Supplier Segmentation using Fuzzy Linguistic Preference Relations and Fuzzy Clustering
Автор: Pegah Sagheb Haghighi, Mahmoud Moradi, Maziar Salahi
Журнал: International Journal of Intelligent Systems and Applications(IJISA) @ijisa
Статья в выпуске: 5 vol.6, 2014 года.
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In an environment characterized by its competitiveness, managing and monitoring relationships with suppliers are of the essence. Supplier management includes supplier segmentation. Existing literature demonstrates that suppliers are mostly segmented by computing their aggregated scores, without taking each supplier’s criterion value into account. The principle aim of this paper is to propose a supplier segmentation method that compares each supplier’s criterion value with exactly the same criterion of other suppliers. The Fuzzy Linguistic Preference Relations (LinPreRa) based Analytic Hierarchy Process (AHP) is first used to find the weight of each criterion. Then, Fuzzy c-means algorithm is employed to cluster suppliers based on their membership degrees. The obtained results show that the proposed method enhances the quality of the previous findings.
Supply Chain Management (SCM), Supplier Segmentation, Fuzzy Set, Fuzzy Linguistic Preference Relations, Fuzzy C-Means
Короткий адрес: https://sciup.org/15010560
IDR: 15010560
Список литературы Supplier Segmentation using Fuzzy Linguistic Preference Relations and Fuzzy Clustering
- P. Berger, A. Gerstenfeld, A. Z. Zeng, How many suppliers are best? A decision-analysis approach. Omega, 2004, 32(1), pp. 9-15.
- J. Rezaei, R. Ortt, Supplier segmentation using fuzzy logic. Industrial Marketing Management, 2013, 42(4), pp. 507-517.
- A. S.Carr, J. N. Pearson, Strategically managed buyer-supplier relationship and performance outcomes. Journal of Operations Management, 1999, 17(5), pp. 497-519.
- M. G. Day, M. Magnan, M. Moeller, Evaluating the bases of supplier segmentation: A review and taxonomy. Industrial Marketing Management, 2010, 39(4), pp. 625–639.
- S. Khaleie, M. Fasanghari, E. Tavassoli, Supplier selection using a novel intuitionist fuzzy clustering approach. Applied Soft Computing, 2012, 12(6), pp. 1741–1754.
- J. Rezaei, R. Ortt, A multi-variable approach to supplier segmentation. International Journal of Production Research, 2012, 50(16), pp. 4593-4611.
- W.Ho, X. Xu, P. K. Dey, Multi-criteria decision making approaches for supplier evaluation and selection: A literature review. European Journal of Operational Research, 2010, 202(1), pp. 16–24.
- L. De Boer, E. Labro, P. Morlacchi, A review of methods supporting supplier selection. European Journal of Purchasing and Supply Management, 2011, 7(2), pp. 75–89.
- J. Rezaei, R. Ortt, Multi-criteria supplier segmentation using fuzzy preference relations based AHP. European Journal of Operational Research, 2013, 225(1), pp. 75-84.
- A. Parasuraman, Vendor segmentation: an additional level of market segmentation. Industrial Marketing Management, 1980, 9(1), pp. 59–62.
- P. Kraljic, Purchasing must become supply management. Harvard Business Review, 1983, pp. 109–117.
- A. Kaufman, C. H. Wood, G. Theyel, Collaboration and technology linkages: A strategic supplier typology. Strategic Management Journal, 2000, 21(6), pp. 649–663.
- G. Svensson, Supplier segmentation in the automotive industry: A dyadic approach of a managerial model. International Journal of Physical Distribution and Logistics Management, 2004, 34(1), pp. 12–38.
- J. Hallikas, K. Puumalainen, T. Vesterinen, V. M. Virolainen, Risk-based classification of supplier relationships. Journal of Purchasing and Supply Management, 2005, 11(2–3), pp. 72–82.
- L.A. Zadeh, Fuzzy Sets. Information and Control,1965, 8(3), pp. 338–353.
- P.J.M. Laarhoven, W. Pedrycz, A fuzzy extension of Saaty’s priority theory. Fuzzy Sets andSystems, 1983, 11(1-3), pp. 229–241.
- T. C. Wang, Y. H. Chen, Applying fuzzy linguistic preference relations to the improvement of consistency of fuzzy AHP. Information Sciences, 2008, 178(19), pp. 3755–3765.
- J. C. Dunn, A fuzzy relative of the ISODATA processand its use in detecting compact, Well-
- separated cluster. Journal of Cybernetics, 1974, 3(3), pp. 32-57.
- J. C. Bezdek, Pattern recognition with fuzzy objective function algorithm. MA, USA: Kluwer Academic Publishers, 1981.
- G. A. Keskin, S. Ilhan, C. Ozkan, The fuzzy ART algorithm: A categorization method for supplier evaluation and selection. Expert Systems with Applications, 2010, 37(2), pp. 1235-1240.
