A Quantitative Framework for Sustainability Assessment

Abstract

Abstract Sustainability assessment is vital to determine the relative superiority among alternatives, characterized by multiple sustainability indicators. Various methods, such as the Euclidean distance method, geometric mean method, elimination et choice translating reality (ELECTRE), etc., have been suggested in the literature to identify the most sustainable option among alternatives. These diverse approaches adopt different normalization and aggregation formulations (the two most significant steps of any sustainability assessment), leading to conflicting results. This paper proposes a generalized sustainability framework to identify the most suitable alternative quantitatively. The proposed framework identifies various mathematical and physical characteristics of normalization and aggregation processes and identifies mathematical functions that satisfy these characteristics. Based on the desired characteristics, the proposed approach identifies the min-max normalization function and a novel antinorm-based aggregation function as the most appropriate for a quantitative sustainability framework. The applicability of the proposed framework is illustrated via different case studies from the literature: sustainable power plants for electricity generation in Portugal, sustainable feedstock for the biodiesel supply chain, and sustainable negative emission technologies. The results are compared with those reported in the literature, and the efficacy of the suggested framework is demonstrated. The proposed framework may be utilized for multi-criteria decision-making.