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Title:

Who Will Buy Alternative Fueled or Automatic Vehicles: A Modular, Behavioral Modelling Approach

Accession Number:

01623337

Record Type:

Component

Abstract:

Future car purchase can determine an array of things ranging from CO2 emissions to urban life quality. For this reason, models and methods predicting car purchase are valuable to policy makers. This paper examines the future car purchase choice, using modules, different levels of attributes that construct a car and measures the effect of personality traits such as the symbolic/exuberant attitudes towards vehicles on the purchase choice. The results may enable policy makers to focus on certain market segmentation for the promotion of alternative fuel and automated vehicles. The paper proposes a hybrid choice model, with latent variables capturing the pro-environmental, exuberant and tech-friendly attitudes of individuals. The questionnaire presented to the respondents has the form of a menu, participants may choose five different types of vehicle characteristics (engine size, type of car, fuel type, car edition and level of automation) to construct their ideal vehicle. Results indicate that there is a negative correlation between having symbolic, exuberant attitudes towards automobile s, viewing the cars as symbols, and the willingness to purchase a hybrid or electric vehicle. The findings further indicate that there is a correlation among symbol-driven exuberant attitudes and the desire to buy a larger vehicle. This paper examines the relationship between the symbolic perception of cars with a range of characteristics simultaneously, discovering which car attributes does the symbolic perception affect. It also proposes an integrated framework for the modeling of future car purchase, with the hypothesis that each of the three presented latent variables can affect different modules of the individual’s ideal car concept.

Supplemental Notes:

This paper was sponsored by TRB committee ADB40 Standing Committee on Transportation Demand Forecasting.

Monograph Accession #:

01618707

Report/Paper Numbers:

17-03219

Language:

English

Corporate Authors:

Transportation Research Board

500 Fifth Street, NW
Washington, DC 20001 United States

Authors:

Tsouros, Ioannis
Polydoropoulou, Amalia

Pagination:

21p

Publication Date:

2017

Conference:

Transportation Research Board 96th Annual Meeting

Location: Washington DC, United States
Date: 2017-1-8 to 2017-1-12
Sponsors: Transportation Research Board

Media Type:

Digital/other

Features:

Figures; References; Tables

Subject Areas:

Economics; Highways; Planning and Forecasting; Vehicles and Equipment

Source Data:

Transportation Research Board Annual Meeting 2017 Paper #17-03219

Files:

TRIS, TRB, ATRI

Created Date:

Dec 8 2016 11:12AM