Assessing spatial and social dimensions of shared bicycle use in a Southern European island context: The case of Las Palmas de Gran Canaria

Maas, Suzanne; Attard, Maria; Caruana, Mark Anthony

doi:10.1016/j.tra.2020.08.003

Cited by 30 publications

(25 citation statements)

References 45 publications

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“…Therefore, we proved that the E-bike was a good solution compared with motorbikes because E-bike users need bikes for a maximum of 100 km in 2 days' usage and speed capacity from 20 to 30 km/h. In China, long drives, subways, and other sources are good enough for our sampling areas, similar to findings in the Canary Islands in Spain in terms of the factors of distance and cost (Maas et al, 2020).…”

Section: Resultssupporting

confidence: 77%

Factors Affecting Electric Bike Adoption: Seeking an Energy-Efficient Solution for the Post-COVID Era

Yasir

Ahmad

et al. 2022

Front. Energy Res.

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Sustainability think tanks such as the United Nations Organization have a strong focus on achieving economic and environmental sustainability goals globally. On the road to sustainable development, electric bike (E-bike) adoption is crucial. Nevertheless, research on the factors associated with E-Bike use, especially the psychological, financial, and capacity factors, has remained unexplored. This paper extends the theory of planned behavior with six novel factors related to individual choices to analyze E-bike adoption behavior. A sample of 507 Chinese bike riders is collected through the snowball sampling technique. The sample is estimated through structural equation modeling. The key findings are as follows: first, speed capacity, mileage capacity, and real-time camera positively drove E-bike adoption intention. Second, price differentiation negatively affected E-bike adoption intention. Third, the theory of planned behavior factors, including perceived relative advantage, cost savings, subjective norms, perceived behavioral control, and attitudes toward E-bike adoption, proved to be drivers of E-bike adoption intention. Finally, cost savings are the most critical factor of E-bike adoption intention, whereas perceived behavior control is the least critical factor. These results will help green transportation companies and emerging economies promote E-bike adoption to reach the environmental sustainability goals of the United Nations.

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Section: Resultssupporting

confidence: 77%

Factors Affecting Electric Bike Adoption: Seeking an Energy-Efficient Solution for the Post-COVID Era

Yasir

Ahmad

et al. 2022

Front. Energy Res.

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“…Escooters are seen as a convenient and faster alternative to walking, replacing substantially more walking than private car trips (Sanders et al, 2020). Although distances vary between free-floating and stationbased bikesharing trips, reasons to try and use any of the systems are similar, namely high bicycle (station) availability and a user-friendly smartphone application (Link et al, 2020;Maas et al, 2020;Bachand-Marleau et al, 2012). However, the supply density of shared micromobility modes shows a 'plateau effect', i.e.…”

Section: Recent Work About Bike-and E-scootersharingmentioning

confidence: 99%

What drives the utility of shared transport services for urban travellers? A stated preference survey in German cities

Krauss

Krail

Axhausen

2022

Travel Behaviour and Society

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The supply of shared mobility solutions has been increasing during the last years, so has the popularity of Mobility-as-a-Service. Both promise an easy access to and usage of shared vehicles or shared rides. Nevertheless, usage of these services remains low in German cities. Hence, the question arises: what determines the utility of travellers regarding shared modes and how is this different to conventional modes? To answer this, we conduct a stated preference experiment amongst 1,445 respondents (8,670 observations). The sample is drawn from residents of the 83 largest cities in Germany. We consider four shared (e-scooter-, bike-, carsharing, and ridepooling) and three conventional modes (walking, private car, and public transport). We estimate a mixed logit model and calculate the respective value of travel time (VoT) as well as the value of access, egress, and parking search time. The importance of the individual attributes is analysed drawing on a part-worth analysis. Further, we calculate average treatment effects to show simulated mode-choice probability changes. We find that costs are more important than travel time for carsharing and ridepooling whilst they are equally important for the remaining modes. For shared services, access is more important than egress. Moreover, among the shared services, e-scootersharing shows the highest VoT (23.73 EUR/h), followed by bikesharing (18.53 EUR/h). Finally, cost changes to private cars and public transport show the highest simulated shifting potential with carsharing profiting most from cost increases in these two modes.

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“…For bicycle transit, temperature and humidity are positively and negatively associated with cycling, respectively, and precipitation has a significant negative impact on cycling flows with a lagged effect [19][20][21][22]. Further, rain deters cyclists with lower skills from bicycling 2.5 times more strongly than those with better cycling skills in the case study of the Ithaca campus of Cornell [23].…”

Section: Impact Of Weather Elements On Travel Choicesmentioning

confidence: 89%

Understanding Plum Rain’s Effects on Urban Public Bicycle Unavailability Considering Both Place Semantics and Riding Distance

Chen

Zhang

Wang

et al. 2021

IJGI

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The effect of the plum rain weather event on cycling trips reflects the climate resilience of the public bicycle system. However, quantitative studies regarding the impact of plum rain on public bicycle users and corresponding spatial heterogeneity have not been paid much attention. This paper explores the spatial pattern of affected levels from the perspective of cyclist number, place semantics and riding distance. Corresponding public bicycle trips in normal weather are predicted by spatial-temporal random forest prediction. GIS neighborhood statistics and clustering algorithms are adapted to analyze and visualize the affected levels using origin-destination data of public bicycle trips and point of interest data of city public facilities. It is proved that there is an obvious spatial difference in affected levels by plum rain from three dimensions. In the dimension of the number of cyclists, the docking stations with different affected levels are distributed across the whole urban area. In the place semantic dimension, the docking stations with high affected levels show a clustered zonal distribution in the city center. In the dimension of cycling distance, the docking stations with high affected levels are mainly distributed in the periphery of the central urban area. The study theoretically expands the impact mechanism of environment and active transport. It is beneficial for the early monitoring, warning and assessment of climate change risks for public bicycle planning and management.

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Assessing spatial and social dimensions of shared bicycle use in a Southern European island context: The case of Las Palmas de Gran Canaria

Cited by 30 publications

References 45 publications

Factors Affecting Electric Bike Adoption: Seeking an Energy-Efficient Solution for the Post-COVID Era

Factors Affecting Electric Bike Adoption: Seeking an Energy-Efficient Solution for the Post-COVID Era

What drives the utility of shared transport services for urban travellers? A stated preference survey in German cities

Understanding Plum Rain’s Effects on Urban Public Bicycle Unavailability Considering Both Place Semantics and Riding Distance

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