JOURNAL OF TRAVEL RESEARCH

Public transport connectivity and intercity tourist flows

Yang, Yang; Li, Dong; Li, Xiang (Robert)

Abstract

In this study, we investigate how dyadic air and rail transport connectivity affects domestic tourist flows among 343 Chinese cities. Using geo-tagged Sina Weibo data to track tourists during China’s National Day Golden Week in 2014, we estimate several gravity models with a negative binomial distribution. The estimation results suggest that air transport connectivity generally has a greater influence than rail transport on dyadic tourist flows, while connectivity provided by ordinary trains (compared to other rail types) is most important in the context of rail transport. Also, we find the effects of transport connectivity and intermodal transport competition to depend on the origin-to-destination distance. Different types of railway trains appear to have distinct effective distance ranges: the effect of high-speed rail trains is strongest at travel distances between 1,800 and 2,000 km, whereas bullet trains’ effect is strongest at distances between 400 and 600 km.

Keywords

Sina Weibo; gravity model; air transport; transport connectivity; high-speed rail; domestic tourist flows

Research topic

AI and Big Data, Tourist Flows and Location

Research method

Econometrics, Big Data

Geographic area

China

Additional links for this paper

ResearchGate

Publisher Website

Web of Science

HOW TO CITE

Yang, Y., Li, D., & Li, X. (2019). Public transport connectivity and intercity tourist flows. Journal of Travel Research, 58(1), 25-41.

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