知识型员工—岗位匹配评价研究
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摘要
近些年,人力资源在企业中占有着越来越重要的地位,进而人岗匹配开始得到越来越多的企业的重视。知识型员工已经成为当前社会很重要的资源,所以知识型员工岗位匹配评价就更为重要。传统的人岗匹配的评价方法有很多,如:排列法、分类法、评分法、因素比较法等等,这些方法虽有一定的合理性但是主观性却太强。作为人工智能的一种,BP神经网络已经开始被应用到管理评价当中,因此本文致力于研究将BP神经网络与AHP层次分析法这两种理论方法应用于知识型员工-岗位匹配当中,以期更好、更高的效率解决知识型员工人岗匹配问题。
论文比较了传统的人岗匹配方法,介绍了知识型员工以及BP神经网络、AHP的相关理论。在此基础上,基于BP神经网络、AHP原理各自的优势,针对本文要解决的知识型员工岗位匹配问题,论文提出了基于AHP-BP神经网络的知识型员工-岗位匹配评价思想。论文呈现了该方法的流程:利用AHP对评价指标进行筛选,确定知识型员工-岗位匹配评价要素,并且利用AHP进行评价;利用AHP筛选的指标构建BP神经网络模型,然后利用所构建的BP神经网络模型对知识型员工-岗位匹配进行评价;将上述两种评价方法的结果进行组合加权,得出最终的评价结果。接着,论文通过算例仿真对其所构建的评价方法进行验证,结果表明了该模型是科学有效的。最后,本文又分别比较了基于AHP、BP、AHP-BP三种知识型员工-岗位匹配评价方法的优劣,比较结果显示本文所提出的综合评价方法,既利用了AHP评价法操作简单、易于理解、解释力强、可用于比较研究的特点,又利用了BP神经网络的基于客观数据评价的优势,将二者很好地结合了起来。为企业在实际中解决人岗匹配评价问题提供了有效的方法和依据。
In recent years, human resources play increasingly important role in business operations, and then job fit of employees get more and more important. Knowledge workers have become a kind of critical resource for our society, so evaluation of job fit for them has higher priority. There are many traditional evaluation methods of job fit which are reasonable, but too subjective, such as arrangement method, classification method, scoring method, factor-comparison method, etc. As one branch of artificial intelligence, BP neural network has been applied in management evaluation. So this dissertation applied BP neural network and AHP to research on job fit of the knowledge workers
This dissertation compared the characteristic feature of traditional evaluation methods of job fit, introduced the principle of BP neural network and AHP. According of the chief advantages of the two methods, aimming at the problem of the job fit of the knowledge workers, this dissertation proposed an approach to measure job fit by using AHP and BP neural network compensively. The dissertation showed the process of the method:using of AHP to choose indexes and determine the elements then to evaluate the ob fit of the knowledge workers and at last using the indexes to build BP neural network model which is used to evaluate the job fit of the knowledge workers; combining the results of the two methods to get the final result of evaluation.Then the dissertation through arithmetic simulation to validate the evaluation which the is showwed scientific and effective.Finally the dissertation compared the advantages and disadvantages of three evaluationes grouped based on AHP, BP, AHP-BP which shows that this method not only taking the advantage of AHP evaluation possesses virtues of simple to operation, easy to understand, better to interpret, and comparability but also making use of the advantage of BP neural network esteemed is objective.It enjoies profits both of them skillfully and provides effective rules and methods for enterprises to solve the problem in practice.
论文比较了传统的人岗匹配方法,介绍了知识型员工以及BP神经网络、AHP的相关理论。在此基础上,基于BP神经网络、AHP原理各自的优势,针对本文要解决的知识型员工岗位匹配问题,论文提出了基于AHP-BP神经网络的知识型员工-岗位匹配评价思想。论文呈现了该方法的流程:利用AHP对评价指标进行筛选,确定知识型员工-岗位匹配评价要素,并且利用AHP进行评价;利用AHP筛选的指标构建BP神经网络模型,然后利用所构建的BP神经网络模型对知识型员工-岗位匹配进行评价;将上述两种评价方法的结果进行组合加权,得出最终的评价结果。接着,论文通过算例仿真对其所构建的评价方法进行验证,结果表明了该模型是科学有效的。最后,本文又分别比较了基于AHP、BP、AHP-BP三种知识型员工-岗位匹配评价方法的优劣,比较结果显示本文所提出的综合评价方法,既利用了AHP评价法操作简单、易于理解、解释力强、可用于比较研究的特点,又利用了BP神经网络的基于客观数据评价的优势,将二者很好地结合了起来。为企业在实际中解决人岗匹配评价问题提供了有效的方法和依据。
In recent years, human resources play increasingly important role in business operations, and then job fit of employees get more and more important. Knowledge workers have become a kind of critical resource for our society, so evaluation of job fit for them has higher priority. There are many traditional evaluation methods of job fit which are reasonable, but too subjective, such as arrangement method, classification method, scoring method, factor-comparison method, etc. As one branch of artificial intelligence, BP neural network has been applied in management evaluation. So this dissertation applied BP neural network and AHP to research on job fit of the knowledge workers
This dissertation compared the characteristic feature of traditional evaluation methods of job fit, introduced the principle of BP neural network and AHP. According of the chief advantages of the two methods, aimming at the problem of the job fit of the knowledge workers, this dissertation proposed an approach to measure job fit by using AHP and BP neural network compensively. The dissertation showed the process of the method:using of AHP to choose indexes and determine the elements then to evaluate the ob fit of the knowledge workers and at last using the indexes to build BP neural network model which is used to evaluate the job fit of the knowledge workers; combining the results of the two methods to get the final result of evaluation.Then the dissertation through arithmetic simulation to validate the evaluation which the is showwed scientific and effective.Finally the dissertation compared the advantages and disadvantages of three evaluationes grouped based on AHP, BP, AHP-BP which shows that this method not only taking the advantage of AHP evaluation possesses virtues of simple to operation, easy to understand, better to interpret, and comparability but also making use of the advantage of BP neural network esteemed is objective.It enjoies profits both of them skillfully and provides effective rules and methods for enterprises to solve the problem in practice.
引文
[1]任淑美.人力资源管理[M].北京:经济管理出版社,2005:71
[2]樊宏,戴良铁.人与组织匹配招聘的一种新模式[J].企业人力资源管理,2004(3):36-37
[3]Schmidt F. L,Hunter J. E.Measurement Error in Psychological Research: Lessons from 26 Research Scenarios[J].Psychological Methods,1996,1(2):33
[4]Cortina J. M,Goldstein N. B,Payne S. C.The Increment Invalid It You Interview Seoresovemnd above Cognitive Ablaut and Conscientiousness Scores [J].PemonnePsychology,2000(53):325-351
[5]James L. R,Damaree R. G,Wolf G..Estimating within Grounder Rater Reliability with and without Response Bias [J].Joumal of Applied Psychology,1984(19):85-98
[6]Edwards. Spatial Aspects of Rural Development[M].Agricultural Economics Research,1981(33):3
[7]Adem Golec &Esra Kahya.A Fuzzy Model for Competency-Based Employee Evaluation and Selection[J].Computers & Industrial Engineering,2007(52):143–161
[8]Kuo Kuang Huang.Using an Annealed Neural Network in Organization Personal Management[D].University of South Dakota Ph.D,1999
[9]Hart,Ann Yeager.Prediction the Tenure Outcome of Teachers Based on Variables Known at the Time of Application[D].North Carolina State University,1997
[10]金杨华,王重鸣.人与组织匹配研究进展及其意义[J].人类工效学,2001(6):36-37
[11]黄焕山,刘帆.岗位匹配系统论[J].广东行政学院学报,2000(10):37-41
[12]王丽萍.能岗匹配的方法基础—工作设计[J].中国人力资源开发,2003(8):45-47
[13]罗伟良.人力资源配置的个人—岗位匹配动态模型[J].引进与咨询,2003(5):30
[14]张晓娜.基于AHP-ANN模型我国金融安全预警体系研究[D].南京:南京航空航天大学,2008(9):30-34
[15]陈涛.基于AHP与ANN的企业经济效益综合评价[M].商场现代化,2007,7(510):80-81
[16]齐二石,蔺宇,王庆.科技人才岗位匹配度测算研究[J].科技管理研究,2007,1(54):132-134
[17]王庆,齐二石.基于AHP-模糊综合评价的人才岗位匹配度测算[J].人类工效学,2007,2(13):19-21
[18]李广义.层次分析法的岗位评价模型设计[J].中国流通经济,2004(4):40-42
[19]汪克亮,杨力,查甫更.基于BP神经网络的工作岗位评价系统设计[J].企业经济,2007(12):30-32
[20]刘秋连. A海事局人岗匹配优化研究[D].武汉:武汉理工大学,2007:7-8
[21]郭滨洋.企业人岗匹配评分模型及应用研究[D].哈尔滨:哈尔滨理工大学,2009:11
[22]孙艳艳.彭倩.人岗匹配问题初探[J].商场现代化.2008,4(537):313-314
[23]唐琳.华强智能激励研发人员的实证研究[D].武汉:华中科技大学,2004:3-4
[24]柳丽华.企业知识型员工绩效管理研究[D].山东:山东大学,2006:11-12
[25]唐琳.华强智能激励研发人员的实证研究[D].武汉:华中科技大学,2004:3-4.
[26]徐庆.我国外资企业知识型员工激励机制研究[D].吉林:吉林大学,2008:4-5
[27]柳丽华.企业知识型员工绩效管理研究[D].山东:山东大学,2006:11-12
[28]徐庆.我国外资企业知识型员工激励机制研究[D].吉林:吉林大学,2008:4-5
[29]王森.知识型员工流动路径模型及其价值评价[D].天津:天津大学,2007:12-14
[30]王庆.知识型企业知识员工任务指派及调度决策问题研究[D].天津:天津大学,2006:20-22
[31]程建岗.战略视野下的人岗匹配管理[J].人力资源,2007,8(1):14
[32]黄道峰.中国银行JY分行人岗匹配管理变革研究[D].陕西:西北大学,2007:21-23
[33]朱平利.企业中人岗匹配度测算模型及应用[J].湖北工业大学学报,2009,12(15):25-26
[34]刘秋连.A海事局人岗匹配优化研究[D].武汉:武汉理工大学,2007:10-12
[35]向秋华.基于心理契约的中国企业知识型员工管理创新研究[D].武汉:中南大学,2007:27-30
[36]潘春花.浅谈人工神经网络[J].电脑知识与技术,2009,7(5):5502
[37]沈荣.张保文.人工神经网络初探[J].中国科技信息,2009(18):30
[38]陈格.人工神经网络技术发展综述[J].中国科技信息,2009(19):88-89
[39]孙吉辉,孟祥锋.人工神经网络简介[J].教育综合研究,2008(10):159
[40]Martin T. Hagan. Howand B Demuth and Mark H. Beale.戴葵等译.神经网络设计[M].机械工业出版社,2002:56
[41]李俊山,韩先锋,李建军,李丝.基于进化策略的BP神经网络匹配算法研究[J].红外与激光工程-光电信息处理技术,2006(10):2-3
[42]熊明勇,陈宁,张克旭.人工神经网络及其在氨基酸发酵中的应用[J].天津科技大学学报,2007(19):40
[43]唐丛敏.岗位评价技术研究-层次分析法在岗位评价中的应用[D].南京:南京理工大学,2005:15-17
[44]余正,肖峻,莫易敏.基于MATLAB /GUI的层次分析法在投资评价中的应用[J].机械研究与应用,2009,5(3):103-104
[45]唐丛敏.岗位评价技术研究[D].南京:南京理工大学,2005:15-18
[46]张国初.人力资源管理定量测度与评价[M].社会科学文献出版社,2000:34
[47]谢季坚,刘秉平.模糊数学方法及其应用第三版[M].华中科技大学出版,2006(8)
[48]张红.基于AHP-ANN模型的医药类风险投资项目评估方法研究[J].湖南医科大学学报,2005,6(2):69-71
[49]张立明.人工神经网络的模型及其应用[M].复旦大学出版社,1993:12
[50]张晓娜.基于AHP-ANN模型我国金融安全预警体系研究[D].南京:南京航空航天大学,2008:30-34
[2]樊宏,戴良铁.人与组织匹配招聘的一种新模式[J].企业人力资源管理,2004(3):36-37
[3]Schmidt F. L,Hunter J. E.Measurement Error in Psychological Research: Lessons from 26 Research Scenarios[J].Psychological Methods,1996,1(2):33
[4]Cortina J. M,Goldstein N. B,Payne S. C.The Increment Invalid It You Interview Seoresovemnd above Cognitive Ablaut and Conscientiousness Scores [J].PemonnePsychology,2000(53):325-351
[5]James L. R,Damaree R. G,Wolf G..Estimating within Grounder Rater Reliability with and without Response Bias [J].Joumal of Applied Psychology,1984(19):85-98
[6]Edwards. Spatial Aspects of Rural Development[M].Agricultural Economics Research,1981(33):3
[7]Adem Golec &Esra Kahya.A Fuzzy Model for Competency-Based Employee Evaluation and Selection[J].Computers & Industrial Engineering,2007(52):143–161
[8]Kuo Kuang Huang.Using an Annealed Neural Network in Organization Personal Management[D].University of South Dakota Ph.D,1999
[9]Hart,Ann Yeager.Prediction the Tenure Outcome of Teachers Based on Variables Known at the Time of Application[D].North Carolina State University,1997
[10]金杨华,王重鸣.人与组织匹配研究进展及其意义[J].人类工效学,2001(6):36-37
[11]黄焕山,刘帆.岗位匹配系统论[J].广东行政学院学报,2000(10):37-41
[12]王丽萍.能岗匹配的方法基础—工作设计[J].中国人力资源开发,2003(8):45-47
[13]罗伟良.人力资源配置的个人—岗位匹配动态模型[J].引进与咨询,2003(5):30
[14]张晓娜.基于AHP-ANN模型我国金融安全预警体系研究[D].南京:南京航空航天大学,2008(9):30-34
[15]陈涛.基于AHP与ANN的企业经济效益综合评价[M].商场现代化,2007,7(510):80-81
[16]齐二石,蔺宇,王庆.科技人才岗位匹配度测算研究[J].科技管理研究,2007,1(54):132-134
[17]王庆,齐二石.基于AHP-模糊综合评价的人才岗位匹配度测算[J].人类工效学,2007,2(13):19-21
[18]李广义.层次分析法的岗位评价模型设计[J].中国流通经济,2004(4):40-42
[19]汪克亮,杨力,查甫更.基于BP神经网络的工作岗位评价系统设计[J].企业经济,2007(12):30-32
[20]刘秋连. A海事局人岗匹配优化研究[D].武汉:武汉理工大学,2007:7-8
[21]郭滨洋.企业人岗匹配评分模型及应用研究[D].哈尔滨:哈尔滨理工大学,2009:11
[22]孙艳艳.彭倩.人岗匹配问题初探[J].商场现代化.2008,4(537):313-314
[23]唐琳.华强智能激励研发人员的实证研究[D].武汉:华中科技大学,2004:3-4
[24]柳丽华.企业知识型员工绩效管理研究[D].山东:山东大学,2006:11-12
[25]唐琳.华强智能激励研发人员的实证研究[D].武汉:华中科技大学,2004:3-4.
[26]徐庆.我国外资企业知识型员工激励机制研究[D].吉林:吉林大学,2008:4-5
[27]柳丽华.企业知识型员工绩效管理研究[D].山东:山东大学,2006:11-12
[28]徐庆.我国外资企业知识型员工激励机制研究[D].吉林:吉林大学,2008:4-5
[29]王森.知识型员工流动路径模型及其价值评价[D].天津:天津大学,2007:12-14
[30]王庆.知识型企业知识员工任务指派及调度决策问题研究[D].天津:天津大学,2006:20-22
[31]程建岗.战略视野下的人岗匹配管理[J].人力资源,2007,8(1):14
[32]黄道峰.中国银行JY分行人岗匹配管理变革研究[D].陕西:西北大学,2007:21-23
[33]朱平利.企业中人岗匹配度测算模型及应用[J].湖北工业大学学报,2009,12(15):25-26
[34]刘秋连.A海事局人岗匹配优化研究[D].武汉:武汉理工大学,2007:10-12
[35]向秋华.基于心理契约的中国企业知识型员工管理创新研究[D].武汉:中南大学,2007:27-30
[36]潘春花.浅谈人工神经网络[J].电脑知识与技术,2009,7(5):5502
[37]沈荣.张保文.人工神经网络初探[J].中国科技信息,2009(18):30
[38]陈格.人工神经网络技术发展综述[J].中国科技信息,2009(19):88-89
[39]孙吉辉,孟祥锋.人工神经网络简介[J].教育综合研究,2008(10):159
[40]Martin T. Hagan. Howand B Demuth and Mark H. Beale.戴葵等译.神经网络设计[M].机械工业出版社,2002:56
[41]李俊山,韩先锋,李建军,李丝.基于进化策略的BP神经网络匹配算法研究[J].红外与激光工程-光电信息处理技术,2006(10):2-3
[42]熊明勇,陈宁,张克旭.人工神经网络及其在氨基酸发酵中的应用[J].天津科技大学学报,2007(19):40
[43]唐丛敏.岗位评价技术研究-层次分析法在岗位评价中的应用[D].南京:南京理工大学,2005:15-17
[44]余正,肖峻,莫易敏.基于MATLAB /GUI的层次分析法在投资评价中的应用[J].机械研究与应用,2009,5(3):103-104
[45]唐丛敏.岗位评价技术研究[D].南京:南京理工大学,2005:15-18
[46]张国初.人力资源管理定量测度与评价[M].社会科学文献出版社,2000:34
[47]谢季坚,刘秉平.模糊数学方法及其应用第三版[M].华中科技大学出版,2006(8)
[48]张红.基于AHP-ANN模型的医药类风险投资项目评估方法研究[J].湖南医科大学学报,2005,6(2):69-71
[49]张立明.人工神经网络的模型及其应用[M].复旦大学出版社,1993:12
[50]张晓娜.基于AHP-ANN模型我国金融安全预警体系研究[D].南京:南京航空航天大学,2008:30-34