Forecasting the probability of successful knowledge management by consistent fuzzy preference relations

This paper presents an analytic hierarchy prediction model based on the consistent fuzzy preference relations to help the organizations become aware of the essential factors affecting the success of Knowledge Management (KM) implementation, forecasting the possibility of successful KM project, as well as identifying the actions necessary before initiating KM. Pairwise comparisons are utilized to obtain the priority weights of influential factors and the ratings of two possible outcome (success and failure). The subjectivity and vagueness within the prediction process are dealt with using linguistic variables quantified in an interval scale [0,1]. By multiplying the weights of influential factors and the ratings of possible outcome, predicted success/failure values are determined to enable organizations to decide whether to initiate knowledge management, inhibit adoption or take remedial actions to enhance the possibility of successful KM project. This proposed approach is demonstrated with a real case study involving seven major influential factors assessed by eleven evaluators solicited from a semiconductor engineering incorporation located in Taiwan.

[1]  Francisco Herrera,et al.  Multiperson decision-making based on multiplicative preference relations , 2001, Eur. J. Oper. Res..

[2]  Francisco Herrera,et al.  Integrating three representation models in fuzzy multipurpose decision making based on fuzzy preference relations , 1998, Fuzzy Sets Syst..

[3]  Anne P. Massey,et al.  A performance environment perspective of knowledge management , 2003, 36th Annual Hawaii International Conference on System Sciences, 2003. Proceedings of the.

[4]  T. Tanino.  Fuzzy preference orderings in group decision making , 1984 .

[5]  Zbigniew Switalski,et al.  General transitivity conditions for fuzzy reciprocal preference matrices , 2003, Fuzzy Sets Syst..

[6]  Karen Ayas.  Professional project management: a shift towards learning and a knowledge creating structure , 1996 .

[7]  Francisco Herrera,et al.  Linguistic decision analysis: steps for solving decision problems under linguistic information , 2000, Fuzzy Sets Syst..

[8]  Francisco Herrera,et al.  Some issues on consistency of fuzzy preference relations , 2004, Eur. J. Oper. Res..

[9]  J. Spender.  Organizational knowledge, learning and memory: three concepts in search of a theory , 1996 .

[10]  Malcolm Peltu,et al.  Knowledge management practices for innovation: an audit tool for improvement , 2000, Int. J. Technol. Manag..

[11]  D. Teece.  Capturing Value from Knowledge Assets: The New Economy, Markets for Know-How, and Intangible Assets , 1998 .

[12]  J. Liebowitz,et al.  Does measuring knowledge make “cents”? , 1999 .

[13]  William David Salisbury,et al.  Understanding the influence of organizational change strategies on information technology and knowledge management strategies , 2001, Decis. Support Syst..

[14]  Sue Newell,et al.  Limits of IT-driven knowledge management initiatives for interactive innovation processes: towards a community-based approach , 2000, Proceedings of the 33rd Annual Hawaii International Conference on System Sciences.

[15]  Zbigniew Switalski,et al.  Transitivity of fuzzy preference relations - an empirical study , 2001, Fuzzy Sets Syst..

[16]  C. J. Hearne.  Non-conventional Preference Relations in Decision Making , 1989 .

[17]  T. Davenport,et al.  Data to Knowledge to Results: Building an Analytic Capability , 2001 .

[18]  F. Herrera,et al.  A linguistic decision process in group decision making , 1996 .

[19]  Zeshui Xu,et al.  Incomplete linguistic preference relations and their fusion , 2006, Inf. Fusion.

[20]  Francisco Herrera,et al.  Theory and Methodology Choice functions and mechanisms for linguistic preference relations , 2000 .

[21]  C. Anumba,et al.  A CLEVER approach to selecting a knowledge management strategy , 2002 .

[22]  T. Davenport,et al.  Improving Knowledge Work Processes , 1996 .

[23]  D. Leonard,et al.  The Role of Tacit Knowledge in Group Innovation , 1998 .

[24]  Francisco Herrera,et al.  A model based on linguistic 2-tuples for dealing with multigranular hierarchical linguistic contexts in multi-expert decision-making , 2001, IEEE Trans. Syst. Man Cybern. Part B.

[25]  Francisco Herrera,et al.  A note on the reciprocity in the aggregation of fuzzy preference relations using OWA operators , 2003, Fuzzy Sets Syst..

[26]  T. A. Stewart.  Intellectual Capital: The New Wealth of Organizations , 1997 .

[27]  Francisco Herrera,et al.  A model of consensus in group decision making under linguistic assessments , 1996, Fuzzy Sets Syst..

[28]  Francisco Herrera,et al.  A rational consensus model in group decision making using linguistic assessments , 1997, Fuzzy Sets Syst..

[29]  Lyle Brenner,et al.  A random support model of the calibration of subjective probabilities , 2003 .

[30]  Kun Chang Lee,et al.  Erratum to "KMPI: Measuring knowledge management performance" [Information & Management 42 (2005) 469-482] , 2005, Inf. Manag..

[31]  Francisco Herrera,et al.  Integrating multiplicative preference relations in a multipurpose decision-making model based on fuzzy preference relations , 2001, Fuzzy Sets Syst..

[32]  Jifeng Mu,et al.  Establishing a Knowledge Management Programme for Competitive Advantage in an Enterprise , 2002 .

[33]  I. Nonaka.  A Dynamic Theory of Organizational Knowledge Creation , 1994 .

[34]  Tetsuzo Tanino,et al.  Fuzzy Preference Relations in Group Decision Making , 1988 .

[35]  Francisco Herrera,et al.  A Sequential Selection Process in Group Decision Making with a Linguistic Assessment Approach , 1995, Inf. Sci..

[36]  A. Raveh,et al.  National and corporate cultural fit in mergers/acquisition: an exploratory study , 1996 .

[37]  Jinjoo Lee,et al.  Effective team processes for technology internalisation with special emphasis on knowledge management: successful late starter, Samsung case , 2004, Int. J. Technol. Manag..

[38]  Marinus J C Eijkemans,et al.  A nomogram to predict the probability of live birth after clomiphene citrate induction of ovulation in normogonadotropic oligoamenorrheic infertility. , 2002, Fertility and sterility.

[39]  Ray Hackney,et al.  Evolutionary knowledge management: a case of system development within the manufacturing industry , 2005, Int. J. Technol. Manag..

[40]  Jesualdo Tomás Fernández-Breis,et al.  A cooperative tool for facilitating knowledge management , 2000 .

[41]  James T. Walz.  The Wealth of Knowledge: Intellectual Capital and the Twenty‐First Century Organization , 2005 .

[42]  T. L. Saaty.  Exploring the interface between hierarchies, multiple objectives and fuzzy sets , 1978 .

[43]  Shu-Hsien Liao,et al.  Knowledge management technologies and applications - literature review from 1995 to 2002 , 2003, Expert Syst. Appl..

[44]  V. Rajaraman,et al.  A probabilistic method for calculating hit ratios in direct mapped caches , 1996 .

[45]  Susan M. Brookhart,et al.  Enhancing the possibility of success by measuring the probability of failure in an educational program , 1997 .

[46]  T. Saaty,et al.  The Analytic Hierarchy Process , 1985 .

[47]  R. Schroeder,et al.  The crucial interrelationship between manufacturing strategy and organizational culture , 1995 .