Abstract

Clustering nations using sustainability indexes has been proposed as a means to support decision-making in politics, academia and business. This starts by computing indexes that describe the social, economic and environmental progress of countries, and continues by ranking and clustering countries that face similar sustainability challenges. Although multi-criteria methods exist to support this process, two main issues have not been addressed in an integrated approach: uncertainty in decision-making parameters and imprecise data sources. In this study, we propose a procedure in which the PROMETHEE II multi-criteria method is used for ranking countries and an iterative algorithm is applied to find ordered clusters. A stochastic robustness analysis procedure helps to identify groups with robust sustainability paths. The approach is applied to the Human Development Index and the Sustainable Development Goals Index. By analyzing the ambiguous assignments of nations to clusters three groups of countries can be identified. First, countries that have very good arguments to be considered in a given cluster. Second, countries which have some merits to be considered in a cluster and where focusing resources would allow them to improve in their current group or jumping into a better one. Third, nations that have very ambiguous arguments to be considered in any cluster such that the support to improve their performance would have to be analyzed in depth on multiple fronts. Thus, policy decision-making could be enhanced with this approach, providing new and helpful visualizations of nations in HDI and SDG. Finally, limitations of this proposal and future research are discussed.