Modelling car ownership in urban areas: a case study of Hamilton, Canada

Potoglou, Dimitris; Kanaroglou, Pavlos

doi:10.1016/j.jtrangeo.2007.01.006

Cited by 221 publications

(174 citation statements)

References 20 publications

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“…There have been a number of studies on the influential factors of the growth of car ownership in North America (Potoglou and Kanaroglou, 2008) and the European Union (Kain, 2001). The findings have facilitated our understanding on the socioeconomic characteristics and built environment correlates to car ownership and provided important policy implications for interventions (Ding et al, 2017b).…”

Section: Literature Reviewmentioning

confidence: 99%

The Socioeconomic Characteristics, Urban Built Environment and Household Car Ownership in a Rapidly Growing City: Evidence from Zhongshan, China

Zhang

Liu³

et al. 2018

Journal of Asian Architecture and Building Engineering

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Growth in car ownership has significant impacts on the use of urban space and management of urban environments, especially in rapidly developing countries such as China. However, among voluminous literature, few studies have investigated the correlates of household car ownership in the Chinese context, leading to the lack of effective measures to tackle rapid motorization. This study explored the impacts of household-level socioeconomic characteristics and neighborhood-level built environment on household car ownership, with data collected from 25,325 households in Zhongshan, China. The Zero-inflated Poission regression models detect that, all else being equal, living in a neighborhood with a compact and mixed urban form, better bus service and adjacency to CBD is associated with fewer household cars and higher probability to own zero cars. The models also suggest that household size and income, number of employed or students, and availability of competitive vehicles are significantly related to the number of cars in a household. The findings facilitate our understanding of the effects of socioeconomic characteristics and built environment on household car ownership and provide insights into an effective design of measures to slow down the rapid motorization in China.

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Section: Literature Reviewmentioning

confidence: 99%

The Socioeconomic Characteristics, Urban Built Environment and Household Car Ownership in a Rapidly Growing City: Evidence from Zhongshan, China

Zhang

Liu³

et al. 2018

Journal of Asian Architecture and Building Engineering

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“…Nevertheless, while several studies from North America point to a mitigating influence of urban design on car ownership and use (e.g. Bento et al 2005;Potoglou and Kanaroglou 2008;Van Acker and Witlox 2010), there have been relatively fewer studies that have investigated this linkage in the European context (some exceptions include Hedel 2008 andBuehler 2011). Given that choices about land development tend to have long-lasting impacts that span over decades, quantification of the influence of landscape pattern on car use is highly significant to the formulation of contemporary planning strategies.…”

Section: Introductionmentioning

confidence: 99%

Landscape pattern and car use: Linking household data with satellite imagery

Keller

Vance

2013

Journal of Transport Geography

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Abstract:Landscape pattern has long been hypothesized to influence automobile dependency.Because choices about land development tend to have long-lasting impacts that span over decades, understanding the magnitude of this influence is critical to the design of policies to reduce emissions and other negative externalities associated with car use. Combining household survey data from Germany with satellite imagery and other geo-referenced data sources, we undertake an econometric analysis of the relation between landscape pattern and automobile dependency. Specifically, we employ a two-part model to investigate two dimensions of car use, the discrete decision to own a car and, conditional upon ownership, the continuous decision of how far to drive. Results indicate that landscape pattern, as captured by measures of both land cover (e.g. the extent of open space and landscape diversity) and land use (e.g. the density of regional businesses) are important predictors of car ownership and use. Other policy-relevant variables, such as fuel prices and public transit infrastructure, are also identified as correlates. Based on the magnitude of our estimates, we conclude that carefully considered land development and zoning measures -ones that encourage dense development, diverse land cover and mixed land use -can have beneficial impacts in reducing car dependency that extend far into the future.

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“…While Bhat and Pulugurta (7) argued that a multinomial logit model (MNL) model would be more appropriate for modelling car ownership over an ordered logit (ORL) model, subsequent empirical studies have developed ordered probit (ORP) or ORL models claiming the discrete, ordered nature of the dependent variable (8,9) as well as MNL models on the basis of their sound behavioural and theoretical nature (10)(11)(12). In particular, comparing modelling results of MNL and ORL using several datasets, Bhat and Pulugurta (7) found substantial differences in the elasticities of exogenous variables across the choice probabilities of car ownership levels and identified misspecification problems associated with the ORL that could lead to incorrect and inaccurate forecasts.…”

Section: Introductionmentioning

confidence: 99%

“…In particular, comparing modelling results of MNL and ORL using several datasets, Bhat and Pulugurta (7) found substantial differences in the elasticities of exogenous variables across the choice probabilities of car ownership levels and identified misspecification problems associated with the ORL that could lead to incorrect and inaccurate forecasts. Also, Potoglou and Kanaroglou (12) found that a MNL model was a significantly improved model over the ORL through a likelihood-ratio test between the two models using data from the metropolitan area of Hamilton, Canada. This paper offers a comprehensive comparison of car ownership models including MNL, ORL and ORP.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Vehicle-Ownership Models

Potoglou

Susilo

2008

Transportation Research Record

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Empirical studies on household car ownership have used two types of discrete choice modelling structures, the ordered and the unordered. In ordered structures such as the ordered logit and ordered probit models, the choice of the number of household-vehicles arises from a uni-dimensional latent index that reflects the propensity of a household to own vehicles. Unordered response models, on the other hand, are based on the random utility maximization principle, under which a household associates a utility value across different car ownership levels and chooses the one with the maximum utility. The multinomial logit and probit models are representatives of the unordered response models, but only the multinomial logit has been used extensively because of its simple structure and low computational requirements. Following Bhat and Pulugurta's (1998) comparative study between the multinomial logit and ordered logit models, consensus among researchers is still lacking and empirical studies have reported car ownership model based on the multinomial logit, ordered logit as well as ordered probit models. It is apparent that there is still an open question to be addressed: Which of the aforementioned models would reflect better households' car ownership choices? This paper provides an empirical comparison of multinomial logit, ordered logit and ordered probit car ownership models by introducing a number of formal evaluation measures and using three datasets; the 2001 National Household Travel Survey for the metropolitan area of Baltimore, the 2005 Dutch National Travel Survey and the 2000 Osaka Metropolitan Person Trip Data. Results show that the multinomial logit model is the one to be selected for modelling the level of household car ownership over ordered logit and ordered probit.

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Modelling car ownership in urban areas: a case study of Hamilton, Canada

Cited by 221 publications

References 20 publications

The Socioeconomic Characteristics, Urban Built Environment and Household Car Ownership in a Rapidly Growing City: Evidence from Zhongshan, China

The Socioeconomic Characteristics, Urban Built Environment and Household Car Ownership in a Rapidly Growing City: Evidence from Zhongshan, China

Landscape pattern and car use: Linking household data with satellite imagery

Comparison of Vehicle-Ownership Models

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