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Łapczyński Mariusz (Kolegium Nauk o Zarządzaniu i Jakości), Sagan Adam (Kolegium Nauk o Zarządzaniu i Jakości)
Podejście entropijne w badaniach struktur rynkowych
The Entropic Approach in Market Structure Research
Zeszyty Naukowe / Akademia Ekonomiczna w Krakowie, 2007, nr 739, s. 67-90, bibliogr. 19 poz.
Badanie rynku, Struktura rynku, Analiza rynku, Algorytmy, Analizy głównych komponentów
Market research, Market structure, Market analysis, Algorithms, Principal Component Analysis (PCA)
Omówiono entropijne modele przestrzenne oraz przeprowadzono analizę niezależnych składowych. Przedstawiono entropię w metodach drzew klasyfikacyjnych, a także opisano aplikacje i implementacje drzew entropijnych.

The aim of this article is to identify alternative analytical tools based on entropy measures that could be used in market structure analysis. Entropy measures have long been present in marketing research, as is shown by, for instance, J. D. Herniter's models of predicting consumer purchasing behaviour or J. Carter and F. Silverman's analysis of preference shift matrices. Discussion of market structures is based on T. Elrod's popular definition, which states that the primary aim of this type of research is to identify complementary and substitutive products and to better understand competitiveness on the market. The authors of this article describes two methods - one for spatial analysis (independent component analysis) and the other for hierarchical analysis (classification trees). In the first part of the article, the authors briefly characterise the ICA method and describe the stages of the analytical procedure, indicating the advantages of this method over traditional principal component analysis. In the second part, the authors categorise classification tree algorithms based on the popular ID3 method and explain a method for estimating the measure known as information gain and the measure known as the gain ratio. The authors conclude by identifying the areas of theory and practice in which entropie methods have been applied. (original abstract)
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