自然资源学报 ›› 2021, Vol. 36 ›› Issue (4): 866-878.doi: 10.31497/zrzyxb.20210405

• 其他研究论文 • 上一篇    下一篇

陕西省县域旅游效率的空间格局及影响因素

潘秋玲1,2(), 宋玉强1, 陈乐1,2, 潘志奎1   

  1. 1.西安外国语大学旅游学院,人文地理研究所,西安 710128
    2.陕西文化和旅游研究院,西安 710128
  • 收稿日期:2019-11-03 修回日期:2020-03-23 出版日期:2021-04-28 发布日期:2021-06-28
  • 作者简介:潘秋玲(1969- ),女,新疆石河子人,博士,教授,硕士生导师,研究方向为旅游规划与管理。E-mail: xapql@163.com
  • 基金资助:
    陕西省社会科学基金项目(2017D012);西安外国语大学研究生科研基金项目(SSYB2019084)

The spatial pattern and influencing factors of county-scale tourism efficiency in Shaanxi province

PAN Qiu-ling1,2(), SONG Yu-qiang1, CHEN Le1,2, PAN Zhi-kui1   

  1. 1. School of Tourism & Research Institute of Human Geography, Xi'an International Studies University, Xi'an 710128, China
    2. Shaanxi Institute of Culture and Tourism, Xi'an 710128, China
  • Received:2019-11-03 Revised:2020-03-23 Online:2021-04-28 Published:2021-06-28

摘要:

提质增效是目前旅游产业发展面临的重要课题。基于数据包络分析法,选用Python爬取技术,对陕西省107个县域的旅游效率进行测度分析,探讨县域旅游效率的空间格局及其影响的主要因素。研究表明:(1)陕西省旅游效率达到有效的县域数量整体偏低,高旅游效率县域多集中于市辖郊县。(2)县域旅游效率分布不均衡。陕北地区高旅游效率县域主要集中在黄河沿岸,关中地区呈现“西高东低”的现象,陕南地区高旅游效率县域则集中在地市交界处。(3)影响县域旅游总效率、技术效率和规模效率的主导因素不同。旅游收入占GDP比例(反映旅游业水平)、人口密度(反映县域发展水平)及汽车站数量(反映交通服务水平)是影响陕西省县域旅游总效率及技术效率的主导因素,而旅游资源禀赋(反映旅游业水平)、人口密度(反映县域发展水平)则是影响陕西省县域旅游规模效率的主导因素。

关键词: 旅游效率, 数据包络分析(DEA), 空间格局, 陕西省县域

Abstract:

The development of tourism in China in the last four decades builds China into the ranks of the world's tourism powers. At present, the tourism industry is facing an important task of improving the quality and efficiency in the critical period of transformation and development. Recent research efforts have noted the neglect of regional tourism efficiency studies at county scale. Little research has been done on the county-scale tourism efficiency in Northwest China. To expand our understanding of this topic, this paper focuses on the contributions of the spatial pattern and influencing factors on the tourism efficiency of counties. In this paper, the tourism efficiency and spatial pattern of 107 counties in Shaanxi province was measured based on data envelopment analysis and Python crawling technique. The results showed the following: (1) The number of counties in Shaanxi that have reached the effective overall tourism efficiency was relatively small. The counties with high tourism efficiency were mostly suburban counties. In terms of decomposition, the scale efficiency of county-level tourism in the province was generally higher than that of technical efficiency, which suggests that most counties in Shaanxi were still focusing on large-scale investment in tourism development, but neglect to enhance the capacity of conversing resources. (2) From the analysis of the three geographical units of Shaanxi, the counties with high tourism efficiency in the north area of Shaanxi were mainly concentrated along the Yellow River. Guanzhong area presents the spatial layout of "high in the west and low in the east part", as the counties reaching effective tourism efficiency mainly concentrated along the Longxian-Jingyang-Tongguan county axis. The counties with high tourism efficiency in southern Shaanxi are mostly located at the junction of prefectures and cities. Meanwhile, some counties in the west of Hanzhong bordering neighbor province achieved high tourism efficiency. (3) In the analysis of factors affecting tourism efficiency, the proportion of tourism income to GDP, population density and number of bus stations directly affected tourism overall efficiency and technical efficiency. Tourism resource endowment and population density were the main factors influencing the scale efficiency of county tourism. In addition, the density of highways had a significant influence on it as well. Finally, combined with the research results, this paper provides countermeasures and suggestions for the development of county-level tourism in Shaanxi: optimizing resource allocation and accelerating technological innovation in the region, propelling the differentiated development of tourism and highlighting the tourism characteristics of each county, strengthening exchanges and cooperation between counties and promoting the integration of tourism, culture and other related industries.

Key words: tourism efficiency, data envelopment analysis (DEA), spatial pattern, counties in Shaanxi province