Estimating the effects of parameter variability on learning curve model predictions

Estimating the effects of parameter variability on learning curve model predictions

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Article ID: iaor19942139
Country: Netherlands
Volume: 34
Issue: 2
Start Page Number: 187
End Page Number: 200
Publication Date: Mar 1994
Journal: International Journal of Production Economics
Authors: ,
Keywords: learning curves
Abstract:

The learning curve concept has proven to be a valuable management tool. However, regardless of which learning curve model is used, uncertainty is inherent in the forecast due to the empirical nature of learning curve theory and complications with establishing model parameters. Such variability is often ignored but can greatly affect the reliability of the model’s predictions. Thus, as a means of approximating the effects of such uncertainty on model predictions, this paper proposes an analytical stochastic approach to estimating the precision of learning curve forecasts and provides an illustration of the technique with actual product cost data. The example shows that this analytical stochastic approach can provide accurate cost predictions with reliable prediction interval estimates.

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