Car Ownership Research Articles

The challenge of making EVs just affordable enough: Assessing the impact of subsidies on equity and emission reduction in Ireland

Governments support the switch to electric vehicles (EVs) through subsidies and other incentives, as this is expected to help meet climate targets. This research examines the affordability of EVs for Irish households, focusing on equity implications and the impact of affordability on achieving decarbonisation goals. Affordability is estimated for eight scenarios, considering both current and reduced EV prices, and assessed across Ireland. The research finds that flat-rate subsidies do not adequately support lower-income households, impede EV adoption, and could jeopardise the achievement of emission reduction targets. Need-based subsidies would ensure more inclusive EV uptake. If current prices are considered, the target for the number of EVs on the road by 2030 can be met only with the purchase of small-sized EVs. This suggests that achieving EV targets is unlikely without promoting smaller vehicles. The current €3500 EV grant may be insufficient for many households without extended loan terms. Therefore, differentiated subsidies based on income and household size are recommended to increase EV adoption. Households in remote rural areas, where forced car ownership is high, require higher subsidies. In contrast, urban areas could receive lower subsidies to promote the use of more sustainable transport modes, such as cycling, shared mobility, and public transport.

Rebound effects flatten differences in carbon footprints between car-free households, minimal drivers, and green car owners

Abstract While the greenhouse gas emissions of most sectors are declining in the EU, transport emissions are increasing. Passenger cars compose a large share of the transport sector emissions, and a lot of effort has been made to reduce them. Despite the significantly improved environmental performance of passenger cars, there is a prevailing belief that they are the most harmful mode of ground transport. In the study at hand, we illustrate how rebound effects of consumption may change this view. Passenger car is a relatively expensive transport mode. Expenditure on car-ownership reduces the remaining household budget and the related carbon footprint. Here, we compare the total consumer carbon footprints per capita between fossil-fuel car owners, green car owners, and car-free households in the Nordic countries, using survey data including 7 400 respondents. When income and household type are controlled with regression analysis, respondents without a car for climate reasons and “minimal drivers”, meaning the least driving 10% of fossil-fuel car owners, have the lowest carbon footprints. Other car-free households have 6% higher footprints, electric- and biofuel car owners 18%-24% higher footprints, and the increasingly driving fossil-fuel car owners 30%-189% higher carbon footprints than the first two groups. However, the working middle-income green car owners, minimal drivers, and car-free households have very similar sized carbon footprints. The results show some trade-off between car ownership and flying despite that the data was collected between 2021 and 2022, when COVID-19 was still partly affecting air travel.

Merchants and Technological Progress (A Case Study of the Vologda Governorate during the Second Half of the 19th and Early 20th Centuries)

This article shows, based on a detailed analysis of both archival and published sources (including the periodical “Vologodskie Gubernskie Vedomosti” (‘Vologda Provincial Gazette’)), how Vologda merchants used various technological advancements in their business and daily practices during the second half of the 19th and early 20th centuries. In the Russian Empire, it was the time of rapid science and technology development, with innovations becoming increasingly integrated into everyday life. The merchants of the Vologda Governorate, like those in other regions, were the early adopters of this progress, adjusting and exploiting the changes for their benefit. In the 1850s–1860s, they already actively used machinery and equipment, some imported from England, to facilitate industrial manufacturing and ease commercial operations. In the 1870s–1890s, they opened photography studios and began utilizing telephone communications. During the 1880s, electric lighting made its debut in the Vologda Governorate, which was at a distillery owned by the heirs of the merchant I.A. Pervushin. The emergence of electric theaters in the region is also associated with the efforts of local merchants. In the early 20th century, cinematography flourished, with M.D. Pervushin’s electric theater “Apollo” being one of the best in Vologda. Besides, the merchant class was at the forefront of promoting the use of cars, and among the first seven car owners in Vologda was the merchant D.I. Titov.

Car sharing user groups and their changes in car ownership: A latent cluster analysis

Car sharing contributes to reducing emissions, resource depletion, and land take, by promoting more efficient use of vehicles that on average sit idle 96% of the time. But consumer adoption remains limited. User segmentation studies can inform efforts to mobilize potential users to join car sharing, and to anticipate what their needs and usage characteristics will be. This paper proposes a comprehensive segmentation method based on socio-demographic variables, which reveals differences in preferences for car sharing platform type, usage characteristics and societal outcomes of car sharing use. To do so, we apply a three step Latent Cluster Analysis to a nationwide sample of active car sharing users. This method results in a set of user segments that reflect distinct life phases, with different needs in terms of the frequency and type of trips made by car sharing. This is reflected in different preferences for car sharing platform types, as the likelihood to use peer-to-peer car sharing as opposed to business-to-consumer car sharing differs by user segment. The segments do not differ substantially in their motivations for engaging with car sharing. Yet, environmental motivations for car sharing outrank financial motivations, while social motivations play no substantial role. The clusters do show substantial differences in the changes in car ownership that occur while being an active car sharing member as well as the likelihood to use car sharing in place of a private car rather than public transport or walking and biking. We conclude that a comprehensive segmentation method based on socio-demographic variables provides actionable insights for upscaling car sharing adoption, as well as targeting specific user segments in order to optimize societal outcomes from car sharing use.

Short Term Prediction of Urban Traffic Flow based on Machine Learning Algorithms

With the increasing per capita car ownership worldwide, existing transportation facilities are unable to fully meet people's travel needs. The massive traffic flow can lead to traffic congestion, so predicting traffic flow can play a crucial role in urban traffic management. This study predicts the westbound traffic flow data of the Minnesota Department of Transportation (MN DoT) ATR 301 station on Interstate 94 in the United States for 28 consecutive days using a Long Short-Term Memory Network (LSTM) data prediction model. The Random Forest is utilized to analyze the association between attributes and the historical data has been separated into 1-hour intervals. The highway displays a bimodal pattern on weekdays and a unimodal pattern on holidays, according to the final forecast results. Furthermore, after making the necessary adjustments to the parameters, the simulated trend closely resembles the real value, proving that LSTM can be used to model short-term traffic flow. Accurately predicting urban traffic flow can make the management of urban traffic management systems more comprehensive and provide citizens with higher quality travel planning references.

Does Car Dependence Make People Unsatisfied With Life? Evidence From a U.S. National Survey

In the United States (U.S.), cars play a key role in facilitating mobility. Americans heavily rely on their cars for daily travel due to the benefits of access, convenience, comfort, and autonomy that private vehicle travel offers. However, the potential negative implications of high rates of car ownership and use for wellbeing, sustainability, and social equity have sparked the interest of many scholars. We contribute to these lines of inquiry by examining whether and if so, how car dependence relates to people’s satisfaction with life. Our data come from a national survey with a representative sample (n = 2,155) of U.S. adults living in urban and suburban areas. Using descriptive statistics and multivariate regression models, we find that there is a threshold effect of car dependence on life satisfaction. Our results show that beyond a certain point, increases in car dependence yield a decrease in people’s satisfaction with life. For instance, we find that, in a typical week, relying on a car for more than 50 percent of the time for out-of-home activities is associated with a decrease in life satisfaction. These findings suggest that planners and decision-makers should promote multimodality and land use patterns that may help to reduce car dependence and its potential negative effect on subjective wellbeing (SWB).

Impact of Advertisement Informativeness and eWOM on Brand Advocacy: Self-Brand Connection as a Mediator

Advancements in social media technologies have empowered consumers with instant information about anything they wish for. The implications of such power are quite profound on brands, as any word circulating on social media about them can make or break within no time. Brand advocacy can be a ray of hope for brands in helping to set some direction favorable to their image. To understand how brand advocacy works and how consumers convert into brand advocates, it is very important first to understand how relationships between brands and consumers are formed. Nothing better than the concept of self-brand connection explains how a sustainable relationship is formed between brands and consumers. However, how self-brand connection itself is formed and how it leads to brand advocacy is poorly understood in the literature. Informative advertising and electronic word of mouth are among the ways through which self-brand connection is formed. Scant attention has been given in the literature on the relationship of electronic word of mouth with self-brand connection, even if electronic word of mouth today is seen as shaping consumer decisions. More importantly, the negligible attention of scholars has gone on to establish the mediational role of self-brand connection in relationships between advertisement informativeness and, electronic word of mouth and brand advocacy. This study thus provides a two-fold contribution to the literature by not only examining the relationship of electronic word of mouth with self-brand connection alongside advertisement informativeness. But also uncovers mediation of self-brand connection in relationships of advertisement informativeness and electronic word of mouth with brand advocacy. The population for this study was car owners of all auto brands plying in the Kingdom of Saudi Arabia. A snowball sampling method was employed, through which 338 responses from car owners were collected from two regions of Saudi Arabia. Structural equation modeling was used to test all hypotheses of the study simultaneously. Results of the study reported that both advertisement informativeness and electronic word of mouth exhibited a statistically significant positive relationship with the self-brand connection. Self-brand connection was also reported to exhibit a significant positive relationship with brand advocacy in this study. Self-brand connection is fully mediated in both relationships of advertisement informativeness and electronic word of mouth with brand advocacy. The key to converting consumers into brand advocates and sustainable enjoyment of growing market share lies in the understanding of the self-brand connection. However, to achieve a self-brand connection, both advertisement informativeness and favorable electronic word of mouth are indispensable. Future research directions and some limitations are also outlined in this study.

Electric vehicle drivers’ choices of expressway usage and peak avoidance: an empirical analysis considering the random effects among individuals

ABSTRACT Traffic congestion is a persistent challenge in urban areas, particularly with increased private car ownership post-COVID-19. Traditional administrative measures to manage traffic demand have proven unsustainable, necessitating more effective strategies. This study examines trajectory data from 3,064 commuting (CMT) and 2,690 non-commuting (Non-CMT) electric vehicles in Shanghai to analyze how travel purposes, distances, directions, and departure times influence expressway usage and peak avoidance decisions. It identifies significant differences in choices between CMT and Non-CMT users, highlighting the need for personalized travel management methods based on vehicle usage patterns. Route management strategies should focus on commuting trips for CMT vehicle users, while spatial control measures considering the trip distance and direction can reduce Non-CMT vehicle users’ dependence on expressways during peak hours. This research contributes to enhancing our understanding of the heterogeneity of travelers’ behaviors and offers personal and practical insights for managing traffic congestion sustainably in metropolitan cities.

Analysis of Spatiotemporal Changes and Multi-scale Socio-economic Driving Factors of PM2.5 and Ozone in Beijing-Tianjin-Hebei and Its Surroundings

Based on PM2.5 and O3 remote sensing concentration data in Beijing-Tianjin-Hebei and its surrounding areas from 2015 to 2020, we used trend analysis, geographic detectors, and a geographically and temporally weighted regression model to explore the spatiotemporal characteristics and key driving socio-economic factors of multi-scale PM2.5 and O3 concentrations. The results indicated that： ① The changing slope of PM2.5 concentration ranged from -12.93 to 0.43 μg·（m3·a）-1, and the changing slope of O3 concentration ranged from 0.70 to 14.90 μg·（m3·a）-1. The decreasing slope of PM2.5 concentration was the largest in winter, and the increasing slope of O3 concentration was the largest in summer. ② The concentrations of PM2.5 and O3 were spatially correlated, and the H-H concentrations of PM2.5 were located in the southern Hebei Province and the northern Henan Province. The spatial clustering pattern of O3 changed greatly. ③ From the perspective of urban agglomeration, the GDP, population density, and civilian car ownership had a strong explanatory power for PM2.5, while GDP, urbanization rate, and civilian car ownership had a strong explanatory power for O3. The dominant interaction factors of 2016 and 2020 were the population density∩the proportion of the secondary industry and urbanization rate∩road network density, respectively. ④ From the perspective of single city, population density, industrial nitrogen oxide emissions, and electricity consumption had mainly positive effects on PM2.5 and O3 pollution and became the socio-economic driving factors that need to be focused on to control PM2.5 and O3 co-pollution.

Factors Influencing Transportation Mode Preferences for Educational Trips Among Dormitory Resident University Students in Kütahya, Türkiye

This study explores the transportation behaviors of university students residing in dormitories in Kütahya, Türkiye, emphasizing their preferred modes for educational trips. Utilizing a Multinomial Logit model, the research analyzes the influence of socio-demographic factors, trip characteristics, and environmental perceptions on mode choice. The results indicate that public transport and walking are the predominant modes, with significant negative associations being observed between car ownership and the likelihood of choosing these sustainable options. Key findings reveal that, as trip distances increase, students are more likely to use public transport, while higher income levels decrease reliance on both public transport and walking. Male students demonstrate a higher preference for these modes compared to female students. Environmental perceptions, including feelings of safety and satisfaction with infrastructure, play a critical role in shaping transportation choices, highlighting the need for improved lighting, walkability, and public transport quality. These insights have important implications for transportation policy, suggesting that reducing private vehicle reliance and enhancing public transport services can significantly promote sustainable travel behaviors. Overall, the study underscores the importance of comprehensive transportation policies that not only enhance infrastructure and service quality but also consider environmental perceptions and safety to promote sustainable travel behaviors among university students.

The impact of congestion charging on car ownership: Evidence from a quasi-natural experiment

The impact of congestion charging on car ownership: Evidence from a quasi-natural experiment

Augmenting last-mile connectivity with multimodal transport: Do choice riders favor integrated bike taxi-bus service in metro cities?

While the pursuit of sustainable measures to arrest private vehicle usage and externalities continues, poor last-mile connectivity remains a major deterrent for choice riders (car owners) considering the use of public transport. The present study proposes an integrated Bike Taxi-Bus Service (BTBS) system as a solution to last-mile connectivity concerns and investigates the perception of choice riders towards BTBS. The research was carried out in two Indian metro cities, tier 1 (Bangalore) and tier 2 (Kochi), where bike taxi and bus services operate independently, albeit without integration. The study investigates the perception of choice riders in two stages. Firstly, to identify key intervention areas for the development of an integrated BTBS system. Secondly, to develop econometric models for the estimation of choice riders’ Willingness to Pay (WTP) for BTBS attributes and their potential shift in demand towards BTBS. Additionally, a sensitivity analysis was conducted to explore the influence of various attributes on demand shift and to establish appropriate attribute levels to attract choice riders. While intervention areas are identified using Revised Importance Satisfaction Analysis (Revised ISA), Mixed Logit (ML) models are developed to estimate demand and WTP values. Unlike previous studies, intervention areas are identified using factor structure and management schemes. The study demonstrates the application of Revised ISA in attribute selection for econometric modelling. The work identified 50% of the listed attributes as intervention areas and notably higher WTP values of choice riders for BTBS attributes. This indicates the promise of BTBS while emphasizing the need for urgent attention.

An Adaptive Framework for Traffic Congestion Prediction using Deep Learning

Aim and background: Congestion on China's roads has worsened in recent years due to the country's rapid economic development, rising urban population, rising private car ownership, inequitable traffic flow distribution, and growing local congestion. As cities expand, traffic congestion has become an unavoidable nuisance that endangers the safety and progress of its residents. Improving the utilization rate of municipal transportation facilities and relieving traffic congestion depend on a thorough and accurate identification of the current state of road traffic and necessitate anticipating road congestion in the city. Methodology: In this research, we suggest using a deep spatial and temporal graph convolutional network (DSGCN) to forecast the current state of traffic congestion. To begin, we grid out the transportation system to create individual regions for analysis. In this work, we abstract the grid region centers as nodes, and we use an adjacency matrix to signify the dynamic correlations between the nodes. Results and Discussion: The spatial correlation between regions is then captured utilizing a Graph Convolutional-Neural-Network (GCNN), while the temporal correlation is captured using a two-layer long and short-term feature model (DSTM). Conclusion: Finally, testing on real PeMS datasets shows that the DSGCN has superior performance than other baseline models and provides more accurate traffic congestion prediction.

Evaluation of practicality of wireless charging for electric vehicles in the next 10 years

As the electric vehicle market is expanding rapidly due to the need for sustainable development; a solution is needed to deal with current problems related to electric vehicles, this includes relatively limited driving range, relatively lack of charging spots during busy season, and the inconveniences of plug-in charging, such as dealing with cables. Therefore, wireless charging technology capable of charging electric vehicles while they are in motion becomes a potential solution. Assessing whether this technology will be mass-applied in the future is crucial. Given the limited current research that evaluates the practicality of wireless charging technology for electric vehicles with a time scale, this article aims to assess the aspects of safety, cost, efficiency, materials, user acceptance and other factors to determine the likelihood of making wireless charging practical for electric vehicles in the next decade. Furthermore, by distributing questionnaires to electric and gasoline car owners to gather participants’ opinions and expectations on wireless charging for electric vehicles, statistical analysis of the questionnaire results; interview with a professor at Shanghai University who is an expert in magnets and electricity, conducting secondary research, this article concludes whether wireless charging technology for electric vehicles can be implemented in the decade or not. As an impact, this article includes a time scale by conducting an evaluation instead of implicitly mentioning the time scale.

Navigating Urban Mobility: The Relationship between Car Consumption and Public Transport Usage in Malaysia

Increasing private-owned cars in Malaysia has, thus far, contributed to growing congestion, environmental pollution, and decreasing public transport utilization. Car ownership has become possible through economic growth, and convenience and status attached to cars triggered tendencies from shifting to public transit. This development contradicts investments in public transport and aggravates environmental problems. This paper examines the relationship between private car ownership and public transport usage in Malaysia from 2000 to 2022, concentrating on intercity bus services, KTM commuters, and light rail transit. The results indicate that with increased riders for intercity buses and KTM commuter services, car usage drops, while that of light rail may raise car ownership. The study emphasizes the need to upgrade intercity and KTM services to mitigate the pressures of car ownership and calls for further research into the role of light rail.

Sustainable Horizons: Exploring Attitudes and Beliefs on Electric Aircraft Usage in General Aviation

This research was conducted to better understand the perceptions surrounding electrically powered aircraft in the general aviation (GA) sector. The study employed survey methodologies to collect responses from ( N = 780) participants, with an emphasis on data from collegiate aviation students as well as a broad subset of the GA community. The study focused on factors such as generational differences, gender, the impact of flight training, and prior exposure to electric or hybrid cars, and how these factors influence the aviation industry’s sustainable transformation. The results indicate a significant and positive correlation between attitudes toward electric aircraft and prior exposure to or ownership of electric or hybrid cars. Generational differences, gender-based variations, and the impact of flight training on willingness to pay for electric aircraft utilization also had significant relationships with attitudes toward electric aircraft. The findings provide valuable insights for industry stakeholders and policymakers in promoting sustainable aviation practices, and complements prior research into the feasibility of electric flight.

Effects of COVID-19 on flex route transit utilization: An interrupted time series analysis

The COVID-19 outbreak has exerted serious effects on the transportation system, especially public transport. Flex route transit (FRT), one of public transport, has shown significant advantages in transporting passengers during COVID-19 due to its high flexibility and relatively large cabin spaces. This study aims to estimate the effects of the lockdown and first lockdown ease on FRT utilization through interrupted time series analysis. A survey was conducted in Beijing to collect data regarding the daily FRT utilization of individuals, spanning from December 2019 to May 2020. Results indicated that FRT utilization was immediately reduced during the lockdown, and a decreased trend was observed. After the first lockdown ease was rolled out, FRT utilization showed a rising level and trend. Private car owners showed a lower dependence on FRT than non-car owners. The level of income exerted varying effects in a wide range of periods. FRT utilization among the higher income group was more likely to take effect than the lower income group. The study yields various policy implications for FRT operations during COVID-19 or other pandemics.

Key influences on residential photovoltaic solar panel adoption in the United States

ABSTRACT The prevalence of low-density residential development to host solar PV, the ubiquity of solar irradiation, and incentivizing policies have created substantial opportunities for homeowners in the United States. Federal, state, and municipal governments implement regulatory policies and financial incentives to promote photovoltaic solar systems in residential buildings with limited resources. Thus, understanding the main factors and their spatial variations is vital for expanding the accessibility of renewable energy benefits to specific socio-economic groups and submarkets. Our research includes linear regression, principal component regression, and spatial error models to provide empirical evidence for the relationship between the adoption rates and socio-economic, geographical, and technical factors while identifying characteristics of adopter groups. The results suggest that the relative advantage factors – electricity prices and solar irradiation – play the most significant role across all regions and market segmentations. Statewide policy indicators are the second most significant factor, followed by socio-economic variables on employment status, remote working, car ownership, and property value. Our results indicate that homeowners do not only differ in their circumstances but also in their motivations. This highlights a need for policy-makers and the solar industry to place greater emphasis on distinct characteristics of consumers motivated by ideology and consumers motivated by economic benefits.

A prospect theoretical choice model incorporating profitable and punctual uncertainties: an investigation in the participation of private car sharing

This study aims to examine people’s propensity to share private cars between peers accounting for the potential impacts of uncertainties underlying the sharing profit and vehicle returns. A mixed logit prospect theoretical model is developed to estimate the effects of uncertain variables and examine the unobserved heterogeneity using the data collected through a stated choice experiment in Hiroshima City, Japan. Results show that car owners are generally sensitive to the gains and losses for the revenue and the time of delayed returns, and people respond to uncertain situations differently. Individual participation in private car sharing is significantly influenced by the choices made by different social group members like family/relatives and friends/colleagues. These insights on individuals participation mechanism are helpful for service operators to promote the market share of private car sharing.

“I always say, it’s the icing on the cake”: the discursive production of fare-free public transport in Luxembourg

ABSTRACT Although the policy of fare-free public transport (FFPT) continues to gain popularity across diverse geographical contexts, the case of Luxembourg is unique in this global landscape. It is the first nation-state to have universally abolished fares, in a society characterized by high incomes and GDP, and a particularly high car ownership rate. In this paper, we analyze the evolution of political discourses on FFPT in Luxembourg surrounding the introduction of the policy. Using qualitative methods, we reconstruct the decision-making process and examine the competing ideologies that shaped it. We find that the idea germinated on the margins of the political spectrum, but was adopted by those in power because of the unique opportunity to combine territorial marketing with a form of socially-inclusive and sustainable policy that would not harm the widely valued car-based transport system. Hence, this process demonstrates both the post-political aspects of FFPT, illustrated by how its introduction helped to marginalize critical voices around fare abolition, and its political dimension related to the public debate and the contestation that FFPT engendered.