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An Integrated Data Envelopment Analysis and Non-Cooperative Game Approach for Public Transportation Incentive Subsidy Allocation | |
Xie, Qiwei1![]() ![]() ![]() | |
发表期刊 | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
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ISSN | 1524-9050 |
2022-08-01 | |
页码 | 16 |
通讯作者 | Dai, Qianzhi(qianzhi@hfut.edu.cn) ; Zheng, Xiaolong(xiaolong.zheng@ia.ac.cn) |
摘要 | As an important national initiative, China's public transport priority development strategy is conducive to the development of the public transport industry and urban economic construction. However, current public transport operation is inefficient due to the information asymmetry between the government and public transport enterprises, thereby inevitably generating losses. To address the issue of information asymmetry, this study designs a public transport subsidy allocation method from the perspective of incentives and discusses the allocation results using this method through a case study. The rationality of the proposed method and the scientificity and authenticity of the conclusions, are fully explained and demonstrated via the experimental simulation. Based on real published data of public transport enterprises, the proposed method can motivate public transport enterprises to improve their performance. In the case of reporting false data, the proposed method can motivate public transport enterprises to report accurate data. |
关键词 | Resource management Costs Government Games Industries Behavioral sciences Data envelopment analysis Subsidy allocation data envelopment analysis information asymmetry Nash non-cooperative game |
DOI | 10.1109/TITS.2022.3193050 |
关键词[WOS] | CENTRALIZED RESOURCE-ALLOCATION ; FIXED COST ; DEA ; EFFICIENCY ; PERFORMANCE ; OPERATORS ; OUTPUTS ; SERVICE |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Natural Science Foundation of China[61673381] ; National Natural Science Foundation of China[71701060] ; National Natural Science Foundation of China[72171072] ; Natural Science Foundation of Beijing Municipality[9202002] ; State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences ; Ministry of Science and Technology of China[2020AAA0108401] ; Ministry of Science and Technology of China[2019QY(Y)0101] |
项目资助者 | National Natural Science Foundation of China ; Natural Science Foundation of Beijing Municipality ; State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences ; Ministry of Science and Technology of China |
WOS研究方向 | Engineering ; Transportation |
WOS类目 | Engineering, Civil ; Engineering, Electrical & Electronic ; Transportation Science & Technology |
WOS记录号 | WOS:000836678700001 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/49804 |
专题 | 多模态人工智能系统全国重点实验室_平行智能技术与系统团队 |
通讯作者 | Dai, Qianzhi; Zheng, Xiaolong |
作者单位 | 1.Beijing Univ Technol, Res Base Beijing Modern Mfg Dev, Beijing 100124, Peoples R China 2.Hubei Univ, Fac Math & Stat, Wuhan 430062, Peoples R China 3.Hefei Univ Technol, Sch Econ, Hefei 230009, Peoples R China 4.Chinese Acad Sci, State Key Lab Management & Control Complex Syst, Inst Automat, Beijing 100190, Peoples R China 5.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100190, Peoples R China |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Xie, Qiwei,Wu, Xiao,Dai, Qianzhi,et al. An Integrated Data Envelopment Analysis and Non-Cooperative Game Approach for Public Transportation Incentive Subsidy Allocation[J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,2022:16. |
APA | Xie, Qiwei,Wu, Xiao,Dai, Qianzhi,Zheng, Xiaolong,&Wang, Fei-Yue.(2022).An Integrated Data Envelopment Analysis and Non-Cooperative Game Approach for Public Transportation Incentive Subsidy Allocation.IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,16. |
MLA | Xie, Qiwei,et al."An Integrated Data Envelopment Analysis and Non-Cooperative Game Approach for Public Transportation Incentive Subsidy Allocation".IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS (2022):16. |
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