Abstract
This paper outlines the use of linear and nonlinear models in forecasting net car sales of the Japanese automotive Industry. In this method, variables representing complex social phenomena can be included in the mathematical models and can be derived by using actual time series data with no additional mathematical complexity. In this paper, we show that it is possible: to derive four satisfactory model structures from a single set of time series data; to estimate coefficients of the structures; and to make accurate forecasts. Reports on the theory and application of the GMDH method have been published previously, but few of them have actually applied the method to management systems.
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