A Combined Fuzzy Decision Making Approach to Supply Chain Risk Assessment
Many firms implemented various initiatives such as outsourced manufacturing which could make a supply chain (SC) more vulnerable to various types of disruptions. So managing risk has become a critical component of SC management. Different types of SC vulnerability management methodologies have been proposed for managing SC risk, most offer only point-based solutions that deal with a limited set of risks. This research aims to reinforce SC risk management by proposing an integrated approach. SC risks are identified and a risk index classification structure is created. Then we develop a SC risk assessment approach based on the analytic network process (ANP) and the VIKOR methods under the fuzzy environment where the vagueness and subjectivity are handled with linguistic terms parameterized by triangular fuzzy numbers. By using FANP, risks weights are calculated and then inserted to the FVIKOR to rank the SC members and find the most risky partner.
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 Barry J (2004) Supply chain risk in an uncertain global supply chain environment. International Journal of Physical Distribution & Logistics Management. 34/9:695-697
 Bayazita, O., & Karpak, B. (2007). An analytical network processbased framework for successful total quality management (TQM): An assessment of Turkish manufacturing industry readiness. International Journal of Production Economics, 105(1), 79-96.
 Bellman, R. E., & Zadeh, L. A. (1970). Decision-making in a fuzzy environment. Management Science, 17(4), 141-164.
 Blackhurst, J. & Craighead, C. & Elkins, D. & Handfield, R., (2005). An empirically derived agenda of critical research issues for managing supply-chain disruptions. International Journal of Production Research 43 (19), 4067-4081.
 Buyukozkan, G. & Ruan, D. (2008), Evaluation of software development projects using a fuzzy multi-criteria decision approach, Mathematics and Computers in Simulation 77, 464-475.
 Chen, C. T. & Lin, C. T. & Huang, S. F. (2006). A fuzzy approach for supplier evaluation and selection in supply chain management. International Journal of Production Economics, 102(2), 289-301.
 Chen, S. J. & Hwang, C. L. & Hwang, F. P. (1992). Fuzzy multiple attribute decision making. Lecture Notes in Economics and Mathematical System, 375.
 Chen, L. Y. & Wang, T. C. (2008). Optimizing partners- choice in IS/IT outsourcing projects: The strategic decision of fuzzy VIKOR, Int. J. Production Economics.
 Chiclana, F. & Herrera, F. & Herrera-Viedman, E. (1998) Integrating three representation models in fuzzy multipurpose decision making based on fuzzy preference relations, Fuzzy Sets Syst. 97, 33-48.
 Chiou, H. K., & Tzeng, G. H. (2002). Fuzzy multiple-criteria decisionmaking approach for industrial green engineering. Environment Management, 30(6), 816-830.
 Chiou, H. K. & Tzeng, G. H., & Cheng, D. C. (2005). Evaluating sustainable fishing development strategies using fuzzy MCDM approach. Omega, 33(3), 223-234.
 Chopra S. & Sodhi M. (2004) Managing Risk to Avoid Supply Chain Breakdown. MIT Sloan Management Review 46/1:53-61
 Chung, S. H. & Lee, A. H. & Pearn, W. L. (2005). Product mix optimization for semiconductor manufacturing based on AHP and ANP analysis. International Journal of Advanced Manufacturing Technology, 25, 1144-1156.
 Cui, X. & Wang, F. & Li, X. & Zhang, Y. & Yu, S. (2007). A Fuzzy- ANP Approach to Cooperation Risk Evaluation of Virtual Logistics Enterprise, International Conference on Automation and Logistics.
 Dan, W. & Zan, Y. (2007), Risk Management of Global Supply Chain, International Conference on Automation and Logistics.
 Dikmen, M. T. & Birgonul & Han, S. (2007) "Using fuzzy risk assessment to rate cost overrun risk in international construction projects," International Journal of Project Management, vol. 25, pp. 494-505.
 Dubois, D., & Prade, H. (1978). Operations on fuzzy numbers. International Journal ofSystem Sciences, 9(6), 613-626.
 Duncan, R.B., (1972). Characteristics of organizational environments and perceived environmental uncertainty. Administrative Science Quarterly, 17(3).
 Engelhardt-Nowitzki C. & Zsifkovits H. (2006) Complexity-Induced Supply Chain Risks - Interdependencies Between Supply Chain Risk and Complexity Management. In: Kersten W, Blecker T (eds) Managing Risks in Supply Chains: How to Build Reliable Collaboration in Logistics, pp. 37-56, Berlin
 Fisher, M., (1997). What is the right supply chain for your product? Harvard Business Review 75, 105-117.
 Hendricks, K.B. & Singhal, V.R. (2005). An empirical analysis of the effects of supply chain disruptions on long-run stock price performance and equity risk of the firm, Production Operations Management, 14(1).
 Henke M. & Kurzhals R. & Jahns C. (2006) Enterprise and Supply Risk Management from the Perspective of Internat and External Auditors. In: Kersten W, Blecker T (eds) Managing Risks in Supply Chains: How to Build Reliable Collaboration in Logistics. pp. 97- 109, Berlin
 Herrera, F. & Herrera-Viedma, E. & Chiclana, F. (2001) Multiperson decision-making based on multiplicative preference relations, Eur. J. Oper. Res. 129, 372-385.
 Hsieh, T. Y. & Lu, S. T. & Tzeng, G. H. (2004). Fuzzy MCDM approach for planning and design tenders selection in public office buildings. International Journal of Project Management, 22(7), 573- 584.
 Huang, M. & Yang, H.-M. & Wang, X.-W. (2004) "Fuzzy synthetic evaluation based risk evaluation for virtual enterprise," Mathematics in Practice and Theory, vol. 34, no.6, pp. 45-51.
 Jahns C. & Hartmann E. & Moder M. (2006) Managing Supply Risks: A System Theory Approach to Supply Early Warning Systems. In: Kersten W, Blecker T (eds) Managing Risks in Supply Chains: How to Build Reliable Collaboration in Logistics. pp. 195- 212, Berlin
 Jahns C. & Henke M. (2004) Supply Risk Management. Managementund ├£berwachungssystem nach KonTraG zur systematischen Risikobeherrschung, Beschaffung aktuell, 4:38-44
 Jung JY. & Blau G. & Pekny J. & Reklaitis G. & Eversdyk D. (2004) A simulation based optimization approach to supply chain management under demand uncertainty; Computer and Chemical Engineering 28/10:2087-2106
 J├╝ttner U. (2005) Supply chain risk management: Understanding the business requirements from a practitioner perspective. The International Journal of Logistics Management 16/1:120-141
 Kersten W. & Böger M. & Hohrath P. & Sp├ñth H (2006) Supply Chain Risk Management: Development of a Theoretical and Empirical Framework. In: Kersten W, Blecker T (eds) Managing Risks in Supply Chains: How to Build Reliable Collaboration in Logistics, pp. 3-17, Berlin
 Lee, A. H. I. & Chen, W. C. & Chang, C. J. (2008). A fuzzy AHP and BSC approach for evaluating performance of IT department in the manufacturing industry in Taiwan. Expert Systems with Applications, 34(1), 96-107.
 Lee, H., (2002). Aligning supply chain strategies with product uncertainties. California Management Review 44 (3), 105-119.
 Lee, J.W. & Kim, S.H. (2000) Using analytic network process and goal programming for interdependent information system project selection, Comput. Oper. Res. 27, 367-382.
 Li, Y. & Liao, X.-W. (2007) "Decision support for risk analysis on dynamic alliance," Decision Support Systems, vol. 42, pp. 2043-32059.
 March JP. & Shapira Z. (1987) Managerial Perspectives on Risk and Risk Taking, Management Science, 33:1404
 Mikhailov L. & Singh, M. G. (2003) "Fuzzy analytic network process and its application to the development of decision support systems," IEEE Transactions on Systems, Man, and Cybernetics-Part C: Applications and Reviews, vol. 33, no. 1, pp. 33-41, February.
 Miles, R.E. & Snow, C.C., (1978). Organization Strategy, Structure, and Process. McGraw-Hill, New York.
 Mohanty, R. P. & Agarwal, R. & Choudhury, A. K., & Tiwari, M. K. (2005). A fuzzy ANPbased approach to R&D project selection: A case study. International Journal of Production Research, 43(24), 5199- 5216.
 M├╝ssigmann N (2006) Mitigating Risk during Strategic Supply Network Modeling. In: Kersten W, Blecker T (eds) Managing Risks in Supply Chains: How to Build Reliable Collaboration in Logistics, pp. 213-226, Berlin
 Onut, S. & Kara, S. S. & Isik, E. (2009), Long term supplier selection using a combined fuzzy MCDM approach: A case study for a telecommunication company, Expert Systems with Applications 36, 3887-3895.
 Opricovic, S. (1998) Multicriteria Optimization of Civil Engineering Systems, Faculty of Civil Engineering, Belgrade.
 Opricovic, S., & Tzeng, G. H. (2003). Defuzzification within a fuzzy multicriteria decision model. International Journal of Uncertainty, Fuzziness and Knowledgebased Systems, 11(5), 635-652.
 Opricovic, S. & Tzeng, G.H. (2004) Compromise solution by MCDM methods: a comparative analysis of VIKOR and TOPSIS, Eur. J. Oper. Res. 156, 445-455.
 Pepiot, G. & Cheikhrouhou, N. & Furbringer, J.-M., & Glardon, R. (2008). A fuzzy approach for the evaluation of competences. International Journal of Production Economics, 112(1), 336-353.
 Ramik, J. (2006). A decision system using ANP and fuzzy inputs. In 12th international conference on the foundations and applications of utility, risk and decision theory, Roma.
 Ritchie B. & Brindley C. (2007) Supply chain risk management and performance: A guiding framework for future development. International Journal of Operations & Production Management 27/3:303-322
 Saaty, R. W. (2003). Decision making in complex environment: The analytic hierarchy process (AHP) for decision making and the analytic network process (ANP) for decision making with dependence and feedback.
 Saaty, T. L. (1999). Fundamentals of the analytic network process. ISAHP 1999. Kobe, Japan.
 Saaty, T. L., & Vargas, L. G. (1998). Diagnosis with dependent symptoms: Bayes theorem and the analytic network process. Operations Research, 46(4), 491-502.
 Saaty, T.L. (1996) Decision making with dependence and feedback: the analytic network process, RWS Publications, Pittsburgh,.
 Sanayei, A. & Mousavi S. F. & Yazdankhah, A. (2009), Group decision making process for supplier selection with VIKOR under fuzzy environment, Expert Systems with Applications.
 Smeltzer L. & Siferd S. (1998) Proactive supply management: the management of risk, Journal of Supply Chain Management 34/1:38-45
 Spartalis, S. & Iliadis, L. & Maris, F. (2007) "An innovative risk evaluation system estimating its own fuzzy entropy," Mathematical and Computer Modelling, vol. 46, pp. 260-267.
 Spekman RE. & Davis EW. (2004) Risky business: expanding the discussion on risk and the extended enterprise. International Journal of Physical Distribution & Logistics Management 34/5:414-433
 Teufel S. & Erat A. (2001) Sicherheitsmanagement im Electronic Business. In: Meier A (eds) Internet & Electronic Business, Z├╝rich.
 Teuteberg, F. Supply Chain Risk Management: A Neural Network Approach, E-Business and Information Systems & Research Center for Information Systems in Project and Innovation Networks.
 Tuzkaya, U. R., & Onut, S. (2008). A fuzzy analytic network process based approach to transportation-mode selection between Turkey and Germany: A case study. Information Sciences, 178, 3133-3146.
 Tsay, A. & Nahmias, S. & Agrawal, N. (1999) "Modeling supply chain contracts: A review, in: S. Tayur, R. Ganeshan, M. Magazine (Eds.), Quantitative Models for Supply Chain Management," Kluwer Academic Publishers, Norwell, MA, , pp. 299_336.
 Tzeng, G.H. & Lin, C.W. & Opricovic, S. (2005) Multi-criteria analysis of alternative-fuel buses for public transportation, Energy Policy 33, 1373-1383.
 van Wyk J. & Baerwaldt W. (2005) External Risks and the Global Supply Chain in the Chemicals Industry. Supply Chain Forum: An International Journal 6/1:1-15.
 Venkatraman, N. & Camillus, J. (1984). Exploring the concept of ÔÇÿÔÇÿfit-- in strategic management. The Academy of Management Review 9 (3), 513-525.
 Wagner, S.M. & Bode, C., (2008). An empirical examination of supply chain performance along several dimensions of risk. Journal of Business Logistics, 29(1).
 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.
 Wen, L. & Xi, Z. (2007). Supply Chain Risk Evaluation Based on Fuzzy Multi-Criteria Lattice-Order Decision-Making, International Conference on Automation and Logistics.
 Wu, H. Y. & Tzeng, G. H. & Chen, Y. H. (2009). A fuzzy MCDM approach for evaluating banking performance based on Balanced Scorecard, Expert Systems with Applications 36, 10135-10147.
 Wu, W. W., & Lee, Y. T. (2007). Selecting knowledge management strategies by using the analytic network process. Expert Systems with Applications, 32(3), 841-847.
 Y├╝ksel, I., & Dagdeviren, M. (2007). Using the analytic network process (ANP) in a SWOT analysis - A case study for a textile firm. Information Sciences, 177(16), 3364-3382.
 Yu, P.L., (1973). A class of solutions for group decision problems. Management Science 19 (8), 936-946.
 Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338- 353.
 Zadeh, L. A. (1975). The concept of a linguistic variable and its application to approximate reasoning I. Information Science, 8(3), 199- 249.
 Zeleny, M., (1974). The concept of compromise solutions and the method of the displaced ideal. Computers & Operations Research 1 (4), 479-496.