The current study examines the construct validity of the Maximization Scale (MS; Schwartz et al., 2002) and the Maximization Tendency Scale (MTS; Diab et al., 2008) as well as the nomological net of the maximizing construct. We find that both scales of maximizing suffer psychometrically, especially in their proposed dimensionality. Using confirmatory factor analysis and item response theory (IRT) we identify and remove three problematic items from the MTS and six problematic items from the MS. Additionally, we find that the MS appears to be measuring difficulty and restlessness with the search for the best alternative, whereas the MTS is more focused on the search for the best option, regardless of choice difficulty. We then examined these revised scales in relation to other psychological constructs in the nomological net for maximizing and found that maximizers may not be unhappy but are generally distressed in the decision-making context. Finally, we suggest that future maximizng research use revised form of the MTS that seems to us to be most consistent with the original concept of maximizing/satisficing.

Evaluation judgments were affected by information order and not by subsequent unconscious versus conscious deliberation. In three experiments, we examined the influence of early positive information on final evaluations of four objects. Based on a task analysis, we predicted primacy effects in judgments in a sequential data acquisition task. Thinking periods following presentation were used to manipulate conscious or unconscious processing. In all three studies, we found no effects of thinking manipulations but instead found reliable order effects. We developed and tested an online judgment model on the basis of the belief updating model of Hogarth and Einhorn. The model accounted for large proportion of the individual level variability, and model comparison tests supported the presence of a primacy effect. 1 We note that in Strick et al. (2010), participants saw all the information not in random order across options, but the information was organized such that all aspects of one option were viewed before moving to another option. This is a very different information acquisition paradigm from the used by Note: Standard deviations are in parentheses. Rating scale is À10 (very negative) to +10 (very positive).Online Judgment Model 211 C. González Vallejo et al.

The familiarity difference cue has been regarded as a general cue for making inferential judgments (Honda, Abe, Matsuks, & Yamagishi in Memory and Cognition, 39(5), 851-863, 2011; Schwikert & Curran in Journal of Experimental Psychology: General, 143(6), 2341-2365, 2014). The current study tests a model of inference based on familiarity differences that encompasses the recognition heuristic (Goldstein & Gigerenzer, 1999, Goldstein & Gigerenzer in Psychological Review, 109(1), 75-90, 2002). In two studies, using a large pool of stimuli, participants rated their familiarity of cities and made choices on a typical city-size task. The data were fitted with the r-s model (Hilbig, Erdfelder, & Pohl in, Journal of Experimental Psychology: Learning Memory and Cognition, 37(4), 827-839, 2011), which was adapted to include familiarity differences. The results indicated that people used the familiarity difference cue because the participants ignored further knowledge in a substantial number of cases when the familiarity difference cue was available. An analysis of reaction-time data further indicated that the response times were shorter for heuristic judgments than for knowledge-only-based judgments. Furthermore, when knowledge was available, the response times were shorter when knowledge was congruent with a heuristic cue than when it was in conflict with it. Differences between the familiarity difference cue and the fluency heuristic (Schooler & Hertwig, 2005, Psychological Review, 112, 610-628) are discussed.

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