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

Bibliographic Data

ID13135281
AuthorsMehran Rad (0000-0002-0513-5495, RISE Research Institutes of Sweden, corresponding author), Ulf Sonesson (0000-0002-0167-5603, RISE Research Institutes of Sweden), Evelina Höglund (RISE Research Institutes of Sweden), Karin Östergren (0000-0001-8038-1365, RISE Research Institutes of Sweden)
Year2026
Volume11
Pages101657-101657
Publication date2026-01-16
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueSustainable Futures (JOURNAL)
Journal identifiersISSN: 2666-1888
PublisherElsevier BV (PUBLISHER)
DOI10.1016/j.sftr.2026.101657
OpenAlexW7124462665
LanguageEN
References cited28

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.

Decision analysis · Decision model · Decision support system · Decision theory · Key (lock · Sustainability · Environmental and Social Impact Assessments · Sustainable Agricultural Systems Analysis · Sustainable Development and Environmental Policy

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