This paper sets out how models from natural science can be used within the management domain. We contend that this transformation between domains is best served by agent-based models, where the agent behavior is important, not the specifics of the agent type. We also note that these models are useful for exploring complexity and extending the research that has been performed within management to date. We demonstrate this with two models: the NK model, a theoretical biology model that has had 10 years of development within the strategy field, and the Forest Fire model, a model from physics that is at an early stage within its application within the management domain. In doing so, we also focus on the specific issues that need to be addressed when applying and extending these models to management studies due to the ontological differences between the realms of natural science and social science.
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Interest in complexity and, particularly, on understanding the distinctive features that characterize complex systems, has increased dramatically during the last two decades across many scientific disciplines. The reason for this is that the study of complex systems focuses on understanding how parts of a system give rise to its collective behavior, how such collective behavior affects such parts, and how systems interact with their environment (Bar-Yam, 2003). This focus on questions about parts, wholes, and relationships explains the relevance of the study of complex systems in the lives of biologists, physicists, economists, physicians, meteorologists, financial traders, and organizational theorists.
The increasing adoption of the complexity paradigm within the study of organizations has led to the adoption of computational agent based modeling as a method that enables us to address formally central features of complex systems such as nonlinear dynamics, interdependencies between subsystems, and emergent behavior. In this paper we analyze how models originally developed in the context of other sciences were "imported" to the realm of management studies with the purpose of dealing with research questions that require viewing firms as complex systems. We focus on two of these models: Kauffman's NK model, originally developed in biology, and the Forest Fire model, developed in physics. Despite their attractiveness in addressing questions related to the study of organizations, issues can be raised regarding the limitations of such models "imported" from the natural sciences when dealing with social science issues. We analyze these limitations in the context of the above-mentioned models and discuss possible resolutions. We focus first on the NK model, a model used extensively in the last decade in work focused on the impact of organizational trade-offs on performance. We then explore the Forest Fire model as a relatively new model and discuss the challenges related to its migration to the realm of organization studies. The purpose of this paper is twofold. First, we want to remark that these models offer significant potential in providing answers to questions related to organizations that other research methods cannot address effectively. Second, we wish to highlight the fact that work based on these models can only be suitable in the realm of social science if the researcher develops extensions to the model that bridge the important qualitative differences between the behavior of natural and social systems.
The use of models within management science
The use of models is commonplace within management science. We distinguish here between 'models' and 'frameworks'. We use the sense of modeling "to devise a (usually mathematical) model or simplified description of (a phenomenon, system, etc.)" (Suppes, 1974) in contrast to a framework such as Porter's Five Forces: Porter (1980:47) describes this as a "framework for competitor analysis" (emphasis added), not describing it as a model. …