In today's world, large-scale systems are frequently involved in levels of complexity that have a serious and global impact on productivity. A context model is set forth that facilitates a new definition of complexity, providing a background against which a science of complexity can be developed, and describing an empirical process from which the complexity of any particular situation can be quantified through a situation complexity index. In moving toward a science of complexity, the desirability of incorporating semiotics as a component of the science is indicated, because of the contributions semiotics makes to understanding the foundations and ubiquity of modelling. In the development of models, as semiotics indicates, the connection between what is being modelled and the language of description in the model is critical. Structural analysis clarifies the inappropriateness of models comprised only of prose to convey a description of a complex situation. Illustrative examples from the practice of interactive management (a system of management that supports the development and interpretation of structural models of complex situations, and design of improved systems) show the significance of structural thinking as the primary intellectual mode required to manage or cope with complexity. Group activity that would otherwise be invalidated by spreadthink is converted into a powerful approach to in-depth learning about a complex situation, which then provides a well-supported foundation for an organized attack to bring a complex situation under control.
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WARFIELD et al. (1996) studied this question.
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