Car Ownership Choice Research Articles

Investigation of household private car ownership considering interdependent consumer preference.

People are connected by various social networks, resulting in the interdependence of consumer choice. Therefore, it is very important and realistic to assume choice interdependence in private car ownership modeling. In this paper, we investigate the interdependence of private car ownership choice using a spatial autoregressive binary probit model estimated by the Bayesian Markov chain Monte Carlo (MCMC) method. Constructing the autoregressive matrix demographically shows that the private car ownership choice of a household is dependent on other household choices. Compared with the pure binary probit model estimated by the MCMC method, the spatial autoregressive model achieves a significant improvement both in loglikelihood value and log marginal density value, which are calculated using the importance sampling method of Newton and Raftery, from approximately -202 to approximately -63 and from -208 to -145, respectively. Moreover, the results indicated by the spatial autoregressive probit model suggest that the number of children, the ownership of an apartment or the availability of a parking lot are positively and significantly associated with the private car ownership level. To test the out-of-sample performance of the model, we estimate the model using 600 data points and test it using another 148 data points. The results indicate that the predictive power is greatly improved. Finally, we analyze the augmented parameter and discover that it is associated with the parking variable in addition to the license variable.

Social and urban form determinants of vehicle ownership; evidence from a developing country

The car is the most preferred mode of travel among middle and high-income urban residents in Iran, where the car ownership has been growing at a rate of 15% per year and the evidence shows that vehicle ownership and use are strongly supported by urban development patterns. However, the specification of this relationship is not the same as western societies. Thus, this paper investigates the vehicle ownership and usage in three residential neighborhoods of Shiraz, a city in the southwest of Iran and its association to urban form characteristics and development pattern. The data on land use and urban form characteristics were primarily extracted from the existing secondary sources and GIS but in a disaggregated fine-grain method, whereas the data on household characteristics and vehicle ownership were purposefully collected through a household questionnaire survey. A nested logit model (NLM) based on the Discrete Choice Theory (DCT) was then applied to explore the impacts of socio-economic status (SES) and urban form factors on the car ownership choices of households. The results and the associated policy implications can be helpful in defining a strategic framework for community planning and design in order to reduce the level of car ownership and usage.

Individual Mobility Attributes and Their Impact on Modality Style

Mobility attributes such as driver's license, car ownership, reserved parking at work, and transit pass have a very strong impact on travel choices, in particular, mode choice. Mobility attributes are not acquired for a particular trip but rather are driven by the entire set of individual travel needs (commuting being the most basic of them). Some mobility attributes, for example, car ownership and transit pass, are substitutable; others, for example, car ownership and reserved parking at work, are complementary. For this reason, mobility attributes have to be analyzed and modeled jointly. The purpose of the current research is to analyze a wide set of mobility attributes and incorporate them in an operational activity-based model as a set of midterm choices. The approach suggested in this paper is based on an iterative application of three interlinked choice submodels: (a) joint choice of person driver's license, usual driver role (priority in using one of the household cars), car type choice, reserved or reimbursed parking at work, and transit pass; (b) household car ownership choice by type; and (c) intrahousehold car allocation by type. Model estimation results confirmed strong cross- attribute effects as well as revealed many impacts of person, household, and travel accessibility variables. In particular, historical and cultural differences between three population sectors in Jerusalem—secular Jewish, Orthodox Jewish, and Arab—manifested themselves quite strongly. Application of these models for future scenarios is discussed.

Comparison of Vehicle-Ownership Models

Empirical studies on household car ownership have used two types of discrete choice modeling structures: ordered and unordered. In ordered response structures, such as the ordered logit and ordered probit models, the choice of the number of household vehicles arises from a unidimensional latent variable that reflects the propensity of a household to own vehicles. Unordered response structures are based on the random utility maximization principle, which assumes a household associates a utility value across different car ownership levels and chooses the one with the maximum utility. The most common unordered response models are the multinomial logit and probit models, but only the multinomial logit has been used in practical applications because of its simple structure and low computational requirements. Consensus among researchers on unordered or ordered structures is still lacking. Empirical studies have reported various models, including the multinomial logit, ordered logit, and ordered probit. An open question remains: Which model would better reflect households’ car ownership choices? This paper compares multinomial logit, ordered logit, and ordered probit car ownership models through a number of formal evaluation measures and empirical analysis of three data sets: the 2001 National Household Travel Survey for the Baltimore [Maryland] Metropolitan Area, the 2005 Dutch National Travel Survey, and the 2000 Osaka [Japan] Metropolitan Person Trip Data. Results show the multinomial logit model should be selected for modeling the level of household car ownership.

A Logit Analysis of Car Ownership in Hong Kong Based on Stated Intention Information

In this paper, disaggregate car ownership choice models are developedfor Hong Kong using the results of a survey with both revealed preference and stated preference questions. The car ownership choice (Iogit-type) models are calibrated to Investigate the effects of economic chonges andfiscal measures on the choice of car ownership. In the study, households are classified into non-car owning and car owning groups. These separoted groups arefurther sub-divided into those respondents who have no plans to bUy cars and those who plan to bUy cars. The revealed preference survey results were mainly used to collect the relevant data Of the respondents. The stated preference results revealed that monthly household Income, car purchose cost, annuai licence fee, monthly home-end parking and monthly car usage costs are the keyfactors Of pertaining to car ownership in Hong Kong.