Developing a Risk Reduction Support System for Health System in Iran: A Case Study in Blood Supply Chain Management

Ali Sibevei, Adel Azar, Mostafa Zandieh, Seyed Mohammad Khalili and Maziar Yazdani
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Ali Sibevei: Department of Industrial Management, Faculty of Management and Economics, Tarbiat Modares University, Tehran 14115-111, Iran
Adel Azar: Department of Industrial Management, Faculty of Management and Economics, Tarbiat Modares University, Tehran 14115-111, Iran
Mostafa Zandieh: Department of Industrial Management and Information Technology, Management and Accounting Faculty, Shahid Beheshti University, Tehran 1983969411, Iran
Seyed Mohammad Khalili: Department of Industrial Engineering, Faculty of Engineering, Khayyam University, Mashhad 9189747178, Iran
Maziar Yazdani: School of Built Environment, University of New South Wales, Kensington, Sydney, NSW 2052, Australia

IJERPH, 2022, vol. 19, issue 4, 1-19

Abstract: Health systems are recognised as playing a potentially important role in many risk management strategies; however, there is strong evidence that health systems themselves have been the victims of unanticipated risks and have lost their functionality in providing reliable services. Existing risk identification and assessment tools in the health sector, particularly in the blood supply chain, address and evaluate risks without taking into account their interdependence and a holistic perspective. As a result, the aim of this paper is to develop a new systemic framework based on a semi-quantitative risk assessment approach to measure supply chain risks, which will be implemented through a case study on the Iranian BSC. This paper identifies and assesses supply chain risks (SCRs) by employing a novel systemic process known as SSM-SNA-ISM (SSI). First, the supply chain and its risks are identified using Soft Systems Methodology (SSM). Then, given the large number of risks, the second stage uses Social Network Analysis (SNA) to identify the relationships between the risks and select the most important ones. In the third stage, risk levelling is performed with a more in-depth analysis of the selected risks and the application of Interpretive Structural Modelling (ISM), and further analysis is performed using the Cross-Impact Matrix Multiplication Applied to Classification (MICMAC). The study found that by using the new proposed approach, taking into account risk relationships, and taking a holistic view, various supply chain risks could be assessed more effectively, especially when the number of risks is large. The findings also revealed that resolving the root risks of the blood supply chain frequently necessitates management skills. This paper contributes to the literature on supply chain risk management in two ways: First, a novel systemic approach to identifying and evaluating risks is proposed. This process offers a fresh perspective on supply chain risk modelling by utilising systems thinking tools. Second, by identifying Iranian BSC risks and identifying special risks.

Keywords: supply chain risks; blood supply chain; interpretive structural modelling; social network analysis (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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