Organizations are complex systems. They are also information processing systems comprised of a large number of agents such as human beings. Combining these perspectives and recognizing the essential non-linear dynamics that are at work leads to the standard non-linear multi-agent system conclusions such as: history matters, organizational behavior and form is path dependent, complex behavior emerges from individual interaction, and change is inevitable. Such a view while descriptive, is still far from the level of specificity and predictive richness that is necessary for organizational theory. To increase the specificity and value of our theories we will need to take into account more of the actual attributes of tasks, resources, knowledge and human cognition. In doing so, it will be possible to achieve a more adequate description of organizations as complex computational systems. More importantly, we will also achieve a greater ability to theorize about the complexity of organizational behavior. This paper describes complexity theory and computational organization theory. Then a description of organizations as complex computational systems is presented and operationalized as a computational model. Within this perspective, organizational behavior results form the actions of heterogeneous actors, the boundaries between agents, tasks, and resources are permeable, organizational roles emerge, organizational groups are networks, and information technology plays a key role as an interactive agents.
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