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An Improved Shapley Value Method for a Green Supply Chain Income Distribution Mechanism

Low-carbon development and environmental remediation are key factors for green resource-based supply chains in China. With this aim in mind, by applying game theory under uncertain market demand, this paper incorporates low-carbon development and environmental remediation into a resource-based suppl...

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Detalles Bibliográficos
Autores principales: Xu, Zhongwen, Peng, Zixuan, Yang, Ling, Chen, Xudong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6165494/
https://www.ncbi.nlm.nih.gov/pubmed/30201940
http://dx.doi.org/10.3390/ijerph15091976
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author Xu, Zhongwen
Peng, Zixuan
Yang, Ling
Chen, Xudong
author_facet Xu, Zhongwen
Peng, Zixuan
Yang, Ling
Chen, Xudong
author_sort Xu, Zhongwen
collection PubMed
description Low-carbon development and environmental remediation are key factors for green resource-based supply chains in China. With this aim in mind, by applying game theory under uncertain market demand, this paper incorporates low-carbon development and environmental remediation into a resource-based supply chain coordination model for decentralized and centralized markets. The results show that a centralized market can lead to improvement in total profit. Furthermore, based on an improved Shapley value method, a theoretical model for the centralized market income distribution mechanism is developed that incorporates three corrective risk factors, ecological investment, and technological level. Finally, a numerical analysis is conducted using a MATLAB simulation to obtain intuitive results, which, in turn, show the validity of incentive income distribution mechanisms for green supply chain development in China.
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spelling pubmed-61654942018-10-12 An Improved Shapley Value Method for a Green Supply Chain Income Distribution Mechanism Xu, Zhongwen Peng, Zixuan Yang, Ling Chen, Xudong Int J Environ Res Public Health Article Low-carbon development and environmental remediation are key factors for green resource-based supply chains in China. With this aim in mind, by applying game theory under uncertain market demand, this paper incorporates low-carbon development and environmental remediation into a resource-based supply chain coordination model for decentralized and centralized markets. The results show that a centralized market can lead to improvement in total profit. Furthermore, based on an improved Shapley value method, a theoretical model for the centralized market income distribution mechanism is developed that incorporates three corrective risk factors, ecological investment, and technological level. Finally, a numerical analysis is conducted using a MATLAB simulation to obtain intuitive results, which, in turn, show the validity of incentive income distribution mechanisms for green supply chain development in China. MDPI 2018-09-10 2018-09 /pmc/articles/PMC6165494/ /pubmed/30201940 http://dx.doi.org/10.3390/ijerph15091976 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Xu, Zhongwen
Peng, Zixuan
Yang, Ling
Chen, Xudong
An Improved Shapley Value Method for a Green Supply Chain Income Distribution Mechanism
title An Improved Shapley Value Method for a Green Supply Chain Income Distribution Mechanism
title_full An Improved Shapley Value Method for a Green Supply Chain Income Distribution Mechanism
title_fullStr An Improved Shapley Value Method for a Green Supply Chain Income Distribution Mechanism
title_full_unstemmed An Improved Shapley Value Method for a Green Supply Chain Income Distribution Mechanism
title_short An Improved Shapley Value Method for a Green Supply Chain Income Distribution Mechanism
title_sort improved shapley value method for a green supply chain income distribution mechanism
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6165494/
https://www.ncbi.nlm.nih.gov/pubmed/30201940
http://dx.doi.org/10.3390/ijerph15091976
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