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Heterogeneity in brand choice

The Dirichlet Model has been fitted to purchase behaviour in many product categories. The model uses the Dirichlet multinomial distributions to account for heterogeneity between customers in brand choice. The research reported here applies the concept of heterogeneity, developed in the Dirichlet Model, to other areas in marketing. It works through a range of classic market research techniques showing the changes and improvements that result from the consideration of heterogeneity in brand choice. The analysis has implications for (1) sample size calculations (2) the estimation of variance and reliability for nominal variables, (3) the evaluation of logistic and multinomial logit models, (4) the method and design of research which uses discrete choice models, (5) the evaluation of the similarities and differences between product categories and (6) the analysis and measurement of purchase feedback effects. The work also examines methods for identifying if a set of data conforms to the Dirichlet distribution. The work develops a concept of heterogeneity for a nominal variable, which was always known but the implications not fully understood. Discrete choice is a random Bernoulli trial based on a probability. The thesis embodied in the work presented here is that: across the population there is not a single probability, but a probability variable. The probability distribution of this variable is known as the mixing distribution. Analysis should focus on the attributes of this probability variable, and in particular its heterogeneity, rather than on the specific discrete brand choice. If all choice is based on the one, single underlying probability then there is no heterogeneity in the probabilities; there is no mixing distribution. If there is no heterogeneity in the probabilities then an analysis of the discrete choice is an analysis of random data evolving from repeated Bernoulli trials. The Dirichlet and Dirichlet multinomial distributions provide a strong framework for the analysis of the probability variable. / thesis (PhDBusinessandManagement)--University of South Australia, 2000.
Date January 2000
CreatorsRungie, Campbell Maxton
Source SetsAustraliasian Digital Theses Program
Detected LanguageEnglish
RightsCopyright 2000 Campbell Maxton Rungie

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