资源科学 ›› 2021, Vol. 43 ›› Issue (1): 185-196.doi: 10.18402/resci.2021.01.15

• 旅游资源 • 上一篇    下一篇

中国地级单元旅游业发展效率格局及影响因素

纪晓萌1(), 秦伟山1,2(), 李世泰1, 刘肖梅3, 王秋贤1   

  1. 1.鲁东大学资源与环境工程学院,烟台 264025
    2.中国科学院地理科学与资源研究所,北京 100101
    3.泰山学院旅游学院,泰安 271021
  • 收稿日期:2019-12-19 修回日期:2020-08-21 出版日期:2021-01-25 发布日期:2021-03-25
  • 作者简介:纪晓萌,女,山东青岛人,硕士研究生,研究方向为区域发展与产业规划。E-mail: kalaxs@126.com
  • 基金资助:
    国家社会科学基金青年项目(19CGL070);山东省社会科学规划研究项目(20CJJJ14);教育部人文社会科学研究项目(17YJCZH174)

Development efficiency of tourism and influencing factors in China’s prefectural-level administrative units

JI Xiaomeng1(), QIN Weishan1,2(), LI Shitai1, LIU Xiaomei3, WANG Qiuxian1   

  1. 1. School of Resources and Environmental Engineering, Ludong University, Yantai 264025, China
    2. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
    3. School of Tourism, Taishan University, Taian 271021, China
  • Received:2019-12-19 Revised:2020-08-21 Online:2021-01-25 Published:2021-03-25

摘要:

旅游业发展效率是衡量区域内旅游业投入产出状况的重要指标。文章选取中国329个地级行政单元为研究对象,运用DEA模型对2018年旅游业发展效率进行综合测度,通过空间自相关、热点分析和地理探测器探究其空间格局及影响因素。结果表明:①中国旅游业发展效率综合效率高水平、较高水平、中等水平、较低水平及低水平地区分别占评价单元16.11%、17.93%、27.96%、26.75%和11.25%;纯技术效率区域差异明显,高水平地区主要分布于地势阶梯交界处、长三角城市群和珠三角城市群;规模效率空间上大致以“胡焕庸线”为界,表现为东南高而西北低;②旅游业发展效率存在空间自相关性,整体上呈现“大集聚小分散”特点。冷热点空间集聚特征明显,表现出“南热北冷”的特点,其中西南、华南、华东地区表现为高值集聚,华北、东北及西北地区表现为低值集聚。依据其发展水平和空间特征划分为辐射带动型、边缘依附型、整体提升型和优化提升型4种类型;③旅游业发展效率受多重因素影响,其中旅游发展质量、旅游服务水平及旅游资源质量为旅游业发展效率空间分异的主导因素,推动旅游业发展、提高旅游服务水平以及旅游资源利用转化率是提升旅游业发展效率的重要途径。本文通过探析中国地级单元旅游业发展效率的空间格局及影响因素,以期对旅游业提质增效、转型升级的有效路径及旅游发展资源的投入和利用水平的提升提供决策依据和理论支撑。

关键词: 旅游业发展效率, 综合测度, 热点分析, 地理探测器, 中国

Abstract:

The development efficiency of tourism is an important indicator of the input-output status of tourism in a region. This study used the data envelopment analysis (DEA) model and data from 329 prefectural-level administrative regions of China to comprehensively measure the development efficiency of tourism in 2018. Spatial autocorrelation, Getis-Ord Gi*, and geographical detector were used to explore the spatial pattern and influencing factors of tourism development efficiency. The main conclusions include: (1) Areas with high level, medium-high level, medium level, medium-low level, and low level of comprehensive tourism development efficiency accounted for 16.11%, 17.93%, 27.96%, 26.75%, and 11.25% of the evaluated administrative units respectively. There were clear regional differences in pure technical efficiency, and the high level areas were mainly distributed in the junction of the terrain ladders, the Yangtze River Delta city group, and the Pearl River Delta city group. In terms of scale efficiency, the division was roughly along the “Hu Line”, higher in the southeast and lower in the northwest. (2) The efficiency of tourism development showed spatial autocorrelation, characterized by “large agglomeration and small dispersion” on the whole. Cold and hot spots showed obvious spatial clustering characteristics hot in the south and cold in the north with southwest, South, and East China showing high value clustering, and North, Northeast, and northwest China showing low value clustering. According to the development level and spatial characteristics, tourism development efficiency can be divided into four types: radiation-driven, edge-dependent, overall promotion, and optimized promotion. (3) The efficiency of tourism development is affected by multiple factors, among which tourism service level, tourism development quality, and tourism resource endowments are the leading factors for the spatial differentiation of tourism development efficiency. Promoting tourism development and improving tourism service level and tourism resource use conversion rate are important ways to improve the efficiency of tourism development. By analyzing the spatial pattern and influencing factors of the tourism development efficiency of Chinese prefectural-level administrative units, we hoped to provide a decision-making basis and theoretical support for exploring the effective ways of improving the quality and efficiency of tourism, transforming and upgrading the tourism industry, and increasing the investment and utilization level of tourism development resources.

Key words: tourism development efficiency, comprehensive measurement, Getis-Ord $G^*_i$, geographical detector, China