[1]陶经辉,张晓萍,孙大鹏,等.物流产业发展与物流人才需求模型研究[J].深圳大学学报理工版,2009,26(1):106-110.
 TAO Jing-hui,ZHANG Xiao-ping,SUN Da-peng,et al.Research on the model of logistics industry development and logistics talents demand[J].Journal of Shenzhen University Science and Engineering,2009,26(1):106-110.
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物流产业发展与物流人才需求模型研究()
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《深圳大学学报理工版》[ISSN:1000-2618/CN:44-1401/N]

卷:
第26卷
期数:
2009年1期
页码:
106-110
栏目:
数学与应用数学
出版日期:
2009-01-30

文章信息/Info

Title:
Research on the model of logistics industry development and logistics talents demand
文章编号:
1000-2618(2009)01-0106-05
作者:
陶经辉12张晓萍1孙大鹏1李英1
1)清华大学深圳研究生院,深圳 518055
2)南京财经大学,南京 210046
Author(s):
TAO Jing-hui12ZHANG Xiao-ping1SUN Da-peng1and LI Ying1
1)Graduate School at Shenzhen,Tsinghua University,Shenzhen 518005,P.R.China
2)Nanjing University of Finance & Economics,Nanjing 210046,P.R.China
关键词:
物流产业物流人才物流工程人才需求马尔可夫链
Keywords:
logistics industrylogistics talentslogistics engineeringtalents demandMarkov chain
分类号:
N 31
文献标志码:
A
摘要:
针对阻滞指数增长模型对随机性强系统预测精度较差的弊端,用马尔可夫链模型对阻滞指数增长模型的预测结果进行改进,得到物流产业发展增加值的预测值.验证可知,改进后该值更趋合理.选择5个国家物流产业发展数据进行统计分析,采用回归模型论证了物流产业发展与物流人才需求之间存在高度相关.
Abstract:
Logistics model for prediction precision in stochastic systems is not satisfactory. To improve it, firstly this paper improves the prediction by Markov chain model,obtains the improved prediction logistics GDP values,and proves that these values are more reasonable than those of the logistics model.Secondly,this paper chooses five countries’ logistics development data to process the statistical analysis,and uses the regression model to reason out the causality and high relevance between the development of the logistics industry and the demand of the logistics talents.Finally,this paper predicts the demand quantity of logistics talents from year 2011 to year 2015 by the regression model,hoping that it will be helpful to the operation of the logistics talents training market in China.

参考文献/References:

[1]Paul Choudhury J,Bijan Sarkar,Mukherjee S K.模糊神经网络与ARIMA模型对工程技术人才的预测:一种比较研究[J].神经元计算,2002,47:241-257(英文版).
[2]Linda O’Brien-Pallas.卫生保健人才需求预测模型[J].高级养护学报,2004,33(1):120-129(英文版).
[3]Gert Zülch,Jan Krüger,Hermann Schindele,等. 基于仿真的生产系统高层次人才结构规划[J].应用人类工程学,2003,34:293-301(英文版).
[4]David C,Lee W S. 劳动力特征和人口统计学信息[J].高级养护学报,2006,30(1):87-99(英文版).
[5]周秀群.我国高等人才年需求量预测[J].统计与决策,2005(7):52-53.
[6]何荣旺,刘伟.基于灰色系统理论的科技人才资源优化配置[J].系统工程与电子技术,2003(25):678-681.
[7]李友俊,贾振歧,覃生高.马尔可夫链在石油企业科技人才教堂预测中的应用[J].大庆石油学院学报,2008,32(5):104-107.
[8]史忠良.产业经济学[M].北京:经济管理出版社,2004.
[9]Theodore Levitt.产品寿命周期的开发[J].哈佛商业评论,1995,12:81-94(英文版).

[1]Paul Choudhury J,Bijan Sarkar,Mukherjee S K.Forecasting of engineering manpower through fuzzy associative memory neural network with ARIMA: a comparative study[J].Neurocomputing,2002,47:241-257.
[2]Linda O’Brien-Pallas.Forecasting models for human resources in health care[J].Journal of Advanced Nursing,2004,33(1):120-129.
[3]Gert Zülch,Jan Krüger,Hermann Schindele,et al.Simulation-aided planning of quality-oriented personnel structures in production systems[J]. Applied Ergonomics.2003,34:293-301.
[4]David C,Lee W S. Using worker personality and demographic information[J].Journal of Advanced Nursing,2006,30(1):87-99.
[5]ZHOU Xiu-qun.The forecasting of the year requirement about advanced talent[J].Statistic & Decision-Making,2005(7):52-53(in Chinese).
[6]HE Rong-wang,LIU Wei.The optimal allocation of intellectual resources based on the grey system theory[J].Systems Engineering and Electroni,2003(25):678-681(in Chinese).
[7]LI You-jun,JIA Zhen-qi,QIN Sheng-gao.Application of Markov chain in the prediction of technical personnel size in petroleum enterprises[J].Journal of Daqing Petroleum Iastitute,2008,32(5):104-107(in Chinese).
[8]SHI Zong-liang.Industrial Economics [M].Beijing: Economics Management Publishing House,2004(in Chinese).
[9]Theodore Levitt.Exploit the product life cycle[J].Harvard Business Review,1995,12:81-94.

备注/Memo

备注/Memo:
收稿日期:2008-07-02;修回日期:2008-10-25
基金项目:国家自然科学基金资助项目(70573056);广东省自然科学基金资助项目(7301729);江苏省高校自然科学基础研究项目(07KSD120067)
作者简介:陶经辉(1969-),男(汉族),安徽省马鞍山市人,清华大学副教授、博士后研究人员.E-mail:taojh@sz.tsinghua.edu.cn
更新日期/Last Update: 2009-02-17