Industrial Innovations

Industrial Innovations

Identification and Weighting of Supply Chain Risks with the Help of Fuzzy Analytical Hierarchy Process Approach (Case Study: Mobarakeh Steel Complex of Isfahan)

Document Type : Original Article

Authors
parisa fatemi 1
alireza Hosseinbeigi 2
Mohammad hossein arman 3
shima falahi 4
1 Master of Industrial Management, Shahid Ashrafi Isfahani University, Isfahan, Iran
2 Assistant Professor, Department of Management and Accounting, Niriz Branch, Islamic Azad University, Niriz, Iran
3 Assistant Professor, Department of Management, Mobarakeh Branch, Islamic Azad University, Mobarakeh, Isfahan, Iran
4 PhD student, Department of Industrial Engineering, Faculty of Engineering, University of Kurdistan, Iran
https://doi.org/10.61186/jii.1.4.302
Abstract
Supply chains play an important and integral role in today's global economy. Supply chain operations are sensitive to various uncertainties such as disruptions in suppliers, transportation disruptions, or fluctuations in customer demand. Supply chain risk management can be defined as a management activity aimed at identifying and managing risks for the supply chain through a collaborative approach among supply chain members to reduce the vulnerability of the supply chain. The aim of this study is to identify and prioritize supply chain risks of Mobarakeh Steel Complex in Isfahan through the fuzzy analytic hierarchy process. To this end, the company's supply chain risks were identified using previous research studies and interviews with relevant experts, and the most important ones were selected through questionnaires, screening, and selection. Then, these risks were classified into different categories and fuzzy pairwise comparison tables were designed and distributed among experts for collection. Finally, the relative weights of the elements in these tables were extracted using the non-linear fuzzy preference programming method, and then the final weights of each of the company's risks were obtained using the fuzzy analytic hierarchy process.
Keywords
Supply Chain
Supply Chain Risk
Fuzzy Preference Programming
Fuzzy Hierarchical Analysis Process
[1] Vanany I, Zailani S, Pujawan N. Supply chain risk management: literature review and future research. International Journal of Information Systems and Supply Chain Management (IJISSCM). 2009;2:16-33. 
[2] Oliver RK, Webber MD. Supply-chain management: logistics catches up with strategy. Logistics: The strategic issues. 1982:63-75. 
[3] Heckmann I, Comes T, Nickel S. A critical review on supply chain risk–Definition, measure and modeling. Omega. 2015;52:119-32. 
[4] Mirfakhredini SH, Andalib Ardakani D, Rezaei Asal M. Applying multi-criteria decision-making techniques to evaluate supply chain risk factors: Case Study: Small and medium-sized enterprises' information technology field. Scientific-Research Quarterly of Management Studies Industrial. 2013;8:107-30. 
[5] Ritchie B, Brindley C. Supply chain risk management and performance: A guiding framework for future development. International journal of operations & production management. 2007;27:303-22. 
[6] Aitken J. Supply chain integration within the context of a supplier association: case studies of four supplier associations. 1998. 
[7] Bogataj D, Bogataj M. Measuring the supply chain risk and vulnerability in frequency space. International Journal of Production Economics. 2007;108:291-301. 
[8] Neiger D, Rotaru K, Churilov L. Supply chain risk identification with value-focused process engineering. Journal of operations management. 2009;27:154-68. 
[9] Trkman P, McCormack K. Supply chain risk in turbulent environments—A conceptual model for managing supply chain network risk. International Journal of Production Economics. 2009;119:247-58. 
[10] Kırılmaz O, Erol S. A proactive approach to supply chain risk management: Shifting orders among suppliers to mitigate the supply side risks. Journal of Purchasing and Supply Management. 2017;23:54-65. 
[11] Mehr Ali Dehnavi, Masouma. Aghaei, Abdallah. Stock, Mustafa. supply chain risk management: a literature review.  9th international management conference2018. 
[12] Schoenherr T, Tummala VR, Harrison TP. Assessing supply chain risks with the analytic hierarchy process: Providing decision support for the offshoring decision by a US manufacturing company. Journal of Purchasing and Supply Management. 2008;14:100-11. 
[13] Blackhurst JV, Scheibe KP, Johnson DJ. Supplier risk assessment and monitoring for the automotive industry. International journal of physical distribution & logistics management. 2008;38:143-65. 
[14] Sofyalıoğlu Ç, Kartal B. The selection of global supply chain risk management strategies by using fuzzy analytical hierarchy process–a case from Turkey. Procedia-Social and Behavioral Sciences. 2012;58:1448-57. 
[15] Aqlan F. A software application for rapid risk assessment in integrated supply chains. Expert Systems with Applications. 2016;43:109-16. 
[16] Tummala R, Schoenherr T. Assessing and managing risks using the supply chain risk management process (SCRMP). Supply Chain Management: An International Journal. 2011;16:474-83. 
[17] Mazaheri A, Karbasian M, Shirouyezad H. Identifying and prioritizing supply chain risks in manufacturing organizations using the hierarchical analysis process. Supply Chain Management Quarterly. 2013;13:28-37. 
[18] Shahbandarzadeh H, Jamali G, Shafiei F. Analytical approach in identifying factors affecting supply chain risk in the country's dairy industries. Supply Chain Management Scientific-Promotional Quarterly. 2013;15:42-53. 
[19] Hayati M, Ataei M, Khalukakaei R, Sayadi AR. presenting a model for assessing supply chain risks using multi-indicator decision-making techniques. Scientific-Research Quarterly of Industrial Management Studies. 2013;12:19-40. 
[20] Alfat L, Khosravani F, Jalali R. project risk identification and prioritization based on the PMBOK standard with a fuzzy approach: (Study case: non-level intersection construction projects in Bushehr province). scientific-research quarterly Industrial Management Studies. 2009;8:163-47. 
[21] Shahraki MR, Adalat Sarostani, Reza M. comparing the ranking of effective factors in supply chain risk management using the fuzzy electret method and the jackknife sampling method together with interval analysis. Scientific and Research Quarterly of Crisis Management. 2014;8:110-7. 
[22] Zarinpour N, Amiri M, Nematalahi MH. Risk assessment of green buildings using the combined approach of Dimetal and the analysis process network. Journal of Operations Research Decision Making. 2021;6. 
[23] Jüttner U, Peck H, Christopher M. Supply chain risk management: outlining an agenda for future research. International Journal of Logistics: research and applications. 2003;6:197-210. 
[24] Moeinzadeh P, Hajfathaliha A. A combined fuzzy decision making approach to supply chain risk assessment. International Journal of Industrial and Manufacturing Engineering. 2009;3:1631-47. 
[25] Aqlan F, Lam SS. A fuzzy-based integrated framework for supply chain risk assessment. International Journal of Production Economics. 2015;161:54-63. 
[26] Abbasi-Parizi S, Aminnayeri M, Bashiri M. Robust solution for a minimax regret hub location problem in a fuzzy-stochastic environment. Journal of Industrial & Management Optimization. 2018;14. 
[27] Kaewfak K, Ammarapala V, Charoensiriwath C. Fuzzy AHP approach for route selection in multimodal transportation: The case of coal industry in Thailand. Science & Technology Asia. 2021:84-95. 
[28] Srdjevic B, Medeiros YDP. Fuzzy AHP assessment of water management plans. Water Resources Management. 2008;22:877-94. 
[29] Mikhailov L. Deriving priorities from fuzzy pairwise comparison judgements. Fuzzy sets and systems. 2003;134:365-85. 
 
Industrial Innovations
Volume 1, Issue 4 - Serial Number 4
Autumn 2023
Pages 302-314

  • Receive Date 28 November 2023
  • Revise Date 24 January 2024
  • Accept Date 02 February 2024