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The impact of high-speed technology on railway demand 总被引:1,自引:0,他引:1
This paper estimates a passenger railway demand function to analyse effects arising from the introduction and use of high-speed
technologies. The paper reports estimates of demand elasticities with respect to price, income, quality of service and a range
of exogenous characteristics. The results show that travel time savings from conventional high-speed technology have a larger
impact on passenger demand than tilting train technology. The introduction of conventional high-speed technology is associated
with an 8% increase in passenger railway demand. Increasing the use of either type of high-speed technology appears to induce
small positive effects on demand beyond those obtained from usual traffic density increases on non-high-speed existing technology.
Antonio Couto is an assistant professor in the Faculty of Engineering (FEUP) at the University of Porto. He received his PhD from FEUP in 2005 having completed a thesis in railway transport economics. His research focuses on issues related to transport economics and infrastructures. Daniel J. Graham is a Reader in the Centre for Transport Studies at Imperial College London. He specialises in the economics of transport, focusing in particular on modelling the implications of transport provision and accessibility for productivity and economic growth. 相似文献
Daniel J. Graham (Corresponding author)Email: |
Antonio Couto is an assistant professor in the Faculty of Engineering (FEUP) at the University of Porto. He received his PhD from FEUP in 2005 having completed a thesis in railway transport economics. His research focuses on issues related to transport economics and infrastructures. Daniel J. Graham is a Reader in the Centre for Transport Studies at Imperial College London. He specialises in the economics of transport, focusing in particular on modelling the implications of transport provision and accessibility for productivity and economic growth. 相似文献
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Understanding of the activity-travel patterns of children is becoming increasingly important to various policy makers. Further,
there is also a growing recognition that intra-household interactions need to be explicitly accommodated in travel models
for realistic forecasts and policy evaluation. In the light of these issues, this paper contributes towards an overall understanding
of the school-travel behavior of children and the related interdependencies among the travel patterns of parents and children.
An econometric model is formulated to simultaneously determine the choice of mode and the escorting person for children’s
travel to and from school. The 2000 San Francisco Bay Area Travel Survey (BATS) data are used in the model estimation process.
Empirical results indicate that the characteristics of child like age, gender, and ethnicity, and employment and work flexibility
characteristics of the parents have strong impacts on the mode choice decisions. In addition, the impacts of some of these
attributes on the choice of mode to school are different from the corresponding impacts on the choice of mode from school. The distance between home and school is found to strongly and negatively impact the choice of walking to and from
school, with the impact being stronger for walking to school. Several land-use and built-environment variables were explored,
but were found not to be statistically significant predictors.
相似文献
Sivaramakrishnan Srinivasan (Corresponding author)Email: |