地理学报 ›› 2022, Vol. 77 ›› Issue (6): 1391-1410.doi: 10.11821/dlxb202206007

• 京津冀协同发展 • 上一篇    下一篇

京津冀地区旅游经济增长的时空演化及影响因素

崔丹1(), 李沅曦2, 吴殿廷3()   

  1. 1.中国科学技术信息研究所,北京 100038
    2.北京大学政府管理学院,北京 100871
    3.北京师范大学地理科学学部,北京 100875
  • 收稿日期:2021-05-06 修回日期:2022-04-24 出版日期:2022-06-25 发布日期:2022-08-19
  • 通讯作者: 吴殿廷(1958-), 男, 辽宁大连人, 博士, 教授, 主要研究方向为区域经济与区域规划等。E-mail: wudianting@bnu.edu.cn
  • 作者简介:崔丹(1985-), 女, 河南漯河人, 博士, 助理研究员, 主要从事区域经济与区域创新发展研究。E-mail: cuidan1@istic.ac.cn
  • 基金资助:
    国家自然科学基金项目(41771128)

Spatiotemporal evolution and influencing factors of tourism economic growth in Beijing-Tianjin-Hebei region

CUI Dan1(), LI Yuanxi2, WU Dianting3()   

  1. 1. Institute of Scientific and Technical Information of China, Beijing 100038, China
    2. School of Government, Peking University, Beijing 100871, China
    3. Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
  • Received:2021-05-06 Revised:2022-04-24 Published:2022-06-25 Online:2022-08-19
  • Supported by:
    National Natural Science Foundation of China(41771128)

摘要:

揭示区域旅游经济增长的时空演化特征并探究其影响因素有助于丰富区域旅游经济发展理论,也可为京津冀地区旅游协同发展政策的制定提供科学依据。在初步构建京津冀地区旅游经济增长时空演化研究框架及多因素分析模型的基础上,运用基尼系数、核密度曲线、双变量局域自相关等方法,从旅游空间的规模、等级和形态变化等方面考察京津冀地区2001—2019年旅游经济增长的空间格局及演化过程,并基于面板多元回归模型和空间计量模型对其影响因素进行深入剖析。结果表明:① 京津冀地区旅游经济增长的空间格局从双核心逐渐转为多核心,旅游区域中心城市和部分旅游节点城市逐步成为旅游经济增长的主要载体,京津冀旅游协同发展初见成效。② 京津冀地区旅游经济增长的时空演化过程大体可分为3个阶段:高速增长下的双核心极化缓解阶段;中速增长下的双核心向多核心转变阶段;快速增长下的多核心形成阶段。③ 影响京津冀地区旅游经济增长的主要因素有人均GDP、星级饭店的数量、到北京/天津高速公路距离、旅游发展政策和旅游大事件等,其中人均GDP对旅游经济增长有显著的空间溢出效应。④ 影响核心枢纽城市、旅游区域中心城市和节点城市的旅游经济增长因素有一定差异,星级饭店数量、旅游大事件和PM2.5浓度对核心枢纽城市和旅游区域中心城市旅游经济增长有较大影响,城市道路面积、到北京/天津高速公路距离、旅游发展政策、旅游大事件、年末实有出租车数量、PM2.5浓度等则是影响旅游节点城市旅游经济增长的主要因素。

关键词: 旅游经济增长, 时空演化, 影响因素, 京津冀

Abstract:

Revealing the spatiotemporal evolution of regional tourism economic growth and exploring its influencing factors will help enrich the theoretical and practical research on regional tourism economic development and formulate relevant policies. In terms of methodology, this study is based on the constructed research framework and multivariate analysis model of the spatiotemporal evolution of tourism economic growth in the Beijing-Tianjin-Hebei region, and employs the methods including Gini coefficient, kernel density estimation, and bivariate local autocorrelation. The spatial pattern and its evolution process of tourism economic growth in the study region from 2001 to 2019 are investigated from the scale, level and pattern changes of the tourism space. The influencing factors are deeply analyzed based on the panel multiple regression model and spatial econometric model. The results show that: (1) The spatial pattern of tourism economic growth gradually shifted from dual cores to multi-cores. Regional tourism central cities and some peripheral tourism node cities became the main areas of tourism economic growth. (2) The spatiotemporal evolution process of tourism economic growth can be divided into three stages, namely, the dual core polarization alleviation stage under high-speed growth, the transition stage from dual cores to multi-cores under medium speed growth, and the multi-core formation stage under fast-speed growth. (3) The main factors affecting the tourism economic growth are per capita GDP, the number of star grade hotels, the length of expressway to Beijing or Tianjin, tourism development policies, and tourism events. Among them, the per capita GDP had a significant spatial spillover effect on the growth of tourism economy in this region. (4) There are some differences in tourism economic growth factors among core hub cities, regional tourism central cities and node cities. The number of star grade hotels, tourism events and PM2.5 concentration have great influence on tourism economic growth of core hub cities and regional tourism central cities, while the urban road area, the length of expressway to Beijing or Tianjin, tourism development policies, tourism events, the number of taxis and PM2.5 concentration are the main influencing factors on the tourism economic growth in tourism node cities.

Key words: tourism economic growth, spatiotemporal evolution, influencing factor, Beijing-Tianjin-Hebei region