摘要
探究旅游环境系统服务价值的时空分异及影响因素对于科学评估旅游环境系统服务价值,实现旅游业的可持续发展具有重要意义。文章界定旅游环境系统服务价值的内涵,以我国31个省域为研究对象,从经济、生态和社会三个层面构建省域旅游环境系统服务价值指标体系,采用熵权TOPSIS法和空间自相关法对31个省域的旅游环境系统服务价值进行测度和时空分异特征探究,通过地理探测器和地理加权回归模型分析其影响因素。结果表明:(1)2012—2019年,31个省域旅游环境系统服务价值均值在时间层面总体呈上升趋势,2020年因新冠疫情出现轻微下降,2021年有所回升;空间层面上,东、中、西三大区域空间格局差异显著,年均值东部>中部>西部。(2)31个省域旅游环境系统服务价值的全局莫兰指数呈现下降—上升—下降—上升—平稳的小幅波动趋势,存在空间正向集聚效应,且局部自相关集聚模式变化较大。(3)对外经济贸易水平、政府扶持力度和科技投入对旅游环境系统服务价值均为正向影响,高等教育规模呈负向影响,对外经济贸易水平的影响强度由北向南递增,政府扶持力度和高等教育规模的影响强度由西北向东南递增,科技投入的影响强度由西向东递减。
Exploring the spatial-temporal differentiation and influencing factors of the service value of the tourism environment system is of great significance for scientifically evaluating the service value of the tourism environment system and achieving sustainable development of the tourism industry.The article defines the connotation of the service value of the tourism environment system,and takes 31 provinces in China as the research object to construct an indicator system of provincial service value of tourism environment system from the three levels of economy,ecology,and society.The entropy weighted TOPSIS method and spatial autocorrelation method are used to measure the service value of the tourism environment system in 31 provinces and explore the spatial-temporal differentiation characteristics.The influencing factors are analyzed through geographical detector and geographic weighted regression model.The results show that:(1)From 2012 to 2019,the average service value of tourism environment system in 31 provinces showed an overall upward trend at the temporal level,with a slight decline in 2020 due to the COVID-19,and a rebound in 2021;at the spatial level,there is a significant difference in the spatial pattern of the three major regions,with an average annual value of the east>the center>the west.(2)The global Moran’s I of the service value of the tourism environment system in 31 provinces shows a small fluctuation trend of“decreasing-rising-decreasing-rising-stable”,with a spatial positive agglomeration effect and significant changes in local autocorrelation agglomeration patterns.(3)The level of foreign economic trade,government support and scientific and technological inputs have a positive impact on the service value of tourism environment system,and the scale of higher education has a negative impact.The influence intensity of foreign economic trade increases from the north to the south.The influence strength of government support and the scale of higher education increases from the northwest to the southeast.The influence strength of science and technology investment decreases from west to east.
作者
杨秀平
解西凤
YANG Xiuping;XIE Xifeng(School of Economics and Management,Lanzhou University of Technology,Lanzhou 730050,Gansu,China)
出处
《国土资源科技管理》
2024年第4期1-17,共17页
Scientific and Technological Management of Land and Resources
基金
国家自然科学基金项目(41961020)
教育部“春晖计划”合作科研项目(GS2019002)
甘肃省哲学社会科学规划项目(2023YB015)
兰州市社会科学规划项目(23-B33)。
关键词
旅游环境系统服务价值
熵权TOPSIS法
空间自相关
地理加权回归模型
service value of tourism environment system
entropy weight TOPSIS method
spatial autocorrelation
geographically weighted regression models