Discovering spatial patterns of tourist flow with multi-layer transport networks. Issue 1 (2nd January 2023)

• Record Type: Journal Article
• Authors: Liu, Shuang; Zhang, Jie; Liu, Peixue; Xu, Yifan; Xu, Li; Zhang, Honglei
• Is Part Of: Tourism geographies. Volume 25:Issue 1(2023)
• Page Start: 113
• Page End: 135
• Publication Date: 2023-01-02
• Subjects: Spatial pattern -- tourist flow -- multi-layer transport networks -- network analysis -- transition probability -- Dunhuang -- China; 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; Travel -- Periodicals; Ecotourism -- Periodicals; 910
• DOI: 10.1080/14616688.2020.1850849
• Languages: English
• ISSNs: 1461-6688

Abstract

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。