SupplyChainDCL: Enhancing Resilience, Optimizing Efficiency, and Mitigating Disruption Risks in Supply Chain Networks

This award will enhance national welfare by providing a systematic framework to analyze the efficiency and resilience of demand and supply networks. These systems are challenging to analyze due to the complex interdependencies among firms in the network, which adjust their decision-making processes collectively and strategically in response to both idiosyncratic and systemic shocks. The project will develop novel tools and measures for assessing the impact of risk mitigation plans against supply and demand shocks in the network. The framework will elucidate the mechanisms by which supply shortages of specific goods and services during periods of distress can lead to price spikes and increase the fragility of the supply chain network. For instance, the project will help understand how a global semiconductor shortage can cause significant price surges in the U.S. market for second-hand cars, or how an unexpected surge in demand for hand sanitizers during the pandemic led to widespread supply shortages, impacting the industry and its related sectors. This award will also provide research opportunities for graduate students, equipping them with the tools, background, and expertise to advance research in this area. The project will develop a dynamic decision-making framework to quantify the trade-offs between efficiency and resilience within supply chain networks and provide an empirical analysis of supply chain fragility. This analysis aims to assess how diversification strategies can mitigate risks associated with supply chain vulnerabilities. The research will leverage, extend, and specialize tools from dynamic games, risk management, optimization, and network theory to incorporate the incentives of firms facing information and technological constraints in establishing cost-effective demand-supply relationships and managing risks against supply and demand shocks. The framework will explicitly model both preventive actions taken by firms to hedge against potential future shocks and corrective actions implemented in response to significant disruptions. The project will lead to the development of game-theoretical algorithms for determining optimal firms' levels of investment in production capacity and for final good producers to enter into competitive risk-sharing agreements with intermediate good producers to meet unanticipated demand and hedge against production shocks. The resulting analysis will quantify the conditions under which market-based supply networks are inherently fragile, particularly when these networks prioritize routine operational efficiency over systemic robustness. Additionally, the project will explore whether public institutions can reduce inefficiencies and facilitate outcomes superior to those achieved through decentralized market operations by implementing data-driven control policies. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.