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Supplier Selection and Order Allocation under a Carbon Emission Trading Scheme: A Case Study from China

In implementing carbon emission trading schemes (ETSs), the cost of carbon embedded in raw materials further complicates supplier selection and order allocation. Firms have to make decisions by comprehensively considering the cost and the important intangible performance of suppliers. This paper use...

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Autores principales: Wang, Chen, Yang, Qingyan, Dai, Shufen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6982311/
https://www.ncbi.nlm.nih.gov/pubmed/31877860
http://dx.doi.org/10.3390/ijerph17010111
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author Wang, Chen
Yang, Qingyan
Dai, Shufen
author_facet Wang, Chen
Yang, Qingyan
Dai, Shufen
author_sort Wang, Chen
collection PubMed
description In implementing carbon emission trading schemes (ETSs), the cost of carbon embedded in raw materials further complicates supplier selection and order allocation. Firms have to make decisions by comprehensively considering the cost and the important intangible performance of suppliers. This paper uses an analytic network process–integer programming (ANP–IP) model based on a multiple-criteria decision-making (MCDM) approach to solve the above issues by first evaluating and then optimizing them. The carbon embedded in components, which can be used to reflect the carbon competitiveness of a supplier, is integrated into the ANP–IP model. In addition, an international large-scale electronic equipment manufacturer in China is used to validate the model. Different scenarios involving different carbon prices are designed to analyze whether China’s current ETS drives firms to choose more low-carbon suppliers. The results show that current carbon constraints are not stringent enough to drive firms to select low-carbon suppliers. A more stringent ETS with a higher carbon price could facilitate the creation of a low-carbon supply chain. The analysis of the firm’s total cost and of the total cost composition indicates that the impact of a more stringent ETS on the firm results mainly from indirect costs instead of direct costs. The indirect cost is caused by the suppliers’ transfer of part of the low-carbon investment in the product, and arises from buying carbon permits with high carbon prices. Implications revealed by the model analysis are discussed to provide guidance to suppliers regarding the balance between soft competitiveness and low-carbon production capability and to provide guidance to the firm on how to cooperate with suppliers to achieve a mutually beneficial situation.
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spelling pubmed-69823112020-02-07 Supplier Selection and Order Allocation under a Carbon Emission Trading Scheme: A Case Study from China Wang, Chen Yang, Qingyan Dai, Shufen Int J Environ Res Public Health Article In implementing carbon emission trading schemes (ETSs), the cost of carbon embedded in raw materials further complicates supplier selection and order allocation. Firms have to make decisions by comprehensively considering the cost and the important intangible performance of suppliers. This paper uses an analytic network process–integer programming (ANP–IP) model based on a multiple-criteria decision-making (MCDM) approach to solve the above issues by first evaluating and then optimizing them. The carbon embedded in components, which can be used to reflect the carbon competitiveness of a supplier, is integrated into the ANP–IP model. In addition, an international large-scale electronic equipment manufacturer in China is used to validate the model. Different scenarios involving different carbon prices are designed to analyze whether China’s current ETS drives firms to choose more low-carbon suppliers. The results show that current carbon constraints are not stringent enough to drive firms to select low-carbon suppliers. A more stringent ETS with a higher carbon price could facilitate the creation of a low-carbon supply chain. The analysis of the firm’s total cost and of the total cost composition indicates that the impact of a more stringent ETS on the firm results mainly from indirect costs instead of direct costs. The indirect cost is caused by the suppliers’ transfer of part of the low-carbon investment in the product, and arises from buying carbon permits with high carbon prices. Implications revealed by the model analysis are discussed to provide guidance to suppliers regarding the balance between soft competitiveness and low-carbon production capability and to provide guidance to the firm on how to cooperate with suppliers to achieve a mutually beneficial situation. MDPI 2019-12-22 2020-01 /pmc/articles/PMC6982311/ /pubmed/31877860 http://dx.doi.org/10.3390/ijerph17010111 Text en © 2019 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
Wang, Chen
Yang, Qingyan
Dai, Shufen
Supplier Selection and Order Allocation under a Carbon Emission Trading Scheme: A Case Study from China
title Supplier Selection and Order Allocation under a Carbon Emission Trading Scheme: A Case Study from China
title_full Supplier Selection and Order Allocation under a Carbon Emission Trading Scheme: A Case Study from China
title_fullStr Supplier Selection and Order Allocation under a Carbon Emission Trading Scheme: A Case Study from China
title_full_unstemmed Supplier Selection and Order Allocation under a Carbon Emission Trading Scheme: A Case Study from China
title_short Supplier Selection and Order Allocation under a Carbon Emission Trading Scheme: A Case Study from China
title_sort supplier selection and order allocation under a carbon emission trading scheme: a case study from china
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6982311/
https://www.ncbi.nlm.nih.gov/pubmed/31877860
http://dx.doi.org/10.3390/ijerph17010111
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AT daishufen supplierselectionandorderallocationunderacarbonemissiontradingschemeacasestudyfromchina