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An integrated decision-making approach for cause-and-effect analysis of sustainable manufacturing indicators

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journal contribution
posted on 23.04.2020 by Neeraj Bhanot, Fahham Qaiser, Mohammed Alkahtani, Ateekh Ur Rehman
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.

Funding

Deanship of Scientific Research at King Saud University grant number [RG-1439-027]

History

School

  • Business and Economics

Department

  • Business

Published in

Sustainability

Volume

12

Issue

4

Publisher

MDPI AG

Version

VoR (Version of Record)

Rights holder

© The Authors

Publisher statement

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

Acceptance date

14/02/2020

Publication date

2020-02-18

Copyright date

2020

eISSN

2071-1050

Language

en

Depositor

Mr Fahham Hasan Qaiser. Deposit date: 20 April 2020

Article number

1517

Licence

Exports