前瞻性情绪作为社会风险的信息源假说：公共场景下风险决策的情绪及文化机制探讨

本研究从梳理决策的情绪理论入手, 在综合几种主要理论的基础上提出了“前瞻性情绪作为社会风险信息源”的假说。前瞻性情绪是在决策过程中产生的, 由于对决策选择的预期而感受到的, 进而影响决策行为的情绪。社会环境下的风险事件具有突发和稍纵即逝的特征, 如果一个公民对这类风险事件做出反应, 其结果的概率难于量化。在这种情况下, 前瞻性情绪能够为决策者快速提供有关信息, 并形成对决策预期结果严重性和可能性的综合表征, 从而成为公众场景下风险决策的有效线索。不同前瞻性情绪的组合在面对社会性风险事件时具有针对性的作用。近年来在文化比较中对于面子、荣誉和尊严文化的划分, 也为我们研究文化的情绪特征和行为效应提供了理论框架。本研究拟通过四项研究和多个实验探讨前瞻性情绪如何影响公众场景下人们的风险应对行为, 并对三种文化的情绪特征进行比较, 探索情绪性决策中个人因素、群体因素、及文化因素如何共同决定公共场景下风险决策(如亲社会行为或反社会行为)的发生与发展, 同时也期望为公共政策的制定及风险管理提供科学依据。     

从对框架效应的分析看风险决策的神经基础

对风险决策的研究近年来一直是微观经济学和心理学的热门,但是从传统的决策理论到主张有限理性的预期理论大多是对决策行为的研究,决策的心理机制一直是无法解释的黑箱子。令人兴奋的是近几年来神经科学家及其他领域的学者开始用先进的神经心理学的方法来研究风险决策,试图理解神经过程调节风险决策行为的方式。文章从分析违背“不变性”原则的框架效应入手,从正反框架、确定选择和风险选择、风险规避和风险寻求、高估小概率事件几个方面,全面分析风险决策可能的神经基础。在总结已有研究的基础上提出了把风险决策研究扩展到不确定决策,把风险决策中的一次决策研究扩展到多次决策的研究思路     

概率估计的趋势效应及其对决策的影响机制——基于心理动量的视角

概率是反映风险与不确定性的重要指标, 概率估计具有趋势效应, 会对决策产生影响。文章描述了概率估计趋势效应的两种表现形式, 概率估计变化的趋势性(即不同时间点概率估计变化产生的趋势作用)与单边概率估计的趋势性(即高于或低于某个概率区间范畴的上界或下界的估计表述所产生的趋势作用), 揭示了概率估计趋势效应对于个体判断、决策行为和非理性决策偏差的影响; 基于心理动量的理论视角提出了一个整合模型, 阐述了概率估计趋势效应催生心理动量体验继而引发后续决策行为的内在机理。未来的研究可进一步关注：多方信息来源主体下概率估计的趋势效应; 动态趋势效应与静态概率估计的交互作用; 风险沟通中的概率估计变化趋势。     

行为决策研究的新取向——基于经验的决策

基于经验的决策是指,在统计概率情境中,个体通过重复选择与反馈获得选项的收益分布信息后进行的决策.基于经验的决策的研究范式主要包括探索-利用范式和探索→利用范式.其暗含的决策人假设是朴素直觉统计学家.其研究关注的主要内容是描述-经验的差异及其原因,以及基于经验的决策内部过程.未来的研究主要从描述-经验差异的原因、描述性决策范式下的结论的重新检验、基于经验的决策的解释模型及其应用研究等方面进行探讨.     

用文字概率衡量不确定性：特征和问题

文字概率是衡量不确定性的方式之一, 即人们使用诸如“也许”、“未必”的词汇来描述特定事件发生的可能性。文字概率不同于数字概率, 主要体现在文字概率的模糊性、非概率运算性和语义特性上。这使得相对于数字概率, 用文字概率衡量不确定性既有优势也有问题, 进而对人们的不确定信息沟通和风险决策造成影响。虽然文字概率与数字概率存在特征上的差异并且人们在日常交流中偏爱文字概率, 但是大部分风险领域的研究却仅局限于数字概率, 今后有必要研究使用文字概率测量的风险决策。在已有文字概率特征研究的基础上, 还可以进一步探究其不同于数字概率的其它特征(文字/数字概率与双系统模型的联系、文字概率的跨文化差异等)及其对风险决策的影响。     

风险偏好、信息完整性对职业决策信息加工的影响

本研究旨在探讨个体风险偏好如何影响信息加工过程;同时呈现信息的完整性是否影响个体信息加工过程。以31名正在求职的大学生为被试,探讨了他们在信息板上进行职业决策的信息加工过程。结果显示：(1) 低风险偏好者比高风险偏好者更关注与概率相关的线索;(2) 当信息不完整时,个体在决策中增加了对概率相关线索的关注;(3) 信息完整性对个体决策信息加工过程并未产生显著的影响。     

信息外部表征形式对初中生学习决策框架效应的影响

333名初中生被分配到基于描述表征的两种条件下,分别对获得框架与损失框架下的风险回避类与风险寻求类学习时间选项进行抉择,以探讨信息外部表征对学习决策框架效应的影响.结果表明:1)在基于描述表征的条件下,学习决策领域中存在框架效应,但有其领域特殊性,被试在获得框架中无明显决策偏向,但在损失框架中的决策明显偏向风险寻求.2)在基于经验表征的条件下,学习决策不存在框架效应.无论是在获得框架还是损失框架中的学习决策均不存在明显的偏向.     

描述信息与经验不一致对个体风险选择的影响：决策模型的拟合

采用描述−经验冲突范式,考察损益情境下,描述信息与经验不一致对个体风险选择的影响,通过模型拟合探究其内在机制。研究1a和研究1b采用单因素被试间设计,自变量为描述信息与经验不一致程度,因变量为风险选项选择率。结果发现,获益情境中,描述信息与经验不一致程度的主效应不显著;而损失情境中,风险选项选择率受到显著影响。研究2比较决策模型参数发现,获益情境中,描述信息权重参数ξ和选择一致性参数c显著小于损失情境,而近因参数φ显著大于损失情境。这表明,当描述信息与经验不一致时,相对于获益情境,损失情境下个体更大程度地采用描述信息进行决策。研究揭示了损益情境中描述信息与经验不一致影响个体风险选择的机制。     

心理距离、封面故事对框架效应的影响

该研究旨在比较志愿决策和“亚洲疾病”决策两种任务领域下,人们风险偏好的特征情况,以考察远、近不同社会距离对风险偏好的影响.同时,在传统的坏封面故事下,增设好封面故事情景,以期发现封面故事作为决策前的必要背景信息对人们决策的影响.选取高中生为被试,结果发现：（1）在近的社会距离下决策时,风险偏好受到时间距离、封面故事、概率和框架的影响;在远的社会距离下,这些因素的影响作用不大;（2）志愿决策中,风险偏好仅在小概率条件下,受封面故事、框架等因素的影响;在好封面故事下,风险偏好受到框架的影响;在坏的封面故事下,风险偏好受时间距离和框架的交互作用影响.     

行为决策中的比率偏差

比率偏差是指小概率事件以不同比率形式呈现时,人们倾向于认为以较小数字呈现的事件更不可能发生.这种现象在医疗卫生领域和职业生涯决策中有重要的应用价值.目前关于比率偏差产生的解释主要包括标准理论与认知经验自我理论.比率偏差的影响因素主要包括元认知技能、计算能力、认知视角和任务性质等.未来的研究需要从比率偏差现象的产生、心理机制及应用方面进行深入研究.     

The gap between medical and monetary choices under risk persists in decisions for others

Decisions under risk in the medical domain have been found to systematically diverge from decisions in the monetary domain. When making choices between monetary options, people commonly rely on a decision strategy that trades off outcomes with their probabilities; when making choices between medical options, people tend to neglect probability information. In two experimental studies, we tested to what extent differences between medical and monetary decisions also emerge when the decision outcomes affect another person. Using a risky choice paradigm for medical and monetary decisions, we compared hypothetical decisions that participants made for themselves to decisions for a socially distant other (Study 1) and to recommendations as financial advisor or doctor (Study 2). In addition, we examined people's information search in a condition in which information about payoff distributions had to be learned from experiential sampling. Formal modeling and analyses of search behavior revealed a similarly pronounced gap between medical and monetary decisions in decisions for others as in decisions for oneself. Our results suggest that when making medical decisions, people try to avoid the worst outcome while neglecting its probability—even when the outcomes affect others rather than themselves.     

Extreme Outcomes Sway Risky Decisions from Experience

Whether buying stocks or playing the slots, people making real‐world risky decisions often rely on their experiences with the risks and rewards. These decisions, however, do not occur in isolation but are embedded in a rich context of other decisions, outcomes, and experiences. In this paper, we systematically evaluate how the local context of other rewarding outcomes alters risk preferences. Through a series of four experiments on decisions from experience, we provide evidence for an extreme‐outcome rule, whereby people overweight the most extreme outcomes (highest and lowest) in a given context. As a result, people should be more risk seeking for gains than losses, even with equally likely outcomes. Across the experiments, the decision context was varied so that the same outcomes served as the high extreme, low extreme, or neither. As predicted, people were more risk seeking for relative gains, but only when the risky option potentially led to the high‐extreme outcome. Similarly, people were more risk averse for relative losses, but only when the risky option potentially led to the low‐extreme outcome. We conclude that in risky decisions from experience, the biggest wins and the biggest losses seem to matter more than they should. Copyright © 2013 John Wiley & Sons, Ltd.     

Maximizing Scales Do Not Reliably Predict Maximizing Behavior in Decisions from Experience

In this paper, we explore the relationships between psychometric and behavioral measures of maximization in decisions from experience (DfE). In two experiments, we measured choice behavior in two experimental paradigms of DfE and self‐reported maximizing tendencies using three prominent scales of maximization. In the repeated consequentialist choice paradigm, participants made repeated choices between two unlabeled options and received consequential feedback on each trial. In the sampling paradigm, participants freely sampled from two options and received feedback on their sampling before making a single consequential choice. Individuals exhibited different degrees of maximizing behavior in both paradigms and across different payoff distributions, but none of the maximizing scales predicted this behavior. These results indicate that maximization scales address constructs that are different from the maximization behavior observed in DfE, and that these measures will need to be improved to reflect behavioral aspects of choice and search from experience. Copyright © 2017 John Wiley & Sons, Ltd.     

The decision to check in multialternative choices and limited sensitivity to default

Given the rapid proliferation of smartphone applications and data aggregation websites, in many situations people can use decision aids to guide their choices. For example, they may consider whether to use a navigation device to check the fastest route or whether to use a price comparison website to find the cheapest deal. In what circumstances will subjects use a costly comparison decision aid (which I refer to as “checking”) to choose for them? In six studies, I investigate the impact of the number of available alternatives and checking's attractiveness on the decision to check. While at first increasing the attractiveness of checking led to higher checking rates, a further increase in the number of available alternatives (and thus checking's attractiveness) did not increase the checking rate. Surprisingly, even when checking had a 40% higher expected value compared with not checking, the observed checking rate was below 45%, contrary to risk and ambiguity aversion predictions. Furthermore, labeling the checking alternative as the default had no impact on its choice rate. I find large individual differences in decisions to check. Surprisingly, subjects' initial decisions had high predictive power over their subsequent checking rates, even after 100 trials with full feedback. I propose two simple learning models that capture well the aggregated results.