Computational and mathematical organization theory: Perspective and directions

Computational and mathematical organization theory is an interdisciplinary scientific area whose research members focus on developing and testing organizational theory using formal models. The community shares a theoretical view of organizations as collections of processes and intelligent adaptive agents that are task oriented, socially situated, technologically bound, and continuously changing. Behavior within the organization is seen to affect and be affected by the organization's, position in the external environment. The community also shares a methodological orientation toward the use of formal models for developing and testing theory. These models are both computational (e.g., simulation, emulation, expert systems, computer-assisted numerical analysis) and mathematical (e.g., formal logic, matrix algebra, network analysis, discrete and continuous equations). Much of the research in this area falls into four areas: organizational design, organizational learning, organizations and information technology, and organizational evolution and change. Historically, much of the work in this area has been focused on the issue how should organizations be designed. The work in this subarea is cumulative and tied to other subfields within organization theory more generally. The second most developed area is organizational learning. This research, however, is more tied to the work in psychology, cognitive science, and artificial intelligence than to general organization theory. Currently there is increased activity in the subareas of organizations and information technology and organizational evolution and change. Advances in these areas may be made possible by combining network analysis techniques with an information processing approach to organizations. Formal approaches are particularly valuable to all of these areas given the complex adaptive nature of the organizational agents and the complex dynamic nature of the environment faced by these agents and the organizations.This paper was previously presented at the 1995 Informs meeting in Los Angeles, CA.     

Putting the organization back into computational organization theory: a complex Perrowian model of organizational action

At best, computational models that study organizations incorporate only one perspective of how organizations are known to act within their environments. Such single-perspective models are limited in their generalizability and applicability to the real world and allow for researcher bias. This work develops a multi-agent simulation using eight different well-known organizational perspectives: Strategic choice, contingency theory, behavioral decision theory, enactment, resource dependence, institutional theory, population ecology, and transaction cost economics. A literature review of each field is applied to the construction of algorithms which, when combined with techniques derived from a literature review of computational modeling of organizations, was applied to the construction of a series of algorithms describing a multi-perspective computational model. Computer code was written based on the algorithms and run across different types of environments. Results were statistically analyzed to both validate the model and to generate contingency-oriented hypotheses. Conclusions were made with regard to the expected behavior of organizations and the model’s applicability toward further research.

Modeling and Analyzing Cultural Influences on Project Team Performance

Research on international joint ventures (IJV) finds managers experience difficulties in working with cross-cultural teams. Our research aims to understand how cultural differences between Japanese and American firms in IJV projects effect team performance through computational experimentation. We characterize culture and cultural differences using two dimensions: practices and values.Practices refer to each cultures typical organization style, such as centralization of authority, formalization of communication, and depth of organizational hierarchy. Values refer to workers preferences in making task execution and coordination decisions. These preferences drive specific micro-level behavior patterns for individual workers. Previous research has documented distinctive organization styles and micro-level behavior patterns for different nations. We use a computational experimental design that sets task complexityat four levels and team experience independently at three levels, yielding twelve organizational contexts. We then simulate the four possible combinations of USvs.Japanese organization style and individual behavior in each context to predict work volume, cost, schedule andprocess quality outcomes. Simulation results predict that: (1) both Japanese and American teams show better performance across all contexts when each works with its familiar organization style; (2) the Japanese organization style performs better under high task complexity, with low team experience; and (3) process quality risk is not significantly affected by organization styles. In addition, culturally driven behavior patterns have less impact on project outcomes than organization styles. Our simulation results are qualitatively consistent with both organizational and cultural contingency theory, and with limited observations of US-Japanese IJV project teams.This paper won the best Ph.D. student paper award at NAACSOS 2004, Pittsburgh PA. NAACSOS is the main conference of the North American Association for Computational Social and Organizational Science.Tamaki Horii is a Ph.D. candidate in the Civil and Environmental Engineering Department at Stanford University. His research focuses on various aspects of cultural and institutional influences on team performance. He is currently developing new models to capture and distinguish the cultural factors that emerging in global projects. He received a MS in Architecture at the Science University of Tokyo and a MS in Civil and Environmental Engineering at Stanford University.Yan Jin is an Associate Professor of Mechanical Engineering at University of Southern California and Director of USC IMPACT Laboratory , and a visiting Professor of Civil Engineering Department at Stanford University. He received his Ph.D. degree in Naval Engineering from the University of Tokyo in 1988. Prior to joining USC faculty in the Fall of 1996, Dr. Jin was a Senior Research Scientist at Stanford University. His current research interests include design methodology, agent-based collaborative engineering, and computational organization modeling. Dr. Jin is a recipient of National Science Foundation CAREER Award (1998), TRW Excellence in Teaching Award (2001), Best Paper in Human Information Systems (5th World Multi-Conference on Systemic, Cybernetics and Informatics, 2001), and Xerox Best Paper Award (ASME International Conference on Design Theory and Methodology, 2002).Raymond E. Levitt is a Professor of Civil Engineering Department at Stanford University, a Professor, by Courtesy, Medical Informatics, an Academic director of Stanford Advanced Project Management Executive Program, and a Director of Collaboratory for Research on Global Projects (CRGP) . His Virtual Design Team (VDT) research group has developed new organization theory, methodology and computer simulation tools to design organizations that can optimally execute complex, fast-track, projects and programs. VDT is currently being extended to model and simulate service/maintenancework processes such as health care delivery and offshore platform maintenance. Ongoing research by Professor Levitts Virtual Design Team research group attempts to model and simulate the significant institutional costs that can arise in global projects due to substantial differences in goals, values and cultural norms among project stakeholders.     

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.     

When does management matter in a dog-eat-dog world: An “Interaction Value Analysis” model of organizational climate

Interaction Value Interaction Value Analysis (I.V.A.) models a network of rational actors who generate value by interacting with each other. This model can be used to understand human organizations. Since people form organizations to facilitate interactions between productive individuals, the value added by interaction is the contribution of the organization. This paper examines the result of varying the queuing discipline used in selecting among back-logged interaction requests. Previously developed I.V.A. models assumed a First-in-first-out (FIFO) discipline, but using other disciplines can better represent the “Climate” of an organization. I.V.A. identifies circumstances under which organizations that control members’ interaction choices outperform organizations where individuals choose their own interaction partners. Management can be said to “matter” when individual choices converge to a point where interactions generate a lower than optimal value. In previous I.V.A. models, relinquishing central control of interaction choices reduced the aggregate value by anything from 0% to 12%, depending on circumstances. This paper finds the difference between the two modes of organization to go as high as 47% if actors display preferences between interaction partners instead of treating all equally. A politically divided, dog-eat-dog, “Capitalist” climate follows one queuing discipline, which is found to generally increase the value that a strong control structure can add. A chummy, in-bred “Fraternal” climate gains from control in some circumstances (low interdependence or low differentiation), but not in others (high or medium interdependence and differentiation under low diversity, for example). These are compared to the previous version of I.V.A., in which the queuing discipline was FIFO and the climate deemed “Disciplined”. Previously published findings on Organizational Climate are duplicated and extended with a higher level of detail. Priority queuing in an I.V.A. model is thus a useful proxy for Organizational Climate, open to future validation because its detailed predictions can be confirmed or falsified by observation. Walid Nasrallah is currently Assistant Professor in the Engineering Management program at the American University of Beirut (AUB). He received his Ph.D. from the Construction Engineering and Management program at Stanford University in 2000 and his Master’s degree at MIT in 1989. Between the two, he occupied several positions in the construction and software engineering fields. His research interests today include simulation, decision theory, and the evolution of organizations in response to new technologies.     

Computational Modeling of Organizations Comes of Age

As they are maturing—i.e., as they are becoming validated, calibrated and refined—computational emulation models of organizations are evolving into: powerful new kinds of organizational design tools for predicting and mitigating organizational risks; and flexible new kinds of organizational theorem-provers for validating extant organization theory and developing new theory. Over the past 50 years, computational modeling and simulation have had enormous impacts on the rate of advancement of knowledge in fields like physics, chemistry and, more recently, biology; and their subsequent application has enabled whole new areas of engineering practice. In the same way, as our young discipline comes of age, computational organizational models are beginning to impact behavioral, organizational and economic science, and management consulting practice. This paper attempts to draw parallels between computational modeling in natural sciences and computational modeling of organizations as a contributor to both social science and management practice.To illustrate the lifecycle of a computational organizational model that is now relatively mature, this paper traces the evolution of the Virtual Design Team (VDT) computational modeling and simulation research project at Stanford University from its origins in 1988 to the present. It lays out the steps in the process of validating VDT as a computational emulation model of organizations to the point that VDT began to influence management practice and, subsequently, to advance organizational science. We discuss alternate research trajectories that can be taken by computational and mathematical modelers who prefer the typical natural science validation trajectory—i.e., who attempt to impact organizational science first and, perhaps subsequently, to impact management practice.The paper concludes with a discussion of the current state-of-the-art of computational modeling of organizations and some thoughts about where, and how rapidly, the field is headed.     

Derivation of a Logistic Equation for Organizations,and its Expansion into a Competitive Organizations Simulation

One of the earliest and most famous of the models that produce chaotic behaviour is the Logistic equation. It has a long history of use in economics and organization science studies. In those studies, the applicability of the equation is generally assumed rather than derived from first principles, with only conjecture offered as to the identity of the parameters.This paper shows a deductive derivation of a Logistic equation for organizations in a competitive economy. The construct is based on a system that consists of one or more organizations, each with its own cost, productivity, and reinvestment parameters, and each having its individual population of employees.The model is chaotic, and demonstrates some fascinating characteristics when organizations with parameters that individually would generate chaotic behaviour are mixed with organizations with parameters that individually would generate complex or stable behaviour. Some such mixed systems tend to initially behave like a complex or chaotic system, but transition over time to match the behaviour of the organization with the most “stable” parameters.If a system is at equilibrium, changing one organization’s parameters can result in a burst of oscillations or chaotic activity while the system transitions to a new equilibrium. However, this activity can be delayed or might not occur at all.Adding a number of real world complications to the Organization Logistic equation created a deterministic time-step simulation of an economic system. This simulation was also found to exhibit chaotic behaviour, nonmonotonicity, and the Butterfly Effect, as well as spontaneous bankruptcies.The possibility that a competitive economic system might be inherently chaotic deserves further investigation. A broader insight is that the Scientific Method is not an appropriate scientific paradigm under which to grow social science knowledge if those social science systems are governed by chaotic mechanisms.Alan Zimm graduated from UCLA with a B.S. in physics. He served in the United States Navy for 20 years as a nuclear power qualified surface warfare officer, reaching the rank of Commander. He received a M.S. degree in Operations Research from the Naval Postgraduate School, and a D.P.A. in Public Administration with emphasis on policy analysis and strategic planning from the University of Southern California. Since 1993 he has worked at The Johns Hopkins University Applied Physics Laboratory involved with warfare analysis and the modeling of complex human systems. In 1999 he was awarded the Arleigh Burke Award from the United States Naval Institute and in 2001 a Distinguished Citation Award from the University of Southern California School of Policy, Planning, and Development.     

The virtual design team: A computational model of project organizations

Large scale and multidisciplinary engineering projects (e.g., design of a hospital building) are often complex. They usually involve many interdependent activities and require intensive coordination among actors (i.e., designers) to deal with activity interdependencies. To make such projects more effective and efficient, one needs to understand how coordination requirements are generated and what coordination mechanisms should be applied for given project situations. Our research on the Virtual Design Team (VDT) attempts to develop a computational model of project organizations to analyze how activity interdependencies raise coordination needs and how organization design and communication tools change team coordination capacity and project performance. The VDT model is built based on contingency theory (Galbraith, 1977) and our observations about collaborative and multidisciplinary work in large, complex projects. VDT explicitly models actors, activities, communication tools and organizations. Based on our extended information-processing view of organizations, VDT simulates the actions of, and interactions among actors as processes of attention allocation, capacity allocation, and communication. VDT evaluates organization performance by measuring emergent project duration, direct cost, and coordination quality. The VDT model has been tested internally, and evaluated externally through case-studies. We found three way qualitative consistency among predictions of the simulation model, of organization theory, and of experienced project managers. In this paper, we present the VDT model in detail and discuss some general issues involved in computational organization modeling, including level of abstraction of tasks and actors' reasoning, and model validation.     

A Trajectory for Validating Computational Emulation Models of Organizations

Validation of complex simulation models is a challenging problem in computational organization theory research. In this paper, we describe a validation strategy suitable for emulation simulation systems, and show how a comprehensive validation consists of a sequence of steps that evaluate different aspects of a computational organizational simulation model. We demonstrate how this strategy can be applied to the evaluation of the Virtual Team Alliance (VTA), an emulation simulation system designed to guide managers charged with organizational change. VTA required a &201C;trajectory&201D; of successive validation experiments, before managers where willing to follow the recommendations of VTA. Ultimately, we believe this validation approach can be applied to a wide range of different simulation systems, and will make identification of the strengths and weaknesses of organizational simulations easier.     

Adapting to the Changing Environment: A Theoretical Comparison of Decision Making Proficiency of Lean and Mass Organization Systems

In this paper weexamine the adaptability of the Japanese style leanorganization system and the traditional American style mass organizationsystem under changing environments. From an organizational designperspective, key structural aspects of the two organizations are modeled ina problem solving context using computational methods. Organizational-levelperformance in terms of decision making accuracy and severity of errors ismeasured as an indicator of organizational adaptability under conditionswhere the task environment shifts between predictable to unpredictable orvise versa. Our study shows that both organizations have their respectiveadvantages under different task environments and that they adapt toenvironmental shifts in different forms. Specifically, when the timepressure is high the lean organization system's performance isvirtually identical to the mass organization system, even though the leanorganization systemÆs members are more proactive. When the timepressure is low, the mass organization system shows a much fasteradaptability when the environment shifts to a predictable one but it is alsomore vulnerable when the environment shifts to an unpredictable one. Incontrast, the lean organization systemÆs response to the changingenvironment is characterized by its slower adaptability. When theenvironment shifts to an unpredictable one, the lean organization systemshows a gradual improvement till reaching a high level. When the environmentshifts to a predictable one, however, the lean organization system shows agradual decrease of performance. Our study further shows that the leanorganization system, with its strong team decision making emphasis, can bemore successful in avoiding severe errors when compared with the massorganization system, even under a predictable task environment.     

Designing tree-structured organizations for computational agents

We describe a framework for defining the space of organization designs for computational agents, use our framework for analyzing the expected performance of a class of organizations, and describe how our analyses can be applied to predict performance for a distributed information gathering task. Our analysis specifically addresses the impact of the span of control (branching factor) in tree-structured hierarchical organizations on the response time of such organizations. We show quantitatively how the overall task size and granularity influence the design of the span of control for the organization, and that within the class of organizations considered the apropriate span of control is confined to a relatively narrow range. The performance predicted by our overall model correlates with the actual performance of a distributed organization for computer network monitoring. Consequently, we argue that our framework can support aspects of organizational self-design for computational agents, and might supply insights into the design of human organizations as well.     

The Virtual Team Alliance (VTA): Extending Galbraith’s Information-Processing Model to Account for Goal Incongruency

This paper introduces a newComputational organizational analysis and design model, Called the Virtual Team Alliance (VTA), that builds on the Virtual Design Team (VDT) (Jin and Levitt, 1996). VTA extends Galbraiths framework implemented in VDT in two ways: (1) it addresses less routine tasks with some flexibility in how they are performed, and (2) it treats project participants as teleological professionals with potentially incongruent goals. Because tasks in the VTA model are flexible, differences in goals may influence which solution approach project participants prefer; thus, goal incongruencyCan have profound implications for the performance of project teams. We describe how VTA actorsComprise aComplex system that is endowed with fragments ofCanonical information-processing micro-behavior. TheCanonical micro-behaviors in VTA include exception generation, monitoring, selective delegation of authority, searching for alternatives,Clarifying goals, steamrolling, and politicking. The VTA model simulates the micro-levelCommunication andCoordination behavior of actors within the organization, including the impact of goal incongruency between individual actors, in order to determine the emergent, aggregate project behavior and performance. To Galbraiths sociological analysis, based on information-processing organizational physics, we add new organizationalChemistry notions based on social psychological and economic agency theories.The National Science Foundation, Transformations to Quality Organizations program, Grant SBR-9422389, supported this research.Jan Thomsen is a Director at Det Norske Veritas (DNV). (DNV is a global consulting, certification and classi-fication firm with approximately 6000 employees headquartered in Oslo, Norway). Thomsen earned his Ph.D. in Engineering Management at Stanford Universitys School of Engineering in 1998. Before coming to Stanford in 1994, Thomsen worked six years in industry. He was a Management Consultant with Arthur Andersen/Andersen Consulting for four years before joining DNV. Thomsens current research interest is organizational analysis and design of semi-routine, fast-paced project organizations consisting of professionals with potentially incongruent goals.Raymond Elliot Levitt is Professor of Civil & Environmental Engineering and, by courtesy, of Medical Informatics, at Stanford University. Since 1988, Dr. Levitts Virtual Design Team (VDT) research group has developed new organization theory and new computational analysis tools that enable managers to design organizations for executing projects and service/maintenance tasks systematically. His current research is extending VDT to predict and mitigate risks caused by gaps between the core values, behavioral norms and legal institutions of participants in global projects. He serves as Director of Stanfords Collaboratory for Research on Global Projects, a multi-school, multi-university initiative aimed at enhancing the performance of global projects. He also founded and serves as Academic Director of Stanfords Advanced Project Management (APM) Executive Program. He co-founded, and has served as a Director of, Design Power, Inc., Vité Corporation and Visual Network Design, Inc.Clifford I. Nass (Ph.D., Sociology, Princeton University) is a professor of Communication at Stanford University, with appointments in Computer Science, Science, Technology, and Society, Sociology, and Symbolic Systems (cognitive science). He is Director of the SPEECH Lab and co-Director of the Kozmetsky Global Collaboratory at Stanford. Nass is author of two books—Voice Activated: How Humans areWired for Speech and How Computers Will Speak With Us (MIT Press), The Media Equation (Cambridge University Press), and over 75 articles on human-computer interaction and statistical methodology. Nass has consulted on more than 100 products for companies including Microsoft, BMW, Fidelity, Philips, Verizon, Dell, Hewlett-Packard, and Toyota.     

Communication Networks from the Enron Email Corpus “It's Always About the People. Enron is no Different”

The Enron email corpus is appealing to researchers because it represents a rich temporal record of internal communication within a large, real-world organization facing a severe and survival-threatening crisis. We describe how we enhanced the original corpus database and present findings from our investigation undertaken with a social network analytic perspective. We explore the dynamics of the structure and properties of the organizational communication network, as well as the characteristics and patterns of communicative behavior of the employees from different organizational levels. We found that during the crisis period, communication among employees became more diverse with respect to established contacts and formal roles. Also during the crisis period, previously disconnected employees began to engage in mutual communication, so that interpersonal communication was intensified and spread through the network, bypassing formal chains of communication. The findings of this study provide valuable insight into a real-world organizational crisis, which may be further used for validating or developing theories and dynamic models of organizational crises; thereby leading to a better understanding of the underlying causes of, and response to, organization failure. Jana Diesner is a Research Associate and Linguistic Programmer at the Center for Computational Analysis of Social and Organizational Systems at the School of Computer Science (CASOS), Carnegie Mellon University (CMU). She received her Masters in Communications from Dresden University of Technology in 2003. She had been a research scholar at the Institute for Complex Engineered System at CMU in 2001 and 2002. Her research combines computational linguistics, social network analysis and computational organization theory. Terrill L. Frantz is a post-doc researcher at the Center for Computational Analysis of Social and Organizational Systems (CASOS) in the School of Computer Science at Carnegie Mellon University. His research involves studying the dynamics of organization social-networks and behavior via computer modeling and simulation. He is developing an expertise in workforce integration strategy and policy evaluation during organization mergers. He earned his doctorate (Ed.D. in Organization Change) from Pepperdine University, a MBA from New York University and a BS in Business Administration (Computer Systems Management) from Drexel University. Prior to entering academic research, for nearly 20 years he was a software applications development manager in the global financial services and industrial chemicals industries; most recently as a Vice President in Information Technology at Morgan Stanley in Hong Kong, New York and London. 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) <http://www.casos.cs.cmu.edu/>, a university wide interdisciplinary center that brings together network analysis, computer science and organization science (www.casos.ece.cmu.edu) and has an associated NSF funded training program for Ph.D. students. She carries out research that combines cognitive science, social networks and computer science to address complex social and organizational problems. Her specific research areas are computational social and organization theory, group, organizational and social adaptation and evolution, social and dynamic network analysis, computational text analysis, and the impact of telecommunication technologies and policy on communication, information diffusion, disease contagion and response within and among groups particularly in disaster or crisis situations.     

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.     

Shortest paths algorithms: Theory and experimental evaluation

We conduct an extensive computational study of shortest paths algorithms, including some very recent algorithms. We also suggest new algorithms motivated by the experimental results and prove interesting theoretical results suggested by the experimental data. Our computational study is based on several natural problem classes which identify strengths and weaknesses of various algorithms. These problem classes and algorithm implementations form an environment for testing the performance of shortest paths algorithms. The interaction between the experimental evaluation of algorithm behavior and the theoretical analysis of algorithm performance plays an important role in our research. This work was done while Boris V. Cherkassky was visiting Stanford University Computer Science Department and supported by the NSF and Powell Foundation grants mentioned below. Andrew V. Goldberg was supported in part by ONR Young Investigator Award N00014-91-J-1855, NSF Presidential Young Investigator Grant CCR-8858097 with matching funds from AT&T, DEC, and 3M, and a grant from Powell Foundation. Corresponding author. This work was done while Tomasz Radzik was a Postdoctoral Fellow at SORIE, Cornell University, and supported by the National Science Foundation, the Air Force Office of Scientific Research, and the Office of Naval Research, through NSF grant DMS-8920550, and by the Packard Fellowship of éva Tardos.     

Adaptation as a Morphing Process: A Methodology for the Design and Evaluation of Adaptive Organizational Structures

Changes in objectives, in resources, or in the environment may necessitate the adaptation of an organization from one form to another. However, in many cases, the organizations need to continue functioning while adaptation takes place, i.e., it is not possible to stop the organizational activity in order to reorganize, and then start again. In this case, adaptation can be expressed as a morphing process in which the organization transitions from one form with its attendant task allocation to a different one through a series of incremental steps that preserve overall functionality and performance. Coordination between organization members during adaptation is critical. A computational model for this type of organizational adaptation at the operational level is presented. The model is implemented using the Colored Petri Net formulation of discrete event dynamical systems. A design methodology that utilizes this model is outlined and a simple example is used to illustrate the approach.     

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.     

Teiji Takagi, Founder of the Japanese School of Modern Mathematics

This article is a brief historical report on Teiji Takagi which was prepared at the commencement of ‘Takagi Lectures’ of The Mathematical Society of Japan. The first of its two purposes is to give some informations on the circumstances of education and research of mathematics in Japan surrounding Takagi who could finally established himself as the founder of the Japanese school of modern mathematics. The other is a brief overview on Takagi’s works of mathematics some of which are still attractive to and influential on especially ambitious students of mathematics. The author hopes that careful readers may find some hints for the questions how and why Takagi was able to establish his class field theory. At the end of this article the readers will find an English translation of the preface of his book Algebraic theory of numbers (in Japanese) which is the only thing that he left for us to see his total view over class field theory after the establishment of Artin’s reciprocity law.