Software for building composite indicators with maximum stability: the S-CI-MaxS

Composite indicators simplify the understanding of multidimensional phenomena such as sustainability and economic performance. However, composite indicators can be constructed using different methods, generating uncertainty about which one to use. This study presents the Python tool S-CI-MaxS, with a Streamlit interface, which offers several functionalities. Automatic identification of the polarity and normalization function of sub-indicators. Construction of composite indicator by Principal Component Analysis, Benefit of the Doubt, Equal Weights, and Entropy methods. The novel maximum stability method that minimizes uncertainty in composite indicator classification while ensuring consistency between sub-indicator weights and expert opinion. Providing information demonstrating the method's superiority over more popular methods. These advantages of S-CI-MaxS are demonstrated in two case studies: 1.) “Affordable and Clean Energy Index” for Latin American countries; and 2.) “Photovoltaic Generation Potential Index” of Brazilian municipalities.