Combining big data technology to study the geographical distribution characteristics of tourism consumption behavior

Survey of local correlation of travel consumption level

Region	Moran’s I					Geary’s C
	Ii	E(Ii)	sd(Ii)	z	p-value*	ci	E(ci)	sd(ci)	z	p-value*
Beijing	1.253	-0.043	0.725	1.078	0.018	0.652	2.352	1.872	-0.789	0.179
Tianjin	0.893	-0.043	0.380	0.783	0.167	0.666	2.352	2.376	-0.133	0.234
Hebei	-0.425	-0.043	0.378	-0.606	0.516	4.463	2.352	1.887	0.848	0.476
Shanxi	0.025	-0.043	0.093	0.741	0.839	1.324	2.352	1.409	-0.789	0.092
Neimenggu	-0.072	-0.043	0.740	-0.674	0.239	4.884	2.352	1.307	0.275	0.399
Liaoning	0.024	-0.043	0.573	0.456	0.853	0.630	2.352	1.135	-0.509	0.174
Jilin	-0.142	-0.043	0.931	1.182	0.223	0.723	2.352	1.330	-0.058	0.383
Heilongjiang	1.352	-0.043	0.310	-0.431	0.283	1.835	2.352	1.037	-0.146	0.187
Shanghai	-0.012	-0.043	0.145	0.508	0.371	1.639	2.352	1.404	-0.393	0.120
Jiangsu	-0.157	-0.043	0.095	0.437	0.151	1.320	2.352	1.520	-0.710	0.831
Zhejiang	-0.214	-0.043	0.685	-0.609	0.396	1.493	2.352	1.047	-0.183	0.179
Anhui	0.135	-0.043	0.603	0.428	0.443	0.562	2.352	1.316	-0.422	0.334
Fujian	-0.024	-0.043	0.041	0.446	0.625	1.403	2.352	1.966	-0.798	0.409
Jiangxi	0.328	-0.043	0.546	0.772	0.036	0.527	2.352	1.306	-0.990	0.805
Shandong	0.258	-0.043	0.239	0.404	0.391	1.754	2.352	1.264	-0.245	0.759
Henan	0.321	-0.043	0.202	0.491	0.340	1.700	2.352	1.253	-0.682	0.097
Hubei	0.205	-0.043	0.079	0.334	0.756	0.620	2.352	1.351	-0.050	0.428
Hunan	0.172	-0.043	0.422	0.779	0.832	1.545	2.352	1.378	-0.052	0.526
Guangdong	-0.724	-0.043	0.353	-0.276	0.407	5.592	2.352	1.250	0.960	0.630
Guangxi	0.024	-0.043	0.180	0.756	0.144	0.603	2.352	1.364	-0.660	0.083
Hainan	-0.825	-0.043	0.537	-0.664	0.068	4.566	2.352	1.177	0.135	0.608
Chongqing	0.152	-0.043	0.244	0.728	0.540	1.793	2.352	1.265	-0.562	0.173
Sichuan	0.283	-0.043	0.395	0.710	0.617	0.656	2.352	1.022	-0.072	0.235
Guizhou	-0.983	-0.043	0.517	-0.340	0.230	5.449	2.352	1.261	-0.088	0.709
Yunnan	0.058	-0.043	0.406	0.635	0.802	1.519	2.352	1.113	0.422	0.429
Xizang	0.089	-0.043	0.244	0.759	0.262	1.538	2.352	1.210	-0.215	0.312
Shanxi	0.087	-0.043	0.369	0.696	0.677	1.707	2.352	1.434	-0.602	0.533
Gansu	-0.135	-0.043	0.364	-0.363	0.590	6.610	2.352	1.177	0.494	0.309
Qinghai	0.198	-0.043	0.610	0.195	0.505	3.765	2.352	1.923	-0.028	0.013
Ningxi	-0.675	-0.043	0.205	-0.525	0.359	4.656	2.352	1.375	0.952	0.128
Xinjiang	-0.178	-0.043	0.380	1.078	0.862	2.597	2.352	1.526	0.416	0.021

The results of the whole domain tourism development index were returned

Variable	OLS(Individual fixation)	SLM	SEM	SDM(Time fixed)
hcl	-0.4254***	0.2986***	-0.1527**	0.2975***
	(-4.2151)	(8.5407)	(-2.0124)	(7.8697)
asa	0.3048***	0.1243***	0.2235***	0.1543***
	(8.0053)	(3.6381)	(5.7680)	(4.0517)
pcgdp	0.2176***	0.2688***	0.2104***	0.2493**
	(4.5206)	(7.9618)	(3.6524)	(6.3124)
nta	-0.5248	0.1275***	-0.827**	0.1993***
	(-1.2701)	(3.3562)	(9.8571)	(6.4215)
nsh	0.4867***	0.2534***	-0.875**	0.1942***
	(10.4813)	(4.8965)	(-2.5354)	(4.2513)
W* hcl	-	-	-	-0.1896*
	-	-	-	(-0.1935)
W*asa	-	-	-	0.0027
	-	-	-	(0.0528)
W*pcgdp	-	-	-	0.0924
	-	-	-	(1.657)
W*nta	-	-	-	-0.5246***
	-	-	-	(-8.2012)
W*nsh	-	-	-	0.1530
	-	-	-	(1.7852)
ρ/λ	-	0.1893***	0.5243***	0.3562***
		(3.6538)	(11.2042)	(7.4251)
Adj·R2	0.9147	0.7896	0.4869	0.7892
Log L	653.2568	541.2305	598.6258	463.5284

Global correlation test for consumption levels

YEAR	Moran’s I					Geary’s C
	I	E(I)	sd(I)	z	p-value*	C	E(C)	sd(C)	z	p-value*
2010	-0.025	-0.027	0.124	0.042	0.925	1.524	1.000	0.142	0.254	0.724
2011	-0.018	-0.027	0.124	0.214	0.798	0.839	1.000	0.143	-0.078	0.951
2012	0.105	-0.027	0.125	1.53	0.335	0.827	1.000	0.146	-1.241	0.352
2013	0.042	-0.027	0.124	0.721	0.652	0.931	1.000	0.142	-0.158	0.816
2014	0.045	-0.027	0.128	0.715	0.652	0.993	1.000	0.145	-0.129	0.948
2015	0.142	-0.027	0.127	1.568	0.241	0.824	1.000	0.145	-1.505	0.247
2016	-0.064	-0.027	0.124	-0.415	0.825	1.124	1.000	0.142	-1.557	0.124
2017	-0.089	-0.027	0.124	-0.524	0.662	1.181	1.000	0.143	0.682	0.542
2018	-0.036	-0.027	0.124	0.069	0.963	1.012	1.000	0.143	0.725	0.415
2019	-0.021	-0.027	0.125	0.051	0.942	1.068	1.000	0.142	0.241	0.856
2020	-0.055	-0.027	0.127	-0.182	0.785	1.043	1.000	0.143	0.359	0.521
2021	-0.075	-0.027	0.124	-0.358	0.852	1.029	1.000	0.142	0.522	0.856
2022	-0.061	-0.027	0.126	-0.182	0.896	1.014	1.000	0.145	0.384	0.722

Direct effect, indirect effect and total effect of tourism development index

Variable	hcl	asa	pcgdp	nta	nsh
Direct effect	0.3512***	0.1375***	0.2635***	0.2286**	0.2425***
	(7.8695)	(4.5264)	(6.9865)	(5.6838)	(4.4151)
Indirect effect	-0.0921	0.0785	0.2513***	-0.6879***	0.2441*
	(-0.8879)	(0.7196)	(3.5628)	(-6.0591)	(2.3561)
Total effect	0.2041	0.2215	0.5237***	-0.3604***	0.5124***
	(1.7245)	(1.8206)	(7.2653)	(-4.0111)	(2.9815)

Average consumption of scenic spots in different scenic spots

Scenic spot name	Average consumption number (time)
Changbaishan	5
Changbaishanxiagufushilinjingqu	2
Longshunxueshanfeihujingqu	8
Daxitaihejingqu	3
Chuangxingchangbaishanyuanshisamanbuluofengjingqu	2
Daguandongwenhuayuan	7
Mojiefengjingqu	3
Shangbaishanlishiwenhuayuan	5
Shangbaishanhepinghuaxuechang	5
Hongqichaoxianminsucun	12
Changbaishanbaoshixiaozhenlvyoudujiaqu	15
Xidongyouleyuan	4
Songhuacun	8
Baihuagujingqu	6
Changbaishandiyicunfengjingqu	4
Changbaishanwenhuaboliancheng	5
Haigouhuangjincheng	3
Huiyiyizhi	4
Genjudizhanshijinianguan	2