Multi-Criteria Decision Analysis (MCDA) for sustainability assessment–How reliable are the results?

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Authors: Mehran Rad, Ulf Sonesson, Evelina Höglund, Karin Östergren
Cited by: 7
References: 28

Abstract

Navigating through widely different strategies for pursuing sustainability in complex systems demands comprehensive approaches to thoroughly assess their performance, accounting for multiple, often conflicting, domains of sustainability. Multi-Criteria Decision Analysis (MCDA) proves well-suited for the task. Despite its growing use, the reliability of MCDA-based sustainability assessment outcomes, particularly under uncertainty and in dynamic contexts, remains underexplored. This study evaluates the robustness and sensitivity of such results through five case studies in the Swedish food production and consumption system, analysed across four considered future supply chain solutions. This study conducts a comprehensive sensitivity and uncertainty analysis to assess the impact of variations in indicator weights and performance scores. Findings show that while the sustainability assessment results are generally, but not in all cases, robust, certain sustainability indicators disproportionately influence final rankings across case studies. Small perturbations in these critical indicators can shift the top-performing solution, highlighting the need for rigorous weighting strategies and context-specific indicator selection. Such critical indicators were found to be not the ones recognised with the highest weights. The study demonstrates the value of incorporating sensitivity and uncertainty analysis into MCDA-based sustainability assessment studies to enhance transparency, decision confidence, and practical applicability, particularly in complex, interdisciplinary domains such as food systems sustainability.

Fields of Study & Subjects

Environmental and Social Impact Assessments Sustainable Agricultural Systems Analysis Sustainable Development and Environmental Policy

Publication details

Journal / source
Sustainable Futures
Publisher
Elsevier BV
Volume
11
Pages
101657–101657
Publication date
16 January 2026
Language
EN