01332898

Component

https://doi.org/10.3141/2231-09

http://scholar.google.com...wara&publication_year=2011

A dynamic discrete choice model for multiple social interactions was developed on the basis of retrospective panel data in the context of household vehicle-type choice. “Social interactions” refer to the influence of reference groups on household choice behavior. However, most studies in transportation have considered a household as a decision maker independent from the society to which it belongs. Social interactions have therefore not been well represented, especially if there were two or more types of reference groups, which may further vary over time. The model was built within the dynamic generalized extreme value framework, which included a set of dynamic elements, such as initial conditions, state dependence, and future expectation. This study defined three types of social interactions: diffusion rates of a vehicle type at the national level and at the neighborhood level and diffusion rate of households with the same income level. A survey was conducted in local Japanese cities in 2006. The survey focused on household vehicle ownership behavior over the 10 years from 1997 to 2006. Model estimation results confirmed that social interactions from reference groups of neighborhoods and households with the same income level were especially influential in decisions about household vehicle-type choice. On the contrary, social interaction from the whole society did not significantly influence the household choice. It was further found that effects of dynamic elements on the household choice were statistically significant.

01357425

11-3714

English

pp 68-75

2011

Transportation Research Record: Journal of the Transportation Research Board

9780309167475

Print

Figures (2) ; References (21) ; Tables (3)

Automobile ownership; Automobiles by type; Choice models; Households; Income; Social factors; Surveys; Travel behavior

Discrete choice models; Social interaction

Japan

Highways; Planning and Forecasting; Society; I72: Traffic and Transport Planning

TRIS, TRB, ATRI

Feb 17 2011 6:37PM

• Applying Sequence Alignment Methods to Large Activity–Travel Data Sets: Heuristic Approach
• Barriers to Teenage Mobility in the Greater Toronto Area, Ontario, Canada: Attitudes, Concerns, and Policy Implications
• Built Environment, Individual Attributes, and Variability of Body Mass Index of Drivers in the Chicago, Illinois, Metropolitan Area: Empirical Analysis
• Dynamic Choice Set Generation Based on Global Positioning System Trajectories and Stated Preference Data
• Empirical Analysis of Decision-Making and Tour Formation Process: Comparison Between Seniors and Younger Individuals
• Empirical Analysis of the Activity-Planning Process
• Estimating Value of Travel Time Savings by Using Large-Scale Household Survey Data from Japan
• Joint Analysis of Time Use and Consumer Expenditure Data: Examination of Two Approaches to Deriving Values of Time
• Modeling the Impacts of Information and Communication Technologies and Virtual Activities on Activity and Travel Behavior: Case Study of Cairo, Egypt
• Nonwork Travel Behavior Changes During Temporary Freeway Closure: The Fix I-5 Project in Sacramento, California
• Personal Network Maintenance, Face-to-Face Interaction, and Distance: Role of Availability and Use of Information and Communication Technologies
• Propensity to Telecommute: Exploring the National Household Travel Survey
• Subjective Measure of Car Dependence
• Travel Determinants and Multiscale Transferability of National Activity Patterns to Local Populations