Sustainable Blood Supply Chain Modeling with Government Intervention: A Three-Level Stackelberg Programming Approach

Abstract

The present study aimed to develop and evaluate a sustainable blood supply chain model incorporating government intervention through a three-level Stackelberg programming framework to improve rare blood collection, reduce shortages and waste, and enhance economic, social, and environmental performance under demand uncertainty. This applied quantitative study employed a mathematical optimization approach based on game theory and mixed-integer linear programming (MILP). A three-level Stackelberg structure was developed in which the government acted as the strategic leader, the Iranian Blood Transfusion Organization (IBTO) and provincial blood centers served as first-level followers, and distribution centers functioned as second-level followers. The model explicitly incorporated platelet perishability, rare blood group incentives, demand uncertainty, and sustainability objectives. Four categories of demand, including urgent-fresh, non-urgent-fresh, urgent-non-fresh, and non-urgent-non-fresh requests, were considered. Historical operational data from the Iranian Blood Transfusion Organization covering March 2022 to March 2023 were used for model calibration. Uncertainty was represented through ten stochastic demand scenarios generated using Latin Hypercube Sampling. The bilevel follower problem was transformed into a single-level formulation using Karush–Kuhn–Tucker conditions and optimized Big-M linearization. The resulting MILP model was solved using IBM ILOG CPLEX 22.1 with a 1% optimality gap. The results demonstrated that government incentives substantially improved the collection of rare Rh− platelet units, increasing collection volume from 5 units in the baseline scenario to 43 units under optimal conditions, representing a 760% improvement. The model reduced urgent-fresh demand shortages from 30% to 5% (83% reduction) and non-urgent-fresh shortages from 25% to 8% (68% reduction). Platelet waste decreased by 61% when shelf life increased from three to five days. Compared with the non-intervention scenario, the proposed framework reduced operational costs by 32%, decreased biological waste by 63%, and increased the social service level from 61% to 91%. Sensitivity analyses revealed diminishing marginal returns for government budgets beyond approximately 60 units. The proposed three-level Stackelberg model outperformed benchmark optimization approaches in terms of cost efficiency, shortage reduction, sustainability performance, and service quality. The findings indicate that integrating government intervention, hierarchical decision-making, demand prioritization, and sustainability objectives within a unified three-level Stackelberg framework significantly enhances blood supply chain performance. The proposed model effectively balances economic efficiency, social welfare, and environmental sustainability while maintaining computational tractability for large-scale healthcare networks. The results support the implementation of targeted government incentive policies and coordinated multi-echelon planning strategies to improve the resilience, effectiveness, and sustainability of blood supply systems.