Sensitivity analysis of sustainability indicators using a shifted geometric assessment model

• Published in: International journal of sustainable development and world ecology Vol. ahead-of-print; no. ahead-of-print; pp. 1 - 11
• Main Authors: Kouikoglou, Vassilis S., Phillis, Yannis A.
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis 17.11.2023; Taylor & Francis Ltd
• Subjects: data aggregation; Decision analysis; Decision making; Developed countries; Environmental performance; Indicators; Mathematical models; national sustainability; Sensitivity analysis; shifted geometric mean; Social conditions; Sustainability; sustainability indicators
• ISSN: 1350-4509; 1745-2627
• DOI: 10.1080/13504509.2023.2231866

A multitude of sustainability assessment models exist relying on given sets of basic indicators. In this work we use an analytical model called shifted geometric mean (SGM), which is based on a set of mathematical postulates to perform sensitivity analysis. The purpose of this analysis is to find those indicators with the highest potential for sustainability improvement. This is done via a gradient method under a given budget constraint leading to a novel closed-form expression. The method is applied to 164 countries which are ranked accordingly and then the corresponding most influential indicators are found. Unsurprisingly, European countries, Australia and Uruguay top the list, whereas the bottom is occupied by Sub-Saharan African countries, Iraq, Afghanistan, Yemen and Haiti. However, the model revealed that Israel, South Korea and Singapore rank surprisingly low due to their poor environmental performance. For similar reasons, Romania and Bulgaria ranked above the USA. Finally, the model exposed the most important aspects in need of improvement, which for developing and low-income countries comprise the economy and social conditions. At the other end of the spectrum, developed countries need to improve their environmental performance. SGM augmented with sensitivity analysis can thus be a practical tool for sustainability decision-making.