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Erschienen in: Clean Technologies and Environmental Policy 1/2015

01.01.2015 | Original Paper

Constructing a network model to rank the optimal strategy for implementing the sorting process in reverse logistics: case study of photovoltaic industry

verfasst von: Jung-Tang Hsueh, Chun-Yueh Lin

Erschienen in: Clean Technologies and Environmental Policy | Ausgabe 1/2015

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Abstract

This study constructs a network model to rank the alternatives for implementing the sorting process of reverse logistics (RL) in the downstream photovoltaic industry. The RL procedure includes three major stages: (1) collecting, (2) sorting, and (3) reprocessing. The proposed model combines the benefits, opportunities, costs, and risks (BOCR) and the network concept to construct a framework for ranking the optimal alternatives for the sorting process. First, the BOCR and the network concept are used to define the relationship with four perspectives on RL. Second, the relative weights of the evaluative criteria are determined by using the Analytic Network Process. Finally, a ranking of the optimal alternative for implementing the sorting process is calculated, which can assist the photovoltaic industry’s downstream decision makers in evaluating RL activity. The results show that the most important perspectives concerning RL in sorting process are “Benefits” and “Costs”; the most crucial of the 20 criteria are “Reducing production cost by using recycled materials” and “Labor cost,” and the optimal alternative in implementing the sorting process is “Outsourcing.” Therefore, when a photovoltaic industry downstream company applies this model, the company will find that its optimal alternative for waste disposal is outsourcing treatment at the sorting stage.

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Metadaten
Titel
Constructing a network model to rank the optimal strategy for implementing the sorting process in reverse logistics: case study of photovoltaic industry
verfasst von
Jung-Tang Hsueh
Chun-Yueh Lin
Publikationsdatum
01.01.2015
Verlag
Springer Berlin Heidelberg
Erschienen in
Clean Technologies and Environmental Policy / Ausgabe 1/2015
Print ISSN: 1618-954X
Elektronische ISSN: 1618-9558
DOI
https://doi.org/10.1007/s10098-014-0770-3

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