search query: @author Schorling, C. / total: 1
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| Author: | Agrawal, D. Schorling, C. |
| Title: | Market share forecasting: an empirical comparison of artificial neural network and multinominal logit model |
| Journal: | Journal of Retailing
1996 : FALL, VOL. 72:4, p. 383-407 |
| Index terms: | RETAILING FORECASTING LOGIT MODELS |
| Language: | eng |
| Abstract: | The authors empirically compare the forecasting ability of artificial neural network (ANN) with multinominal logit model (MNL) in the context of frequently purchased grocery products for a retailer. Using scanner data on three grocery product categories, the authors find that performance of ANN compares favourably to MNL in forecasting brand shares. The authors test the sensitivity of the forecasting error in the two approaches to the length of the estimation period and the clustering of households which is used to define homogenous segments of households. |
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