AN ANALYSIS OF BRAND INTERDEPENDENCIES USING ARTIFICIAL NEURAL NETWORKS
AN ANALYSIS OF BRAND INTERDEPENDENCIES USING ARTIFICIAL NEURAL NETWORKS
Author(s): Marusya IvanovaSubject(s): Economy
Published by: Editura Universităţii »Alexandru Ioan Cuza« din Iaşi
Keywords: market response models; artificial neural networks; MCI market share models; cross-elasticities; competitive market structure; competitive map
Summary/Abstract: The purpose of this article is to present the abilities of Artificial Neural Networks in analyzing the existing structure of brand interdependencies compared to DE-MCI model. To achieve this pur-pose a comparative study is done based on POS data used by Cooper and Nakanishi in their monograph. The results suggest that ANN model outperform DE-MCI model with regards to model fit and they offer face valid estimates of self and cross-elasticities. Based on the transformed cross-elasticity estimates, a MDS map is produced. This competitive map is used to identify the existing interdepend-encies among the brands in the market.
Journal: Analele Ştiinţifice ale Universităţii »Alexandru Ioan Cuza« din Iaşi. Ştiinţe economice
- Issue Year: 2008
- Issue No: 55
- Page Range: 183-189
- Page Count: 7
- Language: English