The impact of tourism industry agglomeration on economic resilience: A comparative study between inbound and domestic markets

doi:10.3969/j.issn.1004-9479.2026.08.20250265

Abstract

Abstract:

Based on China's provincial panel data from 2007 to 2019, this study employs GIS methods, spatial Markov chains, and panel econometric models to depict the spatial-temporal evolution patterns of tourism agglomeration, inbound tourism economic resilience, and domestic tourism economic resilience under the impact of the 2008 global financial crisis, as well as a comparative study on the differential effects of tourism industrial agglomeration on inbound and domestic tourism economic resilience across different periods. The results indicate that: ①From 2007 to 2019, there was significant heterogeneity in the changes in specialization agglomeration of the tourism industry, with a spatial distribution that was misaligned with China's economic growth map. In contrast, diversification agglomeration levels steadily increased, evolving toward a spatial pattern of high in the inland and low in the southeast. ②During the shock-resistance period, inbound and domestic tourism economic resilience exhibited a spatial pattern of high in the central and eastern regions and low in the western regions, while in the recovery and adjustment period, it showed a stepped characteristic of high in the western regions and low in the eastern regions. Moreover, the volatility, spatial disparity, and non-spatial dependence of inbound tourism economic resilience were more pronounced than those of domestic tourism in both periods. ③The scale effect and brand effect of specialization agglomeration in the tourism industry were more conducive to local inbound and domestic tourism economies resisting shocks compared to the risk-diversifying effect and automatic stabilizer role of diversification agglomeration. Specialization agglomeration could even radiate to neighboring domestic tourism, while the effect of diversification agglomeration was limited to within provinces and cities. ④The role of diversification agglomeration in the tourism industry in promoting the recovery and adjustment capabilities of local inbound, local, and neighboring domestic tourism industries was more pronounced than that of specialization agglomeration, and over-competition in the tourism industry affected the realization of specialization agglomeration effects.

Key words: tourism economic resilience, specialization agglomeration, diversification agglomeration, inbound tourism, domestic tourism

摘要：

基于2007―2019年中国省际面板数据，运用GIS空间分析方法、空间马尔科夫链和面板计量模型，刻画了2008年金融危机冲击下旅游产业集聚水平、入境和国内旅游经济韧性的时空演化格局，对比研究了旅游产业集聚对不同时期入境旅游和国内旅游经济韧性的作用差异。结果表明：①2007―2019年旅游产业专业化集聚水平的变化具有显著异质性，空间分布与我国经济增长态势存在错位；多样化集聚水平则稳步提升，演变为内陆高、东南低的空间格局。②在冲击抵御期，我国入境与国内旅游经济韧性呈“中高西低”的空间格局；至恢复调整期，则转变为“西高东低”的阶梯状分布。两时期相比，入境旅游经济韧性的波动性、空间差异性和非空间依赖性均明显强于国内旅游。③相较于多样化集聚的分散风险效应和自动稳定器作用，旅游产业专业化集聚的规模效应和品牌效应更有利于增强本地入境和国内旅游经济抵御冲击的能力；专业化集聚甚至还能辐射带动邻地国内旅游，而多样化集聚的作用仅局限于本省市内部。④旅游产业多样化集聚对本地入境旅游、本地和邻地国内旅游产业的恢复调整能力的影响，较专业化集聚更突出，但旅游产业过度竞争影响了专业化集聚效应的发挥。本研究将为后续其他全球性冲击事件下国内和入境旅游经济的短期应对及长期发展提供借鉴，同时也拓展了演化经济地理学中区域经济韧性的应用领域。

关键词: 旅游经济韧性, 专业化集聚, 多样化集聚, 入境旅游, 国内旅游

Yanan DU, Qingxi WANG. The impact of tourism industry agglomeration on economic resilience: A comparative study between inbound and domestic markets[J]. World Regional Studies, 2026, 35(8): 17-32.

杜亚楠, 王庆喜. 旅游产业集聚对经济韧性的影响——基于入境和国内市场的对比研究[J]. 世界地理研究, 2026, 35(8): 17-32.

Figures/Tables 7

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邻域类型	本域类型	入境旅游经济韧性						国内旅游经济韧性
		冲击抵御期			恢复调整期			冲击抵御期			恢复调整期
		1	2	3	1	2	3	1	2	3	1	2	3
1	1	1.000	0.000	0.000	0.511	0.323	0.166	0.716	0.145	0.139	0.958	0.042	0.000
	2	0.602	0.000	0.398	0.342	0.488	0.170	0.000	1.000	0.000	0.195	0.805	0.000
	3	0.000	0.000	1.000	0.492	0.324	0.184	0.000	0.000	1.000	0.000	0.000	1.000
2	1	1.000	0.000	0.000	0.594	0.086	0.320	0.750	0.250	0.000	0.895	0.052	0.053
	2	0.215	0.224	0.561	0.086	0.687	0.227	0.000	1.000	0.000	0.091	0.804	0.105
	3	0.000	0.000	1.000	0.493	0.183	0.324	0.000	0.000	1.000	0.137	0.086	0.777
3	1	1.000	0.000	0.000	0.700	0.226	0.074	0.667	0.333	0.000	0.795	0.173	0.032
	2	0.000	0.000	1.000	0.091	0.690	0.219	0.000	1.000	0.000	0.104	0.781	0.115
	3	0.000	0.000	1.000	0.607	0.219	0.174	0.000	0.000	1.000	0.026	0.101	0.873

邻域类型	本域类型	入境旅游经济韧性						国内旅游经济韧性
		冲击抵御期			恢复调整期			冲击抵御期			恢复调整期
		1	2	3	1	2	3	1	2	3	1	2	3
1	1	1.000	0.000	0.000	0.511	0.323	0.166	0.716	0.145	0.139	0.958	0.042	0.000
	2	0.602	0.000	0.398	0.342	0.488	0.170	0.000	1.000	0.000	0.195	0.805	0.000
	3	0.000	0.000	1.000	0.492	0.324	0.184	0.000	0.000	1.000	0.000	0.000	1.000
2	1	1.000	0.000	0.000	0.594	0.086	0.320	0.750	0.250	0.000	0.895	0.052	0.053
	2	0.215	0.224	0.561	0.086	0.687	0.227	0.000	1.000	0.000	0.091	0.804	0.105
	3	0.000	0.000	1.000	0.493	0.183	0.324	0.000	0.000	1.000	0.137	0.086	0.777
3	1	1.000	0.000	0.000	0.700	0.226	0.074	0.667	0.333	0.000	0.795	0.173	0.032
	2	0.000	0.000	1.000	0.091	0.690	0.219	0.000	1.000	0.000	0.104	0.781	0.115
	3	0.000	0.000	1.000	0.607	0.219	0.174	0.000	0.000	1.000	0.026	0.101	0.873

年份	入境旅游经济韧性	国内旅游经济韧性	年份	入境旅游经济韧性	国内旅游经济韧性
2007	-0.004	0.080^*	2014	-0.037	0.023^*
2008	0.178^***	0.013^**	2015	0.114^**	0.035^**
2009	-0.045	0.019	2016	0.059	0.143^**
2010	-0.001	0.105^*	2017	0.021	0.088^*
2011	-0.008	0.006^*	2018	0.009	0.116^*
2012	-0.177^*	0.201^***	2019	-0.096	0.136^**
2013	-0.030	0.085^*

年份	入境旅游经济韧性	国内旅游经济韧性	年份	入境旅游经济韧性	国内旅游经济韧性
2007	-0.004	0.080^*	2014	-0.037	0.023^*
2008	0.178^***	0.013^**	2015	0.114^**	0.035^**
2009	-0.045	0.019	2016	0.059	0.143^**
2010	-0.001	0.105^*	2017	0.021	0.088^*
2011	-0.008	0.006^*	2018	0.009	0.116^*
2012	-0.177^*	0.201^***	2019	-0.096	0.136^**
2013	-0.030	0.085^*

变量	入境旅游经济韧性非空间面板模型1	国内旅游经济韧性（SPDM模型2）
变量	入境旅游经济韧性非空间面板模型1	总效应	直接效应	间接效应
Spe	2.006^**(0.959)	1.023^***(0.312)	0.460^***(0.112)	0.562^**(0.243)
Div	1.474^**(0.707)	0.661^***(0.233)	0.347^***(0.079)	0.313(0.193)
Inc	1.752^***(0.507)	0.240^**(0.108)	0.183^***(0.048)	0.058(0.104)
Net	-0.292(1.097)	-1.238^***(0.446)	0.014 1(0.092)	-1.252^***(0.484)
Fin	-0.789^***(0.166)	-0.072^**(0.031)	-0.024^**(0.012)	-0.048 (0.033)
Mar	-0.393(0.560)	0.185(0.168)	-0.095 7^*(0.055)	0.281^**(0.137)
Open	-0.980^**(0.405)	-0.150(0.154)	0.006 56(0.065)	-0.156(0.122)
Tech	-0.306(0.264)	-0.192^**(0.085)	-0.028 3(0.021)	-0.163^**(0.080)
空间效应	控制	控制
时间效应	控制	控制
rho	—	-0.347^*(0.200)
Log-L	—	-120.992
R²	0.691	0.849