中国旅游产业组织的时空耦合关系及影响因素

doi:10.11821/dlxb202304012

Abstract

Abstract:

Against the background of the industrial transformation and upgrading, the coupling coordination concerning the scale, structure, and efficiency of the tourism industry is conducive to rationally optimizing its productivity, quality, and efficiency. There is great theoretical and practical significance in understanding the evolution characteristics and its factors influencing the high-quality development of the regional tourism industry. This study constructed an analysis framework regarding the coupling coordination relationship among scale, structure, and efficiency. The spatiotemporal dynamics characteristics and factors influencing the coupling coordination of scale, structure, and efficiency in China's tourism industry were studied from 2011 to 2019. The methods used to achieve this included the modified coupling coordination model, the Local Indicators of Spatial Auto-correlation (LISA) time path, spatiotemporal transition, and spatiotemporal weighted regression. The results show that: (1) The level of coupling coordination of the scale, structure, and efficiency of tourism industry in China showed a significant increasing trend, with the ranking of the regions in terms of this level being Easter Area> Central Area> Northeastern Area > Western Area. Moreover, a trend of a gradual increase in spatial diffusion was also evident. (2) There was an overall small range of fluctuation of local spatial structure and spatial dependence within the level of coupling coordination of scale, structure, and efficiency of tourism industry in China, whereas there was strong spatial integration. In addition, the structure of local spatial correlation was relatively stable and there were obvious transfer inertia and path dependence, particularly in the Northeastern and Western Areas. (3) Scientific and technological innovation, urbanization, and transportation facilities have all had significant positive impacts on the level of coupling coordination of the scale, structure, and efficiency of tourism industry in China. Furthermore, government regulation and industrial structure will play an increasingly important role in promoting the Central and Western Areas, while human capital will have a strong positive impact on the Eastern Area.

Key words: tourism industry scale, tourism industry, tourism industry efficiency, coupling coordination, spatiotemporal transition, driving factors

WANG Zhaofeng, XIE Jialiang. Spatiotemporal coupling relationship and influencing factors of China's tourism industry organization[J].Acta Geographica Sinica, 2023, 78(4): 961-979.

Figures/Tables 11

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References 43

[1]	Liu Ning, Song Qiuyue, Hou Jiajia, et al. Evolution of tourism industrial structure and spatial network in China. Geography and Geo-Information Science, 2020, 36(5): 119-127.
	[刘宁, 宋秋月, 侯佳佳, 等. 中国旅游产业结构变迁及空间网络演进. 地理与地理信息科学, 2020, 36(5): 119-127.]
[2]	Zhao Songsong, Wang Zhaofeng. Spatial and temporal dynamic evolution and coupling relationship of regional tourism development scale and efficiency: A case study of 14 cities and municipalities in Hunan province. Resources and Environment in the Yangtze Basin, 2019, 28(10): 2386-2396.
	[赵松松, 王兆峰. 区域旅游发展规模与效率时空动态演化及耦合研究: 以湖南省14地市(州)为例. 长江流域资源与环境, 2019, 28(10): 2386-2396.]
[3]	Liu Chunji, Feng Xuegang, Gao Jing. Changes in the structure of the tourism industry and their effect on the growth of the tourism economy in China. Tourism Tribune, 2014, 29(8): 37-49.
	[刘春济, 冯学钢, 高静. 中国旅游产业结构变迁对旅游经济增长的影响. 旅游学刊, 2014, 29(8): 37-49.]
[4]	Fang Shimin, Huang Yan. Spatio-temporal evolutions and coordination of tourism efficiency and scale in the Yangtze River Economic Belt. Acta Geographica Sinica, 2020, 75(8): 1757-1772. doi: 10.11821/dlxb202008014
	[方世敏, 黄琰. 长江经济带旅游效率与规模的时空演化及耦合协调. 地理学报, 2020, 75(8): 1757-1772.] doi: 10.11821/dlxb202008014
[5]	Chenery. Comparative Study on Industrialization and Economic Growth. Wu Qi, Wang Songbao, trans. Shanghai: Shanghai Sumerian Press, 1989: 59.
	[钱纳里. 工业化和经济增长的比较研究. 吴奇, 王松宝, 译. 上海: 三联书店上海分店, 1989: 59.]
[6]	Rostow. The Stages of Economic Growth. Guo Xibao, Wang Songmao, trans. Beijing: China Social Science Press, 2001: 54.
	[罗斯托. 经济增长的阶段. 郭熙保, 王松茂, 译. 北京: 中国社会科学出版社, 2001: 54.]
[7]	Li Ruzi, Liu Yaobin, Xie Dejin. Evolution of economic efficiency and its influencing factors in the industrial structure changes in China. Acta Geographica Sinica, 2017, 72(12): 2179-2198. doi: 10.11821/dlxb201712005
	[李汝资, 刘耀彬, 谢德金. 中国产业结构变迁中的经济效率演进及影响因素. 地理学报, 2017, 72(12): 2179-2198.] doi: 10.11821/dlxb201712005
[8]	Cuccia T, Guccio C, Rizzo I. The effects of UNESCO World Heritage List inscription on tourism destinations performance in Italian regions. Economic Modelling, 2016, 53: 494-508. doi: 10.1016/j.econmod.2015.10.049
[9]	Yan Youbing, He Wenjuan. Analysis on the time-space evolution of the domestic tourism flow to China. Economic Geography, 2013, 33(4): 179-185.
	[阎友兵, 贺文娟. 国内旅游流流量与流质的时空演化分析. 经济地理, 2013, 33(4): 179-185.]
[10]	Tang R. Trade facilitation promoted the inbound tourism efficiency in Japan. Tourism Management Perspectives, 2021, 38: 100805. DOI: 10.1016/j.tmp.2021.100805. doi: 10.1016/j.tmp.2021.100805
[11]	Corne A. Benchmarking and tourism efficiency in France. Tourism Management, 2015, 51: 91-95. doi: 10.1016/j.tourman.2015.05.006
[12]	Kim W, Jun H M, Walker M, et al. Evaluating the perceived social impacts of hosting large-scale sport tourism events: Scale development and validation. Tourism Management, 2015, 48: 21-32. doi: 10.1016/j.tourman.2014.10.015
[13]	Wang Zhaofeng, Zhao Songsong. Temporal and spatial dynamic evolution and influencing factors of tourism efficiency in Hunan Province based on DEA-Malmquist model. Resources and Environment in the Yangtze Basin, 2019, 28(8): 1886-1897.
	[王兆峰, 赵松松. 基于DEA-Malmquist模型的湖南省旅游产业效率时空动态演化及影响因素. 长江流域资源与环境, 2019, 28(8): 1886-1897.]
[14]	Li Qiuyu, Zhu Linqi, Wang Jiyu. Coordination degree among the tourism-economy-society-ecology system of Jilin Province under the background of all-for-one tourism. Scientia Geographica Sinica, 2020, 40(6): 948-955. doi: 10.13249/j.cnki.sgs.2020.06.010
	[李秋雨, 朱麟奇, 王吉玉. 全域旅游背景下吉林省旅游业—经济—社会—生态环境协调性研究. 地理科学, 2020, 40(6): 948-955.] doi: 10.13249/j.cnki.sgs.2020.06.010
[15]	Xiong Jianxin, Wang Wenhui, He Saihua, et al. Spatio-temporal pattern and influencing factor of coupling coordination of tourism urbanization system in the Dongting Lake Region. Scientia Geographica Sinica, 2020, 40(9): 1532-1542. doi: 10.13249/j.cnki.sgs.2020.09.015
	[熊建新, 王文辉, 贺赛花, 等. 洞庭湖区旅游城镇化系统耦合协调性时空格局及影响因素. 地理科学, 2020, 40(9): 1532-1542.] doi: 10.13249/j.cnki.sgs.2020.09.015
[16]	Zhao Shuhong, Bai Meng, Ruan Mengzhi, et al. Spatio-temporal evolution characteristics and obstacle factors of coordinated development of tourism resources and ecological security in Yunnan Province. Scientia Geographica Sinica, 2021, 41(3): 493-503. doi: 10.13249/j.cnki.sgs.2021.03.014
	[赵书虹, 白梦, 阮梦枝, 等. 云南省旅游资源与生态安全协调发展的时空演化特征及障碍因子分析. 地理科学, 2021, 41(3): 493-503.] doi: 10.13249/j.cnki.sgs.2021.03.014
[17]	Wang Zhaofeng, Du Yaoyao. A study on the coupling of traffic-tourism industry-ecological environment in the middle of the Yangtze River. Resources and Environment in the Yangtze Basin, 2020, 29(9): 1910-1921.
	[王兆峰, 杜瑶瑶. 长江中游城市群交通—旅游产业—生态环境的耦合协调评价研究. 长江流域资源与环境, 2020, 29(9): 1910-1921.]
[18]	Zhu Linqi, Li Qiuyu, Liu Jisheng. Coordination relationship between tourism development and regional development with improvement of people's livelihood in China. Scientia Geographica Sinica, 2020, 40(8): 1328-1335. doi: 10.13249/j.cnki.sgs.2020.08.012
	[朱麟奇, 李秋雨, 刘继生. 中国旅游业与地区发展及民生改善协调关系研究. 地理科学, 2020, 40(8): 1328-1335.] doi: 10.13249/j.cnki.sgs.2020.08.012
[19]	Liu Anle, Yang Chengyue, Ming Qingzhong, et al. Spatial-temporal coordination and driving forces of provincial culture industry and tourism industry in China. Economic Geography, 2020, 40(6): 203-213.
	[刘安乐, 杨承玥, 明庆忠, 等. 中国文化产业与旅游产业协调态势及其驱动力. 经济地理, 2020, 40(6): 203-213.]
[20]	Huang Rui, Wang Kun, Huang Zhenfang, et al. Spatio-temporal dynamics and coupling relationship of regional tourism development pattern from the perspective of performance: A case study of Pan-Yangtze River Delta. Geographical Research, 2018, 37(5): 995-1008. doi: 10.11821/dlyj201805011
	[黄睿, 王坤, 黄震方, 等. 绩效视角下区域旅游发展格局的时空动态及耦合关系: 以泛长江三角洲为例. 地理研究, 2018, 37(5): 995-1008.] doi: 10.11821/dlyj201805011
[21]	Fu Bojie. Geography: From knowledge, science to decision making support. Acta Geographica Sinica, 2017, 72(11): 1923-1932. doi: 10.11821/dlxb201711001
	[傅伯杰. 地理学: 从知识、科学到决策. 地理学报, 2017, 72(11): 1923-1932.] doi: 10.11821/dlxb201711001
[22]	Sheng Yanchao. On the evolution of the optimization of tourism industrial structure to the contribution of economic growth of regional tourism. Tourism Tribune, 2012, 27(10): 11-19.
	[生延超. 旅游产业结构优化对区域旅游经济增长贡献的演变. 旅游学刊, 2012, 27(10): 11-19.]
[23]	Zhao Lei, Tang Chengcai. China's tourism industry, industrial structure and economic growth. Resources Science, 2017, 39(10): 1918-1929.
	[赵磊, 唐承财. 产业结构变迁、旅游业与经济增长: 来自中国的经验证据. 资源科学, 2017, 39(10): 1918-1929.] doi: 10.18402/resci.2017.10.11
[24]	Tong Yun, Ma yong, Liu Jun. Does the inbound tourism increase the city's green total factor productivity? Based on nonlinear perspective. Tourism Tribune, 2021, 36(9): 120-133.
	[童昀, 马勇, 刘军. 入境旅游提升了城市绿色全要素生产率吗? 基于非线性视角. 旅游学刊, 2021, 36(9): 120-133.]
[25]	Liu Yingji, Han Yuanjun. Factor structure, institutional environment and high-quality development of the tourism economy in China. Tourism Tribune, 2020, 35(3): 28-38.
	[刘英基, 韩元军. 要素结构变动、制度环境与旅游经济高质量发展. 旅游学刊, 2020, 35(3): 28-38.]
[26]	Liu Jia, An Keke. Departmental contribution and driving forces analysis of tourism industry structure optimization in Shandong Province. Geography and Geo-Information Science, 2019, 35(3): 105-111.
	[刘佳, 安珂珂. 山东省旅游产业结构优化的部门贡献与动能分析. 地理与地理信息科学, 2019, 35(3): 105-111.]
[27]	Wang Shujia, Kong Wei, Ren Liang, et al. Research on misuses and modification of coupling coordination degree model in China. Journal of Natural Resources, 2021, 36(3): 793-810. doi: 10.31497/zrzyxb.20210319
	[王淑佳, 孔伟, 任亮, 等. 国内耦合协调度模型的误区及修正. 自然资源学报, 2021, 36(3): 793-810.] doi: 10.31497/zrzyxb.20210319
[28]	Getis A, Aldstadt J. Constructing the spatial weights matrix using a local statistic. Geographical Analysis, 2004, 36(2): 90-104. doi: 10.1111/gean.2004.36.issue-2
[29]	Wang Shaojian, Gao Shuang, Huang Yongyuan, et al. Spatio-temporal evolution and trend prediction of urban carbon emission performance in China based on super-efficiency SBM model. Acta Geographica Sinica, 2020, 75(6): 1316-1330. doi: 10.11821/dlxb202006016
	[王少剑, 高爽, 黄永源, 等. 基于超效率SBM模型的中国城市碳排放绩效时空演变格局及预测. 地理学报, 2020, 75(6): 1316-1330.] doi: 10.11821/dlxb202006016
[30]	Rey S J. Spatial empirics for economic growth and convergence. Geographical Analysis, 2010, 33(3): 195-214. doi: 10.1111/gean.2001.33.issue-3
[31]	Rey S J, Janikas M V. STARS: Space-time analysis of regional systems. Geographical Analysis, 2006, 38(1): 67-86. doi: 10.1111/gean.2006.38.issue-1
[32]	Wang Haijun, Zhang Bin, Liu Yaolin, et al. Multi-dimensional analysis of urban expansion patterns and their driving forces based on the center of gravity-GTWR model: A case study of the Beijing-Tianjin-Hebei urban agglomeration. Acta Geographica Sinica, 2018, 73(6): 1076-1092. doi: 10.11821/dlxb201806007
	[王海军, 张彬, 刘耀林, 等. 基于重心-GTWR模型的京津冀城市群城镇扩展格局与驱动力多维解析. 地理学报, 2018, 73(6): 1076-1092.] doi: 10.11821/dlxb201806007
[33]	Qin Weishan, Zhang Yifeng, Li Shitai. Study on the spatio-temporal evolution of coastal city tourism of China. Geographical Research, 2014, 33(10): 1956-1965. doi: 10.11821/dlyj201410015
	[秦伟山, 张义丰, 李世泰. 中国东部沿海城市旅游发展的时空演变. 地理研究, 2014, 33(10): 1956-1965.] doi: 10.11821/dlyj201410015
[34]	Weng Gangmin, Li Lingyan. The coupling coordination degree and spatial correlation analysis on integrational development of tourism industry and cultural industry in China. Economic Geography, 2016, 36(1): 178-185.
	[翁钢民, 李凌雁. 中国旅游与文化产业融合发展的耦合协调度及空间相关分析. 经济地理, 2016, 36(1): 178-185.]
[35]	Liu Jia, Song Qiuyue. Space network structure and formation mechanism of green innovation efficiency of tourism industry in China. China Population, Resources and Environment, 2018, 28(8): 127-137.
	[刘佳, 宋秋月. 中国旅游产业绿色创新效率的空间网络结构与形成机制. 中国人口·资源与环境, 2018, 28(8): 127-137.]
[36]	Fang Yelin, Huang Zhenfang, Wang Fang, et al. Spatiotemporal evolution of provincial tourism efficiency and its club convergence in the Chinese mainland. Progress in Geography, 2018, 37(10): 1392-1404. doi: 10.18306/dlkxjz.2018.10.009
	[方叶林, 黄震方, 王芳, 等. 中国大陆省际旅游效率时空演化及其俱乐部趋同研究. 地理科学进展, 2018, 37(10): 1392-1404.] doi: 10.18306/dlkxjz.2018.10.009
[37]	Wang Zhaofeng, Liu Qingfang. The evolution and influencing factors of spatial network structure of China's provincial tourism efficiency. Scientia Geographica Sinica, 2021, 41(3): 397-406. doi: 10.13249/j.cnki.sgs.2021.03.004
	[王兆峰, 刘庆芳. 中国省域旅游效率空间网络结构演化及其影响因素. 地理科学, 2021, 41(3): 397-406.] doi: 10.13249/j.cnki.sgs.2021.03.004
[38]	Sheng Yanchao, Liu Qing. Spatial difference of Human capital promoting regional tourism economic efficiency: Empirical research based on "Hu Line". Scientia Geographica Sinica, 2020, 40(10): 1710-1719. doi: 10.13249/j.cnki.sgs.2020.10.015
	[生延超, 刘晴. 人力资本促进区域旅游经济效率的空间差异研究. 地理科学, 2020, 40(10): 1710-1719.] doi: 10.13249/j.cnki.sgs.2020.10.015
[39]	Fang Yuanping, Bi Doudou, Chen Hongyang, et al. Spatial effects of knowledge-intensive business services clustering on tourism innovation in urban aggolomerations. Acta Geographica Sinica, 2021, 76(6): 1521-1536. doi: 10.11821/dlxb202106014
	[方远平, 毕斗斗, 陈宏洋, 等. 知识密集型服务业集聚对城市群旅游创新影响的空间效应. 地理学报, 2021, 76(6): 1521-1536.] doi: 10.11821/dlxb202106014
[40]	Mu Xueqing, Guo Xiangyang, Ming Qingzhong. Temporal and spatial pattern characteristics and spatial effect of tourism financial efficiency in the Yangtze River Economic Belt. Economic Geography, 2020, 40(6): 214-223.
	[穆学青, 郭向阳, 明庆忠. 长江经济带旅游金融效率时空格局特征及空间效应. 经济地理, 2020, 40(6): 214-223.]
[41]	Mu Xueqing, Guo Xiangyang, Ming Qingzhong. The spatio-temporal evolution and impact mechanism of county tourism poverty alleviation efficiency from the perspective of multidimensional poverty: A case study of 25 border counties(cities)in Yunnan Province. Economic Geography, 2020, 40(12): 199-210.
	[穆学青, 郭向阳, 明庆忠. 多维贫困视角下县域旅游扶贫效率时空演化及影响机理: 以云南25个边境县(市)为例. 经济地理, 2020, 40(12): 199-210.]
[42]	Lin Shuang, Zhao Lei. Study on the threshold effect of urbanization on the competitiveness of tourism industry. Tourism Tribune, 2020, 35(11): 27-41.
	[林爽, 赵磊. 城镇化进程对旅游产业竞争力的门槛效应研究. 旅游学刊, 2020, 35(11): 27-41.]
[43]	Fölster S, Henrekson M. Growth effects of government expenditure and taxation in rich countries. European Economic Review, 2001, 45(8): 1501-1520. doi: 10.1016/S0014-2921(00)00083-0

跃迁类型	跃迁形式	符号表示
I型	自身跃迁、邻域稳定	HH→LH、LH→HH、LL→HL、HL→LL
II型	自身稳定、邻域跃迁	HH→HL、LH→LL、LL→LH、HL→HH
III型	自身跃迁、邻域跃迁	HH→LL、LH→HL、LL→HH、HL→LH
IV型	自身稳定、邻域稳定	HH→HH、LH→LH、LL→LL、HL→HL

系统层	一级指标	二级指标
旅游产业规模	旅游资源本底	旅游资源丰富度
	旅游资源本底	旅游资源品位度
	旅游接待能力	旅游业从业人员占比
		星级酒店数量
		旅行社数量
	旅游产出规模	旅游总收入
	旅游产出规模	旅游总人次
旅游产业结构	结构合理化	修正泰尔指数
	结构高级化	旅行社劳动生产率
		旅游景区劳动生产率
		星级酒店劳动生产率
		旅游专利申请数量
旅游产业效率	投入指标	旅游业从业人员数量
		旅游服务要素
		旅游资源要素
	产出指标	旅游总收入
	产出指标	旅游总人次

年份	2011	2012	2013	2014	2015	2016	2017	2018	2019
全局莫兰指数值	0.280	0.217	0.379	0.407	0.395	0.370	0.320	0.369	0.295
P值	0.012	0.026	0.002	0.001	0.001	0.002	0.003	0.002	0.003

时间段	t/t+1	HH	LH	LL	HL
2011—2015	HH	IV(8, 0.2580）	I(1, 0.0323）	III(0, 0.0000）	II(0, 0.0000）
	LH	I(2, 0.0645）	IV(4, 0.1290）	II(0, 0.0000）	III(0, 0.0000）
	LL	III(0, 0.0000）	II(1, 0.0323）	IV(9, 0.2903）	I(0, 0.0000）
	HL	II(1, 0.0323）	III(0, 0.0000）	I(1, 0.0323）	IV(4, 0.1290）
2015—2019	HH	IV(9, 0.2903）	I(1, 0.0323）	III(0, 0.0000）	II(1, 0.0323）
	LH	I(4, 0.1290）	IV(2, 0.0645）	II(0, 0.0000）	III(0, 0.0000）
	LL	III(0, 0.0000）	II(1, 0.0323）	IV(8, 0.2581）	I(1, 0.0323）
	HL	II(0, 0.0000）	III(0, 0.0000）	I(1, 0.0323）	IV(3, 0.0968）

变量	GTWR					OLS	VIF
变量	最小值	下四分位数	中位数	上四分位数	最大值	OLS	VIF
LNGMR	-0.404	0.011	0.121	0.202	0.383	0.206^***	2.31
LNHR	-0.211	0.005	0.056	0.083	0.221	0.087^***	3.25
LNIS	-0.194	0.133	0.197	0.259	0.670	0.124^***	9.04
LNKX	-2.363	0.253	0.343	0.483	0.935	0.497^***	2.61
LNTRA	-0.330	0.061	0.127	0.176	0.327	0.110^***	4.77
LNUL	-0.892	0.211	0.393	0.700	2.186	0.322^***	5.89
R²	0.903					0.793
R²Adj	0.901					0.788
RSS	3.132					6.671
AICc	-308.203					-235.837

Spatiotemporal coupling relationship and influencing factors of China's tourism industry organization

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[6]	WANG Shaojian, CUI Zitian, LIN Jingjie, XIE Jinyan, SU Kun. Coupling relationship between urbanization and ecological resilience in the Pearl River Delta [J]. Acta Geographica Sinica, 2021, 76(4): 973-991.
[7]	ZHOU Kan, LI Hui, SHEN Yuming. Spatiotemporal patterns and driving factors of environmental stress in Beijing-Tianjin-Hebei region: A county-level analysis [J]. Acta Geographica Sinica, 2020, 75(9): 1934-1947.
[8]	FANG Shimin, HUANG Yan. Spatiotemporal evolutions and coordination of tourism efficiency and scale in the Yangtze River Economic Belt [J]. Acta Geographica Sinica, 2020, 75(8): 1757-1772.
[9]	LIU Yujie, GE Quansheng, DAI Junhu. Research progress in crop phenology under global climate change [J]. Acta Geographica Sinica, 2020, 75(1): 14-24.
[10]	WANG Zhengxiong,JIANG Yongjun,ZHANG Yuanzhu,DUAN Shihui,LIU Jiuchan,ZENG Ze,ZENG Sibo. Spatial distribution and driving factors of karst rocky desertification based on GIS and geodetectors [J]. Acta Geographica Sinica, 2019, 74(5): 1025-1039.
[11]	CAO Xiaoshu, XU Jianbin. Spatial heterogeneity analysis of regional economic development and driving factors in China's provincial border counties [J]. Acta Geographica Sinica, 2018, 73(6): 1065-1075.
[12]	Tao LI, Jiaming LIU, Lei WANG, He ZHU, Ling YU. Spatial differences in international investment in hotels and its driving factors in China [J]. Acta Geographica Sinica, 2017, 72(10): 1904-1919.
[13]	Jun YANG, Yuting GE, Jianchao XI, Quansheng GE, Xueming LI. Spatial-temporal island tourismification effects differentiation of Changhai county [J]. Acta Geographica Sinica, 2016, 71(6): 1074-1094.
[14]	YANG Xingzhu, WANG Qun. Evaluation of rural human settlement quality difference and its driving factors in tourism area of southern Anhui Province [J]. Acta Geographica Sinica, 2013, 68(6): 851-867.
[15]	TAO Zhuomin, XUE Xianwei, GUAN Jingjing. Efficiency Characteristics Analysis of Tourism Industry in China Based on the Method of DEA [J]. Acta Geographica Sinica, 2010, 65(8): 1004-1012.