Application of Logistic Growth Curve

Abstract

Efficient design of new processes and products requires not only an effective problem solving, but reliable forecasts of coming and distant changes. Decision making about investments into emerging technologies and strategic planning activities also rely upon consistent forecasts of technological substitution. There is a long record of applying different extrapolation techniques and, in particular, the logistic growth curves (S-curves) for studies about future changes. However, inappropriate use of S-shaped curves often leads to strange and inadequate results. Thus, among others, it is important to well define the system to forecast and provide an interpretable model from data. The paper illustrates the use of single logistic curve and logistic component analysis focusing on the coherence between model, data and interpretation. Directions for improving these techniques are discussed and a process for unambiguous definition of system is introduced.

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