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Erschienen in: Transportation 5/2020

28.05.2019

Steering short-term demand for car-sharing: a mode choice and policy impact analysis by trip distance

verfasst von: Weibo Li, Maria Kamargianni

Erschienen in: Transportation | Ausgabe 5/2020

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Abstract

Car-sharing could have substantial benefits. However, there is not enough evidence about if more people choosing car-sharing would reduce private car usage or public transport demand. This work aims to bring forward some insights by studying short-term car-sharing choice behavior. A mode choice analysis is conducted first followed by a simulation analysis to evaluate modal substitution pattern. Policy implications are obtained in terms of the possible measures that could effectively bring down private car usage. The case study is Taiyuan-China; stated and revealed preference data are collected. Mixed nested logit models are developed to study the pooled SP/RP data. The analysis is conducted separately for a shorter trip case (2–5 km) and a longer trip case (more than 5 km) to examine if results would differ by distance. It is found that raising the cost of private car usage (travel cost, parking cost) should be prioritized for shorter trips since car is more difficult to be substituted when trip distance increases. Shorter trips also need such direct measures to help suppress the demand for private car when promoting a car-sharing service; otherwise car-sharing would attract more bus users instead. Longer trips need a more effective solution to bring down private car usage and that is discovered as making car-sharing service more appealing so that it can serve as a practical substitute to private car. A number of informative indicators (e.g. willingness to pay for travel time savings, direct and cross point elasticity) are also derived to enrich the findings.

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Fußnoten
1
They are named as “medium” and “long” distances because the survey also collected short-distance (within 2 km) trip data. However, < 2 km trips are excluded from this research since car-sharing is not expected to be competitive within such a distance due to the associated access and alighting time (Martínez et al. 2017).
 
2
Recall the strategic-tactical choice framework in Le Vine et al. (2014), our survey did not address the strategic-level car-sharing choice behavior; this is because most car-sharing services in China do not require regular membership fee/long-term commitment, which makes the effect of strategic choice trivial.
 
3
As per the pilot survey feedback there was imperfect knowledge among Taiyuan citizens about what car-sharing really represents. Thus, the concept and key features of a free-floating car-sharing scheme were described in the survey to reduce the bias in their understanding.
 
4
Although an orthogonal design is not as advanced as several later proposed designs, such as the various forms of D-efficient design (Bliemer et al. 2009; Rose and Bliemer 2009; Bliemer and Rose 2010), we still employed this technique given the constraints we had on project cost (i.e. more advanced software such as Ngene is usually needed to handle an efficient design).
 
5
The difference is due to there are different number of attributes between short-dist scenarios and mid- & long-dist scenarios as a result of the different choice sets involved.
 
6
We also tested how many choice tasks being presented in the SP experiment were acceptable to respondents. In the pilot survey we included 10 for each individual to answer, and we found most respondents were averse to a number of scenarios larger than 8.
 
7
However, insignificant “policy variables” (or, level of service variables, such as travel times, travel costs, access times and app availability) are still included in light of the discussions in Ortúzar and Willumsen (2011).
 
8
Possession of a driving license is not an availability condition in this case since we allow the choices of car and car-sharing to come from both drivers and passengers.
 
9
The only exception is observed on the impact of trip purpose. When RP data is involved, bike-sharing is no longer a preferred mode for mid-dist commute trips while taxi and bus are no longer among the preferred modes for long-dist commute trips.
 
10
In fact, we found another nest (between car driver and car passenger) using only the RP data, where the t-statistic also shows significance; however, the nesting parameter μ has a value of 1.03 which is almost equivalent to an MNL specification. Thus, we discarded this nest by following the practice of Ortúzar and Willumsen (2011), in order to retain efficiency in model estimation.
 
11
λ was defined earlier in Eqs. 3 and 4.
 
12
Electric bike does not involve a perceived travel cost.
 
13
The simulation analysis only aims to reveal how people make trade-offs across the attributes; it does not intend to forecast market demand in the real world.
 
14
The findings on car correspond to the cross elasticity values. The probability to choose car is much more elastic to the changes in car-sharing’s attributes in the long-dist case (0.180 is much higher than the rest).
 
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Metadaten
Titel
Steering short-term demand for car-sharing: a mode choice and policy impact analysis by trip distance
verfasst von
Weibo Li
Maria Kamargianni
Publikationsdatum
28.05.2019
Verlag
Springer US
Erschienen in
Transportation / Ausgabe 5/2020
Print ISSN: 0049-4488
Elektronische ISSN: 1572-9435
DOI
https://doi.org/10.1007/s11116-019-10010-0

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