Coupling and coordination situation and dynamic mechanism between tourism and transportation industry in China

doi:10.3969/j.issn.1004-9479.2020.01.2018429

Abstract

Abstract:

Studying the coupling relationship between tourism and transportation is of great significance for promoting the transformation and upgrading of the two industries and enhancing the synergistic development effect.Based on the comprehensive development index, gravity center model and the coupled coordination model,this paper comprehensively explores the gravity coupling dynamics and coordinated development degree of tourism and transport industry in 31 provinces and autonomous regions from 2000 to 2016, and analyzes its dynamic mechanism with geodetectors. The research finds that: 1)The center of gravity of the tourism and transportation industries is generally migrating to the southwest, and the spatial overlap of the center of gravity of the two has significantly increased, and the migration directions have also become the same, showing obvious spatial coupling feature; 2)The level of coupled coordinated development between the tourism and transportation industries is gradually increasing, and the balanced development situation is significant, and the degree of coupling and coordination presents strong spatial correlation characteristics; 3)The spatial development differences in the degree of coupling and coordination among provinces and regions show obvious non-equilibrium. The spatial pattern has undergone an evolutionary process from decentralized "plaque-like" to agglomerated "plane",showing a"three-step ladder" distribution trend of high east and low west; 4)Science and technology information driving force, economic driving force, market driving force and policy control driving force on the two coupling and coordinated development of the impact of decreasing in turn, the interaction of various factors and various driving forces, together constitute a driving mechanism to promote the coordinated development between tourism and transportation industry.

Key words: tourism industry, transportation industry, coupling development, geodetector, dynamic mechanism

摘要：

在国内经济转型升级和消费升级带来旅游消费市场新需求的大背景下，研究旅游与交通的耦合发展关系对于促进二者产业转型升级、提升协同发展效应具有重要意义。基于综合发展指数、重心模型及耦合协调模型对2000—2016年全国31个省区旅游业与交通运输业的重心耦合动态及协调发展程度进行综合探究，并结合地理探测器分析其动力机制。研究发现：1)旅游业与交通运输业重心总体呈现出向西南方向迁移的态势，且二者重心迁移的空间重叠性显著升高，迁移方向也趋于一致，表现出明显的空间耦合性特征；2)二者耦合协调发展水平渐趋提升，均衡化发展态势日益显著，其耦合协调度呈现出较强的空间关联性特征；3)耦合协调度空间发展差异的省际非均衡性较为明显，其空间格局经历了由“分散型斑块状”向“集聚型散面状”的演化过程，呈现出东高西低的“三级阶梯状”分布态势；4)科技信息驱动力、经济驱动力、市场驱动力及政策调控驱动力对二者耦合协调发展的影响力度依次递减，各因素与各种驱动力的相互作用，共同构成推动旅游业与交通运输业协调发展的动力机制。

关键词: 旅游业, 交通运输业, 耦合发展, 地理探测器, 动力机制

Baoyi LU, Mengmeng LIU, Qingzhong MING, Anle LIU, Ting LI. Coupling and coordination situation and dynamic mechanism between tourism and transportation industry in China[J]. World Regional Studies, 2020, 29(1): 148-158.

陆保一, 刘萌萌, 明庆忠, 刘安乐, 李婷. 中国旅游业与交通运输业的耦合协调态势及其动力机制[J]. 世界地理研究, 2020, 29(1): 148-158.

Figures/Tables 7

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年份	旅游业				交通运输业
年份	重心坐标（经度、纬度）		偏移/km	方向	重心坐标（经度、纬度）		偏移/km	方向
2000	114.74°E	32.02°N	—	—	114.53°E	33.86°N	—	—
2001	114.82°E	32.20°N	22.42	东北	114.47°E	33.54°N	36.28	西南
2002	114.82°E	32.16°N	4.05	西南	114.44°E	33.50°N	5.59	西南
2003	114.85°E	31.99°N	19.50	东南	114.41°E	33.40°N	11.27	西南
2004	114.79°E	32.18°N	22.20	西北	114.43°E	33.49°N	10.13	东北
2005	114.61°E	32.52°N	43.11	西北	114.39°E	33.42°N	8.56	西南
2006	114.52°E	32.28°N	28.57	西南	114.29°E	33.28°N	19.80	西南
2007	114.59°E	32.27°N	7.94	东南	114.40°E	33.46°N	24.44	东北
2008	114.82°E	32.26°N	25.93	东南	114.53°E	33.66°N	25.70	东北
2009	114.66°E	32.26°N	18.17	西北	114.42°E	33.44°N	27.06	西南
2010	114.66°E	32.38°N	12.80	西北	114.39°E	33.34°N	11.25	西南
2011	114.42°E	32.56°N	33.38	西北	114.25°E	33.04°N	37.02	西南
2012	114.49°E	32.26°N	34.46	东南	114.37°E	33.28°N	29.74	东北
2013	114.28°E	32.16°N	26.02	西南	114.15°E	33.25°N	24.43	西南
2014	114.18°E	32.04°N	17.10	西南	114.13°E	33.11°N	16.51	西南
2015	113.95°E	32.21°N	31.85	西北	113.96°E	33.05°N	20.26	西南
2016	113.93°E	31.89°N	35.37	西南	113.92°E	32.99°N	6.91	西南

年份	旅游业				交通运输业
年份	重心坐标（经度、纬度）		偏移/km	方向	重心坐标（经度、纬度）		偏移/km	方向
2000	114.74°E	32.02°N	—	—	114.53°E	33.86°N	—	—
2001	114.82°E	32.20°N	22.42	东北	114.47°E	33.54°N	36.28	西南
2002	114.82°E	32.16°N	4.05	西南	114.44°E	33.50°N	5.59	西南
2003	114.85°E	31.99°N	19.50	东南	114.41°E	33.40°N	11.27	西南
2004	114.79°E	32.18°N	22.20	西北	114.43°E	33.49°N	10.13	东北
2005	114.61°E	32.52°N	43.11	西北	114.39°E	33.42°N	8.56	西南
2006	114.52°E	32.28°N	28.57	西南	114.29°E	33.28°N	19.80	西南
2007	114.59°E	32.27°N	7.94	东南	114.40°E	33.46°N	24.44	东北
2008	114.82°E	32.26°N	25.93	东南	114.53°E	33.66°N	25.70	东北
2009	114.66°E	32.26°N	18.17	西北	114.42°E	33.44°N	27.06	西南
2010	114.66°E	32.38°N	12.80	西北	114.39°E	33.34°N	11.25	西南
2011	114.42°E	32.56°N	33.38	西北	114.25°E	33.04°N	37.02	西南
2012	114.49°E	32.26°N	34.46	东南	114.37°E	33.28°N	29.74	东北
2013	114.28°E	32.16°N	26.02	西南	114.15°E	33.25°N	24.43	西南
2014	114.18°E	32.04°N	17.10	西南	114.13°E	33.11°N	16.51	西南
2015	113.95°E	32.21°N	31.85	西北	113.96°E	33.05°N	20.26	西南
2016	113.93°E	31.89°N	35.37	西南	113.92°E	32.99°N	6.91	西南

年份	空间重叠性/km	变动一致性
2000	205.54	—
2002	153.78	0.93
2004	150.19	0.84
2006	113.64	0.95
2008	158.92	0.50
2010	110.84	-0.95
2012	114.27	-0.76
2014	118.42	0.88
2016	122.52	0.86

年份	空间重叠性/km	变动一致性
2000	205.54	—
2002	153.78	0.93
2004	150.19	0.84
2006	113.64	0.95
2008	158.92	0.50
2010	110.84	-0.95
2012	114.27	-0.76
2014	118.42	0.88
2016	122.52	0.86

年份	Moran’s I	Z	P
2000	0.2534	2.6550	0.0079
2002	0.2705	2.8175	0.0048
2004	0.2448	2.5801	0.0098
2006	0.2429	2.5645	0.0103
2008	0.2741	2.8568	0.0042
2010	0.2941	3.0379	0.0023
2012	0.2937	3.0475	0.0023
2014	0.3057	3.1617	0.0015
2016	0.3092	3.2061	0.0013