Inter-Temporal Analysis of Household Car and Motorcycle Ownership Behaviors

Sanko, Nobuhiro; Dissanayake, Dilum; Kurauchi, Shinya; Maesoba, Hiroaki; Yamamoto, Toshiyuki; Morikawa, Takayuki

doi:10.1016/s0386-1112(14)60243-0

Cited by 24 publications

(15 citation statements)

References 2 publications

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“…For the study of vehicle ownership of different types, the ordered probit (OP) model was found to be an appropriate modeling method compared with multinomial logit (MNL) model in such cases [10][11][12], because the non-ordered discrete choice model cannot properly account for the ordinal nature of the number of vehicles owned. Most previous literature in this field developed bivariate ordered probit (BOP) model that analyzes both household automobiles and motorcycles ownership, which need to take account of the interdependencies between them [13][14][15][16][17]. Furthermore, the multivariate ordered probit model can be developed by extending the dimensions of the study object.…”

Section: Introductionmentioning

confidence: 99%

Development of Multivariate Ordered Probit Model to Understand Household Vehicle Ownership Behavior in Xiaoshan District of Hangzhou, China

Shi

2018

Sustainability

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With the rapid increase of motorization in China, transitions have taken place in regards to traditional private transportation modes. This paper aims to understand four types of vehicle ownership within a household, including automobile, motorcycle, electric bicycle and human-powered bicycle. This study presents a cross-sectional multivariate ordered probit model, with a composite marginal likelihood estimation approach that accommodates the effects of explanatory variables, and capturing the dependence among the propensity to household vehicle ownership. The sample data are obtained from the residents’ household travel survey of Xiaoshan District, Hangzhou, in 2015, which can analyze the significant effects of sociodemographic attributes and built environment attributes. Interestingly, the major findings suggest that: (1) The households with higher income tend to own more automobiles, yet the effect is not obvious with a small value of elasticity, which is similar to developed countries. (2) The household education level, which takes a positive effect on automobile ownership, is a more elastic factor than income. (3) The higher population density contributes to less ownership of automobiles and motorcycles, due to traffic congestions and parking challenges. (4) There is a large substitutive relation between automobile and electric bicycle/motorcycle, and the vehicle ownership of electric bicycle/motorcycle and bicycle are mutually promoted, while motorcycle and electric-bicycle are mutually substituted.

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Section: Introductionmentioning

confidence: 99%

Development of Multivariate Ordered Probit Model to Understand Household Vehicle Ownership Behavior in Xiaoshan District of Hangzhou, China

Shi

2018

Sustainability

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“…The literature on motorcycle ownership is rather scarce, with most studies conducted in East Asian countries, such as Taiwan, Malaysia, Indonesia, Thailand, Japan and Vietnam (Pongthanaisawan and Sorapipatana, 2010;Sillaparcharn, 2007;Tuan, 2011;Tuan and Shimizu, 2005;Sanko et al, 2009;Hsu, 2005;Nagai et al, 2003;Dao and Duc, 2005). Previous evidence revealed an inverted U-shaped relationship between motorcycle ownership and income growth (Pongthanaisawan and Sorapipatana, 2010;Sillaparcharn, 2007;Tuan, 2011;Senbil et al, 2007;Nishitateno and Burke, 2014).…”

Section: Introductionmentioning

confidence: 99%

The motorcycle to passenger car ownership ratio and economic growth: A cross-country analysis

Law

Hamid

Goh

2015

Journal of Transport Geography

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“…In addition, the bivariate ordered Probit model was used for model the number of 195 different mobility tools at the household level, e.g. car and motorcycle ownership [38,39] or car and season ticket ownership [30]. [40] also used a bivariate ordered Probit model to study the frequency of use of car-sharing and ridesourcing services.…”

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Modeling car-sharing membership as a mobility tool: A multivariate Probit approach with latent variables

Becker

Loder

Schmid

et al. 2017

Travel Behaviour and Society

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Individual travel behavior is to a large extent shaped by the respective portfolio of available mobility tools such as cars, season-tickets or a car-sharing membership. However, the choices of different mobility tools are interdependent and are also affected by individual attitudes. This paper presents an approach to jointly model the choice of four different mobility tools -including car-sharing. Using data from the Swiss transportation micro census of 2005 and 2010, itis shown that car-sharing is used as a supplement to a public transportationoriented lifestyle, but is also used by car owners. The results further indicate that personal attitudes have a substantial effect on the choice of mobility tools and should therefore be accounted for when modeling such decisions.

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Inter-Temporal Analysis of Household Car and Motorcycle Ownership Behaviors

Cited by 24 publications

References 2 publications

Development of Multivariate Ordered Probit Model to Understand Household Vehicle Ownership Behavior in Xiaoshan District of Hangzhou, China

Development of Multivariate Ordered Probit Model to Understand Household Vehicle Ownership Behavior in Xiaoshan District of Hangzhou, China

The motorcycle to passenger car ownership ratio and economic growth: A cross-country analysis

Modeling car-sharing membership as a mobility tool: A multivariate Probit approach with latent variables

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