Exploiting the Wisdom of Others to Make Better Decisions: Suspending Judgment Reduces Egocentrism and Increases Accuracy

Although decision makers often consult other people's opinions to improve their decisions, they fail to do so optimally. One main obstacle to incorporating others' opinions efficiently is one's own opinion. We theorize that decision makers could improve their performance by suspending their own judgment. In three studies, participants used others' opinions to estimate uncertain quantities (the caloric value of foods). In the full‐view condition, participants could form independent estimates prior to receiving others' opinions, whereas participants in the blindfold condition could not form prior opinions. We obtained an intriguing blindfold effect. In all studies, the blindfolded participants provided more accurate estimates than did the full‐view participants. Several policy‐capturing measures indicated that the advantage of the blindfolded participants was due to their unbiased weighting of others' opinions. The full‐view participants, in contrast, adhered to their prior opinion and thus failed to exploit the information contained in others' opinions. Moreover, in all three studies, the blindfolded participants were not cognizant of their advantage and expressed less confidence in their estimates than did the full‐view participants. The results are discussed in relation to theories of opinion revision and group decision making. Copyright © 2011 John Wiley & Sons, Ltd.     

When guessing what another person would say is better than giving your own opinion: Using perspective-taking to improve advice-taking

We investigated how perspective-taking might be used to overcome bias and improve advice-based judgments. Decision makers often tend to underweight the opinions of others relative to their own, and thus fail to exploit the wisdom of others. We tested the idea that decision makers taking the perspective of another person engage a less egocentric mode of processing of advisory opinions and thereby improve their accuracy. In Studies 1–2, participants gave their initial opinions and then considered a sample of advisory opinions in two conditions. In one condition (self-perspective), they were asked to give their best advice-based estimates. In the second (other-perspective), they were asked to give advice-based estimates from the perspective of another judge. The dependent variables were the participants' accuracy and indices that traced their judgment policy. In the self-perspective condition participants adhered to their initial opinions, whereas in the other-perspective condition they were far less egocentric, weighted the available opinions more equally and produced more accurate estimates. In Study 3, initial estimates were not elicited, yet the data patterns were consistent with these conclusions. All the studies suggest that switching perspectives allows decision makers to generate advice-based judgments that are superior to those they would otherwise have produced. We discuss the merits of perspective-taking as a procedure for correcting bias, suggesting that it is theoretically justifiable, practicable, and effective.     

A Fuzzy Topsis Method for Prioritized Aggregation in Multi‐Criteria Decision Making Problems

Aggregation in a decision making environment requires the fusion of opinions of a group of decision makers. The group of decision makers are required to analyse a set of interrelated criteria that are usually measured on a linguistic scale. This process requires, in many instances, to capture experts experience, intuition and thinking that are traditionally expressed in a linguistic fashion rather than a numerical fashion. Furthermore, the necessity of considering the relationship between the criteria to the overall decision must be considered by the group of decision makers. This paper extends the application of fuzzy numbers, fuzzy relative importance scores (FRIS), fuzzy relative weights (FRW) and the fuzzy technique of order preference by similarity to ideal solution (TOPSIS) in prioritized aggregation. This extension provides a mean to systematically aggregate a group of decision makers' views for a set of interrelated criteria that are measured on a linguistic scale. First, an overview of the application of fuzzy numbers and the characteristics of aggregating fuzzy numbers in multi‐criteria decision making problems are presented. Then, the application of TOPSIS in fuzzy environments is presented. Next, past research is highlighted to present prioritized aggregation and the different aggregation operators' classes. Subsequently, a new prioritized aggregation method is presented. This method utilizes fuzzy TOPSIS with prioritized aggregation in fuzzy environments. Finally, the fuzzy prioritized aggregation method presented in this paper is applied on an actual case study. According to the results, the method presented in this paper provides a systematic approach to capture the uncertainty and imprecision associated with quantifying linguistic measurements in multi‐criteria decision making problems. Furthermore, it considers the relationship between the set of linguistically measured criteria undergoing prioritized aggregation in a fuzzy environment. Lastly, findings, conclusions and future work are presented. Copyright © 2016 John Wiley & Sons, Ltd.     

Advice Taking in Decision Making: Egocentric Discounting and Reputation Formation

Our framework for understanding advice-taking in decision making rests on two theoretical concepts that motivate the studies and serve to explain the findings. The first is egocentric discounting of others' opinions and the second is reputation formation for advisors. Advice discounting is attributed to differential information, namely, the notion that decision makers have privileged access to their internal reasons for holding their own opinion, but not to the advisors' internal reasons. Reputation formation is related to the negativity effect in impression formation and to the trust asymmetry principle. In three studies we measured decision makers' weighting policy for advice and, in a fourth study, their willingness to pay for it. Briefly, we found that advice is discounted relative to one's own opinion, while advisors' reputations are rapidly formed and asymmetrically revised. The asymmetry implies that it may be easier for advisors to lose a good reputation than to gain one. The cognitive and social origins of these phenomena are considered.     

Linguistic–Numeric Presentation Mode Effects on Risky Option Preferences

In this study, we examine preferences between lotteries with chances presented either numerically or linguistically. Presentation mode is predicted to affect preferences due to the perception of linguistic chance as skewed distributions of risk. Based upon weighting functions incorporating risk/uncertainty aversion from ambiguity theory and cumulative prospect theory, we predict that presentation mode effects on risky choices will be detectable in very small risks and in large risks. In two experiments, subjects chose between both gain and loss lotteries with constant payoffs and equivalent numeric and linguistic chances. Presentation mode affected choices when chances were above 50%, where lotteries with numeric chances were more frequently preferred in gains while lotteries with linguistic chances were more often preferred in losses. The effect of presentation mode for low-chance lotteries (5% and less) also affected choices such that numeric choices were generally preferred more frequently in losses and linguistically expressed choices were generally preferred more often in gains. Overall, these results suggest that theories of the effects of second order uncertainty on risky choice may be used to model decisions involving linguistic risk. They also suggest that the study of the perception of linguistic risk assessments can provide insight into the cognitive processing behind the weighting functions proposed to depict decision under risk and uncertainty. Finally, the results have practical implications since information providers can affect decision makers’ choices by controlling presentation mode in such a way as to alter the relative attractiveness of uncertain events.     

Aggregation of opinions based on correlated cues and advisors

We study the process by which decision makers (DMs) aggregate probabilistic opinions from multiple, correlated sources with a special emphasis on the determinants of the DM's confidence, which is a predictor of the DM's willingness to accept the implications of the aggregation process. Our model assumes that (a) DM combines the advisors' opinions by weighting them according to the amount of information underlying them, and (b) the DM's confidence increases as a function of a variety of factors that reduce the variance of the aggregate. We report results of three studies that manipulate the predictive validity of the cues and their inter‐correlations. Most of the models' predictions are supported but, contrary to the model's prediction, the DMs' confidence is not sensitive to the inter‐cue correlation. The best predictors of the DMs' confidence are the perceived predictability of the event, the level of agreement among the advisors, and the advisors' self‐reports of confidence. This pattern of results is explained by the ‘system neglect’ hypothesis. Copyright © 2006 John Wiley & Sons, Ltd.     

Contingent Weighting in Self-Other Decision Making

Three studies are presented that examine the decision-making processes that lead advisors to have preferences distinct from personal decision makers (Kray & Gonzalez, 1999). Advising and personal decision making were hypothesized to invoke different interpersonal frames, which lead to different weighting of decision attributes. Alternatively, advisors might simply exert less effort in decision making for others than do personal decision makers. In Study 1, the contingent weighting of attributes was examined in two decision-making tasks (choice vs. matching). Advisors were more likely to choose in a manner consistent with "what most people would prefer" than personal decision makers, but no differences in preferences were observed in the matching task. Advisors subsequently reported experiencing less regret and blame and more strongly preferred the chosen alternative than did personal decision makers. In Study 2, advisors considered more decision attributes to be important in the abstract compared to personal decision makers, and the choice pattern of Study 1 was replicated. In Study 3, advisors and personal decision makers generated more considerations when making a decision compared to individuals making decisions in the abstract. Finally, the preferences of personal decision makers were more consistent with their reported attribute importance judgments than were those of advisors. In total, the results suggest advisors incorrectly infer others' preferences, rather than suffer from a deficit of motivation, when giving advice. Copyright 2000 Academic Press.     

Analytic Confidence and Political Decision‐Making: Theoretical Principles and Experimental Evidence From National Security Professionals

When making decisions under uncertainty, it is important to distinguish between the probability that a judgment is true and the confidence analysts possess in drawing their conclusions. Yet analysts and decision‐makers often struggle to define “confidence” in this context, and many ways that scholars use this term do not necessarily facilitate decision‐making under uncertainty. To help resolve this confusion, we argue for disaggregating analytic confidence along three dimensions: reliability of available evidence, range of reasonable opinion, and responsiveness to new information. After explaining how these attributes hold different implications for decision‐making in principle, we present survey experiments examining how analysts and decision‐makers employ these ideas in practice. Our first experiment found that each conception of confidence distinctively influenced national security professionals' evaluations of high‐stakes decisions. Our second experiment showed that inexperienced assessors of uncertainty could consistently discriminate among our conceptions of confidence when making political forecasts. We focus on national security, where debates about defining “confidence levels” have clear practical implications. But our theoretical framework generalizes to nearly any area of political decision‐making, and our empirical results provide encouraging evidence that analysts and decision‐makers can grasp these abstract elements of uncertainty.     

Optimal cue aggregation in the absence of criterion knowledge

The study of multi‐cue judgment investigates how decision makers aggregate cues to predict the value of a criterion variable. We consider a multi‐cue judgment task in which decision makers have prior knowledge of inter‐cue relationships but are ignorant of how the cues correlate with the criterion. In this setting, a naive judgment strategy prescribes weighting the cues equally. Although many participants are well described via an equal weighting scheme, we find that a substantial minority of participants make predictions consistent with a weighting scheme based on a low‐dimensional projection of the cue space that optimally takes into account inter‐cue correlations. The use of such a weighting scheme is consistent with minimizing maximal error in prediction when the cue‐criterion relationships are unknown.     

The general model and the particular decision: decision makers' awareness of their cue weightings

This paper examines the accuracy with which decision makers can predict the effects of the characteristics of a research study on their evaluations of its usefulness to their work. It draws on survey data from a sample of 155 decision makers in mental health: each of them predicted the effects of 26 research characteristics on usefulness and rated each of two research studies on usefulness and the extent to which each characteristic described the study. The principal finding is that decision makers' predictions of the effects of characteristics on usefulness correspond much more closely to the effects actually observed when these effects are calculated across individuals than when they are taken for a single individual rating one (or two) studies. After examining several alternative explanations, it is suggested that an individual decision maker uses multiple evaluation functions to judge research, weighting the characteristics differently in each, and that investigators should consider the possibility of such variation whenever they attempt to model individuals' evaluation functions.     

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.     

On the shape of the probability weighting function

Empirical studies have shown that decision makers do not usually treat probabilities linearly. Instead, people tend to overweight small probabilities and underweight large probabilities. One way to model such distortions in decision making under risk is through a probability weighting function. We present a nonparametric estimation procedure for assessing the probability weighting function and value function at the level of the individual subject. The evidence in the domain of gains supports a two-parameter weighting function, where each parameter is given a psychological interpretation: one parameter measures how the decision maker discriminates probabilities, and the other parameter measures how attractive the decision maker views gambling. These findings are consistent with a growing body of empirical and theoretical work attempting to establish a psychological rationale for the probability weighting function.     

Reliance on Numerical Precision: Compatibility between Accuracy versus Efficiency Goals and Numerical Precision Level Influence Attribute Weighting in Two‐Stage Decisions

This research examines how the weighting of an attribute is jointly affected by attribute precision and decision stage. Building on prior work suggesting (a) that less (more) precise numerical values are easier to process (more accurate), (b) that decision‐makers' motivation to be efficient (accurate) is greater when creating a consideration set (making a final choice), and (c) that decision‐makers tend to overweight information that is compatible with their goals, we hypothesize that when creating a consideration set (making a choice) participants tend to assign greater weight to less (more) precise attributes. Five studies (two of them reported in the Appendix S1) offer triangulating evidence for these predictions. Overall, this work contributes to research on numerical cognition, efficiency versus accuracy trade‐offs, attribute weighting, and two‐stage decisions.     

Uncertainty forecasts improve weather-related decisions and attenuate the effects of forecast error

Although uncertainty is inherent in weather forecasts, explicit numeric uncertainty estimates are rarely included in public forecasts for fear that they will be misunderstood. Of particular concern are situations in which precautionary action is required at low probabilities, often the case with severe events. At present, a categorical weather warning system is used. The work reported here tested the relative benefits of several forecast formats, comparing decisions made with and without uncertainty forecasts. In three experiments, participants assumed the role of a manager of a road maintenance company in charge of deciding whether to pay to salt the roads and avoid a potential penalty associated with icy conditions. Participants used overnight low temperature forecasts accompanied in some conditions by uncertainty estimates and in others by decision advice comparable to categorical warnings. Results suggested that uncertainty information improved decision quality overall and increased trust in the forecast. Participants with uncertainty forecasts took appropriate precautionary action and withheld unnecessary action more often than did participants using deterministic forecasts. When error in the forecast increased, participants with conventional forecasts were reluctant to act. However, this effect was attenuated by uncertainty forecasts. Providing categorical decision advice alone did not improve decisions. However, combining decision advice with uncertainty estimates resulted in the best performance overall. The results reported here have important implications for the development of forecast formats to increase compliance with severe weather warnings as well as other domains in which one must act in the face of uncertainty.     

Social Judgement Theory and Medical Judgement

Social judgement theory is particularly well suited to the study of medical judgements. Medical judgements characteristically involve decision making under uncertainty with inevitable error and an abundance of fallible cues. In medicine, as in other areas, SJT research has found wide variation among decision makers in their judgements and in the weighting of clinical information. Strategies inferred from case vignettes differ from physicians' self-described strategies and from the weights suggested by experts. These observations parallel recent findings of unexplained variation in diagnosis and management in clinical practice that have been the source of concern in the medical community. The lens model provides one of the few methods for quantitatively analysing physicians' judgements. Contrary to what one might expect from the variation in strategies on paper cases, several studies suggest that, in practice, physicians' diagnostic judgements are highly accurate. Cognitive feedback has been less successful as a practical teaching tool than originally hoped, but some aspects of this methodology show promise, particularly in conjunction with the increasing emphasis on statistical decision support. All things considered, SJT has provided insight into physicians' decisions and gives the medical research community important tools for studying judgements in actual practice.     

A new fuzzy multicriteria evaluation method for group site selection in GIS

Multiple criteria group site selection problems involve a group of individuals evaluating a set of alternative sites on the basis of multiple criteria. This paper presents an application of a new fuzzy algorithm for finding and exploring potential solutions to these problems in a raster Geographical Information System (GIS) environment. Linguistic assessments from decision‐makers are represented as triangular fuzzy numbers (TFN's), which are adjusted for uncertainty in the source data and their relationship to suitability by using an approach based on type‐2 fuzzy sets. The first aggregation of inputs is a compensatory one based on fuzzy multiattribute decision‐making (MADM) theory. An adjusted aggregation then factors in conflicts, risks and uncertainties to enable a variety of compensatory and non‐compensatory outcomes to be generated based on decision‐maker preferences. The algorithm was implemented in ArcView GIS as part of an ongoing collaborative project with Brisbane Airport. This paper outlines the fuzzy algorithm and its use in site selection for a recycling facility on the Brisbane Airport site. Copyright © 2005 John Wiley & Sons, Ltd.     

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.     

Consequences of Regret Aversion 2: Additional Evidence for Effects of Feedback on Decision Making

We discuss the effects of anticipated and experienced regret on decision making under uncertainty. In previous research, using the standard, context-free, gamble paradigm, we found that decision makers anticipate the regret they can experience as a result of post-decisional feedback on forgone outcomes (Zeelenberg, Beattie, van der Pligt, & de Vries, 1996). In the present research we move away from the gamble paradigm, on to richer contexts. In Experiments 1 and 2, involving investment decision making and decision making in the ultimatum game, it is shown that the expectation of feedback on forgone outcomes influences decision making and can promote more risk seeking behavior. Experiment 3 focused on effects of retrospective regret and shows that actual feedback on foregone outcomes influences the experience of regret and subsequent decision making. The results of these studies support our earlier work on regret aversion.