SUPPLIER SELECTION WITH TOPSIS METHOD IN FUZZY ENVIRONMENT: AN APPLICATION IN BANKING SECTOR

Year 2015, Volume: 33 Issue: 3, 351 - 362, 01.09.2015

Berk Ayvaz Eda Boltürk Sibkat Kaçtıoğlu

Abstract

Evaluation and selection of the appropriate supplier is complicated and time consuming decision making process for companies. Selection of inappropriate supplier leds to higher cost and it influences negatively business process of companies in competitive environment. In this paper, fuzzy-TOPSIS method, considering combination of quantitative and qualitative evaluation criteria, is presented to select appropriate supplier under uncertain environment. The proposed model is applied to the electronic signature purchasing process of a firm that operates in banking sector in Turkey. Quality, purchasing costs, additional costs (maintenance, training, and update costs etc.), security level, compatibility with existing IT infrastructure, after-sales support, and technical competence are selected for supplier selection process in accordance with a detailed literature review and experts’ opinions.

Keywords

Supply chain management, fuzzy TOPSIS, supplier selection

References

• [1] J.Sarkis, S. Talluri. A model for strategic supplier selection. Journal of Supply Chain Management, 38, 1: 18–28, 2002.
• [2] S.H. Huang, H. Keskar. Comprehensive and Configurable Metrics for Supplier Selection. International Journal of Production Economics, 105, 510-52, 2007.
• [3] G.W. Dickson. An Analysis of Vendor Selection Systems and Decisions. Journal of Purchasing, 2, 5-17,1966.
• [4] S.H. Huang, H. Keskar. Comprehensive and Configurable Metrics for Supplier Selection. International Journal of Production Economics, 105, 510-52, 2007.
• [5] C.A. Weber, J.R. Current, W.C. Benton. Vendor Selection Criteria and Methods. European Journal of Operational Research, 50, 2–18, 1991.
• [6] S.E. Fawcet, L.L. Stanley. S.R. Smith, Developing A Logistics Capability to Improve the Performance of International Operations. Journal of Business Logistic, 18 (2), 101–127, 1997.
• [7] S.H. Ghodsypour, C. O’Brien. A Decision Support System for Supplier Selection using an Integrated Analytic Hierarchy Process and Linear Programming. International Journal of Production Economics, 56- 57,199-212, 1998.
• [8] D. Çelebi, D. Bayraktar. An Integrated Neural Network and Data Envelopment Analysis for Supplier Evaluation Under Incomplete Information. Expert Systems with Applications, 35, 1698–1710, 2008.
• [9] A.S. Jadhav, R.M. Sonar. Framework for evaluation and selection of the software packages: A hybrid knowledge based system approach. The Journal of Systems and Software, 84, 1394–1407, 2011.
• [10] B. Baki, K. Çakar. Determining the ERP package-selecting criteria: the case of Turkish manufacturing companies. Business Process Management Journal, 11 (1), 75–86, 2005.
• [11] J. Otamendi, J.M. Pastor, A. Garcia. Selection of the simulation software for the managementbof the operations at an international airport. Simulation Modelling Practice and Theory, 16, 1103–1112, 2008.
• [12] C.T. Lin, C.B. Chen, Y.C. Ting. An ERP model for supplier selection in electronics industry. Expert Systems with Applications, 38, 1760–1765, 2011.
• [13] C.C. Wei, C.F. Chien, M.J.J. Wang. An AHP based approach to ERP system selection. International Journal of Production Economics, 96, 47–62, 2005.
• [14] E.E. Karsak, C.O. Özogul. An integrated decision making approach for ERP system selection. Expert Systems with Applications, 36(1),660-667,2009.
• [15] Liang, C., & Li, Q. Enterprise information system project selection with regard to BOCR. International Journal of Project Management, 26(8), 810-820, 2008.
• [16] H.R.Yazgan, S. Boran, K. Goztepe. An ERP software selection process with using artificial neural network based on analytic network process approach. Expert Systems with Applications, 36, 9214–9222, 2009
• [17] T. Gürbüz, S. E. Alptekin, G. I. Alptekin. A hybrid MCDM methodology for ERP selection problem with interacting criteria. Decision Support System, 54, 206–214, 2012.
• [18] H. S. Kilic, S. Zaim, D. Delen. Selecting The Best ERP system for SMEs using a combination of ANP and PROMETHEE methods. Expert Systems with Applications, 42, 2343–2352, 2015.
• [19] E. Öz ve Ö.F. Baykoç. Tedarikçi Seçimi Problemine Karar Teorisi Destekli Uzman Sistem Yaklaşımı. Gazi Üniv. Müh. Mim. Fak. Der, 19(3), 275-286, 2004.
• [20] B. Gökalp ve B. Soylu. Tedarikçinin Süreçlerini İyileştirme Amaçlı Tedarikçi Seçim Problemi. Endüstri Mühendisliği Dergisi YA/EM 2010 Özel Sayısı, 23(1),4-15, 2010.
• [21] D. Çelebi, D. Bayraktar. An Integrated Neural Network and Data Envelopment Analysis for Supplier Evaluation Under Incomplete Information. Expert Systems with Applications, 35, 1698–1710, 2008.
• [22] K.L. Choy, W.B. Lee, V. Lo. Design of an Intelligent Supplier Relationship Management System: A Hybrid Case based Neural Network Approach. Expert Systems with Applications, 24, 225–237, 2003.
• [23] D. Bayraktar, F. Çebi, H.H. Turan, A Prototype Expert System Approach for Supplier Evaluation and Selection Process. Proceedings of the 34th International Conference on Computers & Industrial Engineering [CD-ROM],2004.
• [24] S. Soner ve S. Önüt. Çok Kriterli Tedarikçi Seçimi: Bir ELECTRE-AHP Uygulaması. Sigma Mühendislik ve Fen Bilimleri Dergisi, 24:4, 110-120, 2006.
• [25] S.H. Hashemi, A. Karimi, M. Tavana. An integrated green supplier selection approach with analytic network process and improved Grey relational analysis. International Journal of Production Economics, 159:178-191, 2015.
• [26] A. Sanayei, S.F. Mousavi, A. Yazdankhah. Group decision making process for supplier selection with VIKOR under fuzzy environment. Expert Systems with Applications, 37, 24–30, 2010.
• [27] K. Shaw, R. Shankar, S. S. Yadav, L.S. Thakur. Supplier selection using fuzzy AHP and fuzzy multi- objective linear programming for developing low carbon supply chain. Expert Systems with Applications, 39, 8182–8192, 2012. [28] G. Büyüközkan ve G. Çiftçi. A novel fuzzy multi-criteria decision framework for sustainable supplier selection with incomplete information. Computers in Industry, 62, 164-174, 2011.
• [29] D. Dalalah, M. Hayajneh, F. Batieha. A fuzzy multi-criteria decision making model for supplier selection. Expert Systems with Applications. 38, 8384–8391, 2011. [30] S. Önüt, S.S. Kara, E. Isık. Long term supplier selection using a combined fuzzy MCDM approach: A case study for a telecommunication company. Expert Systems with Applications, 36(2), 3887–3895, 2009.
• [31] F.E. Boran, S. Genç, M. Kurt, D. Akay. A multi-criteria intuitionistic fuzzy group decision making for supplier selection with TOPSIS method. Expert Systems with Applications, 36, 11363–11368, 2009.
• [32] J.W. Wang, C.H. Cheng, H. Kun-Cheng. Fuzzy hierarchical TOPSIS for supplier selection. Applied Soft Computing, 9, 377–386, 2009.
• [33] J. Roshandela, S.S. Miri-Nargesib, L. Hatami-Shirkouhic. Evaluating and selecting the supplier in detergent production industry using hierarchical fuzzy TOPSIS. Applied Mathematical Modelling, 37(24), 10170–10181, 2013.
• [34] F.R.L. Junior, L. Osiro, L.C.R. Carpinetti. A comparison between Fuzzy AHP and Fuzzy TOPSIS methods to supplier selection. Applied Soft Computing, 21, 194-209, 2014.
• [35] D. Kannan, A.B.L.D.S. Jabbour, C.J.C. Jabbour. Selecting green suppliers based on GSCM practices: Using fuzzy TOPSIS applied to a Brazilian electronics company. European Journ al of Operational Research, 233, 432–447, 2014.
• [36] G. Akyüz. Bulanık VIKOR Yöntemi İle Tedarikçi Seçimi. Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 26(1),197-215, 2012.
• [37] R. Rajesh ve V. Ravi. Supplier selection in resilient supply chains: a grey relational analysis approach. Journal of Cleaner Production, 86, 343-359, 2015.
• [38] M. Zeydan, C. Çolpan, C. Çobanoğlu. A combined methodology for supplier selection and performance evaluation. Expert Systems with Applications, 38, 2741–2751, 2011.
• [39] F. Arikan. A fuzzy solution approach for multi objective supplier selection. Expert Systems with Applications. 40, 947–952, 2013.
• [40] F. R. L. Junior, L. Osiro, L.C. R.Carpinetti. A comparison between Fuzzy AHP and Fuzzy TOPSIS methods to supplier selection. Applied Soft Computing, 21, 194–209, 2014.
• [41] A. K. Kar. A hybrid group decision support system for supplier selection using analytic hierarchy process, fuzzy set theory and neural network. Journal of Computational Science, 6, 23–33, 2015.
• [42] H.S. Kılıç, S. Zaim, D. Delen. Development of a hybrid methodology for ERP system selection:The case of Turkish Airlines. Decision Support Systems, 66, 82-92, 2014.
• [43] A. Özdağoğlu. Çok Ölçütlü Karar Verme Yöntemleri ve Uygulama Örnekleri. 1.Baskı, MMO, İzmir, 2011.
• [44] T. Yang, C.C. Hung. Multiple-attribute decision making methods for plant layout design problem. Robotics and Computer-Integrated Manufacturing, 23, 126-137, 2007.
• [45] M. Dağdeviren, S. Yavuz, N. Kılınç, Weapon selection using the AHP and TOPSIS methods under fuzzy environment, Expert Systems with Applications, 36, 8143–8151, 2009.
• [46] C.T. Chen. Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy Sets Syst, 114, 1–9, 2000.
• [47] C.T. Chen, C.T. Lin, S.F. Huang. A fuzzy approach for supplier evaluation and selection in supply chain management. International Journal of Production Economics, 102(2), 289–301, 2006.