The influence of neighbourhood environment on Airbnb: a geographically weighed regression analysis

Abstract

Sharing accommodation has emerged recently as a new business model in the accommodation sector. Due to the potential gentrification Airbnb might bring to an area, it is critical to understand the spatial patterns of sharing economy and its possible determinants. The neighbourhood environment has proven to be an important factor in the traditional hotel business, and whether it is the same for sharing accommodation is worth investigating. In this study, location data of 29,780 houses/apartments on Airbnb.com in London was collected. Using Ordinal Least Square and Geography Weighed Regression analysis, the spatial distribution features of Airbnb and its relationship with neighbourhood environment in London were explored. The results show that sharing accommodation is mainly located in the city centre and around tourist attractions. Neighbourhood elements such as Water, Vegetation Coverage, Art & Human Landscape, Travel & Transport, University, Nightlife Spot emerged as important factors influencing Airbnb. In addition, the distribution of Airbnb in London is spatially non-stationary, in some areas high Airbnb is associated with higher transportation accessibility, in other areas, high Airbnb is associated with more attractions or nightlife spots, suggesting that the role of different factors varies in different regions, proving Tobler’s first law of geography.

摘要：

共享住宿已经成为住宿业中的一种新型商业模式。由于共享住宿对某一地区可能产生高档化的潜在影响, 了解共享住宿的空间分布及其影响因素是至关重要的。周边环境因素已经被证明是影响传统酒店分布的重要因素, 而这些因素对共享住宿的空间分布是否起着同样的作用值得探究。本研究收集了爱彼迎网站上伦敦地区的29, 780个房源的位置数据, 并采用最小二乘法和地理加权回归方法研究了爱彼迎房源的空间分布特征及其与周边环境因素的关系。研究结果表明共享住宿主要集中于市中心及旅游景点周边区域, 周边环境因素（包括水、植被、人文艺术景点、交通、大学、夜生活点）是影响Airbnb空间分布的重要因素。另外, 伦敦爱彼迎房源的分布在空间上是非均匀的, 一些地区有较多的房源分布与该地区的交通发达程度有关, 其他地区较多的房源分布与该地区具有较多的景点和夜生活点有关, 这表明周边环境因素对共享住宿空间分布的作用因区域而不同, 验证了地理学第一定律。

Keywords:

• Sharing economy
• sharing accommodation
• spatial distribution
• Airbnb
• London
• neighbourhood environment

• 关键词：共享经济
• 共享住宿
• 空间分布
• 爱彼迎
• 伦敦
• 周边环境

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by National Nature Science Foundation of China (41571133; 4171530650; 71671038).

Notes on contributors

Feifei Xu

Feifei Xu, PhD, is a professor in Southeast University, China. She is also associated with the School of International Business, University of Lincoln, UK. Her main research interests include tourism geography, cross-cultural issues in tourism, as well as etourism.

Mingxing Hu

Minxing Hu, PhD, is a professor in the School of Architecture, Southeast University, China. His main research interests include GIS and urban planning.

Liqing La

Liqing La, is a master student in Southeast University. Her main research interest is on sharing economy and big data.

Jialing Wang

Jialing Wang, is a master student in Southeast University. Her main research interest includes the application of GIS in urban planning.

Chao Huang

Chao Huang, PhD, is a professor in the School of Economics and Management, Southeast University, China. His main research interest includes big data.