{"title":"纽约市的打车拥堵费有用吗?","authors":"Yanchao Li, Daniel Vignon","doi":"10.1016/j.tra.2024.104274","DOIUrl":null,"url":null,"abstract":"<div><div>What is the impact of congestion policies targeting ride-hailing systems? This work empirically evaluates NYC’s congestion surcharge policy, particularly in light of the city’s forthcoming implementation of congestion pricing. Using a Difference-in-Differences (DiD) framework, our analysis reveals a statistically significant reduction of approximately 11% in overall ride-hailing travel volume following the implementation of the policy. In particular, Lyft experienced a 17% reduction in travel demand while Uber and yellow-cabs experienced reductions of about 9% and 8% respectively. We further elucidate two key mechanisms — travel distance and subway station availability — to explain this reduction. The surcharge policy has a more pronounced impact on shorter trips (with the most significant decline observed in trips less than one mile), and on ride-hailing trips originating from areas with at least one substitute (such as subway or Citi Bike). Furthermore,the policy’s effect seems more pronounced in lower-income areas of the city and seems to reduce street-hailing industry revenues by 8%. However, despite these reductions, the policy does not result in a corresponding decrease in traffic congestion. Thus, it seems that the policy results in a net welfare loss for the city, at least in the shorter term. Our findings provide insights for understanding the dynamics of congestion policies focused on the ride-hailing industry, especially as New York City prepares to introduce congestion pricing.</div></div>","PeriodicalId":49421,"journal":{"name":"Transportation Research Part A-Policy and Practice","volume":"190 ","pages":"Article 104274"},"PeriodicalIF":6.3000,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Do ride-hailing congestion fees in NYC work?\",\"authors\":\"Yanchao Li, Daniel Vignon\",\"doi\":\"10.1016/j.tra.2024.104274\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>What is the impact of congestion policies targeting ride-hailing systems? This work empirically evaluates NYC’s congestion surcharge policy, particularly in light of the city’s forthcoming implementation of congestion pricing. Using a Difference-in-Differences (DiD) framework, our analysis reveals a statistically significant reduction of approximately 11% in overall ride-hailing travel volume following the implementation of the policy. In particular, Lyft experienced a 17% reduction in travel demand while Uber and yellow-cabs experienced reductions of about 9% and 8% respectively. We further elucidate two key mechanisms — travel distance and subway station availability — to explain this reduction. The surcharge policy has a more pronounced impact on shorter trips (with the most significant decline observed in trips less than one mile), and on ride-hailing trips originating from areas with at least one substitute (such as subway or Citi Bike). Furthermore,the policy’s effect seems more pronounced in lower-income areas of the city and seems to reduce street-hailing industry revenues by 8%. However, despite these reductions, the policy does not result in a corresponding decrease in traffic congestion. Thus, it seems that the policy results in a net welfare loss for the city, at least in the shorter term. Our findings provide insights for understanding the dynamics of congestion policies focused on the ride-hailing industry, especially as New York City prepares to introduce congestion pricing.</div></div>\",\"PeriodicalId\":49421,\"journal\":{\"name\":\"Transportation Research Part A-Policy and Practice\",\"volume\":\"190 \",\"pages\":\"Article 104274\"},\"PeriodicalIF\":6.3000,\"publicationDate\":\"2024-10-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transportation Research Part A-Policy and Practice\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0965856424003227\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation Research Part A-Policy and Practice","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0965856424003227","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
What is the impact of congestion policies targeting ride-hailing systems? This work empirically evaluates NYC’s congestion surcharge policy, particularly in light of the city’s forthcoming implementation of congestion pricing. Using a Difference-in-Differences (DiD) framework, our analysis reveals a statistically significant reduction of approximately 11% in overall ride-hailing travel volume following the implementation of the policy. In particular, Lyft experienced a 17% reduction in travel demand while Uber and yellow-cabs experienced reductions of about 9% and 8% respectively. We further elucidate two key mechanisms — travel distance and subway station availability — to explain this reduction. The surcharge policy has a more pronounced impact on shorter trips (with the most significant decline observed in trips less than one mile), and on ride-hailing trips originating from areas with at least one substitute (such as subway or Citi Bike). Furthermore,the policy’s effect seems more pronounced in lower-income areas of the city and seems to reduce street-hailing industry revenues by 8%. However, despite these reductions, the policy does not result in a corresponding decrease in traffic congestion. Thus, it seems that the policy results in a net welfare loss for the city, at least in the shorter term. Our findings provide insights for understanding the dynamics of congestion policies focused on the ride-hailing industry, especially as New York City prepares to introduce congestion pricing.
期刊介绍:
Transportation Research: Part A contains papers of general interest in all passenger and freight transportation modes: policy analysis, formulation and evaluation; planning; interaction with the political, socioeconomic and physical environment; design, management and evaluation of transportation systems. Topics are approached from any discipline or perspective: economics, engineering, sociology, psychology, etc. Case studies, survey and expository papers are included, as are articles which contribute to unification of the field, or to an understanding of the comparative aspects of different systems. Papers which assess the scope for technological innovation within a social or political framework are also published. The journal is international, and places equal emphasis on the problems of industrialized and non-industrialized regions.
Part A''s aims and scope are complementary to Transportation Research Part B: Methodological, Part C: Emerging Technologies and Part D: Transport and Environment. Part E: Logistics and Transportation Review. Part F: Traffic Psychology and Behaviour. The complete set forms the most cohesive and comprehensive reference of current research in transportation science.