01155419

Component

https://doi.org/10.3141/2157-06

http://scholar.google.com...mans&publication_year=2010

With a focus on the multitasking behavior of public transportation users during travel, an examination is made of factors affecting activity participation along the axis of travel time. The probability of participation in an activity is represented by using a scobit (or a skewed logit) model, within which the widely used logit model is nested with the help of a skewness parameter. With this skewness parameter, it is not necessary to assume that individuals with a probability of 0.5 for performing an activity are most sensitive to changes in travel time or other influential factors. This analysis is the first attempt to apply the scobit model to transportation issues. An empirical analysis was conducted by using data (523 individuals) collected in Hiroshima City, Japan, in December 2008. Because multitasking behavior along the axis of travel time may be interrelated, the scobit model is extended to simultaneously incorporate the influences of state dependency and the remaining travel time as well as the other influential factors, by dealing with the data as panel data. As a result, a scobit-based panel model was developed. Model estimation results confirm the effectiveness of the scobit model. It was further revealed that introduction of a heterogeneous skewness parameter is more effective for representing activity participation than assumption of a homogeneous skewness parameter. Calculation results of travel time elasticity show that activity participation is sensitive to change in the travel time up to the first half of travel time and becomes less sensitive to travel time afterward.

01172525

10-0829

English

pp 46-53

2010

Transportation Research Record: Journal of the Transportation Research Board

9780309142830

Print

Figures (3) ; References (15) ; Tables (4)

Logits; Multitasking; Public transit; Travel behavior; Travel time

Activity participation; Scobit model; Travel time elasticity

Hiroshima (Japan)

Planning and Forecasting; Public Transportation; I72: Traffic and Transport Planning

TRIS, TRB, ATRI

Jan 25 2010 10:23AM

• Analyzing Route Choice Behavior with Mobile Phone Trajectories
• Assessing the Impact of Public Holidays on Travel Time Expenditure: Differentiation by Trip Motive
• Changes in Travel Behavior in Response to Weather Conditions: Do Type of Weather and Trip Purpose Matter?
• Cross-Clustered Model of Frequency of Home-Based Work Participation in Traditional Off-Work Hours
• Eliciting the Needs That Underlie Activity–Travel Patterns and Their Covariance Structure: Results of Multimethod Analyses
• Empirical Case Study of Spatial–Temporal Student Activity Population
• Exploring Sense-of-Place Attitudes as Indicators of Travel Behavior
• Factors Influencing the Planning of Social Activities: Empirical Analysis of Data from Social Interaction Diaries
• Genetic Algorithm to Estimate Cumulative Prospect Theory Parameters for Selection of High-Occupancy-Vehicle Lane
• Influence of E-Shopping on Shopping Travel: Evidence from Minnesota’s Twin Cities
• Models of Mode Choice and Mobility Tool Ownership Beyond 2008 Fuel Prices
• Spatial Econometrics Approach to Integration of Behavioral Biases in Travel Demand Analysis
• Structural Equation Model to Analyze Sociodemographics, Activity Participation, and Trip Chaining Between Household Heads: Survey of Shangyu, China
• Time to Play? Activity Engagement in Multiplayer Online Role-Playing Games
• Two-Stage Hedonic Price Model for Light-Duty Vehicles: Consumer Valuations of Automotive Fuel Economy in Maine
• Urban Structure and Socioeconomic Barriers to Consumer Adoption of Energy-Efficient Automobile Technology in a Dispersed City: Case Study of Brisbane, Australia
• Vehicle Emission Control Strategies and Public Opinion in Bhutan