Developing a Virtual Group Decision Support System Based on Fuzzy Hybrid MCDM Approach
Автор: Bahram Izadi, Saeedeh Ketabi
Журнал: International Journal of Information Technology and Computer Science(IJITCS) @ijitcs
Статья в выпуске: 2 Vol. 5, 2013 года.
Бесплатный доступ
Organizational decisions involve with unusually vague and conflicting criteria. This controversy increases empirical uncertainties, disputes, and the resulting consequences of these decisions. One possible method in subduing this problem is to apply quantitative approaches to provide a transparent process for resolute conclusions which enables decision makers to formulate accurate and decisive on time decisions. Although numerous methods are presented in the literature, the majority of them aim to develop theoretical models. However, this article aims to develop and implement an integrated fuzzy virtual MCDM model based on fuzzy AHP and fuzzy TOPSIS as a decision support system (DDS). Preventing disadvantageous face-to-face decision-making by achieving positive benefit from virtual decision making causes the proposed DDS to be suitable for making crucial decisions such as supplier selection, employee selection, employee appraisal, R&D project selection, etc. The proposed DDS has been implemented in an optical company in Iran.
Virtual Group Decision Making, Decision Support System, MCDM
Короткий адрес: https://sciup.org/15011809
IDR: 15011809
Список литературы Developing a Virtual Group Decision Support System Based on Fuzzy Hybrid MCDM Approach
- P., Tsvetinov and L. Mikhailov, “Reasoning under uncertainty during pre-negotiations using a fuzzy AHP”, 7th International Conference on Business Information Systems, Poznań, Poland, 21-23 April 2004
- E. Forman and M.A Selly, Decision By Objectives, How to convince others that you are right, George Washington University, 2001, pp. 1
- A. Thatcher and A. De La Cour, “Small group decision-making in face-to-face and computer-mediated environments: the role of personality”, Behaviour and Information Technology, vol. 22, no.3, pp. 203-218, 2003
- V. Chichernea1, “The decision support systems for the information society (i-Society)”, Journal of Information Systems and Operations Management, vol. 4, no. 2, pp. 58-92, 2010
- J. Fjermestad, “Virtual group strategic decision making using structured conflict and consensus approaches”, International Journal of e-Collaboration vol. 1, no. 1, pp. 43-61, 2005
- R.E. Bellman and L. Zadeh,, “Decision making in a fuzzy environment”, Management Science, vol. 17, no. 4, 1970
- Yi W. Hung, T. Gwo-Hshiung and C. Yi Hsuan, “A fuzzy MCDM approach for evaluating banking performance based on Balanced Scorecard, Expert Systems with Applications vol.36, pp. 10135–10147, 2009
- L.A. Zadeh, “Fuzzy sets”, Information and Control, no.8, pp. 338–353, 1956
- T.Y. Hsieh, S.T. Lu and G.H Tzeng, “Fuzzy MCDM approach for planning and design tenders selection in public office buildings”, International Journal of Project Management, vol. 22, no.7, pp. 573–584, 2004
- T. Saaty, The analytic hierarchy process, McGraw-Hill, New York., 1980
- C. H. Cheng, K.L. Yang and C.L. Hwang, “Evaluating attack helicopters by AHP based on linguistic variable weight”, European Journal of Operational Research, no. 116, pp. 423-435, 1999
- C. Kahraman, U. Cebeci and Z. Ulukan, “Multi criteria supplier selection using fuzzy AHP”, Logistic Information Management, vol. 16, no. 6, pp. 382–394, 2003
- H. M. Hsu, and C. T. Chen, “Aggregation of fuzzy opinions under group decision making”, Fuzzy Sets and System, no. 79, pp. 279–285, 1996
- R .L. Keeney and C.W. Kirkwood, “Group decision making Using Cardinal Social Welfare Functions, Management Science 22 (4), 430–437, 1975
- D. C. Kingsley and T. C. Brown, “Preference uncertainty, preference learning, and paired comparison experiments”, Land Economics, vol. 86, no. 3, pp. 530-544, August 2010
- J. Sheth, “A model of industrial buyer behavior”, Journal of Marketing, no. 37, pp. 50-56, 1973
- A.F. Guneri, A..Yucel and G. Ayyildiz, “An integrated fuzzy - lp approach for a supplier selection problem in supply chain management”, Expert Systems with Applications, no. 36, pp. 9223–9228, 2009
- S.H. Tsaur, T.Y. Chang and C.H. Yen, “The evaluation of airline service quality by fuzzy MCDM”, Tourism Management, no. 23, pp. 107-115, 2002
- CT. Chen, CT. Lin and SF. Huang, “A fuzzy approach for supplier evaluation and selection in supply chain management”, International Journal of Production Economics, vol. 102, pp. 289–301, 2006
