基于组合预测模型的保险业人才需求预测研究——以上海市为例
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摘要
为了突破上海市保险业人才供需失衡而制约行业发展的瓶颈,设计人才需求预测模型来预测未来几年的人才需求量具有实际意义。基于2011—2016年上海市保险业人才有关数据,构建包括GM(1,1)模型和指数平滑模型的组合预测模型,预测2019—2021年上海市的保险业人才需求量。结果表明:上海市未来三年内以每年约17%的速度增长,明显高于2016年的13. 83%。最后,从高校培养人才的角度提出相关建议,以期为该行业的未来发展提供参考。
In order to break through the bottleneck that restricts the development of Shanghai's insurance industry due to the imbalance between supply and demand of talents,it is of practical significance to design a talent demand prediction model to predict the number of talents in the next few years. Based on the relevant data of insurance talents in Shanghai from 2011 to 2016,this paper constructs a combined forecasting model including GM( 1,1) model and exponential smoothing model to forecast the demand for insurance talents in Shanghai from2019 to 2021. The results show that Shanghai will grow at an annual rate of approximately 17% in the next three years,significantly higher than the 13. 83% in 2016. Finally,some suggestions are put forward from the perspective of cultivating talents in colleges and universities so as to provide reference for the future development of the industry.
In order to break through the bottleneck that restricts the development of Shanghai's insurance industry due to the imbalance between supply and demand of talents,it is of practical significance to design a talent demand prediction model to predict the number of talents in the next few years. Based on the relevant data of insurance talents in Shanghai from 2011 to 2016,this paper constructs a combined forecasting model including GM( 1,1) model and exponential smoothing model to forecast the demand for insurance talents in Shanghai from2019 to 2021. The results show that Shanghai will grow at an annual rate of approximately 17% in the next three years,significantly higher than the 13. 83% in 2016. Finally,some suggestions are put forward from the perspective of cultivating talents in colleges and universities so as to provide reference for the future development of the industry.
引文
[1]许飞琼.中国保险业人才战略:现状、目标与关键措施[J].保险研究,2011(12):108-112.
[2]陈靖.保险人才培养模式创新策略探究[J].上海金融,2011(01):116-118.
[3]崔惠贤.“新国十条”颁布后上海高校保险人才培养改革探析[J].上海保险,2014(11):52-57.
[4]王保贤,刘毅.基于灰色BP神经网络模型的人力资源需求预测方法[J].统计与决策,2018,34(16):181-184.
[5]汪江龙,杨旭,李严锋.物流发展潜力预测模型研究———以云南省为例[J].经济问题探索,2006(10):148-152.
[6]杨堃.全球经济危机对我国物流业区域分布的影响———基于指数平滑法的定量分析[J].物流技术,2012,31(17):310-312.
[7]于博,孙安国,陈丽萍,等.基于指数平滑法的云南省物流需求预测[J].物流工程与管理,2018,40(12):39-40+38.
[8]贡文伟,黄晶.基于灰色理论与指数平滑法的需求预测综合模型[J].统计与决策,2017(01):72-76.
[9]汪强,刘晓佳,闫长健,等.基于组合模型的厦门港集装箱吞吐量预测[J].集美大学学报(自然科学版),2019,24(01):31-36.
[10]李鹏.应用型本科院校保险专业教学改革[J].教育与职业,2014(30):123-124.
[2]陈靖.保险人才培养模式创新策略探究[J].上海金融,2011(01):116-118.
[3]崔惠贤.“新国十条”颁布后上海高校保险人才培养改革探析[J].上海保险,2014(11):52-57.
[4]王保贤,刘毅.基于灰色BP神经网络模型的人力资源需求预测方法[J].统计与决策,2018,34(16):181-184.
[5]汪江龙,杨旭,李严锋.物流发展潜力预测模型研究———以云南省为例[J].经济问题探索,2006(10):148-152.
[6]杨堃.全球经济危机对我国物流业区域分布的影响———基于指数平滑法的定量分析[J].物流技术,2012,31(17):310-312.
[7]于博,孙安国,陈丽萍,等.基于指数平滑法的云南省物流需求预测[J].物流工程与管理,2018,40(12):39-40+38.
[8]贡文伟,黄晶.基于灰色理论与指数平滑法的需求预测综合模型[J].统计与决策,2017(01):72-76.
[9]汪强,刘晓佳,闫长健,等.基于组合模型的厦门港集装箱吞吐量预测[J].集美大学学报(自然科学版),2019,24(01):31-36.
[10]李鹏.应用型本科院校保险专业教学改革[J].教育与职业,2014(30):123-124.