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An application of hybrid life cycle assessment as a decision support framework for green supply chains

Lake, Alison, Acquaye, Adolf, Genovese, Andrea, Niraj, Kumar, Koh, S.C. Lenny (2014) An application of hybrid life cycle assessment as a decision support framework for green supply chains. International Journal of Production Research, . ISSN 0020-7543. E-ISSN 1366-588X. (doi:10.1080/00207543.2014.951092) (KAR id:43166)

Abstract

In an effort to achieve sustainable operations, green supply chain management has become an important area for firms to concentrate on due to its inherent involvement with all the processes that provide foundations to successful business. Modelling methodologies of product supply chain environmental assessment are usually guided by the principles of life cycle assessment (LCA). However, a review of the extant literature suggests that LCA techniques suffer from a wide range of limitations that prevent a wider application in real-world contexts; hence, they need to be incorporated within decision support frameworks to aid environmental sustainability strategies. Thus, this paper contributes in understanding and overcoming the dichotomy between LCA model development and the emerging practical implementation to inform carbon emissions mitigation strategies within supply chains. Therefore, the paper provides both theoretical insights and a practical application to inform the process of adopting a decision support framework based on a LCA methodology in a real-world scenario. The supply chain of a product from the steel industry is considered to evaluate its environmental impact and carbon ‘hotspots’. The study helps understanding how operational strategies geared towards environmental sustainability can be informed using knowledge and information generated from supply chain environmental assessments, and for highlighting inherent challenges in this process.

Item Type: Article
DOI/Identification number: 10.1080/00207543.2014.951092
Uncontrolled keywords: green supply chain, life cycle assessment, decision support framework
Subjects: Q Science > Operations Research - Theory
Divisions: Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems
Depositing User: Adolf Acquaye
Date Deposited: 02 Oct 2014 09:27 UTC
Last Modified: 05 Nov 2024 10:27 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/43166 (The current URI for this page, for reference purposes)

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