A tour-based analysis of travel mode choice accounting for regional transit service

The aim of this work is to explore the impact of regional transit service on tour-based commuter travel behavior by using the Bayesian hierarchical multinomial logit model, accounting for the spatial heterogeneity of the people living in the same area.With two indicators, accessibility and connectivity measured at the zone level, the regional transit service is captured and then related to the travel mode choice behavior. The sample data are selected from Washington-Baltimore Household Travel Survey in 2007,including all the trips from home to workplace in morning hours in Baltimore city. Traditional multinomial logit model using Bayesian approach is also estimated. A comparison of the two different models shows that ignoring the spatial context can lead to a misspecification of the effects of the regional transit service on travel behavior. The results reveal that improving transit service at regional level can be effective in reducing auto use for commuters after controlling for socio-demographics and travel-related factors.This work provides insights for interpreting tour-based commuter travel behavior by using recently developed methodological approaches. The results of this work will be helpful for engineers, urban planners, and transit operators to decide the needs to improve regional transit service and spatial location efficiently.

Modeling urban housing price： The perspective of household activity demand

Existing studies about the modeling of urban housing price have figured out sets of factors and the main focus is on the relative spatial location. Generally, this line of research is descriptive rather than modeling in nature. The underlying reasons for the distribution of housing price are largely unexplored and more research is needed. The paper therefore attempted to systematically explore the spatial heterogeneities of urban housing price based on the urban activity interaction rule. Using Beijing as a case study, this study first developed a new measurement of accessibility which directly depicts the cost and possibilities to access opportunities of different activities such as employments, educational, shopping and medical services. From the perspective of demands of different households, the paper then modelled the relationships between urban housing price and these accessibilities and found that the distribution pattern of housing price can be relatively well represented by this model that the R^2 could achieve 0.7. We investigated the relationship between housing price and the demands of different kinds of households categorized by households of one-generation, two-generation, three-generation and four-and-plus-generation and found that the demands of household of four-and-plus-generations is the most highly correlated with housing prices. The reason might be that this kind of household has more household members and the demands are more diverse and complex, which is more similar to the distributions of all kinds of activity opportunities in the real world. In the end of the paper, some implications for policy-making are proposed based on the results of the analyses.