Examining the impact of car-sharing on private vehicle ownership

2020 ◽  
Vol 138 ◽  
pp. 322-341 ◽  
Author(s):  
Fan Zhou ◽  
Zuduo Zheng ◽  
Jake Whitehead ◽  
Robert K. Perrons ◽  
Simon Washington ◽  
...  
Keyword(s):  
Vehicle Ownership ◽  
Car Sharing ◽  
Private Vehicle ◽  
The Impact

Development Trends in Automation

2022 ◽  
pp. 160-167
Keyword(s):  
United States ◽  
21St Century ◽  
Autonomous Vehicles ◽  
The United States ◽  
Current Development ◽  
Vehicle Ownership ◽  
Development Trends ◽  
Private Vehicle ◽  
History Of ◽  
The Impact

This chapter analyzes current development trends in automation. The chapter begins by discussing the history of automation in the 21st century, beginning with Honda's creation of ASIMO. Next, the chapter analyzes how automation gave rise to the relocating of many Western manufacturing centers to Asia, particularly those in the United States. The chapter then analyzes trends in the development of autonomous vehicles. This section includes a detailed projection of likely developments over the next several decades, such as the impact of autonomous vehicles on private vehicle ownership. The chapter concludes with a brief summary of these trends.

scholarly journals The Influence of Urban Sprawl on Air Pollution and the Mediating Effect of Vehicle Ownership

Processes ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 1261
Author(s):  
Aiping Tao ◽  
Qun Liang ◽  
Peng Kuai ◽  
Tao Ding
Keyword(s):  
Air Pollution ◽  
Urban Sprawl ◽  
Negative Impact ◽  
Empirical Support ◽  
Mediating Effect ◽  
Vehicle Ownership ◽  
Mediating Role ◽  
Effect Model ◽  
Significant Negative Impact ◽  
The Impact

Based on the panel data of 224 prefecture-level and above cities in China from 2003 to 2016, this paper empirically studies the impact of urban sprawl on air pollution and introduces a mediating effect model to test the mediating role of vehicle ownership concerning the impact of urban sprawl on air pollution. The research in this paper arrives at three conclusions. First, urban sprawl has a significant positive effect on air pollution, and this conclusion is still valid after solving the endogeneity problem and conducting a robustness test. Second, the results of mediating effect test show that urban sprawl indirectly affects air pollution through the partial mediating effect of vehicle ownership. By removing the mediating effect, urban sprawl has a significant negative impact on air pollution, indicating that the mediating effect of vehicle ownership is higher concerning the impact of urban sprawl on air pollution. Third, further panel quantile regression results show that the higher the level of air pollution, the weaker the mediating effect of vehicle ownership and the stronger the direct effect of urban sprawl on air pollution. These conclusions can provide some empirical support for solving the air pollution problems caused by urban sprawl in China.

scholarly journals Car Sharing In a Compact City: Pinning Down the Benefits and Barriers

2020 ◽  
pp. 1-8
Author(s):  
Ralph Chapman ◽  
◽  
Lucia Sobiecki ◽  
Keyword(s):  
New Zealand ◽  
Urban Development ◽  
Full Advantage ◽  
Carbon Emissions ◽  
Policy Support ◽  
Sustainable Transport ◽  
Vehicle Ownership ◽  
Compact City ◽  
Car Sharing ◽  
Transport Patterns

New Zealand’s sprawling urban development and high levels of car dependency have resulted in significant environmental impacts, including increased carbon emissions and pollution. Car sharing can support sustainable transport patterns by offering an alternative to private vehicle ownership. Internationally, it has become increasingly popular but is still in the early stages of development in New Zealand. A survey of 356 Wellington residents and interviews with 13 car share stakeholders collected data on interest in car sharing and barriers facing the service in New Zealand’s capital. The results suggest that car sharing could become an important mobility option in Wellington and further policy support for car sharing could enable Wellington to take full advantage of its benefits.

scholarly journals Preference Reasons for Recreational Areas Which Belongs to the Local Administrations

2017 ◽  
Vol 5 (11) ◽  
pp. 73
Author(s):  
Abdurrahman Kırtepe ◽  
Oguzhan Altungul ◽  
M. Fatıh Karahuseyınoglu
Keyword(s):  
Health Status ◽  
Normal Distribution ◽  
Outdoor Recreation ◽  
Local Governance ◽  
Distribution Data ◽  
Vehicle Ownership ◽  
Private Vehicle ◽  
Recreation Areas ◽  
Significant Difference ◽  
Multiple Groups

The purpose of this study was to determine the effective factors of people choosing outdoor recreation areas, which is belonging to local government in Elazıg Province Center, for feel comfortable in social, cultural and physiological aspects where they can evaluate their free time and benefit from different purposes according to different variables.The sample group of the study consisted of 232 persons, 106 male and 126 female, selected randomly using recreational areas of local governance in Elazıg province center. The data were obtained by participation preference factors for use of recreation area survey which consist 24 questions and 5 sub-dimensions that developed by Gümüs H. and Alay Özgül S. (2017) with face to face survey application method.The data obtained from the study were analyzed using the SPSS 22 packet program. The normality test has been done so that analyzes can be done correctly. According to this, Kruskal-wallis was used in multiple groups in the analysis of data which not normal distribution and Mann Whitney-u Test was applied to determine the group which the difference occurred. In the analysis of normal distribution data, anova in multiple groups and independent samples t test in binary groups were applied. Significance level was accepted as p<0.05. There was a statistically significant difference between participants who are married and have children, who perform sports 3-4 days a week and who state their health status as good and good and sport diversity, personnel and activity sub-dimensions of the scale (p<0.05). There was no statistically significant difference between the private vehicle ownership variable and participation preference for recreation areas scale (p>0, 05).It was determined that, for participants who married and with children, it is effective that there is playground for children in the recreational areas, the individuals who are good and very good health status are influenced by the sport diversity, activity and personnel situation in choosing these areas, private vehicle ownership is not that important for choosing these areas.

scholarly journals Does free-floating carsharing reduce private vehicle ownership? The case of SHARE NOW in European cities

2020 ◽  
Vol 141 ◽  
pp. 373-395
Author(s):  
Patrick Jochem ◽  
Dominik Frankenhauser ◽  
Lukas Ewald ◽  
Axel Ensslen ◽  
Hansjörg Fromm
Keyword(s):  
Vehicle Ownership ◽  
European Cities ◽  
Private Vehicle

scholarly journals China’s Provincial Vehicle Ownership Forecast and Analysis of the Causes Influencing the Trend

2019 ◽  
Vol 11 (14) ◽  
pp. 3928 ◽  
Author(s):  
Lin Ma ◽  
Manhua Wu ◽  
Xiujuan Tian ◽  
Guanheng Zheng ◽  
Qinchuan Du ◽  
...  
Keyword(s):  
Growth Rate ◽  
Economic Development ◽  
Gompertz Model ◽  
Sustainable Transportation ◽  
Gdp Per Capita ◽  
Employment Rate ◽  
Vehicle Ownership ◽  
Per Capita ◽  
Transport Problems ◽  
The Impact

The growth of vehicle ownership not only brings opportunity for the economy, but also brings environment and transport problems, which is not good for sustainable transportation. It is of great significance to build supporting infrastructure and other services based on accurate forecasts of vehicle ownership in various provinces because of the variance of economic development stages, the carrying capacity of resources, and different degrees of transport planning in each province. We used the Gompertz model in order to predict China’s provincial vehicle ownership from 2018 to 2050. Considering the impact of the population structure, we summed up the growth rate of GDP per labor, the growth rate of population and the growth rate of employment rate to get the growth rate of GDP and then the GDP per capita of each province. We found that the vehicle ownership in each province will grow rapidly in the next 30 years; however, the change in the ranking of vehicle ownership among provinces varies. The ranking of some provinces with high or middle ranking now will decline in the following years, especially Beijing, Tianjin, Shanghai and Xinjiang. While the ranking of some provinces that locates in the middle and low ranking now will increase, such as Chongqing, Hubei, Anhui, Sichuan, Heilongjiang, Jiangxi, Hunan and Guangxi. We also investigate the reasons that affect the trend in each province and we find that the suitable vehicle growth pattern of each province, the stage of economic development and government policy, which are related to the growth rate of GDP per labor, employment rate, and GDP per capita, can affect vehicle ownership in the future.

scholarly journals Does Car-Sharing Reduce Car-Use? An Impact Evaluation of Car-Sharing in Flanders, Belgium

2020 ◽  
Vol 12 (19) ◽  
pp. 8155
Author(s):  
Donald A. Chapman ◽  
Johan Eyckmans ◽  
Karel Van Acker
Keyword(s):  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Experimental Methods ◽  
Car Ownership ◽  
Car Sharing ◽  
Car Use ◽  
Binomial Regression ◽  
Quasi Experimental ◽  
Private Car ◽  
The Impact

Private car-use is a major contributor of greenhouse gases. Car-sharing is often hypothesised as a potential solution to reduce car-ownership, which can lead to car-sharing users reducing their car-use. However, there is a risk that car-sharing may also increase car-use amongst some users. Existing studies on the impacts of car-sharing on car-use are often based on estimates of the users’ own judgement of the effects; few studies make use of quasi-experimental methods. In this paper, the impact of car-sharing on car-ownership and car-use in Flanders, Belgium is estimated using survey data from both sharers and non-sharers. The impact on car-use is estimated using zero-inflated negative binomial regression, applied to matched samples of car-sharing users and non-users. The results show that the car-sharing may reduce car-use, but only if a significant number of users reduce their car-ownership. Policy intervention may therefore be required to ensure car-sharing leads to a reduction in car-use by, for example, discouraging car-ownership. Further research using quasi-experimental methods is required to illuminate whether the promise of car-sharing is reflected in reality.

scholarly journals Identifying and Predicting the Expenditure Level Characteristics of Car-Sharing Users Based on the Empirical Data

2019 ◽  
Vol 11 (23) ◽  
pp. 6689 ◽  
Author(s):  
Sai ◽  
Bi ◽  
Xie ◽  
Guan
Keyword(s):  
Prediction Methods ◽  
Multi Layer Perceptron ◽  
Vehicle Ownership ◽  
Car Sharing ◽  
Positive Role ◽  
Healthy Development ◽  
User Management ◽  
High Investment ◽  
Management Method ◽  
Scientific Decision

Car-sharing plays a positive role in reducing vehicle ownership and greenhouse gas emissions. However, the developmental contradictions between high investment and low revenues hinder the development of the car-sharing industry. Fully understanding car-sharing users can effectively ensure the healthy development of car-sharing companies and promote the development of the entire industry. To this end, this study attempts to develop a user management method that is based on user layering and prediction methods. By using order data from the Lan Zhou car-sharing company in China, this paper develops a clustering method for layering car-sharing users. A multi-layer perceptron model is also developed to categorize these users into different expenditure level categories while considering periodic features. Results show that new users can be divided into three categories according to their expenditures to car-sharing companies within 84 days. After 5 weeks of observation, the 84-day category of new users can be predicted with an accuracy of over 85%. These results provide scientific decision support for the user management and profitability of car-sharing companies.

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