Implementation of stochastic multi attribute analysis (SMAA) in comparative environmental assessments. (November 2018) - Prado, Valentina; Heijungs, Reinout
Abstract: 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. Highlights: Step by step demonstration of SMAA for life cycle based quantitative comparative environmental assessments. Illustration of an alternative interpretation approach for outputs of multi-criteria environmental assessments. Introduces method that incorporates performance and weight uncertainty in a selection problem.