Limits to decision-making ability in direct multiattribute alternative evaluation

In recent years there has been considerable interest in how decision strategies in choice problems depend on such characteristics as the number of available criteria and the number of available alternatives. Along with multicriteria choice problems, classification tasks are treated where alternatives are classified into several decision (evaluative) classes. We believe that in classification problems one's ability in information processing is limited and depends on task complexity. In this paper we describe two experiments involving categorization of a large number of multiattribute alternatives into two or four evaluative classes. The results demonstrate that the subjects use different decision strategies and that there is a limit in human ability to implement these two tasks.     

An efficient technique for revealing visual search strategies with classification images

We propose a novel variant of the classification image paradigm that allows us to rapidly reveal strategies used by observers in visual search tasks. We make use of eye tracking, 1/f noise, and a grid-like stimulus ensemble and also introduce a new classification taxonomy that distinguishes between foveal and peripheral processes. We tested our method for 3 human observers and two simple shapes used as search targets. The classification images obtained show the efficacy of the proposed method by revealing the features used by the observers in as few as 200 trials. Using two control experiments, we evaluated the use of naturalistic 1/f noise with classification images, in comparison with the more commonly used white noise, and compared the performance of our technique with that of an earlier approach without a stimulus grid.     

The response dynamics of preferential choice

The ubiquity of psychological process models requires an increased degree of sophistication in the methods and metrics that we use to evaluate them. We contribute to this venture by capitalizing on recent work in cognitive science analyzing response dynamics, which shows that the bearing information processing dynamics have on intended action is also revealed in the motor system. This decidedly “embodied” view suggests that researchers are missing out on potential dependent variables with which to evaluate their models—those associated with the motor response that produces a choice. The current work develops a method for collecting and analyzing such data in the domain of decision making. We first validate this method using widely normed stimuli from the International Affective Picture System (Experiment 1), and demonstrate that curvature in response trajectories provides a metric of the competition between choice options. We next extend the method to risky decision making (Experiment 2) and develop predictions for three popular classes of process model. The data provided by response dynamics demonstrate that choices contrary to the maxim of risk seeking in losses and risk aversion in gains may be the product of at least one “online” preference reversal, and can thus begin to discriminate amongst the candidate models. Finally, we incorporate attentional data collected via eye-tracking (Experiment 3) to develop a formal computational model of joint information sampling and preference accumulation. In sum, we validate response dynamics for use in preferential choice tasks and demonstrate the unique conclusions afforded by response dynamics over and above traditional methods.     

Holistic Information Integration in Child Decision Making

Weighted‐additive (WADD) strategies require decision makers to integrate multiple values weighted by their relevance. From what age can children make choices in line with such a WADD‐strategy? We compare multi‐attribute decisions of children (6–7; 8–10; 11–12‐year‐olds) with adults in an open information‐board environment without pre‐decisional information search. In two experiments, we classify decision strategies based on individual choice patterns and find that in all age groups the majority of participants are users of a WADD‐strategy. Simple decision heuristics such as lexicographic strategies were applied rarely by children and not at all by adults. In two additional follow‐up studies, we further investigate the underlying process of WADD‐application by analysing decision latencies in combination with a retrospective think‐aloud study. Results suggest that children did not apply WADD‐strategies in a deliberate fashion in our experiments. Overall, our findings demonstrate that the ability to make good and quick decisions by holistically integrating information is already present in young children. Copyright © 2017 John Wiley & Sons, Ltd.     

Decision moving window: using interactive eye tracking to examine decision processes

It has become increasingly more important for researchers to better capture the complexities of making a decision. To better measure cognitive processes such as attention during decision making, we introduce a new methodology: the decision moving window, which capitalizes on both mouse-tracing and eye-tracking methods. We demonstrate the effectiveness of this methodology in a probabilistic inferential decision task where we reliably measure attentional processing during decision making while allowing the person to determine how information is acquired. We outline the advantages of this methodological paradigm and how it can advance both decision-making research and the development of new metrics to capture cognitive processes in complex tasks.     

Analysis of proposed three-class classification decision rules in terms of the ideal observer decision rule

We analyze recently proposed decision rules for three-class classification from the point of view of ideal observer decision theory. We consider three-class decision rules proposed by Scurfield, by Chan et al., and by Mossman. Scurfield's decision rule is shown to be a special case of the three-class ideal observer decision rule in three different situations. Chan et al. start with an ideal observer model and specify its decision-consequence utility structure in a way that causes two of the decision lines used by the ideal observer to overlap and the third line to become undefined. Finally, we show that, for a particular and obvious choice of ideal-observer-related decision variables, the Mossman decision rule cannot be a special case of the ideal observer decision rule. Despite the considerable difficulties presented by the three-class classification task, the three-class ideal observer provides a useful framework for analyzing a variety of three-class decision strategies.     

Fitting decisions: Mood and intuitive versus deliberative decision strategies

We investigated the influence of the compatibility between mood and decision strategies on the subjective value of a decision outcome. Several studies have provided evidence for the idea that a sad mood induces people to analyse information carefully, probably fitting well with a deliberative decision strategy. In a happy mood, people tend to act more strongly on their feelings, probably fitting well with an intuitive decision strategy. However, sometimes the situation demands the use of decision strategies that seem incompatible with mood states. We expected that decision makers would value a decision outcome higher in the case of a fit between mood and decision strategy than in the case of a non-fit. After a mood manipulation, participants were instructed to decide either based on their first affective reaction or after deliberation. Results confirmed our expectations: fitting decisions enhanced the subjective value of a decision outcome.     

Decision noise: An explanation for observed violations of signal detection theory

In signal detection theory (SDT), responses are governed by perceptual noise and a flexible decision criterion. Recent criticisms of SDT (see, e.g., Balakrishnan, 1999) have identified violations of its assumptions, and researchers have suggested that SDT fundamentally misrepresents perceptual and decision processes. We hypothesize that, instead, these violations of SDT stem from decision noise: the inability to use deterministic response criteria. In order to investigate this hypothesis, we present a simple extension of SDT—the decision noise model—with which we demonstrate that shifts in a decision criterion can be masked by decision noise. In addition, we propose a new statistic that can help identify whether the violations of SDT stem from perceptual or from decision processes. The results of a stimulus classification experiment—together with model fits to past experiments—show that decision noise substantially affects performance. These findings suggest that decision noise is important across a wide range of tasks and needs to be better understood in order to accurately measure perceptual processes.     

Life choices well made: How selective control strategies relate to career and partner decision processes

There are many benefits of applying control strategies that foster engagement in pursuing selected goals (i.e., selective control strategies). We examined one such benefit by investigating how use of selective control strategies when making important real-life decisions helps young adults make satisfactory choices in the areas of work and love. In a prospective longitudinal study, 60 students who intended to choose a college major and/or find a romantic partner initially reported on their control strategies. Subsequently, we assessed changes in the perceived attractiveness of considered majors and partners during decision making and our participants’ satisfaction with their choices. As expected, use of selective control strategies predicted greater choice satisfaction. This association was mediated by the greater perceived attractiveness of chosen majors or partners, which increased during decision making. Applying selective control strategies during real-life decisions thus leads to more favorable evaluations of the resulting choices, which can ease their implementation.     

An Optimized Design of Choice Experiments: A New Approach for Studying Decision Behavior in Choice Task Experiments

In this paper, we present a new approach for the optimal experimental design problem of generating diagnostic choice tasks, where the respondent's decision strategy can be unambiguously deduced from the observed choice. In this new approach, we applied a genetic algorithm that creates a one‐to‐one correspondence between a set of predefined decision strategies and the alternatives of the choice task; it also manipulates the characteristics of the choice tasks. In addition, this new approach takes into account the measurement errors that can occur when the preferences of the decision makers are being measured. The proposed genetic algorithm is capable of generating diagnostic choice tasks even when the search space of possible choice tasks is very large. As proof‐of‐concept, we used this novel approach to generate respondent‐specific choice tasks with either low or high context‐based complexity that we operationalize by the similarity of alternatives and the conflict between alternatives. We find in an experiment that an increase in the similarity of the alternatives and an increase in the number of conflicts within the choice task lead to an increased use of non‐compensatory strategies and a decreased use of compensatory decision strategies. In contrast, the size of the choice tasks, measured by the number of attributes and alternatives, only weakly influences the strategy selection. Copyright © 2014 John Wiley & Sons, Ltd.     

Instrumental Bias in Motivated Reasoning: More When More Is Needed

Decision makers must often make judgments in an environment in which they have a strong motivation to reach a particular conclusion. While normative theory would indicate that they should use available information to make their most accurate judgment without being influenced by the conclusion or outcome it may imply, evidence from the social judgment literature suggests that motivation does bias the judgment process. Specifically, decision makers motivated to support a particular conclusion tend to adopt information processing strategies most likely to yield the desired conclusion. We propose and empirically demonstrate two extensions to the motivation literature. First, we argue that motivated reasoning isinstrumental,meaning motivated decision makers bias their judgments more or less as needed to support the desired conclusion, subject to “reasonableness” constraints. Second, we propose that motivated decision makers exhibitconfidence bolsteringand thereby remain at least as confident as non-motivated decision makers in their biased estimates. We illustrate that motivated subjects even report confidence in utilizing these estimates outside the original motivating context. We investigate motivational effects within a business context involving forecasting, strategic decision making, and new product introductions. We explore the impact of motivation on quantitative forecasts and estimates, rather than on social judgments and perceptions. In addition, we go a step beyond the judgment phase to demonstrate that motivation influences choice.     

The classification of children's knowledge: development on the balance-scale and inclined-plane tasks

R.S. Siegler (1981, Monographs of the Society for Research in Child Development, 46 C2, Serial No. 189) has shown that performance on several Piagetian tasks is governed by similar rule structures. The purpose of the first study was to extend his analysis to the inclined-plane task, replicate his original observations about development on the balance-scale task, and determine the consistency in children's rule usage across tasks. We found that Siegler's (1981) binary decision representations adequately characterized development on these tasks, and there was fair correspondence of rule classifications across tasks. An alternative classification procedure, used to diagnose the rules of children who failed our original classification criteria, showed that most of these children's performance patterns were very similar to Siegler's rule patterns. In the second experiment, we improved the diagnosticity of our rule-assessment protocol in light of F. Wilkening and N. H. Anderson's (1982, Psychological Bulletin, 92, 215-237) criticisms, and observed that many Rule III children's predictions were associated with those of integration rules on both tasks. Despite these methodological improvements, many children, especially 5- to 7-year-olds, evidenced use of centration and lexicographic strategies, suggesting that these classifications are not simply an artifact of problem sampling. Some of the problems associated with the classification of children's knowledge are discussed.     

Does practice in category learning increase rule use or exemplar use—or both?

Categorization research has demonstrated the use of both rules and remembered exemplars in classification, although there is disagreement over whether learners shift from one to the other or use both strategies simultaneously. Theoretical arguments can motivate predictions for both rule use and exemplar use increasing with more practice. We describe a single large experiment (n = 190) that manipulated the number of training items (category size), the number of presentations of each training item, and the similarity between the training and the transfer stimuli in order to discover when rules and exemplars are most likely to be used. Results showed that rules and exemplars both influenced classification and that exemplars were used more often with smaller categories, with more training on items, and when test items were similar to training items. There was no consistent evidence of a shift from rule-based to exemplar-based categorization with more learning. Importantly, we found a number of conditions in which rules and exemplars were both used, even within individual participants. We discuss our results in terms of hybrid models of classification.     

Description and Evaluation of a Measurement Technique for Assessment of Performing Gender

The influence of masculinity and femininity on behaviors and outcomes has been extensively studied in social science research using various measurement strategies. In the present paper, we describe and evaluate a measurement technique that uses existing survey items to capture the extent to which an individual behaves similarly to their same-gender peers. We use data from the first four waves of The National Longitudinal Study of Adolescent to Adult Health (Add Health), a nationally representative sample of adolescents (age 12–18) in the United States who were re-interviewed at ages 13–19, 18–26, and 24–32. We estimate split-half reliability and provide evidence that supports the validity of this measurement technique. We demonstrate that the resulting measure does not perform as a trait measure and is associated with involvement in violent fights, a pattern consistent with theory and empirical findings. This measurement technique represents a novel approach for gender researchers with the potential for expanding our current knowledge base.     

Cognitive niches: an ecological model of strategy selection

How do people select among different strategies to accomplish a given task? Across disciplines, the strategy selection problem represents a major challenge. We propose a quantitative model that predicts how selection emerges through the interplay among strategies, cognitive capacities, and the environment. This interplay carves out for each strategy a cognitive niche, that is, a limited number of situations in which the strategy can be applied, simplifying strategy selection. To illustrate our proposal, we consider selection in the context of 2 theories: the simple heuristics framework and the ACT-R (adaptive control of thought-rational) architecture of cognition. From the heuristics framework, we adopt the thesis that people make decisions by selecting from a repertoire of simple decision strategies that exploit regularities in the environment and draw on cognitive capacities, such as memory and time perception. ACT-R provides a quantitative theory of how these capacities adapt to the environment. In 14 simulations and 10 experiments, we consider the choice between strategies that operate on the accessibility of memories and those that depend on elaborate knowledge about the world. Based on Internet statistics, our model quantitatively predicts people's familiarity with and knowledge of real-world objects, the distributional characteristics of the associated speed of memory retrieval, and the cognitive niches of classic decision strategies, including those of the fluency, recognition, integration, lexicographic, and sequential-sampling heuristics. In doing so, the model specifies when people will be able to apply different strategies and how accurate, fast, and effortless people's decisions will be.     

More Rational or More Emotional Than Others? Lay Beliefs About Decision-Making Strategies

Research demonstrates that people utilize both reasoning and feeling in decision making and that both strategies can be advantageous. However, little is known about how people perceive their decision-making relative to others. Despite research findings and popular appeals supporting the use of affective decision processes, across a series of studies, we find that individuals believe they rely more on reasoning, and less on feelings, than others. These effects are driven by the motivation to self-enhance where, in most contexts, individuals believe the use of reasoning is superior, and self-enhancing, compared to the use of feelings. Consistent with this mechanism, beliefs that one’s decisions are more rational than others’ are as follows: (a) stronger for those who exhibit greater beliefs in the superiority of reasoning (vs. feeling), (b) attenuated when the decision context precludes motivational thinking about the self or the self is affirmed, and (c) reversed when the use of feelings is perceived as more self-enhancing. We demonstrate downstream consequences (e.g., decision delegation), rule out alternative explanations, and discuss practical implications of these lay beliefs.     

Surreal decisions

Although expected utility theory has proven a fruitful and elegant theory in the finite realm, attempts to generalize it to infinite values have resulted in many paradoxes. In this paper, we argue that the use of John Conway's surreal numbers shall provide a firm mathematical foundation for transfinite decision theory. To that end, we prove a surreal representation theorem and show that our surreal decision theory respects dominance reasoning even in the case of infinite values. We then bring our theory to bear on one of the more venerable decision problems in the literature: Pascal's Wager. Analyzing the wager showcases our theory's virtues and advantages. To that end, we analyze two objections against the wager: Mixed Strategies and Many Gods. After formulating the two objections in the framework of surreal utilities and probabilities, our theory correctly predicts that (1) the pure Pascalian strategy beats all mixed strategies, and (2) what one should do in a Pascalian decision problem depends on what one's credence function is like. Our analysis therefore suggests that although Pascal's Wager is mathematically coherent, it does not deliver what it purports to, a rationally compelling argument that people should lead a religious life regardless of how confident they are in theism and its alternatives.     

Arousal enhances herding tendencies when decision making

This research examines how arousal enhances consumer tendencies to be influenced by the majority when decision making, also known as “herding.” Physiological arousal was manipulated in three controlled experiments, using discrete choice decisions as the dependent variable. The results suggest that arousal enhances tendencies to choose more popular options and that deindividuation mediates the effect of arousal on choice. This research enriches our understanding of the theoretical relationship between arousal and consumer decision making, by suggesting that arousal increases herding. The practical relevance of our findings suggests that strategies to increase herding effects, such as “popular choice” stickers and social media metrics, may be enhanced by making the experience more arousing.     

Categorizing entities by common role

Many categories group together entities that play a common role across situations. For example, guest and host refer to complementary roles in visiting situations and, thus, are role-governed categories (A. B. Markman & Stilwell, Journal of Experiment & Theoretical Artificial Intelligence, 13, 329-358, 2001). However, categorizing an entity by role is one of many possible classification strategies. This article examines factors that promote role-governed categorization over thematic-relation-based categorization (Lin & Murphy, Journal of Experimental Psychology: General, 130, 3-28, 2001). In Experiments 1a and 1b, we demonstrate that the use of novel category labels facilitates role-governed categorization. In Experiments 2a and 2b, we demonstrate that analogical comparison facilitates role-governed categorization. In Experiments 1b and 2b, we show that these facilitatory factors induce a general sensitivity to role information, as opposed to only promoting role-governed categorization on an item-by-item basis.