Rapid decisions from experience

In many everyday decisions, people quickly integrate noisy samples of information to form a preference among alternatives that offer uncertain rewards. Here, we investigated this decision process using the Flash Gambling Task (FGT), in which participants made a series of choices between a certain payoff and an uncertain alternative that produced a normal distribution of payoffs. For each choice, participants experienced the distribution of payoffs via rapid samples updated every 50 ms. We show that people can make these rapid decisions from experience and that the decision process is consistent with a sequential sampling process. Results also reveal a dissociation between these preferential decisions and equivalent perceptual decisions where participants had to determine which alternatives contained more dots on average. To account for this dissociation, we developed a sequential sampling rank-dependent utility model, which showed that participants in the FGT attended more to larger potential payoffs than participants in the perceptual task despite being given equivalent information. We discuss the implications of these findings in terms of computational models of preferential choice and a more complete understanding of experience-based decision making.     

Dominance Measuring Method Performance under Incomplete Information about Weights

In multi‐attribute utility theory, it is often not easy to elicit precise values for the scaling weights representing the relative importance of criteria. A very widespread approach is to gather incomplete information. A recent approach for dealing with such situations is to use information about each alternative's intensity of dominance, known as dominance measuring methods. Different dominance measuring methods have been proposed, and simulation studies have been carried out to compare these methods with each other and with other approaches but only when ordinal information about weights is available. In this paper, we use Monte Carlo simulation techniques to analyse the performance of and adapt such methods to deal with weight intervals, weights fitting independent normal probability distributions or weights represented by fuzzy numbers. Moreover, dominance measuring method performance is also compared with a widely used methodology dealing with incomplete information on weights, the stochastic multicriteria acceptability analysis (SMAA). SMAA is based on exploring the weight space to describe the evaluations that would make each alternative the preferred one. Copyright © 2012 John Wiley & Sons, Ltd.     

The illusion of the framing effect in risky decision making

The present study elucidates that the illusion of framing in risky decisions is induced by the expected losses with the shift of independent or complementary schemata. Throughout three studies, the reversal of risk preferences in the gain and loss frames was confirmed when the expected number of losses was unknown. When it was known, however, the reversal was reduced in Study 2 where the decision makers were informed of all the options in both frames, and eliminated in Study 3 where they elaborated the numbers of lives at stake before making decisions. Further, the complementary schema was more pervasive when the number of expected losses was known, while the independent schema was more common when the number was unknown. These results imply that the illusion of framing is due to the shift of schemata concerning the lives saved and lost. Copyright © 2010 John Wiley & Sons, Ltd.     

Integrating Cognitive Process and Descriptive Models of Attitudes and Preferences

Discrete choice experiments—selecting the best and/or worst from a set of options—are increasingly used to provide more efficient and valid measurement of attitudes or preferences than conventional methods such as Likert scales. Discrete choice data have traditionally been analyzed with random utility models that have good measurement properties but provide limited insight into cognitive processes. We extend a well‐established cognitive model, which has successfully explained both choices and response times for simple decision tasks, to complex, multi‐attribute discrete choice data. The fits, and parameters, of the extended model for two sets of choice data (involving patient preferences for dermatology appointments, and consumer attitudes toward mobile phones) agree with those of standard choice models. The extended model also accounts for choice and response time data in a perceptual judgment task designed in a manner analogous to best–worst discrete choice experiments. We conclude that several research fields might benefit from discrete choice experiments, and that the particular accumulator‐based models of decision making used in response time research can also provide process‐level instantiations for random utility models.     

Compound invariance implies prospect theory for simple prospects

Behavioral conditions such as compound invariance for risky choice and constant decreasing relative impatience for intertemporal choice have surprising implications for the underlying decision model. They imply a multiplicative separability of outcomes and either probability or time. Hence the underlying model must be prospect theory or discounted utility on the domain of prospects with one nonzero outcome. We indicate implications for richer domains with multiple outcomes, and with both risk and time involved.     

Psychologists' perspectives on the diagnostic classification of mental disorders: Results from the WHO‐IUPsyS Global Survey

This study examined psychologists' views and practices regarding diagnostic classification systems for mental and behavioral disorders so as to inform the development of the ICD‐11 by the World Health Organization (WHO). WHO and the International Union of Psychological Science (IUPsyS) conducted a multilingual survey of 2155 psychologists from 23 countries, recruited through their national psychological associations. Sixty percent of global psychologists routinely used a formal classification system, with ICD‐10 used most frequently by 51% and DSM‐IV by 44%. Psychologists viewed informing treatment decisions and facilitating communication as the most important purposes of classification, and preferred flexible diagnostic guidelines to strict criteria. Clinicians favorably evaluated most diagnostic categories, but identified a number of problematic diagnoses. Substantial percentages reported problems with crosscultural applicability and cultural bias, especially among psychologists outside the USA and Europe. Findings underscore the priority of clinical utility and professional and cultural differences in international psychology. Implications for ICD‐11 development and dissemination are discussed.     

决策的选择偏好研究述评

决策的选择偏好具有可变性。当前主要有三类不同取向的解释。第一类观点以效用概念为核心,分别讨论了评价模式和效用折扣对选择偏好的影响。第二类观点以心理表征概念为基础,分别提出了建构水平和表征差别对选择偏好的影响。第三类观点以联结和人工神经网络概念为要素,分别探讨了心理场距离和规避损失偏向对选择偏好的影响     

两难情景下任务结构与价值取向的效用特征转换

实验采用两难对策任务的情景模拟 ,研究决策者在群体决策情景当中的效用特征转换。 6 2名被试参加了实验。研究发现 ,任务结构与个体价值取向都是影响决策效用特征转换的重要因素 ,并且这种效用特征的转换有稳定关系存在 ,以此为基础来设计组织计算机团队工作具有重要意义     

Fairness

The main body of this paper assesses a leading recent theory of fairness, a theory put forward by John Broome. I discuss Broome's theory partly because of its prominence and partly because I think it points us in the right direction, even if it takes some missteps. In the course of discussing Broome's theory, I aim to cast light on the relation of fairness to consistency, equality, impartiality, desert, rights, and agreements. Indeed, before I start assessing Broome's theory, I discuss two very popular conceptions of fairness that contrast with his. One of these very popular conceptions identifies fairness with the equal and impartial application of rules. The other identifies fairness with all-things-considered moral rightness.