Coupling and Coordination Analysis of Accessibility Improvement and Tourism Network Attention Change in Scenic Areas and Cities Influenced by High‐Speed Rail

ABSTRACT The continuous expansion of the high‐speed rail (HSR) network not only shortens tourists' travel time but also significantly impacts the network attention of destinations. This study uses door‐to‐door HSR travel times from the Baidu Map API to compute weighted average travel time (WATT) for transportation accessibility (TA) and Baidu Index search data for tourism network attention (TNA) and applies coupling coordination degree (CCD) and relative development degree (RDD) models to evaluate TA‐TNA coordination across 28 scenic areas and their host cities in the urban agglomerations in the middle reaches of the Yangtze River (UAMRYR) for 2016–2023. The results indicate that WATT fell by 14.9%, whereas TNA rose overall but remained uneven. The CCD‐RDD analysis reveals that most scenic areas exhibit a TA lag category, whereas cities perform better than scenic areas in the coordinated development. To translate these findings into practice, three priorities emerge. (1) Last‐mile transport and visitor services in fringe nodes should be improved; (2) Digital marketing and pricing should guide scenic area operations; (3) National and regional transport‐tourism governance tools need to be strengthened. These insights provide a quantitative basis for aligning rail expansion, destination marketing, and infrastructure finance to achieve balanced regional tourism growth.

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Publication Details

Journal
IET Intelligent Transport Systems
Published
2025-01-01
DOI
https://doi.org/10.1049/itr2.70077
Primary Topic
Urban Transport and Accessibility
Type
article
Field-Weighted Citation Impact
0.00

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article

Coupling and Coordination Analysis of Accessibility Improvement and Tourism Network Attention Change in Scenic Areas and Cities Influenced by High‐Speed Rail

Xiaoping Luo, Lei Wu, S. L. Cheng
IET Intelligent Transport Systems
Urban Transport and Accessibility
article

Coupling and Coordination Analysis of Accessibility Improvement and Tourism Network Attention Change in Scenic Areas and Cities Influenced by High‐Speed Rail

Xiaoping Luo, Lei Wu, S. L. Cheng
article en

Abstract

ABSTRACT The continuous expansion of the high‐speed rail (HSR) network not only shortens tourists' travel time but also significantly impacts the network attention of destinations. This study uses door‐to‐door HSR travel times from the Baidu Map API to compute weighted average travel time (WATT) for transportation accessibility (TA) and Baidu Index search data for tourism network attention (TNA) and applies coupling coordination degree (CCD) and relative development degree (RDD) models to evaluate TA‐TNA coordination across 28 scenic areas and their host cities in the urban agglomerations in the middle reaches of the Yangtze River (UAMRYR) for 2016–2023. The results indicate that WATT fell by 14.9%, whereas TNA rose overall but remained uneven. The CCD‐RDD analysis reveals that most scenic areas exhibit a TA lag category, whereas cities perform better than scenic areas in the coordinated development. To translate these findings into practice, three priorities emerge. (1) Last‐mile transport and visitor services in fringe nodes should be improved; (2) Digital marketing and pricing should guide scenic area operations; (3) National and regional transport‐tourism governance tools need to be strengthened. These insights provide a quantitative basis for aligning rail expansion, destination marketing, and infrastructure finance to achieve balanced regional tourism growth.

IET Intelligent Transport SystemsVol. 19(1)
Jiangxi University of Technology (CN), East China University of Technology (CN), Jiangxi University of Finance and Economics (CN)
Education Department of Jiangxi Province
Openalex Percentile: Top 77%
Urban Transport and Accessibility
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Coupling and Coordination Analysis of Accessibility Improvement and Tourism Network Attention Change in Scenic Areas and Cities Influenced by High‐Speed Rail — Xiaoping Luo, Lei Wu, et al. · IET Intelligent Transport Systems (2025) | TGRS Research Map | TGRS