AN INNOVATIVE APPROACH TO EVALUATE GREEN SUPPLY CHAIN MANAGEMENT (GSCM) DRIVERS BY USING INTERPRETIVE STRUCTURAL MODELING (ISM)
Green supply chain management (GSCM) comprises of the Manufacturing process that minimizes waste and pollution. It also integrates environmental thinking into supply chain management; from conceptual product design to the delivery of final product to the consumers, and also involves end-of-life mana...
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Published in | International Journal of Innovation and Technology Management (IJITM) Vol. 8; no. 2; pp. 315 - 336 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
World Scientific Publishing Company
01.06.2011
World Scientific Publishing World Scientific Publishing Co. Pte. Ltd |
Series | International Journal of Innovation and Technology Management (IJITM) |
Subjects | |
Online Access | Get full text |
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Summary: | Green supply chain management (GSCM) comprises of the Manufacturing process that minimizes waste and pollution. It also integrates environmental thinking into supply chain management; from conceptual product design to the delivery of final product to the consumers, and also involves end-of-life management. Many business organizations have implemented GSCM and many more are in the process to put into practice. Its implementation is supported by few factors which are known as GSCM drivers. These drivers could assist in adoption of Green supply chain management. The aim of this paper is to develop a relationship amongst the identified GSC drivers; including management commitments, regulatory pressure etc. This paper is also helpful in understanding mutual influences of drivers, it helps in identifying those drivers which support other drivers as well as those drivers which are most influenced by other drivers (dependent) using interpretive structural modeling (ISM) and it classifies these drivers depending upon their driving and dependency on power. |
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Bibliography: | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23 ObjectType-Article-1 ObjectType-Feature-2 |
ISSN: | 0219-8770 1793-6950 1793-6950 |
DOI: | 10.1142/S0219877011002453 |