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

Alan D. Zimm
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Alan D. Zimm: The Johns Hopkins University Applied Physics Laboratory 1987

Computational and Mathematical Organization Theory, 2005, vol. 11, issue 1, No 2, 37-57

Abstract: Abstract 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.

Keywords: chaos; population ecology; organizations; economic systems; competitive systems; Logistic equation; Organization Logistic equation (search for similar items in EconPapers)
Date: 2005
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DOI: 10.1007/s10588-005-1726-2

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