Attribute-Based Choice

Alternative-based approaches to decision making generate overall values for each option in a choice set by processing information within options before comparing options to arrive at a decision. By contrast, attribute-based approaches compare attributes (such as monetary cost and time delay to receipt of a reward) across options and use these attribute comparisons to make a decision. Because they compare attributes, they may not use all available information to make a choice, which categorizes many of them as heuristics. Choice data have suggested that attribute-based models can better predict choice compared to alternative-based models in some situations (e.g., when there are many options in the choice set, when calculating an overall value for an option is too cognitively taxing). Process data comparing alternative-based and attribute-based processing obtained from eye-tracking and mouse-tracking technology support these findings. Data on attribute-based models thus align with the notion of bounded rationality that people make use of heuristics to make good decisions when under time pressure, informational constraints, and computational constraints. Further study of attribute-based models and processing would enhance our understanding of how individuals process information and make decisions