摘要
以大陆31个地区2000—2012年入境旅游产业发展数据为例,综合利用产业集中指数、区位熵、偏离—份额分析等方法,揭示入境旅游产业结构时空格局演化特征,进一步对各产业部门进行类型划分。结果表明:2000—2012年大陆入境旅游产业各部门均获得一定程度发展,长途交通、购物、住宿部门在入境旅游产业中占据较大份额。入境旅游产业集中指数及专业化程度具有明显的地带特征。结构性因素与竞争性因素对入境旅游经济增长的贡献,具有显著的地带效应,结构因素对东部地区入境旅游经济的贡献较大,对中部地区的贡献较小,2000—2012年中国入境旅游经济增长中"结构红利"现象明显。根据动态SSM分析结果,可将入境旅游各产业划分为4种类型,交通、游览、购物总体上属于结构驱动型产业,住宿、餐饮、邮电通信属于竞争力驱动型产业。
By taking the tourism industrial developing data in 31 provinces from 2000 to 2012 as an example,comprehensively using the methods of industrial concentration index, location entropy and shift-share analysis, it reveals the time-space evolution characteristic of inbound tourism industrial structure, and then divides types of various industrial sectors. The results show that： every sector of inbound tourism industrial structure has made a certain degree of development in Chinese mainland from 2000 to 2012, long distance transportation, shopping, and accommodation sector has occupied a larger share in inbound tourism industry. The industrial concentration index and specialization degree of inbound tourism industry has obvious regional characteristic. The contribution to the inbound tourism economic growth of structural factors and competitive factors has a significant regional effect, the structural factors has a larger contribution to the inbound tourism economy in eastern area, however, a smaller contribution in the central region. There is an obvious phenomenon of structure bonus in the increasing of inbound tourism economy. According the analysis results of dynamic SSM, it can divide the inbound tourism industry into 4 types, generally speaking, transportation,sightseeing, shopping belong to a structure- driven industry, while the accommodation, catering, posts and telecommunications belong to compete-driven industry.
出处
《经济地理》
CSSCI
北大核心
2016年第3期179-185,共7页
Economic Geography
基金
教育部人文社会科学青年基金项目(15YJC790018)
安徽省教育厅人文社会科学重点项目(SK2015A235)
安徽大学青年骨干教师培养项目(J01005141)
安徽大学校学术与技术带头人引进工程(J10117700056)
关键词
入境旅游
产业结构
时空格局
偏离—份额分析
中国
inbound tourism
industrial structure
time-space pattern
shift-share analysis
China
