A Group Based Fuzzy MCDM for Selecting Knowledge Portal System

Despite of many scholars and practitioners recognize the knowledge management implementation in an organizations but insufficient attention has been paid by researchers to select suitable knowledge portal system (KPS) selection. This study develops a Multi Criteria Decision making model based on the fuzzy VIKOR approach to help organizations in selecting KPS. The suitable portal is the critical influential factors on the success of knowledge management (KM) implementation in an organization.




References:
[1] Chang,T.H., Wang, T.H.,(2009). Using the fuzzy multi-criteria decision
making approach for measuring the possibility of successful knowledge
management. Information Sciences, 179,355-370.
[2] Hsieh,P.J.,Lin,B.,Lin,CH.,(2009). The construction and application of
knowledge navigator model (KNMTM): An evaluation of knowledge
management maturity. Expert Systems with Applications, 36, 4087-
4100.
[3] Lee, K.C., Lee, S., Kang, I.W., (2005). KPMI: measuring knowledge
management performance. Information and Management 42, 469-482.
[4] Zack, M. (1999) Managing codified knowledge. Sloan Management
Review, 40 (4), 45-58.
[5] Nonaka I., (1994). A dynamic theory of organization knowledge
creation. Organization Scinces 5 (1), pp.14-37.
[6] Marwick, A., D, (2001). Knowledge management technology. IBM
System Journal 40 (4), 814-830.
[7] Kim, Y.G., Yu S.H., Lee J.H., (2003).Knowledge strategy planning:
methodology and case. Expert System with Applications (24), 295-307.
[8] Earl, M., (2001).Knowledge management strategies: toward a
taxonomy. Journal of Management Information systems 18(1), 215-233.
[9] Choi, B., Poon, S., K., Davis, J., G., (2007).Effects of knowledge
management strategy on organizational performance: A
complementarily theory-based approach. Omega 36,235-251.
[10] White, M., 2000. Enterprise information portals. The Electronic Library
18 (5), 354-362.
[11] Kim, Y.J., Chaudhury, A., Raghav Rao, H., 2002. A knowledge
management perspective to evaluation of enterprise information portals.
Knowledge and Process Management 9 (2), 57-71.
[12] Hwang, C.L., Yoon, N., (1981). Multiple Attributes Decision Making
Methods And Application, Springer-Verlag, Berlin
[13] Kreng, V. B., Wu, C., 2007. Evaluation of knowledge portal
development tools using a fuzzy AHP approach: The case of Taiwanese
stone industry. Europian Journal of Operational Research 176, 1795-
1810.
[14] Chang, D., 1996. Applications of the extent analysis method on fuzzy
AHP. European Journal of Operational Research, Volume 95, Issue 3,
Pages 649-655
[15] Saremi, M., Mousavi,S. F., Sanayei, A., (2009). TQM consultant
selection in SME's with TOPSIS under fuzzy environment. Expert
Systems with Applications (36), 2742-2749
[16] Opricovic, S. (1998). Multi-criteria optimization of civil engineering
systems. Belgrade: Faculty of Civil Engineering.
[17] Opricovic, S., & Tzeng, G.-H. (2002). Multicriteria Planning of Post-
Earthquake Sustainable Reconstruction. Computer-Aided Civil and
Infrastructure Engineering, 17 (3), 211-220.
[18] Chu, M.-T., Shyu, J., Tzeng, G.-H., & Khosla, R. (2007). Comparison
among three analytical methods for knowledge communities groupdecision
analysis. Expert Systems with Applications, 33 (4), 1011-1024.
[19] Opricovic, S., & Tzeng, G.-H. (2004). Compromise solution by MCDM
methods:A comparative analysis of VIKOR and TOPSIS.
[20] Opricovic, S., & Tzeng, G.-H. (2007). Extended VIKOR method in
comparison with outranking methods.
[21] Yu, P. (1973). A class of solutions for group decision problems.
Management Science, 19 (8), 936-946.
[22] Zadeh, L. A. (1965). Fuzzy sets. Information Control , 8, 338-353.
[23] Bellman, RE., Zadeh, L.A., 1970. Decision-making in a fuzzy
environment. Management Science 17 (4), 141-146.
[24] Tong, R., & Bonissone, P. (1980). A linguistic approach to
decisionmaking with fuzzy sets. IEEE Transactions On Systems, Man,
Cybernetics SMC, 10 (11), 716-723.
[25] Bevilacqua, M., Ciarapica, F., & Giacchetta, G. (2006). A fuzzy-QFD
approach to supplier selection. Journal of Purchasing & Supply
Management, 14-27.
[26] Carlsson, C., & Fuller, R. (1996). Fuzzy multiple criteria decisionmaking:
Recent development. Fuzzy Sets and Systems , 78 (2), 139-153.
[27] Wang, T.-C., & Chang, T.-H. (2007). Application of TOPSIS in
evaluating initial training aircraft under a fuzzy environment. Expert
Systems with Applications , 33 (4), 870-880.
[28] de Boer, L., Labro, E., & Morlacchi, P. (2001). A review of methods
supporting supplier selection. European Journal of Purchasing & Supply
Management, 7, 75-89.
[29] Kaufmann, A., & Gupta, M. (1991). Introduction to Fuzzy Arithmetic:
Theory and Applications. New York: Van Nostrand Reinhold.
[30] Dubois, D., & Prade, H. (1980). Fuzzy Sets and Systems: Theory and
Applications. New York: Academic Press Inc.
[31] Zadeh, L. (1975). The concept of a linguistic variable and its application
to approximate reasoning. Information Sciences, 8, 199-249(I) 301-
357(II).
[32] Chena, C.-T., Lin, C.-T., & Huangb, S.-F. (2006). A fuzzy approach for
supplier evaluation and selection in supply chain management. Int. J.
Production Economics, 289-301.
[33] Hess, P., & siciliano, J. (1996). Management:responsibility for
performance. New York: McGraw-Hill.