Knowledge Management Implementation: A Predictive Model Using an Analytical Hierarchical Process

被引：14
作者：
Anand A. [1 ]
Kant R. [2 ]
Patel D.P. [2 ]
Singh M.D. [1 ]
机构：
[1] Department of Mechanical Engineering, Motilal Nehru National Institute of Technology, Allahabad
[2] Department of Mechanical Engineering, S. V. National Institute of Technology, Surat
来源：
Journal of the Knowledge Economy | 2015年 / 6卷 / 1期
关键词：
Analytical hierarchical process; KME; Knowledge management; Priority weights;
D O I：
10.1007/s13132-012-0110-y
中图分类号：
学科分类号：
摘要：
The aim of this paper is to understand knowledge management enablers (KMEs) and to identify priority weights to evaluate the strength of the corresponding factors present before knowledge management (KM) implementation. It uses analytic hierarchy process (AHP) methodology to prioritize KMEs that support the KM implementation in organizations. Further, a questionnaire-based survey was also conducted to rank the KMEs. These KMEs were selected from literature reviews and expert discussion. The AHP method, which has the ability to structure complex, multiperson, multiattribute, and multiperiod problem hierarchically, has been used. Pairwise comparisons of KMEs (usually, alternatives and attributes) can be established using a scale indicating the strength with which one KME dominates another with respect to a higher level KME. This scaling process can then be translated into priority weights. The AHP can be a useful guide in the decision-making process of KM implementation. It has been observed that KME11 has high priority weights. © 2012, Springer Science+Business Media New York.
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页码：48 / 71
页数：23
相关论文
共 73 条
[1]  
Bair J., Knowledge management: the era of share ideas, Forbes, 1, 1, (1997)
[2]  
Baker M., Baker M., Thorne J., Dutnell M., Leveraging human capital, J Knowl Manag, 1, 1, pp. 63-74, (1997)
[3]  
Beamish N.G., Armistead C.G., Selected debate from the arena of knowledge management: new endorsements for established organizational practices, Int J Manag Rev, 3, 2, pp. 101-111, (2001)
[4]  
Beckman T., A methodology for knowledge management, Proceedings of the IASTED International Conference on Artificial Intelligence and Soft Computing, ASC ‘97, pp. 29-32, (1997)
[5]  
Beckman T.J., The current state of knowledge management, Knowledge management handbook, (1999)
[6]  
Beynon M., DS/AHP method: a mathematical analysis, including an understanding of uncertainty, Eur J Oper Res, 140, pp. 148-164, (2002)
[7]  
Bhatt G.D., Knowledge management in organizations, J Knowl Manag, 5, 1, pp. 68-75, (2001)
[8]  
Bierly P.E., Kessler E.H., Christensen E.W., Organizational learning, knowledge and wisdom’, J Organ Chang Manag, 13, 6, pp. 595-618, (2000)
[9]  
Blake P., The knowledge management expansion’, Inf Today, 15, 1, pp. 12-13, (1998)
[10]  
Bohn R.E., Measuring and managing technological knowledge, Sloan Manag Rev, 26, 1, pp. 61-73, (1994)
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