This book is the first comprehensive presentation of a Markov model with covariates and a multivariate Poisson model with competing destinations. These two models are core techniques when the author and his colleagues carry out their studies. The two models usually are used in combination to forecast the effects of specific urban redevelopment on both the number of visitors and consumer shop-around movements. The author’s studies originated from the constructions of a Markov model and the disaggregated hierarchical decision Huff model almost at the same time around the early 1980s. This book reviews in retrospect how these models have evolved from the start to the present state and previews the ongoing efforts to make further extensions of these models. The extension of the Huff model started from the disaggregated hierarchical decision Huff model with shop-arounds. In retrospect, the model formulated as a joint probability the consumer’s simultaneous choice of destinations. The mechanism to determine this joint probability was a recursive conditional probability system. Now the Huff model has shifted from joint probability to multivariate frequency Poisson with competing destinations. The Markov model started from a descriptive model. Because it cannot forecast changes of shop-arounds, the Markov model with covariates was developed in which entrance and shop-around choice probabilities are explained by the respective two logit models with covariates such as distances and shop-floor area. The noticeable point is that it can explain the probability of consumers to quit shop-arounds. Thus the model enables one to evaluate the effects of urban revitalization policy that promotes consumer shop-arounds. If the Markov model can estimate the actual numbers of flows of consumer shop-arounds among shopping sites, the corresponding money flows also can be estimated as economic effects. This book discusses step by step the evolution of all these topics. weiterlesen