ISSN 0439-755X
CN 11-1911/B
主办:中国心理学会
   中国科学院心理研究所
出版:科学出版社

心理学报, 2024, 56(6): 799-813 doi: 10.3724/SP.J.1041.2024.00799

研究报告

基金投资决策中老手与新手的信息加工差异及干预

辛自强,1, 王鲁晓1, 李越2

1中国人民大学心理学系, 北京 100872

2中央财经大学社会与心理学院, 北京 100081

Differences in information processing between experienced investors and novices, and intervention in fund investment decision-making

XIN Ziqiang,1, WANG Luxiao1, LI Yue2

1Department of Psychology, Renmin University of China, Beijing 100872, China

2Department of Psychology at School of Sociology and Psychology, Central University of Finance and Economics, Beijing 100081, China

通讯作者: 辛自强, E-mail:xinziqiang@sohu.com

收稿日期: 2022-11-25  

基金资助: 中国人民大学科学研究基金(中央高校基本科研业务费专项资金资助)项目(22XNKJ01)
国家社会科学基金重大项目(17ZDA325)

Received: 2022-11-25  

摘要

以往的基金研究多从专业的角度构建复杂的决策模型, 难以直接被普通基金投资者所理解和应用。为了引导众多的基金投资新手正确理财, 我们引入“老手−新手”比较范式探寻二者投资决策时的信息加工过程差异, 并探讨如何对新手予以干预以提升其决策质量。研究1通过Mouselab技术收集信息加工过程数据, 发现在基金信息搜索和加工过程中, 老手比新手更倾向于基于属性的信息搜索模式, 信息加工的补偿性更低; 基于属性的信息搜索模式有利于决策质量, 但这一结果仅在新手中存在, 这可能在于老手的信息搜索模式较为稳定, 其变异性难以为决策质量提供解释。由于现有的理财客户端的页面呈现方式使得投资新手难以使用基于属性的信息搜索模式, 研究2向被试提供表格纸来帮助他们进行结构化加工, 以降低基于属性进行搜索的难度, 结果发现结构化加工组被试的决策质量高于控制组。上述结果反映了老手和新手基金投资决策的信息加工特征, 为改进新手理财决策提供了干预思路。

关键词: 投资决策; 老手; 新手; 信息加工; 干预

Abstract

Many individuals now participate in online fund investment, but novice investors often struggle with the complex information they encounter due to the lack of professional guidance in traditional offline financing. Previous research on decision-making has primarily focused on outcomes and utilized statistical methods to construct decision models, which fail to provide direct evidence of information processing. To assist novices in developing the necessary skills for making investment decisions, this study employs process tracking technology in the field of fund investment for the first time. The aim is to explore the differences in information processing between experienced investors and novices, thereby identifying the advantages experienced investors possess in information processing. Additionally, this research investigates the relationship between the decision-making process and outcomes, proposing interventions based on information processing to aid novices in making accurate investment decisions.

To achieve the research objectives, two studies were conducted. Study 1 involved a comprehensive exploration that traced the fund investment decision-making process using Mouselab. It compared various information processing indicators between experienced investors and novices, including decision-making time, depth of search, variability of search, compensatory index, and SM (strategy measure) value of the search pattern. The study also examined the impact of the search pattern on decision quality for experienced investors and novices through grouping logistic regression. Study 2 involved an intervention experiment utilizing a single- factor (structured intervention group vs. control group) between-subject design. Participants in the structured intervention group were provided a piece of form paper to guide them to structure information of funds, while participants in the control group were provided blank paper. Then all participants completed a simulated fund investment task and their decision quality was recorded.

Study 1 revealed that: (1) Experienced investors, compared to novices, preferred to utilize attribute-based search pattern during fund investment decision-making, and displayed a more non-compensatory approach to information processing. (2) Only the decision quality of novices in fund investment was affected by the information search pattern, indicating that their decision quality improved when they searched for information based on attributes. In contrast, the decision quality of experienced investors was unaffected by the information search pattern but positively influenced by working memory. Study 2 demonstrated that participants who used form paper for intervention had higher decision-making quality than those who used blank paper, indicating the effectiveness of the structured intervention.

This study makes theoretical and practical contributions to the literature. First, it explores the characteristics of the information processing process during fund investment decision-making and its relationship with decision outcomes, filling the research gap regarding the “process” of information processing and deepening the understanding of the essence of decision-making ability in fund investment. Second, it extends the “expert-novice” paradigm to the field of fund investment, summarizing the differences in the search pattern and compensatory behavior between experts and novices, further supporting the heuristic decision model. Third, it proposes effective interventions to assist novice investors in improving their online fund investment and inspires the interface design of fund applications.

Keywords: fund investment decision; experienced investors; novices; information processing; intervention

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本文引用格式

辛自强, 王鲁晓, 李越. 基金投资决策中老手与新手的信息加工差异及干预. 心理学报, 2024, 56(6): 799-813 doi:10.3724/SP.J.1041.2024.00799

XIN Ziqiang, WANG Luxiao, LI Yue. Differences in information processing between experienced investors and novices, and intervention in fund investment decision-making. Acta Psychologica Sinica, 2024, 56(6): 799-813 doi:10.3724/SP.J.1041.2024.00799

1 引言

随着我国居民可支配收入的持续增长, 投资理财市场日益壮大。截止2021年底, 我国基金投资者(也称“基民”)已达7.2亿人(中国证券业协会, 2022)。随着大量新手基民涌入市场, 如何引导他们正确理财将成为重要问题, 其意义不仅是保证个人的财富增长, 也有助于我国资本市场的稳定发展。然而以往的相关研究多在对市场数据进行分析后构建复杂的统计模型来预测收益走向, 虽具有专业性却难以被普通基金投资者所理解和利用。本研究关注普通基金投资者的心理过程, 通过“专家−新手”或者“老手−新手”比较范式揭示其基金投资决策结果及背后信息加工方式的差异, 重点在于通过此研究为增进新手的投资决策能力提供干预思路, 助力心理学研究在投资实践层面的应用。同时目前国内外决策心理学、经济心理学等心理学分支关于基金投资决策的信息加工过程研究还亟需积累实证依据。

1.1 基金投资决策的信息加工过程

在以往基金投资的研究中, 研究者多采用基于结果(outcome-based)的研究范式, 通过构建数据模型对过程进行推测(如, 骆盈盈, 任颋, 2015), 但多种模型间存在竞争且难以证伪, 实际上这是利用基于结果的研究范式进行决策研究的通病(Johnson et al., 2008; 魏子晗, 李兴珊, 2015)。若能直接考察决策的信息加工过程, 则有助于理解某一决策结果何以产生。不过, 国内外目前对基金投资决策的研究还较少, 包括基金、股票等各类投资决策的相关研究也多关注投资者非理性的心理异象、投资风格或投资参与度(Arora & Kumari, 2015; Talwar et al., 2021; 王佳, 于泳红, 2017), 较少直接探讨其背后的信息加工过程。鉴于基金投资是投资者在有风险的情境下做出的决策, 投资者在获得收益的同时, 也有损失的风险(邓尧 等, 2022), 因而这种决策是一种特殊的风险决策, 也是日常生活中最典型的风险决策之一(Weber et al., 2002)。有关风险决策过程的一般性研究可以为基金决策过程研究提供借鉴。

研究者多聚焦于信息加工策略来对风险决策进行探讨, 然而, 他们的理论认识和研究结论并不相同(Pachur et al., 2013)。部分研究者以期望价值理论为基础提出整合模型(Birnbaum & LaCroix, 2008), 主张风险决策是一个补偿性的、期望值最大化的过程, 其中补偿性(compensatory)是指对各个维度的信息加权求和后缩减到单一“价值”维度上进行评估(Anderson, 2003)。采用补偿性加工策略时, 人们尽可能地考虑所有信息, 通过计算得出最优选项(周蕾 等, 2014), 反映了基于选项(option-based)的信息搜索模式。与之相对, 其他研究者以“有限理性”假设为基础提出启发式模型(Brandstätter et al., 2006), 主张风险决策是一个非补偿性的、启发式的过程, 即个体不会进行审慎计算, 而是会利用部分重要属性信息做出决策(Brams et al., 2019), 这对应着基于属性(attribute-based)的信息搜索模式。

基金投资决策通常也涉及选项和属性两个维度。例如, 在支付宝理财中存在医药、科技等不同门类的基金产品(选项), 每支基金产品又在业绩、净值等属性上存在不同。总之, 投资者需要获取市场上纷繁多样的基金选项和属性信息后再进行决策, 这无疑是一个难题。当面临这类复杂的决策任务时, 人们更倾向于采用基于属性的搜索模式, 这一点已在风险较低的日常消费决策任务以及风险较高的赌博任务中得以验证(Lohse & Johnson, 1996; Weenig & Maarleveld, 2002)。其心理机制是:因为任务的选项和属性过多, 个体往往难以获取和分析所有信息, 也就无法做出期望值最大的选择; 此时, 为了降低认知负荷, 个体更倾向于采取基于属性的信息搜索模式和非补偿性策略。投资市场上逾万支的基金产品带来了海量的信息, 这使得投资决策复杂而充满风险, 在此情境下, 投资者在对基金信息进行加工时可能不会对“价值”进行合并计算后再选出最佳选项, 即不会基于选项进行信息搜索, 而会基于属性进行信息搜索。虽然有关基金投资决策过程的直接证据尚很少见, 但根据上述对一般性风险决策的研究成果和机制分析, 我们可提出假设1:在进行基金投资决策时, 人们更多倾向于使用基于属性的信息搜索模式。

1.2 老手、新手的信息加工差异

近年来, 受基金市场行情的吸引, 有大量经验不足的新手投资者涌入, 截止2021年一季度, 42%的投资者的投资经验不足一年(景顺长城 等, 2021)。这些基金新手通常更容易在选择基金时陷入信息加工困境, 因此促进基金市场健康发展的关键之一是帮助已进场新手掌握必要的投资决策技能。在现实生活中, 若要学习一门技能, 人们往往会向经验丰富者, 即老手或专家, 寻求经验。先前研究表明, 老手较新手普遍具有一定的信息加工优势, 这一结果在象棋竞技、医学诊断等多个领域得以验证(Brams et al., 2019; Ji et al., 2022; 王福兴 等, 2016)。不过在基金投资领域, “老手−新手”的信息加工过程差异如何体现, 目前缺少直接的研究证据。

其他决策场景或认知任务研究中“老手−新手”的比较结果, 可为基金领域提供启发。经过梳理, “老手−新手”信息加工的不同之处可能在于三个方面。首先, 老手对每一步信息搜索的意义更明确, 决策时更自信, 信息搜索量少但多为重要信息(Brams et al., 2019; Spence & Brucks, 1997), 即他们可以基于已有经验识别出选项的重要特征或属性, 进行启发式加工(Klein & Peio, 1989)。不过, 有一项模拟放贷决策的研究发现老手在做决策时反而会搜索更多信息(Andersson, 2004), 这一结果与通常的认识相矛盾。其次, 与前一点相关, 老手更依赖于直觉决策甚至是无意识决策(Dijksterhuis et al., 2009)。再次, 根据模糊痕迹理论(fuzzy-trace theory), 老手会使用更为简要的要义加工, 而不是逐字逐句的精细加工(Reyna & Lloyd, 2006)。综合这三点, 老手在做决策时可能不会进行审慎计算, 决策过程更偏向以基于经验的启发式方式选择关键属性作为决策依据, 即老手可能更多采用非补偿性的、基于属性的加工策略。由此推理出假设2:相比于新手, 老手在基金投资决策中信息加工的非补偿性更高, 表现为搜索深度和补偿性指数更低, 且更遵循基于属性的搜索模式。

1.3 信息加工方式对决策结果的影响

对信息加工过程进行研究的目的终究是为说明某种决策结果何以产生。以往研究表明, 在进行多属性决策的复杂任务时, 依赖直觉的启发式策略表现更佳, 要优于审慎计算的分析式策略(Dijksterhuis & Olden, 2006; Krava et al., 2021)。基金投资决策也属于多属性决策, 因而偏向于启发式系统的基于属性的信息搜索模式可能带来更优的基金投资决策。然而, 这一关系是否在老手与新手中均成立还不得而知。

当人们在某一领域已经有较多经验时, 他们会从经验中形成认知图式, 在面临类似的决策情境时, 他们往往依赖标准化的程序进行决策(Gillespie & Peterson, 2009), 因而其行为决策方式和行为表现都较为稳定(Itzkowitz & Itzkowitz, 2017), 不易因为问题难度和呈现方式而改变(Saravanan & Menold, 2022; Spence & Brucks, 1997)。因此, 老手的表现优劣不在于策略, 而是与一些能力有关(白改平, 韩龙淑, 2011), 例如研究表明专家的表现关键在于工作记忆(Furley & Wood, 2016)。由此提出假设3:基于属性的信息搜索模式带来的决策质量更好, 与新手投资者相比, 两者关系强度在老手中可能被削弱。

1.4 信息加工方式的干预

基于老手与新手在基金选择时信息加工方式可能存在的差异及其结果, 我们可以有针对性地干预新手的信息加工方式, 改善其理财决策。以往研究忽视对过程的分析, 未有从信息加工角度开展的干预研究, 而只能泛泛强调通过理财知识教育、理财观念培养来改善理财行为(王佳, 于泳红, 2017)。但是这种财经教育往往需要社会的共同配合, 工程量大且见效缓慢, 若要快速帮助人们自主习得理财, 则需要将干预主体定位在基民本身。

就个体的信息加工过程来看, 基于属性的信息搜索模式似乎带来的决策结果更好; 而且在复杂决策场景下, 若以“选项 × 属性”的结构化矩阵形式呈现信息, 则更便于人们对比信息, 并使用基于属性的搜索模式(Weenig & Maarleveld, 2002; 于泳红, 汪航, 2005)。这可能是因为当信息得到排列时, 个体能够更加直观地获取同一行或同一列的数据, 从而更容易关注和识别属性间的差异(Slovic & MacPhillamy, 1974), 很多研究者认为矩阵模式呈现信息的方式降低了信息搜索难度(丁夏齐 等, 2004; 余雯 等, 2013)。因此这种呈现方式可为改善被试的决策策略并提升决策表现提供启发。在日常生活中, 属性信息不会像决策任务一样得到结构化排列, 或者会被打散在各个选项内。正如在现有的理财客户端软件中, 人们往往在一页中只能看到一支基金(选项)的若干属性信息, 必须通过页面间的跳转才能查看更多基金选项。在这种情况下, 选项信息在同一页面内呈现, 得到了结构化整合, 但是属性信息却被打散。决策者在不同基金间进行比较时的认知负荷增大, 而更容易在同一基金内对各属性进行加权计算, 从而采取基于选项的搜索模式, 换言之, 当前的基金呈现方式致使人们难以使用基于属性的信息搜索模式。因此, 本研究希望通过助推的理念(Thaler & Sunstein, 2008), 参考Spence和Brucks (1997)给决策者提供表格纸的方式, 引导被试对信息进行结构化整合, 以此来促进属性信息与选项信息一样得到直观呈现, 帮人们摆脱仅仅因为便利性而一味使用基于选项的加工方法, 从而回归基于属性的信息搜索模式(Weenig & Maarleveld, 2002), 这将有助于他们规避认知上的不足, 提升基金决策的正确率。如前所述, 投资新手大量涌入基金市场, 他们的投资模式并不像老手那样稳定, 因此对新手的信息搜索模式进行干预可能更为有效。实际上, Spence和Brucks (1997)的干预研究也发现了引导经验丰富的老手进行结构化加工对他们的决策表现并无助益。由此提出假设4:通过引导基金投资新手对信息进行属性的结构化整合能够提升基金投资决策的质量。

1.5 本研究目的和方法

本研究首先采用鼠标实验室技术(Mouselab)获取信息加工的过程数据(研究1)。鼠标实验室技术具体操作为向被试呈现一个“选项 × 属性”的信息矩阵, 开始时所有信息均被遮蔽, 鼠标移至单元格时则呈现信息, 移开则再次遮蔽, 被试可反复查看各个信息。通过采集鼠标的移动数据可获取被试的信息搜索时间和内容, 计算补偿性指数和搜索模式等指标(Payne, 1976)。研究者常用此方法获取被试的决策过程数据(如, 张树凤 等, 2017), 以便刻画被试在搜集和处理决策信息时的心理过程。同时, 虽然难以仅凭此刻的基金属性来预测未来的收益, 但是为了探讨投资者进场的问题, 即人们在最初决定投资基金时的推理过程和结果, 我们在实验任务中设置理论上的最优选项以考察人们的决策质量。综上, 研究1通过Mouselab技术对老手和新手在基金决策中的信息加工过程差异进行分析, 并考察决策过程对决策结果有何影响, 由此为干预措施提供思路。

研究2基于日常生活中属性信息不会像决策任务一样得到结构化排列的现状, 在研究1结果基础上开展干预研究, 模拟的互联网基金理财情境, 通过引导被试对信息做结构化整合来干预其加工方式, 探究其决策质量的改善, 以期通过帮助基金新手掌握恰当的信息加工方式改善理财行为。

2 研究1:基金决策中老手与新手的信息加工差异

2.1 预研究

由于至今尚无明确的行业标准划定拥有多久的基金投资经验可被称为基金老手, 所以通过预研究对社会人士的基金投资经验分布进行统计, 以此来确定老手与新手的分组标准, 同时选出人们最为关注的5个基金属性, 用于研究材料的设计。

2.1.1 调查对象及工具

利用见数(Credamo)平台的被试资源线上回收了94份有效问卷, 其中男性51人, 女性43人, 平均年龄为27.61岁(SD = 5.87)。受教育程度在大学本科以下的共8人, 大学本科共73人, 研究生及以上共13人。

首先调查被试的基金投资经验, 包括2题。第1题为“您正在或曾经进行过基金投资理财吗?”对有基金投资经验的被试追问第2题“您的基金投资理财经验大概有多久?”选项包括“0至1年” “1至2年” “2至3年” “3至4年” “4至5年”以及“5年及以上” 6个选项。

接着调查被试投资时关注的基金属性, 选项包括“近一年收益率” “单位净值” “费率” “日涨跌幅” “风险等级” “基金行业” “历史业绩” “基金评级” “基金持仓情况” “基金经理情况” “基金公司情况” “基金排名”和“基金规模”等13个属性(这些属性的确定主要参考了市场上常见的支付宝理财以及各大银行的基金所具有的属性信息, 已尽可能涵盖了各个理财App上所呈现的基金属性), 需要被试在13个选项中选出5个最为关注的基金属性。

最后调查性别、年龄、受教育程度等人口学信息。

2.1.2 研究结果

在基金投资经验上, 不足3年投资经验和3年及以上投资经验的被试占比分别为67.0%、33.0%, 与连榕等人(2003)在自然情况下调查样本中的新手(60.3%)、熟手/专家(39.7%)的占比相似, 故本研究将以3年经验作为新手与老手的分组标准, 以此进行后续的被试招募。

在基金属性上, 被试选择最多的5个属性依次为近一年收益率、风险等级、历史业绩、基金评级、日涨跌幅, 选择频率分别为86.2%、69.1%、64.9%、36.2%、35.1%, 其余属性的选择频率均未超过30%, 最终以这5个属性来设计研究材料。

2.2 被试

以预研究提供的标准, 研究1共线下招募了39名基金投资经验在3年以下, 对基金投资感兴趣且具有简单知识的基金新手; 以及35名基金投资经验在3年及以上, 对基金投资非常了解的基金老手。共获得74名有效被试, 男性30人, 女性44人, 平均年龄为29.04岁(SD = 11.70), 受教育程度在大学本科及以下、研究生及以上的分别有47人、27人, 财经类专业和非财经类专业各半。参考国内 “老手−新手”决策过程研究的结果(陈梅香, 白学军, 2019), 选择中等偏上的效果量Cohen’s d = 0.7估算样本量, 在power为0.8, α = 0.05的情况下, G*Power计算样本量为68人, 本研究74名有效被试符合要求。所有被试的视力或矫正视力均正常, 无智力障碍, 且能正确操纵鼠标。

2.3 研究设计及程序

为探究老手、新手基金投资决策的信息加工过程的差异, 采用单因素被试间设计, 以经验水平(老手、新手)作为自变量, 信息加工过程的各项指标和决策质量为因变量。

被试首先完成模拟基金投资任务, 在此任务中, 被试需要查看基金信息并做出投资判断, 其信息加工的时间、信息搜索模式数据以及最终决策将被记录。随后采用操作广度任务测量被试的工作记忆水平, 因为以往研究表明工作记忆是影响老手、新手表现的关键因素(苗浩飞, 迟立忠, 2023), 故将被试的工作记忆水平作为控制变量纳入研究。最后, 被试完成人口学信息及其他控制变量的问卷调查。

2.4 实验任务及变量测量

2.4.1 模拟基金投资任务

模拟基金投资任务参考Posavac等(2019)的设计思路, 在Johnson等人(1989)开发的Mouselab标准程序的基础上进行调整, 通过Mouselab 1.0软件在计算机上呈现。

实验材料为自编的6 (基金选项) × 5 (基金属性)基金信息矩阵, 按照规范的Mouselab技术进行呈现, 每一行表示一个基金选项, 共6支基金选项, 分别为基金102、基金316、基金443、基金987、基金536、基金224 (各选项的数字部分表示基金代码, 均为三位随机数, 无其他意义, 仅为模拟现实中的基金呈现情况, 这是以往研究中常用的选项呈现方法, 例如: 陈军, 2009; 冷静 等, 2017)。每个选项含有并列的5个基金属性, 为预研究选择出的年收益率、风险等级、历史业绩、基金评级、日涨跌幅。参考支付宝基金的呈现方式, 在本研究中年收益率(分别为22.36%和15.08%)和日涨跌幅(分别为1.03%和0.64%)直接提供数字信息; 风险等级包括 “中风险” “高风险”两个等级; 历史业绩包括“与同类均值持平” “高于同类均值”两个等级; 基金评级包括“三星”和“四星”。在6个选项中, 除基金443外, 每个选项均有某一属性存在劣势, 如基金536的评级为“三星”, 而其他选项均为“四星”。可见基金443为最优选项, 若被试最终选中该最优选项, 则决策质量记为1, 若未选中则记为0。

图1所示, 任务开始时所有信息均被遮蔽, 在被试利用鼠标查看信息前, 会通过指导语告知被试正在参与一项模拟基金投资任务, 现分配给其1000元进行投资, 其在任务中的所有投资收益都将按比例折算为现金报酬发放, 并会在指导语中为被试解释各属性的等级含义。此外, 为了平衡顺序效应, 所有选项和属性的呈现位置随机。

图1

图1   研究1模拟基金投资任务页面样例


本研究采取以往研究常用的过程性指标, 包括决策时长、搜索深度、搜索变异性、补偿性指数和搜索模式(如Borozan et al., 2022; Payne, 1976; Reisen et al., 2008; 王阿妹 等, 2018), 其中决策时长往往反映被试决策的困难程度, 搜索深度、搜索变异性和补偿性指数是对个体补偿性的反映, 搜索模式则是对被试进行搜索时基于属性或是基于选项规则的反映, 这些指标能够较好地刻画出被试在决策时的心理过程。指标说明及计算方法如下:(1)决策时长:各单元格的查看时长之和, 以秒(s)为单位; (2)搜索深度(depth of search, DS):查看的单元格数/所有单元格数, 得分越高表明搜索深度越高, 即补偿性越高; (3)搜索变异性(variability of search, VS):每个选项被查看的单元格数比例的标准差, 得分越高表明搜索变异性越高, 即补偿性越低; (4)补偿性指数(compensation index, CI; Koele & Westenberg, 1995):补偿性指数由搜索深度DS和搜索变异性VS计算得来, 是对补偿性策略的直接体现。计算公式为CI = DS (1 - 2VS), 范围在0至1之间, 数值越大表明补偿性越高。(5)搜索模式:以策略量值(strategy measure, SM)衡量个体的信息搜索模式是基于属性还是基于选项, 这是决策研究领域中过程追踪的重要指标(余雯 等, 2013)。通过鼠标在选项内的转换次数ra和选项间(属性内)的转换次数rd的差异来反映(见公式1), 该指标已被多项研究使用(如Schulte-Mecklenbeck et al., 2013; Su et al., 2013)。当SM值大于0时, 表示基于选项的

搜索模式; 当SM值小于0时, 则表示基于属性的搜索模式。整体上, 该值越小, 表示搜索模式越基于属性。

$ S M=\frac{\sqrt{N}\left(\frac{A D}{N}\right)\left(r_{a}-r_{d}\right)-(D-A)}{\sqrt{A^{2}(D-1)+D^{2}(A-1)}}$

注:A表示选项数量, D表示属性数量, ra表示鼠标基于选项的转换次数, rd表示鼠标基于属性的转换次数, N表示所有转换次数之和。

2.4.2 操作广度任务

采用Unsworth等(2005)开发的操作广度任务测量工作记忆, 运用MATLAB软件和PsychToolbox-3工具箱在计算机上呈现。梅高兴等人(2021)对该任务进行了中文译制, 信效度良好。被试进行三次练习任务(记忆字母练习、判断算式练习、正式任务练习)后, 开始正式测试, 如图2所示, 屏幕上会先呈现一个算式(如72/8 + 2 = ?), 被试需计算结果并判断下一页给出的数字是否为此算式的正确结果, 被试需尽快给出结论, 若判断超时会自动跳转到下一页, 并认定判断错误(若算式判断上的累计正确率低于85%, 表明被试可能为了记忆字母而不认真完成算式判断, 则被试的工作记忆得分无效; 梅高兴 等, 2021)。算式判断完成后, 屏幕上都会呈现一个字母, 持续800 ms, 随后进入下一个算式判断, 因此每组任务呈现的算式数与字母数相同, 被试需按顺序记忆所有字母, 并在相应页面中依次点选出字母。正式测试会呈现15组任务, 每组任务的字母数3到7个不等, 全部测试共含有75个字母, 以回忆正确的字母数量作为被试工作记忆水平的指标。

图2

图2   操作广度任务流程图


2.4.3 人口学信息及其他控制变量的测量

被试报告性别、年龄、受教育程度、是否为财经类专业、风险承受能力等信息。其中, 风险承受能力的测量题目为“当您进行投资时, 愿意承担的风险如何?” 采用5点计分(1 = “不愿意承担任何风险”, 5 = “高风险, 高回报”), 得分越高表明风险承受能力越高。

2.5 研究结果

2.5.1 整体信息搜索模式

按照Willemsen和Johnson (2011)建议的Mouselab数据处理标准, 筛选掉所有停留时间低于200 ms的鼠标停留点, 根据公式计算出所有被试信息搜索的SM值。结果表明, 被试的SM值均值为−4.11 (SD = 5.22), 全距为[−14.08, 11.55]; 其中, SM值大于0的被试有16人, 占比21.6%, SM值小于0的被试有58人, 占比78.4%, 卡方检验表明两组人数存在显著差异, χ2 = 23.84, p < 0.001, φ = 0.57, 即多数被试倾向于进行基于属性的信息搜索, 验证了假设1。

2.5.2 老手与新手的信息加工过程和决策质量的差异

为探讨老手与新手在补偿性和信息搜索模式上的区别, 进行独立样本t检验(见表1)。老手组和新手组在决策时长上无差异, t(72) = −0.07, p = 0.942, 表明在基金决策任务中, 决策时长不受经验丰富与否的影响。在补偿性各指标上, 老手组的搜索深度显著低于新手组, t(72) = −2.20, p = 0.031, Cohen’s d = 0.51; 老手组的搜索变异性略高于新手组, 两组间差异边缘显著, t(72)= 1.95, p = 0.056, Cohen’s d = 0.47; 老手组的补偿性指数显著低于新手组, t(72) = −2.15, p = 0.035, Cohen’s d = 0.50, 效果量为中等水平。综合可得, 老手信息加工的“补偿性”低于新手, 即与新手相比, 老手不会对所有信息进行深度挖掘和审慎计算, 而多采用启发式的加工策略。在信息搜索模式上, 老手组的SM值显著低于新手组, t(72) = −2.20, p = 0.031, Cohen’s d = 0.51, 效果量为中等水平, 即与新手相比, 老手在信息加工时更倾向于选择基于属性的搜索模式, 验证了假设2。

表1   老手与新手在各变量上的差异比较

变量老手组新手组t
MSDMSD
决策时长50.1828.5850.6020.15−0.07
搜索深度DS0.900.150.960.07−2.20*
搜索变异性VS0.090.090.050.081.95
补偿性指数CI0.770.250.880.19−2.15*
搜索模式SM−5.484.34−2.885.67−2.20*
风险承受能力3.110.822.670.702.51*
工作记忆54.5011.3361.849.12−2.94**

注:工作记忆水平的比较中, 老手组30人, 新手组37人, 其余各变量的差异比较分析中, 样本量为老手组35人, 新手组39人。*p < 0.05, **p < 0.01

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我们还对老手(正确率48.57%)和新手(正确率46.15%)的决策质量进行比较, 但未发现两者有显著差异, χ2 = 0.04, p > 0.05。

2.5.3 信息搜索模式对决策质量的影响

为探究信息搜索模式对决策质量(为0、1记分的二分变量)的作用, 将信息搜索模式(以SM为指标)作为自变量, 经验水平(老手、新手)为调节变量, 控制个体的性别、年龄、受教育程度、专业、风险承受能力、工作记忆, 同时决策受制于对有效信息的检索率, 因此我们也纳入搜索深度作为控制变量, 进行Logistic回归, 其中有7人在操作广度任务中算式正确率低于85%, 未纳入后续分析。模型拟合χ2 = 7.82, p = 0.451, 表明模型拟合度良好, 从表2来看, SM对决策质量有负向预测作用, B = −0.18, SE = 0.08, Wald χ2 = 4.72, OR = 0.84, 95% CI = [0.71,0.98], p = 0.030, 变化的Nagelkerke R2 = 0.14, 即个体越偏向基于属性的信息搜索模式, 决策质量越好, 越偏向基于选项的信息搜索模式, 决策质量越差。但是并未发现经验水平和SM的交互作用(p = 0.267)。

表2   信息搜索模式对决策质量影响的Logistic回归分析

变量整体上(N = 67)老手组(n = 30)新手组(n = 37)
BSEWald χ2ORBSEWald χ2ORBSEWald χ2OR
控制变量
性别0.350.700.261.431.501.231.484.460.021.08<0.011.02
年龄0.020.050.251.020.180.103.221.19-0.030.370.010.97
受教育程度0.760.711.152.143.97*2.013.9053.110.761.690.212.15
专业0.950.681.962.581.241.201.053.441.220.941.683.38
风险承受能力−0.620.432.060.54−1.610.972.750.20−0.210.600.130.81
工作记忆0.070.033.671.070.16*0.084.151.180.020.050.111.02
搜索深度3.552.841.5634.635.185.650.84176.93−2.435.810.180.09
预测变量
SM−0.18*0.08 4.72 0.84 −0.030.130.070.97−0.17*0.08 4.12 0.84
经验水平1.301.041.573.67
经验水平×SM0.150.131.231.16

注:性别为分类变量, 女性编码为0(对照组), 男性编码为1; 受教育程度中本科及以下编码为0(对照组), 研究生及以上编码为1; 专业中非财经类专业编码为0(对照组), 财经类专业编码为1; 经验水平为分类变量, 新手编码为0 (对照组), 老手编码为1。 * p < 0.05。

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为了更深入理解信息搜索模式在老手和新手中的作用情况, 我们根据经验水平分组进行Logistic回归, 结果发现在老手和新手中信息搜索模式显示出了不同作用。在新手组中, 模型拟合χ2 = 4.51, p = 0.720, 表明模型拟合度良好。当控制了性别等变量后, SM对决策质量的负向预测作用显著, B = −0.17, SE = 0.08, Wald χ2 = 4.12, OR = 0.84, 95% CI = [0.72,0.99], p = 0.042, 变化的Nagelkerke R2 = 0.16, 这表明与基于属性进行信息搜索相比, 若新手基于选项进行搜索, 其正确率下降16%; 在老手组中, 模型拟合良好, χ2 = 9.90, p = 0.272。然而却发现SM值对决策质量没有影响(p = 0.799, 变化的Nagelkerke R2 = 0.002), 但是工作记忆能够正向预测老手的决策质量, B = 0.16, SE = 0.08, Wald χ2 = 4.15, OR = 1.18, 95% CI = [1.01,1.38], p = 0.042, 工作记忆水平越高则决策质量越好。以上结果表明, 基于属性的信息搜索模式对新手的决策质量有积极影响, 而对老手的决策质量无影响, 这一结果可能是因为老手信息搜索模式的稳定性高而变异性低, 因此不足以预测决策质量, 验证了假设3。

此外, 并未发现决策时间、搜索深度、搜索变异性和和补偿性指数对决策质量的作用, ps > 0.05。

2.6 讨论

研究1表明, 当同时向被试呈现基金的选项和属性信息时, 被试整体上倾向于采用基于属性的搜索模式。同时结果表明, 老手比新手基于属性的程度更高, 信息加工补偿性更低, 该发现与以往研究结论在本质上相似, 即老手以更为启发式的方式进行信息加工(Reingold & Charness, 2005)。信息搜索模式能够影响决策质量, 但仅在新手中成立, 当新手使用的搜索模式越是基于属性时则决策质量越高, 老手则不然。这说明新手的确会因为信息加工问题导致决策质量的下降, 同时也为启发式系统在复杂决策中的优势(孙彦 等, 2007)提供了一些支持。综上, 若要提升新手的决策质量, 可从信息搜索模式入手, 但老手的决策质量与信息搜索模式关系不大。研究1与先前类似文献(于泳红, 汪航, 2005)均表明, 矩阵式呈现信息时个体多采用基于属性的信息搜索模式。

在实际生活中, 信息多不以结构化呈现(Weenig & Maarleveld, 2002), 会存在难以基于属性进行信息搜索的情况。当下的理财App大多在一个页面中只呈现单支基金(选项), 而将属性信息囊括在选项当中, 似乎在引导人们使用基于选项的搜索模式, 这不利于新手决策质量的改善。研究1的结果提示我们只需将属性信息与选项信息同时按照结构化的方式呈现给投资者, 他们则会更倾向采用基于属性的搜索模式, 从而有更好的表现。基于此, 研究2模拟真实的理财APP的信息呈现方式, 并通过提供表格纸的方式引导被试对属性信息进行结构化整合, 以促进新手转向使用基于属性的信息搜索模式, 提高决策质量。

3 研究2:对基金新手的结构化干预研究

3.1 被试

以预研究提供的标准, 线下招募了73名基金投资经验在3年以下、对基金投资感兴趣且具有简单知识的基金新手。参考信息呈现方式影响信息搜索正确率的效果量(φ = 0.52; 潘运娴 等, 2018), 在power为0.8, α = 0.05的情况下, G*Power计算样本量为31人, 本研究样本量符合要求。其中, 男性43人, 女性30人, 平均年龄为34.90岁(SD = 9.06)。受教育程度在大学本科以下的有21人, 大学本科51人, 研究生及以上1人, 所有被试的视力或矫正视力均正常, 无智力障碍。被试被随机分入实验组和控制组。

3.2 研究设计

研究2采用单因素被试间设计。自变量为是否接受结构化整合干预, 分为结构化加工组(n = 36)和控制组(n = 37); 因变量为决策质量, 其衡量标准与研究1相同。

3.3 任务、材料与程序

被试通过计算机完成一项模拟基金投资任务, 并且被告知在投资中的表现将决定着最终获得的实验报酬。参考Spence和Brucks (1997)的干预方式, 通过向决策者提供表格纸为其提供结构化引导, 即引导决策者将基金选项信息和属性信息进行结构化排列。当被试落座于计算机前, 桌上已为其备好纸笔, 结构化加工组会备一张表格纸(纸上已绘制好一个6 × 5的空白矩阵), 引导其结构化整合基金的属性信息, 控制组则备一张白纸。

本研究全程采用PPT形式呈现基金信息。计算机屏幕上首先会呈现模拟基金投资任务的主页面, 在这一页中仅呈现指导语及6个基金按钮, 点击基金按钮可通过超链接跳转到该按钮所代表基金的子页面(见图3), 在子页面中可以看到该基金的所有信息, 被试在查看过程中可在表格纸(结构化加工组)或白纸(控制组)上进行信息整理, 每个子页面均设置了“返回”键, 点击“返回”便可回到主页面, 继续通过点击基金按钮查看信息, 以此保证被试在一个页面中只能看到一支基金的信息。在被试决定做出投资选择前, 所有基金信息都可重复查看, 整体呈现方式基本复制了人们在理财App中查看基金信息的全流程。当认为可做出投资选择时, 被试可以停止查看信息并给出自己的选择。

图3

图3   研究2模拟基金投资子页面样例


最后报告性别、年龄、受教育程度、对基金知识的了解程度、风险承受能力等信息。其中基金知识的了解程度通过1题“您对基金知识的了解程度为?”, 5点计分(1 = “非常差”, 5 = “非常好”), 得分越高表明被试对基金知识越了解; 风险承受能力测量方式同研究1。任务结束后, 会根据被试的投资选择给予相应的报酬。

本任务中涉及的6支基金的选项及属性信息与研究1相同, 在指导语上也保留了研究1中的任务介绍和对属性的基本解释。唯一不同的是, 信息呈现为每屏只呈现一支基金的信息, 这与真实理财App的呈现方式一致。

3.4 研究结果

首先对两组被试的基金知识了解程度及风险承受能力进行独立样本t检验, 结构化加工组的基金知识了解程度(M = 2.53, SD = 0.91)与控制组(M = 2.24, SD = 0.83)不存在显著差异, t(71) = 1.39, p = 0.17; 结构化加工组的风险承受能力(M = 2.81, SD = 1.04)与控制组(M = 3.03, SD = 1.04)也不存在显著差异, t(71) = −0.91, p = 0.37, 表明两组被试在基金知识和风险承受能力上同质。

为探究结构化干预能否改善新手的决策质量, 进行卡方分析。结果表明结构化加工组的决策质量(正确人数17人, 正确率47.22%)显著高于控制组(正确人数9人, 正确率24.32%), χ2 = 4.17, p = 0.041, φ = 0.24, 效果量为中等水平, 验证了假设4。

3.5 讨论

在理财App的主页面结合子页面的信息呈现形式下, 仅仅是给基金新手一张画有表格线的纸张就能够帮助其做出更好的基金投资决策。表格式记录有助于对信息进行结构化整合, 引导个体将基金属性信息和选项进行排列, 而这种排列有助于个体跳出属性从属于选项的认知, 从而更多地使用基于属性的信息搜索模式(于泳红, 汪航, 2005), 这也与在研究1的基金呈现方式中被试多使用基于属性的搜索模式吻合。而且, 结构化后的信息可以降低个体进行信息加工的难度, 从而更快速地找到有效线索, 便于进行综合判断(Chernev, 2003)。因此, 在现实生活中, 当人们在理财App上自主进行基金投资时, 尽管缺少线下理财渠道所拥有的理财服务与专业分析, 但仅仅使用一张画有表格的纸就可以帮助缺少经验的基民更多采用基于属性的信息搜索模式, 从而提高决策质量。因为这种表格在助推他们以“选项 × 属性”的结构化矩阵方式整合信息, 更快找到可资抉择的关键属性。

4 综合讨论

4.1 老手与新手在基金投资决策中的信息加工差异

研究1利用Mouselab技术从过程到结果比较全面地探究了基金投资决策中老手与新手的信息加工差异。在过程上, 研究1比较了老手和新手在补偿性和搜索模式上的区别; 在结果上, 则确定了过程与结果之间的关系, 基于决策过程的视角尝试打开决策黑箱。

一方面, 研究1验证了假设1和假设2, 表明人们在进行基金决策时, 面对矩阵式呈现的选项和属性信息, 会偏向使用基于属性的信息搜索模式。这与决策领域的理论研究结论相符, 决策模型正逐渐从传统的基于选项的假设转向基于属性的假设, 由支持补偿性规则转向非补偿性规则, 即更支持启发式模型(Gigerenzer et al., 2022; 刘永芳, 2022)。在研究1中, 选项参照以往研究者多采用的无意义代码的方式进行呈现(如: 陈军, 2009; 冷静 等, 2017), 但这种呈现方法并不意味着被试难以基于选项进行转换, 因为每一行表示一个选项, 每一列表示一个属性, 竖向查看信息的方式是有悖于人们日常的横向阅读习惯的(Tullis, 1988), 研究也表明在时间压力小且信息较少的情况下, 被试可能会采用基于选项的信息搜索模式(陈军, 2009), 因而基金投资者在决策时偏好基于属性的信息搜索模式这一结果不能通过信息的布局进行解释。同时由于经验的作用, 老手比新手更倾向于基于属性的信息搜索模式, 在信息加工补偿性上也更低, 启发式程度更高(Dijksterhuis et al., 2009)。

另一方面, 研究1发现信息搜索模式会影响决策质量, 这种影响仅见于新手:新手的信息搜索越基于属性时决策质量越好, 老手则不受信息搜索模式的影响, 验证了假设3。对于新手来说, 他们在基金投资中还处于摸索阶段, 往往感受到更高的决策不确定性, 在此情境下启发式的优势会更加凸显(Gigerenzer & Gaissmaier, 2011)。而老手在信息搜索模式上已较为成熟, 形成了稳定的决策风格和习惯(Gillespie & Peterson, 2009)。研究1发现老手SM值的变异性小于新手(见表1), 且90%的老手SM值小于0, 这可能意味着老手已经更多地且更稳定地依赖属性搜索模式来决策, 他们在信息搜索模式上的低变异性可能导致信息搜索模式无法在实际决策中或统计结果上为决策质量提供帮助和解释。

这也能解释虽然老手的信息搜索模式更加有效, 但他们的决策质量并未优于新手, 即他们在基金投资时并非仅依靠信息的检索和加工。一方面, 老手的决策更依赖于一般认知能力, 如个体的工作记忆水平(Ericsson, 2000)和实际认知能力(Furley & Wood, 2016); 另一方面, 老手更依赖于个体风格和习惯, 经验丰富者可能反而无法规避过度自信的干扰(Lambert et al., 2012), 所以出现忽视重要信息的情况。很多研究表明经验不会改善决策质量(Lambert et al., 2012; Larrick & Feiler, 2016; Posavac et al., 2019), 大量财经素养的相关研究同样发现人们的客观财经知识和技能对其理财行为的作用非常有限(Fernandes et al., 2014; Liao et al., 2022)。

此外, 老手和新手的决策时长没有区别。复杂的任务往往需要人们用更长的时间进行加工和决策(王阿妹 等, 2018)。随着经验的增加, 基金决策任务对老手来说更简单、更熟悉。因而老手比新手的决策时间更短似乎才符合常理, 确有研究表明老手会用更少地时间进行信息搜索和决策(Ramachandran et al., 2021), 但是当干扰因素较多时, 老手也会用更多的时间对信息进行整合和处理(Ognjanovic et al., 2019), 似乎新手和老手在决策用时上的差异并不稳定。鉴于现有文献的矛盾, 这些问题的本质和成因仍有待探讨。

4.2 互联网基金理财的干预措施

本研究通过模拟线上理财的形式, 试图发现在缺少专业人员指点迷津的情况下引导基金新手自我规避理财失误的有效措施。基于研究1的结果, 研究2设计了训练新手在逐个查看若干基金的信息后进行结构化整合的干预方法, 使被试由因受迫于线上理财时的信息呈现形式而可能采用的基于选项的信息搜索模式转换为基于属性做决策, 结果证明该措施的确提升了决策质量, 验证了假设4。

研究2的这一结果提供了一种简单改变信息呈现方式以助推决策改进的方法。大量证据表明通过凸显或移除特定信息能够达到干预的目的, 例如将健康食物排在选项的首位(Dayan & Bar-Hillel, 2011)或者进行生动描述(Wilson et al., 2016)都可提升消费者购买健康商品的可能性; 移除烟盒上的营销信息能够帮助吸烟者逐步戒烟(Pechey et al., 2013)。虽然我们提出的干预手段不是凸显属性信息或移除选项信息——因为这很难在现实投资中进行改变, 但是通过矩阵呈现的方式能够将属性信息的凸显程度与选项拉平, 起到干预的目的。

以往的干预研究经常建议开展财经素养教育以改善人们的财经知识、能力和价值观, 最终改进理财决策质量, 但是这类干预方式成本较高且需要伴随其他训练才能达到干预效果(Fernandes et al., 2014)。与教育不同, 本研究基于投资者角度, 证明通过掌握恰当的信息加工方法也可以达到相当的干预效果, 为基金理财干预提供了一条简单易行的低成本思路。本研究同样为相关机构助推理财效果提供了启发, 具体而言, 理财APP信息呈现方式应当有所改变, 若理财APP可通过页面设计引导用户进行基于属性的信息搜索, 则能形成助推, 实现“以小拨大” (何贵兵 等, 2018), 提升基金决策正确率。

在实际的基金市场上, 投资者将面临比模拟的基金投资任务更加复杂的情境, 需要对更多的信息进行检索。此时, 与形成稳定决策模式的老手相比, 新手更难提取有效信息(Schubert et al., 2013), 从而做出非理性或毫无根据的决策(Saravanan & Menold, 2022)。换言之, 面对更复杂的基金决策情境时, 基于属性的信息搜索策略将对新手来说更为有效, 采用简便的方式进行结构化整合将更有助于新手免于陷入低级的决策错误中。

4.3 研究价值

随着基金投资新手涌入市场, 基金理财得到研究者关注。但是相关结论多来自经济学研究, 这些研究多是分析大量的市场数据, 而脱离现实的理财场景(如: 邴涛 等, 2022; 谈漪 等, 2020), 难以给普通投资者提供指导。鉴于此, 本文立足基金投资者个体, 挖掘新手和老手决策时的心理过程并提出干预措施, 目的并不在于提出基金的函数模型或改进决策理论, 而是希望能够引导庞大规模的基金新手正确理财。

具体而言, 本研究的贡献一是使用Mouselab技术探讨了基金投资决策中的信息加工过程特征及其与决策质量的关系, 深化了对基金投资决策能力本质和过程机制的认识, 为本领域的“过程性”研究提供新的实证证据; 二是将“老手(专家)−新手”范式拓展到了基金投资领域, 并灵活地与多属性决策的信息加工衡量指标相结合, 总结出老手与新手在信息搜索模式和补偿性方面的差异, 进一步支持了启发式决策模型(Gigerenzer & Gaissmaier, 2011); 三是提出了可以引导投资者利用矩阵形式对属性信息进行结构化整合这一简单有效的干预措施, 可帮助人们改进线上基金理财, 同时对理财APP的界面设计有启发。

4.4 局限及展望

首先, 本研究样本量不够大, 这可能使得研究存在统计检验力不足的风险。不够大的样本量一方面可能导致错误接受虚无假设的风险增大, 另一方面也可能会导致虚假的阳性结果(Asendorpf et al., 2013), 这在一定程度上限制了研究的统计效度。招募特定的“老手−新手”基金投资者作为被试进行研究存在难度, 所以我们的样本量并未像一般的社会心理学研究中那样大, 我们希望未来研究者用更加充足的样本去验证结论, 同时我们也想要提醒未来研究者在进行类似实验时, 应选择更为保守的效果量进行样本量估计。

其次, 未来研究可改进研究任务。本研究尽可能地模拟了现实中复杂的基金投资情境, 参考以往研究(Weenig & Maarleveld, 2002)设计了6 (选项) × 5 (属性)的信息板, 但是仍存在简化现实情境的可能性。正如研究1结果表明的, 老手和新手在搜索深度上整体均值都较高, 这可能是因为矩阵式的信息呈现方式降低了信息搜索的难度(丁夏齐 等, 2004), 实际上这也是研究2的干预能够起效的背后机制。同时, 本研究仅能模拟投资者对基金的即时选择, 无法体现持续累计的长远收益。因此, 今后可以考虑适当增加基金选项和属性的数量, 并在真实情境下对投资决策行为进行长期研究。

再次, 未来研究可改进被试选取程序。本研究发现老手与新手在工作记忆水平上存在差异, 这可能来源于两组被试平均年龄不同(老手: M = 37.60, SD = 12.04; 新手: M = 21.36, SD = 2.28, t(72) = 8.27, p < 0.001; Salthouse, 1985), 实际上年龄差异也常在以往“老手(专家)−新手”比较研究中存在(如: 陈梅香, 白学军, 2019)。虽然我们通过统计分析尽可能地控制年龄对结果的影响, 但今后应该选择年龄和工作记忆水平更为同质的老手和新手进行加工过程的比较。另外, 老手和新手只是一种相对的划分, 可借鉴以往研究(如, 连榕 等, 2003)将老手细化为专家和熟手, 进一步考察两者的差异。

最后, 本研究只关注了如何改进新手在投资初期的表现, 对老手缺少关注。实际上, 研究1发现老手在基金决策时表现并不优于新手, 而他们的决策质量又相对稳定且不受到信息搜索模式的影响。那么, 如何使得基金老手免于犯错值得未来研究进行探讨。

5 结论

本研究得到以下结论:(1)在进行基金投资决策时, 老手比新手信息加工的补偿性更低, 更倾向于基于属性的信息搜索模式; (2)新手越偏向使用基于属性的信息搜索模式, 则决策质量越好; (3)结构化干预能够提升基金新手的决策质量。

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Psychological Bulletin, 129(1), 139-166.

PMID:12555797      [本文引用: 1]

Several independent lines of research bear on the question of why individuals avoid decisions by postponing them, failing to act, or accepting the status quo. This review relates findings across several different disciplines and uncovers 4 decision avoidance effects that offer insight into this common but troubling behavior: choice deferral, status quo bias, omission bias, and inaction inertia. These findings are related by common antecedents and consequences in a rational-emotional model of the factors that predispose humans to do nothing. Prominent components of the model include cost-benefit calculations, anticipated regret, and selection difficulty. Other factors affecting decision avoidance through these key components, such as anticipatory negative emotions, decision strategies, counterfactual thinking, and preference uncertainty, are also discussed.

Andersson, P. (2004).

Does experience matter in lending? A process-tracing study on experienced loan officers’ and novices’ decision behavior

Journal of Economic Psychology, 25(4), 471-492.

[本文引用: 1]

Arora, M., & Kumari, S. (2015).

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Psychologia, 58(3), 115-126.

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Asendorpf, J. B., Conner, M., De Fruyt, F., De Houwer, J., Denissen, J. J., Fiedler, K.,... Wicherts, J. M. (2013).

Recommendations for increasing replicability in psychology

European Journal of Personality, 27(2), 108-119.

[本文引用: 1]

Bai, G. P., & Han, L. S. (2011).

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[白改平, 韩龙淑. (2011).

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教育理论与实践, 31(32), 34-36.]

[本文引用: 1]

Bing, T., Gao, S. X., & Sha, Y. Z. (2022).

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[本文引用: 1]

[邴涛, 高圣贤, 沙叶舟. (2022).

基金规模效应与业绩持续性: 投资风格漂移视角

证券市场导报, (11), 48-59.]

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Birnbaum, M. H., & LaCroix, A. R. (2008).

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Organizational Behavior and Human Decision Processes, 105(1), 122-133.

[本文引用: 1]

Borozan, M., Loreta, C., & Riccardo, R. (2022).

Eye-tracking for the study of financial decision-making: A systematic review of the literature

Journal of Behavioral and Experimental Finance, 35, Article e100702.

[本文引用: 1]

Brams, S., Ziv, G., Levin, O., Spitz, J., Wagemans, J., Williams, A. M., & Helsen, W. F. (2019).

The relationship between gaze behavior, expertise, and performance: A systematic review

Psychological Bulletin, 145(10), 980-1027.

DOI:10.1037/bul0000207      PMID:31414844      [本文引用: 3]

Perceptual-cognitive skills enable an individual to integrate environmental information with existing knowledge to be able to process stimuli and execute appropriate responses on complex tasks. Various underlying processes could explain how perceptual-cognitive skills impact on expert performance, as articulated in three theoretical accounts: (a) the long-term working memory theory, which argues that experts are able to encode and retrieve visual information from long-term working memory more than less experienced counterparts; (b) the information-reduction hypothesis, which suggests that experts can optimize the amount of information processed by selectively allocating their attentional resources to task relevant stimuli and ignore irrelevant stimuli; and (c) the holistic model of image perception, which proposes that experts are able to extract visual information from distal and para-foveal regions, allowing more efficient global-local processing of the scene. In this systematic review, we examine the validity of the aforementioned theories based on gaze features associated with the proposed processes. The information-reduction hypothesis was supported in most studies, except in medicine where the holistic model of image perception garners stronger support. These results indicate that selectively allocating attention toward important task-related information is the most important skill developed in experts across domains, whereas expertise in medicine is reflected more in an extended visual span. Large discrepancies in the outcomes of the papers reviewed suggest that there is not one theory that fits all domains of expertise. The review provides some essential building blocks, however, to help synthesize theoretical concepts across expertise domains. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Brandstätter, E., Gigerenzer, G., & Hertwig, R. (2006).

The priority heuristic: Making choices without trade-offs

Psychological Review, 113(2), 409-432.

DOI:10.1037/0033-295X.113.2.409      PMID:16637767      [本文引用: 1]

Bernoulli's framework of expected utility serves as a model for various psychological processes, including motivation, moral sense, attitudes, and decision making. To account for evidence at variance with expected utility, the authors generalize the framework of fast and frugal heuristics from inferences to preferences. The priority heuristic predicts (a) the Allais paradox, (b) risk aversion for gains if probabilities are high, (c) risk seeking for gains if probabilities are low (e.g., lottery tickets), (d) risk aversion for losses if probabilities are low (e.g., buying insurance), (e) risk seeking for losses if probabilities are high, (f) the certainty effect, (g) the possibility effect, and (h) intransitivities. The authors test how accurately the heuristic predicts people's choices, compared with previously proposed heuristics and 3 modifications of expected utility theory: security-potential/aspiration theory, transfer-of-attention-exchange model, and cumulative prospect theory.((c) 2006 APA, all rights reserved).

Chen, J. (2009).

The influence of attributive style and time pressure on information processing in decision making

Journal of Psychological Science, 32(6), 1445-1447.

[本文引用: 3]

[陈军. (2009).

归因风格、时间压力对决策信息加工的影响

心理科学, 32(6), 1445-1447.]

[本文引用: 3]

Chen, M. X., & Bai, X. J. (2019).

The impact of clue on different radiologists' decision making: Evidence from eye movement

Journal of Psychological Science, 42(2), 484-491.

[本文引用: 2]

[陈梅香, 白学军. (2019).

线索提示对放射医学决策的影响:来自眼动的证据

心理科学, 42(2), 484-491.]

[本文引用: 2]

Chernev, A. (2003).

When more is less and less is more: The role of ideal point availability and assortment in consumer choice

Journal of Consumer Research, 30(2), 170-183.

[本文引用: 1]

Dayan, E., & Bar-Hillel, M. (2011).

Nudge to nobesity II: Menu positions influence food orders

Judgment and Decision Making, 6(4), 333-342.

[本文引用: 1]

Deng, Y., Wang, M. M., & Rao, H. Y. (2022).

Risk-taking research based on the Balloon Analog Risk Task

Advances in Psychological Science, 30(6), 1377-1392.

DOI:10.3724/SP.J.1042.2022.01377      [本文引用: 1]

In daily life and work, people inevitably need to make choices and decisions under risky situations. The existence of risks may bring some negative consequences to the decision-makers or maybe the beginning of new opportunities. Therefore, how people make effective decisions in different risky situations and the cognitive neural mechanism behind it has been a research hotspot in many disciplines. For many years, a variety of measurements have been used to explore an individual’s risk-taking behaviors. Many studies leverage self-reported instruments to investigate risk (e.g., Sensation-Seeking Scale, Barratt Impulsiveness Scale), while others measure risk-taking using some paradigms. The Balloon Analog Risk Task (BART) is extensively accepted and applied by many researchers due to its well simulation of real-life risk-taking situations in a laboratory environment. The current study synthesizes the BART’s reliability and validity compared to other paradigms and further probes the advantages of using the BART as the measuring instrument of risk-taking behaviors. Moreover, the present study also discusses the evolution of the paradigm and summarizes the research progress of BART based on the existing behavioral and neural studies. Finally, some deficiencies of BART and the prospects for its development are put forward in conclusion. Compared with other risk-taking paradigms, the BART has been proved to be of high ecology, stability, and reliability under different risk circumstances. It has become one of the most widely used paradigms for risky decision-making research. It also has unique advantages in the prediction of some risks, such as smoking, drinking and substance use. As the pioneering behavioral paradigm that was exploited to measure adolescent risk-taking behaviors, the BART contributes a lot to exploring youths' addiction and substance use. Recently, researchers have developed a series of variants of the BART paradigm to adapt to the needs of different research situations. Many studies have leveraged the BART to extensively explore neural correlates of risk-taking behaviors in developmental, healthy, pathological, and addiction research. Overall, BART can not only meet the needs of behavioral measurement in different risk scenarios; but also be well combined with a series of neural measurement techniques. Neuroimaging studies have confirmed that risk-taking in the BART is associated with activations in multiple brain regions, including the ventral striatum, anterior cingulate cortex, insula, midbrain, and dorsolateral prefrontal cortex. These findings suggest that the risk-taking behaviors measured by the BART involve rewards, emotions, learning, and evaluation. BART is also regarded as a classical paradigm for sequential risk decision-making. Similar findings are mentioned in the computational modeling of the BART data in sequential risk-taking consequences, emphasizing the critical role of learning and evaluation processes in the task. Although the BART has been widely used in risk-taking research, future studies are still needed to further improve the reliability and stability of the BART for cognitive neuroscience research and expand its application scope. Currently, the BART research at the neural level still lacks large sample data, which may lead to incorrect research results like underestimating the possibility of an individual’s risk-taking in real life. It is necessary to further expand the sample size, build a database based on the BART behavior and neuroimaging experiments, and share data and research results in different fields and levels to enhance our understanding of risky decision-making.

[邓尧, 王梦梦, 饶恒毅. (2022).

风险决策研究中的仿真气球冒险任务

心理科学进展, 30(6), 1377-1392.]

DOI:10.3724/SP.J.1042.2022.01377      [本文引用: 1]

仿真气球冒险任务(The Balloon Analog Risk Task, BART)能在实验室环境下模拟真实世界的风险情境, 具有高生态性, 稳定性和可靠性等优点, 已经成为风险决策研究中最常用的实验范式之一。近年来, 研究者发展了多种BART变体范式, 对发展、健康以及精神病理等多领域的风险决策行为及其神经基础开展了广泛探索。BART任务中的风险决策加工与腹侧纹状体、前扣带皮层、脑岛、中脑及背外侧前额叶等脑区的激活相关。未来研究需要进一步完善BART任务在风险决策认知神经领域的信效度并扩展BART的应用情境。

Dijksterhuis, A., & Olden, Z. V. (2006).

On the benefits of thinking unconsciously: Unconscious thought can increase post-choice satisfaction

Journal of Experimental Social Psychology, 42(5), 627-631.

[本文引用: 1]

Dijksterhuis, A., Bos, M. W., van der Leij, A., & van Baaren, R. B. (2009).

Predicting soccer matches after unconscious and conscious thought as a function of expertise

Psychological Science, 20(11), 1381-1387.

DOI:10.1111/j.1467-9280.2009.02451.x      PMID:19818044      [本文引用: 2]

In two experiments, we investigated the effects of expertise and mode of thought on the accuracy of people's predictions. Both experts and nonexperts predicted the results of soccer matches after conscious thought, after unconscious thought, or immediately. In Experiment 1, experts who thought unconsciously outperformed participants in all other conditions. Whereas unconscious thinkers showed a correlation between expertise and accuracy of prediction, no such relation was observed for conscious thinkers or for immediate decision makers. In Experiment 2, this general pattern was replicated. In addition, experts who thought unconsciously were better at applying diagnostic information than experts who thought consciously or who decided immediately. The results are consistent with unconscious-thought theory.

Ding, X. Q., Ma, M. C., Wang, Y., & Fan, C. L. (2004).

Applications of IDB in consumer researches

Advances in Psychological Science, 12(3), 440-446.

[本文引用: 2]

Information Display Board (IDB) is a process tracing technique, which shows an m×n information matrix to subjects and monitors their information acquisition behavior. Researchers employ this technique to study subjects’ information searching and acquiring process in problem solving and decision-making. Mouselab is the generally adopted software of IDB and applied in many researches. Since consumers are problem solvers with bounded rationality, IDB is fitted for the studies of consumer behavior. Using IDB, the patterns of information acquisition and some influence factors were studied in consumer decision-making studies.

[丁夏齐, 马谋超, 王詠, 樊春雷. (2004).

信息显示板(IDB)实验在消费行为研究中的应用

心理科学进展, 12(3), 440-446.]

[本文引用: 2]

信息显示板(Information Display Board, IDB)实验是一种过程跟踪技术,以m×n矩阵方式呈现信息阵列,通过观测被试信息检索和浏览的一系列行为,来研究被试问题解决和决策中的信息获得(information acquisition)过程。Mouselab是常用的IDB计算机化程序。消费者是有限理性的问题解决者,因此IDB实验被用于消费行为领域的研究。应用不同的IDB实验设置,研究者探索了消费决策中消费者信息获得的模式和影响因素。

Ericsson, K. A. (2000).

How experts attain and maintain superior performance: Implications for the enhancement of skilled performance in older individuals

Journal of Aging and Physical Activity, 8(4), 366-372.

[本文引用: 1]

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Management Science, 60(8), 1861-1883.

[本文引用: 2]

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Working memory, attentional control, and expertise in sports: A review of current literature and directions for future research

Journal of Applied Research in Memory and Cognition, 5(4), 415-425.

[本文引用: 2]

Gigerenzer, G., & Gaissmaier, W. (2011).

Heuristic decision making

Annual Review of Psychology, 62(1), 451-482.

[本文引用: 2]

Gigerenzer, G., Reb, J., & Luan, S. H. (2022).

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Annual Review of Organizational Psychology and Organizational Behavior, 9(1), 171-198.

[本文引用: 1]

Gillespie, M., & Peterson, B. L. (2009).

Helping novice nurses make effective clinical decisions: The situated clinical decision-making framework

Nursing Education Perspectives, 30, 164-170.

PMID:19606659      [本文引用: 2]

The nature of novice nurses' clinical decision-making has been well documented as linear, based on limited knowledge and experience in the profession, and frequently focused on single tasks or problems. Theorists suggest that, with sufficient experience in the clinical setting, novice nurses will move from reliance on abstract principles to the application of concrete experience and to view a clinical situation within its context and as a whole. In the current health care environment, novice nurses frequently work with few clinical supports and mentors while facing complex patient situations that demand skilled decision-making. The Situated Clinical Decision-Making Framework is presented for use by educators and novice nurses to support development of clinical decision-making. It provides novice nurses with a tool that a) assists them in making decisions; b) can be used to guide retrospective reflection on decision-making processes and outcomes; c) socializes them to an understanding of the nature of decision-making in nursing; and d) fosters the development of their knowledge, skill, and confidence as nurses. This article provides an overview of the framework, including its theoretical foundations and a schematic representation of its components. A case exemplar illustrates one application of the framework in assisting novice nurses in developing their decision-making skills. Future directions regarding the use and study of this framework in nursing education are considered.

He, G. B., Li, S., & Liang, Z. Y. (2018).

Behavioral decision- making is nudging China toward the overall revitalization

Acta Psychologica Sinica, 50(8), 803-813.

[本文引用: 1]

[何贵兵, 李纾, 梁竹苑. (2018).

以小拨大: 行为决策助推社会发展

心理学报, 50(8), 803-813.]

DOI:10.3724/SP.J.1041.2018.00803      [本文引用: 1]

作为《心理学报》“以小拨大:行为决策助推社会发展”专栏的开篇, 本文尝试简要介绍助推含义和发展历程, 分析助推的必要性, 小结助推的主要方法和应用领域, 评述助推研究在提升民众的健康、财富、幸福等方面“以小拨大”的作用, 澄清关于助推的若干争议, 并对研究者开展助推研究提出了若干建议。在文章的最后, 我们简要勾勒了本专栏论文的主要内容, 讨论了助推研究在国内起步发展的方向, 冀望更多的心理学工作者加入到“助推研究”的行列。

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[景顺长城, 富国基金, 交银施罗德. (2021). 公募权益类基金投资者盈利洞察报告. https://www.fullgoal.com.cn/contents/2021/10/21-c36271d311864fbd9792344c36fdb541.html]

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Process models deserve process data: Comment on Brandstätter, Gigerenzer, and Hertwig (2006)

Psychological Review, 115(1), 263-273.

DOI:10.1037/0033-295X.115.1.263      PMID:18211202      [本文引用: 1]

Comments on the article by E. Brandstätter, G. Gigerenzer, and R. Hertwig. Resolution of debates in cognition usually comes from the introduction of constraints in the form of new data about either the process or representation. Decision research, in contrast, has relied predominantly on testing models by examining their fit to choices. The authors examine a recently proposed choice strategy, the priority heuristic, which provides a novel account of how people make risky choices. The authors identify a number of properties that the priority heuristic should have as a process model and illustrate how they may be tested. The results, along with prior research, suggest that although the priority heuristic captures some variability in the attention paid to outcomes, it fails to account for major characteristics of the data, particularly the frequent transitions between outcomes and their probabilities. The article concludes with a discussion of the properties that should be captured by process models of risky choice and the role of process data in theory development.(c) 2008 APA, all rights reserved

Ji, Y., Kong, Z. Y., Deng, Y. Y., Chen, J. X., Liu, Y., & Zhao, L. (2022).

The role of eye tracker in teaching video-assisted thoracoscopic surgery: The differences in visual strategies between novice and expert surgeons in thoracoscopic surgery

Annals of Translational Medicine, 10(10), Article e592.

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Larrick, R. P., & Feiler, D. C. (2016).

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In G. B. Keren, & G. Wu (Eds.), Wiley Blackwell handbook of judgment and decision making (pp. 696-722). MA: Blackwell.

[本文引用: 1]

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[冷静, 刘伟臻, 侯东敏, 司继伟. (2017).

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心理发展与教育, 33(3), 282-288.]

[本文引用: 2]

Lian, R., Meng, Y. F., & Liao, M. L. (2003).

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[本文引用: 2]

[连榕, 孟迎芳, 廖美玲. (2003).

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心理科学, 26(1), 28-31.]

[本文引用: 2]

Liao, K. C., Zhang, Y. C., Lei, H. Y., Peng, G., & Kong, W. (2022).

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Frontiers in Psychology, 13, Article e842277.

[本文引用: 1]

Liu, Y. F. (2022).

The essence of bounded rationality and debate over its value

Acta Psychologica Sinica, 54(11), 1293-1309.

DOI:10.3724/SP.J.1041.2022.01293      [本文引用: 1]

<p id="p00005">Bounded rationality theory derives from contemporary cognitive psychology, manifests itself in economics, and radiates to many disciplines. However, different opinions exist on what bounded rationality is and what it means to people, not only causing confusion in theory but also bringing confusion in practice.</p> <p id="p00010">The purpose of this study is to: (1) clarify the essential meaning of bounded rationality from the philosophical and historical backgrounds of human rational evolution; (2) put forward different views on the value of bounded rationality; (3) summarize the far-reaching historical significance and theoretical value of existing achievements.</p> <p id="p00015">The author points out that bounded rationality is not the optimization under constraint, not to mention the irrationality. In essence, it is an objective description of the level of human rational evolution and development so far, that is, human beings are rational either in the attitude to reality or in the ability to recognize and transform reality. However, limits to human rationality are observed. Bounded rationalists question popular rationalism in contemporary social science and the reliability of the methodology and knowledge system derived from it, but they do not question rationality itself. They eliminate the dualism thinking mode of rationalism or irrationalism in history, which provides us with a new perspective to understand the nature of rationality from the resource, quantitative, and dynamic development views. In the sense of value rationality, bounded rationality is defective, but in the sense of instrumental rationality, bounded rationality is reasonable, so finding a proper balance point between them is necessary.</p> <p id="p00020">The concept of bounded rationality in psychology and its extensive influence have led to another human rational evolution after the &#x0201c;probability revolution&#x0201d; of the Renaissance. It is one of the most important contributions made by this discipline to the treasure house of human thought and knowledge. It not only has far-reaching historical significance but also has interdisciplinary methodological significance.</p>

[刘永芳. (2022).

有限理性的本质辨析与价值之争

心理学报, 54(11), 1293-1309.]

DOI:10.3724/SP.J.1041.2022.01293      [本文引用: 1]

有限理性不是受约束条件下的最优化, 更不能等同于非理性。从本质上说, 它是对迄今为止人类理性进化和发展水平的客观描述, 意味着无论在对待现实的态度上, 还是在认识和改造现实的能力上, 人都是理性的, 但人的理性是有限度的。有限理性观质疑当代社会科学中流行的强势理性观及其推演出来的方法论和知识体系的可靠性, 但并不质疑人的理性本身, 摆脱了历史上形形色色的理性论或非理性论非此即彼的二元论思维模式, 为我们提供了从资源观、量化观及动态发展观角度理解和把握人类理性本质的新视角。在价值理性意义上, 有限理性是有缺陷的, 但在工具理性意义上, 有限理性具有合理性, 需要在二者之间寻找适当的均衡点。心理学的有限理性研究及其产生的广泛影响酿成了继文艺复兴的概率革命之后又一次人类理性观的革命, 是这门学科为人类知识和思想宝库做出的最重要的贡献之一, 不仅具有深远的历史意义, 而且具有跨学科的方法论意义。

Lohse, G. L., & Johnson, E. J. (1996).

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Organizational Behavior and Human Decision Processes, 68(1), 28-43.

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Luo, Y. Y., & Ren, T. (2015).

Management mode, investment style and fund performance: An evidence from Chinese Mutual Funds

Modern Finance and Economics-Journal of Tianjin University of Finance and Economics, 35(4), 22-33.

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[骆盈盈, 任颋. (2015).

基金管理模式、投资风格与经营绩效:来自中国公募基金探索性研究

现代财经(天津财经大学学报), 35(4), 22-33.]

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Mei, G. X., Xiao, X., Chen, S. Y., Gou, L. N., & Li, X. Y. (2021).

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Journal of Guizhou Normal University (Natural Sciences), 39(4), 98-103.

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[梅高兴, 肖寻, 陈仕语, 苟丽娜, 李席英. (2021).

中文版工作记忆容量测量任务——“自动化运算广度任务”的信效度检验

贵州师范大学学报(自然科学版), 39(4), 98-103.]

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Cognitive neural characteristics of professional action video game players

Advances in Psychological Science, 31(1), 127-144.

DOI:10.3724/SP.J.1042.2023.00127      [本文引用: 1]

<p id="p00010">Action video games (AVG) are probably one of the most popular and mentally challenging games in e-sports. The skill profile of AVG's professional players is unclear. The professional players and players ranked in the top 7% of their games were both of the professionals in this review. The cross-sectional studies incorporating professionals compared to non-professional players and the intervention studies with AVG were searched to analyze the cognitive and neural characteristics of professionals. According to the selected studies, professional action video game players had faster selective attention, better sustained attention and multiple-object tracking performance. Professional players also had better working memory capacity. In particular, the spatial working memory capacity advantage was prominent. In addition, the professionals were less susceptible to the attentional blink effect. However, the current findings for professional players in attentional inhibition and mental flexibility were inconclusive. A little evidence showed potential advantages for action video game players in terms of mathematical and reasoning abilities.</p> <p id="p00015">The better attentional performance of the professionals may be related to the higher P3 amplitude of event-related potential (ERP). The working memory capacity of the professionals was associated with plastic changes in the dorsolateral prefrontal cortex and right posterior parietal cortex. These plastic changes may be the neurological features that are linked to their excellent visuospatial abilities. The ERP results also revealed that the differences in the contralateral delay activity (CDA) component between professionals and amateurs, suggesting that the professionals had better working memory capacity. In addition, professionals also had enhanced resting-state intra-network functional connectivity of the Central Executive Network. And the enhanced inter-network functional connectivity between the Central Executive Network and Salience Network in professionals reflected the advantages of professionals in information integration.</p> <p id="p00020">According to the intervention studies with AVG, the attention and working memory capabilities, as well as mathematical skills can be improved by AVG training. The mechanism of improvement may be that the AVG play did not teach any one particular skill but instead increases the ability to extract patterns or regularities in the environment. This enhanced learning capability was termed learning to learn. However, the overall duration of game training in intervention studies tended to be less than 30 days. Accordingly, the degree of cognitive promotion from AVG training is not enough to bridge the cognitive gap between professional players and novices.</p> <p id="p00025">In terms of the prediction of game performance by cognitive ability, the relatively basic cognitive abilities such as attention and working memory have low predictive power for the player’s game performance. Any kind of cognitive ability could only explain less than 10% of the variance of player’s rankings. In traditional sports, sports-specific tasks refer to tests that include information about sports scenarios. And there was a greater discriminating effect for sport-specific task compared to general ones. The cognitive tests in AVG did not incorporate information from game scenarios which still stayed on general cognitive tests. What’s more, decision-making ability test is a good way to distinguish the level of players. The weak predictive power in AVG may be limited by the lack of research on decision making or the anticipation task. Therefore, these relatively basic cognitive abilities did not distinguish or predict the player’s game performance very well. Whether they were specific cognitive tests or decision making tests, they contained information about real-life sports scenarios. This real-world information in the sports scene is essentially Chunking or patterns. And it was these patterns that experts hold. Chunking theory may explain the phenomenon of the low predictive power of game performance by cognitive abilities. That is, the player's long-term memory of the game lineup, the spatial position of the characters in the game confrontation, etc. The abundant chunking of game confrontation reserved in the long-term memory is the more important cognitive feature of professionals. The basic cognitive ability may not be as important to the player's game performance as the player's chunking reserved in long-term memory. In the future, we can extend the cognitive studies of the decision-making, chunking or patterns recognizing based on the spatial location of characters.</p>

[苗浩飞, 迟立忠. (2023).

动作视频游戏专业玩家的认知神经特征

心理科学进展, 31(1), 127-144.]

DOI:10.3724/SP.J.1042.2023.00127      [本文引用: 1]

动作视频游戏是电子竞技中受众最广、心智挑战最高的游戏项目之一。目前对动作视频游戏专业玩家的能力特征了解尚不清晰。以职业选手和排名较高的玩家为对象, 横断研究发现动作视频游戏专业玩家具有更快的注意选择、更稳定的持续注意、更好的注意瞬脱表现、更高的多目标追踪能力和工作记忆容量。专业玩家更好的注意表现主要与更高的P3波幅有关, 工作记忆表现与背外侧前额叶和右后顶叶等可塑性变化有关。此外, 专业玩家还存在中央执行网络与多个脑网络间的功能连接增强。目前游戏训练对认知的促进程度尚不足以弥补专业玩家和新手的认知差距。基础的认知能力对玩家游戏表现的预测有限。未来可扩展更高级的游戏决策, 游戏组块或游戏模式的认知研究。

Ognjanovic, S., Thüring, M., Murphy, R. O., & Hölscher, C. (2019).

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Display clutter is a widely studied phenomenon in ergonomics, where information density and other properties of task-relevant visualizations are related to effective user performance and visual attention. This paper examines the impact of clutter in the context of financial stock visualizations. Depending on their expertise, traders can use a variety of different cues to judge the current and future value of a stock and to assess its riskiness. In our study, two groups of participants (novices and experts) judge the riskiness of 28 pairs of stocks under two clutter conditions (low and high). Consistency of judgments and group concordance serve as measures for judgment performance, while mean fixation duration, fixation frequency, and transition matrix density are employed to capture visual attention. Our results reveal significant effects of display clutter and expertise on both the performance measures as well as the visual attention measures.Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.

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The objectives of this study are to elicit and document descriptions of emergency physician expertise, to characterize cognitive differences between novice and expert physicians, and to identify areas in which novices' skill and knowledge gaps are most pronounced. The nature of the differences between novices and experts needs to be explored to develop effective instructional modalities that accelerate the learning curve of inexperienced physicians who work in high-complexity environments.We interviewed novice emergency physicians (first-year residents) and attending physicians with significant expertise, working in an academic Level I trauma center in Southern California. With cognitive task analysis, we used task diagrams to capture nonroutine critical incidents that required the use of complex cognitive skills. Timelines were constructed to develop a detailed understanding of challenging incidents and the decisions involved as the incident unfolded, followed by progressive deepening to tease out situation-specific cues, knowledge, and information that experts and novices used. A thematic analysis of the interview transcripts was conducted to identify key categories. Using classification techniques for data reduction, we identified a smaller set of key themes, which composed the core findings of the study.Five interns and 6 attending physicians participated in the interviews. Novice physicians reported having difficulties representing the patient's story to attending physicians and other health care providers. Overrelying on objective data, novice physicians use linear thinking to move to diagnosis quickly and are likely to discount and explain away data that do not "fit" the frame. Experienced physicians draw on expertise to recognize cues and patterns while leaving room for altering or even changing their initial diagnosis. Whereas experts maintain high levels of spatial, temporal, and organizational systems awareness when overseeing treatment modalities of multiple patients, novices have difficulty seeing and maintaining the "big picture."Novice physicians use sense-making styles that differ from those of experts. Training novices to respond to the high cognitive demand of complex environments early in their careers requires instructional modalities that not only increase their knowledge base but also accelerate the integration of knowledge and practice. Simulation and custom-designed avatar-mediated virtual worlds are a promising new technology that may facilitate such training. Future research should expand on the results of this study through the use of larger sample sizes and interviews conducted at multiple sites to increase generalizability.Copyright © 2012. Published by Mosby, Inc.

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近来,在决策与推理的研究中,研究者提出了双系统作用模型:基于直觉的启发式系统和基于理性的分析系统。启发式系统加工速度较快,不占用或占用很少的心理资源,容易受背景相似性、刻板印象的影响;分析系统加工速度慢,占用较多的心理资源,遵从逻辑和规则,而且两个系统有不同进化历史和神经基础。该文根据已有的相关研究,综述了双系统在决策与推理中可能的作用机制、相互关系、个体差异,同时指出了目前研究存在的不足

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<p>Previous chess studies have found that the experienced chess players who are better than novices on memorizing chess board show superior perceptual encoding advantage. However, the Chinese chess have the similar expertise superior advantage? The present research designed three experiments to explore whether Chinese chess experts performed better on perceptual encoding, chess board memory, and detection than novices. Ten Chinese chess players who have already got more than 10-years experiences were regarded as experienced players. Fifteen college students who could understand the basic rules of Chinese chess were recruited as novices. EyeLink 1000 desktop eye tracker with 1000 Hz sample rate was used to record participants&rsquo; eye movement. Materials were the real Chinese chess playing-board pictures with 14 pieces on board. Each board had seven red and seven blue pieces. All three experimental materials were assessed by two experienced players on the authenticity and difficulty. In experiment 1, we presented random chess board or real chess board to participants. Each board presented for five seconds. Then, we asked participants to reproduce what they have seen on a real chess board. All the eye fixation data were recorded during the 5s viewing. In experiment 2, we used moving window paradigm to control their visual field size, including one piece size (1.3 degree visual angle), four pieces size (2.9 degree) and 16 pieces size (5.1 degree), to explore whether the experienced players could use the parafovea to process and extract information from chess board. Experiment 3 used flicker paradigm to investigate whether experienced players could notice the change much faster than novices and use their parafovea to fixate the changed pieces before their oral reports. Results of experiment 1 suggested that experienced Chinese chess players could recall much more pieces in the real chess board and random chess board than novices. In addition, experienced players showed wider saccade span and greater pupil size than novices. Consistent with the previous studies, the experienced chess players fixated more between pieces rather than on the pieces, but the novices allocated more attention on the pieces. Experiment 2 showed that, the experienced players can take advantage of parafoveal processing (16 and 4-piece window) to remember more pieces than the fovea condition (one piece window); but the novices did not show this difference. The eye movement data also showed that the experienced players had wider saccade span than novices when pieces in the parafovea (16 pieces window). Results of experiment 3 showed that the experienced players perceived changed pieces faster and their correct rate were higher than novices. For the changed pieces, the eye movement data indicated that experienced chess players could perceive changes quicker than novices with fovea and parafovea. In conclusion, compared to novices, experienced Chinese chess players can remember and reproduce more chess pieces than novices. Second, experienced players allocate more attention on between pieces based on their chess chunks and templates. Third, experienced Chinese chess players have wider visual span, and can use parafovea to encode information from chess board. Finally, Chinese experienced chess players can perceive changed pieces quickly and more accurately, showing superior perceptual advantage. In sum, consistent with the chess studies, Chinese chess did have expertise superior advantage and superior perceptual encoding advantage.</p>

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利用过程追踪技术实现对&ldquo;决策过程&rdquo;的追踪, 或能真正解答&ldquo;人类是如何做出决策&rdquo;这一科学问题。在各种过程追踪技术中, 眼动技术由于具有无干扰性、适用范围广泛、采集信息多样等独一无二的优势, 已被广泛应用于各种决策研究中, 为验证和比较不同决策理论的不同假设和预测做出了贡献。本文介绍了眼动技术如何被应用于验证补偿性决策理论与非补偿性决策理论对风险决策过程的不同假设, 眼动技术如何用于检验多次决策与单次决策的决策过程差异, 以及眼动技术如何用于检验&ldquo;剔除&ndash;关注模型&rdquo;与&ldquo;齐当别决策模型&rdquo;对多属性决策中共享信息发挥作用机制的不同预测。

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With in-depth exploration of core issues and the development of information technology, process information has been receiving more and more attention in decision making researches in last 50 years. Process technologies mainly include Mouselab, Eye Track, and Decision Moving Window (DMW). Mouselab and Eye Track have been used in varieties of decision tasks to test prevailing decision-making theories. DMW is developed recently and combines the advantages of both Mouselab and Eye Tracking. Its scope of application needs to be extended in more researches. In future studies, the comprehensive use of different technologies will help avoid the defect of single technology, separate the impact of the research technology from people&rsquo;s behavior and improve the validity of studies.

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在过去50年的决策研究中, 随着对核心问题的深入探索和信息技术的发展, 决策过程信息得到了越来越多的重视。过程研究技术主要包括鼠标实验室技术、眼动技术及新提出的决策移窗技术。鼠标实验室技术和眼动技术已被用于解决多种决策问题。决策移窗技术结合了前两种技术的优势, 其适用范围需在日后研究中进行更多探索。在未来的研究中, 多种技术的结合使用将有助于回避单一技术的缺陷, 分离研究方法对于被试行为的影响, 提高研究效度。

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[周蕾, 李纾, 许燕, 梁竹苑. (2014).

决策风格的理论发展及建构: 基于信息加工视角

心理科学进展, 22(1), 112-121.]

DOI:10.3724/SP.J.1042.2014.00112      [本文引用: 1]

决策风格是人们在决策中表现出来的习惯性或独特的行为模式, 对决策、管理等领域均有重要影响。近年兴起的决策风格理论主要基于个体信息加工策略, 如基于双加工理论和基于后悔情绪的决策风格模型等。决策风格对个体决策的影响表现在决策策略与偏差、情绪和无意识加工等方面。该领域在诸如决策风格的主要理论、测量工具和理论检验等方面亦取得积极进展, 未来研究方向应注意基于双加工理论和进化心理学建构决策风格理论。

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