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Weighting or aggregating? Investigating information processing in multi-attribute choices
Mesfin G Genie1,2, Nicolas Krucien3, Mandy Ryan1
1Health Economics Research Unit, University of Aberdeen, Aberdeen, UK.
Health Economics
|March 19, 2021
Summary
Individuals often simplify complex choices by aggregating attributes into meta-attributes. This attribute aggregation (AA) model improves understanding of decision-making and economic valuation, especially when cognitive load is high.
Area of Science:
- Behavioral Economics
- Decision Science
- Cognitive Psychology
Background:
- Economic valuation typically assumes individuals process all attributes in multi-attribute choices.
- Cognitive demands of processing numerous attributes can lead to simplified decision-making strategies.
- Alternative decision rules, such as attribute aggregation, may be employed to reduce cognitive load.
Purpose of the Study:
- To develop and test a new model of multi-attribute choice incorporating attribute aggregation (AA).
- To investigate the conditions under which individuals are likely to use AA.
- To assess the impact of AA on model fit and welfare estimates in economic valuation.
Main Methods:
- Development of a theoretical model where individuals aggregate multi-attribute information into meta-attributes.
- Application of the AA model to a choice experiment (CE) dataset.
- Statistical analysis to determine factors influencing the probability of adopting AA and its effect on model fit.
Main Results:
- Accounting for attribute aggregation (AA) significantly improves the fit of choice models.
- AA is more probable with homogenous attribute information, shorter participant response times, and failed dominance tests.
- The adoption of AA influences welfare estimates derived from choice experiments.
Conclusions:
- Attribute aggregation (AA) is a prevalent information processing rule in multi-attribute decision-making.
- Models of economic choice should account for cognitive shortcuts like AA to accurately reflect behavior.
- Ignoring AA can lead to biased welfare estimates and an incomplete understanding of consumer choices.
Keywords:
attributes aggregationchoice experimentchoice modellinginformation processingmulti-attribute choicesMore Related Videos
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