MCMC Bayes-Mixed Logit for corridor transport mode split

Author

Gong, Weiwei ; Wang, Xi

Author_Institution

Transp. & Econ. Res. Inst., Beijing, China

fYear

2011

fDate

16-18 Dec. 2011

Firstpage

1867

Lastpage

1871

Abstract

Market share is a key indicator of competitiveness especially for a new band or mode. In order to develop effective marketing strategies for high-speed railway operation, the discrete choice concept model for mode split is constructed with seven elements based on the application of consumer choice theory. The MCMC Bayes-Mixed Logit algorithm is proposed analyzing a designed travel survey with intercity travel behavior information taking occupation and income into the utility function and applying the MCMC method with Matlab language. Finally, take the Beijing-Shanghai direct passenger traffic as an example with the real survey data. The experiment result shows that the fitting accuracy of Bayes-Mixed Logit is improved by 18.2% comparing with the MLE-Logit model.

Keywords

Bayes methods; Monte Carlo methods; consumer behaviour; economic indicators; railways; strategic planning; transportation; travel industry; Beijing-Shanghai direct passenger traffic; MCMC Bayes-mixed logit algorithm; MCMC method; Matlab language; consumer choice theory; designed travel survey; discrete choice concept model; fitting accuracy; high-speed railway operation; income; intercity travel behavior information; marketing strategies; mode split; occupation; utility function; Atmospheric modeling; Computational modeling; Economics; Educational institutions; Estimation; Mathematical model; Transportation; Bayes estimation; High-Speed Railway; Mixed logit; Mode split;

fLanguage

English

Publisher

ieee

Conference_Titel

Transportation, Mechanical, and Electrical Engineering (TMEE), 2011 International Conference on

Conference_Location

Changchun

Print_ISBN

978-1-4577-1700-0

Type

conf

DOI

10.1109/TMEE.2011.6199578

Filename

6199578