Knowledge Management Criteria among Malaysian Organizations: An ANOVA Approach
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.
[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.
[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.
@article{"International Journal of Business, Human and Social Sciences:58495", author = "Reza Sigari Tabrizi and Yeap Peik Foong and Nazli Ebrahimi", title = "Knowledge Management Criteria among Malaysian Organizations: An ANOVA Approach", 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", volume = "4", number = "12", pages = "2259-5", }