Household Car Research Articles

Persisting social disadvantage and intercensal social mobility in Northern Ireland: an examination of morbidity and all-cause mortality using three waves of the Northern Ireland Longitudinal Study (NILS).

Objective and ApproachUsing census returns from three waves of NILS (1991, 2001, 2011) linked with mortality data, we examined morbidity/mortality outcomes by socio-economic disadvantage over time (using an individual-level deprivation index derived from educational attainment, social class, housing tenure and household car availability at each census). These were combined to generate two indicators of Intercensal social mobility: measuring no change, and upward/downward mobility between censuses. The relationship between mobility (2001-2011) and (separately) self-reported mental ill-health (MIH) at the 2011 Census and all-cause mortality (2011-2015) were examined using logistic regression and Cox PH modelling respectively. Results Population comprised 288,262 individuals aged 25-74 in 2011, recording 19,318 deaths (2011-2015) and 23,959 (8.3%) reporting MIH. MIH: those with no intercensal mobility followed the standard pathway associated with persisting disadvantage (comparing with the most advantaged the least advantaged recorded OR=16.13:95%CI=13.50,19.28); and while both the upwardly and downwardly mobile generally recorded higher ORs than those consistently most advantaged, the magnitude of ORs increased with social distance traversed; and ORs for downward mobility were consistently higher than with upward mobility. Patterns associated with all-cause mortality were similar. ConclusionsThis suggests: upward mobility retains something of the social patterning pertaining in social disadvantage levels left behind; downward mobility may be connected to ongoing health issues. Poor health outcomes remain strongly associated with socio-economic circumstance. Implications Research focusing on relationship between social mobility, disadvantage and health outcomes in NI is limited: access to more precise administrative data will enhance possibilities associated with evidence-based policy formation.

Company cars and household car choices

Tax systems that favour company cars for personal use could cause households to have more cars. It could also affect the choice of fuel type. We investigate the relationship between household car choices and access to a company car through a difference-in-differences design using Norwegian microdata. We find that access to a company car is associated with an increase in the total number of cars and the number of combustion-engine cars. For electric cars, the results are inconclusive. However, wage growth and access to company cars are also positively correlated. Therefore, we cannot interpret the difference in the number of cars between the treatment and control groups as a causal effect of the company car scheme, but as a correlation. Still, existing evidence on the income elasticity of car demand suggests that the increase in the number of cars is unlikely to be driven by wage growth alone.

An Analysis of the Health Effects of Physical Activity due to Active Travel Policies in Rennes, France.

Rennes, a midsize city in France, features many opportunities for active travel. City officials seek to increase walking and cycling by 2030 to improve public health. Physical inactivity, a leading risk factor for premature mortality around the globe, has been shown to be associated with many chronic diseases including heart disease, type 2 diabetes, and cancer. Using the 2018 household travel survey of Rennes residents, we apply the Health-Oriented Transportation statistical model to assess health impacts associated with population-level rates of walking and cycling. We consider two proposed mobility and climate objectives which outline sustainable transportation goals by 2030. These include a shift in transportation mode share to increase walking and cycling trips, as well as a broad reduction in vehicle miles traveled (VMT) across the metropolitan area. Our regression analysis demonstrated that factors of household car access and inner-city residency were predictors of prevalence (observed one-day proportion engaging in walking or cycling), participation (weekly proportion), and intensity (mean individual physical activity achieved through walking/cycling) of active travel. Age and education were additionally associated with prevalence. The 2030 mobility objective (mode share: 9% cycle, 35% walk) was associated with a reduction of 1,051 DALYs (disability-adjusted life-years), translating to $73 million USD ($23-$177) in averted costs. The climate objective (10% reduction in VMT) was associated with a reduction of 369 DALYs when replaced entirely by walking and 714 DALYs with cycling, translating to $26 million ($8-$62) and $50 million ($15-$121) saved, respectively. Rennes residents experience high participation in active travel, particularly those in the inner city. If residents achieve the city's active travel goals for 2030, there is potential for a large reduction in health burden and subsequent costs. Reaching these goals may require significant investment in transportation programming and infrastructure to improve active travel opportunities.

Logit and Probit Models Explaining Mode Choice and Frequency of Public Transit Ridership among University Students in Krakow, Poland

The predictors of urban trip mode choice and one of its important components, public transit ridership, have still not been thoroughly investigated using case studies in Central Europe. Therefore, this study attempts to clarify the correlates of mode choices for commute travel and shopping, and entertainment travel to distant places, as well as the frequencies of public transit use of university students, using a wide range of explanatory variables covering individual, household, and socio-economic attributes as well as their perceptions, mobility, and the nearby built environment. The correlation hypothesis of these factors, especially the role of the street network, was tested by collecting the data from 1288 university students in Krakow and developing Binary Logistic and Ordinal Probit models. The results show that gender, age, car ownership, main daily activity, possession of a driving license, gross monthly income, duration of living in the current home, daily shopping area, sense of belonging to the neighborhood, quality of social/recreational facilities of the neighborhood, and commuting distance can predict commute and non-commute mode choices, while gender, daily activity, financial dependence from the family, entertainment place, quality of social/recreational facilities, residential self-selection, number of commute trips, time living in the current home, and street connectivity around home are significantly correlated with public transit use. Some of these findings are somewhat different from those regarding university students in Western Europe or other high-income countries. These results can be used for policy making to reduce students’ personal and household car use and increase sustainable modal share in Poland and similar neighboring countries.

Who does new trips and why?: An analysis toward the modeling of induced demand

ABSTRACT Improvements in infrastructure capacity and travel conditions including the introduction of a new transport mode can induce changes in traffic. Although this can occur through a variety of behavioral mechanisms, in this study, the main focus is on the increase of individual mobility rates – namely induced trips. A three-step methodological framework is proposed to identify and model-induced trips, along with the development of discrete choice models, which is the first step of the framework and acts as its foundation. Multinomial logit (MNL) and nested logit (NL) models are estimated, with trip frequencies as the dependent variable. Factors such as age, household type, household car ownership, the number of children and trip reason are found to be influential on the decision of making new trips. Results also suggest that shared mobility significantly paves way to new trips. The contributions from this study can support in understanding the reasons behind the generation of new trips and devise pertinent policies.

An Analysis of the Health Effects of Physical Activity due to Active Travel Policies in Rennes, France

Background Rennes, a midsize city in France, features many opportunities for active travel. City officials seek to increase walking and cycling by 2030 to improve public health. Physical inactivity, a leading risk factor for premature mortality around the globe, has been shown to be associated with many chronic diseases including heart disease, type 2 diabetes, and cancer. Methods Using the 2018 household travel survey of Rennes residents, we apply the Health-Oriented Transportation statistical model to assess health impacts associated with population-level rates of walking and cycling. We consider two proposed mobility and climate objectives which outline sustainable transportation goals by 2030. These include a shift in transportation mode share to increase walking and cycling trips, as well as a broad reduction in vehicle miles traveled (VMT) across the metropolitan area. Results Our regression analysis demonstrated that factors of household car access and inner-city residency were predictors of prevalence (observed one-day proportion engaging in walking or cycling), participation (weekly proportion), and intensity (mean individual physical activity achieved through walking/cycling) of active travel. Age and education were additionally associated with prevalence. The 2030 mobility objective (mode share: 9% cycle, 35% walk) was associated with a reduction of 1,051 DALYs (disability-adjusted life-years), translating to $73 million USD ($23-$177) in averted costs. The climate objective (10% reduction in VMT) was associated with a reduction of 369 DALYs when replaced entirely by walking and 714 DALYs with cycling, translating to $26 million ($8-$62) and $50 million ($15-$121) saved, respectively. Conclusions Rennes residents experience high participation in active travel, particularly those in the inner city. If residents achieve the city’s active travel goals for 2030, there is potential for a large reduction in health burden and subsequent costs. Reaching these goals may require significant investment in transportation programming and infrastructure to improve active travel opportunities.

Who stopped riding buses and what would motivate them to return? A New Jersey case study

New Jersey Transit (NJT) sponsored a research project in 2019 to examine the factors associated with bus ridership decline. As a part of that research, this paper examines the personal and geographic characteristics of the riders who stopped riding and identifies service improvements that could motivate riders to return to the bus. It uses a binary logit model and a multinomial logit model (MNL) with survey data from 2055 past and present NJT bus riders. The binary model compares current riders with all riders who stopped riding for any reason, whereas the MNL model separately compares the current riders with the riders who stopped riding for COVID-19 and the riders who stopped riding for non-COVID reasons. The results showed that ride discontinuation for both COVID-19 and non-COVID reasons is directly correlated with having disability, high education, a household car, and a driver’s license, but inversely correlated with the number of bus stops and the proportion of commuting trips by transit in the riders’ residential location. Lower satisfaction with the bus was found to be directly related to ride discontinuation. Based on survey responses, the study concludes that greater frequency during the peak periods, more reliable on-time arrivals, and more direct connections to typical destinations such as employment centers could be the three most effective strategies to retain current riders and bring back past riders. As this research also examines ride discontinuation for non-COVID reasons, it is expected to be more beneficial for post-COVID bus service planning than typical COVID-impact studies.

Family Car Ownership: Driving Inactivity in Young People? Cross-Sectional and Longitudinal Analyses in the International Children's Accelerometry Database.

Ubiquitous car ownership may affect children's activity and health. We assessed the cross-sectional and longitudinal associations between household car ownership and children's daily time spent sedentary (SED) and in moderate to vigorous physical activity (MVPA). Pooled cohort data were from the International Children's Accelerometry Database. Outcome measures were average daily accelerometer-measured SED and MVPA (in minutes per day). Exposures were household car ownership (none, 1, and ≥2) and change in car ownership. Associations were examined using multivariable mixed-effects linear regression. Mean age of participants (N = 4193) was 10.4years (SD = 2.0), 53.4% were girls, and mean follow-up duration (N = 1333) was 3.3years (SD = 1.1). Cross-sectionally, household car ownership was associated with higher SED (vs none: 1 car: β = 14.1min/d, 95% CI, 6.7-21.5; ≥2 cars: 12.8, 95% CI, 5.3-20.4) and lower MVPA (vs none: 1 car: β = -8.8, 95% CI, -11.9 to -5.7; ≥2 cars: β = -8.8, 95% CI, -12.0 to -5.7). Associations were stronger in boys than girls and in children from lower socioeconomic backgrounds (SED only). Prospectively, there were no associations with increased car ownership. Reductions in household car ownership (of which 93.1% had ≥ 2 cars at baseline) were associated with a greater reduction in MVPA (vs no change: β = -8.4, 95% CI, -13.9 to -3.0) but not SED. Children in households with car access were more SED and less active than those without. Losing access to a second car was associated with greater decreases in MVPA, potentially related to losing access to activity-enabling environments. Reducing car access and use are important public health targets (eg,reducing air pollution), but their potential impact on children's activity opportunities should be mitigated.

Optimizing vehicle aerodynamics through the synergistic application of Design of Experiments (DoE) and Computational Fluid Dynamics (CFD)

The aerodynamic design of cars not only creates aesthetic and diverse car shapes, but also ensures their safety and fuel economy. According to Mustafa Cakir's research[1], approximately of the fuel consumption of a car traveling at high speeds is used to counteract air resistance. However, with the increasing severity of global warming, emissions standards for automobile exhaust are becoming increasingly stringent. Considering that gasoline vehicles still dominate the household car market, optimizing the aerodynamic design of automobiles is imperative. This work analyzes and optimizes the aerodynamic design of automobiles through the synergistic application of Design of Experiments (DoE) and Computational Fluid Dynamics (CFD). Before conducting experiments, the article first introduces and derives the basic control equations of computational fluid dynamics, namely the continuity equation and Navier-Stokes equation, and describes how they are used in experiments. Then, the article briefly introduces the drag coefficients of automobiles, which are important theoretical basis for subsequent aerodynamic design optimization in this article. In the experimental part, this study focuses on the influence of four important design parameters: angle of the front window , angle of the hood , angle of the back window , and length of the trunk . Using Solidworks 3D modeling software, the article simulates these design parameters and prepares for CFD numerical simulation by geometry, setting computational domain, boundary conditions, and objective functions, and generating mesh. Based on the DoE and numerical simulation results, the article ultimately selects a front window angle of , a hood angle of , a back window of , and as the optimized design. Compared with the basic model, the optimized model reduces the drag coefficient by about . The conclusion of this study provides ideas and theoretical basis for the aerodynamic optimization design of new generation automobiles with the incorporation of DoE. However, the design parameters of automobiles are countless, and in the future, this article will strive to research and simulate more diverse automobile designs and analyze their aerodynamic performance to explore more optimized designs.

The Effects of Green Supply Chain Management Practices on The Performance Of The Turkish Iron and Steel Industry

Sustainability is fundamental to complete development since it minimizes the negative impacts of work that is beneficial to society. Some sectors, such as the Iron and Steel Industry (ISI), have served the development of humanity for centuries and have enabled humanity to create new tools and build solid structures. ISI is a main material provider for different industries such as household appliances, car production, building, and medical devices. The importance of iron and steel for humanity is obvious and the sector serves humanity for being an advanced civilization. On the other hand, iron and steel production requires complex production methods, high energy consumption, and toxic materials. An industry that is so important for the development of civilization harms the planet that we all live in and threatens all living creatures when it doesn’t have environmental consciousness. The iron and steel sector should make its production model more environmentally friendly. In this context, this study aims to explore the effects of Green Supply Chain Management practices on 3 performance aspects (environmental, operational, and economic) of Turkish ISI. Findings indicate that every single GSCM practices have a different level of positive impact on environmental and operational performance. However, the findings suggest that the effects of GSCM practices on economic performance are not enough to declare a positive relationship because it is not obvious and highly clear as environmental performance and operational performance.

Sustainable Automated Mobility-On-Demand Strategies in Dense Urban Areas: A Case Study of the Tel Aviv Metropolis in 2040

The emergence of automated mobility-on-demand (AMoD) services in urban regions has underscored crucial issues concerning the sustainable advancement of urban mobility. In particular, the impact of various AMoD implementation strategies in dense, transit-oriented cities has yet to be investigated in a generalized manner. To address this gap, we quantify the effects of AMoD on trip patterns, congestion, and energy and emissions in a dense, transit-oriented prototype city via high-fidelity simulation. We employ an activity- and agent-based framework, with specific demand and supply considerations for both single and shared AMoD rides. Our findings suggest that, in densely populated, transit-oriented cities such as the Tel Aviv metropolis, AMoD contributes to higher congestion levels and increased passenger vehicle kilometers traveled (VKT). However, when AMoD is integrated with public transit systems or introduced alongside measures to reduce household car ownership, it helps alleviate the VKT impact. Furthermore, these combined approaches effectively counter the negative impact of AMoD on public transit ridership. None of the AMoD strategies analyzed in our study reduce the congestion effects of AMoD and all strategies cannibalize active mobility in dense, transit-oriented cities compared to the base case. Nevertheless, our analysis reveals that a policy leading to decreased car ownership proves to be a more efficient measure in curbing energy consumption and greenhouse gas emissions.

At the nexus of grocery access and transportation: Assessing barriers and preferences for alternative approaches to enhancing food access

IntroductionMost households, especially those experiencing food insecurity, choose their preferred food retailers based on prices, rather than proximity. However, food-insecure households are often transit-dependent, further burdening vulnerable households seeking healthy, affordable groceries. This study sought to better understand the multi-faceted transportation experiences of households with varying food security levels and preferences for grocery access models designed to help overcome transportation barriers to groceries. MethodsQuestionnaires assessing household's transportation modes and preferences for accessing groceries, and their preferences for proposed grocery access models were collected through intercept and online surveys. ResultsOf the 578 survey respondents, 35% were nonwhite; 22% at risk for food insecurity; 29% without a household car. Respondents at risk for food insecurity had longer travel times (20 min or more) to the grocery store (35%) compared with food-secure respondents (14%), as did transit-dependent respondents (31%) compared to households with access to a car (13%). Most at risk for food insecurity, low education, or nonwhite respondents preferred to drive a household car to the store, whereas most food-secure, high education, or white respondents preferred to walk. Respondents indicated they would be likely or very likely to use the following general grocery access models—grocery delivery (28%), and rideshare (22%)—and neighborhood-market based models—veggie box (50%), pre-chopped produce (36%), and extra $10 SNAP (35%). Preferences for the different models varied by respondents’ demographic, transportation, and food security status. ConclusionsResults suggest unequal transportation-based access to preferred grocery stores among respondents, with longer travel times for those most vulnerable to food insecurity. Respondents’ preferences for grocery access models—which may have changed since the onset of the COVID-19 pandemic—provide insight for designing a multi-faceted policy approach to transportation barriers to grocery access.

Is car traffic close to saturation in France?

After decades of uninterrupted growth, car traffic temporarily levelled off during the 2000′s in France, before coming back to growth after 2008. However, there are reasons to believe that car traffic growth is potentially limited, among which completion of the diffusion process for car ownership, limited travel time budgets, decreasing returns of additional car travel. In this study, we implement a disaggregate model at the household level to project future car ownership and car mileage per household in France, along with total car traffic, accounting for demographic growth. Our model relies on a sequential approach using panel data, with an ordered response probit model for the number of vehicles, including saturation thresholds by vehicle rank, and a log-linear model for car mileage, conditional on the number of vehicles, both with correlated random effects. A time trend is also incorporated to account for the decreasing household car mileage that was noticed over the last twenty years, which is not entirely explained by decreasing household size and the gradual decline of income growth. Assuming this trend to go on, total car traffic in France would grow only a little by 2050, despite demographic growth, and start decreasing from 2040. We discuss these results by questioning the structural nature of this trend.

Gendered access to household car in China: The mediation role of subjective attitudes

Increasing women’s access to car is advocated as a key strategy to improve women’s capability to move. However, car ownership is not equal to car access and independent car use. The men-favored car distribution within the household may exist to limit women’s access to car. This paper enriches the understanding of gendered access to household car by unpacking the mediation role of subjective attitudes. Perceived necessity to use household car and confidence in driving ability are examined specifically. The results of structural equation modelling support the assumptions that in China, (a) perceived necessity increases individual access to household cars; (b) being employed and in parenthood both increase women’s perceived necessity and thus the access to household car, while men’s access to household car and perceived necessity is increased only by the employment status; and (c) women’s access to household car is reduced by their tendency to lack confidence in driving. The findings suggest that recognizing the necessity of using a car and developing the confidence to drive is essential for women to improve their automobile mobility.

Travel behavior changes due to life events: Longitudinal evidence from Dutch couple households

Despite increasing interest in how travel behavior changes over time, few studies have investigated how life events alter travel behavior, especially from a household perspective. This study examined the extent to which life events influenced changes in travel mode frequencies at the household level. We applied structural equation modeling based on the Netherlands Mobility Panel data for 2014 and 2016. For both partners, acquiring a household car significantly increased car use, and disposing of household cars decreased car use frequency. The number of household cars was inversely related to men’s train use. Childbirth in the household decreased both partners’ cycling frequency. Men’s job changes increased train use. These findings emphasize that life events can influence changes in travel behavior within household partners.

TO WHAT EXTENT ARE GENDER STEREOTYPES PORTRAYED THROUGH ADVERTISEMENTS AND HOW CAN THEY INFLUENCE CONSUMER COGNITION?

The portrayal of genders in marketing, specifically advertising, can in many ways be demeaning, objectifying, and sexualizing. By repeatedly reaching consumers, advertisements can substantially influence their perceptions. While some advertisements may be educational, others reinforce gender norms by abiding by them. This research paper aims to address advertisements where such oppressive depictions are evident, to evaluate the psychological effect on consumer perception, and to explain what their perception may transform into. The selection of this topic finds root in the desire to advocate and promote Gender Equality. Applying the learnings from the AP Psychology curriculum, the aim is to evaluate gender depictions in product advertising and analyse how the sexes, male and female, are presented in two distinct manners and why this characterization is flawed. Advertisements for household products, perfumes, cars, and other products will be analysed. The gender stereotypes will not be analysed in terms of psychological manners. However, they will explain why and how consumers may perceive gender stereotypes by referring to a list of gender norms.

What are important factors to determine CO2 reduction by car sharing? Simulation of car-sharing impact in cities with different car dependencies considering variable uncertainty

The spread of car sharing is influenced by the characteristics of cities, such as the convenience of existing public transportation and degree of car dependencies. In this study, 60 Japanese cities were categorized into five clusters based on car-use share, household car ownership, and population density, and seven cities including a representative city of each cluster and two extreme cities were used as case studies to simulate the CO2 emissions associated with the introduction of car sharing. To determine the significant factors that affect CO2 emissions, we took up multiple variables and performed Monte Carlo simulations on them to calculate the final distribution of CO2 emissions. The cities with lower car dependency show significant CO2 increases in the simulation. The fuel economy of cars is one significant influential factor for CO2 reduction, whereas the transition from public transportation to car sharing is the most significant factor for CO2 increases.

Influential Factors of Household Car and Vehicle Ownership in Urban Areas of Turkey

Car and vehicle ownership levels in developing countries are gradually increasing, leading to traffic congestion, energy consumption, and air pollution. As a developing country, Turkey encounters many of the issues caused by this rapid increase in car ownership. This paper aims to examine potential determinants of household car and vehicle ownership behavior in urban areas of Turkey by concentrating on three cities (Ankara, Erzurum, and Bayburt) that are distinct in population, geographical region, and public transit services. For this purpose, a written survey was administered to 1389 households living in these cities. The data is analyzed using alternative ordered response models—the generalized ordered logit, partial proportional odds (PPO), and heteroskedastic ordered logit models. To the best of our knowledge, this study is the first attempt to compare alternative ordered response models to determine car and vehicle ownership behavior in Turkey. Consequently, the PPO model was found to be the most parsimonious model among the others. The results demonstrated that household car and vehicle ownership behavior in Turkey differs significantly with urban area size. The estimation results also revealed that several key drivers, including type of dwelling, parking availability, household monthly income, and public transit use, significantly influence Turkish households’ car and vehicle ownership levels. This study’s empirical findings may provide insight to policymakers and stakeholders for future transportation strategies and policies.

Usage Intention of Shared Autonomous Vehicles with Dynamic Ride Sharing on Long-Distance Trips

Technology advancements have paved the way for public access to shared autonomous vehicles (SAVs), but there is still no travel survey examining how SAVs with dynamic ride sharing (DRS) affect long-distance (LD) trips. Given the growth in these trips and the higher importance of travel time and cost on LD trips, assessing potential impacts of SAVs could be a vital tool in planning for a sustainable transportation system. This paper examines the impact of various attitudinal, sociodemographic, and travel-related characteristics on the usage intention of SAVs with DRS on LD trips. We have designed and conducted a web-based survey for this purpose and based on a representative sample of 723 individuals in 2021, a Generalized Ordered Logit model is estimated. Estimation results highlight the key importance of following psychological factors in a descending order: price evaluation, perceived usefulness, consumer innovativeness, sharing attitude, and privacy concern. Further, key factors among sociodemographic and travel-related characteristics are gender, education level, driving license, household car ownership, generational element, and crash history. These findings provide crucial insights into the likely effects of SAVs with DRS on LD trip behavior, based on which a number of practical implications are proposed for facilitating policy-making.

Gendered Interactions Mediated by Design: Sexual Harassment on Public Transport

This paper explores the gendered interactions that are mediated by designed products in actual use contexts. Our case is vehicle design for public transportation, a product category that is, from the outset, relatively gender-neutral when compared to explicitly gender-segregated categories such as household electronics, cars, and toys, even if public transit users are more often women than men. The empirical basis of research comes from interviews with women passengers. Our analysis demonstrates that seemingly gender-neutral designs can be merely gender-blind in that they have significant impact in the gendered experiences of its users, which includes, in this case, being exposed to or feeling at risk of sexual harassment and assault in public transportation as a woman. Therefore, feminist design interventions into mobility environments can provide immediate practical solutions that would complement policy and lawmaking efforts that are necessary to ensure safety for women on public transport.