October 24, 2012
PacTrans Seminar Series: Discrete Choice Analysis for Travelers: A Semi-parametric Approach
When: October 24, 2012 from 2:30pm to 3:30pm
Where: More 234
Discrete choice modelling is a widely used econometric approach to analyse the behaviour of travellers. The multinomial logit model is one of the most commonly used models in discrete choice analysis. This research develops a new model, semi-parametric multinomial logit model. The developed model links travellers’ attributes and alternatives to the choice probabilities via a sensitivity function. This sensitivity function reflects the degree of travellers’ sensitivity to the changes in the travelling costs. A Bayesian approach is investigated to draw statistical inference for the semi-parametric logit model. An empirical study on travellers’ value of time that involves stated preferences about two train-related alternatives and two bus-related alternatives is conducted to illustrate the developed model.
Short Bio of Professor Li:
Baibing Li is a professor in business statistics & management science at Loughborough University, U.K. He received the Ph.D. degree from the Management School, Shanghai Jiao Tong University, Shanghai, China. He was a Postdoctoral Research Fellow with Katholieke Universiteit Leuven, Leuven, Belgium, and a Research Associate with Newcastle University, Newcastle upon Tyne, U.K. In 2001, he was appointed as a Lecturer in statistics at School of Mathematics & Statistics, Newcastle University. In 2004, he moved to the School of Business and Economics, Loughborough University, Loughborough, U.K., as a Lecturer, where he was subsequently appointed as a Reader and a Professor. His current research interests are Bayesian statistical modelling and forecasting for Gaussian and non-Gaussian dynamic problems in various management areas. In recent years, much of his work has also involved transport and traffic management such as transportation demand analysis, travel behaviour modelling, and intelligent transportation systems. Professor Li is a member of the Royal Statistical Society.