Modeling free-floating car-sharing use in Switzerland: A spatial regression and conditional logit approach

Becker, Henrik; Ciari, Francesco; Axhausen, Kay W.

doi:10.1016/j.trc.2017.06.008

Cited by 87 publications

(37 citation statements)

References 36 publications

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“…Thus, the observations from travel diaries support the theory that free-floating car-sharing does not necessarily lead to more car traffic. Also, these findings complement earlier research showing that free-floating car-sharing is used most often in situations, for which public transport is not attractive [40]. Further, a substantial share of the freefloating car-sharing trips are multi-stage or round trips.…”

Section: Discussionsupporting

confidence: 85%

Measuring the car ownership impact of free-floating car-sharing – A case study in Basel, Switzerland

Becker

Ciari

Axhausen

2018

Transportation Research Part D: Transport and Environment

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128

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Free-floating car-sharing schemes operate without fixed car-sharing stations, ahead reservations or return-trip requirements. Providing fast and convenient motorization, they attract both public transport users and (former) car-owners. Thus, their impact on individual travel behavior depends on the user type. Estimating the travel behavior impact of these systems therefore requires quantitative data. Using a two-wave survey approach (shortly after launch of the scheme plus one year later) including travel diaries, this research indicates that (due to their membership) 6 % of the free-floating car-sharing customers reduce their private vehicle ownership. Moreover, the results suggest that freefloating car-sharing both complements and competes with station-based car-sharing.

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Section: Discussionsupporting

confidence: 85%

Measuring the car ownership impact of free-floating car-sharing – A case study in Basel, Switzerland

Becker

Ciari

Axhausen

2018

Transportation Research Part D: Transport and Environment

Self Cite

128

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“…The validation dataset was collected with a different smartphone application in the city of Basel (Switzerland) during early 2018 (following the setup described in Becker et al 2018and Becker et al (2017)). It contains GPS data from 625 users, with an average of 7.4 days of travel each.…”

Section: Validation Datasetmentioning

confidence: 99%

Developing a passive GPS tracking system to study long-term travel behavior

Marra

Becker

Corman

2019

Transportation Research Part C: Emerging Technologies

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This paper describes development and testing of a passive GPS tracking smartphone application and corresponding data analysis methodology designed to increase the quality of travel behavior information collected in long-term travel surveys. The new approach is intended to replace the pencil-and-paper travel diaries and prompted recall methods that require more user involvement due to requirements for manual data entry and/or high battery usage. Reducing the burden placed on users enables researchers to collect data over longer periods, thus improving the quality of travel behavior research. To reduce battery use the smartphone-based application collects GPS data less frequently than other methods. Therefore, new algorithms were developed to identify trips and activities, transport mode, and even the specific vehicle used by the traveler. An important finding was the significant advantage of using users past data to improve mode detection results. The system was tested successfully in Zürich and Basel (Switzerland).

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“…The conditional Logit model allows us to take into account multiple alternative-specific attributes simultaneously and thus evaluate the effect of these attributes on the choice of bikesharing brands. Additionally, the conditional Logit model has been applied in multiple transportation fields, including carsharing use [41] and travel mode choice [42]. As a member of disaggregate probability models, the conditional Logit model is a discrete choice and analysis method in microeconometrics, and its theoretical basis is that cyclists pursue "utility" maximization when selecting shared bike brands.…”

Section: Methodsmentioning

confidence: 99%

Empirical Study on Bikesharing Brand Selection in China in the Post-Sharing Era

Xiao

Wang

2020

Sustainability

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With the rapid popularization of mobile Internet technology and smart terminal equipment in recent years, the volume and usage of dockless bikesharing (hereafter referred to as bikesharing), which is green, environmentally friendly and convenient, have grown rapidly, making it one of the China’s “new four major inventions.” The development of the bikesharing in China consists of a pre-sharing era and a post-sharing era. In the pre-sharing era, capital-driven vicious market competition and lack of precise control have led to the abuse of urban space. Since the post-sharing era, the industry structure has returned to rationality, and many participants have been forced out of the market. The bikesharing has formed an oligopoly market consisting of head players such as Hellobike, Mobike, and Ofo. Therefore, how to improve the level of refined operations, promote sustainable development, improve cyclist satisfaction, and contribute to China’s strength in transportation have become urgent problems for bikesharing companies and traffic management departments. From the perspective of the cyclist experience, the brand choice of the bikesharing is taken as the research object. An online revealed preference survey is used to collect data on cyclists’ socio-economic attributes and subjective evaluations on the bikesharing. The conditional Logit model is used to explore the important factors that influence cyclists on the choice of bikesharing brands. Research results include: (1) age, occupation type, after-tax monthly income of the faculty group, riding comfort, rent, picking up/returning convenience, word of mouth, and volume have a significant impact on cyclists’ bikesharing brand choices; (2) gender, educational background, monthly living expenses of the student group, appearance, deposit, deposit returning speed, rate of broken bikes, ease of use of software, and rent discount have no significant impact on cyclists’ bikesharing brand choices. The research results are of great significance for improving the service quality of bikesharing companies and promoting the healthy development of the shared economy in China. Based on the results of the study, policy recommendations are made on the improvement for riding comfort, human-centered design, and word of mouth, and the construction of shared facilities.

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Modeling free-floating car-sharing use in Switzerland: A spatial regression and conditional logit approach

Cited by 87 publications

References 36 publications

Measuring the car ownership impact of free-floating car-sharing – A case study in Basel, Switzerland

Measuring the car ownership impact of free-floating car-sharing – A case study in Basel, Switzerland

Developing a passive GPS tracking system to study long-term travel behavior

Empirical Study on Bikesharing Brand Selection in China in the Post-Sharing Era

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