系统仿真学报 ›› 2016, Vol. 28 ›› Issue (11): 2747-2755.doi: 10.16182/j.issn1004731x.joss.201611015

• 仿真应用工程 • 上一篇    下一篇

O2O模式下供应链失效风险识别模型及仿真

张浩, 王明坤   

  1. 北京工商大学商学院,北京 100048
  • 收稿日期:2016-02-19 修回日期:2016-03-21 出版日期:2016-11-08 发布日期:2020-08-13
  • 作者简介:张浩(1978-),男,河北唐山,博士,副教授,研究方向为供应链系统建模与仿真。
  • 基金资助:
    国家社会科学基金(15BGL202),北京市教育委员会社科计划面上项目(SM201410011002),教育部人文社会科学青年项目(14YJC630114),“十二五”农村领域国家科技计划课题研究任务(2015BAD18B01),2016年研究生科研能力提升计划

Failure Risk Identification Model and Simulation of Supply Chain Under O2O E-commerce Model

Zhang Hao, Wang Mingkun   

  1. Business School, Beijing Technology and Business University, Beijing 100048, China
  • Received:2016-02-19 Revised:2016-03-21 Online:2016-11-08 Published:2020-08-13

摘要: 电子商务O2O模式的市场规模不断扩大,如何有效防范O2O模式下供应链失效的风险,成为确保电商O2O良好运营的关键。对O2O模式下供应链失效风险的关键影响要素进行研究,并根据各影响要素之间的因果关系构建O2O模式下供应链失效风险识别的贝叶斯网络结构,运用三角模糊数方法获取贝叶斯网络条件概率值。以生鲜农产品供应链为例,构建O2O模式下供应链失效风险识别模型,并进行仿真研究。

关键词: 供应链, 贝叶斯网络, 失效风险, 三角模糊数, 条件概率

Abstract: With the expansion of Online to Offline (O2O) e-commerce market size, how to effectively prevent the occurrence of supply chain failure risk becomes the key factor to ensure O2O e-commerce market to operate well. The key influencing factors of the supply chain failure risk were analyzed and sorted. Based on causal relationship between various influencing factors, Bayesian network was constructed to analyze crucial factors. The application of triangle fuzzy number was introduced to gather value of conditional probability of Bayesian network. A case study on the failure risk identification model of fresh agricultural product supply chain under O2O model was made by using simulation software.

Key words: supply chain, Bayesian network, failure risk, triangular fuzzy-number, conditional probability

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