Title

Operations research for sustainability assessment of products: A review

Document Type

Article

Date of Original Version

4-1-2019

Abstract

The environmental and social impacts of products are being increasingly scrutinized. This necessitates systematic assessment methods. Life Cycle Sustainability Assessment (LCSA) provides a framework to addresses diverse sustainability issues over the product's life cycle, but its application is complicated. Major challenges, such as the selection of relevant indicators, multi-criteria comparisons of alternatives, the treatment of uncertainties, or the integration of spatially differentiated data, can be facilitated by adopting advanced analytical methods from Operations Research. This paper reviews 142 articles that use Operations Research methods for product-related sustainability assessments. The articles were selected from peer-reviewed scientific literature in a systematic search and screening process. Descriptive analysis shows that related publication output is growing over time and originates mainly in journals related to Environmental Management. While ecological indicators are considered by most articles, the integration of economic and social indicators is emerging. Focusing on the contributions of Operations Research, a detailed analysis shows that more than half of the articles adopt methods from Multi-Attribute Decision Making (MADM), followed by Data Envelopment Analysis (DEA) and Multi-Objective Decision Making (MODM). Uncertainties with regard to inventory data and decision makers’ preferences are addressed using fuzzy logic, stochastic models, or sensitivity analysis. The use of spatially differentiated data is not frequently found in the reviewed articles. Research needs derived from this analysis comprise the integration of qualitative and semi-quantitative (social) indicators, the simultaneous consideration of global and local sustainability objectives, and the application of systematic procedures to address uncertainty.

Publication Title

European Journal of Operational Research

Volume

274

Issue

1

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