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多尺度网络视角下企业产业扶贫资源跨区域配置及减贫效应
引用本文:徐维祥,周建平,郑金辉,李露,刘程军.多尺度网络视角下企业产业扶贫资源跨区域配置及减贫效应[J].自然资源学报,2022,37(10):2703-2719.
作者姓名:徐维祥  周建平  郑金辉  李露  刘程军
作者单位:1.浙江工业大学经济学院,杭州 3100232.无锡学院商学院,无锡 2100443.浙江工业大学之江学院,绍兴 312030
基金项目:国家社会科学基金重大项目(18ZDA045)
摘    要:扶贫网络研究有助于解构扶贫资源的跨区域配置方式,挖掘扶贫要素的空间适配机制,对于巩固拓展脱贫攻坚成果同乡村振兴有效衔接有一定借鉴意义。基于上市公司精准扶贫数据构建了区域间的扶贫关联网络,运用社会网络分析法及地理加权回归(GWR)模型分析了多尺度扶贫网络格局、网络结构及其减贫效应,得到结论如下:(1)多尺度视角下的网络格局的空间异质性明显,企业的扶贫行为趋于空间邻近区域,空间指向性较强,城市间的精准扶贫关联网络呈现由“少核互联”的较稀疏网络向“多核交织”的密集型网络演进。地理距离对企业扶贫的约束仍然存在,但约束性逐渐降低。(2)扶贫关联网络复杂度不断强化,净溢出、经纪人、净受益和双向溢出四个板块间的溢出效应明显。(3)扶贫关联网络中扶贫多元化提升、区域连接数增加、区域联系强度增强及区域节点中介性提升对产业扶贫效应的发挥具有促进作用。

关 键 词:乡村振兴  扶贫网络  减贫效应  社会网络分析  GWR模型  
收稿时间:2021-09-13
修稿时间:2022-01-23

Cross-regional allocation of industrial poverty alleviation resources and poverty reduction effects from the perspective of multi-scale network
XU Wei-xiang,ZHOU Jian-ping,ZHENG Jin-hui,LI Lu,LIU Cheng-jun.Cross-regional allocation of industrial poverty alleviation resources and poverty reduction effects from the perspective of multi-scale network[J].Journal of Natural Resources,2022,37(10):2703-2719.
Authors:XU Wei-xiang  ZHOU Jian-ping  ZHENG Jin-hui  LI Lu  LIU Cheng-jun
Institution:1. School of Economics, Zhejiang University of Technology, Hangzhou 310023, China2. Business School, Wuxi University, Wuxi 210044, Jiangsu, China3. Zhijiang college of Zhejiang University of Technology, Shaoxing 312030, Zhejiang, China
Abstract:The study of poverty alleviation networks can help deconstruct the cross-regional allocation of poverty alleviation resources and explore the spatial adaptation patterns of poverty alleviation factors, which can be useful for consolidating and expanding the effective linkage between poverty alleviation and rural revitalization. This paper constructs inter-regional poverty alleviation networks based on the data of listed companies on targeted poverty alleviation, and analyses the multi-scale poverty alleviation network pattern, network structure and its poverty alleviation effect by using social network analysis and GWR geographical weighting model. The following conclusions were obtained: (1) The network pattern from a multi-scale perspective is spatially heterogeneous. Enterprises are more willing to help spatially adjacent areas, and the spatial directionality is stronger. The inter-city network of targeted poverty alleviation is evolving from a sparse network with few interconnected nuclei to a dense network with multiple intertwined nuclei, and geographical constraints still exist but the distance to help outward gradually increases. (2) The spatial network for targeted poverty alleviation has been strengthening in terms of concentration and aggregation, with the eastern coastal and more developed inland regions at the core of the network and the remote and less developed central and western regions at the periphery of the network. At the provincial level, the "net spillover" and "two-way spillover" segments are mainly located in the central and western regions, the northeast region, the "net spillover" segments are mainly located in the coastal region and the Yangtze River. The "net spillover" segment is mainly located in the coastal region and the upper and middle reaches of the Yangtze River, while the "broker" segment is mainly located in the Bohai Sea Rim and Xinjiang. At the municipal level, the "net spillover" segment is mainly located in the core cities and regional centers of the provinces, while the "broker" segment is mainly located in the eastern coastal provinces and the sub-core cities of other provinces, and the "net beneficiary" segment is mainly located in the "net benefit" segment. The cities in the "net benefit" segment are mainly located in the central and western regions and some regions in need of poverty alleviation, and the cities in the "two-way spillover" segment are mainly the sub-core cities in the central and western regions. (3) The increase in pro-poor diversification, the increase in the number of regional connections, the strength of regional ties and the increase in the intermediation of regional nodes in the poverty alleviation linkage network have a catalytic effect on the poverty alleviation effect.
Keywords:targeted poverty alleviation  spatial network  poverty reduction effect  social network analysis  GWR model  
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