Green Manufacturing: An Assessment of Enablers’ Framework Using ISM-MICMAC Analysis

IF 1.8 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
S. Ali
{"title":"Green Manufacturing: An Assessment of Enablers’ Framework Using ISM-MICMAC Analysis","authors":"S. Ali","doi":"10.2478/fcds-2022-0015","DOIUrl":null,"url":null,"abstract":"Abstract Manufacturing is one of the biggest drivers of a country’s economic growth. Nevertheless, due to globalization and flourishing consumer markets, the technological influx in manufacturing evolution poses a significant threat to climate change. To deal with the situation, green manufacturing came forward to play a vital role in lowering the impact of mass production on the global environment. The qualitative research based on expert opinion is used to have viewpoints for the implementation of green manufacturing based on green supply chain manufacturing (GSCMEs) enablers. The study, in this regard, focuses on exploring the key enablers adopted by the manufacturers to embrace green practices by using framework based on Interpretative Structural Modelling and Cross-Impact Multiplication Applied to Classification (MICMAC) analysis. Results indicate that economic constraints and the regulatory framework have high driving power and less dependency power. Researchers provide managers with a new outlook on the future towards building an eco-friendly supply chain and gaining a competitive edge over their competitors.","PeriodicalId":42909,"journal":{"name":"Foundations of Computing and Decision Sciences","volume":"47 1","pages":"271 - 290"},"PeriodicalIF":1.8000,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Foundations of Computing and Decision Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2478/fcds-2022-0015","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0

Abstract

Abstract Manufacturing is one of the biggest drivers of a country’s economic growth. Nevertheless, due to globalization and flourishing consumer markets, the technological influx in manufacturing evolution poses a significant threat to climate change. To deal with the situation, green manufacturing came forward to play a vital role in lowering the impact of mass production on the global environment. The qualitative research based on expert opinion is used to have viewpoints for the implementation of green manufacturing based on green supply chain manufacturing (GSCMEs) enablers. The study, in this regard, focuses on exploring the key enablers adopted by the manufacturers to embrace green practices by using framework based on Interpretative Structural Modelling and Cross-Impact Multiplication Applied to Classification (MICMAC) analysis. Results indicate that economic constraints and the regulatory framework have high driving power and less dependency power. Researchers provide managers with a new outlook on the future towards building an eco-friendly supply chain and gaining a competitive edge over their competitors.
绿色制造:运用ISM-MICMAC分析的推动者框架评估
制造业是一个国家经济增长的最大推动力之一。然而,由于全球化和繁荣的消费市场,制造业发展中的技术涌入对气候变化构成了重大威胁。为了应对这种情况,绿色制造在降低大规模生产对全球环境的影响方面发挥了至关重要的作用。采用基于专家意见的定性研究,对绿色制造的实施提出了基于绿色供应链制造(GSCMEs)驱动因素的观点。在这方面,本研究的重点是通过基于解释结构建模和交叉影响乘法应用于分类(MICMAC)分析的框架,探索制造商采用绿色实践的关键推动因素。结果表明,经济约束和监管框架具有较高的驱动力和较低的依赖性。研究人员为管理者提供了一个新的未来前景,以建立一个生态友好的供应链,并获得竞争对手的竞争优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Foundations of Computing and Decision Sciences
Foundations of Computing and Decision Sciences COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
2.20
自引率
9.10%
发文量
16
审稿时长
29 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信