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Open AccessArticle

An Integrated Decision-Making Approach for Cause-And-Effect Analysis of Sustainable Manufacturing Indicators

1
Quantitative Methods and Operations Management, Indian Institute of Management Amritsar, Punjab 143105, India
2
School of Business and Economics, Loughborough University, Loughborough LE11 3TU, UK
3
Department of Industrial Engineering, College of Engineering, King Saud University, Riyadh 11421, Saudi Arabia
*
Author to whom correspondence should be addressed.
Sustainability 2020, 12(4), 1517; https://doi.org/10.3390/su12041517
Received: 30 December 2019 / Revised: 9 February 2020 / Accepted: 14 February 2020 / Published: 18 February 2020
(This article belongs to the Special Issue Lean Manufacturing, Operational Excellence and Sustainability)
Sustainability is a growing concern for manufacturing companies, as they are major contributors to pollution and consume a substantial portion of the world´s natural resources. Sustainable manufacturing can reduce waste, conserve energy and increase resource efficiency. However, one of the main challenges facing manufacturing organisations to put sustainability into practice is the lack of understanding of the cause-and-effect relationships between critical indicators of sustainable manufacturing. To overcome this challenge, a novel, rigorous and integrated framework, composed of four quantitative methods, is proposed to analyse critical indicators of sustainable manufacturing. The analysis is based on responses from both academic and industry experts. These four methods including DEMATEL (decision-making trial and evaluation laboratory), the MMDE (maximum mean de-entropy) algorithm, ISM (interpretive structural modelling) and SEM (structural equation modelling) are uniquely integrated to present statistically validated relationships between critical indicators using information on varying degrees of relationship between them. The final cause-and-effect models for the respondent groups (i.e., researchers and industry experts) are further validated through gathering the viewpoints of a researcher and an industry practitioner for its robustness. The novelty of our research lies in: (1) proposing a novel and integrated rigorous quantitative framework combined with qualitative research method; (2) applying the proposed framework to analyse contextual relationships between critical indicators of implementing sustainability, in the manufacturing sector as a whole, which to the best of authors’ knowledge is the first of its kind; and (3) comparing and contrasting results of researchers and industry practitioners’ groups along with a check of their validation and robustness. View Full-Text
Keywords: sustainable manufacturing; critical indicators; interpretive structural modeling; decision making trial and evaluation laboratory; structural equation modeling; max-mean de entropy algorithm; cause-and-effect analysis sustainable manufacturing; critical indicators; interpretive structural modeling; decision making trial and evaluation laboratory; structural equation modeling; max-mean de entropy algorithm; cause-and-effect analysis
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Bhanot, N.; Qaiser, F.H.; Alkahtani, M.; Rehman, A.U. An Integrated Decision-Making Approach for Cause-And-Effect Analysis of Sustainable Manufacturing Indicators. Sustainability 2020, 12, 1517.

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