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A modification of the procedure originally used by Davidson, Suppes, and Siegel (1956) to measure subjective utility was used to study the influence of positive affect on individuals' perceived value (utility) functions. Results indicated, as expected, that persons in whom positive affect had been induced showed a more negative subjective utility for losses than did controls. This indicates that losses seem worse to people who are feeling happy than to those in a control condition. The subjective utility functions of the two groups did not differ as much, however, when people were considering potential gain. Thus, at least in the situation tested in this study, potential gains did not seem to be more appealing (nor less so) for affect subjects than they did for controls. These findings are discussed in relation to theoretical issues in decision making and work suggesting that positive affect can promote increased sensitivity to losses in situations of potential meaningful loss.

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This paper examines fundamental measurement issues that have largely been ignored in scaling techniques for assessing perceived mental workload. It is argued that both theoretical and practical advances in workload assessment have been unnecessarily slowed by a lack of concern for measurement issues. Typical of this impedance are some recently reported “empirical results“ comparing various workload assessment techniques which actually follow directly from some misunderstood statistical properties of the scales. The commonly used subjective workload assessment procedures have distinct psychometric properties that make each procedure sensitive to different kinds of workload measurement. Examination of the properties for the National Aeronautics and Space Administration Task Load Index (NASA TLX) support its potential as a general prediction model for experienced workload and for the Subjective Workload Assessment Technique (SWAT) as a cognitive model sensitive to individual differences.

We present the Maximization Inventory, which consists of three separate scales: decision difficulty, alternative search, and satisficing. We show that the items of the Maximization Inventory have much better psychometric properties when compared to the original Maximization Scale (Schwartz et al., 2002). The satisficing scale is a new addition to the study of maximization behavior, and we demonstrate that this scale is positively correlated with positive adaptation, whereas the decision difficulty and alternative search scales are positively correlated with nonproductive decisional behavior. The Maximization Inventory was then compared to previous maximization scales and, while the decision difficulty and alternative search scales are positively correlated with similar previous constructs, the satisficing scale offers a dimension entirely different from maximization.