Yearly Development of Car Ownership in Urban and Rural Environments

Jullian Van Kampen; Luk Knapen; Rob Van De Mei; Eric Pauwels; Elenna Dugundji

doi:10.1016/j.procs.2022.03.016

Yearly Development of Car Ownership in Urban and Rural Environments

Jullian Van Kampen^*, Luk Knapen, Rob Van De Mei, Eric Pauwels, Elenna Dugundji

^*Corresponding author for this work

Mathematics

Research output: Contribution to Journal › Article › Academic › peer-review

Abstract

The decision to own a car usually results from a mix of changes in socio-economics, residential location, demographics or preferences of the individuals. These changes do not directly influence car ownership but are lagged in time or sometimes occur on anticipation of future events. In this research we investigate how some of the most common predictors for car ownership change over the years and how much impact they actually have in their decision for owning a car. We make a distinction in impact for people living in an urban and people living in a rural environment. A multinomial logit was estimated in 4 separate years to assess the impact of changes in residential location, age and income. The results show that not only the impact of these common predictors is changing but also the relation that they have regarding car ownership. These results illustrates the complexity of car ownership and suggests a more dynamic approach for the prediction of car ownership in both urban and rural environments.

Original language	English
Pages (from-to)	101-108
Number of pages	8
Journal	Procedia Computer Science
Volume	201
Issue number	C
Early online date	27 Apr 2022
DOIs	https://doi.org/10.1016/j.procs.2022.03.016
Publication status	Published - 2022
Event	13th International Conference on Ambient Systems, Networks and Technologies, ANT 2022 / 5th International Conference on Emerging Data and Industry 4.0, EDI40 2022 - Porto, Portugal Duration: 22 Mar 2022 → 25 Mar 2022

Bibliographical note

Part of special issue: The 13th International Conference on Ambient Systems, Networks and Technologies (ANT) / The 5th International Conference on Emerging Data and Industry 4.0 (EDI40), Edited by Elhadi Shakshuki.

Publisher Copyright:
© 2022 Elsevier B.V.. All rights reserved.

Keywords

car ownership
discrete choice
multinomial logit
residential location
rural environment
self-selection
urban environment

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title = "Yearly Development of Car Ownership in Urban and Rural Environments",

abstract = "The decision to own a car usually results from a mix of changes in socio-economics, residential location, demographics or preferences of the individuals. These changes do not directly influence car ownership but are lagged in time or sometimes occur on anticipation of future events. In this research we investigate how some of the most common predictors for car ownership change over the years and how much impact they actually have in their decision for owning a car. We make a distinction in impact for people living in an urban and people living in a rural environment. A multinomial logit was estimated in 4 separate years to assess the impact of changes in residential location, age and income. The results show that not only the impact of these common predictors is changing but also the relation that they have regarding car ownership. These results illustrates the complexity of car ownership and suggests a more dynamic approach for the prediction of car ownership in both urban and rural environments.",

keywords = "car ownership, discrete choice, multinomial logit, residential location, rural environment, self-selection, urban environment",

author = "{Van Kampen}, Jullian and Luk Knapen and {Van De Mei}, Rob and Eric Pauwels and Elenna Dugundji",

note = "Part of special issue: The 13th International Conference on Ambient Systems, Networks and Technologies (ANT) / The 5th International Conference on Emerging Data and Industry 4.0 (EDI40), Edited by Elhadi Shakshuki. Publisher Copyright: {\textcopyright} 2022 Elsevier B.V.. All rights reserved.; 13th International Conference on Ambient Systems, Networks and Technologies, ANT 2022 / 5th International Conference on Emerging Data and Industry 4.0, EDI40 2022 ; Conference date: 22-03-2022 Through 25-03-2022",

year = "2022",

doi = "10.1016/j.procs.2022.03.016",

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AU - Van Kampen, Jullian

AU - Knapen, Luk

AU - Van De Mei, Rob

AU - Pauwels, Eric

AU - Dugundji, Elenna

N1 - Part of special issue: The 13th International Conference on Ambient Systems, Networks and Technologies (ANT) / The 5th International Conference on Emerging Data and Industry 4.0 (EDI40), Edited by Elhadi Shakshuki. Publisher Copyright: © 2022 Elsevier B.V.. All rights reserved.

PY - 2022

Y1 - 2022

N2 - The decision to own a car usually results from a mix of changes in socio-economics, residential location, demographics or preferences of the individuals. These changes do not directly influence car ownership but are lagged in time or sometimes occur on anticipation of future events. In this research we investigate how some of the most common predictors for car ownership change over the years and how much impact they actually have in their decision for owning a car. We make a distinction in impact for people living in an urban and people living in a rural environment. A multinomial logit was estimated in 4 separate years to assess the impact of changes in residential location, age and income. The results show that not only the impact of these common predictors is changing but also the relation that they have regarding car ownership. These results illustrates the complexity of car ownership and suggests a more dynamic approach for the prediction of car ownership in both urban and rural environments.

AB - The decision to own a car usually results from a mix of changes in socio-economics, residential location, demographics or preferences of the individuals. These changes do not directly influence car ownership but are lagged in time or sometimes occur on anticipation of future events. In this research we investigate how some of the most common predictors for car ownership change over the years and how much impact they actually have in their decision for owning a car. We make a distinction in impact for people living in an urban and people living in a rural environment. A multinomial logit was estimated in 4 separate years to assess the impact of changes in residential location, age and income. The results show that not only the impact of these common predictors is changing but also the relation that they have regarding car ownership. These results illustrates the complexity of car ownership and suggests a more dynamic approach for the prediction of car ownership in both urban and rural environments.

KW - car ownership

KW - discrete choice

KW - multinomial logit

KW - residential location

KW - rural environment

KW - self-selection

KW - urban environment

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Y2 - 22 March 2022 through 25 March 2022

ER -

Yearly Development of Car Ownership in Urban and Rural Environments

Abstract

Bibliographical note

Keywords

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