Genovese, Andrea, Acquay, Adolf, Figueroa, Alejandro, Koh, S.C. Lenny (2017) Sustainable Supply Chain Management and the transition towards a Circular Economy: Evidence and some Applications. Omega, . ISSN 0305-0483. (doi:10.1016/j.omega.2015.05.015) (KAR id:49202)
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Official URL: http://dx.doi.org/10.1016/j.omega.2015.05.015 |
Abstract
In the last decades, green and sustainable supply chain management practices have been developed, trying to integrate environmental concerns into organisations by reducing unintended negative consequences on the environment of production and consumption processes. In parallel to this, the circular economy discourse has been propagated in the industrial ecology literature and practice. Circular economy pushes the frontiers of environmental sustainability by emphasising the idea of transforming products in such a way that there are workable relationships between ecological systems and economic growth. Therefore, circular economy is not just concerned with the reduction of the use of the environment as a sink for residuals but rather with the creation of self-sustaining production systems in which materials are used over and over again.
Through two case studies from different process industries (chemical and food), this paper compares the performances of traditional and circular production systems across a range of indicators. Direct, indirect and total lifecycle emissions, waste recovered, virgin resources use, as well as carbon maps (which provide a holistic visibility of the entire supply chain) are presented. The paper asserts that an integration of circular economy principles within sustainable supply chain management can provide clear advantages from an environmental point view. Emerging supply chain management challenges and market dynamics are also highlighted and discussed.
Item Type: | Article |
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DOI/Identification number: | 10.1016/j.omega.2015.05.015 |
Uncontrolled keywords: | Green supply chain management; Circular economy; Product lifecycle analysis; Environmental sustainability; Decision support |
Subjects: | Q Science > Operations Research - Theory |
Divisions: | Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems |
Depositing User: | Adolf Acquaye |
Date Deposited: | 01 Jul 2015 09:36 UTC |
Last Modified: | 05 Nov 2024 10:33 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/49202 (The current URI for this page, for reference purposes) |
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