01518544

Component

https://doi.org/10.3141/2413-01

http://scholar.google.com...eene&publication_year=2014

The objective of this research was to isolate the factors influencing non–distance-based definitions of long-distance travel to help long-distance survey makers know which demographic factors they should query about in their surveys. Instead of the use of a distance-based threshold to define long-distance travel, this study included variations in purpose (e.g., work travel or leisure or personal travel), durations (e.g., overnight trips), modes (e.g., intercity rail or bus), and destinations (e.g., international travel) to consider which demographic, employment, commute, household, and geographic factors affected the frequency of long-distance travel. The data were from self-reported retrospective surveys collected from approximately 1,200 participants. Results from ordered probit analysis revealed that education and income generally increased most types of long-distance travel, whereas having a spouse or children decreased some types of long-distance travel. In general, limited factors had the same impact on the work and non–work travel and modes used. Factors also varied by trip type. Commute and employment factors were valuable even for non–work trip frequency estimation. The findings suggest that future data collection for long-distance travel can be tailored to address the specific definition being studied.

01537243

14-4024

English

pp 1–12

2014

Transportation Research Record: Journal of the Transportation Research Board

9780309295123

Print

References (34) ; Tables (4)

Demographics; Probits; Recreational trips; Travel patterns; Travel time; Trip length; Work trips

Passenger Transportation; Planning and Forecasting; Society; I72: Traffic and Transport Planning

TRIS, TRB, ATRI

Jan 27 2014 3:23PM

• Analysis of Car Usage Time Frontiers Incorporating Both Inter- and Intraindividual Variation with GPS Data
• Choice, Frequency, and Engagement: Framework for Telecommuting Behavior Analysis and Modeling
• Discrepancy Analysis of Activity Sequences: What Explains the Complexity of People’s Daily Activity–Travel Patterns?
• Effects of Transit-Oriented Development on Trip Generation, Distribution, and Mode Share in Washington, D.C., and Baltimore, Maryland
• How Drivers Adapt to Traffic Accidents and Dynamic Travel Information: Stated Preference Survey in Japan
• Joint Model of Weekend Discretionary Activity Participation and Episode Duration
• Life Events and Travel Behavior: Exploring the Interrelationship Using UK Household Longitudinal Study Data
• Modeling Mobility Tool Ownership of Youth in Toronto, Ontario, Canada
• Route Choice Modeling Using GPS-Based Travel Surveys
• Travel to Common Destinations: An Exploration Using Multiday GPS Data