| 摘要: |
| 目的］乡村旅游是现代旅游业发展的重要组成部分，县域单元是乡村旅游业的主要空间载体。以福建省84个县域单元为研究对象，在参考旅游竞争力相关研究的基础上，构建乡村旅游竞争力评价指标体系。［方法］采用主成分分析法进行定量分析，并在此基础上利用Geoda软件进行空间可视化和探索性空间分析。［结果］研究显示：福建省县域乡村旅游竞争力空间近邻效应十分明显，竞争力水平相似的县在空间上呈集聚分布态势； 乡村旅游竞争力空间分布极不平衡，沿海地区明显高于内陆地区，二元结构明显； 市场潜力竞争力空间分布与综合竞争力空间分布高度耦合，说明市场区位条件在乡村旅游开发中的作用显著； 自身开发能力、农业资源特色、人文旅游资源、旅游知名度竞争力的优势区和劣势区呈零星分散分布。［结论］如何扬长避短，以县域为单元打造各具特色的乡村旅游产业集群、塑造乡村旅游整体品牌和客源市场的共享是提升整体竞争力的有效途径。 |
| 关键词: 乡村旅游竞争力 主成分分析 探索性空间分析 福建省 |
| DOI：10.7621/cjarrp.1005-9121.20170328 |
| 分类号: |
| 基金项目: |
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| RESEARCH ON COUNTY RURAL TOURISM COMPETITIVE ABILITY IN FUJIAN PROVINCE |
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Zhao Wei, Li Zirong, Li Ruirui, Fu Jing
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College of Resource and Environment, Quanzhou Normal University, Quanzhou, Fujian 362000, China
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| Abstract: |
| The rural tourism is an important part of modern tourism development, the county unit is the main carrier of rural tourism. Taking 84 counties (including county, county-level cities, municipal districts) in Fujian province as the research object, this paper built a rural tourism competitiveness evaluation index system using principal component analysis and quantitative analysis, and analyzed the spatial visualization and exploratory using space Geoda software. The results showed that the space neighborhood effect of the rural tourism competitiveness in Fujian was very obvious. The rural tourism competitiveness spatial distribution was extremely uneven, especially in the inland and coastal areas. The market competitiveness was highly correlated with the comprehensive competitiveness, indicating that the market conditions played an important role in the regional development of rural tourism. The areas with the development ability, agriculture resources characteristics, cultural tourism resources and tourism publicity distributed sporadically. The effective approaches to improve rural tourism competitiveness were to build characteristic tourism cluster, shape rural tourism brand, and share the customer market. |
| Key words: rural tourism competitive ability principal component analysis exploratory spatial analysis Fujian province |
