Behaviour characteristics identification of inbound tourists in Shandong Province from three perspectives of space-network-emotion
Bibliographic Data
| ID | 24030358 |
|---|---|
| Authors | Lin Liu (0000-0002-7202-3418, Institute of Geodesy and Geophysics), Wanwu Li (0000-0002-7960-3554, Institute of Geodesy and Geophysics, corresponding author), Zilin Xu (Institute of Geodesy and Geophysics), Jiufu Ying (Institute of Geodesy and Geophysics), Lijun Sun (0009-0001-6484-438X, Institute of Geodesy and Geophysics) |
| Year | 2026 |
| Pages | 1-16 |
| Publication date | 2026-08-09 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Tourism Recreation Research (JOURNAL) |
| Journal identifiers | ISSN: 0250-8281 • E-ISSN: 2320-0308 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/02508281.2026.2705476 |
| OpenAlex | W7202031727 |
| Language | EN |
| References cited | 34 |
The research explores the behavioural characteristics of inbound tourists from three different perspectives of space, network and emotion, and compensates for the limitations of current single-perspective analysis. Methodologically, the complex network analysis method is integrated into GIS spatial analysis and statistical analysis, and a geotagged photo-based Emotion State Index (ESI) is proposed, along with its measurement method. The kernel density analysis, path tracking technology and others are adopted to explore the spatial agglomeration characteristics, tourism trajectory patterns and distribution characteristics of inbound tourists. The methods of network density and central potential, structural hole, community discovery algorithm are used to analyse the overall structural characteristics, local competitiveness and community aggregation of the inbound tourism network, and to verify its spatial aggregation from the perspective of the network. A method for recognizing tourism emotions is proposed, the Emotion Index (El) for tourist hotspots and ESI for tourist communities are computed, and the correlation between the emotional index and the types of attractions is analysed. Taking Shandong Province as an example for empirical research, the findings can provide decision-making support for the allocation of tourism resources, the planning of tourism routes, and the management of tourist flows.
Distribution (mathematics) · Economies of agglomeration · Empirical research · Identification (biology) · Index (typography) · Kernel density estimation · Perspective (graphical) · Social network analysis · Tourism · Advanced Technologies in Various Fields · Complex Network Analysis Techniques · Diverse Aspects of Tourism Research
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| Highly cited | No |
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