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作 者:任义科[1] 宋连成[1] 佘瑞芳[1] 杜海峰[2]
机构地区:[1]山西师范大学经济与管理学院,山西临汾041004 [2]西安交通大学公共政策与管理学院,西安710049
出 处:《地理科学进展》2017年第8期940-951,共12页Progress in Geography
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)~~
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。Migrant workers' migration at the micro level is associated with intercity economic linkages at the macro level. Jointly considering attributes of migrant workers and source/destination cities and network relation structures provides a powerful tool for the analysis of such association. Using the survey data of 1142 migrant workers and network data of 198 cities from official websites, this article analyzes the effects of individual and city attributes, individual social network factors, and city network factors on migrant workers' migration.Regression results indicate that individual attributes such as age, education, occupation type, working years,emigration and immigration areas, and individual network factors such as the type of helpers in job seeking and whether the helpers hold a public service position, have significant impact on migrant workers' choice of destination area, migration distance, and income. Through analyzing city attributes and whole networks' outdegree and in-degree, correlation between networks, scale-free properties, core-periphery structure, and small world characteristics, the following migration patterns are revealed: from underdeveloped areas to developed cities, pursuing high wages at the expense of long distance, clustering in target cities, no guarantee of high salary working in developed cities, and migrating to developed cities directly rather than through indirectly routes.Based on the above conclusions, some countermeasures and suggestions are proposed for guiding migration decision making, reducing information cost, and optimizing the allocation of labor resources.
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