个体采纳与群体采纳：决策过程中的两类建议采纳行为

决策者借助外界的建议通常能够获得更好的决策结果, 但是个体和群体对待建议的态度和行为却不尽相同。基于已有研究, 阐述了个体和群体在建议采纳过程中的特点并分析了造成二者差异的因素, 主要包括二者在面对决策任务和外界建议时的不同表现。此外, 根据群体动力理论, 未来研究可以从群体的动力源因素(凝聚力, 驱动力, 耗散力)来解释和预测群体的建议采纳及其与个体建议采纳的差异, 以期为不同决策情景下决策人员的合理安排和配置提供参考。     

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。     

自我—他人危机决策信息加工过程的差异:来自眼动的证据

本研究采用iView X-RED眼动仪,分两个实验来考察自我-他人危机决策的信息加工过程的差异。实验一采用单因素实验设计探讨自我-他人危机决策的信息加工过程,结果表明：为自我决策组的平均阅读时间、平均注视时间、平均注视次数、平均凝视时间、平均回视次数都显著高于为他人决策组。实验二采用2（任务框架：积极,消极）x2（决策者角色：为自我、为他人）混合实验设计,结果表明：在积极框架下,为自我决策组平均阅读时间、平均注视时间、平均注视次数、平均凝视时间、平均回视次数显著高于为他人决策组;在消极框架下,两个组没有显著差异。总体表现为,自我-他人危机决策的信息加工过程存在差异,且受任务框架的影响。     

Guiding Decision Makers' Eye Movements with (Un)Predictable Object Locations

We propose a new approach for guiding eye movements by controlling the predictability of object locations. We hypothesize that when a high (low) relevance object has a predictable location, observers are more (less) likely to fixate it compared with objects in unpredictable locations. We tested this hypothesis in three decision‐making studies, manipulating the location of a product label in an unpredictable, a predictable, and a mixed visual environment. In Study 1 and Study 2, we find that participants are less likely to fixate a low and medium relevance label in a predictable location, and in Study 3, we find that participants are more likely to fixate a high relevance label in a predictable location. Our findings suggest that predictable locations increase while unpredictable locations decrease top‐down control. The approach can be used to increase or decrease eye movements towards specific information depending on the goals of the choice architect. Copyright © 2017 John Wiley & Sons, Ltd.     

Using Statistical Models of Morphology in the Search for Optimal Units of Representation in the Human Mental Lexicon

Determining optimal units of representing morphologically complex words in the mental lexicon is a central question in psycholinguistics. Here, we utilize advances in computational sciences to study human morphological processing using statistical models of morphology, particularly the unsupervised Morfessor model that works on the principle of optimization. The aim was to see what kind of model structure corresponds best to human word recognition costs for multimorphemic Finnish nouns: a model incorporating units resembling linguistically defined morphemes, a whole‐word model, or a model that seeks for an optimal balance between these two extremes. Our results showed that human word recognition was predicted best by a combination of two models: a model that decomposes words at some morpheme boundaries while keeping others unsegmented and a whole‐word model. The results support dual‐route models that assume that both decomposed and full‐form representations are utilized to optimally process complex words within the mental lexicon.     

A model‐based process to improve robustness in Multicriteria Decision Aiding interventions

A model‐based process is a methodological approach that facilitates interventions in new and ill or not structured problem situations. It is oriented towards improving the robustness of the intervention and its results in an incremental definition of both the problem formulation and the model, in order to reduce the uncertainty that is not only associated with the model parameters but also with the model structure, and sometimes also with the problem formulation. The nature and results of this approach, which consider the interaction between an analyst and the actors of the decision system as the decision aiding core, are proposed in relation to some actual interventions.     

On the advancement and software support of decision‐making in focused ultrasound therapy

Focused ultrasound therapy (FUS) is a modern and promising way for minimally invasive cancer treatment. Recent advances in treatment technology, bio‐physical models, and numerical simulation methods have given rise to a significant curative potential. However, clinical routine of FUS still features classical planning approaches, which widely fail in exploiting this potential. The structure of FUS planning problems strongly suggests interactive multi‐criteria decision‐making concepts in order to improve treatment quality. This research work introduces an multi‐criteria decision‐making approach to FUS planning and explains how to bridge the conceptual gap between the clinical state of the art and this new planning paradigm.     

Attribute Partitioning in Multiple Attribute Decision Making Problems for a Decision with a Purpose – a Fuzzy Approach

This work introduces a methodology to find solutions corresponding to different purposes in a multiple attribute decision‐making problem under fuzzy environment. The discernment of purpose‐based solutions becomes important when the problem is defined vaguely and solution is targeted to heterogeneous population. Depending on the purpose, for which the solution is sought, the attributes are identified and weighted in an appropriate proportion. The level of similarity between a pair of attributes plays an important role to determine the aggregated value of attributes specific to a purpose. Our work determines the similarity levels between a pair of attributes by calculating their maximum attainability in presence of each other. The achievement of an attribute in presence of another is represented as a fuzzy set in the unit interval. The crisp equivalents of the fuzzy sets in the unit interval are used to define their simultaneous satisfaction denoted as 1‐step relation. The 1‐step relation is extended to (m‐1)‐step relation to calculate the degree of attainability of the same pair of attributes in the presence of m (all) attributes. The different levels of (m‐1)‐step relations generate several partitions of the attributes corresponding to multiple purposes in the multiple attribute decision‐making problems. The degree of fulfilment of the purposes in the alternatives are numerically derived by first taking weighted average of attributes within the equivalence classes of a partition and then aggregating the values corresponding to equivalence classes through ordered weighted averaging. The methodology is illustrated with a numerical example. Copyright © 2016 John Wiley & Sons, Ltd.     

The Subtle Influence of Check and X Marks: How Symbolic Markings Influence Judgment

Symbols can exert an influence on how we think, feel, and even behave. Here we examine whether symbolic markings serve as primes and influence how people make judgments. We propose that making either a check or an X mark to indicate an opinion can lead people to process the same information differently, thereby influencing the judgment people make. Across four experiments, we find that the check and X marks carry different symbolic associations; people associate check with good and X with bad. We also find downstream consequences of these mental associations. People who make positively connoted check marks (as opposed to negatively connoted X marks) to indicate their judgments are more agreeable toward familiar, controversial social policies as well as market research survey items on values and life styles. Differential symbolic markings with check and X marks seem to shape how people think and make judgments.     

Bringing (Contingent) Loss Aversion Down to Earth — A Comment on Gal & Rucker's Rejection of “Losses Loom Larger Than Gains”

Although we disagree with some of Gal and Rucker's (2018 – this issue) specific evidence and with their overstated conclusion regarding loss aversion, their overarching message makes a worthwhile contribution. In particular, loss aversion is less robust and universal than has been assumed while its most prominent empirical support — the endowment effect and the status quo bias — is susceptible to multiple alternative explanations. Instead of accepting loss aversion as true unless proven otherwise, we should treat it like other decision properties and psychological accounts that are contingent on various moderators and call for an analysis of psychological mechanisms. In this commentary, we suggest that gatekeepers, such as reviewers, tend to favor loss aversion and other widely accepted tendencies, while demanding a much higher support‐threshold for alternative or newer accounts. Although building on prior theories and concepts is of course important, the bias in favor of incumbent assumptions can impede scientific progress, bar new ideas from the literature, and reinforce well‐established but contingent notions that may apply under some conditions but not others.