Benefit of the Doubt Composite Indicators System (BoD-CI-Sy) and its application in representing the energy sustainability of the Global South

The analysis of Sustainable Development Goal 7 (SDG 7) uses various individual indicators that need comparable metrics across countries. Composite indicators group these dimensions and require robust weighting and aggregation. The commonly used Benefit of the Doubt (BoD) approach has traditional limitations that can hide flaws in evaluated units. To address these, this article introduces the BoD Composite Indicator Construction System. Created in Python and R, it offers thirteen frontier-based approaches. The practical utility of this computational tool was demonstrated by applying four approaches (BoD, Constrained BoD, Constrained BoD with Bad Indicators, and Robust BoD) to assess energy performance in 121 Global South Decision Making Units (DMUs) in 2021. Results showed that weighting constraints and probabilistic sampling help avoid overestimated regional performances. This software represents a computational contribution that helps governments identify real bottlenecks in the energy transition.