Heuristics in Multi-attribute Decision Making: Effects of Representation Format

Heuristics in Multi-attribute Decision Making: Effects of Representation Format Georg Jahn (georg.jahn@phil.tu-chemnitz.de) Chemnitz University of Technology, Department of Psychology Wilhelm-Raabe-Str. 43, D-09107 Chemnitz, Germany Frank Renkewitz (frank.renkewitz@uni-erfurt.de) University of Erfurt, Department of Psychology Nordhauser Str. 63, D-99089 Erfurt Sonja Kunze (sonja.kunze@s2001.tu-chemnitz.de) Chemnitz University of Technology, Department of Psychology Wilhelm-Raabe-Str. 43, D-09107 Chemnitz, Germany Abstract of the murderer. The description of suspects and the description of the murderer contained four cues (accompanying dog, type of the jacket, type of trousers, and color of the shirt) that were the more valid the more witnesses were said to agree on the respective cue value. The results of this experiment suggested that participants differed with regard to how completely they considered cue dimensions and cue validity. Furthermore, the format in which cue values were learned affected how they were used in decisions. Participants who were presented with suspects’ images in the learning phase considered more cue dimensions than participants who learned lists of suspects’ attributes. This effect of presentation format supported Broder and Schiffer’s prediction that integrated images should induce a holistic memory representation of alternatives. A holistic memory representation should then support retrieving and comparing several cue values in parallel in memory-based decisions. More or less complete information integration corresponds to presumed strategies and heuristics in human information processing. Using all cue dimensions and cue validity, decisions could be based on all available cue values that are weighted by their validity. This strategy would choose the alternative with the highest weighted sum. Following Gigerenzer and his colleagues (1999), we will refer to this strategy as Franklin’s rule (FR) after Benjamin Franklin who proposed a similar procedure. A second strategy that also considers all cue dimensions but disregards cue validity has been named Dawes’ rule (DR) after Robyn Dawes (Dawes, 1979). DR weighs each cue dimension equally and decides based on summed cue information. For example, if one suspect would match the description of the murderer in two attributes and the other suspect would match in three attributes, DR would select the latter. A third strategy – prominent for its efficiency as a “fast and frugal” heuristic in some real-world domains as shown by Gigerenzer and his colleagues – is known as “Take the Best” (TTB). TTB uses cue validities, but decides on the basis of a single cue. Cue dimensions are considered in the order of validity starting with the most valid cue. As soon as a cue dimension is found on which the alternatives differ, the alternative with the superior cue value is selected and all dimensions of less validity are ignored. Consequently, TTB When probabilistic inferences have to be drawn based on cue values stored in long term memory, participants appear to use a number of different heuristics. These heuristics vary in the amount of available cue information that is retrieved and integrated, and in the degree to which cue validities are considered. One factor that is assumed to affect strategy selection is the representational format of cue information: Holistic, image-based representations should induce the parallel retrieval of cue values and thus foster the use of compensatory strategies that take into account multiple cue dimensions. In contrast, verbal representations should favor non-compensatory strategies that draw inferences based on a single cue dimension. We tested this hypothesis in an experiment and explored how the learning procedure modulates the use of cue validities. The results suggest that the acquisition of cue knowledge from holistic images increases the use of a compensatory prototype matching strategy that neglects cue validities. Keywords: Multi-attribute decision making, Probabilistic inference, Bounded rationality, Take-the-best heuristic . Memory-based Multi-attribute Decisions In most decisions the alternatives to choose from differ with regard to several attributes. Such multi-attribute decisions are linked to a fundamental issue in the study of human rationality: How do individuals integrate information? A single attribute may be viewed as a value on a cue dimension. Then alternatives can be described by the values that they carry on cue dimensions. Usually, cue dimensions are not equally important. If cue values signal the likelihood of positive or negative outcomes (in probabilistic inferences), cue importance is referred to as cue validity. In deciding between two alternatives, cue values and cue validity can be factored in to varying degrees (e.g., Gigerenzer, Todd, & the ABC Research Group, 1999). Individuals could compare cue values of alternatives on single dimensions, they could integrate the results of such comparisons from several dimensions, and they could weigh cue dimensions according to their validity. Consider, for example, the task studied by Broder and Schiffer (2003b, Experiment 4): Participants learned about ten suspects in a murder and then had to decide for several pairs of suspects who in a pair was more likely to be guilty based on the match with the description that witnesses gave