Extenics has unique advantages in solving contradictions by using formal models to explore the possibility of expanding things and the laws and methods of development and innovation. This paper studies the specific application of the extension strategy generation method in emergency cold chain logistics, in order to solve the problem that the emergency plan is difficult to cover in the face of an emergency. The purpose of this paper is to provide ideas for the generation of strategies to solve the contradictions of cold chain logistics in complex emergency scenarios. Giving full play to the unique advantages of extenics in solving contradictory problems, this paper analyzes the core problems, objectives and conditions of emergency cold chain logistics in four links with the case scenario of the COVID-19 pandemic outbreak, extends and generates 10 measures to form 36 schemes, and evaluates the combination schemes quantitatively and objectively using the dependent function and superiority evaluation formula. In addition, the consideration of carbon constraints is added to the selection of the scheme, and the specific plan of integrating e-commerce platform, expert guidance, establishing temporary cold storage transfer and contactless distribution is designed. The research results provide support for meeting the needs of emergency logistics schemes in different situations and optimizing the energy efficiency of the scheme while ensuring humanitarian support. At the same time, the application of extenics basic-element formal language also provides a reference for further applying artificial intelligence to the design of emergency logistics schemes.

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.