Recognition-based inference: When is less more in the real world?

Common wisdom tells us that more information can only help and never hurt. Goldstein and Gigerenzer (2002) highlighted an instance violating this intuition. Specifically, in an analysis of their recognition heuristic, they found a counterintuitive less-is-more effect in inference: An individual recognizing fewer objects than another individual can, nevertheless, make more accurate inferences. Goldstein and Gigerenzer emphasized that a sufficient condition for this effect is that the recognition validity be higher than the knowledge validity, assuming that the validities are uncorrelated with the number of recognized objects, n. But how is the occurrence of the less-is-more effect affected when this independence assumption is violated? I show that validity dependencies (i.e., correlations of the validities with n) abound in empirical data sets, and I demonstrate by computer simulations that these dependencies often have a strong limiting effect on the less-is-more effect. Moreover, I discuss what cognitive (e.g., memory) and ecological (e.g., distribution of the criterion variable, environmental frequencies) factors can give rise to a dependency of the recognition validity on the number of recognized objects. Supplemental materials may be downloaded from http://pbr.psychonomic-journals.org/content/supplementa

The relative success of recognition-based inference in multichoice decisions

The utility of an "ecologically rational" recognition-based decision rule in multichoice decision problems is analyzed, varying the type of judgment required (greater or lesser). The maximum size and range of a counterintuitive advantage associated with recognition-based judgment (the "less-is-more effect") is identified for a range of cue validity values. Greater ranges of the less-is-more effect occur when participants are asked which is the greatest of to choices (m > 2) than which is the least. Less-is-more effects also have greater range for larger values of in. This implies that the classic two-altemative forced choice task, as studied by Goldstein and Gigerenzer (2002), may not be the most appropriate test case for less-is-more effects

Decision making study: methods and applications of evidential reasoning and judgment analysis

Decision making study has been the multi-disciplinary research involving operations researchers, management scientists, statisticians, mathematical psychologists and economists as well as others. This study aims to investigate the theory and methodology of decision making research and apply them to different contexts in real cases. The study has reviewed the literature of Multiple Criteria Decision Making (MCDM), Evidential Reasoning (ER) approach, Naturalistic Decision Making (NDM) movement, Social Judgment Theory (SJT), and Adaptive Toolbox (AT) program. On the basis of these literatures, two methods, Evidence-based Trade-Off (EBTO) and Judgment Analysis with Heuristic Modelling (JA-HM), have been proposed and developed to accomplish decision making problems under different conditions. In the EBTO method, we propose a novel framework to aid people s decision making under uncertainty and imprecise goal. Under the framework, the imprecise goal is objectively modelled through an analytical structure, and is independent of the task requirement; the task requirement is specified by the trade-off strategy among criteria of the analytical structure through an importance weighting process, and is subject to the requirement change of a particular decision making task; the evidence available, that could contribute to the evaluation of general performance of the decision alternatives, are formulated with belief structures which are capable of capturing various format of uncertainties that arise from the absence of data, incomplete information and subjective judgments. The EBTO method was further applied in a case study of Soldier system decision making. The application has demonstrated that EBTO, as a tool, is able to provide a holistic analysis regarding the requirements of Soldier missions, the physical conditions of Soldiers, and the capability of their equipment and weapon systems, which is critical in domain. By drawing the cross-disciplinary literature from NDM and AT, the JA-HM extended the traditional Judgment Analysis (JA) method, through a number of novel methodological procedures, to account for the unique features of decision making tasks under extreme time pressure and dynamic shifting situations. These novel methodological procedures include, the notion of decision point to deconstruct the dynamic shifting situations in a way that decision problem could be identified and formulated; the classification of routine and non-routine problems, and associated data alignment process to enable meaningful decision data analysis across different decision makers (DMs); the notion of composite cue to account for the DMs iterative process of information perception and comprehension in dynamic task environment; the application of computational models of heuristics to account for the time constraints and process dynamics of DMs decision making process; and the application of cross-validation process to enable the methodological principle of competitive testing of decision models. The JA-HM was further applied in a case study of fire emergency decision making. The application has been the first behavioural test of the validity of the computational models of heuristics, in predicting the DMs decision making during fire emergency response. It has also been the first behavioural test of the validity of the non-compensatory heuristics in predicting the DMs decisions on ranking task. The findings identified extend the literature of AT and NDM, and have implications for the fire emergency decision making

Assessing and explaining individual differences within the adaptive toolbox framework : new methodological and empirical approaches to the recognition heuristic

Individuals do not only show large differences with regard to the judgments and decisions they make, but also with regard to the strategies they use to arrive at their decisions. However, individual differences in decision strategy selection have gained insufficient attention so far. For this reason, I investigate individual differences with respect to the application of the fast-and-frugal heuristics of the adaptive toolbox – a framework that has become increasingly important within the field of decision making. In particular, I address one of the most prominent examples of the adaptive toolbox: the recognition heuristic (RH), that is, a decision strategy for paired comparisons which bases choice solely on recognition while ignoring any additional information. The overarching aim of my thesis is to enhance the understanding of the cognitive and personality traits underlying individual differences in use of the RH. However, so far, there has been a deficiency in the methods relating individual traits to RH-use. For this purpose, I extend a measurement model of the RH to a hierarchical version incorporating individual traits directly into the estimation of RH-use. This methodological advance allows detection of the dispositional determinants of variation in strategy selection regarding the RH in a straightforward and unbiased way. Equipped with the required methods, the first project reported in this thesis investigates temporal and cross-situational stability in use of the RH. By demonstrating these important preconditions, I ensure that it is principally possible to find reliable relations between individual traits and RH-use. Building upon these results, the second project addresses the effect of (fluid and crystallized) intelligence on individual differences in adaptive RH-use. In sum, there is supportive evidence that adaptive application of the RH to the decision context is moderated by fluid but not crystallized intelligence. Extending this line of research, the third project aims at explaining individual differences in RH-use free of any interaction with the situation. In brief, RHuse is found to decrease with need for cognition (i.e., inclination towards cognitively demanding activities) but not to increase with faith in intuition (i.e., trust in feelings). To conclude, by means of the three projects reported herein and with the aid of the newly developed hierarchical measurement model of RH-use, I demonstrate that RH-use represents a person-specific decision making style that is temporally and crosssituationally stable, and that is affected by fluid intelligence and need for cognition