Abstract
There is an increasing use of multi-criteria spatial decision support systems in recent years for dealing with problems that have a spatial distribution of consequences. This growth might be explained by the widespread recognition that there are multiple and conflicting objectives to be considered in spatial planning (e.g. minimizing pollution to air, water and soil, increasing the acceptance of the projects, reducing implementation costs), by new requirements to consider societal values in the evaluation and to increase participation in decision processes, as well as by the crucial role that the spatial dimension plays in such problems. However, we argue in this paper that there are key challenges confronted by DSS designers who are developing such systems and by DSS practitioners who are employing them to support decision making. These challenges impose important meta-choices to designers and practitioners, which may lead to different contents of the evaluation model and to distinctive outcomes of the analysis. In this paper, we present and discuss these key challenges and the associated meta-choices. The contribution that we aim to provide to both researchers and practitioners can be summarized as follows: (i) an increased awareness about choices to be made in the design and implementation of these decision support systems; (ii) a better understanding about the available alternatives for each choice, based on recent developments in the literature; and (iii) a clearer appraisal about the inherent trade-offs between advantages and disadvantages of each alternative.
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