Implementation of stochastic multi attribute analysis (SMAA) in comparative environmental assessments

Valentina Prado*, Reinout Heijungs

*Corresponding author for this work

    Research output: Contribution to JournalArticleAcademicpeer-review

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    The selection of an alternative based on the results of a comparative environmental assessment such as life cycle assessment (LCA), environmental input-output analysis (EIOA) or integrated assessment modelling (IAM) is challenging because most of the times there is no single best option. Most comparative cases contain trade-offs between environmental criteria, uncertainty in the performances and multiple diverse values from decision makers. To circumvent these challenges, a method from decision analysis, namely stochastic multi attribute analysis (SMAA), has been proposed instead. SMAA performs aggregation that is partially compensatory (hence, closer to a strong sustainability perspective), incorporates performance uncertainty in the assessment, is free from external normalization references and allows for uncertainties in decision maker preferences. This paper presents a thorough introduction of SMAA for environmental decision-support, provides the mathematical fundamentals and offers an Excel platform for easy implementation and access.

    Original languageEnglish
    Pages (from-to)223-231
    Number of pages9
    JournalEnvironmental Modelling and Software
    Early online date27 Aug 2018
    Publication statusPublished - Nov 2018


    • Comparative environmental analysis
    • Interpretation
    • Stochastic multi attribute analysis (SMAA)
    • Uncertainty


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