Using cross efficiency method integrating regret theory and WASPAS to evaluate road safety performance of Chinese provinces.

Cross Efficiency Method (CEM) Regret theory Road safety performance WASPAS

Journal

Accident; analysis and prevention
ISSN: 1879-2057
Titre abrégé: Accid Anal Prev
Pays: England
ID NLM: 1254476

Informations de publication

Date de publication:
Nov 2021
Historique:
received: 03 05 2021
revised: 05 08 2021
accepted: 03 09 2021
pubmed: 27 9 2021
medline: 25 2 2023
entrez: 26 9 2021
Statut: ppublish

Résumé

Currently, the road safety performance of a national- or province-level is absorbing much attention from practitioners and academics. A variety of models based on Data Envelopment Analysis (DEA) have been presented to appraise road safety performance in previous literature. However, the main weakness of these methods is that the decision-maker's psychological behavior is neglected. Besides, Cross Efficiency Method (CEM) adopts the weighted average to aggregate the cross efficiencies which may lead to information loss. To address these limitations, a hybrid road safety evaluation model was constructed by integrating CEM, regret theory, and Weighted Aggregated Sum Product Assessment (WASPAS) to appraise the road safety performance of Chinese provinces. In the presented model, regret theory is employed to depict the psychological behavior of the decision-maker. Then entropy weight method is utilized to calculate the weight of self-evaluation and peer-evaluation. To reduce information loss, WASPAS is adopted to fuse the cross efficiencies and derive the ranking of decision-making units. Finally, the presented model is employed to assess the road safety efficiency in the province of mainland China. The results show that the mean of road safety efficiency score for the eastern, central, and western areas is gradually decreasing. Furthermore, the outcomes of a comparative analysis represent that the results obtained by the proposed model outperform the CEM and DEA road safety model.

Identifiants

pubmed: 34563647
pii: S0001-4575(21)00426-7
doi: 10.1016/j.aap.2021.106395
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

106395

Informations de copyright

Copyright © 2021 Elsevier Ltd. All rights reserved.

Auteurs

Jiang-Hong Zhu (JH)

College of Traffic and Transportation, Chongqing Jiaotong University, No. 66, Xuefu Road, Nan' an District, Chongqing 400074, China; School of Transportation and Logistics, Southwest Jiaotong University, West Section, High-tech Zone, Chengdu, Sichuan 611756, China. Electronic address: jhzhu@cqjtu.edu.cn.

Jian Chen (J)

College of Traffic and Transportation, Chongqing Jiaotong University, No. 66, Xuefu Road, Nan' an District, Chongqing 400074, China.

Guo-Fang Li (GF)

School of Transportation and Logistics, Southwest Jiaotong University, West Section, High-tech Zone, Chengdu, Sichuan 611756, China.

Bin Shuai (B)

School of Transportation and Logistics, Southwest Jiaotong University, West Section, High-tech Zone, Chengdu, Sichuan 611756, China.

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