地理科学进展 ›› 2020, Vol. 39 ›› Issue (10): 1698-1707.doi: 10.18306/dlkxjz.2020.10.009

• 研究论文 • 上一篇    下一篇

民宿空间分布的集聚模式与影响因素研究——基于杭州、湖州、恩施的比较

胡小芳(), 李小雅, 王天宇, 赵红敏, 杨铄, 邓磊, 李景旺   

  1. 华中农业大学,武汉 430070
  • 收稿日期:2019-10-21 修回日期:2020-04-07 出版日期:2020-10-28 发布日期:2020-10-27
  • 作者简介:胡小芳(1976— ),女,湖北仙桃人,博士,副教授,主要从事土地资源管理研究。E-mail: xf307@126.com
  • 基金资助:
    北京大学林肯城市发展与土地政策研究中心研究基金(2016001);中央高校基本科研业务费专项资金(2662016PY131);中央高校基本科研业务费专项资金(2662016PY055);国家级大学生创新创业训练计划(201910504135)

Spatial agglomeration pattern of homestay inn and influencing factorsbased on the comparison of Hangzhou, Huzhou, and Enshi cities

HU Xiaofang(), LI Xiaoya, WANG Tianyu, ZHAO Hongmin, YANG Shuo, DENG Lei, LI Jingwang   

  1. Huazhong Agricultural University, Wuhan 430070, China
  • Received:2019-10-21 Revised:2020-04-07 Online:2020-10-28 Published:2020-10-27
  • Supported by:
    Peking University-Lincoln Institute Center for Urban Development and Land Policy(2016001);Fundamental Research Funds for the Central Universities(2662016PY131);Fundamental Research Funds for the Central Universities(2662016PY055);National Training Program of Innovation and Entrepreneurship for Undergraduates(201910504135)

摘要:

近年来,民宿依托其个性化的服务以及温馨的住宿体验发展起来并走向成熟,其在空间上的集聚也推动着民宿产业向集群化和专业化发展。论文选取浙江省杭州市、湖州市和湖北省恩施州3个典型区域作为研究对象,基于途家网的民宿数据,运用全局自相关统计量和局域Getis-Ord Gi *指数分析三地民宿的集聚模式,并从区位、交通、旅游资源和区域品牌4个方面分析其影响因素。研究发现:① 杭州、湖州、恩施民宿空间分布均出现集聚状态,其中杭州最大的热点区域以市中心为圆心向周围扩散,杭州民宿是依托城市区位的集聚模式;湖州民宿的热点区域远离市中心且以莫干山为中心向四周扩散,湖州民宿是依托区域品牌的集聚模式;恩施民宿的热点区域由3个较小的热点区域构成,且均与恩施著名景点相连接,恩施民宿是依托自然景点的集聚模式。② 区位是城市民宿集聚的基础;区域品牌是民宿集聚的助推器;旅游资源是民宿集聚的早期动力;道路交通是民宿集聚和向外扩张的保障。研究结果为民宿的选址、空间优化布局和资源合理化配置提供有益的参考。

关键词: 民宿, 空间, 集聚, 影响因素

Abstract:

In recent years, homestay inn has developed and matured based on its personalized services and cozy accommodation experience. Its spatial agglomeration also promotes the homestay inn industry to grow in clusters and become specialized. This study chose Hangzhou City in Zhejiang Province, Huzhou City in Zhejiang Province, and Enshi City in Hubei Province, which are the typical areas of the homestay inn industry, as cases. Based on the homestay inn data of Tujia.com, this study used global spatial association indicators and Getis-Ord Gi * index to explore the agglomeration pattern and influencing factors of the three areas. The spatial distributions of homestay inn in Hangzhou, Huzhou, and Enshi Cities all show an agglomeration pattern, and the largest hot spot region of Hangzhou spreads around the city center. The spatial agglomeration pattern of homestay inn of Hangzhou is based on locations within the city. The hot spot region of homestay inn in Huzhou is far away from the city center and spreads around the Mogan Mountains. The spatial agglomeration pattern of homestay inn of Huzhou is based on the regional brand. The hot spot region of Enshi homestay inn consists of three small hot spots, which are all connected to the scenic spots. The spatial agglomeration pattern of homestay inn of Enshi is based on the scenic spots. Through the analysis of location, transportation, tourism resources, and regional brands of the three areas, the study showed that location is the basis of the agglomeration of homestay inn in cities. Regional brand is a booster to promote the agglomeration of homestay inn. Tourism resources are the early motivation of clustering for homestay inn. Road transportation is a guarantee for the clustering and expansion of the homestay inn. The conclusions provide a useful reference for choosing reasonable locations for homestay inn and allocating resources rationally.

Key words: homestay inn, space, agglomeration, influencing factors