地理科学进展 ›› 2018, Vol. 37 ›› Issue (9): 1245-1256.doi: 10.18306/dlkxjz.2018.09.007

• 研究论文 • 上一篇    下一篇

中国小城镇基础设施与社会经济发展的关联分析

赵鹏军(), 刘迪   

  1. 北京大学城市与环境学院,北京100871
  • 收稿日期:2018-03-15 修回日期:2018-05-24 出版日期:2018-09-28 发布日期:2018-10-10
  • 作者简介:

    作者简介:赵鹏军(1975-),男,陕西延安人,博士,研究员,研究方向为城市和区域规划等,E-mail: pengjun.zhao@pku.edu.cn

  • 基金资助:
    国家自然科学基金项目(41571147)

Analysis of the relationships between infrastructure and socioeconomic development in towns of China

Pengjun ZHAO(), Di LIU   

  1. College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
  • Received:2018-03-15 Revised:2018-05-24 Online:2018-09-28 Published:2018-10-10
  • Supported by:
    National Natural Science Foundation of China, No. 41571147

摘要:

小城镇基础设施与社会经济发展的相互作用关系是城乡规划学和城市地理学的重要理论研究议题,也是科学制定促进小城镇发展政策、实施新型城镇化规划的关键。学术界普遍认为基础设施缺乏是制约中国小城镇社会经济发展的主要因素,但支撑这一论断的一手调查研究仍属空白。本文采用全国121个镇的调查数据,运用灰色关联分析法构建小城镇基础设施与社会经济发展的关联度模型,定量分析了中国小城镇基础设施与社会经济发展之间的关联度整体水平及其地域性差异和规模类型差异性,以及基础设施与社会经济发展的协调状态。研究结果表明:①中国小城镇基础设施与社会经济发展之间存在较强的关联作用,但社会经济发展对基础设施建设的促进作用较强,而基础设施对社会经济发展的支撑作用相对较弱;②两者之间的关联度存在地域差异,东北地区的小城镇基础设施与社会经济发展之间的联系比其他地区更加紧密;在远离大城市的小城镇,两者之间相互关联度要比距离大城市较近的镇更强;③不同人口规模和功能类型的镇二者相互作用强度也有所不同,人口规模较小和较大的镇基础设施与社会经济发展间的联系比人口规模中等的镇更加紧密;商贸主导型镇二者相互关联强度较高,而工业主导型镇较弱;④小城镇的基础设施与社会经济的协调发展主要表现为中低发展水平的协调,即低发展水平的基础设施和低发展水平的社会经济状况并存;但高发展水平协调发展较少,且主要集中在东部地区和到特大城市距离适中的镇;距离特大城市较近或者较远都会导致两者之间形成一种低发展水平的协调;⑤在导致低发展水平协调的机制中,基础设施建设滞后所产生的作用要强于社会经济发展不足所产生的作用,这在东部地区小城镇和大城市近郊小城镇表现得较为明显。本文研究结论对于指导小城镇规划具有重要的实践意义。

关键词: 基础设施, 社会经济发展, 协调状态, 灰色关联分析, 小城镇, 中国

Abstract:

The relationship between infrastructure supply and socioeconomic development in towns is one of the key research themes in the fields of urban planning and urban geography. This relationship is a vital issue for urban planning practice and development management of towns. It is widely believed that a lack of infrastructure is one of the key factors impeding social and economic development in China's towns. However, empirical research supporting this argument is stull scarce. In particularly, an analysis at the national level is missing. This study aimed to fill the gap by using recently collected survey data from 121 towns in China. It applied grey associative analysis to identify the relationship between infrastructure and socioeconomic development in these towns. The facts, major factors, and the mechanisms for the relationship between infrastructure and socioeconomic development were analyzed. The results show that: (1) Infrastructure and socioeconomic development are significantly related with each other. The effects of socioeconomic development on infrastructure supply are stronger than the effects of infrastructure on socioeconomic development, which contradicts previous understandings; (2) The relationship between socioeconomic development and infrastructure is influenced by local economic contexts. For example, the correlations in the towns located in Northeast China are more significant, and the correlations in the towns far from megacities are stronger than those near these cities; (3) Population size and industry type also influence the relationship between the two systems. Correlations in towns with a small population or tourist towns are stronger than medium-sized towns while commerce-leading towns show greater correlations than industry-leading towns; (4) When the development quality or level is taken into account, for many towns, low level of infrastructure supply and low level of socioeconomic development coincide. In towns located in eastern China or towns that have a moderate distance to megacities, high level of infrastructure supply and high level of socioeconomic development occur at the same time; (5) For towns with a low level of socioeconomic development and infrastructure supply, insufficient infrastructure supply plays a more important role than insufficient development of socioeconomic sectors. This situation particularly happened in towns in eastern China or towns located near megacities. These findings have strong policy implications for the future development and construction of towns in China.

Key words: infrastructure supply, socioeconomic development, coordinative development, grey associative analysis, towns, China