The influence of biased exposure to forgone outcomes

After making decisions, we often get feedback concerning forgone outcomes (what would have happened had we chosen differently). Yet, many times, our exposure to such feedback is systematically biased. For example, your friends are more likely to tell you about a party you missed if it was fun than if it was boring. Despite its prevalence, the effects of biased exposure to forgone outcomes on future choice have not been directly studied. In three studies (five experiments) using a simplified learning task, we study the basic influence of biased exposure to forgone outcomes in the extreme case in which decision makers can easily infer the missing information such that the biased exposure carries almost no informational value. The results in all studies suggest that nevertheless, the biased exposure to forgone outcomes affected choice. Exposure to forgone outcomes only when they were better than the obtained outcomes (Only-Better-Forgone) increased selections of the forgone option compared with exposure to forgone outcomes only when they were worse than the obtained outcome (Only-Worse-Forgone). Moreover, relative to an unbiased exposure to all forgone outcomes, the effect of exposure to Only-Worse-Forgone was larger than the effect of exposure to Only-Better-Forgone feedback. However, these effects were not universal: In environments that include rare negative events (“disasters”), biased exposure to forgone outcomes had very little effect. We raise potential explanations and further discuss implications for marketing and risk awareness.     

The association between risky decision making and attention-deficit/hyperactivity disorder symptoms: A preregistered assessment of need for cognition as underlying mechanism

Attention-Deficit/Hyperactivity Disorder (ADHD) is related to suboptimal decision making in experimental tasks and to real-life risk-taking behavior (RTB) such as substance abuse and unsafe traffic conduct. In this preregistered study, we tested whether these associations are mediated by need for cognition—the extent to which one tends towards, and enjoys, analytical thought. In a large sample of young adults (N = 463, M_age = 19.7 years), we tested whether need for cognition mediated the association between self-reported ADHD symptoms on the one hand and decision-making strategy complexity on an experimental gambling task and self-reported real-life RTB on the other hand. Preregistered confirmatory analyses indicated first that ADHD symptoms were positively associated with real-life RTB, but the association was not mediated by need for cognition. Second, ADHD symptoms were not related to decision-making strategy complexity, and need for cognition was not a significant mediator. Explorative analyses revealed that (a) need for cognition was associated with higher decision-making accuracy and slower reaction time; (b) need for cognition was related to inattentive but not to hyperactive/impulsive ADHD symptoms; (c) need for cognition was associated with health-related RTB but not interpersonal RTB; and (4) only the association between inattention and health-related RTB was mediated by need for cognition. We conclude that need for cognition is not a mediator in the association between ADHD symptoms and RTB. Additionally, we conclude that neither ADHD symptoms nor need for cognition predict decision-making strategy complexity. Implications for both future research and clinical practice are discussed.     

Adding versus averaging: Evaluability theory applied to job choice decisions

While the unique roles of individual job attributes (e.g., salary and benefits) in job and organizational attraction have received extensive research attention, research examining the mechanisms through which an overall evaluation of a job option is made by combining evaluations of individual attributes is scarce. The current study examined the process through which job choice decisions are made under three conditions: when evaluating a single job offer, when comparing two job offers, and when evaluating more than two job offers. In Study 1, it was found that when a single job offer is evaluated, the average of perceived values of attributes in an offer (e.g., the perceived attractiveness of a salary) drives the choice, whereas the difference between jobs is what matters when two jobs are evaluated simultaneously, potentially leading to a preference reversal between conditions when the same two jobs are evaluated. In Study 2, it was found that average values of attributes across options (e.g., average salary in all job offers received) influence job choice when more than two job offers are evaluated simultaneously. These findings indicate that in all three conditions, job choice decisions are influenced by the evaluability of the choice set, which becomes low when a single job offer is evaluated without any context, or when more than two job offers are evaluated simultaneously, and becomes high when two jobs are compared with each other. When evaluability is low, candidates resort to averaging as the decision rule, whereas adding is used when evaluability is high.     

Providing more or less detailed information in job advertisements—Does it matter?

Job advertising is a common and useful recruitment marketing method that is available to a wide range of candidates and offers a practical way to widen the applicant pool. Frequently, retail advertisements only briefly introduce job requirements, but others provide more detailed information. Existing message studies, however, are inconclusive about the effectiveness of message specificity. A scenario‐based experiment that included 164 participants revealed that the type of decision maker (maximizer or satisficer) moderates the specificity effects in recruitment messages. After receiving a detailed job message, more satisficers stop their search process, but only maximizers perceive the company as more attractive and increase intentions toward the advertised job. A follow‐up qualitative study involving 30 participants provided further insights.     

Moderating Loss Aversion: Loss Aversion Has Moderators,But Reports of its Death are Greatly Exaggerated

Loss aversion, the principle that losses impact decision making more than equivalent gains, is a fundamental idea in consumer behavior and decision making, though its existence has recently been called into question. Across five unique samples (N_total = 17,720), we tested several moderators of loss aversion, which supported a preference construction account. Across studies, more domain knowledge and experience were associated with lower loss aversion, though people of all knowledge and experience levels were loss averse. Among car buyers, those who knew more about a particular car attribute (e.g., fuel economy) were less loss averse for that attribute but not other attributes (e.g., comfort), consistent with the idea that people with less attribute knowledge are more likely to construct preferences, thereby increasing loss aversion. Additionally, older consumers were more loss averse across different loss aversion measures and studies. We discuss implications for several accounts of loss aversion, including accounts rooted in status quo bias, emotion, or ownership. In addition to discovering loss aversion moderators, we cast doubt on recent claims that loss aversion is a fallacy or is fully explained by status quo bias, risk aversion, or the educated laboratory samples often used to study loss aversion.     

元认知中自信心对联合决策的预测作用

元认知通常指个体对自身认知活动的主观判断, 自信心作为其指标之一, 对个体认识和调节自己的行为有重要作用。研究表明自信心指标在联合研究过程中常见的任务类型涉及基础和高级心理加工过程, 此外, 自信心对联合决策的预测逐渐向基于计算模型的探索性参数变化。最后, 自信心的神经生理研究发现了前额叶皮层及其相关脑区和后顶叶皮层的重要性。今后应注重探索可能的预测参数和模型, 优化自信心对联合决策的预测作用。     

睡眠剥夺对风险决策的影响机制探讨

许多行业的决策者必须在睡眠不足的状态下做出选择与判断。睡眠剥夺是睡眠不足的实验室模型, 被证明能显著影响风险决策, 但内在机制不明。基于前人研究基础提出假设模型, 即睡眠剥夺通过影响个体的反馈加工、风险感知、抑制控制、决策理性, 进而影响风险决策。拟通过实验室研究与现场研究, 采用简单赌博任务、概率折扣任务、双选择Oddball任务等研究范式, 对比睡眠剥夺前后被试在执行上述实验任务时的行为差异, 同时比较执行控制网络、奖赏网络等脑功能网络连接强度, 以及任务诱发的FRN等脑电成分在睡眠剥夺前后的变化, 进而论证上述反应被试反馈加工等心理过程的行为-脑电-脑成像指标的变化与睡眠剥夺后被试风险决策变化的关系。研究结果将科学地解释睡眠剥夺影响风险决策的内在机制, 为进一步探讨如何规避睡眠不足导致的决策失误提供理论与实证依据。     

Information Processing and Decision-Making in Pathological Worriers and their Potential Role in Mechanisms of Generalized Anxiety Disorder

Systematic information processing and decision-making under uncertainty are key constructs of new conceptions explaining the severity of pathological worry. The current study attempted to analyze their usefulness in subclinical and clinical groups. In the first phase of the study (N = 251) participants were examined with the Penn State Worry Questionnaire (PSWQ), a GP consultationrelated survey, and a screening survey for generalized anxiety disorder (GAD). In the second phase (N = 220), the State-Trait Anxiety Inventory, the PSWQ, and tasks measuring systematic information processing (SIP) versus heuristic reasoning (HR) were applied. In the third phase (N = 60), GAD (n = 30) and healthy control (n = 30) groups were examined with the above methods and the Iowa Gambling Task (IGT). In the low risk group, a relationship between mood and the representativeness heuristic (ρ = 0.50), as well as anchoring and adjustment heuristic (anxiety-related stimuli) was found (ρ = −0.53). In the GAD group, significant correlations between the PSWQ score, the IGT loss avoidance score (ρ = 0.40), and total IGT score (ρ = 0.48) were found. The results did not confirm a particular usefulness of the systematic/heuristic information processing construct in subclinical and clinical groups. Theory-consistent results were rather found in the nonclinical groups. Nevertheless, the data revealed some interesting findings supporting potential explanatory power of some theoretical models.     

How do investors make predictions? Insights from analogical reasoning research

Previous work on investor decision making has focused almost exclusively on information specific to the company being judged. Consequently, every decision is viewed as a novel event, disconnected from the investor's existing knowledge. In this study, the analogical reasoning literature provides the theoretical support for arguing that investors frequently utilize existing knowledge as a basis for generating predictions about a company's future. The specific proposal is that investors transfer their existing knowledge via two different forms of analogical reasoning. The first, relational reasoning, is based primarily on structural correspondence between a novel company and an existing schema. The second, literal similarity reasoning, is based primarily on surface correspondence of a novel company and a previously encountered company. Our theoretical framework is tested in a study in which experienced investors predict the outcome of a novel company's strategy after reading about the experiences of other companies who implemented a similar strategy. The results are consistent with the occurrence of both relational and literal similarity reasoning, with relational reasoning emerging as the dominant approach to generating investors' predictions. Copyright © 2000 John Wiley & Sons, Ltd.