地理科学 ›› 2021, Vol. 41 ›› Issue (11): 1992-2001.doi: 10.13249/j.cnki.sgs.2021.11.012

• • 上一篇    下一篇

旅游景区客流规模特征与影响因素研究——以江苏省204家景区为例

刘培学(), 张捷(), 张建新, 张金悦, 张迎莹   

  1. 南京大学地理与海洋科学学院,江苏 南京 210023
  • 收稿日期:2020-06-05 修回日期:2020-09-06 出版日期:2021-11-10 发布日期:2022-01-24
  • 通讯作者: 张捷 E-mail:pixliu@nju.edu.cn;jiezhang@nju.edu.cn
  • 作者简介:刘培学(1987-),男,山东潍坊人,助理研究员,博士,主要从事大数据与流空间研究。E-mail: pixliu@nju.edu.cn
  • 基金资助:
    国家自然科学基金项目(42001145);教育部人文社会科学研究一般项目(20YJC790080)

The Rank-size Distribution and Influencing Factors of Tourist Flow: A Case Study of 204 Scenic Spots in Jiangsu Province

Liu Peixue(), Zhang Jie(), Zhang Jianxin, Zhang Jinyue, Zhang Yingying   

  1. School of Geography and Ocean Science, Nanjing University, Nanjing 210023, Jiangsu, China
  • Received:2020-06-05 Revised:2020-09-06 Online:2021-11-10 Published:2022-01-24
  • Contact: Zhang Jie E-mail:pixliu@nju.edu.cn;jiezhang@nju.edu.cn
  • Supported by:
    National Natural Science Foundation of China(42001145);MOE (Ministry of Education in China) Project of Humanities and Social Sciences(20YJC790080)

摘要:

以江苏省204家4A级及以上景区为例,利用手机信令漫游监测所得的旅游客流客源数据,基于Zifp法则表现江苏景区年客流量的位序-规模特征,在全省景区旅游客流规模的不同组间差异特征分析的基础上,使用多元线性回归和最优标度回归方法研究了景区客流规模的影响因素。研究表明:① 省域目的地内部景区客流规模等级明显,省外客源的客流规模分布较省内差异大,更符合首位型分布特征;② 全省整体客流的季节性不明显,各景区的季节性较强,不同产品类型的景区存在季节波动性差异;③ 景区客流受景区等级、季节性、市中心距离、所在城市经济发展水平等因素的影响,省内外客流在部分因素影响程度上存在明显差异,景区季节波动增大会显著降低其接待的省内客流规模。对优化景区客流规模等级体系和目的地区域空间结构提出建议。

关键词: 目的地区域, 大数据, 旅游流, 位序规模, 最优标度回归

Abstract:

This study takes 204 scenic spots of 4A and 5A levels within the provincial destination as an example. Using the big data of tourist flow from mobile signaling roaming monitoring, based on the Zifp rule to show the order-scale characteristics of the annual tourist flow in Jiangsu scenic area. Taking the Gini coefficient, the Tyre coefficient and the seasonal ratio to analyze the seasonal differences and characteristics of the tourist flow scale in the provincial scenic spot. The optimal scale regression was used to study the influencing factors of the tourist flow scale in the scenic spot. Results shows that: 1) The size of the tourist flow scale in the internal scenic spot of the provincial destination is obvious, and the distribution of the tourist flow outside the province is larger than that in the province, which is more consistent with the distribution of the law of the primate city; 2) The seasonality of the overall tourist flow in Jiangsu Province is not obvious, while seasonal is strong in different scenic spots, there is a certain regional differentiation difference in this region; 3) Tourist flow is significantly affected by many factors such as scenic spot level, downtown distance, and economic development level of the city. There are significant differences in the degree of influence on tourist flow inside and outside the province. Combined with the background of all-area tourism-based development, this paper puts forward suggestions for optimizing the hierarchical system of tourist flow scale and the spatial structure of the destination area.

Key words: tourist destination district, big data, tourist flow, rank-size, Categorical Regression (CATREG)

中图分类号: 

  • F591.99