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State-of-the-art sustainability analysis methodologies for efficient decision support in green production operations

Over the last three decades, new concepts, strategies, frameworks and systems have been developed to tackle the sustainable development issue. This paper reviews the challenges, perspectives and recent advances in support of sustainable production operations decision-making. The aim of this review i...

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Bibliographic Details
Published in:International journal of sustainable engineering 2011-09, Vol.4 (3), p.236-250
Main Authors: Liu, Shaofeng, Leat, Mike, Smith, Melanie Hudson
Format: Article
Language:English
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Summary:Over the last three decades, new concepts, strategies, frameworks and systems have been developed to tackle the sustainable development issue. This paper reviews the challenges, perspectives and recent advances in support of sustainable production operations decision-making. The aim of this review is to provide a holistic understanding of advanced scientific analysis methodologies for the evaluation of sustainability, to provide efficient decision support. Over 100 publications have been analysed, and a characterisation of state-of-the-art sustainability analysis methodologies has been produced, which includes life cycle assessment and multi-criteria decision analysis (MCDA), along with their applications to three key areas of production operations: sustainable design, sustainable manufacture and sustainable supply chain management. Distribution of existing work is discussed and future research directions are elicited from the literature. The paper finds three trends in supporting sustainable production operations decisions: (a) sustainability analysis has moved to whole life cycle assessment from single-stage assessment, (b) sustainability analysis has shifted away from single criterion to MCDA and (c) sustainability analysis has evolved from stand-alone approaches to integrated systematic methodologies. The paper concludes that integrated sustainability analysis can provide more efficient and effective support to complex decision-making in sustainable production operations.
ISSN:1939-7038
1939-7046
DOI:10.1080/19397038.2011.574744