Title : ( Application of green supply chain management in the oil Industries: Modeling and performance analysis )
Authors: ahmad ghorbanpour , Alireza Pooya , Zahra Naji Azimi ,Access to full-text not allowed by authors
Abstract
Environmental concerns relating to production affairs have made various organizations use green prac-tices in different processes of supply chain, because the green supply chain management (GSCM) is con-sidered as an important organizational philosophy to decrease environmental risks and as a preventiveapproach in order to increase environmental performance and achievement of competitive advantagesfor organizations. The purpose of the present article is to design an interactive model for the practicesof GSCM and its application to clustering oil industries for analyzing their green performance.Therefore, the literature was studied and a total of fifteen practices were obtained using experts’ opinionsin academic and oil industry professionals. In next, the fuzzy interpretative structural modeling (FISM)approach was utilized so as to determine the relationship between the practices through consideringthe linguistic ambiguities of judgments and designing the structural model. The existing relationshipswithin the structural model were studied and tested by means of structural equation modeling (SEM).After that, the relative importance of each practice was calculated by applying fuzzy analysis networkprocess (FANP). In the next, the oil industries were categorized in two clusters using the K-means algo-rithm aggregated to the particle swarm optimization algorithm. Results of the present study showed that‘‘legal requirements and regulations”, ‘‘intra-organizational environmental management”, ‘‘green design”and ‘‘green technology” are of root and influential practices with relatively more importance than others;in addition, it was cleared that the first cluster industries have high performance whereas the secondones have medium performance from the viewpoint of considering the practices of GSCM. Finally, the dis-criminant function designed to forecasting environment performance of the oil industries and member-ship to clusters for each of them
Keywords
Green Supply Chain Management Oil industries Fuzzy interpretative structural modeling Kmeans Particle swarm optimization Clustering Discriminant analysis@inproceedings{paperid:1084726,
author = {Ghorbanpour, Ahmad and Pooya, Alireza and Naji Azimi, Zahra},
title = {Application of green supply chain management in the oil Industries: Modeling and performance analysis},
booktitle = {Materials Today: Proceedings},
year = {2021},
location = {ENGLAND},
keywords = {Green Supply Chain Management Oil industries Fuzzy interpretative structural modeling Kmeans Particle swarm optimization Clustering Discriminant analysis},
}
%0 Conference Proceedings
%T Application of green supply chain management in the oil Industries: Modeling and performance analysis
%A Ghorbanpour, Ahmad
%A Pooya, Alireza
%A Naji Azimi, Zahra
%J Materials Today: Proceedings
%D 2021