Journal of New Approaches in Management and Marketing

Determining the relationships and ranking of desirable risk control factors in the medical laboratory supply chain using an interpretive structural approach

Document Type : Original Article (Qualitative)

Authors

Masoumeh Pashapour 1
Mehdi Zakipour 2
Reza Mohamadi 3
Amir Mohammadzadeh 4

1 Department of Business Management, Qa.C., Islamic Azad University, Qazvin, Iran

2 Department of Business Management, Qa.C., Islamic Azad University, Qazvin, Iran.

3 Department of Clinical Biochemistry, TeMS.C., Islamic Azad University, Tehran, Iran

4 Department of Accounting and Financial Department, Qa.C., Islamic Azad University, Qazvin, Iran

https://doi.org/10.22034/jnamm.2026.569528.1241
Abstract
This study aimed to present a model for achieving optimal risk control by managing risk and failure in the medical laboratory supply chain. The information required for the study for interpretive structural modeling (ISM) to provide a model was collected from experts, namely 15 high-ranking managers and experts in medical laboratories who were active throughout the supply chain. In this study, interpretive structural modeling was used to present the model. The results of interpretive structural analysis by the exploratory model showed that the exploratory model of the study had 4 main factors and 13 sub-factors identified at four levels. The fourth level is the identification of supply chain risks, including the dimensions of financial and legal risks, quality risks, and supplier and logistics risks. The third level is the analysis of failure and its effects, including identifying weaknesses; analyzing the effects of failure and prioritizing risks. The second level is the dimension of coping strategies and risk management, including supplier diversity, emergency planning, and quality control with information technology. Ultimately, the factors and dimensions in the previous three levels at level one lead to achieving optimal risk control with the dimensions of reducing risk and failure, increasing supply chain efficiency, continuous improvement, and monitoring performance.

Keywords

optimal risk control
risk management
failure management
medical laboratory
Subjects

  • Receive Date 29 December 2025
  • Revise Date 26 February 2026
  • Accept Date 18 April 2026

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