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<p>Supply chain management is in a period of rapid development, and future competition in the distribution industry will be centered around competition between supply chains. Agricultural product distribution, as an important part of modern distribution, plays a positive role in ensuring people’s daily lives and improving the modernization level of agricultural distribution. Clarifying the performance of the supply chain is the key to enhancing its development level and market competitiveness. Given that most current supply chain performance evaluation studies focus on the industrial sector and there are limited methods for evaluating the performance of agricultural product distribution supply chains, this paper attempts to analyze the performance evaluation system of agricultural product supply chains centered on supermarkets. In terms of research methodology, it is based on the BP(Back Propagation) neural network and considers five aspects of the agricultural product distribution supply chain: financial situation, operational capability, growth capability, customer satisfaction, and agility. A corresponding evaluation index system is established. Finally, the performance evaluation system was applied in practice to Yonghui Supermarket and its suppliers. The findings demonstrate that the BP neural network developed in this study can effectively identify the performance indicators and overall performance level of the sample firms, yielding highly reliable results. These conclusions further illuminate beneficial pathways for enhancing the performance of agricultural-product circulation supply chains.It should also be noted that the argumentative process presented in this paper still has certain methodological limitations, lacking scientific practice and systematic reflection. Due to the limited application of computer algorithms in evaluating the performance of agricultural product circulation supply chains, this paper has not yet developed a theory related to the performance of agricultural product circulation supply chains based on its research findings, nor has it provided practical guidance for improvement. These are areas that future research should focus on enhancing and optimizing.</p>

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Research on the performance evaluation of agricultural product distribution supply chain based on BP neural network

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月22日

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  • Lu Zheng

摘要

Supply chain management is in a period of rapid development, and future competition in the distribution industry will be centered around competition between supply chains. Agricultural product distribution, as an important part of modern distribution, plays a positive role in ensuring people’s daily lives and improving the modernization level of agricultural distribution. Clarifying the performance of the supply chain is the key to enhancing its development level and market competitiveness. Given that most current supply chain performance evaluation studies focus on the industrial sector and there are limited methods for evaluating the performance of agricultural product distribution supply chains, this paper attempts to analyze the performance evaluation system of agricultural product supply chains centered on supermarkets. In terms of research methodology, it is based on the BP(Back Propagation) neural network and considers five aspects of the agricultural product distribution supply chain: financial situation, operational capability, growth capability, customer satisfaction, and agility. A corresponding evaluation index system is established. Finally, the performance evaluation system was applied in practice to Yonghui Supermarket and its suppliers. The findings demonstrate that the BP neural network developed in this study can effectively identify the performance indicators and overall performance level of the sample firms, yielding highly reliable results. These conclusions further illuminate beneficial pathways for enhancing the performance of agricultural-product circulation supply chains.It should also be noted that the argumentative process presented in this paper still has certain methodological limitations, lacking scientific practice and systematic reflection. Due to the limited application of computer algorithms in evaluating the performance of agricultural product circulation supply chains, this paper has not yet developed a theory related to the performance of agricultural product circulation supply chains based on its research findings, nor has it provided practical guidance for improvement. These are areas that future research should focus on enhancing and optimizing.