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This paper addresses the problem of recovering the spatial market potentialof a retail product from spatially distributed sales data. In order to tacklethe problem in a general way, the concept of spatial potential is introduced.The potential is concurrently measured at different spatial locations and themeasurements are analyzed in order to recover the spatial potential. Themeasuring instruments used to collect the data interact with each other, thatis, the measurement at a given spatial location is affected by the concurrentmeasurements at other locations. An approach based on a novel geostatisticalmodel is developed. In particular, the model is able to handle both themeasuring instrument interaction and the missing data. A model estimationprocedure based on the expectation-maximization algorithm is provided as wellas standard inferential tools. The model is applied to the estimation of thespatial market potential of a newspaper for the city of Bergamo, Italy. Theestimated spatial market potential is eventually analyzed in order to identifythe areas with the highest potential, to identify the areas where it isprofitable to open additional newsstands and to evaluate the newspaper totalmarket volume of the city.

annals of applied statistics/the annals of applied statistics

Geostatistical modeling in the presence of interaction between the  measuring instruments, with an application to the estimation of spatial  market potentials