IT行业经济与管理指标测度与预报模型实证研究
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摘要
为了解决我国IT行业项目管理所面临的工期延误、费用超支、质量差强人意等典型问题,本文进行分析后认为造成这些问题的根本原因之一在于缺乏为IT行业项目设置量化目标的客观方法,因而本文的主要目标在于为IT行业项目建立关键管理指标体系,并研究这些指标之间的定量依赖关系。论文主要设计了IT行业项目质量和管理关键指标体系,并采用定量分析方法对指标之间的关系进行了分析和研究。
对于IT行业项目质量和管理指标体系及其关系研究论文采用了定性方法和定量方法相结合的研究方法。定性分析方法主要用于建立指标体系,通过查阅IT行业项目管理领域以及相关领域的参考文献,并结合作者在IT行业项目量化管理领域的咨询实践,对业界三种主要的IT行业项目管理相关模型——PMBOK、ICB以及CMMI模型进行了分析,认为当前的项目管理模型缺乏关于对建立IT行业项目质量和管理指标体系的指导。在项目管理模型分析的基础上,又对业界所涉及常见指标体系——ISO15939、SEI indicator ISBSG data questionnaires、SPR indicator和Bangalore SPIN indicator进行了分析,这些指标体系不同程度地存在体系不完整或者操作性较弱的缺点,因而本文从指标的管理意义、数据的可获得性以及对于IT行业项目关键指标的影响程度三方面综合考虑,以IT行业项目管理三角形为依据建立了四类指标,十六个指标项为内容的IT行业项目关键指标体系,该指标体系包含了IT行业项目的主要管理目标以及影响这些目标的关键因素。
论文对于指标依赖关系的研究则主要采用了定量分析的方法,对指标关系的研究又可以区分为线形关系和非线性关系研究。其中的线性研究采用简化指标关系的处理方式,给出了一种实际工作中容易操作,基于项目生产率、缺陷率和交付率三个派生指标的简化线性模型。而现实世界的IT行业项目质量和管理指标的依赖关系应该是非线性的依赖关系,因而非线性依赖关系的研究作为论文定量研究的主要内容。
对于非线性关系的研究根据所研究的对象特点采用了不同的研究方法。因为对于IT行业项目质量状况研究往往缺乏客观数据,论文采用了可以综合处理主观经验数据和客观数据的贝叶斯信任网络模型。论文首先建立了IT行业项目质量的基本贝叶斯网络,通过参数模型预报IT项目中的“潜伏”缺陷数目,在此基础上,论文对项目质量的基本贝叶斯网络进行了扩展,提出了对于客户更为有意义的项目质量的扩展贝叶斯网络,该网络引入了IT项目评审、IT项目测试、IT系统的使用程度等重要网络节点,从而使得扩展后的贝叶斯网络可以为实际使用中的IT系统进行IT项目质量预报。为项目质量预报建立的贝叶斯网络还可以通过IT系统实际使用过程中所积累的缺陷信息为网络提供反馈,以有效修改网络中的先验概率,从而为后续的IT系统的质量预报提供更准确的参考信息,最终达到持续优化项目质量预报贝叶斯网络的目的。
论文对于相对直观的IT项目管理指标的研究则采用了支持向量机算法模型。在对IT项目的工期指标和工作量指标的历史数据进行了归一化处理之后,将所研究的样本数据分割为训练数据、试验数据和检验数据。在进行支持向量机建模时主要应用了径向基核函数的向量机对于工期和工作量指标进行了回归模拟,并采用模拟模型对数据进行了预报。在使用支持向量机分析IT项目工期和IT项目工作量后,论文还对影响工期和工作量的相关指标进行了灵敏度分析,发现项目规模对于IT项目工作量的影响最为明显,项目团队人员规模位居其次,而项目类型、行业类型以及开发语言类型对于工作量的影响则相对轻微,甚至可以忽略不计；项目规模对于IT项目工期的影响程度则不如对工作量的影响更为明显,项目团队人员规模和项目类型对工期的影响仅次于项目规模,而行业类型和开发语言的影响则相对轻微。
在论文中作者根据IT项目质量和管理指标的特点不同而选用了不同的研究方法,但其结论应该结合起来使用,以便为IT项目的量化管理提供决策参考依据。论文最后还介绍了作者在IT项目质量和管理指标体系应用方面所从事的咨询工作,指出IT项目质量和管理指标体系关系的建立和应用对于IT行业的可持续发展有着不可替代的重要作用。
There usually exists typical difficulties for domestic IT project management work, such as time slippage, cost overrun, low-grade quality and so on. Based on careful examination, the thesis derives the conclusion that one of the root causes for the failed IT project is lack of quantitative method to establish objectives for the IT projects. Hence, the main goal of the thesis is to establish an IT project management indicator framework and explore the quantitative dependant relationship among the project quality and management indicators.
The thesis combines the qualitative and quantitative method to study the IT project quality and management indicator framework, the qualitative method is mainly used to establish the management indicator framework. According to the results of careful examination of the literatures in the field of project management and author's consulting practices in the field of IT quantitative project management, thesis explores three dominant IT project management models-PMBOK, ICB and CMMI. However, there is no definite guiding rule in these management models for establishing IT project management indicator framework. The thesis also analyses the industry indicator frameworks, such as ISO 15939, SEI indicator, ISBSG data questionnaire, SPR indicator and Bangalore SPIN indicator. Due to incompletency or lack of practice, these indicator frameworks are still not satisfying to describe the complete and practical management objectives for the IT project management. Therefore, the thesis designs a new framework for the IT project management indicator. Combining three factors, management concept of the indicator, data availability of the indicator and the important relation to the key indicator, the thesis suggests a 4-catogory 16-indicator framework. The suggested indicator framework is also based on project management triangle model, it encompasses 4 key indicators and other 12 affiliated indicators.
The thesis uses quantitative method to study the dependency relationship among the indicators. The thesis assumes that there exist two types of dependant relationship, linear relationship and non-linear relationship. The linear model simplifies the indicator relationship and presents a simple and linear model in order to achieving better operation performance. However, the IT project management indicator relationship in the real world should be more complex and the relationship is non-linear. Therefore, the non-linear relationship among the indicator framework is the main content for the quantitative study method. Considering different features of the study objects, the thesis adopts two types of analysis model. Because there is usually lacking the IT system quality related data, the Bayesian Belief Network(BBN) model is selected for it can combine the pre-tested subjective information with post-tested objective information. The first step of modeling a BBN IT quality model is building a Basic BBN model, it can forecast the potential defect number. The second step of BBN modeling is to extend the basic BBN IT quality model to form the Extended BBN model, it introduces review node, testing node, usage frequency node to predict the potential defect number which will be found during the end user operation period. The BBN predicting model can also use the real defect number information and feedback it to the BBN model to adjust the corresponding probability of the pre-test condition. Therefore, the BBN model can optimize the model for predicating IT system defect number in a continuous manner.
The thesis uses the Support Vector Machine (SVM) to study the IT project schedule indicator and effort indicator. The IT project schedule and effort related historical data are firstly normalized to meet the needs for SVM processing, then the data is divided up to 3 data files, including training sub-data, testing sub-data and predicting sub-data. Then the thesis adopts Radial Basis Function SVM to regress and predict the IT project schedule indicator and effort indicator。The thesis also analyses the sensitive degree among the indicators. Among the indicators which affect the IT project effort, the project size is the most important factor, the project team size is the second important. However, the contribution from project type, application type and the development language type are comparatively slight, even can be omitted. Project size contributes less to IT project schedule comparing with contribution to IT project effort, although it is still the most important one. The project team size and project type contribute similarly to the project schedule, the contributions from the application type and the language type are still very slight.
Although the thesis applies different research methods, the research results should be linked together in order to provide information for IT project management decision work. Finally, the thesis also introduces author's consulting practices in the field of IT quantitative project management, points out that IT project management indicator framework study and application is indispensable to continuous development for IT industry.
对于IT行业项目质量和管理指标体系及其关系研究论文采用了定性方法和定量方法相结合的研究方法。定性分析方法主要用于建立指标体系,通过查阅IT行业项目管理领域以及相关领域的参考文献,并结合作者在IT行业项目量化管理领域的咨询实践,对业界三种主要的IT行业项目管理相关模型——PMBOK、ICB以及CMMI模型进行了分析,认为当前的项目管理模型缺乏关于对建立IT行业项目质量和管理指标体系的指导。在项目管理模型分析的基础上,又对业界所涉及常见指标体系——ISO15939、SEI indicator ISBSG data questionnaires、SPR indicator和Bangalore SPIN indicator进行了分析,这些指标体系不同程度地存在体系不完整或者操作性较弱的缺点,因而本文从指标的管理意义、数据的可获得性以及对于IT行业项目关键指标的影响程度三方面综合考虑,以IT行业项目管理三角形为依据建立了四类指标,十六个指标项为内容的IT行业项目关键指标体系,该指标体系包含了IT行业项目的主要管理目标以及影响这些目标的关键因素。
论文对于指标依赖关系的研究则主要采用了定量分析的方法,对指标关系的研究又可以区分为线形关系和非线性关系研究。其中的线性研究采用简化指标关系的处理方式,给出了一种实际工作中容易操作,基于项目生产率、缺陷率和交付率三个派生指标的简化线性模型。而现实世界的IT行业项目质量和管理指标的依赖关系应该是非线性的依赖关系,因而非线性依赖关系的研究作为论文定量研究的主要内容。
对于非线性关系的研究根据所研究的对象特点采用了不同的研究方法。因为对于IT行业项目质量状况研究往往缺乏客观数据,论文采用了可以综合处理主观经验数据和客观数据的贝叶斯信任网络模型。论文首先建立了IT行业项目质量的基本贝叶斯网络,通过参数模型预报IT项目中的“潜伏”缺陷数目,在此基础上,论文对项目质量的基本贝叶斯网络进行了扩展,提出了对于客户更为有意义的项目质量的扩展贝叶斯网络,该网络引入了IT项目评审、IT项目测试、IT系统的使用程度等重要网络节点,从而使得扩展后的贝叶斯网络可以为实际使用中的IT系统进行IT项目质量预报。为项目质量预报建立的贝叶斯网络还可以通过IT系统实际使用过程中所积累的缺陷信息为网络提供反馈,以有效修改网络中的先验概率,从而为后续的IT系统的质量预报提供更准确的参考信息,最终达到持续优化项目质量预报贝叶斯网络的目的。
论文对于相对直观的IT项目管理指标的研究则采用了支持向量机算法模型。在对IT项目的工期指标和工作量指标的历史数据进行了归一化处理之后,将所研究的样本数据分割为训练数据、试验数据和检验数据。在进行支持向量机建模时主要应用了径向基核函数的向量机对于工期和工作量指标进行了回归模拟,并采用模拟模型对数据进行了预报。在使用支持向量机分析IT项目工期和IT项目工作量后,论文还对影响工期和工作量的相关指标进行了灵敏度分析,发现项目规模对于IT项目工作量的影响最为明显,项目团队人员规模位居其次,而项目类型、行业类型以及开发语言类型对于工作量的影响则相对轻微,甚至可以忽略不计；项目规模对于IT项目工期的影响程度则不如对工作量的影响更为明显,项目团队人员规模和项目类型对工期的影响仅次于项目规模,而行业类型和开发语言的影响则相对轻微。
在论文中作者根据IT项目质量和管理指标的特点不同而选用了不同的研究方法,但其结论应该结合起来使用,以便为IT项目的量化管理提供决策参考依据。论文最后还介绍了作者在IT项目质量和管理指标体系应用方面所从事的咨询工作,指出IT项目质量和管理指标体系关系的建立和应用对于IT行业的可持续发展有着不可替代的重要作用。
There usually exists typical difficulties for domestic IT project management work, such as time slippage, cost overrun, low-grade quality and so on. Based on careful examination, the thesis derives the conclusion that one of the root causes for the failed IT project is lack of quantitative method to establish objectives for the IT projects. Hence, the main goal of the thesis is to establish an IT project management indicator framework and explore the quantitative dependant relationship among the project quality and management indicators.
The thesis combines the qualitative and quantitative method to study the IT project quality and management indicator framework, the qualitative method is mainly used to establish the management indicator framework. According to the results of careful examination of the literatures in the field of project management and author's consulting practices in the field of IT quantitative project management, thesis explores three dominant IT project management models-PMBOK, ICB and CMMI. However, there is no definite guiding rule in these management models for establishing IT project management indicator framework. The thesis also analyses the industry indicator frameworks, such as ISO 15939, SEI indicator, ISBSG data questionnaire, SPR indicator and Bangalore SPIN indicator. Due to incompletency or lack of practice, these indicator frameworks are still not satisfying to describe the complete and practical management objectives for the IT project management. Therefore, the thesis designs a new framework for the IT project management indicator. Combining three factors, management concept of the indicator, data availability of the indicator and the important relation to the key indicator, the thesis suggests a 4-catogory 16-indicator framework. The suggested indicator framework is also based on project management triangle model, it encompasses 4 key indicators and other 12 affiliated indicators.
The thesis uses quantitative method to study the dependency relationship among the indicators. The thesis assumes that there exist two types of dependant relationship, linear relationship and non-linear relationship. The linear model simplifies the indicator relationship and presents a simple and linear model in order to achieving better operation performance. However, the IT project management indicator relationship in the real world should be more complex and the relationship is non-linear. Therefore, the non-linear relationship among the indicator framework is the main content for the quantitative study method. Considering different features of the study objects, the thesis adopts two types of analysis model. Because there is usually lacking the IT system quality related data, the Bayesian Belief Network(BBN) model is selected for it can combine the pre-tested subjective information with post-tested objective information. The first step of modeling a BBN IT quality model is building a Basic BBN model, it can forecast the potential defect number. The second step of BBN modeling is to extend the basic BBN IT quality model to form the Extended BBN model, it introduces review node, testing node, usage frequency node to predict the potential defect number which will be found during the end user operation period. The BBN predicting model can also use the real defect number information and feedback it to the BBN model to adjust the corresponding probability of the pre-test condition. Therefore, the BBN model can optimize the model for predicating IT system defect number in a continuous manner.
The thesis uses the Support Vector Machine (SVM) to study the IT project schedule indicator and effort indicator. The IT project schedule and effort related historical data are firstly normalized to meet the needs for SVM processing, then the data is divided up to 3 data files, including training sub-data, testing sub-data and predicting sub-data. Then the thesis adopts Radial Basis Function SVM to regress and predict the IT project schedule indicator and effort indicator。The thesis also analyses the sensitive degree among the indicators. Among the indicators which affect the IT project effort, the project size is the most important factor, the project team size is the second important. However, the contribution from project type, application type and the development language type are comparatively slight, even can be omitted. Project size contributes less to IT project schedule comparing with contribution to IT project effort, although it is still the most important one. The project team size and project type contribute similarly to the project schedule, the contributions from the application type and the language type are still very slight.
Although the thesis applies different research methods, the research results should be linked together in order to provide information for IT project management decision work. Finally, the thesis also introduces author's consulting practices in the field of IT quantitative project management, points out that IT project management indicator framework study and application is indispensable to continuous development for IT industry.
引文
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64.杨志民刘广利,“不确定性支持向量机原理及应用”,科学出版社ISBN978-7-03-018775-8
65. Hugh Bucknall著,郑伟译,“人力资源量化管理”,中信出版社ISBN978-7-5086-0977-5／F 1206
66.孙向东,“蛋白质结构预测——支持向量机的应用”,科学出版社,ISBN978-7-03-022387-6
67.安迪等著,李剑峰等译,“战略绩效管理”,电子工业出版社,ISBN7-5053-9449-5
68.李子奈,“计量经济学(第二版)”,高等教育出版社,ISBN 7-04-016430-2
69. Brian E. Becker著郑晓明译,“人力资源记分卡”,机械工业出版社,ISBN7-111-12392-1
70. Rajeev T Shandilya著王克仁译,“软件项目管理”,科学出版社,ISBN7-03-010788-8
71.陈峰,“医用多元统计分析方法”,中国统计出版社,ISBN978-7-5037-3982-8
72.项目管理协会著卢有杰译,“项目管理知识体系指南(第三版)”,电子工业出版社,ISBN 7-121-00656-1
73.张德,“组织行为学”,高等教育出版社,ISBN 7-04-007080-4
74.全国注册资产评估师考试用书编写组,“建筑工程评估基础”,中国财政经济出版社,ISBN 7-5005-7107-0
75.汤铭端,“航天型号软件研制过程”,宇航出版社,ISBN 7-80144-247-4
76. Stephan H. Kan著吴明晖译,“软件质量工程——度量与模型(第二版)”,电子工业出版社,ISBN 7-5053-9912-8
77. Stacy J. Prowell著贲可荣译,“净室软件工程：技术与过程”,电子工业出版社,ISBN 7-5053-6726-9
78.周正伐,“可靠性工程基础”,宇航出版社,ISBN 7-80144-273-3
79.黄锡滋,“软件可靠性、安全性与质量保证”,电子工业出版社,ISBN7-5053-7990-9／TP 4644
80.全国造价工程师执业资格考试培训教材编审委员会,“工程造价计价与控制”,ISBN 978-7-80177-658-7
81.曹济王宁,“甲方如何采用量化机制管理项目”,项目管理技术,ISSN1672-4313,2006.9总第39期
82.曹济,“挣值分析在IT单项目与组合项目管理中的应用研究”,北京工业大学学报,ISSN0254-0037第33卷
83.曹济,刘黎明,“功能点分析方法在软件需求管理中的应用”,项目管理技术,ISSN1672-4313,2007.9总第51期
84.曹济,刘黎明,“基于货币价值的IT项目风险管理方法”,项目管理技术,ISSN1672-4313,2008.8总第62期
85.刘晓春,“航天科研人员绩效考评体系研究与应用”,国防科学技术大学硕士学位论文,2006.12
86.邢大红,“基于度量的软件过程改进方法的研究”,合肥工业大学博士学位论文,2004.02
87.侯红,“基于度量的软件过程管理方法与分析技术的研究”,西北大学博士学位论文,2006.488.李彦锋,“缺陷分类及度量方法在软件缺陷管理中的应用”,湖南大学博士学位论文,2006.0389.李心科,“软件故障分析及质量评估方法的研究”,合肥工业大学博士学位论文,2001.02
90.王双成,“用于风险管理的贝叶斯网络学习”,控制与决策,Vol.22 No.5
91.张亦含,“CMM4中量化管理的解决方案”,计算机工程与设计,Vol.27No.5
92.占永红,“IT项目成员离职预警模型研究”,武汉理工大学学报(信息管理与工程版),Vol.29 No.8
93.蒋国萍, “软件项目风险管理的贝叶斯网络模型研究”,国防科技大学博士学位论文,2005.10
94.白成刚,“基于Bayes网的软件残留错误数度量”,计算机工程,Vol.29No.18
95.郑翠芳,“基于贝叶斯网络的软件缺陷预测技术研究与应用”,中国工程物理研究院硕士论文,2005.06
96.周光,“一个基于统计过程的软件项目定量控制综合模型及其应用”,华中科技大学硕士学位论文,2005.05
97.吉格迪,“大型项目进度-费用绩效评价模型与应用研究”,内蒙古工业大学硕士学位论文,2005.10
98.王求真,“软件开发项目工作量估算技术的比较研究”,浙江大学学报(人文社会科学版),Vol.35 No.4
99.马辉,“公共项目管理绩效过程评价指标体系的构建”,管理科学,Vol.22No.7100.张园林,“国防预研项目中期评估指标体系”,武器装备自动化,Vol.27No.6101.卢梅,“建筑工程项目实施状态健康诊断指标体系研究”,西安建筑科技大学博士学位论文,2008.10
102.李方方,“贝叶斯框架下的LSSVM和贝叶斯网络及其应用”,计算机工程与设计,Vol.28 No.15
103.曾绍华,“供应商评价的支持向量机模型及应用研究”重庆师范大学学报(自然科学版),Vol.24 No.1
104.惠守博,“基于支持向量机的财务预警模型与应用研究”,计算机工程与设计,第27卷第7期
105.陈婷婷,“基于支持向量机的重庆外贸进出口信息分析及决策方法研究”,重庆大学硕士学位论文,2006.04
106.夏志杰,“基于组合权衡的IT项目投资决策模型及方法研究”,同济大学博士学位论文,2008.09
107.王继生,“支持向量机在交通量预测中的应用”,信息技术,第28卷第4期
108.肖燕彩,“支持向量机在变压器状态评估中的应用研究”,北京交通大学博士学位论文,2008.07
109.方骏,“支持向量机在工业质量检测中的应用研究”,浙江大学硕士学位论文,2004.02
110.陈艳,“ERP软件成本估算研究”,武汉理工大学硕士学位论文,2008.04
111.牛东晓,“非确定性工程项目计划管理的新方法研究”,华北电力大学博士学位论文,2001.12
112.谭仁先,“功能点分析在软件工程中的应用”,兰州交通大学学报(社会科学版),第24卷第5期
113.周海玲,“关于软件成本估算模型COCOMO的研究与校准的探讨”,苏州大学硕士学位论文,2005.04
114.周建,“关于软件质量的定量评估的研究”,电子科技大学硕士学位论文,2007.04
115.李亚红,“基于GQM模型的软件项目进度的度量过程”,计算机应用,第25卷第6期
116.陈宁,“基于IT的多项目共享资源均衡配置模型研究”,西南交通大学硕士学位论文,2006.10
117.周惠,“基于目标度量和预估技术的软件过程评估”,河海大学硕士学位论文,2004.03
118.刘殿奎,“基于时间成本双主线软件项目管理系统的研究与设计”,哈尔滨工程大学硕士学位论文,2003.02
119.胡冠林,“软件缺陷分类及其度量技术研究”,舰船电子工程,第25卷第3期
120.易海峰,“软件质量管理中过程性能度量与分析研究”,西安电子科技大学,2006.01
121.邵小亮,“银行软件项目管理及质量控制”,西南财经大学硕士学位论文,2003.10
15. P N Bukh, "Multiple integrated performance management systems:IC and BSC in a software company", Singapore Management Review,2002
16. Young H Kwak, "Calculating project management's return on investment", Proj ect Management Journal, June 2000
17. LUIS F. COPERTARI, "TIME, COST AND PERFORMANCE TRADEOFFS IN PROJECT MANAGEMENT ", Doctoral Dissertation from McMASTER University,2002
18. J-G Cho, "Functional estimation of activity criticality indices and sensitivity analysis of expected project completion time", Journal of the Operational Research Society (2004) 55,850-859
19. Megan Seen, "Benchmarking Business processes in software production:A case study", Benchmarking Journal,2001
20. J Art Go wan Jr, "The importance of management practices in IS project performance:Am empirical study", Journal of Enterprise Information Management,2005
21. Cao Ji, " Software Data Based Method Application in China", Proceedings of 1st Conference on Effective Software by Measurement and Analysis, Netherlands
22. GRANT R. CATES, "IMPROVING PROJECT MANAGEMENT WITH SIMULATION AND COMPLETION DISTRIBUTION FUNCTIONS", Doctoral Dissertation from University of Central Florida,2004
23. Farideh V. Gosleveli, "An Investigations of Project Dependencies and Risks in Project Schedule Slippage and Effort Overrun in the Engineering Computing Organization", Doctoral Dissertation from Nova Southeastern University, 2002
24. Deborah A. Walsh, "AN EVALUATION OF THE MATURING INDIAN SOFTWARE INDUSTRY ", Doctoral Dissertation from Capella University, November 2005
25. Guo Lan, "Software Quality and Reliability Prediction Using Dempster-Shafer Theory", Doctoral Dissertation from College of Engineering and Mineral Resources at West Virginia University,2004
26. Rodriguez Andy, "CRITICAL FACTORS IN HIRING, PROMOTING, AND
DESIGNING JOB DESCRIPTIONS FOR STRATEGIC PROJECT MANAGERS", Doctoral Dissertation from Capella University, February 2005
27. Joseph Gerard Szmerekovsky, "Maximizing Project Net-Present Value and Minimizing Work-in-progress in Projects", Case Western Reserve University, January 2003
28. Farideh V. Gozleveli, "An investigation of Project Dependencies and Risks in Project Schedule Slippage and Effort Overrun in the Engineering Computing Organization", Nova Southeastern University,2002
29. Minnesh Kaliprasad, "Proactive Risk Management", Cost Engineering, Dec 2006
30. Sary Regev, Avraham Shtub, Yakov Ben-Haim, "MANAGING PROJECT RISKS AS KNOWLEDGE GAPS", Project Management Journal, Dec 2006
31. B. Kayis, "IRMAS-development of a risk management tool for collaborative multi-site, multi-partner new product development projects", Journal of Manufacturing Technology Management, Vol.18 No.4,2007
32. Noor, Robert Martin, Douglas Bowman, "Implementation of Successful Risk-Based Portfolio Management", AACE International Transactions,2005
33. Wayne Haga, Kathryn Marold, "Monitoring and Control of PERT Networks", The Business Review, Cambridge, Summer 2005
34. J-G Cho, B-J Yum, "Functional estimation of activity criticality indices and sensitivity analysis of expected project completion time", Journal of the Operational Research Society,2004, Vol.55
35. Nick J. Lavingia, "World-Class Project Performance with Value Improving Practices",2007 AACE International Transactions
36. Keith R Molenaar, "Framework for Comparing Project Delivery Costs", Cost Engineering, Nov 2004
37. Albert P C Chan, Ada P L Chan, "Key performance indicators for measuring construction success", Benchmarking Journal,2004
38. Young H Kwak, C William Ibbs, "Calculating project management's return on investment", Project Management Journal, Jun 2000;
39. Carlos M Alvarado, Robert P Silverman, David S Wilson, "Assessing the performance of construction projects:Implementing earned value system",
Journal of Facilities Management, Jul 2004
40. Arif Mohamed, "IT spending set to rise during slump", Computer Weekly, Mar 18,2008
41. Gary Anthes, "Projects Get More Troublesome", Computerworld, Jan 1,2008
42. Scott W Ambler, "Defining Success", Dr. Dobb's Journal,Dec 2007
43. Tarek M. Hegazy, Wail Menesi, "Delay Analysis Under Multiple Baseline Updates",2007 AACE International Transactions
44. Steven H Appelbaum, "Critical Success Factors in the Client-Consulting Relationship", Journal of American Academy of Business, Mar 2004
45. Walter J Strutt, "Single-entry online progress measurement", AACE International Transactions,1997
46. Peerapong Aramvareekul, Daniel J Seider, "Cost-Time-Risk Diagram:Project Planning and Management", Cost Engineering, Nov 2006
47. Bruno Urli, Didier Urli, "Project management in North America, stability of the concepts", Project Management Journal, Sep 2000
48. Rodney L Robertson, Donald D Tippett, "Linking project team performance with team health", Engineering Management Journal, Mar 2002
49. Sara Ann McComb, Stephen G Green, W Dale Compton, "Project goals, team performance, and shared understanding", Engineering Management Journal, Sep 1999
50. James D Whiteside II, "Craft curves for estimating and project evaluation", AACE International Transactions,2002
51. J Kent Crawford, "THE PROJECT MANAGEMENT MATURITY MODEL", Information Systems Management, Fall 2006;
52. Michael Hardy, "Performance basis", Federal Computer Week, Dec 13,2004
53. Julia G Safronova, Vladislav V Dokuchaev, "Performance control system implementation", AACE International Transactions,2002
54. "Ofer Zwikael, Shlomo Globerson, Tzvi Raz, "Evaluation of models for forecasting the final cost of a project", Project Management Journal, Mar 2000
55. "Outputs and Outcomes",Russ Westcott, Quality Progress, Jul 2008
56. Edward Muzio, Deborah J Fisher, "SOFT SKILLS QUANTIFICATION (SSQ) FOR PROJECT MANAGER COMPETENCIES", Project Management Journal, Jun 2007
57. Donna J. Nardella, "Innovative Schedule Performance Measurements",2007 AACE International Transactions
58. Henri Barki, Suzanne Rivard, "An integrative contingency model of software project risk management", Management Decision,2001;
59. Jitesh Thakkar, "Development of a balanced scorecard:An integrated approach of Interpretive Structural Modeling (ISM) and Analytic Network Process (ANP)", Project Management Journal, Jun 2000
60. Eric O. Olsen, "Performance measurement system and relationships with performance results:A case analysis of a continuous improvement approach to PMS design", International Journal of Productivity and Performance Management Vol.56 No.1,2007
61. Martin Neil, Norman Fenton, "Predicting Software Quality using Bayesian Belief Networks", Proceedings of 21st Annual Software Engineering Workshop 62. Norman E Fenton, "Software Metrics:Roadmap", NASA/Goddard Space Flight Centre, December 4-5,1996
63.邓乃杨田英杰著,“支持向量机——理论、算法与拓展”,科学出版社ISBN 978-7-03-025031-5
64.杨志民刘广利,“不确定性支持向量机原理及应用”,科学出版社ISBN978-7-03-018775-8
65. Hugh Bucknall著,郑伟译,“人力资源量化管理”,中信出版社ISBN978-7-5086-0977-5／F 1206
66.孙向东,“蛋白质结构预测——支持向量机的应用”,科学出版社,ISBN978-7-03-022387-6
67.安迪等著,李剑峰等译,“战略绩效管理”,电子工业出版社,ISBN7-5053-9449-5
68.李子奈,“计量经济学(第二版)”,高等教育出版社,ISBN 7-04-016430-2
69. Brian E. Becker著郑晓明译,“人力资源记分卡”,机械工业出版社,ISBN7-111-12392-1
70. Rajeev T Shandilya著王克仁译,“软件项目管理”,科学出版社,ISBN7-03-010788-8
71.陈峰,“医用多元统计分析方法”,中国统计出版社,ISBN978-7-5037-3982-8
72.项目管理协会著卢有杰译,“项目管理知识体系指南(第三版)”,电子工业出版社,ISBN 7-121-00656-1
73.张德,“组织行为学”,高等教育出版社,ISBN 7-04-007080-4
74.全国注册资产评估师考试用书编写组,“建筑工程评估基础”,中国财政经济出版社,ISBN 7-5005-7107-0
75.汤铭端,“航天型号软件研制过程”,宇航出版社,ISBN 7-80144-247-4
76. Stephan H. Kan著吴明晖译,“软件质量工程——度量与模型(第二版)”,电子工业出版社,ISBN 7-5053-9912-8
77. Stacy J. Prowell著贲可荣译,“净室软件工程：技术与过程”,电子工业出版社,ISBN 7-5053-6726-9
78.周正伐,“可靠性工程基础”,宇航出版社,ISBN 7-80144-273-3
79.黄锡滋,“软件可靠性、安全性与质量保证”,电子工业出版社,ISBN7-5053-7990-9／TP 4644
80.全国造价工程师执业资格考试培训教材编审委员会,“工程造价计价与控制”,ISBN 978-7-80177-658-7
81.曹济王宁,“甲方如何采用量化机制管理项目”,项目管理技术,ISSN1672-4313,2006.9总第39期
82.曹济,“挣值分析在IT单项目与组合项目管理中的应用研究”,北京工业大学学报,ISSN0254-0037第33卷
83.曹济,刘黎明,“功能点分析方法在软件需求管理中的应用”,项目管理技术,ISSN1672-4313,2007.9总第51期
84.曹济,刘黎明,“基于货币价值的IT项目风险管理方法”,项目管理技术,ISSN1672-4313,2008.8总第62期
85.刘晓春,“航天科研人员绩效考评体系研究与应用”,国防科学技术大学硕士学位论文,2006.12
86.邢大红,“基于度量的软件过程改进方法的研究”,合肥工业大学博士学位论文,2004.02
87.侯红,“基于度量的软件过程管理方法与分析技术的研究”,西北大学博士学位论文,2006.488.李彦锋,“缺陷分类及度量方法在软件缺陷管理中的应用”,湖南大学博士学位论文,2006.0389.李心科,“软件故障分析及质量评估方法的研究”,合肥工业大学博士学位论文,2001.02
90.王双成,“用于风险管理的贝叶斯网络学习”,控制与决策,Vol.22 No.5
91.张亦含,“CMM4中量化管理的解决方案”,计算机工程与设计,Vol.27No.5
92.占永红,“IT项目成员离职预警模型研究”,武汉理工大学学报(信息管理与工程版),Vol.29 No.8
93.蒋国萍, “软件项目风险管理的贝叶斯网络模型研究”,国防科技大学博士学位论文,2005.10
94.白成刚,“基于Bayes网的软件残留错误数度量”,计算机工程,Vol.29No.18
95.郑翠芳,“基于贝叶斯网络的软件缺陷预测技术研究与应用”,中国工程物理研究院硕士论文,2005.06
96.周光,“一个基于统计过程的软件项目定量控制综合模型及其应用”,华中科技大学硕士学位论文,2005.05
97.吉格迪,“大型项目进度-费用绩效评价模型与应用研究”,内蒙古工业大学硕士学位论文,2005.10
98.王求真,“软件开发项目工作量估算技术的比较研究”,浙江大学学报(人文社会科学版),Vol.35 No.4
99.马辉,“公共项目管理绩效过程评价指标体系的构建”,管理科学,Vol.22No.7100.张园林,“国防预研项目中期评估指标体系”,武器装备自动化,Vol.27No.6101.卢梅,“建筑工程项目实施状态健康诊断指标体系研究”,西安建筑科技大学博士学位论文,2008.10
102.李方方,“贝叶斯框架下的LSSVM和贝叶斯网络及其应用”,计算机工程与设计,Vol.28 No.15
103.曾绍华,“供应商评价的支持向量机模型及应用研究”重庆师范大学学报(自然科学版),Vol.24 No.1
104.惠守博,“基于支持向量机的财务预警模型与应用研究”,计算机工程与设计,第27卷第7期
105.陈婷婷,“基于支持向量机的重庆外贸进出口信息分析及决策方法研究”,重庆大学硕士学位论文,2006.04
106.夏志杰,“基于组合权衡的IT项目投资决策模型及方法研究”,同济大学博士学位论文,2008.09
107.王继生,“支持向量机在交通量预测中的应用”,信息技术,第28卷第4期
108.肖燕彩,“支持向量机在变压器状态评估中的应用研究”,北京交通大学博士学位论文,2008.07
109.方骏,“支持向量机在工业质量检测中的应用研究”,浙江大学硕士学位论文,2004.02
110.陈艳,“ERP软件成本估算研究”,武汉理工大学硕士学位论文,2008.04
111.牛东晓,“非确定性工程项目计划管理的新方法研究”,华北电力大学博士学位论文,2001.12
112.谭仁先,“功能点分析在软件工程中的应用”,兰州交通大学学报(社会科学版),第24卷第5期
113.周海玲,“关于软件成本估算模型COCOMO的研究与校准的探讨”,苏州大学硕士学位论文,2005.04
114.周建,“关于软件质量的定量评估的研究”,电子科技大学硕士学位论文,2007.04
115.李亚红,“基于GQM模型的软件项目进度的度量过程”,计算机应用,第25卷第6期
116.陈宁,“基于IT的多项目共享资源均衡配置模型研究”,西南交通大学硕士学位论文,2006.10
117.周惠,“基于目标度量和预估技术的软件过程评估”,河海大学硕士学位论文,2004.03
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119.胡冠林,“软件缺陷分类及其度量技术研究”,舰船电子工程,第25卷第3期
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