Abstract

Evaluating supply chain performance of fresh agricultural products is one of the key techniques and a research hotspot in supply chain management and in fields related. The paper designs a new evaluation indicator system and presents a new model for evaluating supply chain performance of fresh agriculture product companies. First, based on analyzing the specific characteristics of the supply chain performance evaluation of fresh agriculture products, the paper designs a new evaluation indicator system including external and internal performance. Second, some improvements, such as adjusting dynamic strategy and the value of momentum factor, are taken to speed up calculation convergence and simplify the structure and to improve evaluating accuracy of the original BP evaluation model. Finally the model is realized with the data from certain supply chains of three fresh agriculture product companies and the experimental results show that the algorithm can improve calculation efficiency and evaluation accuracy when used for supply chain performance evaluation of fresh agriculture product companies practically.

Keywords:

BP neural network, evaluation indicator system, fresh agriculture products, performance evaluation, supply chain management,

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Competing interests

The authors have no competing interests.

Open Access Policy

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Copyright

The authors have no competing interests.