世界地理研究 ›› 2023, Vol. 32 ›› Issue (10): 161-172.DOI: 10.3969/j.issn.1004-9479.2023.10.2021805
• 文化与社会 • 上一篇
收稿日期:
2021-10-29
修回日期:
2022-03-29
出版日期:
2023-10-15
发布日期:
2023-10-25
通讯作者:
汪侠
作者简介:
闫艺涵(1998—),女,硕士研究生,研究方向为休闲与旅游地理,E-mail:yhyan1998@163.com。
基金资助:
Yihan YAN1(), Xia WANG1(), Ying ZHANG1, Lizhen SHEN2
Received:
2021-10-29
Revised:
2022-03-29
Online:
2023-10-15
Published:
2023-10-25
Contact:
Xia WANG
摘要:
基于中国综合社会调查数据,利用模糊综合评价法对中国居民休闲参与进行测度,并运用地理探测器对其空间分异的制约因素进行研究。结果表明:①2010—2017年中国居民休闲参与指数不断提高。从休闲类型看,除媒体消遣休闲参与略有下降外,其他维度休闲参与均有所改善。②2010—2017年中国居民休闲参与呈现“东部领先、中部一般、西南洼地、西北加速”的发展态势,其中京、津、沪、粤居民休闲参与水平较高,贵、蒙、皖则始终较低。③家庭经济条件、宏观休闲环境是居民休闲参与空间分异的主导制约因素,但制约作用逐渐减弱;休闲设施的制约作用不断强化,成为又一主导制约因素;休闲时间、休闲出行始终是次要制约因素。整体来看,各制约因素存在交互强化作用,说明居民休闲受到经济、社会、环境等多种要素的综合制约。
闫艺涵, 汪侠, 张颖, 沈丽珍. 中国居民休闲参与测度及其制约因素探究[J]. 世界地理研究, 2023, 32(10): 161-172.
Yihan YAN, Xia WANG, Ying ZHANG, Lizhen SHEN. Study on measurement and constraint factors of residents' leisure participation in China[J]. World Regional Studies, 2023, 32(10): 161-172.
图1 2010—2017年中国东中西部居民休闲参与指数、变异系数及各维度休闲参与指数
Fig.1 Measurement, coefficient of variation and multidimensional leisure participation index in Eastern, Central and Western China during 2010-2017
图2 2010—2017年居民休闲参与指数空间分布注:该图基于国家测绘地理信息局标准地图(审图号为GS(2019)1825号)绘制,底图无修改
Fig.2 Spatial distribution of residents’ leisure participation index in China during 2010-2017
一级指标 | 二级指标 | 文献来源 |
---|---|---|
家庭经济条件制约 | 人均可支配收入 | [ |
人均教育/文化/娱乐支出 | [ | |
休闲时间制约 | 社会抚养比 | [ |
宏观休闲环境制约 | 地区生产总值 | [ |
第三产业占GDP比重 | [ | |
城镇化率 | [ | |
休闲设施制约 | 人均公园绿地面积 | [ |
每百万人艺术表演场馆数 | [ | |
人均体育场地面积 | [ | |
人均公共图书馆藏量 | [ | |
居民每百户计算机拥有量 | [ | |
休闲出行制约 | 居民每百户家用汽车拥有量 | [ |
建成区公共交通路网密度 | [ |
表1 休闲制约因素选取
Tab.1 Factors system for leisure constraints in China
一级指标 | 二级指标 | 文献来源 |
---|---|---|
家庭经济条件制约 | 人均可支配收入 | [ |
人均教育/文化/娱乐支出 | [ | |
休闲时间制约 | 社会抚养比 | [ |
宏观休闲环境制约 | 地区生产总值 | [ |
第三产业占GDP比重 | [ | |
城镇化率 | [ | |
休闲设施制约 | 人均公园绿地面积 | [ |
每百万人艺术表演场馆数 | [ | |
人均体育场地面积 | [ | |
人均公共图书馆藏量 | [ | |
居民每百户计算机拥有量 | [ | |
休闲出行制约 | 居民每百户家用汽车拥有量 | [ |
建成区公共交通路网密度 | [ |
变量 | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
0.818 | ||||||||||||
0.697 | 0.768 | |||||||||||
0.722 | 0.895 | 0.600 | ||||||||||
0.747 | 0.956 | 0.582 | 0.637 | |||||||||
0.687 | 0.851 | 0.728 | 0.760 | 0.887 | ||||||||
0.741 | 0.860 | 0.380 | 0.641 | 0.790 | 0.894 | |||||||
0.862 | 0.918 | 0.507 | 0.713 | 0.840 | 0.911 | 0.580 | ||||||
0.685 | 0.839 | 0.691 | 0.595 | 0.902 | 0.774 | 0.760 | 0.806 | |||||
0.827 | 0.948 | 0.728 | 0.895 | 0.950 | 0.864 | 0.878 | 0.945 | 0.901 | ||||
0.775 | 0.956 | 0.901 | 0.803 | 0.873 | 0.832 | 0.853 | 0.935 | 0.871 | 0.941 | |||
0.703 | 0.871 | 0.352 | 0.589 | 0.751 | 0.842 | 0.577 | 0.859 | 0.650 | 0.937 | 0.824 | ||
0.719 | 0.906 | 0.561 | 0.575 | 0.812 | 0.847 | 0.731 | 0.914 | 0.793 | 0.948 | 0.864 | 0.549 |
表2 2017年地理探测器交互探测结果
Tab.2 Interaction detector of the geo-detector in 2017
变量 | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
0.818 | ||||||||||||
0.697 | 0.768 | |||||||||||
0.722 | 0.895 | 0.600 | ||||||||||
0.747 | 0.956 | 0.582 | 0.637 | |||||||||
0.687 | 0.851 | 0.728 | 0.760 | 0.887 | ||||||||
0.741 | 0.860 | 0.380 | 0.641 | 0.790 | 0.894 | |||||||
0.862 | 0.918 | 0.507 | 0.713 | 0.840 | 0.911 | 0.580 | ||||||
0.685 | 0.839 | 0.691 | 0.595 | 0.902 | 0.774 | 0.760 | 0.806 | |||||
0.827 | 0.948 | 0.728 | 0.895 | 0.950 | 0.864 | 0.878 | 0.945 | 0.901 | ||||
0.775 | 0.956 | 0.901 | 0.803 | 0.873 | 0.832 | 0.853 | 0.935 | 0.871 | 0.941 | |||
0.703 | 0.871 | 0.352 | 0.589 | 0.751 | 0.842 | 0.577 | 0.859 | 0.650 | 0.937 | 0.824 | ||
0.719 | 0.906 | 0.561 | 0.575 | 0.812 | 0.847 | 0.731 | 0.914 | 0.793 | 0.948 | 0.864 | 0.549 |
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