属性和网络结构双重视角下农民工流动规律研究

发布时间：2018-02-17 06:45

本文关键词： 农民工属性因素个体网络整体网络复杂性结构特征流动规律　出处：《地理科学进展》2017年08期 　论文类型：期刊论文

【摘要】：微观层面的农民工流动与宏观层面的城市间经济联系存在关联性,属性与网络关系结构相结合为分析这种关联性提供了有力工具。运用1142名农民工调查数据和198个城市官方统计数据构建的网络数据,分别分析了属性因素和个体网络以及城市整体网络因素对农民工流动的影响。结果显示:年龄、文化程度、行业类型、打工年限、流出与流入地区域等个体属性因素,以及求职帮助关系人类型、是否有公职人员等个体网络因素对农民工打工地选择、流动距离和工资收入影响显著。通过分析城市属性与整体网络出度入度、网络相关性、无标度特征、核心—边缘结构和小世界特征等因素,得出了农民工流动具有从落后地区流向发达城市,以远距离流动为代价追求高工资,选择务工城市具有扎堆趋势,聚集在发达城市并非必然获得高工资,向发达地区流动倾向于一步到位等结论。在此基础上,提出引导农民工合理流动,降低信息费用,优化劳动力资源配置的相关建议。
[Abstract]:The micro level of migrant workers flow and macro level of inter-city economic links exist relevance, The combination of attribute and network relationship structure provides a powerful tool for analyzing this kind of correlation. Using the survey data of 1142 migrant workers and the official statistics of 198 cities, the network data is constructed. The effects of attribute factors, individual network factors and urban network factors on migrant workers' mobility are analyzed respectively. The results show that: age, education level, industry type, working years, outflow and inflow area, etc. The personal network factors, such as whether there are public officials or not, have a significant impact on the choice of construction site, mobility distance and wage income of migrant workers. Through the analysis of the urban attributes and the overall network output, the network correlation. Factors such as scale-free characteristics, core-edge structure and small world characteristics show that migrant workers flow from backward areas to developed cities, pursue high wages at the cost of long-distance mobility, and choose migrant cities with a tendency to pile up. Gathering in developed cities is not necessarily to obtain high wages, and the mobility to developed areas tends to be in one step, etc. On this basis, some suggestions are put forward to guide the reasonable flow of migrant workers, reduce the cost of information, and optimize the allocation of labor resources.
【作者单位】：山西师范大学经济与管理学院;西安交通大学公共政策与管理学院;
【基金】：国家社会科学基金项目(13BRK016);国家社会科学基金重大项目(13&ZD044,15ZDA048)~~
【分类号】：F323.6

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