摘要
在"流动空间"背景下,城市网络中次级城市受到区域经济研究的关注。区域内部及跨区域联系对次级城市发展的作用关系到城市区际合作的成败,但对其认识存在差异。以行业结构作为切入点,基于机器学习行业分类后的工商企业数据,研究哈尔滨与东北地区城市联系的总量变化及行业特征,发现:(1)哈尔滨的内向经济联系中,东北地区城市的重要性在减退,其外向网络腹地范围正在缩小;(2)哈尔滨与东北地区的产业联系有制造业联系下降及服务业低端化的趋势;(3)与全国相比,东北地区内部缺乏"服务中心"。通过研究哈尔滨与东北地区以外城市联系与距离、地区生产总值(GRP)等的关系,以及行业比较优势,发现:(1)哈尔滨联系网络呈现无标度网络特征,与国家中心城市的联系不符合距离衰减规律,且连接度与GRP强线性正相关;(2)哈尔滨的高级生产者服务业联系集聚化,制造业与其他服务业联系偏长尾分布。相对于联系广度,更应重视与少数"服务中心"的联系质量。
Under the background of"flow space",secondary cities in urban network have attracted the attention from regional economic researchers.The role of intra-regional and interregional linkages in the development of secondary cities is related to the success or failure of inter-regional cooperation,but we have different understandings toward such a network.Based on the data of enterprises classified by machine learning,after industry classification,this paper studies the total changes and industry characteristics of urban linkages between Harbin and other cities in Northeast China.It is found that:(1)In the inward economic linkages of Harbin,the importance of cities in Northeast China is declining,and the hinterland of outward network is shrinking.(2)There is a trend of industrial-reversal and low-end in service industry in industrial linkages between Harbin and other cities in Northeast China.(3)Unlike other parts of the country,there is no"service center'*in Northeast China.By studying the relationship between the total number of links and distance,gross regional product(GRP)and industry comparative advantages between Harbin and cities outside the northeast region,it is found that:(1)Harbin's linkage network shows scale-free characteristics,and the linkages with national central cities do not conform to the distance attenuation law;and the linkages are strongly linearly positively correlated with GRP.(2)The connection in advanced producer services shows a character of agglomeration,while the connection in manufacturing and other services presents a long tail distribution.Compared with the scope of contact,we should pay more attention to the quality of contact with a few"service centers".
作者
崔喆
沈丽珍
刘子慎
汪侠
CUI Zhe;SHEN Li-zhen;LIU Zi-shen;WANG Xia(School of Architecture and Urban Planning,Nanjing University,Nanjing 210093,China;School of Geographic and Oceanographic Sciences,Nanjing University,Nanjing 210023,China)
出处
《自然资源学报》
CSSCI
CSCD
北大核心
2020年第7期1672-1685,共14页
Journal of Natural Resources
基金
国家自然科学基金项目(41871160,41871134)。
关键词
城市网络
跨区域
行业结构
公司流
机器学习
city network
cross-region
industry structure
enterprise flow
machine learning
