasconcelos, Á. Rocha, and R. Pereira, "A knowledge management approach to capture organizational learning networks", Int. J. Inf. Manage., vol. 37, no. 6, pp. 735–740, 2017, doi: 10.1016/j.ijinfomgt.2017.07.013.

S. Abualoush, R. Masa’deh, K. Bataineh, and A. Alrowwad, ‘The role of knowledge management process and intellectual capital as intermediary variables between knowledge management infrastructure and organization performance’, Interdiscip. J. Information, Knowledge, Manag., vol. 13, pp. 279–309, 2018, doi: 10.28945/4088.

Y. Wang, V. K. Thangasamy, Z. Hou, R. L. K. Tiong, and L. Zhang, "Collaborative relationship discovery in BIM project delivery: A social network analysis approach", Autom. Constr., vol. 114, no. February, p. 103147, 2020, doi: 10.1016/j.autcon.2020.103147.

P. Xiang and T. Yuan, "A collaboration-driven mode for improving sustainable cooperation in smart industrial parks", Resour. Conserv. Recycl., vol. 141, no. March 2018, pp. 273–283, 2019, doi: 10.1016/j.resconrec.2018.10.037.

A. Rachman and R. M. Chandima Ratnayake, "Social Network Analysis in Lean Thinking: A Method for Improving Information Flow in Technical Integrity Management System Development", IEEE Int. Conf. Ind. Eng. Eng. Manag., vol. 2019-Decem, pp. 1293–1298, 2019, doi: 10.1109/IEEM.2018.8607433.

A. C. Issac and T. S. Thomas, "Whom to appease and whom to circumvent: analyzing knowledge sharing with social networks", Glob. Knowledge, Mem. Commun., vol. 69, no. 1–2, pp. 75–93, 2019, doi: 10.1108/GKMC-03-2019-0041.

A. Kasztler and K. H. Leitner, "An SNA/based approach for management control of intellectual capital", J. Intellect. Cap., vol. 10, no. 3, pp. 329–340, 2009, doi: 10.1108/14691930910977761.

P. Lawson, "Network Visualization." library.jhu.edu. https://guides.library.jhu.edu/datavisualization/network (accessed Nov. 30, 2021).

M. Chopra and C. Mahapatra, "Through Network Analysis Software Applications in Strategizing Higher", 2019, doi: 10.1007/978-981-13-0550-4.

P. Wethyavivorn and W. Teerajetgul, "Tacit knowledge capture in Thai design and consulting firms", J. Constr. Dev. Ctries., vol. 25, no. 1, pp. 45–62, 2020, doi: 10.21315/jcdc2020.25.1.3.

A. Kuznetsov, J. Dinwoodie, D. Gibbs, M. Sansom, and H. Knowles, "Knowledge capture to inform sustainable maritime operations", 2016, doi: 10.1108/IJOPM-10-2015-0657.

A. S. Herbst, "Capturing knowledge from lessons learned at the work package level in project engineering teams", J. Knowl. Manag., vol. 21, no. 4, pp. 765–778, 2017, doi: 10.1108/JKM-07-2016-0273.

B. Drake and B. Nadler, "Increasing Knowledge Capture of Space Instrumentation Using Systems Engineering Model Architecture", IEEE Aerosp. Conf. Proc., 2020, doi: 10.1109/AERO47225.2020.9172430.

J. T. Marchewka, "Information Technology Project Management: Providing Measurable Organizational Value, 5th Edition", Willey, 2015.

M. Valeri and R. Baggio, "Italian tourism intermediaries: a social network analysis exploration", Curr. Issues Tour., vol. 24, no. 9, pp. 1270–1283, 2021, doi: 10.1080/13683500.2020.1777950.

U. Can and B. Alatas, "A new direction in social network analysis: Online social network analysis problems and applications", Phys. A Stat. Mech. its Appl., vol. 535, p. 122372, 2019, doi: 10.1016/j.physa.2019.122372.

S. Yang, F. B. Keller, and L. Zheng, "Social Network Analysis: Methods and Examples", Soc. Netw. Anal. Methods Examples, 2020, doi: 10.4135/9781071802847.

Digital Promise, "Planning a Social Network Analysis", p. 29, 2018, [Online]. Available: https://digitalpromise.org/wp-content/uploads/2018/09/SNA-Toolkit.pdf.

D. L. Hansen, B. Shneiderman, M. A. Smith, and I. Himelboim, "Twitter: Information flows, influencers, and organic communities",

Anal. Soc. Media Networks with NodeXL, pp. 161–178, 2020, doi: 10.1016/b978-0-12-817756-3.00011-x.

D. L. Hansen, B. Shneiderman, M. A. Smith, and I. Himelboim, "Social network analysis: Measuring, mapping, and modeling collections of connections", Anal. Soc. Media Networks with NodeXL, pp. 31–51, 2020, doi: 10.1016/b978-0-12-817756-3.00003-0.

M. Krnc et al., "Eccentricity of Networks with Structural Constraints To cite this version : HAL Id : hal-01385481 Eccentricity of Networks with Structural Constraints ∗", pp. 0–18, 2018.

D. Easley and J. Kleinburg, "Chapter 3 Strong and Weak Ties", Networks, Crowds Mark. Reason. about a Highly Connect. World., pp. 47–84, 2010, [Online]. Available: http://www.cs.cornell.edu/home/kleinber/networks-book/.

Ulrik Brandes and Thomas Erlebach, Network Analysis. Methodological Foundations. 2005.

O. Lizardo, "Affiliations and Bipartite Graphs". http://olizardo.bol.ucla.edu/classes/soc-111/textbook/_book/8-1-affiliations-and-bipartite-graphs.html#affiliations-and-bipartite-graphs (accessed Jun. 06, 2021).

R. L. Breiger, "The duality of persons and groups", Soc. Forces, vol. 53, no. 2, pp. 181–190, 1974, doi: 10.1093/sf/53.2.181.

S. Aslan and M. Kaya, "Topic recommendation for authors as a link prediction problem", Futur. Gener. Comput. Syst., vol. 89, pp. 249–264, 2018, doi: 10.1016/j.future.2018.06.050.




DOI: http://dx.doi.org/10.33021/icsecc.v1i1.4162

Refbacks

  • There are currently no refbacks.



President University Press

Lembaga Riset dan Pengabdian Masyarakat

President University

Jalan Ki Hajar Dewantara, Mekarmukti, Bekasi

Jawa Barat, Indonesia 17530