Spatial ordered weighted averaging: incorporating spatially variable attitude towards risk in spatial multi-criteria decision-making

The paper discusses a decomposition–analysis–aggregation approach to multi-criteria spatial decision-making and proposes a novel aggregation method applicable to problems of the object-location or suitability for application type, concentrating on methodological rather than software development aspects. The approach allows the decision maker to: (a) break the problem down into a series of elementary (easier to understand) problems, (b) analyse them (in the broad sense of the word), and then (c) produce an answer for the complex problem by aggregating the answers derived for the elementary problems. The choice of methodology used for this aggregation is very important as different aggregating techniques may yield different results to the (same) original problem. The method presented here, which is in effect an extension of the ordered weighted averaging (OWA) method into a spatial decision-making technique, is termed spatial ordered weighted averaging (SOWA). The main advantage of the method proposed is the incorporation of spatially variable attitude to risk into the decision-making process. The mathematical background of the method and an example of its application in urban water management are presented and discussed. The authors suggest that the method could be useful as an analytical and decision-making tool for the incorporation of spatially variable risk perception in GIS-based decision support systems.