Stochastic Models of Buying Behaviour - Tapa dura

Sinopsis

This is the first book on stochastic models of consumer buying behavior, and indeed one of a relative few books dealing with original contribution to research for marketing management (as opposed to textbooks) published to date. The purpose of the book is to present an integrated treatment of the authors' research on the title subject. Including the 15% or so of material discussing the work of others in the field, and one chapter on statistical methodology, the book covers almost all aspects of the field of stochastic process models of buyer behavior as it is known today. Thus the book is both intensive, in that it covers both the theoretical and empirical aspects of the authors' models in detail, and extensive in that it provides a comprehensive treatment of the general subject.

While all essential concepts of stochastic process and estimation theory are developed in the body of the work, it assumes prior knowledge of mathematics through calculus and matrix algebra. However, every effort has been made to write for the practicing management scientist as well as the academic specialist.

The approach of the book is to develop, in order, the theory of successively more refined stochastic models of buyer behavior. We begin with the heterogeneous Bernoulli model and then extend the treatment to a class of heterogeneous Markov processes. The next two chapters deal with independent and contagious probability diffusion processes for explaining time changes in market shares. The linear learning model is considered in the next chapter. The treatment then shifts to stochastic market penetration models, of which several different varieties are explored. Empirical results from marketing applications are provided for nearly all the models. Separate chapters on parameter estimation procedures and ways in which the models may be applied to management problems are provided early in the book.

Many of the models and empirical results presented in the book have never been published before, and others have received only limited attention. The general approach to stochastic model development and testing will serve to put the rather extensive but scattered literature on stochastic marketing models on a common footing. Finally, many of the models developed in the book should find applications in other branches of social science, such as sociology or political science.

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