Accommodating variations in responsiveness to level-of-service measures in travel mode choice modeling
An individual's responsiveness to level-of-service variables affects her or his travel mode choice for a trip. This responsiveness will, in general, vary across individuals based on observed (to an analyst) and unobserved (to an analyst) individual characteristics. The current paper formulates a multinomial-logit based model of travel mode choice that accommodates variations in responsiveness to level-of-service measures due to both observed and unobserved individual characteristics in a comprehensive manner. The choice probabilities in the resulting model are evaluated using Monte Carlo simulation techniques and the model parameters are estimated using a maximum simulated likelihood approach. The model is applied to examine the impact of improved rail service on weekday, business travel in the Toronto--Montreal corridor. The empirical results show that not accounting adequately for variations in responsiveness across individuals leads to a statistically inferior data fit and also to inappropriate evaluations of policy actions aimed at improving inter-city transportation services.
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Volume (Year): 32 (1998)
Issue (Month): 7 (September)
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- Lee, Lung-Fei, 1992.
"On Efficiency of Methods of Simulated Moments and Maximum Simulated Likelihood Estimation of Discrete Response Models,"
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- Gary Chamberlain, 1980. "Analysis of Covariance with Qualitative Data," Review of Economic Studies, Oxford University Press, vol. 47(1), pages 225-238. Full references (including those not matched with items on IDEAS)
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