Show simple item record

dc.contributor.authorYadav, G
dc.contributor.authorKumar, Anil
dc.contributor.authorLuthra, S
dc.contributor.authorGarza-Reyes, Jose Arturo
dc.contributor.authorKumar, V
dc.contributor.authorBatista, L
dc.date.accessioned2020-08-13T14:12:41Z
dc.date.available2020-08-13T14:12:41Z
dc.date.issued2020-07-07
dc.identifier.citationYadav, G., Kumar, A., Luthra, S., Garza-Reyes, J.A., Kumar, V., Batista, L. (2020). 'A frame-work to achieve sustainability in manufacturing organisations of developing economies using Industry 4.0 technologies’ enablers'. Computers in Industry, 122, pp. 1-13.en_US
dc.identifier.issn0166-3615
dc.identifier.doi10.1016/j.compind.2020.103280
dc.identifier.urihttp://hdl.handle.net/10545/625074
dc.description.abstractSustainability has emerged as one of the most important issues in the international market. Ignorance of sustainability aspects has led many manufacturing organisations to face huge financial losses. It has been observed that developed nations have successfully achieved sustainability in their manufacturing sectors. However, the rate of sustainability adoption in developing nations is significantly poorer. The current business trend offers new technologies such as the Internet of Things, Big data analytics, Blockchain, Machine learning, etc. These technologies can be termed under the Industry 4.0 paradigm when considered within a manufacturing context. It is significant to notice that such new technologies directly or indirectly contribute to sustainability. So, it is necessary to explore the enablers that facilitate sustainability adoption. This study aims to develop a framework to improve sustainability adoption across manufacturing organisations of developing nations using Industry 4.0 technologies. Initially, the enablers that strongly influence sustainability adoption are identified through a literature review. Further, a large scale survey is conducted to finalise the Industry 4.0 technologies’ enablers to be included in the framework. Based on the empirical analysis, a framework is developed and tested across an Indian manufacturing case organisation. Finally, Robust Best Worst Method (RBWM) is utilised to identify the intensity of influence of each enabler included in the framework. The findings of the study reveal that managerial and economical, and environmental enablers possess a strong contribution toward sustainability adoption. The outcomes of the present study will be beneficial for researchers, practitioners, and policymakers.en_US
dc.description.sponsorshipN/Aen_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.urlhttps://www.journals.elsevier.com/computers-in-industryen_US
dc.relation.urlhttps://www.sciencedirect.com/science/article/pii/S0166361520305145en_US
dc.rightsCC0 1.0 Universal*
dc.rights.urihttp://creativecommons.org/publicdomain/zero/1.0/*
dc.subjectSustainability; Manufacturing supply chain; Industry 4.0; Developing nations; New technologies, Empirical study, Robust Best Worst Method (RBWM).en_US
dc.titleA framework to achieve sustainability in manufacturing organisations of developing economies using Industry 4.0 technologies’ enablersen_US
dc.typeArticleen_US
dc.contributor.departmentVeermata Jijabai Technological Institute, Mumbai, Indiaen_US
dc.contributor.departmentLondon Metropolitan Universityen_US
dc.contributor.departmentCh. Ranbir Singh State Institute of Engineering and Technology, Jhajjar, Haryana, Indiaen_US
dc.contributor.departmentUniversity of Derbyen_US
dc.contributor.departmentUniversity of the West of Englanden_US
dc.contributor.departmentAston Universityen_US
dc.identifier.journalComputers in Industyen_US
dcterms.dateAccepted2020-06-25
dc.author.detail780891en_US


Files in this item

Thumbnail
Name:
Publisher version
Thumbnail
Name:
Manuscript Revised Version2.pdf
Embargo:
2022-07-07
Size:
703.3Kb
Format:
PDF
Description:
Accepted Manuscript

This item appears in the following Collection(s)

Show simple item record

CC0 1.0 Universal
Except where otherwise noted, this item's license is described as CC0 1.0 Universal