Title :
Predicting the success possibility for Green Supply chain management implementation
Author :
Malviya, Rakesh Kumar ; Kant, R.
Author_Institution :
Dept. of Mech. Eng., Sardar Vallabhbhai Nat. Inst. of Technol., Surat, India
Abstract :
The objective of this paper is to predict the success possibility for implementation of Green Supply chain management enablers (GSCMEs). The combined fuzzy decision-making trail and evaluation laboratory (DEMATEL) and fuzzy multi-criteria decision making (MCDM) methodology is used to prioritize GSCMEs for supporting the green supply chain management (GSCM) implementation. The case study of automobile ancillary is selected which is supplying component to the reputed automobile company. It has been observed that GSCME6 (top management commitment and support) has high influencing factor. If the enablers with higher influencing factor are properly concentrate during implementation, definitely the GSCM implementation will be a success. The organizations can apply the proposed method before initiating GSCM adoption to avoid wastage, time as well as money.
Keywords :
automobile industry; decision making; environmental factors; fuzzy set theory; supply chain management; DEMATEL; GSCM implementation; GSCME6; GSCMEs; MCDM methodology; automobile ancillary; fuzzy decision-making trail and evaluation laboratory; fuzzy multicriteria decision making methodology; green supply chain management enablers; success possibility prediction; top management commitment; Automobiles; Bibliographies; Green products; Industries; Organizations; Pragmatics; Supply chain management; Fuzzy DEMATEL; Fuzzy MCDM; Green Supply Chain Management; Green Supply Chain Management Enablers;
Conference_Titel :
Management of Innovation and Technology (ICMIT), 2014 IEEE International Conference on
Conference_Location :
Singapore
DOI :
10.1109/ICMIT.2014.6942481
