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Computational and mathematical organization theory is an inter-disciplinary 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.

In this paper we propose an extension to the traditional model of bounded rationality and incorporate the extended model into a theory of organizational behavior. We argue that organizations are collections of tasks and intelligent agents engaged in performing those tasks, both situated within an organizational setting. Organizational behavior is an emergent property of such collections and is constrained by the agent, the task, and the situation. We propose that a unified theory of organizational behavior is possible, but only if agents, tasks, and situations are specified at a sufficient level of detail, and only if that specification embodies both the agents' mental models of the task and social-situation and the task and social-situation. Inattention to relevant details of the agent, task, or situation (and their interactions) may produce misleading results. We describe a candidate theory, ACTS theory, that integrates Agents who are Cognitively-restricted, Task-oriented, and Socially-situated in an interlinked set of representational systems. We suggest that the complexity of the theory warrants its realization and testing in a computational form, and that there exist candidate computational theories of cognitive agents and organizational situations. We illustrate the importance of attending to task

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views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Office of Naval Research or the U.S. government. Validating Computational Models The use of computational models in the social sciences has grown quickly in the past decade. For many these models represent a bewildering and possibly intimidating approach to examining data and developing social and organizational theory. Few researchers have had courses or personal experience in the development and building of computational models and even fewer have an understanding of how to validate such models. And while many papers extort the relative advantages and disadvantages of the computational approach, and many call for the validation of such models, few provide insight into how to validate such models and the issues involved in validation. This paper represents an attempt at redressing this oversight. An overview is provided of computational modeling in the social sciences,

a handbook of organizational processes

this paper, we present an algorithm that performs the partial deductive

Organizations are occasionally faced with technology-based and accident-triggered crises that may cause costly disasters if not handled properly. Questions arise: How should organizations, with their complex processes and human involvement, be designed if they are to perform well in such crises? Would organizations benefit from structural changes during crises? From a neo-information processing perspective that views organizations as composed of cognitively restricted, socially situated, and task-oriented actors, we argue that the causes and consequences of crises may be better understood through the systematic examination of both environmental and organizational factors. We address our research questions using a rather unique approach: a matched analysis of 80 real organizational cases and 80 computer-simulated organizations. The findings show that a crisis can present critical challenges to organizational performance both externally and internally, and that there is no design guarantee that a high-performing organization will continue to perform well during a crisis situation. In addition, when organizations restructure to adapt to crisis situations, they often face the serious challenges of having to understand not only the external environment, but also organizational design traps. Key words: organizational performance; organizational design; computational modeling; real-crisis cases Whether theories of organization can be applied to nonconventional events or crisis situations has largely been assumed but certainly not fully explored (Carley

Organizations sometimes face critical situations or crises that can induce severe consequences or even disasters if wrong decisions are made. The bulk of crisis management research has relied heavily on case study methods yet often with rhetorical or even inconsistent suggestions. With an exclusive focus on crisis prevention, the issue of how organizations can maintain good performance when faced with critical situations has largely remained unexplored. There is also an apparent lack of consideration regarding how aspects of organizational design and task environment interact and affect organizational performance under critical situations. In this paper, we attempt to address this issue from an open system’s perspective and integrate techniques of computational modeling with the analyses of two crisis cases, the Vincennes incident and the Hinsdale incident. The use of a computational model with strong organization theory foundation has provided a systematic mechanism for abstracting empirical information and generating theoretical results, thus complementing conventional case analyses, which thrive on in-depth information but are often limited by the lack of analytical ability to provide theoretical insight that goes beyond empirical descriptions. For the two crisis cases, the study shows, through detailed quantitative illustrations, that the computer model can be very effective in predicting organizational performance and suggesting designs that organizations can employ to mitigate the impact of crises. This study has demonstrated that our approach of computational case analysis can be very successful in providing systematic and explicit guidance for effective crisis mitigation both theoretically and empirically.

Foundation, or the U.S. government. The study of complex social and technological systems, such as organizations, requires a sophisticated approach that accounts for the underlying psychological and sociological principles, communication patterns and the technologies within these systems. Social Network Analysis and link analysis have since inception operated on the cutting edge bringing together mathematical analysis of social structures and qualitative reasoning and interpretation. As available computing power grew, social network-based models have become not only an analysis tool, but also a methodology for building new theories of social behaviour and organizational evolution, frequently through the creation of simulation models. This work examines the past approaches of creating Social Network-based semantically consistent and interpretable models of social structure and social