Department of Social and Decision Sciences, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, USA.
Psychol Rev. 2013 Jul;120(3):522-43. doi: 10.1037/a0032457. Epub 2013 Apr 22.
This paper presents a theory of multi-alternative, multi-attribute preferential choice. It is assumed that the associations between an attribute and an available alternative impact the attribute's accessibility. The values of highly accessible attributes are more likely to be aggregated into preferences. Altering the choice task by adding new alternatives or by increasing the salience of preexisting alternatives can change the accessibility of the underlying attributes and subsequently bias choice. This mechanism is formalized by use of a preference accumulation decision process, embedded in a feed-forward neural network. The resulting model provides a unitary explanation for a large range of choice-set-dependent behaviors, including context effects, alignability effects, and less is more effects. The model also generates a gain-loss asymmetry relative to the reference point, without explicit loss aversion. This asymmetry accounts for all of the reference-dependent anomalies explained by loss aversion, as well as reference-dependent phenomena not captured by loss aversion.
本文提出了一种多选择、多属性偏好选择的理论。它假设属性与可用替代方案之间的关联会影响属性的可及性。高度可及属性的值更有可能被聚合到偏好中。通过添加新的替代方案或增加现有替代方案的显著性,可以改变基础属性的可及性,并随后影响选择。该机制通过使用偏好积累决策过程来形式化,该过程嵌入在前馈神经网络中。由此产生的模型为广泛的选择集依赖行为提供了一个单一的解释,包括上下文效应、对齐效应和少即是多效应。该模型还产生了相对于参考点的收益-损失不对称性,而无需明确的损失厌恶。这种不对称性解释了所有由损失厌恶所解释的参照点依赖异常现象,以及损失厌恶无法捕捉的参照点依赖现象。