| Title |
An application of hybrid life cycle assessment as a decision support framework for green supply chains |
| ID_Doc |
75978 |
| Authors |
Lake, A; Acquaye, A; Genovese, A; Kumar, N; Koh, SCL |
| Title |
An application of hybrid life cycle assessment as a decision support framework for green supply chains |
| Year |
2015 |
| Published |
International Journal Of Production Research, 53, 21 |
| DOI |
10.1080/00207543.2014.951092 |
| 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. |
| Author Keywords |
green supply chain; life cycle assessment; decision support framework |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:000361381400010 |
| WoS Category |
Engineering, Industrial; Engineering, Manufacturing; Operations Research & Management Science |
| Research Area |
Engineering; Operations Research & Management Science |
| PDF |
https://kar.kent.ac.uk/43166/1/IJPR%20Proof.pdf
|