The traditional performance evaluation method, which is mainly based on financial indexes, is no longer applicable to the current dynamic, complex, and coordinated evaluation of the service quality of fresh agricultural produce supply chains.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.
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