An analysis of brand interdependencies using Artificial Neural Networks

Marusya Ivanova ()
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Marusya Ivanova: Marketing Department, Faculty of Management and Marketing, "D. Tsenov Academy of Economics", Svishtov
Authors registered in the RePEc Author Service: Marusya Ivanova Smokova

Analele Stiintifice ale Universitatii "Alexandru Ioan Cuza" din Iasi - Stiinte Economice (1954-2015), 2008, vol. 55, 183-189

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.

Keywords: market response models; artificial neural networks; MCI market share models; cross-elasticities; competitive market structure; competitive map (search for similar items in EconPapers)
Date: 2008
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Persistent link: https://EconPapers.repec.org/RePEc:aic:journl:y:2008:v:55:p:183-189

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