| 摘要: |
| 小城镇是实现乡村产业振兴的重要支
点，探索“产业—空间”格局的时空特征与组织
机制是推进镇村产业协同发展的重要基础。以
武汉主城区周边镇村产业为研究对象，以高德
2012—2019年全量POI数据为研究样本，采用
核密度分析、趋势面分析、最近邻分析、空间均
衡分析等方法综合研判镇村“产业—空间”的
时空分布差异特征，并采用双重差分和地理探
测器模型对于影响因素进行验证。结果表明：第
一，研究期内武汉镇村产业发生规模性扩增、且
扩增速度逐年增速，空间分布由“散点集聚”状分布转变为由内向外的“圈层组团”分布特征；第二，总体层面的武汉镇村产业呈现出“凝聚型”
的分布状态且趋于稳定；第三，街道层面的武汉镇村产业呈现出集中分布的态势，且非均衡特征
初显。进一步探讨武汉镇村产业时空差异的组织机制，发现政策环境是镇村产业分布的催化动
力，市场环境与设施环境是镇村产业分布的支撑动力。 |
| 关键词: 镇村产业 时空分布 地域格局 双重差分法 地理探测器 武汉市 |
| DOI：10.13791/j.cnki.hsfwest.20240607 |
| 分类号: |
| 基金项目:国家自然科学基金（52108052） |
|
| The spatio-temporal characteristics and organizational mechanism of the “industry-space”pattern in towns and villages: Taking Wuhan as an example |
|
XU Lige,FAN Zaiyu,GENG Hong,QIAO Jing
|
| Abstract: |
| Small towns are an important fulcrum for achieving the revitalization of rural industries.
Therefore, exploring the spatiotemporal characteristics and organizational mechanisms of the
“industry-space” pattern is an important foundation for promoting the coordinated development
of towns and villages’ industries. Among many cities, Wuhan takes the lead in paying continuous
attention to and giving policies support to the towns and villages’ industries, so that they can gain
the first-mover advantage. In the context of urban expansion and the intensified flow of factors, these
towns and villages’ industries are facing the important task of functional transformation and income
creation. The towns and villages’ industries in Wuhan metropolitan area is interrelated with multiple
levels, which not only serves the vast rural areas, but also continuously extends its functions to the
urban area, forming a unique spatiotemporal organization model and development path, so it is a
typical representative. This study takes the industries of towns and villages surrounding the main
urban area of Wuhan as the research object, and using the POI data of Gaode Map from 2012 to 2019
as the sample. Methods such as kernel density analysis, trend surface analysis, nearest neighbor
analysis, and spatial equilibrium analysis were used to comprehensively study the spatiotemporal
distribution differences of the “industry-space” in towns and villages. The influencing factors were
verified using differences-in-differences and geographical detectors. The results indicate that: 1)
During the research period, Wuhan towns and villages’ industries experienced large-scale expansion,
and the expansion rate increased year by year. The spatial distribution changed from “scattered
cluster” to “circle cluster” characteristic from inside to outside. Each cluster presents a spindletype
structure with significant linear extension. On the whole, the towns and villages’ industries of
each street showed non-synchronous and non-uniform growth; 2) on the overall level, the industries
in Wuhan towns and villages shows a “cohesive” distribution state and tends to stabilize. On the
one hand, such a distribution can maximize the use of the limited resources, and on the other
hand, it can also reach the threshold of economies of scale by mutual assistance and cooperation
to maximize economic benefits; 3) the industries in Wuhan towns and villages at the street level
show a concentrated distribution trend, and the imbalanced characteristics are beginning to emerge.
Such a trend indicates that the towns and villages’ industries are concentrated in a few streets, and
the streets in the weak location are difficult to absorb more industries in the competition, and the
Matthew effect of the towns and villages’ industries layout begins to appear. Further exploring the
organizational mechanism of the spatiotemporal differences of industries in towns and villages in
Wuhan, it was found that the policy environment, market environment and facility environment affectthe spatiotemporal distribution of town and village industries to different degrees. It can be summarized as follows. The policy environment is the catalytic
driving force for the distribution of industries in towns and villages, while the market environment and facility environment are the supporting forces for the
distribution of industries in towns and villages. Specifically, the former is manifested in the fact that all kinds of favorable agricultural policies clearly point
out the problems in the quantity and scale of various agricultural product processing enterprises, and put forward the industrial parks pattern and the linkage
pattern of towns and villages, so as to incline all resources to the key agricultural areas and promote the spatial pattern with characteristics. The latter shows
that the secondary and tertiary industries have greatly accelerated in the process of Wuhan’s urbanization, providing a solid foundation for the modernization
of towns and villages’ industries. At the same time, government departments also actively provide funds and training services, promoting the differentiation
of towns and villages industrial patterns. In terms of transportation facilities, the distribution of towns and villages’ industries has changed from dependence
on high-grade transportation facilities to dependence on logistics networks. In order to further promote the revitalization of towns and villages’ industries,
the study believes that at the level of policy and system, we should fully tap the surplus capacity of township industries, accelerate the process of enterprises
entering the industrial parks, and help industrial entities overcome the difficulties of transformation. At the level of economic environment development,
actively excavate the gaps and shortcomings of the industrial chain within the metropolitan area, sort out and construct the division of labor system between
the towns and villages’ industries and the transfer enterprises in the central urban area. At the level of transportation facilities construction, improve and
make up for the shortcomings of logistics, further enhance the production and service functions of towns and villages industries, and promote their scale
effect and radiation effect. |
| Key words: town and village industries the patio-temporal distribution regional pattern differences-in-differences geographical detectors Wuhan |
