地理学报 ›› 2020, Vol. 75 ›› Issue (11): 2380-2395.doi: 10.11821/dlxb202011008

• 土地利用与农业发展 • 上一篇    下一篇

中国粮食生产空间关联网络的结构特征及其形成机制

冯颖1,2(), 侯孟阳3,4, 姚顺波3,4()   

  1. 1. 西北政法大学商学院,西安 710122
    2. 西北政法大学资源冲突与利用研究所,西安 710122
    3. 西北农林科技大学经济管理学院,杨凌 712100
    4. 西北农林科技大学资源经济与环境管理研究中心,杨凌 712100
  • 收稿日期:2019-11-27 修回日期:2020-05-21 出版日期:2020-11-25 发布日期:2021-01-25
  • 通讯作者: 姚顺波
  • 作者简介:冯颖(1984-), 女, 博士, 副教授, 硕导, 研究方向为资源经济与环境管理。E-mail: yingfeng8410@126.com
  • 基金资助:
    陕西省社会科学基金项目(2019S029);教育部人文社会科学重点基金项目(14JJD790031);国家自然科学基金项目(71473195);陕西省教育厅专项科研项目(016166523);西北政法大学青年学术创新团队计划资助项目

Structural characteristics and formation mechanism of spatial correlation network of grain production in China

FENG Ying1,2(), HOU Mengyang3,4, YAO Shunbo3,4()   

  1. 1. Business School, Northwest University of Political Science and Law, Xi'an 710122, China
    2. Institute of Resource Conflict and Utilization, Northwest University of Political Science and Law, Xi'an 710122, China
    3. College of Economics & Management, Northwest A&F University, Yangling 712100, Shaanxi, China
    4. Research Center for Resource Economics and Environment Management, Northwest A&F University, Yangling 712100, Shaanxi, China
  • Received:2019-11-27 Revised:2020-05-21 Online:2020-11-25 Published:2021-01-25
  • Contact: YAO Shunbo
  • Supported by:
    Social Science Fund of Shaanxi Province(2019S029);Key Fund for Humanities and Social Sciences of the Ministry of Education(14JJD790031);National Natural Science Foundation of China(71473195);Special Scientific Research Project of Shaanxi Provincial Education Department(016166523);Young Academic Innovation Team of Northwest University of Political Science and Law

摘要:

基于1996—2018年中国省际粮食生产面板数据,在修正的引力模型准确测算粮食生产空间关联关系及构建空间关联矩阵的基础上,首先运用社会网络分析方法从整体特征、个体特征及块模型3个方面具体考察了粮食生产空间关联网络的结构特征,进一步采用二次指派程序方法探讨其形成机制。研究发现:① 省际粮食生产空间关联的密切程度在波动中提高,但仍有提升空间,网络结构呈现较好的稳定性和可达性,溢出效应具有多重叠加特性;② 省际粮食生产空间关联网络呈现主产区、主销区、平衡区“核心—边缘”分布格局,粮食主产区在网络中处于核心地位,粮食主销区和平衡区则处于边缘地位;③ 粮食生产空间关联网络可划分为净溢出、主受益、经纪人和双向溢出4个板块,板块间的溢出效应具有明显的梯度传递特征;④ 自然禀赋条件与社会经济因素的共同作用推动了粮食生产空间关联网络的形成,地理空间邻近性、经济发展水平与农村劳动力规模、机械服务规模、耕地资源的差异、降水量和日照时数的相近性对粮食生产空间关联网络的形成具有显著影响。

关键词: 粮食生产, 空间关联网络, 结构特征, 形成机制, 社会网络分析(SNA), QAP分析法

Abstract:

Based on the panel data of China's inter-provincial grain production from 1996 to 2018, the modified gravity model was used to accurately calculate the spatial correlation of grain production and build a spatial correlation matrix. Firstly, the structural characteristics of grain production spatial correlation network were investigated from three aspects: overall characteristics, individual characteristics and block model through the social network analysis method (SNA) and then, the quadratic assignment procedure (QAP) method was used to explore its formation mechanism. The study found that: (1) The level of inter-provincial spatial correlation of grain production increases in fluctuation, but there is still room for improvement. The network structure shows better stability and accessibility, and the spillover effect has multiple superposition. (2) The inter-provincial spatial correlation network of grain production presents a significant core-edge distribution pattern of major grain-producing areas, main-sales areas and grain balance areas, and the major grain-producing areas are at the core position in the network, and the grain main-sales areas and the balance areas are at the edge. (3) The spatial correlation network of grain production can be divided into four functional blocks, namely, net spillover block, main beneficial block, broker block and bidirectional spillover block, and the spillover effect between blocks are featured by obvious gradient transmission. (4) The combined effect of natural endowment conditions and socio-economic factors promote the formation of spatial correlation network of grain production. The geographical proximity, differences in economic development, rural labor scale, mechanical service scale and cultivated land resources, and the similarity of precipitation and sunshine hours have significant impacts on the formation of spatial correlation network of grain production. The conclusions are of great significance for us to grasp the spatial transmission mechanism, realize the cross-regional coordination and formulate differentiated grain policies in China.

Key words: grain production, spatial correlation network, structural characteristics, formation mechanism, social network analysis method (SNA), quadratic assignment procedure (QAP)