Article ID: | iaor2000597 |
Country: | United States |
Volume: | 44 |
Issue: | 8 |
Start Page Number: | 1115 |
End Page Number: | 1130 |
Publication Date: | Aug 1998 |
Journal: | Management Science |
Authors: | Meade Nigel, Islam Towhidul |
Keywords: | forecasting: applications, innovation |
The paper identifies 29 models that the literature suggests are appropriate for technological forecasting. These models are divided into three classes according to the timing of the point of inflexion in the innovation or substitution process. Faced with a given data set and such a choice, the issues of model selection needs to be addressed. Evidence used to aid model selection is drawn from measures of model fit and model stability. An analysis of the forecasting performance of these models using simulated data sets shows that it is easier to identify a class of possible models rather than the ‘best’ model. This leads to the combining of model forecasts. The performance of the combined forecasts appears promising with a tendency to outperform the individual component models.