地理研究 ›› 2014, Vol. 33 ›› Issue (10): 1837-1847.doi: 10.11821/dlyj201410005

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沈阳市部门企业地理集聚与城市结构

孙平军1,2(), 宋伟2, 修春亮3()   

  1. 1. 哈尔滨工业大学建筑学院,哈尔滨 150001
    2. 路易斯维尔大学地理与地球科学系, 路易斯维尔 40292,美国
    3. 东北师范大学地理科学学院,长春 130024
  • 收稿日期:2013-12-19 修回日期:2014-05-28 出版日期:2014-10-10 发布日期:2015-03-13
  • 作者简介:

    作者简介:孙平军(1981- ),男,湖南隆回人,博士,讲师,主要从事城市与区域规划、区域经济开发研究。E-mail: sunpj031@nenu.edu.cn

  • 基金资助:
    国家自然科学基金项目(41071109);中央高校基本科研业务费专项资金(10SSXT101)

Geographic clustering of sector enterprises and urbanform in Shenyang

Pingjun SUN1,2(), Wei SONG2, Chunliang XIU3()   

  1. 1. School of Architecture, Harbin Institute of Technology, Harbin 150001, China
    2. Department of Geography and Geosciences, University of Louisville, Louisville 40292, USA
    3. School of Geography Sciences, Northeast Normal University, Changchun 130024, China
  • Received:2013-12-19 Revised:2014-05-28 Online:2014-10-10 Published:2015-03-13

摘要:

基于产业空间聚集分布情况探寻城市结构特征,是当前大都市区实证研究中的聚焦点所在,但由于方法论的限制而无法真正揭示产业地理集聚之间的内在关联性。基于已有研究基础,试图通过完善潜力模型、设置距离参数、结合主成分分析法实现对产业地理集聚测度方法论的完善与发展,并选取极具代表性大都市区核心城市——沈阳市为样本单元,以2008年的经济普查部门企业数据开展实证检验。结果表明:沈阳市部门企业之间除了交通运输、仓储和邮政中心产业属于地方化经济外,其余的均为企业关联;水利、环境和公共设施管理业产业依附于制造业呈临街抑或隔街集聚,而与公共管理和组织产业之间同街道集聚;支配主角之间,存在中心CBD主宰制造业的布局,而制造业又在很大程度上影响着交通运输、仓储和邮政中心的布局;企业地理集聚形成的城市结构依然是一个明显的“单中心圈层”结构,没有表现出“去中心化”抑或多极化或分散化演变趋势。研究成果与现实情况基本吻合,侧面说明该模式对揭示城市产业地理集聚模式以及由此形成的城市结构特征具有一定的解释力。

关键词: 大都市区, 部门企业, 地理集聚, 城市结构, 潜力模型, 沈阳市

Abstract:

Investigating urban structures based on the intra-metropolitan location of economic activities (e.g. industrial districts or industrial clusters) is an increasingly important theme in empirical metropolitan studies. However, the lack of adequate research methodology has restricted the in-depth and fair exploration of mechanisms underpinning the formation of metropolitan industrial clusters, especially the differentiated roles played by two key processes-localization economies and inter-industry linkages. Therefore, based on existing literatures, this paper proposed an approach to systematically examine and detect the clustering of economic activities within a metropolitan area. Specifically, a modified, gravity model-based potential model is developed to spatialize sectoral data and measure the potential of each economic sector in every spatial unit, taking into account its location relative to firms in that sector at different spatial units. For each city street block and sector, potential is inversely proportional to the distance-decay parameter that is systematically adjusted to capture the varying weights of firms in that sector at nearby and distant locations. To evaluate the inter-correlations among potentials, which help detect geographic clustering model among economic sectors, principal component analysis (PCA) is used. Sectors loading strongly onto a component share similar location patterns. The city of Shenyang and its data from 2008 Second Economic Census (i.e. number of firms in different economic sectors at the city street block level) are used for empirical analysis. Analytical results reveal that interrelations or geographic clustering model among economic sectors in Shenyang are formed primarily because of inter-industry linkages, with the exception of the spatial interconnection among transportation, warehousing and postal services, which is forged, based on localization economies. Water conservancy, environmental protection and public facility management are closely correlated to manufacturing, and their geographic clustering model largely follows patterns of adjacent-street block clustering or across-street block clustering. The sectoral geographic clustering model of water conservancy, environmental protection and public facility management, and healthcare and social welfare, as well as public management and organizations, follows the pattern of within-city block clustering. The central business district in Shenyang where various service sectors concentrated offers many services to manufacturing sectors and thus plays an important role in the locations of manufacturing activities. Manufacturing locations, in turn, strongly affect the locational choices of transportation, warehousing and postal activities. Overall, the spatial organization of economic activities in Shenyang metropolitan area is characterized by a structure of single center and concentric rings. Large-scale decentralization and poly-nucleation of economic activities are not apparent within the metropolitan area. These revelations from the modeling generally match the reality and suggest that the model proposed by this research is capable of exploring spatial patterns and mechanisms of industrial clusters, particularly geographic clustering model (or collocations) among different sectors in the metropolitan context, thus contributing the understanding city structures.

Key words: metropolitan areas, sector enterprise, geographic clustering, urban form, potential model, Shenyang city