A Model for Relationship of Supply Chain Risks in Iran’s Petrochemical Industry

Document Type : Research Paper


1 Ph.D. student, Faculty of Management and Accounting, Allameh Tabataba’i University, Tehran, Iran

2 Professor, Faculty of Management and Accounting, Allameh Tabataba’i University, Tehran, Iran.

3 Associate Prof., Faculty of Management and Accounting, Allameh Tabataba’i University, Tehran, Iran.


In a complex and volatile environment of the supply chain, any attempt to reduce the risks may increase or decrease other risks; thus, achieving an overall picture of the risks of supply chain and relationships between them are necessary and will lead to more effective and comprehensive strategy to response to risks. The purpose of this paper is identifying and extracting the potential risks of supply chain relationships using interpretive structural modeling (ISM) approach. In order to do that, first an in-depth literature review has done and experts opinions with content validity has used, and then, the ISM model representing the structure of risks relationship has extract and the final model has statistically tested using path analysis. The results show that the external environment supply chain risks (natural risks, political/social, policy and macroeconomic), at a low levels of the model, have the most driving power and organizational risks (operational, financial, strategic, liability and organizational culture and employee), at the top the model, are the most dependent risks. industrial risks (market and product competition; market inputs, communications and collaboration).


-            Badurdeen, F., Shuaib, M., & Boden, B., (2014). Quantitative modeling and analysis of supply chain risks using Bayesian theory. Journal of Manufacturing Technology Management, 25(5): 631-654.
-          Cagliano, A. C., De Marco, A., Grimaldi, S. & Rafele, C. (2012). An integrated approach to supply chain risk analysis. Journal of Risk Research, 15 (7): 817-840.
-          Cavinato, J.L. (2004). Supply chain logistics risks: From the back room to the board room. International Journal of Physical Distribution and Logistics Management, 34 (5): 383–387.
-          Charan, P., Shankar, R. & Baisya, R. K. (2008). Analysis of interations among the variables of supply chain performance measurement system implementation. Business Process Management Journal, 14 (4): 512-529.
-          Chopra, S., & Sodhi, M.S. (2004). Managing risk to avoid supply chain breakdown. MIT Sloan Management Review, 46(1): 53-61. 
-          Christopher, M., & Peck, H. (2004). Building the resilient supply chain. International   Journal of Logistics Management, 15 (2): 1–14. 
-          Christopher, M., Mena, C., Khan, O., & Yurt, O. (2011). Approaches to managing   global sourcing risk. Supply Chain Management: An International Journal, 16 (2): 67–81.
-          Diabat, A. & Govindan, K. (2011). An analysis of the drivers affecting the implementation of green supply chain management. Resources, Consevation and Recycling, 55 (6): 659-667.
-          Faisal, M. N. (2010). Sustainable supply chains: a study of interactions among the enablers. Business Process Management, 16 (3): 508-529.
-          Faisal, M. N., Banwet, D. K. & Shankar, R. (2007). Management of risk in supply chains, SCOR approach and analytical process, Supply Chain Forum: An International Journal, 8 (2): 66-79.
-          Franck, C. (2007). Framework for supply chain risk management, Supply Chain Forum: An International Journal, 8 (2): 2-13.
-          Govindan, G., Azevedo, S. G., Carvalho, H. & Machado, V. C. (2015). Lean, green resellient practices influence on supply chain performance: interpretive structural modeling approach. Int. J. Environ. Sci. Technol., 12: 15-34.
-          Hallikas, J., Karvonen, I., Pulkkinen, U., Virolainen, V.M., & Tuominen, M. (2004). Risk management processes in supplier networks. International Journal Production Economics, 90: 47–58.
-          Hallikas, J., Virolainen, V.M., & Tuominen, M. (2002). Risk analysis and assessment in network environment: A dyadic case study. International Journal of Production economics, 78: 45-55.
-          Hachicha, W. & Elmsalmi, M. (2013). An integrated approach based structural modeling for risk prioritization in supply network management. Journal of Risk Research, 17 (10): 1301-1324.
-          Harland, C., Brenchley, R., & Walker, H. (2003). Risk in supply network. Journal of purchasing and supply management, 9: 51-62. 
-          Hauser, L. M. (2003). Risk-adjusted supply chain management. Supply Chain Management Review, 7 (6): 64-71.
-          Hooman, H.A. (2011). Structural Equation Modeling with LISREL Application.SAMT publications, Tehran (in Persian).
-          Islam, A. & Tedford, D. (2012). Risk determinants of small and medium-sized manufacturing enterprises (SMEs) – an exploratory study in New Zealand. Journal of Industrial Engineering International, 8 (12): 1-13.
-          Jia, P., Diabat, A. & Mathiyazhagan, K. (2015). Analysing the SSCM practices in the mining and mineral industry by ISM approach. Resources Policy.. 46 (1): 76-85.
-          Jüttner, U. (2005). Supply chain risk management: Understanding the business requirements from a practitioner perspective. The International Journal of   Logistics Management, 16 (1): 120-141.
-          Jüttner, U., Peck, H., & Christopher, M. (2003). Supply Chain Risk Management: Outlining An Agend A For Future Research. International Journal of Logistics: Research & Applications, 6 (4): 197-210. 
-          Kern, D., Moser, R., Hartmann, E. & Moder, M. (2012). Supply risk management: model development and empirical analysis. International Journal of Physical Distribution & Logistics Management, 42 (1): 60 – 82.
-          Khan, H., Talib, F. & Faisal, M. N. (2015). An analysis of of the barriers to the proliferation of M-commerce in Qatar: a relationship modeling approach. Journal of Systems and Information Technology, 17(1): 54-81.
-          Kleindorfer, P.R., & Saad, G.H. (2005). Managing disruption risks in supply chains. Production and Operations Management, 14 (1): 53–68. 
-          Kordestani, G. R. & Ghasemi, M. (2014). Development of balanced scorecard framework based on an integrated approach of cause and effect diagram, Interpretive Structural Modeling  and Analytic Network Process. Journal of Industrial Management, 3: 573-590 (in Persian).
-          Lawshe, C.H. (1975). A quantitative approach to content validity. Personnel Psychology, 28: 563–575.
-          Lee, A. H., Wang, W. M. & Lin, T. Y. (2010). An evaluation framework for technology transfer of new equipment in high technology industry. Technological Forecasting & Social change, 77 (1): 135-150.
-          Manuj, I., & Mentzer, J. (2008a). Global supply chain risk managementstrategies. International Journal of Physical Distribution and Logistics Management, 38 (3): 192–223. 
-          Manuj, I., & Mentzer, J.T. (2008b). Global supply chain risk management. Journal of   Business Logistics, 29(1): 133–155. 
-          Micheli, G.J.L., Cagno, E., & Zorzini, M. (2008). Supply risk management vs supplier selection to manage the supply risk in the EPC supply chain. Management Research News, 31 (11): 846-866.  
-          Mohammadi, A., MoslehShirazi, A., & Shojayee P. (2013). Interpretivestructural modeling of gas project supply chain risks. Journal of Industrial Management Perspective, 12: 9-37 (in Persian).
-          Norman, A. & Lindorth, R. (2004). Categorization of supply chain risk and risk management. In Brindley, C. (Ed.), Supply Chain Risk, Ashgate, Aldershot: 14-27.
-          Norrman, A., & Jansson, U. (2004). Ericsson's proactive supply chain risk management   approach after a serious sub–supplier accident. International Journal of Physical   Distribution and Logistics Management, 34 (5): 434–456. 
-          Pandy, V. C. & Garg, S. (2009). Analysis of integraction among the enablers of agility in supply chain. Journal of Advances in Management Research, 6 (1): 99-114.
-          Phol, H. C., Gallus, P. & Thomas, D. (2011). Interpretive structural modeling of supply chain risks. International Journal of Physical distribution & Logisticas Management, 41 (9): 839-859.
-          Punniyamoorthy, M., Thamaraiselvan, N. & Manikandan, L. (2013). Assessment of supply chain risks: scale development and validation. Benchmarking: An International Journal, 20 (1): 79-105.
-            Rangel, D. A., Oliveira, T. K., & Leite, M. S. A. (2014). Supply chain risk classification: discussion and proposal. International Journal of Production Research, 52: 1-21.
-          Rao, S. & Glodsby, T. J., (2009). Supply chain risks: a review and typology. The International Journal of Logistics Management, 20 (1): 97-123.
-          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. 
-          Qureshi, M.N., Kumar, D., Kumar, P. (2007). Modeling the logistics outsourcing relationship variables to enhance shippers, productivity and competitiveness in logistical supply chain, International Journal of Productivity and Performance Management, 56 (8): 689-714.
-          Sodhi, M.S., Son, B.G., & Tang, C.S. (2012). Perspectives on Supply Chain Risk   Management. International Journal of Production and Operations Management, 21 (1): 1–13.
-          Svensson, G. (2002). A conceptual framework of vulnerability in firms’ inbound and outbound logistics flows. International Journal of Physical Distribution, 32 (2): 110-134.
-          Tang, C.S. (2006). Perspectives in supply chain risk management: a review. International Journal Production Economics, 103: 451–488. 
-          Tang, C.S., & Tomlin, B. (2008). The power of flexibility for mitigating supply chain   risks. International Journal of Production Economics, 116 (1): 12–27. 
-          Thun, J.H., & Hoenig, D. (2011). An empirical analysis of supply chain risk management in the German   automotive industry. International Journal Production Economics, 131: 242–249. 
-          Tummala, R. & Schoenherr, T. (2011). Assessing and managing risks using the supply chain risk management process (SCRMP). Supply Chain Management: An International Journal, 16 (6): 474-483.
-          Venkatesh, V.G., Rathi, S. & Patwa, S. (2015). Analysis on supply chain risks in Indian apparel retail chains and proposal of risk prioritization model using Interpretive Structural modelling. Journal of Retailing and Consumer Services, 26: 153-167.
-          Vilko, J. (2012). Approaches to supply chain risk management: identification, analysis and control. Lappeenranta University of Technology Digipaino. 
-          Vilko, J., & Hallikas, J.M. (2012). Risk assessment in multi modal   supply chains. International Journal of Production Economics, 140: 586-595. 
-          Wagner, S. M., & Neshat, N. (2010). Assessing the vulnerability of supply chains using graph theory. International Journal Production Economics, 126: 121–129. 
-          Wagner, S. M. & Bode, C. (2008). An empirical examination of supply chain performance along several dimentions of risk. Journal of Business Logistics, 29(1): 307–329.
-          Wieland, A. & Wallenburg, C. M. (2013). The influence of compentencies on supply chain resilience: a relational view. International Journal of Physical Distribution & Logistics Management, 43 (4): 300-320.
-          Wu, T., Blackhurst, J., & Chidambaram, V. (2006). A  model for inbound supply risk analysis. Computers in Industry, 57: 350–365.  
-          Zand Hesami, H., & Savoji, A., (2011). Risk management in supply chain management. International Journal of Economics and Management Sceinces, 1(3): 60-72.
-          Ziegenbein, A. Nienhaus, J. (2004). Coping with supply chain risks on strategic, tactical and operational level. Global Project and Manufacturing Management, the Symposium Proceedings.
-          Zhao, L., Huo, B., Sun, L. & Zhao, X. (2013). The impact of supply chain risk on supply chain integration and company performance: a global investigation. Supply Chain Management: An International Journal, 18 (2), 115-131.
-          Zsidisin, G.A., & Ellram, L.M., Carter, J. & Cavanito, J.L. (2004). An analysis of supply risk assessment techniques. International Journal of Physical Distribution, 34(5): 397–413.