SPATIAL PATTERN AND FORMING MECHANISM OF NEW TOURISM RETAIL IN CTRIP: A CASE STUDY OF OFFLINE STORES IN SHANGHAI
WANG Juan1,2, DING Xuan-wen1
1. College of Management, Ocean University of China, Qingdao 266100, China;
2. Institute of Marine Development, Ocean University of China, Qingdao 266100, China
Abstract:Based on Ctrip's offline stores in Shanghai and 37272 relevant point of interest (POI) data captured from Gaode map developer platform, this study comprehensively used the spatial analysis methods such as Standard Deviation Ellipse, Average Nearest Neighbor, Thiessen Polygon, Kernel Density Estimation and GeoDetector to explore the spatial pattern, location choice and formation mechanism of new tourism retail in Ctrip. The results showed that: 1) At the initial stage of development, new tourism retail in Ctrip still prefers the central location, but the demand for the central location of the city is not as strong as that of the traditional retail industry, and the trend of subsidence is obvious to the edge of the city center and the suburbs; 2) The offline stores of Ctrip show an agglomerative spatial distribution type and form a "multi center - outward expansion" distribution pattern. But they are clustered on a larger spatial scale, with a significant centrifugal trend; 3) The location choice of new tourism retail depends on the offline life service scenes of the target market dominated by office buildings. Compared with the traditional retail industry, the preference for highdensity areas of office buildings exceeds that of high-density areas of shopping malls. Traffic conditions, spatial distribution of traditional travel agencies, and the level of rent take the second place, CBD approach degree and business district grade have less influence; 4) The spatial pattern and location characteristics of Ctrip's offline stores are the result of the joint action of enterprise business segment planning, geographical entity space competition and regional industrial supporting level.
王娟, 丁宣文. 携程旅行网旅游“新零售”空间格局及形成机制——以上海市线下门店为例[J]. 人文地理, 2022, 37(5): 183-192.
WANG Juan, DING Xuan-wen. SPATIAL PATTERN AND FORMING MECHANISM OF NEW TOURISM RETAIL IN CTRIP: A CASE STUDY OF OFFLINE STORES IN SHANGHAI. HUMAN GEOGRAPHY, 2022, 37(5): 183-192.
杜睿云,蒋侃.新零售:内涵、发展动因与关键问题[J].价格理论与实践,2017(2):139-141. [Du Ruiyun, Jiang Kan. New retailing: Connotation, development impetus and key problems[J]. Price: Theory & Practice, 2017(2):139-141.]
[2]
林玥希,汪明峰.中国新零售的空间分布与区位选择[J].经济地理, 2020,40(12):109-118. [Lin Yuexi, Wang Mingfeng. Spatial distribution and location strategy of the "new retail" in China[J]. Economic Geography, 2020,40(12):109-118.]
[3]
金安楠,李钢,王建坡,等.社区化新零售的布局选址与优化发展研究——以南京市盒马鲜生为例[J]. 地理科学进展,2020,39(12): 2013-2027. [Jin Annan, Li Gang, Wang Jianpo, et al. Location choice and optimization of development of community-oriented new retail stores: A case study of Freshippo stores in Nanjing city [J]. Progress in Geography, 2020,39(12):2013-2027.]
[4]
汪凡,林玥希,汪明峰.第三空间还是无限场景:新零售的区位选择与影响因素研究[J]. 地理科学进展,2020,39(9):1522-1531. [Wang Fan, Lin Yuexi, Wang Mingfeng. "Third space" or "infinite occasion": Location choice and influencing factors of the new retail industry[J]. Progress in Geography, 2020,39(9):1522-1531.]
[5]
张建军,赵启兰. 新零售驱动下流通供应链商业模式转型升级研究[J].商业经济与管理,2018(11):5-15. [Zhang Jianjun, Zhao Qilan. Transformation and upgrading of the business model of the circulation supply chain driven by "new retail"[J]. Journal of Business Economics, 2018(11):5-15.]
[6]
孙大尉,赵启兰,张小蒙.新零售业态下物流平台运营策略研究[J]. 北京交通大学学报(社会科学版),2019,18(3):138-144. [Sun Dawei, Zhao Qilan, Zhang Xiaomeng. A study of operation strategy for logistics platform under the new retail[J]. Journal of Beijing Jiaotong University(Social Sciences Edition), 2019,18(3):138-144.]
[7]
狄蓉,曹静,赵袁军.旅游“新零售”背景下在线旅游运营模式——以携程旅行网为例[J].中国流通经济,2019,33(7):45-52. [Di Rong, Cao Jing, Zhao Yuanjun. Research on the operational model of online tourism (OTA) under the background of new retail tourism: A case study of Ctrip[J]. China Business and Market, 2019,33(7):45-52.]
[8]
刘向东,刘雨诗,陈成漳.数字经济时代连锁零售商的空间扩张与竞争机制创新[J]. 中国工业经济,2019(5):80-98. [Liu Xiangdong, Liu Yushi, Chen Chengzhang. Space expansion and competition mechanism innovation of chain retailers in the age of digital economy[J]. China Industrial Economics, 2019(5):80-98.]
[9]
崔璐明,曲凌雁,何丹. 基于深度学习的城市热点空间情绪感知评价——以上海市为例[J].人文地理,2021,36(5):121-130,176. [Cui Luming, Qu Lingyan, He Dan. Evaluating emotional perception of spatial hotspots via deep learning: A case study of Shanghai[J]. Human Geography, 2021,36(5):121-130,176.]
[10]
何伟纯,李二玲,崔之珍,等.开封市主城区零售商业空间布局及其影响因素[J]. 经济地理,2018,38(9):158-167. [He Weichun, Li Erling, Cui Zhizhen, et al. Spatial layout and influencing factors of commercial retail in main urban districts of Kaifeng[J]. Economic Geography, 2018,38(9):158-167.]
[11]
高岩辉,杨晴青,梁璐,等.基于POI数据的西安市零售业空间格局及影响因素研究[J]. 地理科学,2020,40(5):710-719. [Gao Yanhui, Yang Qingqing, Liang Lu, et al. Spatial pattern and influencing factors of retailing industries in Xi'an based on POI data[J]. Scientia Geographica Sinica, 2020,40(5):710-719.]
[12]
张绍云,周忠发,熊康宁,等. 贵州洞穴空间格局及影响因素分析[J]. 地理学报, 2016, 71(11): 1998-2009. [Zhang Shaoyun, Zhou Zhongfa, Xiong Kangning, et al. Spatial pattern of the caves in Guizhou province and their the influencing factors[J]. Acta Geographica Sinica, 2016,71(11):1998-2009.]
[13]
Duyckaerts C, Godefroy G. Voronoi tessellation to study the numerical density and the spatial distribution of neurons[J]. Journal of Chemical Neuroanatomy, 2000,20(1):83-92.
[14]
李哲,申玉铭. 北京市零售业空间格局研究[J]. 城市发展研究, 2018, 25(6): 64-70, 181. [Li Zhe, Shen Yuming. Research on retail sector spatial pattern in Beijing[J]. Urban Development Studies, 2018,25(6):64-70,181.]
Fang Y, Mao J Y, Liu Q H, et al. Exploratory space data analysis of spatial patterns of large-scale retail commercial facilities: The case of Gulou district, Nanjing, China[J]. Frontiers of Architectural Research, 2021,10(1):17-32.
[17]
Geng L, Chen X X, Liang Y T. The location of retail stores and street centrality in Guangzhou, China[J]. Applied Geography, 2018, 100:12-20.
[18]
李莉,侯国林,夏四友,等.成都市休闲旅游资源空间分布特征及影响因素[J].自然资源学报,2020,35(3):683-697. [Li Li, Hou Guolin, Xia Siyou, et al. Spatial distribution characteristics and influencing factors of leisure tourism resources in Chengdu[J]. Journal of Natural Resources, 2020,35(3):683-697.]
[19]
Nilsson I M, Smirnov O A. Clustering vs. relative location: Measuring spatial interaction between retail outlets[J]. Papers in Regional Science, 2017,96(4):721-741.
[20]
张英浩,汪明峰.新零售背景下连锁店区位选择及其空间关联特征[J].热带地理,2021,41(3):573-583. [Zhang Yinghao, Wang Mingfeng. Location selection and correlation characteristics of chain stores against the background of new retail[J]. Tropical Geography, 2021,41(3):573-583.]
[21]
李维维,马晓龙.中国大城市旅游休闲业态的空间格局研究:西安案例[J].人文地理,2019,34(6):153-160. [Li Weiwei, Ma Xiaolong. Spatial pattern and mechanisms of the tourism and leisure industry in China's big cities: A case study of Xi'an[J]. Human Geography, 2019,34(6):153-160.]
[22]
史坤博,杨永春,杨欣傲,等.时间成本是否成为电子商务区位的核心机制——基于成都市O2O电子商务的实证分析[J].地理学报, 2016,71(3):500-514. [Shi Kunbo, Yang Yongchun, Yang Xin'ao, et al. Does time dictate the location of e-commerce business? A study of O2O businesses in Chengdu, China[J]. Acta Geographica Sinica, 2016,71(3):500-514.]
[23]
张逸姬,甄峰,张逸群. 社区O2O零售业的空间特征及影响因素——以南京市为例[J]. 经济地理,2019,39(11):104-112. [Zhang Yiji, Zhen Feng, Zhang Yiqun. Adoption of O2O strategies by community retailers in Nanjing[J]. Economic Geography, 2019,39(11): 104-112.]
[24]
胡志毅,朱康文,李月臣,等.重庆都市区传统旅行社空间竞争格局研究[J]. 旅游学刊,2017,32(8):70-80. [Hu Zhiyi, Zhu Kangwen, Li Yuechen, et al. A study of traditional travel agencies' spatial competition in Chongqing metropolitan area[J]. Tourism Tribune, 2017, 32(8):70-80.]
[25]
江曼琦.对西方竞标地租理论的几点认识[J].南开经济研究,1997(6): 42-45. [Jiang Manqi. Understanding of Western bidding land rent theory[J]. Nankai Economic Studies, 1997(6):42-45.]
[26]
王永明,王美霞,吴殿廷,等.贵州省乡村贫困空间格局与形成机制分析[J]. 地理科学,2017,37(2):217-227. [Wang Yongming, Wang Meixia, Wu Dianting, et al. Spatial patterns and determinants of rural poverty: A case of Guizhou province, China[J]. Scientia Geographica Sinica, 2017,37(2):217-227.]
[27]
谭华云,许春晓.舒适移民型乡村绅士化空间格局及其形成机制——以广西巴马盘阳河流域为例[J].旅游学刊,2021,36(2):40-53. [Tan Huayun, Xu Chunxiao. The spatial pattern and formation mechanism of amenity migration-based rural gentrification: A case study of Panyang River Basin of Bama in Guangxi[J]. Tourism Tribune, 2021,36(2):40-53.]
[28]
王培家,章锦河,孙枫,等.中国西南地区传统村落空间分布特征及其影响机理[J].经济地理, 2021, 41(9): 204-213. [Wang Peijia, Zhang Jinhe, Sun Feng, et al. Spatial distribution and the impact mechanism of traditional villages in Southwest China[J]. Economic Geography, 2021,41(9):204-213.]
[29]
周春山,童新梅,王珏晗,等.2000—2010年广州市人口老龄化空间分异及形成机制[J]. 地理研究,2018,37(1):103-118. [Zhou Chunshan, Tong Xinmei, Wang Juehan, et al. Spatial differentiation and the formation mechanism of population aging in Guangzhou in 2000—2010[J]. Geographical Research, 2018,37(1):103-118.]
[30]
刘汉初,周侃,卢明华. 重点开发区域工业空间格局、集疏差异及影响机制——以福建沿海地区为例[J].人文地理,2020,35(1):85-94. [Liu Hanchu, Zhou Kan, Lu Minghua. Industrial spatial pattern, agglomeration difference and impact mechanism of developmentprioritized zone: A case study of coastal area in Fujian province[J]. Human Geography, 2020,35(1):85-94.]
[31]
王娟,杨晨.中国旅游集团业务布局特征与形成机制研究[J].旅游学刊,2019,34(8):53-64. [Wang Juan, Yang Chen. A study on business distribution and the growth of China national travel service group corporation[J]. Tourism Tribune, 2019,34(8):53-64.]
[32]
谢赤,樊明雪,胡扬斌. 创新型企业成长性、企业价值及其关系研究[J]. 湖南大学学报(社会科学版),2018,32(5):58-64. [Xie Chi, Fan Mingxue, Hu Yangbin. A study on the growth, the enterprise value and their relationship of innovative enterprises[J]. Journal of Hunan University(Social Sciences), 2018,32(5):58-64.]
[33]
徐海峰,陈存欣.企业成长性对研发投入的影响研究[J].科学管理研究,2019,37(3):115-118. [Xu Haifeng, Chen Cunxin. Research on the impact of company growth to R&D investment[J]. Scientific Management Research, 2019,37(3):115-118.]
[34]
白光润. 微区位研究的新思维[J].人文地理,2004,19(5):85-88. [Bai Guangrun. New notion of micro-location research[J]. Human Geography, 2004,19(5):85-88.]
[35]
Mulligan G F. Agglomeration and central place theory: A review of the literature[J]. International Regional Science Review, 1984,9(1): 1-42.