Abstract
This article describes how continuous GIS-MCDM problems are commonly managed by combining some weighting method based on pairwise comparisons of criteria with an aggregation method. The reliability of this approach may be questioned, though. First, assigning weights to criteria, without taking into consideration the actual consequences or values of the alternatives, is in itself controversial. Second, the value functions obtained by this approach are in most cases linear, which is seldom the case in reality. The authors present a new method for GIS-MCDM in continuous choice models based on Even Swaps. The method is intuitive and easy to use, based on value trade-offs, and thus not relying on criteria weighting. Value functions obtained when using the method may be linear or non-linear, and thereby are more sensitive to the characteristics of the decision space. The performed case study showed promising results regarding the reliability of the method in GIS-MCDM context.
Highlights
The ultimate goal of geographic information systems (GIS) is to provide support for spatial decision-making
In this paper we present GISwaps - a new method for GIS decision-making in continuous choice models, inspired by, and in parts based on, the Even Swaps trade-off method developed by Hammond, Keeney and Raiffa (Hammond et al, 1998, 1999)
GISwaps is a method based on the concept of value trade-offs under certainty, when the consequences of each alternative with respect to each criteria or objective are known
Summary
The ultimate goal of geographic information systems (GIS) is to provide support for spatial decision-making. For the last two or three decades there has been a growing interest in the subject of integrating multi-criteria decision analysis (MCDA) and GIS (Malczewski, 2007). The need to address the issue of applying the established concepts of multi-criteria decision making to spatial problems, and adapting them with respect to the nature and the format of GIS data, has resulted in a whole new interdisciplinary field of study, commonly referred to as GIS-based multi-criteria decision analysis (GIS-MCDA). Malczewski & Rinner (2015) define GIS-MCDA as “a collection of methods and tools for transforming and combining geographic data and preferences (value judgments) to obtain information.
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