An Integrated Fuzzy Approach for the Evaluation of Supply Chain Risk Mitigation Strategies
Author(s)
Xiaojun Wang*
ABSTRACT
Competing in an increasingly uncertain business environment, organizations need to mitigate its supply chain risks to enhance their resiliency. However, it is important to implement appropriate strategies to meet business needs. This paper presents a novel approach that integrates fuzzy risk assessment and fuzzy Delphi for the evaluation of strategies in order to mitigate supply chain risks. The novelty of the model lies in the fact that an analytical tool enables the specific business preferences concerning supply chain risks to be taken into consideration in making the strategic decisions. It provides a practical solution by which companies can systematically assess the risks involved in the supply chain and select appropriate strategies to address them.
Cite this paper
Wang, X. (2014) An Integrated Fuzzy Approach for the Evaluation of Supply Chain Risk Mitigation Strategies. Open Journal of Social Sciences, 2, 161-166. doi: 10.4236/jss.2014.29028.
Wang, X. (2014) An Integrated Fuzzy Approach for the Evaluation of Supply Chain Risk Mitigation Strategies. Open Journal of Social Sciences, 2, 161-166. doi: 10.4236/jss.2014.29028.
References
[1] Neiger, D., Botaru, K. and Churilov, L. (2009) Supply Chain Risk Identification with Value-Focused Process Engineering. Journal of Operations Management, 27, 154-168. http://dx.doi.org/10.1016/j.jom.2007.11.003 [2] Jüttner, U., Peck, H. and Christopher, M. (2003) Supply Chain Risk Management, Outlining an Agenda for Future Research. International Journal of Logistics, 6(4), 197-219. http://dx.doi.org/10.1080/13675560310001627016 [3] Giachetti, R.E., Martinez, L.D., Saenz, O.A. and Chen, C.S. (2003) Analysis of the Structural Measures of Flexibility and Agility Using a Measurement Theoretical Framework. International Journal of Production Economics, 86, 47-62. http://dx.doi.org/10.1016/S0925-5273(03)00004-5 [4] Narasimhan, R., Talluri, S. and Das, A. (2004) Exploring Flexibility and Execution Competencies of Manufacturing Firms. Journal of Operations Management, 22, 91-106. http://dx.doi.org/10.1016/j.jom.2003.12.003 [5] Sawhney, R. (2006) Interplay between Uncertainty and Flexibility across the Value-Chain: Towards a Transformation Model of Manufacturing Flexibility. Journal of Operations Management, 24, 476-493. http://dx.doi.org/10.1016/j.jom.2005.11.008 [6] Lee, H. (2004) The Triple—A Supply Chain. Harvard Business Review, 102-112. [7] Tang, C. and Tomlin, B. (2008) The Power of Flexibility for Mitigating Supply Chain Risks. International Journal of production Economics, 116, 12-27. http://dx.doi.org/10.1016/j.ijpe.2008.07.008 [8] Faisal, M.N., Banwet, D.K. and Shankar, R. (2006) Supply Chain Risk Mitigation: Modeling the Enablers. Business Process Management Journal, 12, 535-552. http://dx.doi.org/10.1108/14637150610678113 [9] Yang, Z.B., Aydin, G., Babich, V. and Beil, D.R. (2009) Supply Disruptions, Asymmetric Information, and a Backup Production Option. Management Science, 55, 192-209. http://dx.doi.org/10.1287/mnsc.1080.0943 [10] Chan, H.K. and Wang, X. (2013) Fuzzy Hierarchical Model for Risk Assessment: Principles, Concepts, and Practical Applications. Springer, London. http://dx.doi.org/10.1007/978-1-4471-5043-5 [11] The Royal Society (1992), Analysis, Perception and Management, The Royal Society, London. [12] Wang, X., Li, D. and Shi, X. (2012) A fuzzy Enabled Model for Aggregative Food Safety Risk Assessment in Food Supply Chains. Production Planning and Control, 23, 377-395. http://dx.doi.org/10.1080/09537287.2011.561812 [13] Wang, X., Chan, H.K., Yee, W.Y. and Diaz-Rainey, I. (2012) A Two-Stage Fuzzy-AHP Model for Risk Assessment of Implementing Green Initiatives in the Fashion supply Chain. International Journal of Production Economics, 135, 595-606. http://dx.doi.org/10.1016/j.ijpe.2011.03.021 [14] Kuo, Y.F. and Chen, P.C. (2008) Constructing Performance Appraisal Indicators for Mobility of the Service Industries Using Fuzzy Delphi Method. Expert Systems with Applications, 35, 1930-1939. http://dx.doi.org/10.1016/j.eswa.2007.08.068 [15] Lee, A.H.I., Wang, W. and Lin, T. (2010) An Evaluation Framework for Technology Transfer of New Equipment in High Technology Industry. Technological Forecasting & Social Change, 77, 135-150. http://dx.doi.org/10.1016/j.techfore.2009.06.002 [16] Wang, X. and Durugbo, C. (2013) Analysing Network Uncer-tainty for Industrial Product-Service Delivery: A Hybrid Fuzzy Approach. Expert Systems with Applications, 40, 4621-4636. http://dx.doi.org/10.1016/j.eswa.2013.01.062 [17] Hsiao, T.Y. (2006) Establish Standards of Standard Costing with the Application of Convergent Gray Zone Test. European Journal of Operational Research, 168, 593-611. http://dx.doi.org/10.1016/j.ejor.2004.05.012 [18] Ishikawa, A., Amagasa, T., Shiga, T., Tomizawa, G., Tatsuta, R. and Mieno, H. (1993) The Max-Min Delphi Method and Fuzzy Delphi Method via Fuzzy Integration. Fuzzy Sets Systems, 55, 241-253. http://dx.doi.org/10.1016/0165-0114(93)90251-C
[1] Neiger, D., Botaru, K. and Churilov, L. (2009) Supply Chain Risk Identification with Value-Focused Process Engineering. Journal of Operations Management, 27, 154-168. http://dx.doi.org/10.1016/j.jom.2007.11.003 [2] Jüttner, U., Peck, H. and Christopher, M. (2003) Supply Chain Risk Management, Outlining an Agenda for Future Research. International Journal of Logistics, 6(4), 197-219. http://dx.doi.org/10.1080/13675560310001627016 [3] Giachetti, R.E., Martinez, L.D., Saenz, O.A. and Chen, C.S. (2003) Analysis of the Structural Measures of Flexibility and Agility Using a Measurement Theoretical Framework. International Journal of Production Economics, 86, 47-62. http://dx.doi.org/10.1016/S0925-5273(03)00004-5 [4] Narasimhan, R., Talluri, S. and Das, A. (2004) Exploring Flexibility and Execution Competencies of Manufacturing Firms. Journal of Operations Management, 22, 91-106. http://dx.doi.org/10.1016/j.jom.2003.12.003 [5] Sawhney, R. (2006) Interplay between Uncertainty and Flexibility across the Value-Chain: Towards a Transformation Model of Manufacturing Flexibility. Journal of Operations Management, 24, 476-493. http://dx.doi.org/10.1016/j.jom.2005.11.008 [6] Lee, H. (2004) The Triple—A Supply Chain. Harvard Business Review, 102-112. [7] Tang, C. and Tomlin, B. (2008) The Power of Flexibility for Mitigating Supply Chain Risks. International Journal of production Economics, 116, 12-27. http://dx.doi.org/10.1016/j.ijpe.2008.07.008 [8] Faisal, M.N., Banwet, D.K. and Shankar, R. (2006) Supply Chain Risk Mitigation: Modeling the Enablers. Business Process Management Journal, 12, 535-552. http://dx.doi.org/10.1108/14637150610678113 [9] Yang, Z.B., Aydin, G., Babich, V. and Beil, D.R. (2009) Supply Disruptions, Asymmetric Information, and a Backup Production Option. Management Science, 55, 192-209. http://dx.doi.org/10.1287/mnsc.1080.0943 [10] Chan, H.K. and Wang, X. (2013) Fuzzy Hierarchical Model for Risk Assessment: Principles, Concepts, and Practical Applications. Springer, London. http://dx.doi.org/10.1007/978-1-4471-5043-5 [11] The Royal Society (1992), Analysis, Perception and Management, The Royal Society, London. [12] Wang, X., Li, D. and Shi, X. (2012) A fuzzy Enabled Model for Aggregative Food Safety Risk Assessment in Food Supply Chains. Production Planning and Control, 23, 377-395. http://dx.doi.org/10.1080/09537287.2011.561812 [13] Wang, X., Chan, H.K., Yee, W.Y. and Diaz-Rainey, I. (2012) A Two-Stage Fuzzy-AHP Model for Risk Assessment of Implementing Green Initiatives in the Fashion supply Chain. International Journal of Production Economics, 135, 595-606. http://dx.doi.org/10.1016/j.ijpe.2011.03.021 [14] Kuo, Y.F. and Chen, P.C. (2008) Constructing Performance Appraisal Indicators for Mobility of the Service Industries Using Fuzzy Delphi Method. Expert Systems with Applications, 35, 1930-1939. http://dx.doi.org/10.1016/j.eswa.2007.08.068 [15] Lee, A.H.I., Wang, W. and Lin, T. (2010) An Evaluation Framework for Technology Transfer of New Equipment in High Technology Industry. Technological Forecasting & Social Change, 77, 135-150. http://dx.doi.org/10.1016/j.techfore.2009.06.002 [16] Wang, X. and Durugbo, C. (2013) Analysing Network Uncer-tainty for Industrial Product-Service Delivery: A Hybrid Fuzzy Approach. Expert Systems with Applications, 40, 4621-4636. http://dx.doi.org/10.1016/j.eswa.2013.01.062 [17] Hsiao, T.Y. (2006) Establish Standards of Standard Costing with the Application of Convergent Gray Zone Test. European Journal of Operational Research, 168, 593-611. http://dx.doi.org/10.1016/j.ejor.2004.05.012 [18] Ishikawa, A., Amagasa, T., Shiga, T., Tomizawa, G., Tatsuta, R. and Mieno, H. (1993) The Max-Min Delphi Method and Fuzzy Delphi Method via Fuzzy Integration. Fuzzy Sets Systems, 55, 241-253. http://dx.doi.org/10.1016/0165-0114(93)90251-C