摘要
港澳台地区是中国内地最大的入境旅游客源市场,认识入境港澳台游客空间分布格局,准确把握游客流量流向的空间位移和游客需求,对于拓展入境客源市场具有非常重要的意义。本文借用游客密度指数工具,分析入境港澳台游客空间分布格局及历史变化。研究表明,东部沿海省份始终是入境港澳台游客的主要集中区域,而中西部省份长期处于弱势,在分布上呈现出由东向西、由南向北递减的阶梯特征,从1994~2010年的密度演变来看,这种不平衡的特征开始呈现缓慢收敛的特征。
As known,the regions of Hongkong,Macao and Taiwan（HMT）are always the biggest andsteadiest source markets for entry tourism,tourists from these regions play an important role in entry tourism of China.Studying on the spatial distribution and evolutional process of the tourists from HMT,itcan help us understand the spatial transferring characteristics,the changes and development trend of Tourism Flow more accurately,and this also can be of great significance for developing the strategy for China＇s entry tourism and for conforming the tourism source markets scientifically and rationally.Based on the data of the entry tourists of China mainland from HTM received by aU China Mainland＇s 3 1 provinces,cities directly under the jurisdiction of the State Council and autonomous regions during 1994 and 2010,we use the 16 years＇sequential data in the 31 units to study the spatial distribution pattern andevolution of the entry tourists from HMT,and by overlaying the administration map of China,we＇ve gotthe maps of the spatial distribution pattern and the changes of the entry tourists from HMT.The resultsindicate that the spatial distribution of the entry tourists from HMT in the.past 15 years has been influenced by the degree of economic links greatly,and they are distributed concentratedly,mainly in Guangdong Province,Southeastern China＇s coastal areas and Eastern China＇s economicaUy developed areas,while the central and western parts of China receiving much less entry tourists from HMT,and the discrepancies between different provinces（including their peers）are big with the tendency of escalating their discreDancies.
出处
《特区经济》
2012年第12期129-132,共4页
Special Zone Economy
基金
教育部人文社会科学研究基金项目"经济转型与文化调适:民间传统手工技艺生存与发展"(项目编号:10JC850034)资助
关键词
港澳台游客
入境旅游
游客密度指数
空间格局变化
tourists from Hongkong
Macao and Taiwan
entry tourism
spatial pattern
evolution
