As the retail environment became increasingly competitive and the risks of opening new outlets also increased, there became a need for firms to develop a quantifiable location strategy in order to help them minimize these risks and be successful in the market place. Past location models however, modeled consumer shopping trips as consisting of a single-stop, single-purpose, were home generated and were only considered with the impact of a single store location. Recent literature however, has revealed consumer shopping trips as being more complex with multiple stops and multiple purposes. In addition, the retail environment has shifted from consisting of mainly independent retailers to one comprised of mainly retail chains. Subsequently, what has emerged is a need to incorporate this more complex set of consumer shopping trips into a location model which can optimally locate an entire network of stores. It is this need which forms the basis of this study. The objective of this study is to vary the demand surface according to different combinations of single-stop, single-purpose and multi-stop, multi-purpose shopping trips and assess what impact these variations have in terms of the spatial location of outlets and the economic success of the firm. Each spatial demand pattern is incorporated into a p-median location-allocation model for outlets of a supermarket chain in Kitchener-Waterloo in 1981. It is shown that store locations tend to concentrate in the downtown as the level of multi-stop, multi-purpose trips increase. Also, areas which are highly sensitive to changes in demand patterns tend to be in the outlying areas while those which are insensitive tend to be in the downtowns. Furthermore, the solution which is optimal from the consumers’ perspective is not the same for the retailer. As a result, this study analyses the extent of sensitivity of store locations to the movements of their consumers
