Urban public transport choice behavior analysis and service improvement policy-making: a case study from the metropolitan city, Chengdu, China

DOI10.1080/02664763.2014.986438OpenAlexW2072401348MaRDI QIDQ5130194

No author found.

Publication date: 4 November 2020

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2014.986438

zbMATH Keywords

elasticityhypothesis testcorrelation coefficientgoodness of fitchoice probability

Mathematics Subject Classification ID

Statistics (62-XX)

Uses Software

• NLOGIT

Cites Work

• Deriving Public Transport Level of Service Weights from a Multiple Comparison of Latent and Observable Variables
• Applied Choice Analysis

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