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| 随机需求下基于企业社会责任的多准则供应链网络均衡模型研究 | |
| 引用本文： | 金汉信,彭纪生,霍焱.随机需求下基于企业社会责任的多准则供应链网络均衡模型研究[J].软科学,2009,23(5). |
| 作者姓名： | 金汉信 彭纪生 霍焱 |
| 作者单位： | 1. 南京大学,商学院,南京,210093;南京财经大学营销与物流管理学院,南京,210046 2. 南京大学,商学院,南京,210093 3. 南京财经大学国际经贸学院,南京,210046 |
| 基金项目： | 江苏省教育厅高校哲学社会科学基金 |
| 摘 要： | 企业社会责任包括经济利益最大化、社会效用最大化和环境污染最小化,通过整合这三个决策目标,构建了随机需求下基于企业社会责任的多商品、多准则供应链网络均衡模型。运用Nash均衡及带权重系数的价值函数分析制造商间、零售商间的非合作竞争行为,描述基于企业社会责任的多目标决策行为;使用商品的销售价格、交易成本及企业社会责任等因素产生的品牌差异、消费者偏好的商品效用函数研究需求市场上产品选择问题,分别得到了供应链各层及整个网络的最优化条件,最后给出具体算例以说明企业社会责任活动对随机需求的供应链网络均衡的影响。 |
| 关 键 词： | 供应链网络 企业社会责任 社会效用 环境污染 多准则优化 随机需求 |
A Supply Chain Network Equilibrium Model Based on Corporate Social Responsibility with Multicriteria under Random Demands |
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| JIN Han-xin,PENG Ji-sheng,HUO Yan.A Supply Chain Network Equilibrium Model Based on Corporate Social Responsibility with Multicriteria under Random Demands[J].Soft Science,2009,23(5). | |
| Authors: | JIN Han-xin PENG Ji-sheng HUO Yan |
| Abstract: | Corporate social responsibility includes maximum economic benefits,maximum social utility and minimize environment pollution,this paper develops a three-level supply chain network equilibrium model with multi commodity and Multicriteria based on corporate social responsibility through integrating the three criteria under random demands.Then it analyzes competitive behavior of manufactures and retailers in a noncooperative fashion following Nash is analyzed and describs the multicriteria decision-making behavior by Nash equilibrium theory and the weighted value function.Commodity utility function of the product differentiation of brand and the consumer preferences from product price,transaction cost and corporation social responsibility are used to analyze product choice in demand market,and the optimization conditions of each level and whole network are developed by variational inequality method.At last it illustrates the model with several numerical examples. |
| Keywords: | supply chain network corporate social responsibility social utility environment pollution multicriteria optimization random demands |
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