斯塔克伯格竞赛
供应链
风险厌恶(心理学)
供应链风险管理
收入分享
帕累托原理
微观经济学
供应链管理
业务
偏爱
风险管理
决策模型
风险分析(工程)
服务管理
运筹学
计算机科学
产业组织
经济
运营管理
期望效用假设
营销
数理经济学
机器学习
工程类
财务
作者
Yuhong Wang,Xiaoqi Sheng,Yudie Xie
标识
DOI:10.1108/cms-10-2021-0454
摘要
Purpose This study aims to establish a centralized decision-making game model and manufacturer-led Stackelberg game model based on factors of risk aversion of supply chain members and product greenness. The research aims to study whether the introduction of the “cost + risk sharing” contract affects coordination of this type of green supply by calculating the optimal decision of each mode. Design/methodology/approach This research designs a supply chain model under centralized and decentralized decision-making. This model uses the Stackelberg game to calculate the optimal decision under decentralized decision-making to evaluate the effect of a green supply chain and then analyze the “cost + risk sharing” contract and the degree of coordination of the supply chain. A sensitivity analysis is conducted on the centralized mode for the impact of variables on the supply chain. Findings This research finds a double marginalization effect in decentralized decision-making, and the risk aversion coefficient plays a decisive role in the utility of supply chain members. The specific range of risk- and cost-sharing factors allows supply chain members to achieve Pareto improvements and provides decision-making based on the corresponding management strategies according to each other’s risk preference degree. Research limitations/implications The influence of each variable on the green supply chain in the centralized mode is studied by MATLAB numerical simulation. It provides reference for green supply chain members to formulate corresponding management strategies according to each other's risk preference degree. Originality/value This research innovatively considers manufacturers and retailers to explore the market demand for product greenness. It introduces a novel “cost + risk sharing” contract to coordinate the green supply chain.
科研通智能强力驱动
Strongly Powered by AbleSci AI