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Journal of Advanced Transportation
Volume 2017 (2017), Article ID 8652053, 13 pages
Research Article

Understanding Visitors’ Responses to Intelligent Transportation System in a Tourist City with a Mixed Ranked Logit Model

Department of Civil Engineering, Tsinghua University, Beijing 100084, China

Correspondence should be addressed to Jing Shi; nc.ude.auhgnist@ihsgnij

Received 10 November 2016; Revised 22 January 2017; Accepted 6 February 2017; Published 22 February 2017

Academic Editor: Zhi-Chun Li

Copyright © 2017 Yang Liu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


One important function of Intelligent Transportation System (ITS) applied in tourist cities is to improve visitors’ mobility by releasing real-time transportation information and then shifting tourists from individual vehicles to intelligent public transit. The objective of this research is to quantify visitors’ psychological and behavioral responses to tourism-related ITS. Designed with a Mixed Ranked Logit Model (MRLM) with random coefficients that was capable of evaluating potential effects from information uncertainty and other relevant factors on tourists’ transport choices, an on-site and a subsequent web-based stated preference survey were conducted in a representative tourist city (Chengde, China). Simulated maximum-likelihood procedure was used to estimate random coefficients. Results indicate that tourists generally perceive longer travel time and longer wait time if real-time information is not available. ITS information is able to reduce tourists’ perceived uncertainty and stimulating transport modal shifts. This novel MRLM contributes a new derivation model to logit model family and for the first time proposes an applicable methodology to assess useful features of ITS for tourists.