文献类型：期刊文献

英文题名：Beyond Space: Unraveling Spatial Pattern and Determinants of Urban Commercial Therapeutic Venues in Beijing, China

作者：Zhao, Mingyu[1];Huang, Xingling[2];Liu, Jianguo[3]

第一作者：Zhao, Mingyu

通讯作者：Huang, XL[1]

机构：[1]Northwest Univ, Sch Econ & Management, Xian 710127, Peoples R China;[2]Nankai Univ, Coll Tourism & Serv Management, Tianjin 300071, Peoples R China;[3]Beijing Union Univ, Tourism Coll, Beijing 100101, Peoples R China

第一机构：Northwest Univ, Sch Econ & Management, Xian 710127, Peoples R China

通讯机构：[1]corresponding author), Nankai Univ, Coll Tourism & Serv Management, Tianjin 300071, Peoples R China.

年份：2026

卷号：36

期号：6

起止页码：974-987

外文期刊名：CHINESE GEOGRAPHICAL SCIENCE

收录：;Scopus(收录号：2-s2.0-105042452668);WOS:【SCI-EXPANDED(收录号:WOS:001799840800009)】；

基金：Foundation item: Under the auspices of National Natural Science Foundation of China (No. 41771131)

语种：英文

外文关键词：commercial therapeutic venues; spatial differentiation; driving factors; Geodetector; Beijing, China

摘要：As mental health needs rise and wellness consumption patterns evolve, commercial therapeutic venues have emerged as a novel component of urban health infrastructure in rapidly urbanizing China. This study investigated the spatial differentiation and driving mechanisms of such venues in Beijing, China, using point-of-interest (POI) data collected from Baidu Maps in June 2025. Spatial patterns were analyzed through Ripley's K function, kernel density estimation and hot-cold spot detection in ArcGIS. The Geodetector model was employed to quantify the individual and interactive effects of socio-economic and environmental factors. The results reveal four key findings: 1) all categories of commercial therapeutic venues exhibit significant spatial clustering, with agglomeration intensity varying across spatial scales and venue types. 2) A polycentric spatial structure is evident: body-oriented venues concentrate in dense urban cores, while mind-immersive and interaction-oriented venues expand into peripheral development zones. 3) Hotspots are primarily located in central and expansion districts, whereas coldspots are found in ecologically protected areas. 4) Subway stations, bus stops, population density, nighttime light intensity, mixed-use residential buildings, cultural facilities, vegetation index are major influencing factors, with the interaction between subway stations and cultural facilities significantly enhancing explanatory power. This study proposes an integrated analytical framework that combines Pointof Interest (POI) big data with spatial interaction diagnostics. The findings provide actionable insights for equitable, health-oriented urban planning, supporting sustainable development agendas such as Healthy Cities and the Healthy China 2030 initiative.