Spatio-temporal pattern of the city-level differences of tourism innovation in the Yangtze River Economic Belt

doi:10.3969/j.issn.1004-9479.2020.04.2019165

Abstract

Abstract:

City tourism technology innovation is an important driving force for the construction of the Yangtze River tourism belt. Taking the total amount of tourism science and technology patents in the 130 cities of the Yangtze River economic belt as the research index, the characteristics of spatial and temporal evolution of tourism technological innovation in the Yangtze River economic belt from 2000 to 2017 are analyzed. The research results show that: (1) There are significant and slow fluctuation characteristics, the differences of tourism technological innovation among the city agglomerations in the belt are Chengdu-Chongqing city agglomeration, the middle reaches of the Yangtze River city agglomeration and the Yangtze Delta city agglomeration in turn. (2) The city agglomeration development pattern is formed by the spatial distribution of the core and the edge of the city. The cities with strong innovation in tourism science and technology gather in the Suzhou and Xi Chang metropolitan area, the Hangzhou metropolitan area, the Ningbo metropolitan area and the provincial capital city. (3) The high level and low level clubs, the active middle and low level and the middle and high level clubs, the most probability of transfer between different types of tourism science and technology innovation differences between different cities, especially the number of upward transfer types increased by 11 in the period of 2010-2017, and the increase of city distribution mainly in Hangzhou metropolitan area and Hefei Metropolitan area, Wuhan metropolitan area, and Poyang Lake city group.

Key words: tourism innovation, patent application, spatio-temporal evolution, the Yangtze River Economic Belt

摘要：

城市旅游科技创新是长江旅游带建设的重要驱动力。以长江经济带130个城市旅游科技专利申请总量作为指标，分析2000—2017年长江经济带城市旅游科技创新差异的时空演变格局特征。发现：（1）总体呈现显著且缓慢上下波动的演变特征，带内城市群旅游科技创新差异大小依次是成渝城市群、长江中游城市群、长三角洲城市群。（2）空间分布形成“核心-边缘”的城市聚散发育格局，旅游科技创新较强的城市聚集于苏锡常都市圈、杭州都市圈、宁波都市圈及带内省会城市。（3）呈现锁定的高水平和低水平俱乐部，活跃的中低水平和中高水平俱乐部, 不同城市旅游科技创新差异类型之间发生转移的概率居多，尤其是2010—2017年期间向上转移类型的数量增加了11个，增加城市主要分布于杭州都市圈、合肥都市圈、武汉都市圈、环鄱阳湖城市群。

关键词: 旅游创新, 旅游科技专利申请, 时空演变, 长江经济带

Gang XIAO. Spatio-temporal pattern of the city-level differences of tourism innovation in the Yangtze River Economic Belt[J]. World Regional Studies, 2020, 29(4): 825-833.

肖刚. 长江经济带城市旅游科技创新差异的时空格局演变研究[J]. 世界地理研究, 2020, 29(4): 825-833.

Figures/Tables 7

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区域	省（市）	城市
长江经济带下游（47）	上海市（1）	上海
	江苏省（15）	南京、徐州、常州、扬州、无锡、泰州、南通、盐城、苏州、常熟、连云港、昆山、淮安、镇江、宿迁
	浙江省（15）	杭州、宁波、温州、瑞安、金华、台州、丽水、嘉兴、余姚、义乌、诸暨、衢州、湖州、舟山、绍兴
	安徽省（16）	合肥、芜湖、蚌埠、淮南、马鞍山、淮北、铜陵、安庆、黄山、阜阳、宿州、滁州、六安、宣城、池州、亳州
长江经济带中游（39）	江西省（11）	南昌、赣州、九江、上饶、宜春、吉安、抚州、新余、萍乡、景德镇、鹰潭
	湖北省（14）	武汉、黄石、十堰、荆州、宜昌、襄阳、鄂州、荆门、孝感、黄冈、咸宁、随州、恩施、仙桃
	湖南省（14）	长沙、株洲、湘潭、衡阳、邵阳、岳阳、常德、张家界、益阳、郴州、永州、怀化、娄底、湘西
长江经济带上游（44）	重庆市（1）	重庆
	四川省（21）	成都、自贡、攀枝花、泸州、德阳、绵阳、广元、遂宁、内江、乐山、南充、眉山、宜宾、雅安、广安、达州、彭洲、巴中、资阳、峨眉山、阿坝
	贵州省（9）	贵阳、遵义、毕节、六盘水、安顺、黔西南、黔东南、黔南、铜仁
	云南省（13）	昆明、昭通、曲靖、楚雄、玉溪、红河、文山、普洱、丽江、大理、迪庆、德宏、保山

区域	省（市）	城市
长江经济带下游（47）	上海市（1）	上海
	江苏省（15）	南京、徐州、常州、扬州、无锡、泰州、南通、盐城、苏州、常熟、连云港、昆山、淮安、镇江、宿迁
	浙江省（15）	杭州、宁波、温州、瑞安、金华、台州、丽水、嘉兴、余姚、义乌、诸暨、衢州、湖州、舟山、绍兴
	安徽省（16）	合肥、芜湖、蚌埠、淮南、马鞍山、淮北、铜陵、安庆、黄山、阜阳、宿州、滁州、六安、宣城、池州、亳州
长江经济带中游（39）	江西省（11）	南昌、赣州、九江、上饶、宜春、吉安、抚州、新余、萍乡、景德镇、鹰潭
	湖北省（14）	武汉、黄石、十堰、荆州、宜昌、襄阳、鄂州、荆门、孝感、黄冈、咸宁、随州、恩施、仙桃
	湖南省（14）	长沙、株洲、湘潭、衡阳、邵阳、岳阳、常德、张家界、益阳、郴州、永州、怀化、娄底、湘西
长江经济带上游（44）	重庆市（1）	重庆
	四川省（21）	成都、自贡、攀枝花、泸州、德阳、绵阳、广元、遂宁、内江、乐山、南充、眉山、宜宾、雅安、广安、达州、彭洲、巴中、资阳、峨眉山、阿坝
	贵州省（9）	贵阳、遵义、毕节、六盘水、安顺、黔西南、黔东南、黔南、铜仁
	云南省（13）	昆明、昭通、曲靖、楚雄、玉溪、红河、文山、普洱、丽江、大理、迪庆、德宏、保山

时间	t_i/t_i+1	n	1	2	3	4
2000—2017	1	1473	0.786	0.094	0.033	0.035
	2	256	0.569	0.172	0.094	0.124
	3	134	0.423	0.219	0.073	0.263
	4	347	0.105	0.102	0.071	0.631
2000—2009	1	825	0.797	0.111	0.047	0.047
	2	165	0.612	0.170	0.103	0.115
	3	97	0.458	0.219	0.073	0.260
	4	213	0.144	0.134	0.088	0.620
2009—2017	1	648	0.773	0.075	0.018	0.021
	2	91	0.500	0.176	0.078	0.137
	3	37	0.341	0.220	0.073	0.268
	4	134	0.054	0.060	0.048	0.645

时间	t_i/t_i+1	n	1	2	3	4
2000—2017	1	1473	0.786	0.094	0.033	0.035
	2	256	0.569	0.172	0.094	0.124
	3	134	0.423	0.219	0.073	0.263
	4	347	0.105	0.102	0.071	0.631
2000—2009	1	825	0.797	0.111	0.047	0.047
	2	165	0.612	0.170	0.103	0.115
	3	97	0.458	0.219	0.073	0.260
	4	213	0.144	0.134	0.088	0.620
2009—2017	1	648	0.773	0.075	0.018	0.021
	2	91	0.500	0.176	0.078	0.137
	3	37	0.341	0.220	0.073	0.268
	4	134	0.054	0.060	0.048	0.645

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