Attribute commensurability and context effects in preferential choice

IF 3.2 3区 心理学 Q1 PSYCHOLOGY, EXPERIMENTAL Psychonomic Bulletin & Review Pub Date : 2024-09-16 DOI:10.3758/s13423-024-02565-6
William M. Hayes, William R. Holmes, Jennifer S. Trueblood
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Abstract

Context effects in multi-alternative, multi-attribute choice are widely documented, but often elusive. We show that this elusiveness can arise in part from the way that choices are presented. To illustrate this, we use a modeling framework to predict how changes to the format of attribute values, specifically the commensurability of attribute values, influences attention allocation and consequently context effects. Guided by this framework, we show in two online choice experiments (total N = 954 adults) that manipulating the commensurability of attributes leads to different patterns of context effects. Robust attraction and compromise effects are found when attributes are incommensurable (e.g., CPU speed in GHz and RAM memory in GB, or quality ratings on different scales), and mostly null effects occur when attributes are commensurable (e.g., quality ratings on the same scale). Our findings show how the format of choice information can substantially alter the integration of that information and resulting choice patterns.

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优先选择中的属性可比性和语境效应
多选择、多属性选择中的情境效应被广泛记录,但往往难以捉摸。我们的研究表明,这种难以捉摸可能部分源于选择的呈现方式。为了说明这一点,我们使用了一个建模框架来预测属性值格式的变化,特别是属性值的可比性,是如何影响注意力分配并进而产生情境效应的。在这一框架的指导下,我们在两个在线选择实验(总人数 = 954 名成人)中表明,操纵属性的可比性会导致不同的情境效应模式。当属性不可通约时(例如,CPU 速度以 GHz 为单位,内存以 GB 为单位,或质量评级以不同的标度为单位),会出现稳健的吸引和折衷效应;而当属性可通约时(例如,质量评级以相同的标度为单位),则会出现大部分无效效应。我们的研究结果表明,选择信息的格式会在很大程度上改变信息的整合以及由此产生的选择模式。
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来源期刊
CiteScore
6.70
自引率
2.90%
发文量
165
期刊介绍: The journal provides coverage spanning a broad spectrum of topics in all areas of experimental psychology. The journal is primarily dedicated to the publication of theory and review articles and brief reports of outstanding experimental work. Areas of coverage include cognitive psychology broadly construed, including but not limited to action, perception, & attention, language, learning & memory, reasoning & decision making, and social cognition. We welcome submissions that approach these issues from a variety of perspectives such as behavioral measurements, comparative psychology, development, evolutionary psychology, genetics, neuroscience, and quantitative/computational modeling. We particularly encourage integrative research that crosses traditional content and methodological boundaries.
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