Abstract

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.

Highlights

  • The transportation system affects all aspects of human life including economic, social, and environmental issues

  • This study introduces a dynamic model for vehicle ownership, residential mobility, and employment relocation timing decisions

  • The current study proposes a non-linear system of equations using a hazard-based formulation for modeling household job and residential relocation timing decision along with household vehicle transaction time choice

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Summary

Introduction

The transportation system affects all aspects of human life including economic, social, and environmental issues. While the interaction can result in both short- and long-term effects, the impact can be more influential on decisions such as work or home location choices as well as automobile ownership decisions. Job and home location choices, on the other hand, can influence an individual’s vehicle ownership and utilization behavior. Vehicle ownership or transaction models in the literature are used for a variety of purposes and their applications are considerably increasing (de Jong et al 2004). Travel behavior and environmental researchers, car manufacturers, oil companies, international organizations and different levels of government employ these models to forecast oil and vehicle demand, transportation demand, energy consumption and emission levels. With increasing concerns about environmental issues and fuel consumption, a well-defined vehicle ownership model has become a vital tool for national, regional and local agencies

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