Spatio-temporal differences and influencing factors of network attention to ice-snow tourism in China

doi:10.3969/j.issn.1004-9479.2024.10.20222134

Abstract

Abstract:

Network attention has become an important driving force for the development of ice-snow tourism in China.With the National Bureau of Statistics of China and the Baidu Index as the main data sources, the spatio-temporal differences and influencing factors of network attention on ice-snow tourism in China are analyzed through three modules of Baidu Index:"Search Index" "Crowd Portrait" and "Demand Mapping". The results show that: (1) In terms of time, China's ice-snow tourism network attention is growing year by year, the PC search index is higher than the mobile search index, and seasonal differences are obvious, with November, December and January being the high search months every year. (2) In terms of space, the structure distribution shows the development pattern of "high in the east, balanced in the middle and low in the west", with Beijing, Heilongjiang, Jilin and Guangdong being the provinces with higher ranking of network attention for ice-snow tourism in China.(3)In terms of influencing factors, ranked as economic development level > ice-snow tourism resources > large ice-snow events > regional network penetration rate > per capita consumption expenditure; the proportion of young people is negatively correlated with ice-snow tourism network concern. Finally, it proposes the deep integration of ice-snow tourism with big data and other recommendations to provide a scientific basis and decision-making reference for the formulation of relevant national policies to promote the high-quality development of ice-snow tourism.

Key words: ice-snow tourism, Baidu index, network attention, spatio-temporal difference, influencing factors, China

摘要：

网络关注度已成为数字经济时代中国冰雪旅游发展的重要推手。以中国国家统计局和百度指数为主要数据源，综合运用经济地理学、统计学、计量经济学等研究方法，通过百度指数的“搜索指数”“人群画像”“需求图谱”三个模块，对中国冰雪旅游网络关注度的时空差异与影响因素进行分析。结果显示：（1）时间上，中国冰雪旅游网络关注度呈逐年增长趋势，PC端的搜索指数高于移动端搜索指数，季节性差异明显，每年11、12、1月为高搜索月份。（2）空间上，结构分布呈现“东部高、中部均衡、西部低”的发展格局，北京、黑龙江、吉林、广东依次是中国冰雪旅游网络关注度排名较高的省份。（3）影响因素上，排序为经济发展水平>冰雪旅游资源>大型冰雪赛事>地区网络普及率>人均消费支出；其中，青年人群占比与冰雪旅游网络关注度呈现负相关。最后提出冰雪旅游与大数据深度融合等建议，为国家制定相关政策促进冰雪旅游高质量发展提供科学依据和决策参考。

关键词: 冰雪旅游, 百度指数, 网络关注度, 时空差异, 影响因素, 中国

Yufei ZHANG, Yanlu REN, Limin LIANG. Spatio-temporal differences and influencing factors of network attention to ice-snow tourism in China[J]. World Regional Studies, 2024, 33(10): 155-167.

张宇飞, 任艳路, 梁丽敏. 中国冰雪旅游网络关注度的时空差异与影响因素[J]. 世界地理研究, 2024, 33(10): 155-167.

Figures/Tables 9

Fig.1 Temporal variation of ice-snow tourism network attention in China

Fig.2 Spatial difference of attention of ice-snow tourism network in China

Tab.1 Top 10 cities with the highest attention of China's ice-snow tourism network

排名	城市	省份	区域	关注度/次
1	北京	—	东部	7757
2	哈尔滨	黑龙江	中部	6217
3	长春	吉林	中部	5173
4	广州	广东	东部	3559
5	沈阳	辽宁	东部	2401
6	杭州	浙江	东部	2379
7	上海	—	东部	2299
8	南京	江苏	东部	2264
9	石家庄	河北	东部	2155
10	济南	山东	东部	1624

Tab.2 Geographical concentration index of ice-snow tourism network attention in China

年份	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020
G值	37.71	35.52	38.93	33.64	34.24	36.53	35.94	35.46	34.67	31.75

Tab.3 Rating assessment based on suitability index of ice-snow tourism in China

冰雪旅游适宜度等级	区域分布
冰雪旅游高适宜区	黑龙江中部地区，吉林中、东部地区，新疆天山山脉附近地区
冰雪旅游中适宜区	黑龙江东、西部地区，吉林西部地区，内蒙古中、东部地区，新疆中北部地区，云南北部地区，四川西部地区
冰雪旅游基本适宜区	辽宁地区，北京地区，河北中北部地区，山西北部地区，内蒙古西部地区，新疆南部地区，西藏、青海、甘肃大部分地区，四川北部地区

Tab.4 List of cities hosting the Winter Games and above

赛事	举办城市
冬奥会	北京、张家口
冰雪世锦赛和世界杯	上海、南京、重庆
亚冬会和冬运会	哈尔滨、长春、乌鲁木齐、海拉尔

Tab.5 Correlation analysis of influencing factors of spatial and temporal differences in network attention of ice-snow tourism

	网络关注度	网络普及度	冰雪赛事效应	冰雪旅游资源	人均GDP	青年人群占比	人均消费支出
网络关注度	1.00	—	—	—	—	—	—
网络普及度	0.53	1.00	—	—	—	—	—
冰雪赛事效应	0.71	0.15	1.00	—	—	—	—
冰雪旅游资源	0.77	-0.10	0.70	1.00	—	—	—
人均GDP	0.52	0.01	0.05	-0.04	1.00	—	—
青年人群占比	0.66	0.25	0.07	-0.09	0.01	1.00	—
人均消费支出	0.49	0.46	0.53	0.15	0.18	0.31	1.00

Tab.6 Regression results of Poisson model

Y_t	泊松回归	Z	OLS法	t值
网络普及率	0.49	3.51^***	1.85	0.22
冰雪旅游资源	0.97	68.30^***	8.77	2.68^**
冰雪赛事效应	0.79	66.96^***	6.62	5.05^**
人均GDP	2.77	17.91^***	1.37	0.62
青年人群占比	-0.63	-33.17^***	-1.76	-2.87^***
人均消费支出	0.32	32.61^***	0.43	2.42^**
$β 0$	-5.66	10.20^***	-42.63	-2.84^**
F			17.96^***
R2			0.82

Tab.6 Regression results of Poisson model

Y_t	泊松回归	Z	OLS法	t值
网络普及率	0.49	3.51^***	1.85	0.22
冰雪旅游资源	0.97	68.30^***	8.77	2.68^**
冰雪赛事效应	0.79	66.96^***	6.62	5.05^**
人均GDP	2.77	17.91^***	1.37	0.62
青年人群占比	-0.63	-33.17^***	-1.76	-2.87^***
人均消费支出	0.32	32.61^***	0.43	2.42^**
$β 0$	-5.66	10.20^***	-42.63	-2.84^**
F			17.96^***
R2			0.82

Tab.7 Robust regression results

1.85

（0.20）

8.45^**

（2.31）

6.62^***

（3.22）

1.37^*

（2.00）

－1.76^***

（－3.06）

0.43^**

（2.28）

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