A Multi-Echelon Network Design in a Dual-Channel Reverse Supply Chain Considering Consumer Preference

The rapid development of e-commerce technologies has encouraged collection centers to adopt online recycling channels in addition to their existing traditional (offline) recycling channels, such the idea of coexisting traditional and online recycling channels evolved a new concept of a dual-channel...

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Main Authors: Peng Li, Di Wu
Format: Article
Language:English
Published: MDPI AG 2021-04-01
Series:International Journal of Environmental Research and Public Health
Subjects:
Online Access:https://www.mdpi.com/1660-4601/18/9/4760
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spelling doaj-e42793044a8e4ed198f20b93bea690ce2021-04-29T23:05:35ZengMDPI AGInternational Journal of Environmental Research and Public Health1661-78271660-46012021-04-01184760476010.3390/ijerph18094760A Multi-Echelon Network Design in a Dual-Channel Reverse Supply Chain Considering Consumer PreferencePeng Li0Di Wu1Faculty of Economics and Management, Xi’an University of Technology, Xi’an 710048, ChinaFaculty of Economics and Management, Xi’an University of Technology, Xi’an 710048, ChinaThe rapid development of e-commerce technologies has encouraged collection centers to adopt online recycling channels in addition to their existing traditional (offline) recycling channels, such the idea of coexisting traditional and online recycling channels evolved a new concept of a dual-channel reverse supply chain (DRSC). The adoption of DRSC will make the system lose stability and fall into the trap of complexity. Further the consumer-related factors, such as consumer preference, service level, have also severely affected the system efficiency of DRSC. Therefore, it is necessary to help DRSCs to design their networks for maintaining competitiveness and profitability. This paper focuses on the issues of quantitative modelling for the network design of a general multi-echelon, dual-objective DRSC system. By incorporating consumer preference for the online recycling channel into the system, we investigate a mixed integer linear programming (MILP) model to design the DRSC network with uncertainty and the model is solved using the ε-constraint method to derive optimal Pareto solutions. Numerical results show that there exist positive correlations between consumer preference and total collective quantity, online recycling price and the system profits. The proposed model and solution method could assist recyclers in pricing and service decisions to achieve a balance solution for economic and environmental sustainability.https://www.mdpi.com/1660-4601/18/9/4760dual-channel reverse supply chain (DRSC)network designconsumer preferenceε-constraint method
collection DOAJ
language English
format Article
sources DOAJ
author Peng Li
Di Wu
spellingShingle Peng Li
Di Wu
A Multi-Echelon Network Design in a Dual-Channel Reverse Supply Chain Considering Consumer Preference
International Journal of Environmental Research and Public Health
dual-channel reverse supply chain (DRSC)
network design
consumer preference
ε-constraint method
author_facet Peng Li
Di Wu
author_sort Peng Li
title A Multi-Echelon Network Design in a Dual-Channel Reverse Supply Chain Considering Consumer Preference
title_short A Multi-Echelon Network Design in a Dual-Channel Reverse Supply Chain Considering Consumer Preference
title_full A Multi-Echelon Network Design in a Dual-Channel Reverse Supply Chain Considering Consumer Preference
title_fullStr A Multi-Echelon Network Design in a Dual-Channel Reverse Supply Chain Considering Consumer Preference
title_full_unstemmed A Multi-Echelon Network Design in a Dual-Channel Reverse Supply Chain Considering Consumer Preference
title_sort multi-echelon network design in a dual-channel reverse supply chain considering consumer preference
publisher MDPI AG
series International Journal of Environmental Research and Public Health
issn 1661-7827
1660-4601
publishDate 2021-04-01
description The rapid development of e-commerce technologies has encouraged collection centers to adopt online recycling channels in addition to their existing traditional (offline) recycling channels, such the idea of coexisting traditional and online recycling channels evolved a new concept of a dual-channel reverse supply chain (DRSC). The adoption of DRSC will make the system lose stability and fall into the trap of complexity. Further the consumer-related factors, such as consumer preference, service level, have also severely affected the system efficiency of DRSC. Therefore, it is necessary to help DRSCs to design their networks for maintaining competitiveness and profitability. This paper focuses on the issues of quantitative modelling for the network design of a general multi-echelon, dual-objective DRSC system. By incorporating consumer preference for the online recycling channel into the system, we investigate a mixed integer linear programming (MILP) model to design the DRSC network with uncertainty and the model is solved using the ε-constraint method to derive optimal Pareto solutions. Numerical results show that there exist positive correlations between consumer preference and total collective quantity, online recycling price and the system profits. The proposed model and solution method could assist recyclers in pricing and service decisions to achieve a balance solution for economic and environmental sustainability.
topic dual-channel reverse supply chain (DRSC)
network design
consumer preference
ε-constraint method
url https://www.mdpi.com/1660-4601/18/9/4760
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