| Popis: |
Abstract Progress monitoring and action recalibrations are advocated as promising methods for improving road safety, which significantly relates to economic stability and social development. To achieve this, an auditing framework that can evaluate road safety and aid in policymaking is urgently required. To this end, this study developed a systemic decision model that integrates the method based on the removal effects of criteria (MEREC), additive ratio assessment (ARAS), and quantile-based k-means clustering (QBKM), termed MEREC–ARAS–QBKM, with the aim of auditing road safety achievements and providing corresponding policy suggestions with substantial reliability. In particular, the performance of the traditional k-means clustering model was improved by implanting quantiles to determine the initial clustering, which overcomes the uncertainty of k-means clustering owing to the variety of initial cluster centers. Multiple comparisons of empirical results based on a case study of the Asia-Pacific Economic Cooperation (APEC) member economies verified the robustness of the proposed model, demonstrating its applicability, practicability, and reliability in handling real-world multi-criteria decision-making problems in the field of road safety. The empirical findings show that road safety developments among the APEC countries are of class differentiation, suggesting an urgent regional benchmarking. Overall, the proposed methodology empowers decision-makers and policymakers in APEC to swiftly formulate effective action plans, countermeasures, and investment schemes, ultimately contributing to the enhancement of road safety performance and socio-economic benefit across APEC members. |
