中国包容性旅游发展评估及空间格局研究——基于287个城市面板数据

doi:10.12118/j.issn.1000－6060.2023.133

摘要/Abstract

摘要：

旅游业的包容性发展对促进机会平等、平等发展和成果共享具有重要作用。以全国287个城市为研究对象，基于2010—2019年面板数据构建了综合评价指标体系，综合应用熵值法、灰色关联度和空间分析等方法对中国包容性旅游发展水平进行评估，揭示空间分布特征及演变趋势，并测度影响因素。结果表明：（1）中国包容性旅游发展水平存在显著空间差异，由带状分布逐渐过渡到块状分布，最后形成点状分布。城市间包容性旅游发展差异不断扩大，空间极化现象加剧，不平衡发展问题凸显。（2）中国包容性旅游发展水平可以划分为欠发展地区、低度发展地区、中度发展地区、高度发展地区4种类型，包容性旅游高度发展地区主要集中于东部地区。（3）中国包容性旅游发展可分为2010—2014年缓慢增长和2015—2019年快速增长2个阶段。（4）城镇登记失业率、星级酒店数量和人均公园绿地面积是影响中国包容性旅游发展空间格局的主要因素，空气质量状况和第三产业占地区生产总值比重是次要因素。研究结果可为优化中国包容性旅游空间布局、助推旅游业包容性发展提供参考依据。

关键词: 包容性旅游, 空间格局, 发展趋势, 影响因素, 发展评估

Abstract:

The development of inclusive tourism plays a crucial role in promoting social justice, protecting the rights and interests of vulnerable groups, and ensuring equitable benefits from tourism, particularly in developing countries. However, existing studies lack quantitative assessments of inclusive tourism development at the country and regional levels. In this study, a comprehensive evaluation system of inclusive tourism development was constructed, consisting of nine indicators across three dimensions: tourism participants, economic inclusiveness, and resources and environment. Based on panel data from 2010 to 2019 and applying the entropy method, the inclusive tourism development level of 287 cities in China was assessed in this study. Spatial analysis methods were employed to reveal the spatial distribution characteristics and evolution trends of inclusive tourism. Furthermore, the gray correlation degree method was used to identify the factors influencing inclusive tourism development in China. The results are as follows: (1) Significant spatial differences exist in inclusive tourism development in China, transitioning from zonal to clustered distributions, and finally forming a point-like distribution. The disparity in inclusive tourism development has widened, spatial polarization has intensified, and unbalanced development has become prominent. (2) Inclusion tourism development in China can be divided into four types: underdeveloped, low-development, medium-development, and highly developed areas. The highly developed areas of inclusive tourism are mainly concentrated in the eastern region. (3) The level of inclusive tourism development in China shows a “W-shaped” trend of fluctuation and rise, with increasing spatial differences. It can be divided into two stages: slow growth from 2010 to 2014 and rapid growth from 2015 to 2019. (4) The urban registered unemployment rate, the number of star-rated hotels, and the per capita green park area are the major factors affecting the spatial pattern of inclusive tourism development in China, while air quality and the proportion of tertiary industry in the GDP are secondary factors. This study provides a scientific basis for optimizing the spatial distribution of inclusive tourism development in China. It contributes to enriching the global knowledge system of inclusive tourism development and aids scholars and practitioners in gaining a deeper understanding of inclusive tourism development in China.

Key words: inclusive tourism, spatial pattern, development trend, impact factor, development assessment

王瑞, 郭荔, 戴俊骋, 程哲. 中国包容性旅游发展评估及空间格局研究——基于287个城市面板数据[J]. 干旱区地理, 2024, 47(1): 127-136.

WANG Rui, GUO Li, DAI Juncheng, CHENG Zhe. Assessment and spatial pattern of inclusive tourism development in China: Based on panel data of 287 cities[J]. Arid Land Geography, 2024, 47(1): 127-136.

图/表 6

表1

表2

表3

得分前50城市综合评价结果"

城市	2010年综合得分	城市	2015年综合得分	城市	2019年综合得分
北京市	0.2012	北京市	0.1149	上海市	0.2421
深圳市	0.0975	三亚市	0.0958	成都市	0.1887
成都市	0.0942	广州市	0.0946	北京市	0.1400
重庆市	0.0905	上海市	0.0783	深圳市	0.1090
广州市	0.0829	资阳市	0.0746	重庆市	0.1067
上海市	0.0821	苏州市	0.0721	郑州市	0.0918
杭州市	0.0793	杭州市	0.0714	安顺市	0.0873
宁波市	0.0759	宁波市	0.0654	杭州市	0.0870
天津市	0.0693	六盘水市	0.0654	南京市	0.0856
南京市	0.0670	西安市	0.0630	哈尔滨市	0.0833
西安市	0.0637	昭通市	0.0600	广州市	0.0825
东莞市	0.0633	青岛市	0.0588	沈阳市	0.0777
温州市	0.0633	厦门市	0.0584	大连市	0.0774
烟台市	0.0629	天津市	0.0577	东莞市	0.0711
郑州市	0.0620	武汉市	0.0570	宁波市	0.0701
苏州市	0.0599	南京市	0.0567	厦门市	0.0693
金华市	0.0596	徐州市	0.0562	苏州市	0.0679
武汉市	0.0587	绥化市	0.0561	吉林市	0.0660
淄博市	0.0580	温州市	0.0553	贵阳市	0.0610
绍兴市	0.0568	南通市	0.0541	长春市	0.0598
济南市	0.0564	长沙市	0.0534	温州市	0.0574
南通市	0.0557	福州市	0.0534	天津市	0.0574
大连市	0.0552	齐齐哈尔市	0.0525	合肥市	0.0569
海口市	0.0547	泉州市	0.0524	长沙市	0.0566
无锡市	0.0543	烟台市	0.0523	洛阳市	0.0557
台州市	0.0542	深圳市	0.0516	福州市	0.0551
哈尔滨市	0.0541	株洲市	0.0508	珠海市	0.0533
青岛市	0.0537	邵阳市	0.0503	佛山市	0.0527
泉州市	0.0533	大连市	0.0503	三明市	0.0513
泰安市	0.0527	台州市	0.0503	泉州市	0.0511
丽江市	0.0527	衡阳市	0.0501	丽江市	0.0509
九江市	0.0526	十堰市	0.0501	抚顺市	0.0508
临沂市	0.0521	宁德市	0.0499	桂林市	0.0492
潍坊市	0.0517	临沧市	0.0497	南昌市	0.0491
厦门市	0.0515	常州市	0.0496	双鸭山市	0.0490
济宁市	0.0514	绍兴市	0.0493	黑河市	0.0489
威海市	0.0514	金华市	0.0492	丹东市	0.0488
徐州市	0.0511	牡丹江市	0.0492	南宁市	0.0487
常州市	0.0509	岳阳市	0.0491	衡阳市	0.0480
石家庄市	0.0509	巢湖市	0.0489	韶关市	0.0479
洛阳市	0.0509	常德市	0.0488	淮安市	0.0477
保定市	0.0508	盐城市	0.0487	河池市	0.0477
连云港市	0.0507	无锡市	0.0486	巢湖市	0.0475
唐山市	0.0505	怀化市	0.0485	惠州市	0.0471
菏泽市	0.0505	宜昌市	0.0484	娄底市	0.0470
盐城市	0.0504	嘉兴市	0.0483	鸡西市	0.0468
舟山市	0.0503	扬州市	0.0482	江门市	0.0464
宜昌市	0.0499	襄樊市	0.0481	张家口市	0.0460
嘉兴市	0.0495	淮安市	0.0481	三亚市	0.0459
长春市	0.0495	延安市	0.0479	湛江市	0.0457

表3

图1

图2

表4

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目标层	准则层	指标层	指标属性
包容性旅游发展	旅游活动参与者	文化旅游与传媒支出/10⁸元	正向
		城镇登记失业率/%	负向
		国内人均旅游花费/元	正向
	旅游经济包容性	人均地区生产总值/元	正向
		第三产业占地区生产总值比重/%	正向
		交通运输客运量/10⁴人	正向
	旅游资源环境	人均公园绿地面积/m²	正向
		空气质量状况/d	正向
		星级饭店数量/个	正向

指标	信息熵值	信息效用	权重
文化旅游与传媒支出	0.9676	0.0324	0.1040
城镇登记失业率	0.9863	0.0137	0.0439
人均公园绿地面积	0.9706	0.0294	0.0944
国内人均旅游花费	0.9359	0.0641	0.2056
人均地区生产总值	0.9844	0.0156	0.0502
第三产业占地区生产总值比重	0.9235	0.0765	0.2454
交通运输客运量	0.9555	0.0445	0.1426
空气质量状况	0.9930	0.0070	0.0224
星级酒店数量	0.9715	0.0285	0.0915

指标	关联度	排名
城镇登记失业率	1.000	1
星级酒店数量	0.999	2
人均公园绿地面积	0.998	3
空气质量状况	0.996	4
第三产业占地区生产总值比重	0.988	5
国内旅游人均消费	0.878	6
交通运输客运量	0.850	7
人均地区生产总值	0.595	8
文化旅游与传媒支出	0.405	9