An Integrated Model for Exploring supply Chain Sustainability Drivers Using Big Data Analytics Capacities in the Context of thinking Beyond COVID-19 In An Emerging Economy: Total Interpretive Modeling Approach

Document Type : Articles Abstracts

Abstract

The sustainability of the supply chain (SCS) has been an important research topic in the last two decades due to the changes in the surrounding environment. This research aims at exploring the drivers of SCS to tackle supply chain disruption in a such pandemic in the context of a particular emerging economy to achieve that the total interpretive structuring model is used (TIPSM). The proposed methodology is used to test the opinions of supply chain practitioners as well as experts about the drivers of SCS in the emerging economy.  The results reveal that 20 drivers of (SSC) have an influential relationship and indispensable links, in addition, the results have shown that financial support from the government and the supply chain partners are the most influencing drivers of SSC to tackle the situation of COVID-19. Then, Matricide Impacts Cruoses Multiplication Applique a un Classement (MIMAC) analysis is used to classify drivers into different groups based on the driving power and dependence power.   These results will assist industrial managers, practitioners, policymakers, and government intuition to take initiatives for applying SC and SSC in the emerging economy by considering the recommended drivers.

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Citation: Serag, A.,(2022).  An Integrated Model for Exploring supply Chain Sustainability Drivers Using Big Data Analytics Capacities in the Context of thinking Beyond COVID-19 In An Emerging Economy: Total Interpretive Modeling Approach. Journal of Commercial & Environmental Studies. 13(3). 69 – 113.

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