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Abstract

To address the sustainability challenges related to travel behavior, technological innovations will not be enough. Behavioral changes are also called for. The aim of the present study is to examine the influence of sociodemography, geography, and personality on car driving and use of public transportation. Sociodemographic factors have been defined by age, gender, income, and education. Geographic factors have been studied through residential area (e.g., rural and urban areas). Personality has been studied through the Five-Factor-Model of personality&mdash

degree of Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism. The analysis is based on a survey with 1812 respondents, representative for the Swedish population. Regarding sociodemographic factors, car driving is explained by being male, higher age, higher income, while use of public transportation is explained by lower age and higher education. The user profile of a car driver is the opposite to that of a public transport passenger when it comes to geographic factors

urban residential area explains public transportation while rural area explains car driving. Some personality factors are also opposites

a low degree of Openness and a high degree of Extraversion explain car driving, while a high degree of Openness and a low degree of Extraversion explain use of public transportation. Moreover, car driving is explained by a low degree of Neuroticism, while use of public transportation is explained by a low degree of Conscientiousness and a high degree of Agreeableness. Since sociodemography, geography, and personality influence how people process information and evaluate market propositions (e.g., products and services), the findings presented here are useful for policymakers and transportations planners who would like to change behavior from car driving to public transportation use. Caution should be taken in interpreting the relationship between personality traits and transportation modes, since the personality traits are measured by a short scale (i.e., Big Five Inventory (BFI)-10), with limitations in the factor structure for a representative sample of the Swedish population.

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Original document

The different versions of the original document can be found in:

https://doaj.org/toc/2076-328X under the license cc-by
https://www.mdpi.com/2076-328X/10/6/93/pdf,
https://www.ncbi.nlm.nih.gov/pubmed/32466504,
http://www.diva-portal.org/smash/record.jsf?pid=diva2:1457790,
https://www.scilit.net/article/4450516e7c52fe7b19ecc661ddba42a9,
https://academic.microsoft.com/#/detail/3032612508
http://dx.doi.org/10.3390/bs10060093
under the license https://creativecommons.org/licenses/by/4.0/
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Published on 01/01/2020

Volume 2020, 2020
DOI: 10.3390/bs10060093
Licence: Other

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