自动驾驶汽车时代的打车平台竞争:重资产还是轻资产?

IF 7.6 1区 工程技术 Q1 TRANSPORTATION SCIENCE & TECHNOLOGY Transportation Research Part C-Emerging Technologies Pub Date : 2024-07-08 DOI:10.1016/j.trc.2024.104732
Xiaoyan Wang , Xi Lin , Meng Li , Zhengtian Xu , Ke Zhang
{"title":"自动驾驶汽车时代的打车平台竞争:重资产还是轻资产?","authors":"Xiaoyan Wang ,&nbsp;Xi Lin ,&nbsp;Meng Li ,&nbsp;Zhengtian Xu ,&nbsp;Ke Zhang","doi":"10.1016/j.trc.2024.104732","DOIUrl":null,"url":null,"abstract":"<div><p>Business modes of ride-hailing services in the era of autonomous vehicles (AVs) could be vastly different from those of current human vehicles (HVs). In addition to the asset-heavy mode, wherein platforms both operate and have ownership of the AV assets, a new business mode known as the asset-light mode is emerging. The asset-light mode involves AV crowdsourcing, where private AV owners rent out their vehicles to platforms (Wang et al., 2021). This paper establishes a game-theoretical framework to model the competition between an asset-heavy platform and an asset-light platform. We first examine the mixed-strategy Nash equilibrium between the two AV ride-hailing services, considering that only the asset-light platform can crowdsource AVs, and then extend the model to allow both platforms to crowdsource AVs. Our analyses demonstrate that, in scenarios with insufficient AV supply, once the number of private AVs exceeds a small threshold, at least one of the platforms will crowdsource AVs, even though they cannot derive economic benefits. As the private AV market grows, the asset-light platform becomes more profitable. We then use numerical results to study the impact of price regulations on market participants and find that when urban planners aim to enhance social surplus, it is best not to regulate maximum trip fare, minimum rental payment, or maximum rental payment. These insights offer guidance for AV ride-hailing service providers and government regulators in the future era of AV commercialization.</p></div>","PeriodicalId":54417,"journal":{"name":"Transportation Research Part C-Emerging Technologies","volume":null,"pages":null},"PeriodicalIF":7.6000,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Competition of ride-hailing platforms in the era of autonomous vehicles: Heavy or light asset?\",\"authors\":\"Xiaoyan Wang ,&nbsp;Xi Lin ,&nbsp;Meng Li ,&nbsp;Zhengtian Xu ,&nbsp;Ke Zhang\",\"doi\":\"10.1016/j.trc.2024.104732\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Business modes of ride-hailing services in the era of autonomous vehicles (AVs) could be vastly different from those of current human vehicles (HVs). In addition to the asset-heavy mode, wherein platforms both operate and have ownership of the AV assets, a new business mode known as the asset-light mode is emerging. The asset-light mode involves AV crowdsourcing, where private AV owners rent out their vehicles to platforms (Wang et al., 2021). This paper establishes a game-theoretical framework to model the competition between an asset-heavy platform and an asset-light platform. We first examine the mixed-strategy Nash equilibrium between the two AV ride-hailing services, considering that only the asset-light platform can crowdsource AVs, and then extend the model to allow both platforms to crowdsource AVs. Our analyses demonstrate that, in scenarios with insufficient AV supply, once the number of private AVs exceeds a small threshold, at least one of the platforms will crowdsource AVs, even though they cannot derive economic benefits. As the private AV market grows, the asset-light platform becomes more profitable. We then use numerical results to study the impact of price regulations on market participants and find that when urban planners aim to enhance social surplus, it is best not to regulate maximum trip fare, minimum rental payment, or maximum rental payment. These insights offer guidance for AV ride-hailing service providers and government regulators in the future era of AV commercialization.</p></div>\",\"PeriodicalId\":54417,\"journal\":{\"name\":\"Transportation Research Part C-Emerging Technologies\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":7.6000,\"publicationDate\":\"2024-07-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transportation Research Part C-Emerging Technologies\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0968090X24002535\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"TRANSPORTATION SCIENCE & TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation Research Part C-Emerging Technologies","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0968090X24002535","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"TRANSPORTATION SCIENCE & TECHNOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

自动驾驶汽车(AV)时代的打车服务商业模式可能与当前的载人汽车(HV)大不相同。除了平台同时运营和拥有自动驾驶汽车资产的重资产模式外,一种被称为轻资产模式的新商业模式正在兴起。轻资产模式涉及 AV 众包,即私人 AV 车主将其车辆出租给平台(Wang 等,2021 年)。本文建立了一个博弈理论框架,以模拟重资产平台和轻资产平台之间的竞争。考虑到只有轻资产平台可以众包 AV,我们首先研究了两种 AV 出租服务之间的混合策略纳什均衡,然后将模型扩展到允许两个平台众包 AV。我们的分析表明,在无人驾驶汽车供应不足的情况下,一旦私人无人驾驶汽车的数量超过一个小阈值,至少有一个平台会众包无人驾驶汽车,即使它们无法获得经济利益。随着私人视听市场的增长,轻资产平台的盈利能力会越来越强。然后,我们利用数值结果研究了价格管制对市场参与者的影响,发现当城市规划者以提高社会剩余为目标时,最好不要管制最高行程票价、最低租金支付或最高租金支付。这些启示为未来无人驾驶汽车商业化时代的无人驾驶汽车租赁服务提供商和政府监管机构提供了指导。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Competition of ride-hailing platforms in the era of autonomous vehicles: Heavy or light asset?

Business modes of ride-hailing services in the era of autonomous vehicles (AVs) could be vastly different from those of current human vehicles (HVs). In addition to the asset-heavy mode, wherein platforms both operate and have ownership of the AV assets, a new business mode known as the asset-light mode is emerging. The asset-light mode involves AV crowdsourcing, where private AV owners rent out their vehicles to platforms (Wang et al., 2021). This paper establishes a game-theoretical framework to model the competition between an asset-heavy platform and an asset-light platform. We first examine the mixed-strategy Nash equilibrium between the two AV ride-hailing services, considering that only the asset-light platform can crowdsource AVs, and then extend the model to allow both platforms to crowdsource AVs. Our analyses demonstrate that, in scenarios with insufficient AV supply, once the number of private AVs exceeds a small threshold, at least one of the platforms will crowdsource AVs, even though they cannot derive economic benefits. As the private AV market grows, the asset-light platform becomes more profitable. We then use numerical results to study the impact of price regulations on market participants and find that when urban planners aim to enhance social surplus, it is best not to regulate maximum trip fare, minimum rental payment, or maximum rental payment. These insights offer guidance for AV ride-hailing service providers and government regulators in the future era of AV commercialization.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
15.80
自引率
12.00%
发文量
332
审稿时长
64 days
期刊介绍: Transportation Research: Part C (TR_C) is dedicated to showcasing high-quality, scholarly research that delves into the development, applications, and implications of transportation systems and emerging technologies. Our focus lies not solely on individual technologies, but rather on their broader implications for the planning, design, operation, control, maintenance, and rehabilitation of transportation systems, services, and components. In essence, the intellectual core of the journal revolves around the transportation aspect rather than the technology itself. We actively encourage the integration of quantitative methods from diverse fields such as operations research, control systems, complex networks, computer science, and artificial intelligence. Join us in exploring the intersection of transportation systems and emerging technologies to drive innovation and progress in the field.
期刊最新文献
An environmentally-aware dynamic planning of electric vehicles for aircraft towing considering stochastic aircraft arrival and departure times Network-wide speed–flow estimation considering uncertain traffic conditions and sparse multi-type detectors: A KL divergence-based optimization approach Revealing the impacts of COVID-19 pandemic on intercity truck transport: New insights from big data analytics MATNEC: AIS data-driven environment-adaptive maritime traffic network construction for realistic route generation A qualitative AI security risk assessment of autonomous vehicles
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1