基于网络热度的武汉市餐饮业类型与空间异质性
|
摘要
"网红经济"是一类城市商业新业态,而"网红"餐饮业类型与空间布局的探究相对较少.因此该文以大众点评网提供的武汉市餐饮业热点为研究对象,搜集统计地理区位、评价等级和经营模式等指标数据,利用聚类分析法将"网红"餐饮业分为6大类型并进行特征分析,利用核密度分析、最邻近距离法研究其空间分布特征.发现大部分"网红"餐饮业网点位于客流量较高,交通通达度较好的城市中心商圈附近,同时普遍有着良好口碑,而消费者有着较高的消费热情但也没有迷信品牌.从而给"网红经济"的发展和城市商业格局优化提供参考建议.
"Internet celebrity economy" is one of the new urban commercial activities, while there is little research on the classification and spatial heterogeneity of it. Taking Wuhan catering hotspots provided by dianping.com as the research carrier, the classification factors of location, comments and business models were collected. The "Internet celebrity" catering industry were divided into 6 kinds by cluster analysis. Methods of k-nearest neighbors algorithm and kernel density estimation were utilized to clarify the spatial heterogeneity. It is concluded that most of the "Internet celebrity" restaurants are located in central commercial districts with high passenger flow and good transportation accessibility. These restaurants are generally highly recommended. Customers with relatively high enthusiasm do not have blind faith in brands. We also provided some suggestions on developing "Internet celebrity economy" and optimizing urban business layout.
"Internet celebrity economy" is one of the new urban commercial activities, while there is little research on the classification and spatial heterogeneity of it. Taking Wuhan catering hotspots provided by dianping.com as the research carrier, the classification factors of location, comments and business models were collected. The "Internet celebrity" catering industry were divided into 6 kinds by cluster analysis. Methods of k-nearest neighbors algorithm and kernel density estimation were utilized to clarify the spatial heterogeneity. It is concluded that most of the "Internet celebrity" restaurants are located in central commercial districts with high passenger flow and good transportation accessibility. These restaurants are generally highly recommended. Customers with relatively high enthusiasm do not have blind faith in brands. We also provided some suggestions on developing "Internet celebrity economy" and optimizing urban business layout.
引文
[1] 祝合良,王明雁.消费思维转变驱动下的商业模式创新——基于互联网经济的分析[J].商业研究,2017(9):7-13.ZHU H L,WANG M Y.Business model innovation driven by consumption thinking transformation:An analysis based on Internet economy[J].Commercial Research,2017(9):7-13.(Ch).
[2] CHEN J L,LI K,CHEUNG W K,et al.Effective successive POI recommendation inferred with individual behavior and group preference [J].Neurocomputing,2017,6(3):80.
[3] BARAL R,LI T.Exploiting the roles of aspects in personalized POI recommender systems [J].Data Mining and Knowledge Discovery,2018,32(2):320-343.
[4] ZHANG Z Y,LIU Y,ZHANG Z J,et al.Fused matrix factorization with multi-tag,social and geographical influences for POI recommendation [J].World Wide Web,2018,5(1):1-16.
[5] 倪晔刚.虚拟社区中第三方评价模式对消费者购买意愿的影响研究[D].上海:复旦大学,2008.NI Y G.How the Third-Party Comments Affecting the Customers' Purchase Intention [D].Shanghai:Fudan University,2008.(Ch).
[6] 张子坤.在线点评平台如何影响人们的消费行为?一个信息性社会影响的观点[D].北京:中国科学技术大学,2010.ZHANG Z K.How do Online Review Platforms Affect Individuals' Consumption Behavior?An Informational Social Influence Perspective [D].Beijing:University of Science and Techonology of China,2010.(Ch).
[7] 李启瑄,王录仓,乔杰,等.“物象·意象、经济·情感”新数据环境的餐饮业空间特征——以兰州市为例[J].经济地理,2018,38(7):126-135.LI Q X,WANG C L,QIAO J,et al.“Object·Image,Economic·Feelings” research on catering spatial pattern by newdata:take Lanzhou as an example [J].Economic Geography,2018,38(07):126-135.(Ch).
[8] 夏令军,刘艳芳,刘国炜.中国地级城市餐饮业分布格局及影响因素——基于“大众点评网”数据的实证研究[J].经济地理,2018,38(5):133-141.XIA L J,LIU Y F,LIU G W.Spatial distribution pattern and influencing factors of catering industry in prefecture level and above cities in China:An empirical study based on the Dianping.com data [J].Economic Geography,2018,38(5):133-141.(Ch).
[9] 张莹,李全.武汉市主城区餐饮业空间特征及与动态人口的耦合分析[J].华中师范大学学报(自然科学版),2019,53(1):121-129.ZHANG Y,LI Q.The spatial characters of catering industry and its coupling analysis with dynamic population in the main city of Wuhan [J].Journal of Central China Normal University (Natural Sciences),2019,53(1):121-129.(Ch).
[10] KELLEY M J.The emergent urban imaginaries of geosocial media [J].Geo Journal,2013,78(1):181-230.
[11] TELLER C,REUTTERER T.The evolving concept of retail attractiveness:What makes retail agglomerations attractive when customers shop at them?[J].Journal of Retailing and Consumer Services,2008,15(3):127-143.
[12] DOLEGA L,PAVLIS M,SINGLETON A.Estimating attractiveness,hierarchy and catchment area extents for a national set of retail centre agglomerations [J].Journal of Retailing and Consumer Services,2016,28:78-90.
[13] YANG T R,PAN H Z,HEWINGS G,et al.Understanding urban sub-centers with heterogeneity in agglomeration economies—Where do emerging commercial establishments locate?[J].Cities,2019,86:25-36.
[14] 王明.基于位置签到数据的城市地标提取与商圏挖掘研究[D].武汉:武汉大学,2015.WANG M.Research on Urban Landmark Extracting and Commercial Area Mining with Check-in Data [D].Wuhan:Wuhan University,2015.(Ch).
[15] 秦萧,甄峰,朱寿佳,等.基于网络口碑度的南京城区餐饮业空间分布格局研究——以大众点评网为例[J].地理科学,2014,34(7):810-817.QIN X,ZHEN F,ZHU J S,et al.Spatial pattern of catering industry in Nanjing urban area based on the degree of public praise from Internet:A case study of Dianping.com [J].Scientia Geographica Sinica,2014,34(07):810-817.(Ch).
[16] NGUYEN Q C,MENG H,LI D,et al.Social media indicators of the food environment and state health outcomes [J].Public Health,2017,148(7):120-128.
[17] 许宽.基于网络评价的长沙城区餐饮业空间分布研究[D].长沙:湖南师范大学,2016.XU K.The Study of Space Distribution of Catering Trade in Changsha Urban Area Based on Online Review [D].Changsha:Hunan Normal University,2016.(Ch).
[18] 卢向华,冯越.网络口碑的价值——基于在线餐馆点评的实证研究[J].管理世界,2009(7):126-132,171.LU X H,FENG Y.The value of the online word-of-mouth:demonstration of online restaurants' comments [J].Management World,2009(7):126-132,171.(Ch).
[2] CHEN J L,LI K,CHEUNG W K,et al.Effective successive POI recommendation inferred with individual behavior and group preference [J].Neurocomputing,2017,6(3):80.
[3] BARAL R,LI T.Exploiting the roles of aspects in personalized POI recommender systems [J].Data Mining and Knowledge Discovery,2018,32(2):320-343.
[4] ZHANG Z Y,LIU Y,ZHANG Z J,et al.Fused matrix factorization with multi-tag,social and geographical influences for POI recommendation [J].World Wide Web,2018,5(1):1-16.
[5] 倪晔刚.虚拟社区中第三方评价模式对消费者购买意愿的影响研究[D].上海:复旦大学,2008.NI Y G.How the Third-Party Comments Affecting the Customers' Purchase Intention [D].Shanghai:Fudan University,2008.(Ch).
[6] 张子坤.在线点评平台如何影响人们的消费行为?一个信息性社会影响的观点[D].北京:中国科学技术大学,2010.ZHANG Z K.How do Online Review Platforms Affect Individuals' Consumption Behavior?An Informational Social Influence Perspective [D].Beijing:University of Science and Techonology of China,2010.(Ch).
[7] 李启瑄,王录仓,乔杰,等.“物象·意象、经济·情感”新数据环境的餐饮业空间特征——以兰州市为例[J].经济地理,2018,38(7):126-135.LI Q X,WANG C L,QIAO J,et al.“Object·Image,Economic·Feelings” research on catering spatial pattern by newdata:take Lanzhou as an example [J].Economic Geography,2018,38(07):126-135.(Ch).
[8] 夏令军,刘艳芳,刘国炜.中国地级城市餐饮业分布格局及影响因素——基于“大众点评网”数据的实证研究[J].经济地理,2018,38(5):133-141.XIA L J,LIU Y F,LIU G W.Spatial distribution pattern and influencing factors of catering industry in prefecture level and above cities in China:An empirical study based on the Dianping.com data [J].Economic Geography,2018,38(5):133-141.(Ch).
[9] 张莹,李全.武汉市主城区餐饮业空间特征及与动态人口的耦合分析[J].华中师范大学学报(自然科学版),2019,53(1):121-129.ZHANG Y,LI Q.The spatial characters of catering industry and its coupling analysis with dynamic population in the main city of Wuhan [J].Journal of Central China Normal University (Natural Sciences),2019,53(1):121-129.(Ch).
[10] KELLEY M J.The emergent urban imaginaries of geosocial media [J].Geo Journal,2013,78(1):181-230.
[11] TELLER C,REUTTERER T.The evolving concept of retail attractiveness:What makes retail agglomerations attractive when customers shop at them?[J].Journal of Retailing and Consumer Services,2008,15(3):127-143.
[12] DOLEGA L,PAVLIS M,SINGLETON A.Estimating attractiveness,hierarchy and catchment area extents for a national set of retail centre agglomerations [J].Journal of Retailing and Consumer Services,2016,28:78-90.
[13] YANG T R,PAN H Z,HEWINGS G,et al.Understanding urban sub-centers with heterogeneity in agglomeration economies—Where do emerging commercial establishments locate?[J].Cities,2019,86:25-36.
[14] 王明.基于位置签到数据的城市地标提取与商圏挖掘研究[D].武汉:武汉大学,2015.WANG M.Research on Urban Landmark Extracting and Commercial Area Mining with Check-in Data [D].Wuhan:Wuhan University,2015.(Ch).
[15] 秦萧,甄峰,朱寿佳,等.基于网络口碑度的南京城区餐饮业空间分布格局研究——以大众点评网为例[J].地理科学,2014,34(7):810-817.QIN X,ZHEN F,ZHU J S,et al.Spatial pattern of catering industry in Nanjing urban area based on the degree of public praise from Internet:A case study of Dianping.com [J].Scientia Geographica Sinica,2014,34(07):810-817.(Ch).
[16] NGUYEN Q C,MENG H,LI D,et al.Social media indicators of the food environment and state health outcomes [J].Public Health,2017,148(7):120-128.
[17] 许宽.基于网络评价的长沙城区餐饮业空间分布研究[D].长沙:湖南师范大学,2016.XU K.The Study of Space Distribution of Catering Trade in Changsha Urban Area Based on Online Review [D].Changsha:Hunan Normal University,2016.(Ch).
[18] 卢向华,冯越.网络口碑的价值——基于在线餐馆点评的实证研究[J].管理世界,2009(7):126-132,171.LU X H,FENG Y.The value of the online word-of-mouth:demonstration of online restaurants' comments [J].Management World,2009(7):126-132,171.(Ch).