A Behavioural Approach to the study of Retail Location

Abstract

The thesis develops a behavioural model of retail location which differs from established models in two respects. Firstly, the behavioural model emphasizes the demand for retail outlets rather than the supply of retail outlets. Instead of focusing attention on existing shopping opportunities and assessing their attraction potential, the behavioural model concentrates on the home base of the consumer and attempts to assess how far he/she is able to travel to a shopping location. In addition, emphasis on demand involves the development of a model within the framework of established consumer behaviour theory, thereby using psychological and sociological constructs to help explain store selection behaviour. Secondly, the behavioural model differs from established location theory in that an attempt is made to study the act of shopping in relation to other human activities in which people are involved. The basic postulate of the model is that people are constrained in their shopping behaviour. They are constrained by the commitments they have to the other activities in which they are involved, by their ability to travel, by their attitudes towards shopping, and by their available storage facilities at home. These four constraint characteristics are used to classify shoppers on a scale of constraints which ranges from highly constrained to highly unconstrained behaviour. It is hypothesized that a person's position on the constraints scale may be used as a basis for predicting store selection behaviour. Primary data was collected to test the hypothesis by using the technique of house-to-house interviewing. Analysis was performed with the aid of a computer and involved extensive use of multivariate statistical techniques. The constraints scale proved to be an inadequate analytical tool at the level of analysis considered. Therefore, an alternative approach was developed by establishing groups of shoppers that displayed significantly different retail store selection behaviour patterns. This approach involved an unusual combination of the techniques of cluster analysis and discriminant analysis.