Benchmarking road safety: Lessons to learn from a data envelopment analysis

Hermans, Elke; Brijs, Tom; Wets, Geert; Vanhoof, Koen · 2008 · OpenAlex-citations

DOI: 10.1016/j.aap.2008.10.010

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Summary

This paper addresses the challenge of effectively comparing road safety performance across European countries to guide policy decisions. While traditional metrics like fatality rates provide rankings, they fail to identify specific risk domains requiring intervention. The authors propose a computational model based on Data Envelopment Analysis (DEA) to create actionable Road Safety Performance Indicators (SPIs). The goal is to determine an overall efficiency score for each country, identify benchmarks for underperforming nations, and set specific targets for improvement in key risk areas. The study applies a DEA model to data from 21 European countries. The model treats six road safety risk domains as inputs and two crash outcomes as outputs. The inputs are best-available indicators for alcohol and drug use, speed, protective systems, vehicle age, infrastructure density, and trauma management. The outputs are the number of injury crashes per 100,000 inhabitants and fatalities per million inhabitants. To ensure realistic weighting, the model incorporates constraints derived from budget allocation surveys of 11 road safety experts, limiting the share of each input and output in the final score. The objective is to minimize the ratio of weighted outputs to weighted inputs, with a score of one indicating optimal efficiency. The results identify Denmark and the Netherlands as the only efficient countries, achieving a road safety score of one. The remaining 19 countries are deemed inefficient, with scores exceeding one. For each inefficient country, the model assigns one or more benchmark countries (primarily Denmark, Finland, the Netherlands, or Sweden) that serve as realistic targets for improvement. By comparing current indicator values against these benchmarks, the study derives country-specific priorities. For instance, Austria’s inefficiency is largely driven by poor performance in protective systems and vehicle technology, while the United Kingdom’s primary bottleneck is trauma management. The analysis reveals that different countries require distinct policy focuses; for example, Cyprus and Portugal need to prioritize vehicle technology, whereas Estonia and France should focus on infrastructure improvements. The significance of this work lies in its ability to translate complex road safety data into specific, actionable policy recommendations. Unlike simple rankings, the DEA-RS model identifies exactly which risk domains contribute most to a country’s inefficiency and provides quantitative targets for improvement. This approach allows policymakers to prioritize resources effectively, focusing on the areas that will yield the greatest reduction in crashes and fatalities. The study demonstrates that DEA is a robust tool for composite indicator construction in road safety, offering a structured method for benchmarking and target setting that respects expert knowledge and data realities.

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Topics

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• comparative international
• regulatory evaluation
• demographic disparities

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• Empirical Findings: crash risk outcomes