Interval-valued intuitionistic fuzzy digraph-matrix approach with PERMAN algorithm for measuring COVID-19 impact on...

Area of Science:

• Supply Chain Management
• Food Security
• Disaster Management

Background:

• The COVID-19 pandemic caused widespread business disruption, severely affecting perishable food supply chains (PFSCs).
• Understanding the pandemic's specific impact on PFSCs in developed versus developing nations is crucial for targeted interventions.

Purpose of the Study:

• To analyze the impact of COVID-19 on perishable food supply chains (PFSCs) in developed and developing countries.
• To identify key factors contributing to supply chain disturbances within the PFSC during the pandemic.

Main Methods:

• A two-step analysis was conducted, first identifying unique disturbance factors in PFSCs.
• An interval-valued intuitionistic fuzzy set (IVIFS)-based graph theory and matrix approach (GTMA) was employed to analyze the COVID-19 impact index.
• The PERMAN algorithm was utilized for calculating the permanent function.

Main Results:

• The study identified critical factors affecting PFSCs during the COVID-19 pandemic.
• Developing nations require significant improvements in technological and infrastructural factors to strengthen their PFSCs.
• Comparative analysis highlighted differing impacts and contributing factors between developed and developing nations.

Conclusions:

• Decision-makers can use these findings to anticipate and manage the short-term and long-term consequences of COVID-19 on PFSCs.
• Enhancing technological and infrastructural capabilities is vital for developing countries to build resilient PFSCs.
• The study provides a novel analytical framework integrating IVIFS-GTMA and the PERMAN algorithm for supply chain disruption analysis.