Road safety performance varies considerably across regions, affected by differences in management practices, local conditions, and broader systemic factors. A systematic and comprehensive evaluation helps analyze these variations and translate them into insights that can guide targeted actions to improve road safety. This study proposes a Data Envelopment Analysis (DEA)-based framework, grounded in the Safe System approach, to evaluate and compare the relative efficiency of road safety systems. The framework relies on a careful selection of input and outcome indicators that capture key components of road safety. By applying both CCR and BCC DEA models, it enables the assessment of technical and scale efficiency, sets performance targets, and identifies benchmark peers. When multiple related indicators are considered, the framework integrates the Benefit of the Doubt (BoD) aggregation technique to combine them, preserving the discriminating power of DEA models. The proposed framework is applied to 19 Moroccan cities. Although conceptually designed to cover all Safe System pillars, the empirical application represents a partial operationalization, limited to road user behavioral indicators due to data availability constraints. The findings indicate strong managerial efficiency across cities, alongside significant scale inefficiencies. Target values for inputs and outputs are derived for each city, and the most efficient cities are identified as benchmarks for less efficient ones. The application further highlights the challenges in implementing a Safe System-based evaluation framework in data-constrained contexts.
Khalai et al. (Wed,) studied this question.