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An integrated decision model with reliability to support transport safety system analysis

Author

Listed:
  • Li, Yaxin
  • Ding, Yuxin
  • Guo, Yuliang
  • Cui, Haizhou
  • Gao, Haiyi
  • Zhou, Ziyu
  • (Aaron) Zhang, Nanbo
  • Zhu, Siyao
  • Chen, Faan

Abstract

Multi-Criteria Decision-Making (MCDM) problems necessitate a methodology that is able to produce reliable and defendable decisions. This is especially the case when it comes to safety system analyses. This study constructs an integrated model, CRiteria Importance Through Intercriteria Correlation (CRITIC) – Multi-Objective Optimization on the basis of Ratio Analysis (MOORA) – Spectral Clustering (SC) (i.e., CRITIC–MOORA–SC), which seamlessly incorporates three stages of MCDM (weighting, aggregating, and grouping) with decomposing into one process, with the capacity to deal with decision difficulties while maintaining a high level of reliability. The model is designed to support the transport safety analyses of 10 member countries of the Association of Southeast Asian Nations (ASEAN), as well as Timor-Leste, including measuring road safety development, ranking and grouping safety performances, deconstructing safety performance indicators, decomposing overall achievement, quantifying safety changes over the past decade, and benchmarking approved practices. Enhanced comparisons of the results indicate the reliability and practicability of the proposed model, verifying its applicability for real-world decision activities. By doing so, this study provides policymakers and managers in the ASEAN region, as well as other parts of the world, with a support tool for creditable analyses in transport safety, strengthening their institutional capacity in decision-making activities.

Suggested Citation

  • Li, Yaxin & Ding, Yuxin & Guo, Yuliang & Cui, Haizhou & Gao, Haiyi & Zhou, Ziyu & (Aaron) Zhang, Nanbo & Zhu, Siyao & Chen, Faan, 2023. "An integrated decision model with reliability to support transport safety system analysis," Reliability Engineering and System Safety, Elsevier, vol. 239(C).
    • Handle: RePEc:eee:reensy:v:239:y:2023:i:c:s0951832023004544
    DOI: 10.1016/j.ress.2023.109540
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