Abstract
Depending on the significant increase in the consumption and as a result in the production has caused some problems besides its utilities. One of the biggest concerns at this point is the adverse environmental effects of this growth. Hence, most of the companies take into account the environmental considerations during the design and implementation of their business facilities within their supply chains. As a result of these developments, the attempt to design supply chains greener has increased both practically and theoretically. Various studies have been performed dealing with green supply chains. However, in this study, it is focused on the greenness assessment of supply chains under four stages including inbound logistics, in-plant logistics, outbound logistics and reverse logistics. Different from the few studies in the literature, intuitionistic fuzzy (IF) approach which enables to handle fuzziness and hesitancy is used within DEMATEL and ANP techniques to measure supply chain greenness. The related steps are explicitly provided within the proposed methodology. In general, firstly the main dimensions of greenness are determined with the related indicators. Then, regarding the dependency between the dimensions, the relation network is obtained via IF-DEMATEL by taking the evaluations of supply chain experts. Afterwards, based on the network diagram and expert judgments, the importance weights of dimensions are provided with IF-ANP and used in the developed greenness scoring system. An application in a firm’s supply chain is performed to demonstrate the validation of the proposed methodology and consequently, the greenness score is obtained.
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Topgul, M.H., Kilic, H.S., Tuzkaya, G. (2020). Supply Chain Greenness Assessment Based on Intuitionistic Fuzzy Approaches. In: Kahraman, C., Cebi, S., Cevik Onar, S., Oztaysi, B., Tolga, A., Sari, I. (eds) Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making. INFUS 2019. Advances in Intelligent Systems and Computing, vol 1029. Springer, Cham. https://doi.org/10.1007/978-3-030-23756-1_59
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