Discovering spatial patterns of tourist flow with multi-layer transport networks

Abstract

Transport is an integral part of the tourism industry. The tourist traveling patterns are highly dependent on the transport infrastructure in a tourism destinations. Based on the Social Network Theory, four centrality indicators and the transition possibility are adopted to explore the tourism flow network related to different modes of transportation and tourist transition capabilities in tourism destinations. A complex tourist itinerary visualization model uncovers the spatial structure of multi-layer tourist flows. Dunhuang, a rapidly growing tourist destination in Northwest China, reveals this patterning. Results show that: (1) The spatial structure and flow rate of the tourism flow network is significantly different when different transport modes are observed. (2) The tourists transition capability for different transport modes in the same region varies according to the geographic location and infrastructure level. (3) Tourists manifest different movement patterns among the available transport networks within a destination area.

摘要

交通是旅游系统中十分重要的一部分。旅游目的地交通基础设施的发展情况深刻影响着游客的出行模式。本文基于社会网络理论, 通过中心性分析方法和转移概率的计算, 以中国西北地区重要旅游目的地敦煌为案例地探究了不同交通方式下的旅游流网络, 并建立了一个多层交通下的旅游流网络可视化模型。本文拓展了交通与游客空间行为研究的方法, 并为旅游目的地规划与管理提供了科学依据。结果表明：（1）不同交通方式下的旅游流网络的流量和结构呈现出明显差异；（2）对于同一区域, 不同交通方式之间的转移概率会因为地理位置和交通基础设施水平的差异而不同；（3）游客出行行为模式在不同交通方式网络下表现出差异。

Keywords:

• Spatial pattern
• tourist flow
• multi-layer transport networks
• network analysis
• transition probability
• Dunhuang
• China

关键词:

• 空间模式
• 旅游流
• 多层交通网络
• 网络分析
• 转移概率
• 敦煌
• 中国

Acknowledgements

We would like to express our sincere appreciation to students of Nanjing University for their help in collecting the questionnaire data in Dunhuang. I am also indebted to the anonymous referees for helpful comments.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the National Natural Science Foundation of China (NSFC) [grant numbers 41771153] and MOE (Ministry of Education in China) Project of Humanities and Social Sciences [grant numbers 20YJC790080].

Notes on contributors

Shuang Liu

Shuang Liu, is a master student in the School of Geography and Ocean Science at Nanjing University. Her research interests include tourism flow and tourism transport. E-mail: [email protected]

Jie Zhang

Jie Zhang, PhD, is a Professor in the School of Geography and Ocean Science at Nanjing University. His research interests include tourism geography, tourist flow, soundscape, and Chinese calligraphic landscape. E-mail: [email protected]

Peixue Liu

Peixue Liu, PhD, is a research assistant professor in the School of Geography and Ocean Science at Nanjing University. His areas of research interest include tourist behavior and big data analytics. E-mail: [email protected]

Yifan Xu

Yifan Xu, is a master student in the School of Geography and Ocean Science at Nanjing University. Her research interests include tourism geography. E-mail: [email protected]

Li Xu

Li Xu, is a master student in the School of Geography and Ocean Science at Nanjing University. Her research interests include tourism geography and culture tourism. E-mail: [email protected]

Honglei Zhang

Honglei Zhang, PhD, is an associate professor in theSchool of Geography and Ocean Science at Nanjing University, China. His research interests include tourist behaviour and tourism geography. E-mail: [email protected]