Healthcare is considered one of the necessities for sustaining life. However, frequent emergencies raise the risk of supply chain disruption, seriously threatening people’s lives and health security. Therefore, building a resilient healthcare supply chain is an important initiative to manage the healthcare crisis effectively. Based on the secondary supply chain formed by medical supply manufacturers and retailers, this paper constructs an evolution game model of resilience investment decisions under the non-disruption and disruption symmetry scenarios of the supply chain and analyzes the stabilization strategies employed by both parties based on their asymmetry strategy choices. Subsequently, the numerical simulation is used to analyze the impact of various parameters on the evolutionary results and their evolutionary trends. The results of the study show that additional benefits from resilience investment, potential costs, disruption losses, market encroachment revenue, “free-rider” benefits, additional benefit increase coefficient, resilience investment reduction coefficient, disruption loss reduction coefficient, additional unit cost reduction coefficient, and market encroachment revenue coefficient all influence the resilience investment decisions. Finally, based on the simulation results, specific recommendations are formulated to improve the resilience of the healthcare supply chain.

In the context of supply disruption, having a resilient supply chain is crucial for the survival and growth of enterprises. It is also essential for gaining a competitive advantage in a turbulent environment. Enterprises need to invest in supply chain resilience to better deal with future uncertainties. This paper constructs a Stackelberg game model with the manufacturer as the leader and the retailer as the follower. We explored how supply chain-related factors under supply interruption risk affect supply chain resilience investment, and studied how to choose supply chain coordination strategies to improve the effectiveness of manufacturer capacity recovery and mutual profits in the context of supply interruption. The study also analyzes the asymmetrical impact of changes in product order quantity, supply disruption probability, and the capacity recovery coefficient on retailer decision-making and the profits of supply chain members. The results indicate that manufacturer profits are negatively correlated with supply disruption probability, while retailer profits are positively correlated with supply disruption probability when product order quantities are low and negatively correlated when product order quantities are high. The supply chain resilience investment is positively correlated with the supply disruption probability. Furthermore, the effectiveness of the cost-sharing contract is closely related to product order quantity and supply disruption probability. When the product order quantity $d<{\alpha }_L{\displaystyle \frac{-c[\left(1-\xi \right)a_L+\xi a_H]+s{\alpha }_H\xi +w{\alpha }_L(1-\xi )}{k}}$ or ${\alpha }_H{\displaystyle \frac{-c[\left(1-\xi \right)a_L+\xi a_H]+s{\alpha }_H\xi +w{\alpha }_L(1-\xi )}{k}}<d<{\displaystyle \frac{{\alpha }_H[\left(1-\xi \right)a_L+\xi a_H](w-c)}{k}}$, manufacturers can withstand the risk of supply interruption by investing in supply chain resilience alone. But when the product order quantity is ${\alpha }_L{\displaystyle \frac{-c[\left(1-\xi \right)a_L+\xi a_H]+s{\alpha }_H\xi +w{\alpha }_L(1-\xi )}{k}}<d<{\alpha }_H{\displaystyle \frac{-c[\left(1-\xi \right)a_L+\xi a_H]+s{\alpha }_H\xi +w{\alpha }_L(1-\xi )}{k}}$ and ${\displaystyle \frac{{\alpha }_H[\left(1-\xi \right)a_L+\xi a_H](w-c)}{k}}<d$, the use of cost-sharing contracts is more effective. Additionally, when the sensitivity analysis is conducted, the capacity recovery coefficient positively correlates with supply chain profits in a decentralized mode. However, under the cost-sharing contract mode, it exhibits a U-shaped fluctuation pattern, indicating that the impact of improving capacity recovery efficiency on the profits of both parties is not symmetrical and linear. As $\xi$ approaches 0.5, the profits of manufacturers and retailers decrease. Instead, it undergoes an initial decline followed by a subsequent increase, highlighting the nonlinear benefits of capacity recovery strategies under the cooperative approach.

Fresh produce, as a primary source of nutrition, plays a pivotal role in daily life. However, the unique characteristics of fresh produce—such as perishability, widespread production, short shelf life, long distribution cycles, and high volatility in both supply and demand—render the fresh produce supply chain particularly vulnerable to disruptions. These vulnerabilities not only impact daily consumption but also pose significant challenges to the operational efficiency of enterprises. Enhancing the fresh produce supply chain resilience is crucial for businesses to effectively mitigate risks, ensure consistent product quality, and maintain overall supply chain stability. Nevertheless, there remains a lack of clear, process-oriented guidance for developing resilience improvement strategies within the fresh agricultural product sector. Specifically, there is insufficient clarity regarding which elements should be prioritized for investment in resilience strategies, how these strategies should be formulated, and the absence of a theoretically sound framework to guide the strategic development of supply chain resilience improvements. To address the lack of scientific, quantitative, efficient, and specific processes for generating supply chain resilience improvement strategies in fresh agricultural product enterprises, this study adopts the framework of extensible primitive theory. Initially, an evaluation index system for the fresh produce supply chain is constructed, and the extendable evaluation method is employed to assess the resilience level of fresh agricultural product enterprises. This approach facilitates the identification of the key challenges that must be addressed to enhance supply chain resilience and helps generate strategies that reconcile previously incompatible issues. Next, the core objectives and conditions underlying the resilience incompatibilities in fresh agricultural product enterprises are quantitatively analyzed. Finally, the expansion transformation of both target and condition primitives is carried out to derive the optimal strategy for improving supply chain resilience. The study uses company M as a case example, where the evaluation results indicate that the company’s supply chain resilience is rated as “good”. However, several issues were identified, including inefficiencies in product supply, limited financing capacity, low enterprise visibility, and inadequate production and processing equipment. Based on these findings, the paper proposes a series of optimization strategies aimed at improving the fresh produce supply chain resilience through extension transformation.