“轮毂”模型：城市自驾旅游者的出游空间结构——以北京、西安、武汉为例

doi:10.11821/dlyj020190697

摘要/Abstract

摘要：

自驾游市场是国内旅游市场的重要组成部分。研究自驾旅游者的出游空间大小和结构对于目的地开发和优化自驾游线路产品、有针对性地开展市场营销工作具有重要意义。以北京、西安和武汉为案例地,基于4000多份调查问卷,应用数理统计法、地图法和空间分析法,对自驾旅游者的出游空间结构进行了定量研究,结果发现：① 自驾到访率随出游距离的增加呈指数衰减,在交通距离400 km范围内衰减最快。② 自驾游空间可划分为轴心区、辐射区和边缘区三种不同类型区。其中,轴心区和辐射区是有旅游市场价值的空间。③ 不同城市自驾游空间大小不同。以交通距离衡量,北京自驾游空间半径为1665 km,西安为1196 km,武汉为1176 km,轴心区半径均在交通距离400 km左右。④ 自驾游空间可划分为舒适空间（4 h以内）和疲惫空间（超过4 h）,其中疲惫空间可进一步划分为轻度疲惫空间（4~6 h）和重度疲惫空间（超过6 h）。舒适空间对应轴心区,疲惫空间对应辐射区,轻度疲惫空间对应轴心区与辐射区之间的过渡带。本研究提出的城市自驾旅游者出游空间结构“轮毂”模型为研究自驾游空间结构提供了认知框架。

关键词: 自驾游空间, “轮毂”模型, 自驾到访率, 空间结构

Abstract:

Self-driving tour market has become an important part of China's domestic tourism market. It is of great theoretical significance to study the spatial extent and structure of urban self-driving tourists' tourism space for enriching and deepening the research on the spatial structure of self-driving tourism. Besides, it has practical value to the tourism destination management organizations' (DMOs) works of marketing, development of self-driving tourism products and implementation of self-driving tourism development strategies. This paper explores the characteristics of tourism space structure of Chinese urban self-driving tourists by analyzing their visits to target scenic spots, based on data of more than 4000 questionnaires obtained from three representative case cities of Beijing, Xi'an and Wuhan, and methods of mathematical statistics, mapping and spatial analysis. The results showed that: (1) The self-driving visiting rate decreases exponentially with the increase of travel distance, and it decreases fast within a range of 400 km. (2) Self-driving tourism space centered on origin city can be divided into three types of zones from the nearby to the distance, which are center zone, diffusion zone and edge zone. Among them, center and diffusion zones are self-driving tourism space with important tourism market value. (3) The size of self-driving tourism space varies in different origin cities. Self-driving tourism space radiuses of Beijing, Xi'an and Wuhan measured by travel distance are respectively 1665 km, 1196 km, and 1176 km. The radius of self-driving tourism center zone in all the three cities is about 400 km. (4) With 4 h and 6 h as the time threshold, self-driving tourism space can be divided into comfort space (within 4 h) and fatigue space (over 4 h), which can be further divided into mild fatigue space (4-6 h) and severe fatigue space (over 6 h). The comfort space corresponds to the center zone while the fatigue space corresponds to the diffusion zone, and the mild fatigue space corresponds to the transitional belt between the center and the diffusion zones. In this study, the tourism space structure of urban self-driving tourists is summarized as a “wheel hub” model, which provides a cognitive framework for studying the spatial structure of self-driving tourism.

Key words: self-driving tourism space, “wheel hub” model, self-driving visiting rate, spatial structure

张甜歌, 吴晋峰, 石晓腾, 吴宝清, 邓纯纯, 吴珊珊. “轮毂”模型：城市自驾旅游者的出游空间结构——以北京、西安、武汉为例[J]. 地理研究, 2020, 39(8): 1822-1835.

ZHANG Tiange, WU Jinfeng, SHI Xiaoteng, WU Baoqing, DENG Chunchun, WU Shanshan. “Wheel hub” model: The tourism space structure of urban self-driving tourists: Taking Beijing, Xi'an and Wuhan cities as examples[J]. GEOGRAPHICAL RESEARCH, 2020, 39(8): 1822-1835.

图/表 8

表1

表2

表3

图1

图2

图3

图4

图5

参考文献 56

[1]	张辉 . 全域旅游助推自驾旅游. 旅游研究, 2017,9(4):2-5.
	[ Zhang Hui . Regional tourism boosts self-driving tourism. Tourism Research, 2017,9(4):2-5.]
[2]	中国旅游研究院. 自驾远行的路上, 我们都是追梦人. https://mp.weixin.qq.com/s/fZpnIP0CedkZrp882dYvWA, 2019-03-06.
	[ China Tourism Academy. We are all dreamers on our long drive. https://mp.weixin.qq.com/s/fZpnIP0CedkZrp882dYvWA, 2019-03-06.]
[3]	吴晋峰. 旅游系统: 理论与空间结构模式研究. 南京: 南京大学博士学位论文, 2001: 32.
	[ Wu Jinfeng . Tourism systems: A study of theoretical and spatial structural models. Nanjing: Doctoral Dissertation of Nanjing University, 2001: 32.]
[4]	刘建国, 张妍, 黄杏灵 . 中国人文地理学区域空间结构研究的主要领域及展望. 地理科学, 2019,39(6):874-885.
	[ Liu Jianguo, Zhang Yan, Huang Xingling . Main areas and prospects of regional spatial structure research in Chinese human geography. Scientia Geographica Sinica, 2019,39(6):874-885.]
[5]	Walter Christaller. Some considerations of tourism location in Europe: The peripheral region underdeveloped countries-recreation areas. Paper and Proceedings of Regional Science Association, 1964,12(1):95-105.
[6]	Douglas Pearce. Tourist Today: A Geographical Snalysis: The 2nd Edition. New York: Longman Press, 1995: 8-35.
[7]	Robert Mings, Kevin McHugh. The spatial configuration of travel to Yellowstone National Park. Journal of Travel Research, 1992,30(4):38-46.
[8]	Martin Oppermann. A model of travel itineraries. Journal of Travel Research, 1995,33(4):57-61.
[9]	Alan Lew, Bob McKercher. Modeling tourist movements: A local destination analysis. Annals of Tourism Research, 2006,33(2):403-423.
[10]	James Hooper. A destination too far? Modelling destination accessibility and distance decay in tourism. GeoJournal, 2015,80(1):33-46.
[11]	Yaping Liu, Yinchang Li, Parnpree Parkpian. Inbound tourism in Thailand: Market form and scale differentiation in ASEAN source countries. Tourism Management, 2018,64:22-36.
[12]	Jianhong Xia, Panlop Zeephongsekul, David Pacher. Spatial and temporal modelling of tourist movements using Semi- Markov Processes. Tourism Management, 2011,32(4):844-851.
[13]	Claire Smallwood, Lynnath Bechley, Susan Moore. An analysis of visitor movement patterns using travel networks in a large marine park, North-western Australia. Tourism Management, 2012,33(3):517-528.
[14]	Jacek Kotus, Michal Rzeszewski, Wojciech Ewertowski. Tourists in the spatial structures of a big Polish city: Development of an uncontrolled patchwork or concentric spheres?. Tourism Management, 2015,50:98-110. doi: 10.1016/j.tourman.2015.01.007
[15]	杨新军, 马晓龙, 霍云霈 . 旅游目的地区域(TDD)及其空间结构研究: 以西安为例. 地理科学, 2004,24(5):620-626.
	[ Yang Xinjun, Ma Xiaolong, Huo Yunpei . Tourist destination district and its spatial structure. Scientia Geographica Sinica, 2004,24(5):620-626.]
[16]	史春云, 张捷, 尤海梅 , 等. 四川省旅游区域核心-边缘空间格局演变. 地理学报, 2007,62(6):631-639. doi: 10.11821/xb200706008
	[ Shi Chunyun, Zhang Jie, You Haimei , et al. Core-periphery spatial structure and its evolution of tourism region in Sichuan province. Acta Geographica Sinica, 2007,62(6):631-639.]
[17]	李仁杰, 郭风华, 安颖 . 北京环城游憩地类型结构与自然要素的关系. 地理与地理信息科学, 2010,26(2):103-106.
	[ Li Renjie, Guo Fenghua, An Ying . Relationship between the distribution of recreational region type around Beijing Metropolises and some natural factors. Geography and Geo-Information Science, 2010,26(2):103-106.]
[18]	肖英, 刘思华 . 长沙环城游憩带旅游开发研究. 经济地理, 2012,32(6):173-176.
	[ Xiao Ying, Liu Sihua . The development of recreational belt around metropolis in Changsha. Economic Geography, 2012,32(6):173-176.]
[19]	孙建伟, 田野, 崔家兴 , 等. 湖北省旅游空间结构识别与可达性测度. 经济地理, 2017,37(4):208-217.
	[ Sun Jianwei, Tian Ye, Cui Jiaxing , et al. Identification of tourism spatial structure and measurement of tourism spatial accessibility in Hubei province. Economic Geography, 2017,37(4):208-217.]
[20]	王绍博, 罗小龙, 郭建科 , 等. 高铁网络下东北地区旅游空间结构动态演变分析. 地理科学, 2019,39(4):568-577. doi: 10.13249/j.cnki.sgs.2019.04.006
	[ Wang Shaobo, Luo Xiaolong, Guo Jianke , et al. Dynamic evolution of tourism spatial structure under the improvement of the high speed rail network in Northeast China. Scientia Geographica Sinica, 2019,39(4):568-577.]
[21]	汪德根, 孙峰, 刘昌雪 , 等. 公共交通系统对城市游憩空间格局影响: 以苏州城区为例. 旅游学刊, 2017,32(10):78-90.
	[ Wang Degen, Sun Feng, Liu Changxue , et al. Impact of low-carbon public transport system on urban recreational spatial: A case study of center city of Suzhou. Tourism Tribune, 2017,32(10):78-90.]
[22]	殷平, 杨寒, 张同颢 . 高速铁路网与京津冀旅游: 空间作用与结构演化. 旅游学刊, 2019,34(3):102-112.
	[ Yin Ping, Yang Han, Zhang Tonghao . High-speed railway and tourism development in Beijing-Tianjin-Hebei Region: Spatial interaction and restructuring. Tourism Tribune, 2019,34(3):102-112.]
[23]	吴必虎 . 大城市环城游憩带(ReBAM)研究: 以上海市为例. 地理科学, 2001,21(4):354-359.
	[ Wu Bihu . A study on recreational belt around metropolis (ReBAM): Shanghai Case. Scientia Geographica Sinica, 2001,21(4):354-359.]
[24]	Degen Wang, Yu Niu, Jia Qian. Evolution and optimization of China's urban tourism spatial structure: A high speed rail perspective. Tourism Management, 2018,64:218-232. doi: 10.1016/j.tourman.2017.08.010
[25]	吴必虎, 唐俊雅, 黄安民 , 等. 中国城市居民旅游目的地选择行为研究. 地理学报, 1997,52(2):97-103.
	[ Wu Bihu, Tang Junya, Huang Anmin , et al. A study on destination choice behavior of Chinese urban residents. Acta Geographica Sinica, 1997,52(2):97-103.]
[26]	陆林 . 山岳风景区旅游者空间行为研究: 兼论黄山与美国黄石公园之比较. 地理学报, 1996,51(4):315-321.
	[ Lu Lin . A study on the spatial behavior of tourists in mountain resorts: Giving consideration to comparison of the travelling spatial behavior between tourists in Huangshan Mountain and in Yellowstone Park. Acta Geographica Sinica, 1996,51(4):315-321.]
[27]	杨新军, 牛栋, 吴必虎 . 旅游行为空间模式及其评价. 经济地理, 2000,20(4):105-117.
	[ Yang Xinjun, Niu Dong, Wu Bihu . Spatial models and their assessment on regional tourist behavior. Economic Geography, 2000,20(4):105-117.]
[28]	吴必虎 . 上海城市游憩者流动行为研究. 地理学报, 1994,49(2):117-127.
	[ Wu Bihu . A research on urban recreationists' traveling behavior in Shanghai. Acta Geographica Sinica, 1994,49(2):117-127.]
[29]	张捷, 李升峰, 周寅康 , 等. 九寨沟风景区游客入游距离特征研究. 长江流域资源与环境, 2002,11(1):5-9.
	[ Zhang Jie, Li Shengfeng, Zhou Yinkang , et al. Distance characteristics of tourist travel behavior in Jiuzhaigou district, Sichuan, China. Resources and Environment in the Yangtze Basin, 2002,11(1):5-9.]
[30]	吴晋峰, 潘旭莉 . 京沪入境旅游流网络结构特征分析. 地理科学, 2010,30(3):370-376.
	[ Wu Jinfeng, Pan Xuli . Characteristic of Beijing and Shanghai inbound tourists flow network. Scientia Geographica Sinica, 2010,30(3):370-376.]
[31]	唐澜, 吴晋峰 . 中国入境观光休闲旅游流空间结构与流动特征. 经济管理, 2013,35(10):130-142.
	[ Tang Lan, Wu Jinfeng . Research on the spatial structure and flow characteristic of Chinese inbound sightseeing and leisure tourist flows. Economic Management, 2013,35(10):130-142.]
[32]	杨新菊, 吴晋峰, 唐澜, 王金莹 . 旅华外国散客旅游流地理分布和网络结构研究. 旅游学刊, 2014,29(5):87-96. doi: 10.3969/j.issn.1002-5006.2014.05.0091
	[ Yang Xinju, Wu Jinfeng, Tang Lan , et al. The geographical distribution and network structure of foreign independent tourist flows in China. Tourism Tribune, 2014,29(5):87-96.]
[33]	查晓莉, 徐雨晨, 陆林 , 等. 上海迪士尼国内旅游流地理分布与流动特征. 旅游学刊, 2019,34(6):59-73.
	[ Zha Xiaoli, Xu Yuchen, Lu Lin , et al. Geographical distribution and flows of Chinese visitors to Shanghai Disneyland. Tourism Tribune, 2019,34(6):59-73.]
[34]	Guillem Vich, Oriol Marquet, Carme Miralles-Guasch. Suburban commuting and activity spaces: Using smartphone tracking data to understand the spatial extent of travel behavior. Geographical Journal, 2017,183(4):426-439. doi: 10.1111/geoj.2017.183.issue-4
[35]	Mei-Po Kwan, Alexander Kotsev. Gender differences in commute time and accessibility in Sofia, Bulgaria: A study using 3D geovisualisation. The Geographical Journal, 2015,181(1):83-96. doi: 10.1111/geoj.2015.181.issue-1
[36]	Geoffery Wall. Socio-economic variations in pleasure-trip patterns: The case of hull car-owners. Transactions of the Institute of British Geographers, 1972,1999(57):45-58.
[37]	Hsin-Yu Shih. Network characteristics of drive tourism destinations: An application of network analysis in tourism. Tourism Management, 2006,27(5):1029-1039. doi: 10.1016/j.tourman.2005.08.002
[38]	张晓燕, 张善芹, 马勋 . 中国自驾车旅游者行为研究: 以华北地区为例. 旅游学刊, 2006,21(9):31-35.
	[ Zhang Xiaoyan, Zhang Shanqin, Ma Xun . A study on the behavior of self-driving tourists in China. Tourism Tribune, 2006,21(9):31-35.]
[39]	冯淑华 . 自驾车旅游者的行为特征及空间效应分析. 旅游学刊, 2008,23(9):34-38.
	[ Feng Shuhua . Study on behavorial characteristics of self-driving tourists and their spatial effect. Tourism Tribune, 2008,23(9):34-38.]
[40]	Liu Yaping, Zhang Yu, Nie Linlin. Patterns of self-drive tourists: The case of Nanning city, China. Tourism Management, 2012,33(1):225-227. doi: 10.1016/j.tourman.2011.01.025
[41]	卢松, 吉慧, 蔡云峰 . 黄山市自驾车入游流旅行空间行为研究. 地理研究, 2013,32(1):179-190. doi: 10.11821/yj2013010018
	[ Lu Song, Ji Hui, Cai Yunfeng . A study on the spatial travel behavior of self-driving tourists into Huangshan city. Geographical Research, 2013,32(1):179-190.]
[42]	罗秋菊, 梁思贤 . 基于数字足迹的自驾车旅游客流时空特征研究: 以云南省为例. 旅游学刊, 2016,31(12):41-50. doi: 10.3969/j.issn.1002-5006.2016.12.011
	[ Luo Qiuju, Liang Sixian . Temporal and spatial characteristics of self-driving tourist flows based on tourism digital footprints: A case study in Yunnan province. Tourism Tribune, 2016,31(12):41-50.]
[43]	娄思元, 明庆忠, 陈颖 , 等. 自驾旅游线路分类空间功能分析: 以保山、德宏两地为例. 经济地理, 2018,38(3):217-224.
	[ Lou Siyuan, Ming Qingzhong, Chen Ying , et al. The function of self-driving tour routes' classification spaces: A case study of Baoshan and Dehong. Economic Geography, 2018,38(3):217-224.]
[44]	张文奎 . 行为地理学研究的基本理论问题. 地理科学, 1990,10(2):159-167.
	[ Zhang Wenkui . On some basic theoretical problems in behavioral geography. Scientia Geographica Sinica, 1990,10(2):159-167.]
[45]	戴斌 . 需求驱动景区创新发展. 中国文化报, 2014-09-27(001).
	[ Dai Bin . Demand drives the innovative development of scenic spots. China Culture Daily, 2014-09-27(001).]
[46]	贾垚焱, 胡静, 刘大均 , 等. 长江中游城市群A级旅游景区空间演化及影响机理研究. 经济地理, 2019,39(1):201-209.
	[ Jia Yaoyan, Hu Jing, Liu Dajun , et al. Spatial evolution and influence mechanism of A-Level scenic spots in urban agglomeration in the middle reaches of the Yangtze River. Economic Geography, 2019,39(1):201-209.]
[47]	周芳如, 吴晋峰, 吴潘 , 等. 中国主要入境旅游城市交通通达性对比研究. 旅游学刊, 2016,31(2):12-22. doi: 10.3969/j.issn.1002-5006.2016.02.007
	[ Zhou Fangru, Wu Jinfeng, Wu Pan , et al. Comparative study on traffic accessibility of major inbound tourist cities in China. Tourism Tribune, 2016,31(2):12-22.]
[48]	旅游规划观察. 途牛: 2018年中国西部自驾游发展报告. https://mp.weixin.qq.com/s/pzeW-hMFvgbdHe6_LRNoWQ, 2018-11-01.
	[ Tourism Planning Observation. Tuniu: Development Report of self-drive tourism in Western China in 2018. https://mp.weixin.qq.com/s/pzeW-hMFvgbdHe6_LRNoWQ, 2018-11-01.]
[49]	在线旅讯.驴妈妈发布《2018中国自驾游报告》, 周边自驾愈发高频、房车自驾人气火爆. https://mp.weixin.qq.com/s/oRoqSvYRN_ZZkZID6BMesg, 2018-03-31.
	[ Online travel news. Online travel news. Lvmama released "China Road Trip Report 2018", self-drive in the surrounding area has become increasingly frequent and RV self-drive has become popular. https://mp.weixin.qq.com/s/oRoqSvYRN_ZZkZID6BMesg, 2018-03-31.]
[50]	Yingling Fan, Asad Khattak. Urban form, individual spatial footprints, and travel: Examination of space-use behavior. Journal of the Transportation Research Board, 2008,2082:98-106. doi: 10.3141/2082-12
[51]	Stefan Schonfelder, Kay Axhausen. Activity spaces: Measures of social exclusion?. Transport Policy, 2003,10(4):273-286. doi: 10.1016/j.tranpol.2003.07.002
[52]	Ron Buliung, Pavlos Kanaroglou. Urban form and household activity-travel behavior. Growth and Change, 2006,37(2):172-199. doi: 10.1111/grow.2006.37.issue-2
[54]	Shannon Zenk, Amy Schulz, Stephen Matthews, et al. Activity space environment and dietary and physical activity behaviors: A pilot study. Health and Place, 2011,17(5):1150-1161.
	李山, 王慧, 王铮 . 中国国内观光旅游线路设计中的游时研究. 人文地理, 2005,20(2):51-56.
	[ Li Shan, Wang Hui, Wang Zheng . A study on tour time planning of domestic sightseeing travel itineraries. Human Geography, 2005,20(2):51-56.]
[55]	王小霞 . 中国经济高速增长还将持续20年: 访国务院发展研究中心宏观经济研究部部长余斌. 中小企业管理与科技, 2010, (8):50-53.
	[ Wang Xiaoxia . China's rapid economic growth will continue for another 20 years: Visiting Yu Bin, director of macroeconomic research department, development research center of the state council. SME Management and Technology, 2010, (8):50-53.]
[56]	Gunvor Larsen, Jo Guiver. Understanding tourists' perceptions of distance: A key to reducing the environmental impacts of tourism mobility. Journal of Sustainable Tourism, 2013,21(7):968-981. doi: 10.1080/09669582.2013.819878

调查项目		北京	西安	武汉	调查项目		北京	西安	武汉
性别	男	39.72	40.52	39.94	职业	事业单位人员	11.41	10.72	8.47
	女	53.15	51.02	50.82		教师	4.72	7.56	3.08
	未填写	7.13	8.46	9.24		学生	19.64	24.60	28.39
婚姻	未婚	44.87	43.56	57.84		公务员	1.93	2.26	1.64
	已婚	38.18	42.44	24.74		企业人员		26.82	21.67	23.67
	未填写	16.95	14.00	17.42	私企老板		2.65	1.58	0.96
年龄	≤ 17岁	5.19	3.39	2.60	服务业人员	4.48	6.21	4.62
	18~27岁	47.14	43.57	62.46	自由职业者		12.57	9.71	12.03
	28~37岁	30.81	32.73	22.44	退休		1.49	2.26	1.83
	38~47岁	10.54	10.27	6.35	其他		11.98	10.16	11.65
	48~57岁	2.99	5.64	2.21	未填写		2.31	3.27	3.66
	58~67岁	1.40	1.81	1.06	每月收入	≤ 1500元	4.09	8.69	6.06
	≥ 68岁	0.53	0.56	1.15		1500~4500元	13.24	29.91	28.10
	未填写	1.40	2.03	1.73		4500~9000元	33.80	30.02	26.28
教育程度	初中及以下	3.66	5.30	2.60		9000~35000元	24.60	10.05	6.83
	高中	8.67	9.14	9.82	35000~55000元		1.65	0.23	0.87
	大专	16.13	21.78	22.91	55000~80000元		0.91	0.22	0.48
	本科	52.19	40.41	50.53	≥ 80000元		0.63	0.23	0.67
	研究生	16.42	20.32	10.68	无收入		14.68	14.67	20.12
	未填写	2.93	3.05	3.46	未填写		6.40	5.98	10.59

目标景区	北京	西安	武汉
非共同景区	安庆天柱山、安新白洋淀、大理崇圣寺三塔、济南天下第一泉、天津古文化街、武隆喀斯特、西安兵马俑、西安钟楼、忻州雁门关、尧山-中原大佛	安庆天柱山、池州九华山、衡山、商洛金丝峡、嵩山少林寺、武隆喀斯特、榆林红碱淖	鄂州莲花山、池州九华山、衡山、咸宁赤壁古战场、天津古文化街、商洛金丝峡、嵩山少林寺、榆林红碱淖
共同景区	阿坝九寨沟、阿勒泰喀纳斯、安顺黄果树、八达岭长城、巴丹吉林沙漠、巴州博斯腾湖、包头敕勒川、宝鸡法门寺、北京故宫、成都青城山、承德避暑山庄、大连金石滩、大同云冈石窟、大足石刻、迪庆香格里拉、东方明珠、敦煌鸣沙山、鄂尔多斯成吉思汗陵、甘南草原、广州白云山、贵阳多彩贵州城、桂林漓江、哈尔滨太阳岛、哈密巴里坤古城景区、海北州青海湖、汉中武侯祠、杭州西湖、洪桐大槐树、黄山、吉安井冈山、焦作云台山、九江庐山、喀什噶尔老城、拉萨布达拉宫、乐山峨眉山、洛阳龙门石窟、满洲里中俄边境、漠河北极村、南昌滕王阁、南京中山陵、南宁青秀山、平遥古城、秦皇岛北戴河、青岛崂山、曲阜三孔、三亚天涯海角、厦门鼓浪屿、韶山、深圳华侨城、神农架、沈阳故宫、十堰武当山、石家庄西柏坡、苏州园林、太行大峡谷、太原晋祠、泰安泰山、天水麦积山石窟、吐鲁番葡萄沟、渭南华山、乌鲁木齐天山天池景区、武汉黄鹤楼、武夷山、西宁塔尔寺、西双版纳、忻州五台山、烟台蓬莱阁、延安宝塔山、伊春汤旺河、银川沙湖、张家界、张掖丹霞景区、长春净月潭、舟山普陀山、遵义会议会址

舒适时间(h)	比例(%)	疲惫时间(h)	比例(%)
<3	34.3	>3	17.2
<4	21.4	>4	15.3
<5	16.9	>5	16.3
<6	14.9	>6	19.6
<7	1.9	>7	8.4
<8	5.8	>8	12.5
<9	0.5	>9	2.1
<10	4.4	>10	8.5