天津市人才配置效率动态演化及影响因素研究——基于超效率DEA和Malmquist指数
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摘要
人才对区域创新的驱动和战略性作用日益突出,但区域人才配置的合理性和有效性却成为制约落实人才发展战略和区域持续发展的主要瓶颈。基于投入和产出视角构建区域人才配置效率评价指标体系,采用2009—2016年天津市16个行政区作为样本,运用超效率DEA方法分析人才配置效率动态演化趋势,并使用Malmquist指数甄别人才配置效率变动的影响因素。结果表明,天津市人才配置效率除2011年有所上升,总体呈现下降趋势;中心城区、环城区和远郊区人才配置效率远低于滨海新区,但3个功能区人才配置效率呈现协同发展态势;16个行政区人才配置效率在变动方向和强度方面均存在较大差异。另外,从技术效率和技术进步水平来看,技术进步已成为天津市人才配置的主要影响因素。研究结果有助于天津市优化人才资源配置,并且为该方法应用于其他区域提供了依据。
Talents play a decisive role in boosting regional innovation, whether regional talent allocation is rational and effective will affect talent development and sustainable regional development. Based on the input and output perspective,the evaluating index system about regional talent allocation efficiency is constructed. Using the 16 administrative districts of Tianjin from 2009 to 2016 as samples, the Super-efficient DEA is used to analyze the dynamic evolution trend of talent allocation efficiency. Meanwhile, the Malmquist index is used to analyze the influencing factors of changes about talent allocation efficiency. The results show that the talent allocation efficiency in Tianjin has presented a downward trend except in 2011; the efficiency of talent allocation in the downtown, ring area and suburbs is much lower than that in Binhai New District, but the talent allocation efficiency of the three functional areas shows a synergistic development trend; the efficiency of talent allocation in 16 administrative districts vary greatly in terms of direction and intensity. In addition,technological progress has become the main influencing factor of talent allocation in Tianjin from the perspective of technological efficiency and level of technological progress. The foregoing results will help the government of Tianjin optimize the allocation of talent resources and provide a basis for the application of this method to other fields.
Talents play a decisive role in boosting regional innovation, whether regional talent allocation is rational and effective will affect talent development and sustainable regional development. Based on the input and output perspective,the evaluating index system about regional talent allocation efficiency is constructed. Using the 16 administrative districts of Tianjin from 2009 to 2016 as samples, the Super-efficient DEA is used to analyze the dynamic evolution trend of talent allocation efficiency. Meanwhile, the Malmquist index is used to analyze the influencing factors of changes about talent allocation efficiency. The results show that the talent allocation efficiency in Tianjin has presented a downward trend except in 2011; the efficiency of talent allocation in the downtown, ring area and suburbs is much lower than that in Binhai New District, but the talent allocation efficiency of the three functional areas shows a synergistic development trend; the efficiency of talent allocation in 16 administrative districts vary greatly in terms of direction and intensity. In addition,technological progress has become the main influencing factor of talent allocation in Tianjin from the perspective of technological efficiency and level of technological progress. The foregoing results will help the government of Tianjin optimize the allocation of talent resources and provide a basis for the application of this method to other fields.
引文
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[16]周平.基于超效率DEA模型的区域低碳效率空间分异---以湖南省各市州为例[J].经济地理2017,37(3):188-192.
[17]李闻一,朱祥波,王宇.政府科技投入成本效益分析---基于超效率CCR模型与Malmquist指数模型[J].科技进步与对策,2016,33(21):132-136.
[2]侯爱军,夏恩君,陈丹丹,李森.基于供需视角的我国区域人才流动研究[J].科技进步与对策,2015,32(9):141-145.
[3]桂昭明.改进完善人才流动配置机制的路径[J].中国人才,2010(11):22-23.
[4]宋本江.我国短缺性人才资源配置机制探讨[J].中国人力资源开发,2011(01):73-75.
[5]刘兵,曹文蕊,梁林.京津冀人才配置关键影响因素识别及模式研究[J].科技进步与对策,2017,34(19):41-46.
[6]彭皓玥,王树恩.我国科技人才配置的效率[J].工业工程.2008(02):17-20+28.
[7]牛冲槐,黄娟,李秋霞.基于灰色关联投影模型的科技型人才聚集效应测度---以中部六省为例[J].科技进步与对策,2013,30(1):150-154.
[8]刘兵,李嫄,许刚.开发区人才聚集与区域经济发展协同机制研究[J].中国软科学,2010(12):89-96.
[9]张再生.人才流动态势及影响因素分析---以天津市为例[J].人口学刊,2001(1):8-12.
[10]魏浩,王宸,毛日昇.国际间人才流动及其影响因素的实证分析[J].管理世界,2012(1):33-45.
[11]牛冲槐,接民,张敏,等.人才聚集效应及其评判[J].中国软科学,2006(4):118-123.
[12]牛冲槐,江海洋.硅谷与中关村人才聚集效应及环境比较研究[J].管理学报,2008,5(3):396-401.
[13]R D BANKER,A CHARNES,W W COOPER.Constrained game formulations and interpreations for data envelopment analysis[J].European Journal of Operational Research,1989,40(3):299-308.
[14]ANDERSEN P,PETERSEN N C.A procedure for ranking efficientunits in data envelopment analysis[J].Management Science,1993,39(10):1261-1264.
[15]杨力,王舒鸿,吴杰.基于集成超效率DEA模型的煤炭企业生产效率分析[J].中国软科学,2011(3):169-176.
[16]周平.基于超效率DEA模型的区域低碳效率空间分异---以湖南省各市州为例[J].经济地理2017,37(3):188-192.
[17]李闻一,朱祥波,王宇.政府科技投入成本效益分析---基于超效率CCR模型与Malmquist指数模型[J].科技进步与对策,2016,33(21):132-136.