企业知识群体行为的定性模拟研究
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摘要
市场的国际化加剧了企业环境的不确定性。为了增强企业的灵活性和反应速度,许多企业纷纷在组织内成立一些小组或团队群体,希望通过将不同个人的创新思想进行有效融合,增强企业的创造力。因此,对群体的研究引起了人们的普遍重视。常见的研究方法包括设计实验验证或进行实证分析,而对计算机等现代辅助技术的运用十分贫乏。定性模拟技术的出现为群体行为的研究提供了一种新的方法。
本文首先分析了知识群体中合作的特点,阐述了团队合作的非零和博弈特征。现有的博弈分析都是研究是否合作的问题,即只考虑合作或不合作两种策略。本文将问题扩大到不同合作程度上的分析,并且将收益值也模糊化,从而使分析更加贴近实际。为此,本文设计了一种定性混合建模方法,对于已知的定量关系,构建部份数学函数,即定量子模型; 对于已知的定性关系,建立部份类似定性加和定性减的逻辑关系,即定性子模型。而后通过两个子模型中公用变量间的关联,运用相关辅助知识进行推理,以此获得系统的变化趋势。按照上述方法,构建了一个二人团队的合作博弈模型,设计了模拟规则、算法和步骤。模拟结果表明,对于信息不充分而无法建立数学模型的博弈问题,用本文设计的半定性模拟方法,也可以进行求解。
群体内部是由多个不同的成员群组成的,不同成员群之间的相互作用关系并非是线性的,也不是正式组织结构中的等级关系。有的小群体可能处于主导地位,其行为对其它小群体的影响比它所受到的影响要大。所以本文又设计了一种集成化的定性因果推理算法,用于描述和解释不同人群行为的变化,对变量的描述、显著时间点、显著值和群体行为的因果性等进行了解释,并构建了一个人群行为的因果图。然后,研究了如何将QSIM 算法与基本因果推理技术结合起来,设计了管理策略、环境和群体行为之间相互作用的表述方法,给出了定性模拟方法中的模拟规则和模拟机制。最后,将本方法应用于一个选择管理策略以有效激励员工的例子中,对所述的方法进行了验证。
分析了任务型群体的主要特点,以知识群体的工作过程和群体所处的环境因素为重点,按照单元分解的方法构建了一个任务型知识群体工作过程模型。针对上述模型设计了变量间相互影响的作用规则,运用相关常识和专家知识对变量的状态转换进行
The uncertainty of environment for enterprise has been intensified by the internationalization of market. In order to enhance the flexibility and reaction speed of enterprise, many groups or teams are set up in enterprises. In group, innovation ideas of individual could be blended to enhance the creativity of enterprise. So many professionals have been attracted to work in this field. In these studies, common research methods include experimental verification and demonstrational analysis. But modern auxiliary techniques such as computer simulation have been rarely taken. The advent of the qualitative simulation provides a new way for the research of group behavior.
The characteristics of cooperation in knowledge group are analyzed firstly, in which its non-zero game characteristic is discussed. In most researchs, only two choices are concerned: cooperation or no cooperation. In this dissertation, the degree of cooperation is concerned. Sub-groups’income is fuzzified to make it more close to the fact. Therefore, a hybrid qualitative modeling method is designed. For the known quantitative relations within variables, mathematical function, i.e., quantitative model, is built. For the known qualitative relations, the logical relation, which seem as qualitative “+”and “-”, is built. The trends of change for system are simulated by integrating the two models with common variables, and using auxiliary knowledge. A gaming model of two-person team is then built, in which the rules, algorithm and steps for simulation are designed.
Group consists of different sub-groups. The interactions within them are neither linear nor hierarchical in the formal organization. Some sub-groups may be the leader of the group, their behaviors may take great influence on the others. So an integrated qualitative causal reasoning algorithm is designed to describe and explain behavior changes of different sub-groups. The description of variables, distinctive time points, distinctive value and causality of group behavior are interpreted. A causality graph of group behavior is depicted. Then the method of combining QSIM algorithm with basic causal reasoning technology is studied. Representations for interaction within management strategy,
complexity of environment and group behavior are designed. Simulation rules and simulation mechanism are given. Finally, this method is applied to an example of management decision on motivating employees. The validation of the method is taken. The characteristics of task-oriented-group are analyzed. Then a work process model for task-oriented-group is designed according to the method of cell decomposition. In this model, the work process of group and environment of group are taken as key points. Rules for the interaction of variables are designed. Common sense and expert knowledge are used to constrain transition of variable state. Probability distribution is adopted to resolve the uncertainty of transition. The behaviors of system are yielded by simulation of many times other than one time. Finally, nine situations are chosen to show application of simulation in term of different cross combinations of leader characteristics, management strategy, interference in interpersonal relationship and interference in work. Simulation results indicate that, combination explosion could be avoided by two ways. First, the rules are set up by combining common sense with expert knowledge; Second, probability distribution is used to constrain state transitions. The characteristics of behavior change of group can be simulated using our method. Based on the above researches, the prototype of qualitative simulation system for task-oriented-group behavior is developed. The structure and functions of the system are builded. The modules including initial setting, knowledge management, simulation control, strategy evaluation, result management, are designed. Object oriented programming and qualitative simulation technology are integrated. The qualitative simulation module and other relevant functions are also coded by VB6.0.
本文首先分析了知识群体中合作的特点,阐述了团队合作的非零和博弈特征。现有的博弈分析都是研究是否合作的问题,即只考虑合作或不合作两种策略。本文将问题扩大到不同合作程度上的分析,并且将收益值也模糊化,从而使分析更加贴近实际。为此,本文设计了一种定性混合建模方法,对于已知的定量关系,构建部份数学函数,即定量子模型; 对于已知的定性关系,建立部份类似定性加和定性减的逻辑关系,即定性子模型。而后通过两个子模型中公用变量间的关联,运用相关辅助知识进行推理,以此获得系统的变化趋势。按照上述方法,构建了一个二人团队的合作博弈模型,设计了模拟规则、算法和步骤。模拟结果表明,对于信息不充分而无法建立数学模型的博弈问题,用本文设计的半定性模拟方法,也可以进行求解。
群体内部是由多个不同的成员群组成的,不同成员群之间的相互作用关系并非是线性的,也不是正式组织结构中的等级关系。有的小群体可能处于主导地位,其行为对其它小群体的影响比它所受到的影响要大。所以本文又设计了一种集成化的定性因果推理算法,用于描述和解释不同人群行为的变化,对变量的描述、显著时间点、显著值和群体行为的因果性等进行了解释,并构建了一个人群行为的因果图。然后,研究了如何将QSIM 算法与基本因果推理技术结合起来,设计了管理策略、环境和群体行为之间相互作用的表述方法,给出了定性模拟方法中的模拟规则和模拟机制。最后,将本方法应用于一个选择管理策略以有效激励员工的例子中,对所述的方法进行了验证。
分析了任务型群体的主要特点,以知识群体的工作过程和群体所处的环境因素为重点,按照单元分解的方法构建了一个任务型知识群体工作过程模型。针对上述模型设计了变量间相互影响的作用规则,运用相关常识和专家知识对变量的状态转换进行
The uncertainty of environment for enterprise has been intensified by the internationalization of market. In order to enhance the flexibility and reaction speed of enterprise, many groups or teams are set up in enterprises. In group, innovation ideas of individual could be blended to enhance the creativity of enterprise. So many professionals have been attracted to work in this field. In these studies, common research methods include experimental verification and demonstrational analysis. But modern auxiliary techniques such as computer simulation have been rarely taken. The advent of the qualitative simulation provides a new way for the research of group behavior.
The characteristics of cooperation in knowledge group are analyzed firstly, in which its non-zero game characteristic is discussed. In most researchs, only two choices are concerned: cooperation or no cooperation. In this dissertation, the degree of cooperation is concerned. Sub-groups’income is fuzzified to make it more close to the fact. Therefore, a hybrid qualitative modeling method is designed. For the known quantitative relations within variables, mathematical function, i.e., quantitative model, is built. For the known qualitative relations, the logical relation, which seem as qualitative “+”and “-”, is built. The trends of change for system are simulated by integrating the two models with common variables, and using auxiliary knowledge. A gaming model of two-person team is then built, in which the rules, algorithm and steps for simulation are designed.
Group consists of different sub-groups. The interactions within them are neither linear nor hierarchical in the formal organization. Some sub-groups may be the leader of the group, their behaviors may take great influence on the others. So an integrated qualitative causal reasoning algorithm is designed to describe and explain behavior changes of different sub-groups. The description of variables, distinctive time points, distinctive value and causality of group behavior are interpreted. A causality graph of group behavior is depicted. Then the method of combining QSIM algorithm with basic causal reasoning technology is studied. Representations for interaction within management strategy,
complexity of environment and group behavior are designed. Simulation rules and simulation mechanism are given. Finally, this method is applied to an example of management decision on motivating employees. The validation of the method is taken. The characteristics of task-oriented-group are analyzed. Then a work process model for task-oriented-group is designed according to the method of cell decomposition. In this model, the work process of group and environment of group are taken as key points. Rules for the interaction of variables are designed. Common sense and expert knowledge are used to constrain transition of variable state. Probability distribution is adopted to resolve the uncertainty of transition. The behaviors of system are yielded by simulation of many times other than one time. Finally, nine situations are chosen to show application of simulation in term of different cross combinations of leader characteristics, management strategy, interference in interpersonal relationship and interference in work. Simulation results indicate that, combination explosion could be avoided by two ways. First, the rules are set up by combining common sense with expert knowledge; Second, probability distribution is used to constrain state transitions. The characteristics of behavior change of group can be simulated using our method. Based on the above researches, the prototype of qualitative simulation system for task-oriented-group behavior is developed. The structure and functions of the system are builded. The modules including initial setting, knowledge management, simulation control, strategy evaluation, result management, are designed. Object oriented programming and qualitative simulation technology are integrated. The qualitative simulation module and other relevant functions are also coded by VB6.0.
引文
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