The traditional performance evaluation method, which is mainly based on financial indexes, is no longer applicable to the current dynamic, complex, and coordinated evaluation of the service quality of fresh agricultural produce supply chains. Comprehensive evaluations regarding the quality of coordination-based supply chain services are now required. Specific analyses of index weights, the identification of potential problems, the exploration of the best solutions, and efforts to improve the current situation—regarding the circulation of fresh agricultural products—are also required. By carrying out this research, this paper aims to construct a coordination-based service quality evaluation index system for the fresh agricultural produce supply chain platform. The evaluation system that was created covered the four dimensions involved in platform supply chain coordination. These dimensions are capital flow, logistics, business flow, and information flow. On this basis, this study designed a survey questionnaire to collect data to evaluate customer service quality satisfaction. The research used AHP and the Fuzzy Comprehensive Evaluation method to calculate and analyze indexes and models in the “Fresh Networking” project. Furthermore, this paper proposed a sensitivity analysis model of MCDM evaluation indexes and their weights. In order to verify whether the numerical analysis method was suitable for use in the MCDM evaluation system, in this paper, the sensitivity analysis process of the indexes and their weights was introduced in the evaluation of the “Fresh Networking” project. The evaluation results may reflect the real quality of service in the “Fresh Network” supply chain. The final conclusion to be drawn from this paper is that capital flow is the most sensitive weight, which means that it should be designed and implemented in accordance with optimization-based decisions. The novelty of this paper lies in: (1) the proposal of a coordination-based service quality evaluation index system which includes four dimensions: capital flow, logistics, business flow, and information flow; (2) the design of a research questionnaire for data collection; and (3) the introduction of an improved sensitivity analysis method for the MCDM index. The results presented in this paper will enrich the theoretical research related to MCDM in supply chain evaluations. The results of the analysis can be used to guide supply chain decision makers to make optimization decisions accordingly, which will ensure overall benefits in terms of supply chain coordination, improving the capacity of preservation services, and loss reduction.

In response to the evolving pharmaceutical supply chain market, which is shifting from a seller’s to a buyer’s market, this study introduces an innovative decision-making model that addresses the volatility in output and demand. Our primary innovation lies in the development of a “revenue-sharing plus margin” collaborative decision-making optimization model, designed to enhance supply chain coordination amidst uncertainty. By establishing a revenue function, we propose a coordinated approach that leverages both revenue-sharing coefficients and profit margins to achieve Pareto improvements for supply chain partners. Through numerical analysis, we identify an optimal value range for the model’s parameters, demonstrating the model’s efficacy in balancing the expected returns for both suppliers and retailers. The study’s contributions are threefold: (1) the introduction of a novel decision-making model tailored to the pharmaceutical supply chain, (2) the provision of a clear framework for comparing collaborative versus decentralized decision-making outcomes, and (3) the empirical validation of the model through case studies, showcasing its superiority in overall supply chain efficiency. This research significantly extends the current literature by providing a nuanced understanding of how supply chain coordination can be optimized under conditions of uncertainty. The findings underscore the importance of collaborative decision-making in achieving supply chain stability and offer practical insights for supply chain management in the pharmaceutical industry.

Medicine occupies an important position in people’s lives, and its safety and effectiveness are directly related to people’s lives and health. In recent years, with the frequent occurrence of unqualified vaccines, quality control in drug transportation has been paid more and more attention. Therefore, this paper constructs a tripartite evolutionary game model composed of government, pharmaceutical enterprises, and logistics enterprises and models behavioral strategies. The interaction between the two and the influence of different parameters on the evolution are simulated and analyzed. The results show that implementing a government punishment mechanism, inter-firm revenue sharing and drug failure rate will have different impacts on the outcome of the evolutionary stability strategy of pharmaceutical enterprises and logistics enterprises. These conclusions not only enrich the theoretical literature on factors affecting the decision-making factors of pharmaceutical enterprises and logistics enterprises to ensure drug quality but also provide useful references for improving government policies.