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Investigate Tourist Behavior through Mobile Signal: Tourist Flow Pattern Exploration in Tibet

doi: 10.3390/su12219125
Identifying the tourist flow of a destination can promote the development of travel-related products and effective destination marketing. Nevertheless, tourist inflows and outflows have only received limited attention from previous studies. Hence, this study visualizes the tourist flow of Tibet through social network analysis to bridge the aforementioned gap. Findings show that the Lhasa prefecture is the transportation hub of Tibet. Tourist flow in the eastern part of Tibet is generally stronger than that in the western part. Moreover, the tourist flow pattern identified mainly includes “(diverse or balanced) diffusion from the main center”, “clustering to the main center”, and “diffusion from a clustered circle”.
- Ritsumeikan Asia Pacific University Japan
- Hong Kong Polytechnic University China (People's Republic of)
- Beijing International Studies University China (People's Republic of)
- Ritsumeikan Asia Pacific University Japan
- Beijing International Studies University China (People's Republic of)
social network analysis, Environmental effects of industries and plants, TJ807-830, pattern, Tibet, TD194-195, Renewable energy sources, Environmental sciences, tourist flow, GE1-350, visualization
social network analysis, Environmental effects of industries and plants, TJ807-830, pattern, Tibet, TD194-195, Renewable energy sources, Environmental sciences, tourist flow, GE1-350, visualization
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).12 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
