In this paper the authors are concerned with the application of conjoint measurement models to predict consumer choice of shopping centres. First, conjoint measurement models are discussed in the context of the development of spatial shopping-models. Next, the conceptual framework underlying the model and conjoint measurement are discussed. The second part of the paper describes an application of the methodology. Conjoint measurement is used to estimate consumer utility functions and a multivariate logit model as an approximation of the unit multivariate normal distribution is used to predict the probability that a consumer will choose a particular shopping centre. The results indicate that the methodology offers a potentially valuable approach to the modelling of spatial shopping-behaviour.

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This article reports on an empirical analysis of consumer information and usage fields in the city of Eindhoven. The main purposes of this study are to investigate the distance, sector-al and directional biases of these fields, to analyse whether the degree of biases is related to personal characteristics of consumers and to identify the factors of the basis on which a model which predicts the probability that a shopping centre will be known by consumers can be developed. The findings of the study suggest that strong distance, sectoral and directional biases are present in the information and usage fields of consumers and that no systematic relationships exist between these characteristics of information and usage fields and personal variables of consumers. Finally, the present studies suggests that a model which describes the formation of consumer choice sets should include spatial factors such as distance, size, intervening opportunities and direction towards the city centre.

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