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A Study on Nested Logit Mode Choice Model for Intercity High-Speed Rail System with Combined RP/SP Data

Enjian Yao, T Morikawa, Shinya Kurauchi, T. Tokida

Open publisher page 13 citations

Abstract

This research analyzes the demand for intercity high-speed rail (HSR) system planned in Japan with the integrated demand forecasting model. The model integrates choice of routes and modes is estimated from a combined stated preference (SP) and revealed preference (RP) data. The SP/RP combined estimation method exploits the advantages of both data sets while mitigating the weaknesses of each. The SP survey is conducted to elicit preference for the non-existing high-speed rail together with the RP survey on the actual intercity mode choice for the specific corridor. Considering the independence of irrelevant alternatives (IIA) attribute, a nested structure is applied to these alternatives and the advantages of the nested logit model with the combined SP/RP data are discussed in this paper.

About this research paper

What this paper is about

This research analyzes the demand for intercity high-speed rail (HSR) system planned in Japan with the integrated demand forecasting model. The model integrates choice of routes and modes is estimated from a combined stated preference (SP) and revealed preference (RP) data. The SP/RP combined estimation method exploits the advantages of both data sets while mitigating the weaknesses of each. The SP survey is conducted to elicit preference for the non-existing high-speed rail together with the RP survey on the actual intercity mode choice for the specific corridor. Considering the independence of irrelevant alternatives (IIA) attribute, a nested structure is applied to these alternatives and the advantages of the nested logit model with the combined SP/RP data are discussed in this paper.

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OpenAlex reports 13 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

This research analyzes the demand for intercity high-speed rail (HSR) system planned in Japan with the integrated demand forecasting model. The model integrates choice of routes and modes is estimated from a combined stated preference (SP) and revealed preference (RP) data. The SP/RP combined estimation method exploits the advantages of both data sets while mitigating the weaknesses of each. The SP survey is conducted to elicit preference for the non-existing high-speed rail together with the RP survey on the actual intercity mode choice for the specific corridor. Considering the independence of irrelevant alternatives (IIA) attribute, a nested structure is applied to these alternatives and the advantages of the nested logit model with the combined SP/RP data are discussed in this paper.

Key concepts: Nested logit, Preference, Revealed preference, Mode (computer interface), Computer science, Discrete choice, Independence (probability theory), Mode choice

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