基于结构方程模型的街道专用共享停车场对共享感知和汽车拥有率的影响

IF 1.6 4区 工程技术 Q4 TRANSPORTATION Journal of Transport and Land Use Pub Date : 2023-07-27 DOI:10.5198/jtlu.2023.2256
Felix Czarnetzki
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引用次数: 0

摘要

汽车共享被认为是减少汽车拥有量的有效工具,尤其是在人口密集的城市地区。专用的街道汽车共享停车位(CPS)是一种很有前途但研究不足的方法,以增加汽车共享的吸引力和影响。自2017年以来,德国汉堡一直专注于在市中心居民区提供这种小型共享停车位。本文的研究基于对这些停车位使用者的调查数据。本文采用结构方程模型研究了共享汽车专用车位对共享汽车用户的汽车拥有量和共享汽车感知的影响。研究结果证实,提供专属且方便的共享汽车停车位促进了共享汽车作为私家车可行替代品的认知,最终导致实际汽车保有量降低。然而,这些设施的可用性限制,如使用距离长或停车违规,导致其有效性的重大损失。
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The effects of exclusive on-street carsharing parking on carsharing perception and car ownership: A structural equation modeling approach
Carsharing is considered an effective tool for reducing car ownership, especially in high-density urban areas. Dedicated on-street carsharing parking spaces (CPS) are a promising but under-researched approach to increase the attractiveness and impact of carsharing. Since 2017, Hamburg, Germany, has focused on providing small clusters of such carsharing parking spaces in inner-city residential neighborhoods. This paper is based on survey data of users of these parking spaces. A structural equation model is applied to examine the effects of exclusive carsharing parking spaces on the perception of carsharing as well as on car ownership of carsharing users. The results confirm that the provision of exclusive and conveniently accessible carsharing parking spaces promotes the perception of carsharing as a viable substitute for private cars, which ultimately leads to lower actual car ownership. However, perceived usability constraints of these facilities, such as long access distances or parking violations, lead to significant losses in their effectiveness.
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来源期刊
CiteScore
3.40
自引率
5.30%
发文量
34
审稿时长
30 weeks
期刊介绍: The Journal of Transport and Land Usepublishes original interdisciplinary papers on the interaction of transport and land use. Domains include: engineering, planning, modeling, behavior, economics, geography, regional science, sociology, architecture and design, network science, and complex systems. Papers reporting innovative methodologies, original data, and new empirical findings are especially encouraged.
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