Supply Chain Viability through Optimized System Dynamics and Agent-Based Modeling
Open Access DepositedDuring the COVID-19 pandemic, supply chain issues caused severe shortages in critical goods, chief of which was the personal protective equipment (PPE) that was vital for limiting or preventing the spread of the disease (Bharti and Singh, 2020). The incredible demand for PPE that occurred not just at hospitals and medical centers, but also by the overall populace caused a large spike in prices of healthcare commodities and PPE, and severe delays in supply chain communications further delayed supplies from reaching the necessary destinations (Caggia, Fondrevelle, and Cagliano, 2024).These issues opened a new field of study in supply chain resilience, namely the concept of supply chain viability. Resilience is the ability to recover after a disruption (e.g., an earthquake) and return to some baseline, initial state. Viability is the ability to operate and continue to serve markets/customers with products and services in the presence of disruptions and long-term crises (i.e., the ability to survive in the long-term) through adaptation and reconfiguration changing states dynamically (Ivanov et al., 2023). As supply chain viability is a relatively new area of research, there are many areas of research to explore and further refine to ensure adequate knowledge of and improvement of supply chain viability. To this end, this praxis introduces quantitative methods for analyzing unique supply chains for input parameters that affect overall supply chain viability, as well as a quantitative method for assessing supply chain viability. To complete these tasks, the research includes a model of a generalized baseline healthcare commodity four-level supply chain during steady-state and COVID-19 pandemic operations. This model is created using system dynamics and agent-based modeling through MATLAB and Simulink to create an adaptable baseline for reuse in similar industries. Using this baseline model, both diversity and redundancy of the healthcare commodity supply chain are varied to quantitatively identify input parameters that are able to assist with predicting supply chain viability. This research also analyzes behavioral changes and identifies improvements to both supply chain planning and behavioral changes that will assist in improved supply chain management (SCM) during pandemics. This in turn will allow supply chain professionals in the healthcare commodity industry to be better prepared to maintain supply chain viability and better serve the community during pandemic disruptions of the future.
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