Airbnb供应在洛杉矶的空间分布

IF 1.4 Q3 HOSPITALITY, LEISURE, SPORT & TOURISM
Zhihua Zhang, Rachel J.C. Fu
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引用次数: 2

摘要

随着Airbnb越来越受欢迎,人们进行了很多研究,但对Airbnb的空间模式的关注有限,这可以为Airbnb供应的地理物流提供见解。为了填补这一空白,本研究调查了2014年至2019年洛杉矶市Airbnb供应的空间格局。本研究结合探索性空间数据分析(ESDA),利用空间回归模型探讨了2019年Airbnb供应空间格局的决定因素。空间自相关分析结果表明,Airbnb供应在洛杉矶的空间分布呈正聚集性,且随时间的推移呈现地理物流趋势。Airbnb供应的分布具有明显的中心-外围格局。高-高(HH)集群主要集中在洛杉矶的中心地区,而低-低(LL)集群主要分布在周边地区。此外,通过空间回归分析,确定了影响Airbnb供应空间分布的几个决定因素,如居住人口、住房单元、收入、租金、兴趣点(POI)和到好莱坞的距离。下文将讨论调查结果的进一步影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The spatial distribution of Airbnb supply in Los Angeles
Following the growing popularity of Airbnb, much research has been conducted, while limited attention has been devoted to the spatial patterns of Airbnb, which can provide insights into the geographic logistics of Airbnb supply. To fill this gap, this study investigates the spatial patterns of Airbnb supply in the city of Los Angeles during the years 2014 to 2019. This study integrates Exploratory Spatial Data Analysis (ESDA) and explores the determinants of spatial patterns of Airbnb supply in 2019 with spatial regression models. The results of the spatial autocorrelation analysis show that the spatial distribution of Airbnb supply in Los Angeles is positively clustered and shows a geographical logistical trend over time. The distribution of Airbnb supply has a clear center-periphery pattern. The high-high (HH) clusters are concentrated in the central areas of Los Angeles, while low-low (LL) clusters predominate in the peripheral areas. In addition, with spatial regression analysis, several determinants affecting the spatial distribution of Airbnb supply are identified such as resident population, housing units, income, rent, point of interest (POI), and the distance to Hollywood. Further implications of the findings are discussed below.
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来源期刊
Tourism Analysis
Tourism Analysis HOSPITALITY, LEISURE, SPORT & TOURISM-
CiteScore
2.50
自引率
11.10%
发文量
42
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