haku: @author Gruca, T. S. / yhteensä: 4
viite: 4 / 4
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| Tekijä: | Gruca, T. S. Klemz, B. R. |
| Otsikko: | Using neural networks to identify competitive market structures from aggregate market response data |
| Lehti: | Omega
1998 : FEB, VOL. 26:1, p. 49-62 |
| Asiasana: | MARKET STRUCTURE FORECASTING NETWORKS COMPETITION |
| Kieli: | eng |
| Tiivistelmä: | Elasticity estimates provide the brand manager with useful diagnostics for evaluating competitive market structure. However, an econometric model must often be simplified due to the limited amount of data available to estimate the model's parametres. Capitalizing on the forecasting ability of neural networks, an innovative method of extracting elasticity structure is introduced for a convenient consumer retail product market. The resulting forecasting measures and the elasticity structures are then compared with those obtained from a differential-effects multiplicative competitive interaction (or MCI) aggregate market share model. It is found that the neural network slightly outperformed the differential-effects MCI model with regards to model fit. The results of the paper also suggest that the neural network offered superiour estimates of asymmetric cross-elasticities resulting in superiour forecasting ability of the holdout sample. |
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