How vehicle ownership affect time utilization on study,leisure, social activities,and academic performance of university students? A case study of engineering freshmen in a rural university in Thailand

This study aims to investigate how the ownership of a private vehicle influences time utilization of university students, and whether it impacts their academic performance. This research analyzes travel/activity patterns of 130 engineering freshman students at a rural university in Thailand. An analysis of travel/activity data shows that vehicle ownership seems to play an important role in university student’s time utilization on various activities. It was found that those students who own a vehicle tend to spend less time for academic purposes, and more on leisure and social activities than non-owner students. Nevertheless, a further study using regression analysis on academic performance shows that the ownership of a vehicle does not seem to have a significant impact on the grade point average of students, once the cognitive ability and gender are accounted for. The findings imply that campus policies/measures that restrict the ownership or usage of a private vehicle in rural universities would improve the campus learning environment by influencing university students to put more attention on school-related activities, but such policies do not seem to impact on the academic performance of the college students.     

Land-use and socio-economics as determinants of traffic emissions and individual exposure to air pollution

This paper presents a modeling framework developed for the City of Montreal, Canada, and is intended to quantify two indicators that can explain the spatial distribution of traffic-related air pollution at a metropolitan level. The indicators are estimated at the level of the traffic analysis zone (TAZ) and include: (1) the average level of emissions generated per individual and (2) the level of emissions occurring in a zone as a proxy for air pollution exposure. A regional traffic assignment model is extended with capabilities for emission modeling at an individual trip level while taking into account vehicle (type and age) and trip attributes (road type, speed, and volume). We observe that individuals who generate higher emissions from travel tend to reside in areas with lower exposure to traffic emissions while individuals associated with low levels of travel emissions (e.g. travel smaller distances, conduct less trips, and use alternative modes) reside in areas with high levels of traffic pollution. A regression analysis of the two indicators against a set of land-use and socio-economic variables shows that generated emissions per individual are positively associated with car ownership and larger vehicles, while being negatively associated with ownership of newer vehicles, and location in dense and walkable neighborhoods with high levels of commercial land-use. Meanwhile, exposure to emissions is positively associated with dense and walkable neighborhoods and negatively associated with car ownership and larger vehicles. These findings indicate major inequities in the generation of and exposure to traffic-related air pollution.     

Inter-regional and inter-temporal analysis of travel behaviour for Asian metropolitan cities: Case studies of Bangkok, Kuala Lumpur, Manila, and Nagoya

The unprecedented demand for travel experienced in Asia, in conjunction with the economic development of the1980s, has resulted in a number of detrimental effects on urban systems. Economic development has certainly intensified per capita income enhancing personal mobility. In Asia, private vehicle ownership and usage have continued to be recognised as an obligatory element of travel for many. Undoubtedly there is a direct relationship between vehicle ownership and public transport usage. Inter-regional and inter-temporal investigations of travel behaviour in Asian cities are therefore necessary to develop an understanding of the future transportation system including suitability and the role of public transport. Since travel data are scarce in Asian countries, inter-regional or inter-temporal travel behaviour investigations do not exist to date. Several travel demand models are developed using discrete choice modelling techniques and Bangkok, Kuala Lumpur, Manila, and Nagoya as case studies. Estimation results of the mode choice models are successfully incorporated to compare travel behaviour trends in selected cities in Asia. The developed models are tested for spatial and temporal transferability.     

Study of vehicle ownership for urban and rural households in India

Private vehicle ownership has been growing in double digits over the last decade. This paper examines the factors determining vehicle ownership for urban and rural households in India. Separate nation-wide disaggregate vehicle ownership models for urban and rural areas in India are developed using readily available consumer expenditure survey dataset. A consumption based proxy variable is assumed to represent economic standard of households. Comparison between vehicle ownership behavior of urban and rural households show that rural households are more inclined to own private vehicle than urban households with same economic standards. Amongst households with regular salaried members, rural households' preference to own two wheelers is greater than that of urban households. While the presence of elderly member or children is considered, urban households showed more preference to own four-wheeler than rural households. As a first nation-wise study to understand the differences in vehicle ownership behavior in urban and rural areas of India, this study provides a lot of useful insights which could be valuable to various stakeholders.     

Understanding the process that gives rise to household car ownership level changes

Quantitative studies have revealed that changes to the number of cars owned by households are more likely to occur at the time of life events. However, causal explanations of such relationships are either absent or lacking evidence. To address this knowledge gap, this paper presents a qualitative study which enabled the development of a new conceptual framework to explain the process through which the number of cars owned by households changes over time. The framework emerged through an inductive analysis of 15 in-depth biographical interviews and was validated through a mixed methods survey of 184 households located in Bristol (UK). The following mechanisms of the process are identified: Life events alter roles, relationships, spatial contexts and lifestyle preferences. This can lead to a condition of stress which relates to a discrepancy between satisfaction with the current car ownership level and a more desirable alternative. Attempts to adjust to the new situation are made through processes of travel behaviour adaptation and consideration of whether the car ownership level ought to be altered. A propensity to change car ownership level can emerge from this. However, given the effort involved in taking action, households tend to resist making changes to their car ownership level in the short term. Action to change car ownership level is found to often be prompted by another external stimulus such as the receipt of a maintenance bill. A key message from the analysis is that changes in household car ownership level should be considered as the outcome of a continuous process of development over the life course, rather than as discrete decisions.     

Travel behavior of university students who live on campus: A case study of a rural university in Asia

With their irregular class schedules and considerable freedom in the campus environment, university students are an example of a social group that tends to have complex and unique travel behavior. This study examined travel patterns of 130 students who study and live on campus in a rural university of Thailand. All survey participants completed a travel diary for seven consecutive days in a typical school week. Other than overall travel patterns, such as trip generation, mode split, distance traveled, and travel time, this study also investigated the differences in traffic patterns of four student groups, categorized by their gender and whether they own a private vehicle or not. It was found that students of both genders appeared to have similar travel patterns in all aspects. Whether they own a private vehicle does not appear to impact daily trip generation nor the total distance traveled of the students, but it does have an effect on the travel modes used by students. Those students who own a private vehicle mostly rely on driving the vehicle, while those who do not own a vehicle rely on three modes of travel: primarily being a passenger on or in a friend’s private vehicle, and to a lesser extent, driving a friend’s vehicle, and taking a bus (the only form of public transport on the campus). The results indicate a high social interdependency among university students, which makes the development of a model to simulate travel behavior of university students a complicated task.     

Can travel vouchers encourage more sustainable travel?

The growth of transportation poses difficult dilemmas for social and environmental policy. There is broad agreement that a variety of ‘carrot’ and ‘stick’ measures are needed. This article asks whether tax-free travel vouchers for employees could be important as incentives or ‘carrots’ to encourage the use of public transport. The basic idea of it is like Luncheon Vouchers for public transport. Employers issue the vouchers and claim the tax back from the Government. Potentially, travel vouchers could generate a ‘win–win’ situation in which transport operators’ rising revenues justified new services and these, in turn, encouraged more passengers. The research described here uses survey data and the National Travel Survey to examine acceptability and potential fiscal impact of a rural tax-free travel voucher scheme throughout the UK. These results show that there is sufficient acceptance of the idea of travel vouchers in rural areas to justify the further development of this policy.     

The built environment and vehicle ownership modeling: Evidence from 32 diverse regions in the U.S.

Vehicle ownership is an important determinant of the travel demand forecasting process. Vehicle ownership models are used by policy makers to identify factors that affect vehicle miles traveled, and therefore address problems related to energy consumption, air pollution, and traffic congestion. For the conventional travel demand forecasting, it logically follows land use forecasting, before trip generation, which is commonly treated as step one. The most critical limitation of the vehicle ownership models, especially in the conventional process, is that they are often related mainly to sociodemographic variables, not so much to built environmental variables. In this study, by pooling regional household travel survey data from 32 diverse regions (almost 92,000 households) of the U.S., and by controlling for socio-demographic and the built environmental variables, we estimated a vehicle ownership model that contributes to the understanding of vehicle ownership and improves the accuracy of travel demand forecasts. Two main findings of this research are: 1) The number of vehicles owned by a household increases with socio-demographic variables and decreases with almost all of the built environmental variables. For the urban planning and design practices, this finding suggests that car shedding occurs as built environments become more dense, mixed, connected, and transit-served. 2) We used both count regression and discrete choice models, and the results suggest that count regression models have better predictive accuracy. The model developed in this study can be directly used for travel demand modeling and forecasting by metropolitan planning organizations.     

The factors in residents' mobility in rural towns of China: Car ownership,road infrastructure and public transport services

The improvement of rural people's mobility in developing countries has informed many policies. Still, debates remain on which policies are efficient, for instance, building more roads, providing public transport or promoting car ownership. The empirical evidence for these debates at the national level remains scarce. As a result, this paper aims to provide fresh evidence for discussions by examining residents' mobility in China using nationwide survey data with 12,524 respondents from 119 rural towns. The results of the analysis show car ownership is the most significant factor influencing rural people's mobility than other factors. Higher car ownership relates to a higher travel frequency to counties or cities. Other kinds of transport vehicles (i.e. electric cars, motorcycles and electric bikes) also have positive but relatively weaker impacts on rural mobility. For public transport, it is more accessible to access bus stops, which encourages travel to higher-order centres rather than increasing the frequency of county bus services. The accessibility of high-quality road systems tends to have a negative influence and has combined effects with levels of local services. People from towns with insufficient local services and poor access to highways travel the most frequently to higher-order centres. This study highlights the critical role of road investments and car ownership enhancement policies in improving mobility. Moreover, this study also underscores the supplemental role of public transport services given the current low car ownership rates in rural towns of China and the global consensus on sustainable green transport development. It highlights the importance of engaging eco-friendly and locally adaptive transport alternatives, such as electric cars and electric bikes. It also calls for a rational distribution of bus stops and more flexible, convenient, and physically accessible public transport and carshare modes in rural China.     

Measuring individuals' travel behaviour by use of a GPS-based smartphone application in Dar es Salaam,Tanzania

A range of mega-cities in the Global South have started to invest in Bus Rapid Transit (BRT) systems, as a complement or replacement for informal paratransit services, in an effort to improve the mobility and accessibility in the city. Yet, few studies have tried to analyse the impact of such systems on the mobility patterns of cities' residents, in part because traditional travel diary surveys are often too expensive to conduct and unsuitable to capture spatial mobility patterns in fast growing cities with a high level of informality in spatial development. In this study, we analyse the applicability of a new method of data collection, i.e. a GPS-based smartphone application, to capture individuals travel behaviour in fast growing mega-cities in the Global South. Our case study is the city of Dar es Salaam (DES) in Tanzania, where the first BRT line is currently being implemented. In our study, the GPS-based app was used by individuals in DES to record distances, departure times and destinations of their trips. Socio-demographic data of respondents were recorded in short questionnaires. The spatial distribution of the trip patterns shows the mobility demand in both high and less connected areas. The results reveal a variation in departure times, travel destinations and trip distances that are one the one hand spatially limited within neighbourhoods and away from the planned BRT, and on the other hand along major roads connecting to the Central Business District (CBD). The short average distances of the trips (<3 km) reveal the characteristics of paratransit modes. The GPS-based smartphone application provides an opportunity to policy makers to engage deeply with the spatial reality of local communities, as a basis for transport investments and policy improvements as steps towards an integrated public transport system.     

Investigating household vehicle ownership,mode choice and trip sharing decisions using a combined revealed preference/stated preference Nested Logit model: case study in Bangkok Metropolitan Region

This study proposes a Nested Logit model to investigate household travel behaviour in respect to vehicle ownership, mode choice and trip sharing decisions. The model is analysed using revealed preference (RP) and stated preference (SP) data since a combined estimation of RP/SP data is an effective method of expressing complex travel behaviour and forecasting travel demand for new transport services. In the proposed model, the nesting structure has two levels. The upper level shows car ownership, motorcycle ownership, and no vehicle-ownership choices, and the lower level shows the mode choice combinations for two-traveller households. Trip sharing is considered as one of the mode-choice options in the model. The proposed model is analysed using data from the Bangkok Metropolitan Region. The analysis conducted informs that Central Business District (CBD) travel, long distance travel, household income, job status, age of travellers and presence of school children in households are key aspects in household travel decisions. Based on these aspects, households make important decisions on vehicle ownership, mode choice and trip sharing. In addition, this study reveals commuters’ hidden preferences for modes that are not in existence, in particular the Mass Rapid Transit System in the Bangkok Metropolitan Region due to be fully implemented in 2010.     

Exploring the effects of the rural built environment on household car ownership after controlling for preference and attitude: Evidence from Sichuan,China

With the rapid infrastructure development and economic growth in China, household car ownership in the country's rural areas has changed dramatically in the past 16 years. The total number of cars owned by households in rural areas is currently 12 times higher than it was 16 years ago. The exploration of the effects of the built environment on household car ownership in China's rural areas is worthwhile. However, few studies have investigated this topic. To fill in the research gap, this work collected 374 household data from rural areas in China to examine the effects of the built environment in Sichuan's rural areas on the number of cars in a household. It considered family structure, socioeconomic characteristics, and individual's perceptions of the built environment, preferences towards the built environment and attitudes towards car ownership (shortened to perceptions, preferences and attitudes from now on). Geographic information system (GIS) technology, combined with on-site measurement, was used for data collection. The multinomial logit model was applied for estimation. Household structure and the built environment (including the perceived built environment and the objective built environment) significantly influence the number of cars in a household. By contrast, preference and attitude attributes have less influence on car ownership. Most of the findings are in line with the literature in the context of Chinese cities. Nevertheless, new results are also found. For example, rural hukou, and building density have significant positive impacts on household car ownership in China's rural areas, which is in contrast with their effects on cities. As the first study on rural areas in China, this research provides some insights for rural planners and policymakers to understand better the relationship between built environment and household car ownership.     

A dynamic hazard-based system of equations of vehicle ownership with endogenous long-term decision factors incorporating group decision making

The transportation system affects all aspects of our daily lives including relatively long-term decisions on work and home location choice and automobile ownership decisions. The interdependency existing among these three decisions jointly influences household mobility and overall travel patterns. Therefore, a dynamic modeling framework that can account for the effects of interdependencies between vehicle transaction behavior and residential and job location choices is highly desirable. These decisions are made in the household level while individuals’ decisions influence the overall outcome; therefore, it is also important to incorporate a group decision making process within such modeling frameworks.This study introduces a dynamic model for vehicle ownership, residential mobility, and employment relocation timing decisions. These decisions are modeled at the individual level and then sequentially aggregated to the household level if it is required. A hazard-based system of equations is formulated and applied in which work location and residential location changes are included as endogenous variables in the vehicle transaction model while other important factors such as land-use and built environment variables, household dynamics, and individuals’ socio-demographics are also considered.     

Shared autonomous vehicles and their potential impacts on household vehicle ownership: An exploratory empirical assessment

Emerging transportation technologies have the potential to significantly reshape the transportation systems and household vehicle ownership. Key among these transportation technologies are the autonomous vehicles, particularly when introduced in shared vehicle fleets. In this paper, we focus on the potential impact that fleets of shared autonomous vehicles might have on household vehicle ownership. To obtain initial insights into this issue, we asked a sample of university personnel and members of the American Automobile Association as to how likely they would consider relinquishing one of their household's personal vehicles if shared autonomous vehicles were available (thus reducing their household vehicle ownership level by one). For single-vehicle households, this would be relinquishing their only vehicle, and for multivehicle households (households owning two or more vehicles) this would be relinquishing just one of their vehicles. Possible responses to the question about relinquishing a household vehicle if shared autonomous vehicles are present are: extremely unlikely, unlikely, unsure, likely, and extremely likely. To determine the factors that influence this response, random parameters ordered probit models are estimated to account for the likelihood that considerable unobserved heterogeneity is likely to be present in the data. The findings show that a wide range of socioeconomic factors affects people's likelihood of vehicle relinquishment in the presence of shared autonomous vehicles. Key among these are gender effects, generational elements, commuting patterns, and respondents' vehicle crash history and experiences. While people's opinions of shared autonomous vehicles are evolving with the continual introduction of new autonomous vehicle technologies and shifting travel behavior, the results of this study provide important initial insights into the likely effects of shared autonomous vehicles on household vehicle ownership.     

Effects of neighborhood types & socio-demographics on activity space

This paper examines the relationships between socio-demographic characteristics, travel time, the built environment and resulting average activity spaces for all activities and non-work activities separately using data from the 2012 Northeast Ohio Regional Travel Survey. Multiple regression models are developed to analyze these relationships at individual level. First K-means cluster analysis is conducted to create seven neighborhood types based on five built environment variables. These new neighborhood types are used as discrete explanatory variables to explain average activity spaces, while controlling for travel time, individual and household features, access to transit facilities and the job-population balance. The modeling results indicate that residential location characteristics have significant influences on activity spaces. People living in places away from suburban and rural areas and with a high mix of population and employment tend to have smaller activity spaces. Moreover, this study finds out that while the effects of some explanatory variables (such as age and gender) vary for all activities and non-work activities, socially disadvantaged people (such as the elderly and low income households) generally experience smaller activity spaces.     

Using the car in a fragile rural tourist destination: a social representations perspective

The visitor experience of place is inextricably linked to our ability to travel around an area at will, yet this mobility creates many problems especially in scenic rural areas of the UK. The study presented here attempts to unravel visitors’ experiences of mobility using Moscovici’s social representations approach. Travel diaries were employed to explore visitors’ transport choices and mobility patterns during the peak season in Purbeck, Dorset, UK. Analysis focuses on how such patterns reflect a social representation of mobility and the implications this has for visitor travel at destinations.     

Temporal dynamics in local vehicle ownership for Great Britain

This article explores the stability of local vehicle ownership rates in Great Britain using the technique of spatial Markov chain analysis. Non-spatial Markov chain processes describe the transition of neighbourhoods through levels of ownership with no regard to their neighbourhood context. In reality however, how a neighbourhood transitions to different levels of ownership could be influenced by its neighbourhood context. A spatial Markov chain accounts for this context by estimating transition properties that are conditioned on the surrounding neighbourhood. These spatial Markov chain properties are estimated using a long run census time series from 1971 to 2011 of household vehicle ownership rates in Great Britain. These processes show that there is different behaviour in how neighbourhoods transition between levels of ownership depending on the context of their surrounding neighbours. The general finding is that the spatial Markov process will lead to a greater homogeneity in levels of ownership in each locality, with neighbourhoods surrounded by relatively low ownership neighbourhoods taking longer than a non-spatial Markov process would suggest to transition to higher levels, whilst neighbourhoods of high ownership surrounded by high ownership neighbourhoods take longer to transition to lower levels. This work corroborates Tobler's first law of geography “Everything is related to everything else, but near things are more related than distant things” but also provides practical guidance. Firstly, in modelling ownership, spatial effects need to be tested and when present, accounted for in the model formulation. Secondly, in a policy context, the surrounding neighbourhood situation is important, with neighbourhoods having a tendency towards homogeneity of ownership levels. This allows for the effective planning of transport provision for local services. Thirdly, vehicle ownership is often used as a proxy for the social and aspirational nature of an area and these results suggest that these properties will persist for a prolonged period, possibly perpetuating and exacerbating differentials in society.     

Integrated inventory-transportation model by synchronizing delivery and production cycles

This paper develops an integrated single-vendor multi-buyer inventory-transportation synchronized supply chain model. In this paper, the decisions of truck assignment and routing are also considered and as a result, a series of vehicle routing problems (VRP) are required to be solved. Due to the highly complicated objective function and the NP-hard VRP problems, the problem cannot be solved analytically. Hence, meta-heuristics are proposed. By means of the numerical examples and a case study, the meta-heuristics developed are shown to be very effective in solving such comprehensive supply chain models, and the results so obtained are promising.     

Supply and pricing strategies of informal rural transport providers

Informal paratransit operators using a range of vehicle types (including pickup trucks, small buses, and motorcycles) are a major provider of mobility in rural areas of the developing world. The paper describes a mixed method approach used to examine such operators’ decisions about vehicle deployment, route frequency, network organisation, and pricing in three rural districts in South Africa. New evidence is presented showing that the condition of rural roads (both paved and unpaved) affects the quantity and quality of public transport services provided, as well as the fares charged to passengers. This strengthens the case for judicious infrastructure investment as a way of improving rural access and livelihoods, and suggests how this might happen by way of leveraging better private sector responses. We also describe the emergence of a differentiated service hierarchy involving a variety of vehicle types suited to different operating conditions, and based on intentional coordination among operators of minibus and pickup truck (‘bakkie’) services. We argue that governments should promote such coordination and innovation in rural transport markets.