Knowledge Management Criteria among Malaysian Organizations: An ANOVA Approach
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Knowledge Management Criteria among Malaysian Organizations: An ANOVA Approach

Authors: Reza Sigari Tabrizi, Yeap Peik Foong, Nazli Ebrahimi

Abstract:

The Knowledge Management (KM) Criteria is an essential foundation to evaluate KM outcomes. Different sets of criteria were developed and tailored by many researchers to determine the results of KM initiatives. However, literature review has emphasized on incomplete set of criteria for evaluating KM outcomes. Hence, this paper tried to address the problem of determining the criteria for measuring knowledge management outcomes among different types of Malaysian organizations. Successively, this paper was assumed to develop widely accepted criteria to measure success of knowledge management efforts for Malaysian organizations. Our analysis approach was based on the ANOVA procedure to compare a set of criteria among different types of organizations. This set of criteria was exploited from literature review. It is hoped that this study provides a better picture for different types of Malaysian organizations to establish a comprehensive set of criteria due to measure results of KM programs.

Keywords: KM Criteria, Knowledge Management, KMOutcomes, ANOVA

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1072748

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References:


[1] T. Davenport and L. Prusak, Working Knowledge: How Organisations Manage What They Know. Boston, Massachusetts : Harvard Business School Press., 1998.
[2] Mark E. Van Buren, "A Yardstick for Knowledge Management". 1999, Training & Development, pp. 71-78.
[3] R. LUBIT, "Tacit Knowledge and Knowledge Management: The Keys to Sustainable Competitive Advantage". , 2001, Organizational Dynamics, Vol. 29, pp. 164-178.
[4] A. Macintosh, "Position paper on knowledge asset management". Artificial Intelligence Applications Institute.
[Online] 1998. WWW: http://www.aiai.ed.ac.uk/nalm/kam.html..
[5] L. T. Ndlela and A. S. A du Toit, "Establishing a knowledge management programme for competitive advantage in an enterprise". 2001, International Journal of Information Management, Vol. 21, pp. 151-165.
[6] Chong Siong . Choy and Wong Kuan. Yew and Binshan Lin, "Criteria for measuring KM performance outcomes in organisations". , 2006, Industrial Management & Data Systems, Vol. 106, pp. 917-936.
[7] D. Longbottom and P. Chourides, "Knowledge management: a survey of leading UK companies". Versailles France : s.n., 2001. Proceedings of the Second MAAQE International Conference. pp. 113-26.
[8] Vittal. Anantatmula, and Shivraj Kanungo, "Establishing and Structuring Criteria for Measuring Knowledge Management Efforts". 2005. 38th Hawaii International Conference on System Sciences. pp. 1- 11.
[9] Chong Siong . Choy, "Criteria for measuring KM performance outcomes in organisations". Kuala Lumpur : s.n., 2006. Knowledge Management Conference & Exhibition (KMICE). pp. pp. 123-131.
[10] Vittal S. Anantatmula, "Outcomes of Knowledge Management Initiatives". 2005, International Journal of Knowledge Management, pp. 50-67.
[11] E. Turban and J.E. Aronson, "Decision support systems and intelligent systems". 6th edition. s.l. : Prentice Hall, 2001.
[12] R. Austin and P. Larkey ,"The future of performance measurement: Measuring knowledge work".
[book auth.] In A. Neely (Ed.). Business Performance Measurement. Theory and Practice. s.l. : Cambridge University Press, 2002.
[13] J. Ahn, and S., Chang "Valuation of knowledge: A business performance-oriented methodology" . Hawaii : HICSS35, IEEE Computer Society. , 2002. The 35th Hawaii International Conference on System Sciences, .
[14] A. Fairchild, "Knowledge manage metrics via a balanced scorecard methodology". Hawaii : s.n., 2002. 35th Hawaii International Conference on System Sciences.
[15] P. Royston, "Approximating the Shapiro-Wilk W-Test for nonnormality". 20, 1992, Statistics and Computing, pp. 11-119.