基于知识管理视角的复杂产品研发绩效模型

复杂产品研发团队的知识管理显著地影响其研发绩效,基于知识管理视角研究了复杂产品研发团队的研发绩效。本文基于团队合作理论和知识管理理论,以复杂产品研发活动为背景,提出若干合理假设,应用经济学中成本-收益方法,建立了复杂产品研发绩效的数学模型,分析了影响复杂产品研发绩效的主要因素。研究结果表明:提高成员的知识接受能力可以提高研发绩效,但存在平台现象;团队规模与研发绩效之间呈现倒U型曲线关系;团队分组影响绩效,规模较大的团队适宜进行较多的分组;工作时间分配与绩效的关系取决于成员的知识接受能力。     

基于任务需求的团队知识传播研究

本文从组织内攻关任务的多种知识需求出发,考虑跨部门团队成员在完成任务过程中的知识交流与共享行为,构建了基于任务需求——团队知识相匹配的知识传播模型.模型中定义了任务知识需求矩阵、团队成员知识传播规则、知识协同生成规则以及任务需求与团队知识匹配规则,并通过计算机仿真的方法考察了不同知识交流策略对团队内部知识传播与任务完成效果的影响.仿真结果表明,基于关系的知识交流策略有利于知识在团队内部的快速传播,但不利于知识的广泛传播,在后期容易产生传播停滞现象,而基于知识的交流策略则具有明显的后发优势.混合策略不仅能够确保知识的快速传播,而且当混合策略中基于关系的知识交流概率较小时,知识传播效果甚至优于“基于知识”的交流策略.相应的管理策略是任务初期宜采用基于关系的知识交流策略,而在后期,采取基于知识的交流策略有助于团队顺利、有效地完成任务,与单一的采用基于关系或基于知识的交流策略相比,采用混合交流策略来完成团队任务具有明显的优势.     

变革型领导、知识共享与研发团队创造力:团队成员异质性的倒U型调节作用

本文基于变革型领导理论、知识共享理论、团队创造力理论及团队异质性理论,研究变革型领导对高新技术企业研发团队创造力的影响,及知识共享在这一作用过程中的中介效应,并提出带倒U型调节的混合模型,探索团队成员异质性的倒U型调节效应。通过对162家高新技术企业的实证研究,得出以下主要结论:变革型领导对研发团队创造力有显著正向影响;知识共享在变革型领导与研发团队创造力之间起部分中介作用;团队成员异质性在变革型领导与知识共享之间起倒U型调节作用,在知识共享与研发团队创造力之间起倒U型调节作用。     

基于动态网络模型的研发团队隐性知识转移研究

隐性知识在研发团队成员中迅速和有效的共享，对于企业开发新产品和获取竞争优势有重要意义。本文构建了研发团队隐性知识转移的动态网络模型，探讨了团队成员构成的群体网络的结构特征，对研发团队整体知识水平和知识转移速度产生的影响。并利用系统仿真，对模型的主要参数进行分析。模型为企业有效促进研发团队的隐性知识转移提供了建议。     

基于团队的知识共享和知识形成机理研究

越来越多的企业开始采用以团队为基础的组织结构，团队的核心能力在于能够实现知识共享，因此对团队知识共享及形成进行研究有着重要意义。本在阐述以团队为基础的组织与官僚层级制组织相比更有利于知识共享的基础上，从心理学和经济学的角度分析了团队知识共享的理论基础，指出了团队知识管理的三个误区，并首次提出了团队知识形成的三种机制和途径：事前学习、事中学习和外部学习。     

运算—程序性知识的复习策略——以线性规划问题为例

现代认知心理学家将学生学习的书本知识分为陈述性知识与程序性知识.陈述性知识是关于事物及其关系的知识;程序性知识是指完成某项任务的一系列操作方式.我国学者莫雷认为人有两类学习机制:一类是联结性学习机制,另一类是运算性学习     

谈知识迁移应注意的几个问题

知识迁移也称学习迁移,是一种学习对另一种学习的影响,现代认知心理学认为,学习者在进行迁移前所掌握的知识叫做源知识,学习者将要学习的新知识叫做目标知识,如果学习者将源知识运用到了目标知识的学习,或阻碍或促进了学习,我们就说发生了迁移.     

在高等数学教学中学生团队合作学习的实践与效果

指出了在高等数学教学中，学生团队合作学习的意义、学生团队合作学习的组织形式和奖励方式、教师在团队合作学习中的作用、团队合作学习在高等数学学习中的作用．在高等数学教学中，运用学生团队合作学习方式对培养学生的团队合作意识具有重要的作用，它对提高学生集体荣誉感，张扬个性、表现特长，团结协作共同完成学习任务起到积极的作用．     

高中数学课堂教学中的研究性学习

1. 问题的提出研究性学习是上海二期课改提出的一个崭新的学习概念,其着眼点就是要改变学生那种单纯地被动接受教师知识传输的学习方式,帮助和指导学生在开展有意义接受学习的同时,形成一种对知识技能进行主动探求、并重视实际问题解决的主动积极的学习方式. 笔者在探索研究性学习的内容和实施途径方面作了一定的尝试. 本文将高中数学中的开放题、探索题纳入研究性学习任务之中,并结合高考试题,就如何进行研究性学习作一些交流.2. 高中数学中研究性学习的途径2.1在课堂教学中渗透研究性学习在教学中可采用引趣、设疑、悬念、讨论等多种…     

知识在研发项目间的动态传播过程及其对项目集的影响研究

针对知识在研发项目间的动态传播问题，本文基于传染病(SIR)模型构建了知识的动态传播模型。首先，在项目团队间沟通网络构建的基础上，采用依赖结构矩阵(DSM)方法利用节点间的关联强度测度项目间的知识传播概率；然后，依据对项目间知识传播过程的分析，将知识传播过程中的项目团队界定为四种状态，并分析了知识传播导致的项目在各状态间的转变；进一步，分别测度知识传播导致的项目处于不同状态的概率和项目的知识水平；最后，利用传染病模型构建项目集网络中知识传播的动力学模型，对知识的动态传播过程进行求解与仿真分析。     

Exploring Depth Versus Breadth in Knowledge Management Strategies

This paper provides an early attempt at operationalizing and testing the concept of knowledge strategy. Using a computer-simulated product development process, we compare the performance of generalist and specialist knowledge management strategies under conditions of market turbulence. The generalist knowledge strategy emphasizes breadth of knowledge in product development teams, while the specialist strategy focuses on depth of knowledge. Our generalist and specialist strategies are grounded in Eastern and Western perspectives of knowledge management, respectively. A primary difference between these two approaches is the strong emphasis on cross-learning, or learning across team members, in the Eastern perspective relative to the Western perspective. As such, we examine the performance implications of different modes of cross-learning for teams utilizing the generalist knowledge strategy. Specifically, we examine three modes of cross-learning, which are reflected in the use of three learning decision rules: (1) averaging, (2) majority, and (3) hot hand. A learning decision rule indicates how decision-makers learn from their fellow team members. Under the first rule, the decision-maker adopts an average of the beliefs held by fellow team members. Under the second rule, if a majority of fellow team members agree on a particular solution, then the decision-maker adopts the beliefs held by the majority. Under the third rule, the decision-maker learns from the team member whose beliefs have been consistent with market desires most recently. Surprisingly, we find that specialist strategies outperform generalist strategies under conditions of low and high market turbulence. We also find that cross-learning can be beneficial or detrimental, contingent upon the mode of learning. Generalist teams utilizing the averaging decision rule perform significantly worse, while generalist teams utilizing the hot hand decision rule perform significantly better.     

Who You Know vs. What You Know: The Impact of Social Position and Knowledge on Team Performance

Organizational behavior theories generally agree that human capital is critical to teams and organizations, but little guidance exists on the extent to which such theories accurately explain the relative contributions of individual actors to overall performance. Using newly created network measures and simulations based on data obtained from a software development firm, we investigate the relative effectiveness of social network theory and resource dependency theory as predictors of individuals' contributions to team performance. Our results indicate that individual impacts on team performance are more closely associated with knowledge and task dimensions than with social network structure. Furthermore, given that knowledge may be assessed a priori, these factors provide useful guidance for structuring teams and predicting team performance.     

The wholes that are greater than the sum of their parts: employing cooperative learning in mathematics teachers’ education

This paper presents a study on employing different types of cooperative learning (CL) settings in mathematics teacher education based on multiple research data. The study analyzes mechanisms in which CL contributes to the development of teacher knowledge of three kinds: subject matter knowledge, pedagogical content knowledge, and curricular content knowledge. Additionally, it reflects on interactions between different kinds of teachers’ knowledge in the process of development. Two wholes, which are greater than the sum of their parts, are analyzed in this paper. The first is a course whose design combines different CL settings, hence enhances different mechanisms for teachers’ professional development. The second whole, teachers’ “collaborative mind,” is presented as an outcome of the first. To exemplify possible contributions of employing CL in teacher education, this paper first zooms in on the structure of one particular course for mathematics teachers and then focuses on one particular mathematical activity.     

Complex systems and human movement

Human movement reveals the hall mark characteristics of complex systems: namely, many interacting subsystems, multiple interactions within and between levels of analysis, emergence of movement coordination modes, and the exhibition of varying levels of the complexity of system output that continually evolve with learning and development over the life span. Here we outline how this high or infinitely dimensional complex dynamical system can be modeled by an epigenetic landscape framework—in the sense of Waddington—that captures the key features of the adaptive qualitative and quantitative properties of coordination modes (“order parameters”), the degeneracy of movement organization and the time scales of change. The framework provides some new ways to consider old problems in motor learning and development—such as an explicit and quantitative approach to exploring the concept of motor programs and developmental pathways—and yields new results and insights into the organization of learning during practice and rest times. For instance along one dimension of the landscape most of the changes occur between practice sessions. © 2006 Wiley Periodicals, Inc. Complexity 12: 40–51, 2006     

企业协同知识创新的风险识别与评价

协同知识创新是企业降低创新成本,提高创新能力的重要手段.由于企业知识创新具有高度的不确定性和不可预测性,因此,有效地利用企业协同优势,有针对性地降低协同知识创新的风险,是协同知识创新活动得以顺利开展的重要条件.影响协同知识创新的内外因素有很多,利用粗糙集理论对这些因素进行简约,消除冗余因素,得到在协同知识创新中的核心因素;确定约简集因素权重,判断协同知识创新的风险程度,为协同知识创新的决策提供依据.     

在线知识社区中基于个体异质性的知识与社会系统协同演化研究

在Web 2.0环境下,在线知识社区(Online Knowledge Community, OKC)已成为人们进行学习、利用、分享、传播知识的重要平台。然而,现有关于OKC的研究较多关注其中社会系统对个体知识建构、群体知识建构的影响,缺少从OKC演化的视角,以用户为基础对OKC中社会系统与知识系统间双向交互影响规律的研究。为此,本文将个体异质性作为影响因素引入到OKC的研究中,在一个开放的在线知识社区中模拟个体的观点、认知结构以及个体间形成的社会关系与知识系统的共同演化。将个体间以信任为基础形成的关系网络视为OKC中的社会系统,将群体依据自身认知结构表达出的全部观点视为社区中的知识系统,进而采取了社会科学计算实验的研究方法构建了一个OKC中社会系统与知识系统协同演化模型,并在模型中引入了个体的内在和外在异质性作为影响因素。研究结果表明OKC中个体的学习能力、容忍度、活跃度等个体因素,对其中知识观点的传播与社区中社会网络的演化影响显著。本研究希望能够为OKC中知识的自组织、序化的研究提供理论支持。     

数学学习与数学思想方法

数学学习,实际上就是对数学知识的理解和对数学思想方法的掌握与运用,数学思想方法是对数学知识的概括,也是数学知识的本质所在.对数学思想方法进行层次性划分,使数学学习具有针对性,同时也从方法论角度提供了数学学习的方法.全面地掌握数学方法,不仅有助于对数学知识的理解和运用,能有效提高数学的学习效率,对提高个体的整体素养也具有重要的现实意义.     

A market-based computational approach to collaborative organizational learning

We draw upon the concepts of knowledge market, organizational tacit knowledge, credit assignment, and single-loop learning in proposing a market-based conceptual model for collaborative organizational learning. Our proposed model is characterized by the local competition among seller agents and the global collaboration among winner agents in forming a plan, through a chain of ‘upstream–downstream’ working relationship, for task accomplishment. This feature is achieved through three closely coupled processes: the expert selection process, the capital reallocation process, and the plan formation process. Our model is intended for multiple-step learning environment in which each task consists of a sequence of single-step learning tasks. Learning at the global level is the result of a sequence of nested single-loop learning at the local level.