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作 者:许艳 陆林 周李 储小乐 胡璇 宋丹然 XU Yan;LU Lin;ZHOU Li;CHU Xiao-le;HU Xuan;SONG Dan-ran(School of Resource and Environment,Anqing Normal University,Anqing 246133,China;School of Geography and Tourism,Anhui Normal University,Wuhu 241000,China)
机构地区:[1]安庆师范大学资源环境学院,安徽安庆246133 [2]安徽师范大学地理与旅游学院,安徽芜湖241003
出 处:《安徽师范大学学报(自然科学版)》2019年第2期174-182,共9页Journal of Anhui Normal University(Natural Science)
基 金:国家自然科学基金重点项目(41230631);安徽省自然科学基金(1808085QD99);安徽省自然科学重点项目(KJ2017A371)
摘 要:基于艺龙网获取珠三角经济圈星级酒店的房价监测数据,结合实地调研,运用数理统计和空间插值法比较研究第117届(春季)和第118届(秋季)广交会对珠三角经济圈3005家星级酒店房价影响的时空分异特征。研究发现:(1)广交会举办地广州市的各类型星级酒店房价受广交会影响最为直接,监测时段内酒店房价涨幅呈现波动式交替增长下降态势,往往在广交会一期达到酒店房价最高峰值点。(2)广交会参会者的"特殊身份"使得五星级酒店房价波动曲线最为明显,整体表现出"东高西低"的空间分布格局。展会期间,珠三角经济圈酒店房价呈现明显的圈层结构,以广交会举办地广州市为中心表现出强烈的空间邻近效应。(3)广交会影响下的珠三角经济圈星级酒店房价波动受多种因素的共同作用,包括参会者需求规模和展会类型、酒店规模类型与服务质量、地理空间距离与时间成本、城市社会经济条件与政府宏观政策支持等。Based on Yilong Network,we obtain the monitoring data of the star hotel price in the Pearl River Delta Economic Circle.In combination with field research,we use mathematical statistics and spatial interpolation to compare the spatial and temporal characteristics of the impact of the price of 3005 star hotels in PRD during the 117th and 118th Canton Fair.The study finds:The price of various types of star-level hotels in Guangzhou,where the Canton Fair is held,is most directly affected by the Canton Fair.During the monitoring period,the hotel s price increase shows a wave of alternating growth and decline,and it often reaches the peak point of hotel prices in the first phase of the Canton Fair.Secondly,the“special status”of the participants makes the price fluctuation curve of the five-star hotel the most obvious,and the space division shows a special pattern characteristic,which is higher in the East and lower in the West.During the exhibition,hotel prices in PRD show an obvious ring structure,with Guangzhou as the center to show a strong spatial proximity effect.Finally,the fluctuation of hotel prices in the PRD under the influence of the Canton Fair is caused by a variety of factors,including the size of participants needs and exhibition types,hotel scales and service quality,spatial distance and time costs,urban economic conditions and government macro policy support.
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