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Analyzing the drivers of green manufacturing with fuzzy approach

Green issues have gained more importance in contemporary globalization. Recent years have seen manufacturing processes understand the green issues due to the social and environmental concerns involved. The drivers of green manufacturing, however, have not been thoroughly investigated. Thus, this pap...

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Bibliographic Details
Published in:Journal of cleaner production 2015-06, Vol.96, p.182-193
Main Authors: Govindan, Kannan, Diabat, Ali, Madan Shankar, K.
Format: Article
Language:English
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Summary:Green issues have gained more importance in contemporary globalization. Recent years have seen manufacturing processes understand the green issues due to the social and environmental concerns involved. The drivers of green manufacturing, however, have not been thoroughly investigated. Thus, this paper investigates the responsibility of identifying twelve common drivers of green manufacturing from the combined assistance of existing literature, industrial managers, and expert opinion in the relevant field. A questionnaire on these common drivers was circulated among 120 leading firms in south India, and aided by their replies; a pair-wise comparison was made among the drivers. The pair-wise comparison is used as an input data and the drivers were analyzed on its basis. The analysis resorted to the use of a fuzzy Multi Criteria Decision Making (MCDM) approach. The obtained results are validated by a two-stage sensitivity analysis, namely: (1) using different de-fuzzification methods that are further evaluated through the Spearman coefficient and (2) assigning varying weight to the essential top priority drivers of green manufacturing among all common drivers. This study helps firms to stimulate an essential driver for quick and better adoption of green manufacturing. Finally, the paper concludes with some insight into the future path of green manufacturing in developing countries and an acknowledgment of the study's own limitations. •Common drivers of green manufacturing are identified.•A two stage framework is proposed with fuzzy approach to rank the drivers.•Results are validated through different defuzzification methods and sensitivity analysis was done.
ISSN:0959-6526
1879-1786
DOI:10.1016/j.jclepro.2014.02.054