Decision-makers use social information to update their preferences but choose for others as they do for themselves

People's risky decisions are susceptible to the social context in which they take place. Across three experiments using different paradigms, we investigated the influence of three social factors upon participants' decisions: the recipient of the decision-making outcome (self, other, or joint), the nature of the relationship with the other agent (friend, stranger, or teammate), and the type of information that participants received about others' preferences: none at all, general information about how previous participants had decided, or information about a specific partner's preference. We found that participants' decisions about risk did not differ according to whether the outcome at stake was their own, another agent's, or a joint outcome, nor according to the type of information available. Participants did, however, adjust their preferences for risky options in light of social information.     

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.     

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.     

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。     

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。     

健康领域的跨期决策与健康行为

健康领域的跨期决策关系着个体和国民的健康和福祉。目前学界对该领域的研究主要停留在参考传统金钱领域的相关理论模型和方法的阶段, 但健康跨期决策具有领域特异性, 沿袭金钱领域理论模型和方法, 导致该领域在研究方法和结果上存在较大的不一致性。健康跨期决策的行为后果是该领域关注重点, 多数研究均报告个体的低时间折扣率、高未来时间取向与其健康保护行为正相关, 与健康风险行为呈负相关。该领域也关注健康跨期决策的影响机制, 如决策对象和决策主体的核心特征等因素。未来研究亟需发展适用于健康领域的跨期决策模型和研究范式, 明确健康行为与跨期决策偏好的关系, 深入探讨健康跨期决策的内在选择机制, 并在健康行为干预和医疗卫生政策应用方面进行更多的尝试和探索。