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Ranking of Drivers for Green Manufacturing Implementation Using Fuzzy Technique for Order of Preference by Similarity to Ideal Solution Method
Author(s) -
Mittal Varinder Kumar,
Sangwan Kuldip Singh
Publication year - 2014
Publication title -
journal of multi‐criteria decision analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.462
H-Index - 47
eISSN - 1099-1360
pISSN - 1057-9214
DOI - 10.1002/mcda.1527
Subject(s) - ranking (information retrieval) , incentive , government (linguistics) , preference , order (exchange) , manufacturing , ideal solution , fuzzy logic , similarity (geometry) , industrial organization , environmental economics , business , marketing , computer science , operations research , economics , engineering , microeconomics , artificial intelligence , philosophy , physics , finance , image (mathematics) , thermodynamics , linguistics
Abstract The governments are under tremendous pressure to sustain high manufacturing growth in emerging economies. Unfortunately, the manufacturing sector consumes much energy and other resources and emits a large amount of green house gases, which increases environmental problems such as climate change and global warming. One possible solution to this problem is green manufacturing (GM) implementation in industry. However, GM implementation faces many challenges. Various motivating factors named as ‘drivers’ should be facilitated by the government and industry to make this change possible. This paper investigates the drivers for GM implementation and their ranking based on fuzzy technique for order of preference by similarity to ideal solution method using government, industry and experts perspectives. The study concluded that competitiveness, incentives, organizational resources and technology are top ranked drivers and should be facilitated by the government and industry to help implement GM. The ranking of these drivers is expected to help the government and industry to focus on few important drivers to facilitate the GM implementation with limited resources. Copyright © 2014 John Wiley & Sons, Ltd.