Carsharing’s life-cycle impacts on energy use and greenhouse gas emissions

Chen, T. Donna; Kockelman, Kara M.

doi:10.1016/j.trd.2016.05.012

Cited by 191 publications

(105 citation statements)

References 28 publications

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“…It has been defined as a system that allows people to use locally available cars at any time and for any duration (Frenken 2015), and is often referred to as a prime example to explain the advantages of sharing over owning and exploiting underutilized assets (Botsman and Rogers 2010). Carsharing has the potential to satisfy individualized transportation demands in a sustainable and socially beneficial way, by decreasing the demand for cars, lowering emissions (using smaller and cleaner cars), reducing traffic and parking congestion, and increasing social cohesion amongst sharers (Prettenthaler and Steininger 1999;Loose 2010;Martin and Shaheen 2011;Shaheen and Cohen 2013;Chase 2015).…”

Section: Introductionmentioning

confidence: 99%

Carsharing business models in Germany: characteristics, success and future prospects

Münzel

Boon

Frenken

et al. 2017

Inf Syst E-Bus Manage

100

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Carsharing provides an alternative to private car ownership by allowing car use temporarily on an on-demand basis. Operators provide carsharing services using different business models and ownership structures. We distinguish between cooperative, business-to-consumer (B2C) roundtrip and one-way, as well as peer-topeer (P2P) carsharing. This paper characterizes these different types of business models and compares their success in terms of diffusion using a comprehensive database of all 101 German carsharing providers in 2016. The key result holds that fleet size is significantly different across business models ranging from a few cars (cooperatives in small towns), to a few hundred (B2C roundtrip in larger cities), to over a thousand (B2C one-way in largest cities), up to multiple thousands (P2P across the country). By analyzing for each operator the number of cars per capita in the city they operate in, we do not find significant differences across business models indicating the viability of each separate business model type. Hence, we conclude that business models will continue to co-exist for a while, although some of the business models may well converge in the longer run due to Internet-ofThings applications and the introduction of self-driving cars.

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Section: Introductionmentioning

confidence: 99%

Carsharing business models in Germany: characteristics, success and future prospects

Münzel

Boon

Frenken

et al. 2017

Inf Syst E-Bus Manage

100

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“…The schemes attract both scientific interest and customers around the world [8]. 20 The literature suggests that station-based car-sharing reduces private vehicle ownership as well as vehicle kilometers travelled [9,10,11], although there has been less agreement on the magnitude of this impact [12]. Moreover, previous research has consistently revealed that car-sharing schemes blossom best in dense 25 urban areas with a good public transportation supply and mainly attract young, highly-educated, higher-income, urban, car-free and single-household residents [13,14,3].…”

Section: Introductionmentioning

confidence: 99%

Modeling car-sharing membership as a mobility tool: A multivariate Probit approach with latent variables

Becker

Loder

Schmid

et al. 2017

Travel Behaviour and Society

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Individual travel behavior is to a large extent shaped by the respective portfolio of available mobility tools such as cars, season-tickets or a car-sharing membership. However, the choices of different mobility tools are interdependent and are also affected by individual attitudes. This paper presents an approach to jointly model the choice of four different mobility tools -including car-sharing. Using data from the Swiss transportation micro census of 2005 and 2010, itis shown that car-sharing is used as a supplement to a public transportationoriented lifestyle, but is also used by car owners. The results further indicate that personal attitudes have a substantial effect on the choice of mobility tools and should therefore be accounted for when modeling such decisions.

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“…Few studies have quantified the magnitude of this impact. However, three are summarized in Chen and Kockelman (2016):  Looking at car-sharing and parking at the building scale in Toronto, Engel-Yan and Passmore (2013) found that buildings with dedicated car-share vehicles required 50% fewer parking spaces than those without such dedications.…”

Section: Parking Infrastructure Demandmentioning

confidence: 99%