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Citation |
Shen Y, Hermans E, Bao Q, Brijs T, Wets G. Accid. Anal. Prev. 2020; 138: e105484. |
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Affiliation |
Transportation Research Institute (IMOB), Hasselt University, Wetenschapspark 5 bus 6, 3590 Diepenbeek, Belgium. Electronic address: geert.wets@uhasselt.be. |
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Copyright |
(Copyright © 2020, Elsevier Publishing) |
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DOI |
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PMID |
32105839 |
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Abstract |
Inter-national benchmarking of road safety, with the purpose of achieving continuous improvement by learning lessons from existing best practices, has currently been widely encouraged by most countries as an emerging management tool to improve the level of road safety. However, performing a successful road safety benchmarking practice is by no means easy. Challenges exist from ascertaining the benchmarking framework at the very beginning to making final policy decisions. In this study, based on the identification of leading road safety risk factors, a comprehensive set of hierarchically structured safety performance indicators was developed, some necessary data processing procedures were conducted, and the use of data envelopment analysis (DEA) for composite indicator (CI) construction was elaborated. An interval multiple layer DEA-based CI model was proposed to take both the hierarchical structure of the indicators and the data uncertainty into account, and was used to benchmark road safety performance for a set of European countries. Based on the model output, best-performing and underperforming countries were distinguished and all the countries were further ranked by computing their cross-index score. Moreover, by taking the characteristics of each country in the data set into account, country-specific benchmarks for those underperforming countries were identified, and useful insight in the areas of underperformance in each country was gained. Meanwhile, by summarizing the risk aspects that need urgent policy action for all these countries, some specific road safety enhancing recommendations for this region as a whole were formulated. Language: en |
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Keywords |
Composite indicators; Data envelopment analysis; Hierarchical structure; Inter-national benchmarking; Interval data; Safety performance indicators |