A Bayesian network model for the reliability control of fresh food e-commerce logistics systems

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This paper focuses on the reliability of intelligent logistics for fresh food e-commerce. Based on the development of fresh food e-commerce, this paper analyses the factors that influence the reliability of fresh food logistics from the aspects of information technology, facilities and equipment, personnel operation and external environment. A Bayesian network is used to analyse the influence of each factor on system reliability, and the degree of importance of each factor is calculated. Based on the importance of each influential factor in fresh food e-commerce logistics systems, an intelligent logistics model for reliability control of fresh food is established. The purpose of this model is to improve the economic efficiency and the intelligent level of the fresh food e-commerce logistics system on the premise of meeting the system reliability requirements. Finally, simulation results show that the developed intelligent logistics reliability control model can significantly improve the reliability of fresh food e-commerce logistics systems, and provide practical suggestions for fresh food e-commerce enterprises.

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This study was funded by a Project of the National Key R&D Program of China (2017YFC1600605), a Beijing Project of Philosophy and Social Science (17GLB013), a Project of the National Social Science Foundation of China (15BGL202), a Beijing's “High-grade, Precision and Advanced Discipline Construction (Municipal)-Business Administration” Project (No. 19005902053) and a project of Beijing Talents foundation of Organization Department of Beijing Municipal Committee of the CPC.

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Correspondence to Qian Zhang.

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Communicated by X. Li.

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Zhang, H., Liu, Y., Zhang, Q. et al. A Bayesian network model for the reliability control of fresh food e-commerce logistics systems. Soft Comput (2020) doi:10.1007/s00500-020-04666-5

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  • Fresh food
  • Reliability
  • Bayesian network
  • e-commerce logistics