This paper addresses the challenges faced by supply chain networks (SCNs) during the COVID-19 pandemic, emphasizing the need for sustainable practices and dynamic capacities to ensure resilience and performance. The authors propose an analytical framework to assess environmentally friendly procedures and dynamic capacities, focusing on financial ratios and establishing drivers for sustainable practices during disruptions. The study aims to assist practitioners in creating and implementing sustainable supply chain activities and tracking their effects on business sustainability. The research is structured into several sections, including a literature review, problem statement, model formulation, computational experiment, sensitivity analysis, and management insights. The model integrates material and financial flows, considering logistical constraints and financial constraints, to optimize equity changes and maximize profits. The results show that integrating financial aspects, such as interest rates, can lead to a more productive and efficient supply chain. The study also highlights the importance of financial ratios in evaluating a company's financial health and operational outcomes. Finally, the authors discuss limitations and suggest future research directions, including the use of metaheuristic algorithms and the impact of big data analytics and machine learning on supply chain resilience.This paper addresses the challenges faced by supply chain networks (SCNs) during the COVID-19 pandemic, emphasizing the need for sustainable practices and dynamic capacities to ensure resilience and performance. The authors propose an analytical framework to assess environmentally friendly procedures and dynamic capacities, focusing on financial ratios and establishing drivers for sustainable practices during disruptions. The study aims to assist practitioners in creating and implementing sustainable supply chain activities and tracking their effects on business sustainability. The research is structured into several sections, including a literature review, problem statement, model formulation, computational experiment, sensitivity analysis, and management insights. The model integrates material and financial flows, considering logistical constraints and financial constraints, to optimize equity changes and maximize profits. The results show that integrating financial aspects, such as interest rates, can lead to a more productive and efficient supply chain. The study also highlights the importance of financial ratios in evaluating a company's financial health and operational outcomes. Finally, the authors discuss limitations and suggest future research directions, including the use of metaheuristic algorithms and the impact of big data analytics and machine learning on supply chain resilience.