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考虑政府补贴和过度自信的供应链运营决策研究

Research on Supply Chain Operation Decision Considering Government Subsidies and Enterprise Overconfidence
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摘要 政府补贴与企业过度自信对供应链运营决策有着重要影响。文章以一个制造商和一个零售商组成的供应链为研究对象,构建了Stackelberg博弈模型。在政府对制造商的产品进行补贴的背景下,分别探究了双方均理性、仅制造商过度自信、仅零售商过度自信和双方均过度自信这四种情形下供应链的运营决策特征及变化趋势。以期得到经济和管理启示,并向企业与政府提出合理的建议。研究发现:(1)在考虑政府补贴制造商的情形下,当产品市场情况良好时,制造商或零售商任意一方过度自信都会降低自身的利润,提高对方的利润;当市场情况较差时,过度自信反而会对供应链成员自身的利润有益,并减少对方的收益。(2)政府补贴会对供应链成员利润产生影响。政府应在市场情况良好时降低补贴强度,在市场情况较差时提高补贴强度。 Government subsidies and enterprise overconfidence have an important impact on supply chain operation decisions.This paper takes a supply chain composed of a manufacturer and a retailer as the research object,and constructs a Stackelberg game model.Under the background that the government subsidizes the manufacturer's products,this paper explores the operation decision-making characteristics and change trends of the supply chain under the four situations:Both sides are rational,only the manufacturer is overconfident,only the retailer is overconfident and both sides are overconfident.This paper hopes to get economic and management enlightenment,and put forward reasonable suggestions to enterprises and the government.The results show that:(1)In the case of government subsidies to manufacturer,when the product market is good,the overconfidence of either manufacturer or retailer will reduce their own profits and increase the profits of the other;when the market situation is poor,the overconfident supply chain members'own profits will increase and the other party's profits will decrease.(2)Government subsidies will have an impact on the profits of supply chain members.The government should reduce the subsidy intensity when the market condition is good,and increase the subsidy intensity when the market condition is poor.
作者 方宇 何娣 FANG Yu;HE Di(School of Management,Jiangsu University,Zhenjiang 212013,China)
出处 《物流科技》 2023年第13期103-107,共5页 Logistics Sci-Tech
关键词 供应链决策 政府补贴 过度自信 STACKELBERG博弈 supply chain decision government subsidies overconfidence Stackelberg game
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