PROGRESS IN GEOGRAPHY ›› 2022, Vol. 41 ›› Issue (7): 1261-1273.doi: 10.18306/dlkxjz.2022.07.010

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A new tourist source concentration index (tourCI) and empirical analysis

XING Qian1(), LI Renjie1,2, GUO Fenghua3,4,*(), LI Xiaofeng1   

  1. 1. College of Geographical Sciences, Hebei Normal University, Shijiazhuang 050024, China
    2. Hebei Key Laboratory of Environmental Change and Ecological Construction, Shijiazhuang 050024, China
    3. Hebei Institute of Geographical Sciences, Shijiazhuang 050011, China
    4. Hebei Technology Innovation Center for Geographic Information Application, Shijiazhuang 050011, China
  • Received:2022-01-05 Revised:2022-03-17 Online:2022-07-28 Published:2022-09-28
  • Contact: GUO Fenghua E-mail:Angelina870813@yeah.net;guo_yunxin@126.
  • Supported by:
    National Natural Science Foundation of China(41471127);Foundation for Talent Training Project in Hebei Province(A2016001130);Hebei Province Graduate Student Innovation Ability Training Funding Project(CXZZBS2021060)

Abstract:

Agglomeration characteristics of tourist sources are an important content of the research on the spatial structure of tourist source market, but the existing customer source concentration indices cannot be compared horizontally and it is difficult to explain the driving factors. In this study, we proposed a calculation method of tourist source concentration index tourCI that supports the introduction of different influencing factors, established a conceptual framework of tourist source spatial structure interpretation based on the tourCI index, and provided the multi-dimensional description and meaning analysis of tourCI to calculate the distribution and agglomeration characteristics of tourist source areas under the influence of different factors. Taking Dali ancient town as an example, we used the Sina Weibo data to calculate tourCI based on administrative regions, which shows that local tourists in Yunnan Province have an important impact on the tourist source distribution characteristics of Dali ancient town, and the distribution of tourists outside Yunnan Province is relatively balanced. tourCI based on distance describes the variation of the distribution characteristics of tourist sources in Dali ancient town with the change of distance to the destination. From near to far the index of each distance segment shows a weak-strong-weak-equilibrium change pattern. The results of economic dimension show that tourists from the first tier cities are highly concentrated in areas with high economic development levels, and tourists from the new first tier cities are not significantly affected by economic factors and are evenly distributed. The distribution of tourist sources from second and third tier cities is greatly affected by economic factors. Theoretical and empirical analyses show that tourCI index has a good analytical capability for the agglomeration characteristics and driving factors of the spatial structure of tourist sources, which helps enrich the methods of tourism geography research.

Key words: tourist source, spatial structure, tourCI, concentration index, Dali ancient town