自然科学版
陕西师范大学学报(自然科学版)
资源与环境科学
我国入境游客消费水平空间结构及影响因素
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张广海*, 高俊
(中国海洋大学 管理学院, 山东 青岛 266100)
张广海,男,教授,博士生导师。E-mail:guanghaizh@163.com
摘要:
通过全局Moran′s I指数、局部Moran′s I指数和Moran散点图研究了中国31个省、自治区和直辖市(不含港澳台地区)间入境游客消费水平的空间集聚性和邻近省域间的空间溢出效应;建立了空间计量模型,研究了星级酒店业、景区游览业、旅游购物业、娱乐业、邮电业等对入境游客消费水平的影响。结果显示:我国入境游客消费水平存在正向的空间自相关性,且邻近省域间存在显著的空间溢出效应;入境游客消费水平的低低聚集区占比较大,广泛分布于西部地区,高高聚集区主要分布在东部沿海地区,呈现不合理的两极化分布;星级酒店业、旅游购物业、娱乐业对提高入境游客消费水平有正向的推动作用;而景区游览业和邮电业在我国入境旅游市场发展中存在着亟待解决的问题,需要加大对入境过夜游客在相关业态消费市场的开发。
关键词:
入境游客; 消费水平; 空间自相关; 影响因素; 空间计量模型
收稿日期:
2016-06-02
中图分类号:
F590
文献标识码:
A
文章编号:
1672-4291(2017)02-0096-08doi:10.15983/j.cnki.jsnu.2017.02.423
基金项目:
国家社会科学基金(12CGL059); 中国博士后科学基金(2015M580612)
Doi:
The spatial structure of inbound tourist level and influencing factors of China
ZHANG Guanghai*, GAO Jun
(College of Management, Ocean University of China, Qingdao 266100, Shandong, China)
Abstract:
Using the global Moran′s I index, the local Moran′s I index and Moran scatter plot, the spatial agglomeration of 31 provincial inbound tourist consumption level and spatial spillover benefits between adjacent area of China are studied. Using the spatial econometric method, the effects of the star-level hotel, scenic spots, shopping,entertainment industry and postal service industry on inbound tourist consumption level are estimated. The results showed that the inbound tourist consumption level has positive spatial correlation, and it has spatial spillover effect between neighboring areas.Low accumulation areas of inbound tourist consumption level accounted for larger proportion which are widely distributed in the western region, high accumulation regions are primarily distributed in the eastern coastal region, presenting the unreasonable distribution of polarization. The results suggest that star-level hotels, shopping, entertainment industry had positive roles in improving the consumption level of inbound tourist. However, scenic spots and the postal service industry had problems to be solved,and needs development in the tourist consumption market.
KeyWords:
inbound tourist; consumption level; spatial agglomeration; influencing factors; spatial econometrics