Many real-world spatial decisions are multi-criteria by nature. A multi-criteria spatial decision analysis is a process in which one or more spatial alternatives are evaluated and selected based on a set of different criteria, by one or a group of individuals. Weighting the criteria is an important step of spatial multi-criteria decision-making. It represents the priority of that criterion relative to other criteria in decision making process. According to the range sensitivity principle, the weight of a criterion is the function of the range of changes in the values ​​of that criterion (the difference between the minimum and maximum values ​​for the criterion), in addition to its relative importance of the criterion. However, decision makers often ignore the range values when weighing the criteria in decision making processes. 

The main objective of this paper is to examine the research question “Do decision makers consider criteria ranges during the weighting process in a multi-criteria spatial decision-making process? Understanding how decision makers acquire and integrate decision-related information (i.e., criteria range values) helps to use an appropriate level of decision information in a multicriteria spatial decision analysis. In order to achieve the objectives of this research, the problem of locating public parking facilities in the district # 22 of Tehran was selected as the case study. The decision information including criteria values and ranges were presented to decision makers using decision table and map. The decision table represents the decision information in an alternative × attribute matrix. It consists of a set of values associated with each alternative-attribute pair. The rows of the matrix represent alternatives, the columns represent attributes, and the cells contain the measured values of the attributes associated with the alternatives. In addition to the alternative-attribute values, the table includes the range values of the attributes in the last row. The simultaneous map-table information aids facilitates understanding of the decision problem by enabling the decision makers to explore the basic relationships between the non-spatial attribute values of decision alternatives (criterion outcomes) and the spatial patterns of alternatives (decision space).

The results show that decision makers in individual decision-making (without access to group decision) examined 55.5%, 26.8%, 25.5% and 14.5% of criteria ranges in four levels of decision-making information, respectively.  When it comes to the group decision-making mode (with access to group decision), they looked at 21.8%, 6.6%, 8.8%, and 7.9% of criteria ranges in the four levels. Overall, the results of ANOVA test show that this number decreases with increasing amount of decision making information. Therefore, it can be concluded that decision makers mainly consider the relative importance of the criteria, and in most cases ignore the ranges of changes in the criteria values, when faced with higher levels of decision-making information. The results of this study has implications for investigating behavioral theories in the spatial decision making context and practical implications for the development of multicriteria decision analysis. Explicitly, the findings provide a new perception on the use of decision support aids, and significant signs for designers to develop a suitable user-centered Web-based participatory decision analyses.