民企家长型领导、组织承诺与组织绩效的关系研究

以广东、广西68家民营企业的159名管理者及员工的调查结果为样本,实证分析了民企家长型领导、组织承诺与组织绩效的关系.研究发现:家长型领导行为中德行领导对组织承诺及组织绩效具有较大程度的影响,仁慈领导能够有效地促进员工组织承诺的提升并改善组织绩效,而威权领导则不利于员工组织承诺的提升.组织承诺在德行领导和仁慈领导与组织绩效的关系中有着积极的中介作用,在威权领导与组织绩效间的关系不明确.     

Learning to align organizational design and data

The relationship between organizational learning and organizational design is explored. In particular, we examine the information processing aspects of organizational learning as they apply to a two-valued decision making task and the relation of such aspects to organizational structure. Our primary contribution is to extend Carley's (1992) model of this process. The original model assumes that all data input into the decision making processes are of equal importance or weight in determining the correct overall organizational decision. The extension described here allows for the more natural situation of non-uniform weights of evidence. Further extensions to the model are also discussed. Such organizational learning performance measures provide an interesting framework for analyzing the recent trend towards flatter organizational structures. This research suggests that flatter structures are not always better, but rather that data environment, ultimate performance goals, and relative need for speed in learning can be used to form a contingency model for choosing organizational structure.     

地位差异视角下知识分享策略对组织学习的影响研究

组织学习是提高企业竞争能力的重要途径,人际学习是组织学习的重要组成部分。组织成员间普遍存在的地位差异,会直接影响个体的知识分享策略,继而影响组织学习。然而,以往的组织学习模型通常忽略了个体的地位差异,默认假设每个组织成员的地位是相同的。鉴于此,本文在组织学习经典仿真模型的基础上,引入地位这一特征,综合探讨正向差异化(高地位成员更愿意分享知识)、负向差异化(低地位成员更愿意分享知识)、以及同质化(不同地位的成员有相同的知识分享意愿)这三种知识分享策略对组织学习的影响机理。研究结果表明,三种知识分享策略下,知识分享水平和地位认可度对组织学习的作用关系和作用大小存在显著差异。但总体来说,仅当组织成员的地位认可度较高且知识分享水平较低时,同质化策略才最有利于组织学习;其他情境下,负向差异化策略更有利于提高组织学习绩效。     

Organizational Design of Post Corporation Structure Using Fuzzy Multicriteria Decision Making

A model for organizational design of post corporation structure is developed in this paper. Alternative organization solutions have been designed taking into account the post environment characterized by private operators' competition and development of new message transmission technologies. Criteria for organizational design have been considered as numerical and uncertain linguistic variables describes by fuzzy sets. The model has been tested on a numerical example.     

A Model of Obsolescence of Organizational Rules

The phenomenon of obsolescence has found little attention in past research on organizational change. Most research on organizational change has instead been concerned with the opposite of obsolescence, that is, with mechanisms which render organizational structures increasingly persistent. However, everyday experience teaches that organizational structures become outdated as surrounding conditions shift. This article explores obsolescence by means of mathematical modeling and empirical analysis. Obsolescence is conceptualized as a result of flows of conditions in, out, and between two states: consistent conditions and inconsistent conditions. The model predicts that the obsoleteness curve rises with decreasing increments over time. This is tested with empirical data on organizational rule change. The results confirm the obsolescence model. This revised version was published online in August 2006 with corrections to the Cover Date.     

Making Organizational Learning Operational: Implications from Learning Classifier Systems

The concepts of organizational learning in organization and management science cover a very wide range of organization-related activities in organization. Since socially situated intelligence is one of such activities, this paper makes the concept of organizational learning operational from the computational viewpoint for investigating socially situated intelligence. In particular, this paper focuses on the characteristics of multiagent learning as one kind of socially situated intelligence, and analyzes them using four operationalized learning mechanisms in organizational learning. A careful investigation on the characteristics of multiagent learning has revealed the following implications: (1) there are two levels in the learning mechanisms for multiagent learning (the individual level and organizational level) and each mechanism is divided into two types (single- and double-loop learning). The integration of these four learning mechanisms improves socially situated intelligence; and (2) the following properties support socially situated intelligence: (a) different dimensions in learning mechanisms, (b) interaction among various levels and types of learning mechanisms in addition to interaction among agents, and (c) combination of exploration at an individual level and exploitation at an organizational level.     

基于多Agent仿真的双元创新平衡与组织绩效关系研究

运用多主体仿真方法,探讨了双元创新平衡对组织绩效的作用机理,并且检验了个体间模仿学习速度、任务复杂度、人员流动、环境扰动等情境因素与双元创新平衡对组织绩效的交互影响。仿真实验的结果表明,当组织处于稳定环境下,任务复杂程度适中,并且个体间模仿学习速度中等时,双元创新平衡参数与组织绩效间呈现倒U型的影响关系;当任务过于复杂或者过于简单时,任务本身的特性削弱了双元创新平衡参数对组织绩效的影响,不同平衡模式对应的组织绩效没有明显的差距;当个体间模仿学习速度比较慢时,增强了组织的探索性,此时具有利用式创新倾向的组织可以更好地提升组织绩效水平。但当个体间模仿学习速度过快时,组织更多的倾向探索式创新对组织绩效的提升更有利;当组织存在人员流动和外部环境扰动时,更多的利用式创新可以提升组织对现有知识进行重组和整合的能力,从而更好地适应环境的动态变化。     

A Dynamic Simulation Comparing Classical and Emergent-Network Models: Organizational Design Implications

In the last decade, organizations have spent more on the creation, transformation, and communication of information than on the production of physical goods. The information age has been ushered in by the widespread assimilation of information and communication technologies. Many contemporary practitioners and organizational theorists predict the demise of the classical organizational design because of its inability to accommodate the sociological change engendered by the information age.The current study advances an emergent-network model of organizational design and compares it to the classical approach through a dynamic simulation of prototypical organizational activities. Organizational activities approximating one year were simulated in each of five organizations under constant baseline conditions and over one hundred experimental design conditions. The emergent network model manifested higher levels of goal attainment, resource utilization, and organizational capacity for accommodating change. These findings suggest that organizations will benefit from conformance to the design principals of the emergent-network model.Bernard D. Hill Jr. earned his Ph.D. in Public Policy and Administration from Virginia Commonwealth University. He also holds a Master of Science in Business and a Bachelor of Science in Education. Bernard is currently employed as a Chief Information Officer with the Commonwealth of Virginia. He has held a broad array of technology leadership positions in both the public and private sectors and the academic arena. Bernard was selected as one of Computerworld’s Premier 100 IT Leaders for 2002. As CIO for the Virginia Department of Transportation, he also brokered a public-private partnership that won a nationwide Government Technology Leadership Award. This partnership provides security awareness training for employees in Virginia State government, as well as cities, counties, and localities throughout Virginia.Heinz Roland Weistroffer is an Associate Professor of Information Systems in the School of Business at Virginia Commonwealth University. Roland holds a Doctor of Science degree from the Free University Berlin, Germany, and a Master of Arts degree from Duke University. Previous appointments include Chief Research Officer at the Council for Scientific and Industrial Research in Pretoria, South Africa, and Senior Lecturer at the University of Natal in Durban, South Africa. Roland’s current research interests include computer assisted decision support, computer simulation modeling, object oriented modeling, and software engineering. He has published in IEEE Transactions on Software Engineering, IEEE Transactions on Systems, Man and Cybernetics, the Journal of Multi-Criteria Decision Analysis, and Socio-Economic Planning Sciences, among other journals.Peter Aiken is Director of the Institute for Data Research and an Associate Professor of Information Systems at Virginia Commonwealth University. His research has widely explored the area of data engineering and its relationship to systems and business reengineering. He is the author of Data Reverse Engineering and Clive Finkelstein’s co-author of Corporate Information Portals (McGraw-Hill 1996/99). His sixth book is titled XML in Data Management and is co-authored with David Allen. He has held leadership positions with the US Department of Defense and consulted with more than 50 organizations in 14 different counties. His research publications have appeared in the Communications of the ACM, IBM Systems Journal, IEEE Software and many others. He is a member of ACM, and the IEEE (Senior Member). He has been a DAMA International Advisor since 1999 and received their 2001 International Achievement Award. He has lectured internationally on these and related topics.     

组织学习能力的个性优势识别与评价研究

组织学习能力是个多维概念,定期识别在哪个维度上具备个性优势并在此基础上对组织学习能力状况做出评价将有利于促进组织绩效的提升。本文按照目标规划的思想,依据2-范数距离,提出一种组织学习能力的个性优势识别方法,该方法从尊重每一位被评价者的意见出发识别其个性优势特征,并在此基础上给出综合评价结论。在此基础上以国内某大型软件企业的20个事业部为例进行了应用研究,组织学习能力由发现能力、发明能力、选择能力、执行能力、推广能力、反思能力、获取知识能力、输出知识能力、建立知识库能力九个维度组成。研究结果表明,基于个性优势识别的组织学习能力评价方法符合“人本管理”思想,易于被评价主体接受,且具有客观性的特点,同时可以产生标杆效应。     

Computationally modeling organizational learning and adaptability as resource allocation: An artificial adaptive systems approach

A framework for and a computational model of organizational behavior based on an artificial adaptive system (AAS) is presented. An AAS, a modeling approach based on genetic algorithms, enables the modeling of organizational learning and adaptability. This learning can be represented as decisions to allocate resources to the higher performing organizational agents (i.e., individuals, groups, departments, or processes, depending on the level of analysis) critical to the organization's survival in different environments. Adaptability results from the learning function enabling the organizations to change as the environment changes. An AAS models organizational behavior from a micro-unit perspective, where organizational behavior is a function of the aggregate actions and interactions of each of the individual agents of which the organization is composed. An AAS enables organizational decision making in a dynamic environment to be modeled as a satisficing process and not as a maximization process. To demonstrate the feasibility and usefulness of such an approach, a financial trading adaptive system (FTAS) organization is computationally modeled based on the AAS framework. An FTAS is an example of how the learning mechanism in an AAS can be used to allocate resources to critical individuals, processes, functions, or departments within an organization.     

Promotion Systems and Organizational Performance: A Contingency Model

This study explores the organizational impact of a variety of important promotion systems commonly practiced in organizations including up-or-out systems, absolute merit-based systems, relative merit-based systems, and seniority-based systems. Through the computer simulation of organizations in a distributed decision making setting, the results indicate that the effectiveness of any promotion system is dependent on a range of factors including the nature of the task environment, the design of the organizational structure, the frequency of monitoring, the criteria of performance, and the transferability of task knowledge. This study has implications not only for understanding organizational promotion systems from the contingency perspective, but also for bridging the fields of strategic human resource management and computational organization theory.     

The Dynamics of Organizational Learning

This paper presents a dynamical theory of organizational learning that explicitly accounts for both the introduction of new routines into the manufacturing process and improvements in the selection of which procedures to follow. Besides producing a power law of organizational learning with a rate that depends on the effectiveness of the decision procedure, the theory also accounts for observed anomalies characterized by price increases with cumulative output.     

A Model to Evaluate the Effect of Organizational Adaptation

When an organization's output declines due to either internal changes or changes in its external environment, it needs to adapt. In order to evaluate the effectiveness of different adaptation strategies on organizational performance, an organizational model composed of individual models of a five stage interacting decision maker was designed using an object oriented design approach and implemented as a Colored Petri net. The concept of entropy is used to calculate the total activity value, a surrogate for decision maker workload, based on the functional partition and the adaptation strategy being implemented. The individual decision maker's total activity is monitored, as overloaded decision makers constrain organizational performance. A virtual experiment was conducted; organizations implementing local and global adaptation strategies were compared to a control organization with no adaptation. The level of tolerance of the organization, the workload limit based on the concept of the bounded rationality constraint, was used to determined when a decision maker was overloaded: the limiting effect of the workload on performance. The timeliness of the organization's response was used in order to evaluate organizational output as a function of adaptation strategy.     

Incorporating the learning effect into data envelopment analysis to measure MSW recycling performance

The effect of organizational learning, which results in continuous improvement of organizational performance over time, has been widely discussed. The cumulative learning effect may form as a source of intellectual capital. Thus far, the static data envelopment analysis (DEA) model has not been used to examine the longitudinal learning effect. Therefore, a two-stage approach is developed together with the estimation of a latent learning effect using time-series data; the estimated learning effect is then used as an input in the DEA Slacks-Based Measure (SBM) model. The proposed DEA SBM model can be used to investigate the efficiency of the organizational learning effect of Municipal Solid Waste (MSW) recycling systems.     

基于因子分析的组织文化测量

在吸纳了国内外学者研究成果的基础上,设计了组织文化测量量表.通过因子分析,得到了组织文化创新力、凝聚力、领导力、员工定位、绩效定位、分配定位、团队定位七个维度的测量指标,累计七个维度方差得到组织文化强度,由该强度值的大小得知组织文化的强弱.给出了一种测量组织文化的定量方法,解决了实证研究中组织文化测量困难的问题.     

组织气氛对团队有效性影响机制的实证分析

本研究以10家高科技组织中的48个工作团队作为研究对象,通过文献研究、问卷调查,利用SPSS11.0软件进行多元回归统计分析,研究了组织气氛中的创新、公平、支持、人际关系和员工身份认同等五个维度对团队有效性的影响作用,研究结果表明不同的组织气氛维度对团队的绩效、团队工作成员的满意度以及团队承诺具有不同的影响,同时,团队组织气氛通过团队群体效能感这个中介变量对团队的有效性产生影响作用。     

基于Projection Pursuit-RAGA-NK-GERT的质量绩效提升路径优化——以组织质量特异性免疫和产品生命周期为主导逻辑的解释框架

依据组织免疫和组织质量特异性免疫的相关理论,引入情境变量产品生命周期,构建基于组织质量监视、组织质量防御软要素、组织质量防御硬要素和组织质量记忆的质量绩效提升路径理论框架。使用基于RAGA的投影寻踪模型、适应度景观和NK模型对产品生命周期不同阶段的质量绩效提升路径进行实证分析,实证结果表明:产品生命周期不同阶段有不同的质量绩效提升路径,产品导入期遵循的质量绩效提升路径为组织质量监视→组织质量防御→组织质量记忆,产品成长期遵循的质量绩效提升路径为组织质量防御软要素→组织质量防御硬要素→组织质量监视→组织质量记忆,产品成熟期遵循的质量绩效提升路径为组织质量防御硬要素→组织质量防御软要素→组织质量监视→组织质量记忆,产品衰退期遵循的质量绩效提升路径为组织质量记忆→组织质量监视→组织质量防御。并建立产品生命周期不同阶段质量绩效提升路径优化的GERT网络,优化产品生命周期不同阶段的质量绩效提升路径。     

Can tools help unify organization theory? Perspectives on the state of computational modeling

Scholars engaged in the study of work group and organizational behavior are increasingly calling for the use of integrated methods in conducting research, including the wider adoption of computational models for generating and testing new theory. Our review of the state of modern computational modeling incorporating social structures reveals steady increases in the incorporation of dynamic, adaptive, and realistic behaviors of agents in network settings, yet exposes gaps that must be addressed in the next generation of organizational simulation systems. We compare 28 models according to more than two hundred evaluation criteria, ranging from simple representations of agent demographic and performance characteristics, to more richly defined instantiations of behavioral attributes, interaction with non-agent entities, model flexibility, communication channels, simulation types, knowledge, transactive memory, task complexity, and resource networks. Our survey assesses trends across the wide set of criteria, discusses practical applications, and proposes an agenda for future research and development. Michael J. Ashworth is a doctoral candidate in computational organization science at Carnegie Mellon University, where he conducts research on social, knowledge, and transactive memory networks along with their effects on group and organizational learning and performance. Practical outcomes of his work include improved understanding of the impact of technology, offshoring, and turnover on organizational performance. Mr. Ashworth has won several prestigious grants from the Sloan Foundation and the National Science Foundation to pursue his research on transactive memory networks. Journals in which his research has appeared include Journal of Mathematical Sociology, International Journal of Human Resource Management, and Proceedings of the International Conference on Information Systems. His recent work on managing human resource challenges in the electric power industry has been featured in the Wall Street Journal and on National Public Radio's ``Morning Edition.' Mr. Ashworth received his undergraduate degree in systems engineering from the Georgia Institute of Technology. Kathleen M. Carley is a professor at the Institute for Software Research International in the School of Computer Science at Carnegie Mellon University. She is the director of the center for Computational Analysis of Social and Organizational Systems (CASOS), a university-wide interdisciplinary center that brings together network analysis, computer science and organization science (www.casos.ece.cmu.edu). Prof. Carley carries out research that combines cognitive science, dynamic social networks, text processing, organizations, social and computer science in a variety of theoretical and applied venues. Her specific research areas are computational social and organization theory; dynamic social networks; multi-agent network models; group, organizational, and social adaptation, and evolution; statistical models for dynamic network analysis and evolution, computational text analysis, and the impact of telecommunication technologies on communication and information diffusion within and among groups. Prof. Carley has undergraduate degrees in economics and political science from MIT and a doctorate in sociology from Harvard University.     

Three Controls are Better than One: A Computational Model of Complex Control Systems

This paper investigates theories that integrate and extend currently accepted agency- and transaction-based approaches to organizational control. We use a computational model to build three forms of control systems (market, bureaucratic, clan) and three forms of control targets (input, behavior, output). Using these models, we examine relationships between control systems and both singular and multiple control targets. Results of this study support the emerging broader perspective on organizational control research and suggest that managers can improve organizational performance by focusing attention on multiple control targets. In addition, findings partially support posited relationships between control systems and singular control targets. The authors suggest that results of this study should direct scholars to refocus control research from examinations of singular forms of control to evaluations of more complex control systems.