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基于订单农业的农产品供应链帮扶策略研究

冯春 颜菁 何征 冯宇杰

工业工程2024,Vol.27Issue(4):70-81,12.
工业工程2024,Vol.27Issue(4):70-81,12.DOI:10.3969/j.issn.1007-7375.230082

基于订单农业的农产品供应链帮扶策略研究

Supporting Strategies of Agricultural Supply Chains Based on Contract Farming

冯春 1颜菁 2何征 2冯宇杰2

作者信息

  • 1. 西南交通大学 交通运输与物流学院,四川 成都 610031||西南交通大学 综合交通大数据应用技术国家工程实验室,四川 成都 610031
  • 2. 西南交通大学 交通运输与物流学院,四川 成都 610031
  • 折叠

摘要

Abstract

In order to study the supply chain support decisions of the government and retailers for agricultural products,three contract farming support models are established considering government production subsidies and retailer investment in poverty alleviation efforts,including the government subsidy model(GS model),the retailer poverty alleviation model(RH model),and the government-retailer joint support model(GR model).Through the comparative analysis of profit relationships and profit increment of each party in the three models,the optimal support decisions of the government and retailers are obtained.Results show that if the government provides production subsidies only to high-cost farmers,it is necessary for retailers to devote poverty alleviation efforts.Conversely,if retailers invest in poverty alleviation efforts for all farmers,the government should then provide production subsidies.Retailers poverty alleviation programs can consistently benefit all farmers.In a consumer-sensitive market,government subsidies provided later can benefit all farmers.In addition,in a market with low consumer sensitivity,the government needs to subsidize first,followed by retailer investment in poverty alleviation efforts.In a consumer-sensitive market,retailers are required to invest in poverty alleviation efforts first,followed by government subsidies.

关键词

Stackelberg博弈/政府补贴/零售商扶贫努力/企业社会责任

Key words

Stackelberg game/government subsidies/retailer poverty alleviation efforts/corporate social responsibility

分类

管理科学

引用本文复制引用

冯春,颜菁,何征,冯宇杰..基于订单农业的农产品供应链帮扶策略研究[J].工业工程,2024,27(4):70-81,12.

基金项目

国家社会科学基金资助项目(17BGL085) (17BGL085)

工业工程

OACHSSCDCSTPCD

1007-7375

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