Factors affecting carsharing program participants’ car ownership changes

Ko, Joonho; Ki, Hyeongyun; Lee, Soojin

doi:10.1080/19427867.2017.1329891

Cited by 46 publications

(21 citation statements)

References 29 publications

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“…Other context-specific factors are the availability of public transport and parking spaces, the types of shared cars, and the cultural context. Two studies analyze station-based car-sharing in Seoul, South Korea, and find that good public transport and parking space problems are critical to motivating people to abandon cars [22,23]. The authors estimate that one station-based car replaces three to five private cars, for the latter assuming a member-to-car ratio of 40:1, which is the median ratio of all reviewed studies that report members and vehicles.…”

Section: Station-based Car-sharingmentioning

confidence: 99%

“…However, the share of active subscribers is unknown, and survey participants are disproportionately active. Therefore, we consider a ratio of 40:1 as a conservative but reasonable benchmark [22,23]. Another study from China suggests that the potential savings in the number of cars can be even greater in developing countries, as most households do not yet own a car [24].…”

Section: Station-based Car-sharingmentioning

confidence: 99%

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Does Car-Sharing Reduce Car Ownership? Empirical Evidence from Germany

Kolleck

2021

Sustainability

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The sharing economy is making its way into our everyday lives. One of its business models, car-sharing, has become highly popular. Can it help us increase our sustainability? Besides emissions and vehicle miles traveled, one key aspect in the assessment regards the effect of car-sharing on car ownership. Previous studies investigating this effect have relied almost exclusively on surveys and come to very heterogeneous results, partly suggesting spectacular substitution rates between shared and private cars. This study empirically explores the impact of car-sharing on noncorporate car ownership and car markets in 35 large German cities. The analysis draws on publicly available data for the years 2012, 2013, 2015, and 2017, including, among others, the number of shared cars per operating mode (free-floating and station-based) and the number of cars owned and registered by private individuals (i.e., excluding company cars). We find that one additional station-based car is associated with a reduction of about nine private cars. We do not find a statistically significant relation between car ownership and free-floating car-sharing. Neither type of car-sharing appears to impact the markets for used and new cars significantly. Given the measurable impacts on car ownership levels, this result is surprising and invites future research to study car-sharing’s impact on the dynamics of car markets.

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Section: Station-based Car-sharingmentioning

confidence: 99%

Section: Station-based Car-sharingmentioning

confidence: 99%

Does Car-Sharing Reduce Car Ownership? Empirical Evidence from Germany

Kolleck

2021

Sustainability

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“…The second one is related to their impacts on travel behavior (e.g., impacts on activity patterns or mode choice decisions). The current literature has mainly covered bikesharing [19][20][21][22][23][24], carsharing [15,[25][26][27][28], on-demand ride services [29], and recently kick scooter sharing [30,31]. The scarcity of scientific literature on moped sharing is a point underlined by Howe and Bock [32].…”

Section: Literature Review: Shared Mobility and Travel Behaviormentioning

confidence: 99%

Moped Scooter Sharing: Citizens’ Perceptions, Users’ Behavior, and Implications for Urban Mobility

Aguilera-García¹

2021

Sustainability

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In recent years, moped-style scooter sharing is gaining increasing attention in many urban areas worldwide. Nevertheless, research contributions are still limited, unlike other shared mobility systems. This paper is aimed at providing a first insight on moped sharing demand by exploring the usage and opinions towards this new mobility alternative. To that end, the research exploits the data from a web-based survey conducted in Spain, one of the countries with the largest implementation around the world in terms of the shared e-mopeds fleet. Kruskal–Wallis tests were conducted to identify the segment of the urban population that is more likely adopted moped sharing, and additional statistical mean differences in specific variables concerning moped sharing were carried out. The paper also provides a better understanding of the shared mopeds market and some implications for urban mobility, such as the potential role of shared mopeds in reducing vehicle ownership and its effect on urban modal shift. Furthermore, two discrete choice models were developed to (i) analyze the key drivers determining the willingness to use moped sharing, and (ii) explore individuals’ opinions on whether owning a private vehicle will not be a need in the future. The results indicate that age, occupation, income, and environmental awareness seem to be among the main reasons behind the potential use of these services in the future. The results may be useful for both operators and transport planners when designing actions and policy efforts addressing this mobility option and urban mobility in general.

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“…In fact, car-sharing has been promoted by the City of Bremen, Germany, to reduce vehicular travel (Glotz-Richter 2016). The strong links between car-sharing membership and use and auto ownership levels and use suggest that car-sharing service membership acts as an alternative from among the full range of mobility tools considered by households (Wittwer and Hubrich 2018;Ko, Ki, and Lee 2019;Rotaris, Danielis, and Maltese 2019). As such, car-sharing has been implemented in recent mobility models, including Cangialosi, Di Febbraro, and Sacco (2015), Zhou and Kockelman (2011), Costain, Ardron, and Habib (2012), and de Lorimier and El-Geneidy (2013).…”

Section: Car-sharingmentioning

confidence: 99%

Navigating a fad or the future? Opportunities and limitations in integrating carshare membership and automated vehicle propensity in travel demand forecasting

Petersen¹,

Sweet

2021

Transportation Planning and Technology

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New mobility services, including carsharing and automated vehicles (AVs), are changing mobility. Gathering evidence on the prospective adoption and uncertainty surrounding new technologies is critical, but technological changes outpace the speed with which planners can inform policy. This study demonstrates the feasibility of bridging planners' programming and experimentation responsibilities in navigating uncertainty by developing forecasting tools which account for new technologies and fuse data from a large-scale Canadian household travel survey, the Transportation Tomorrow Survey (2016), with a onetime, internet-based survey with questions related to new mobility services. This study uses a fused nested logit model to explore the characteristics of consumers with propensities towards AV ownership and carshare membership in the Greater Toronto and Hamilton Area. Findings indicate joint effects of these two technologies. This approach of utilizing smaller-scale, issue-focused surveys in conjunction with traditional regional household travel surveys offers significant potential for planners to prepare more nimbly for uncertainty.

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Factors affecting carsharing program participants’ car ownership changes

Cited by 46 publications

References 29 publications

Does Car-Sharing Reduce Car Ownership? Empirical Evidence from Germany

Does Car-Sharing Reduce Car Ownership? Empirical Evidence from Germany

Moped Scooter Sharing: Citizens’ Perceptions, Users’ Behavior, and Implications for Urban Mobility

Navigating a fad or the future? Opportunities and limitations in integrating carshare membership and automated vehicle propensity in travel demand forecasting

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