Weighting or aggregating? Investigating information processing in multi‐attribute choices

Multi‐attribute choices are commonly analyzed in economics to value goods and services. Analysis assumes individuals consider all attributes, making trade‐offs between them. Such decision‐making is cognitively demanding, often triggering alternative decision rules. We develop a new model where indiv...

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Bibliographic Details
Published in:Health economics 2021-06, Vol.30 (6), p.1291-1305
Main Authors: Genie, Mesfin G., Krucien, Nicolas, Ryan, Mandy
Format: Article
Language:English
Subjects:
Accounting
Attributes
attributes aggregation
choice experiment
choice modelling
Dominance
Health economics
Information processing
multi‐attribute choices
Reaction time
Weighting
Welfare
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Summary:Multi‐attribute choices are commonly analyzed in economics to value goods and services. Analysis assumes individuals consider all attributes, making trade‐offs between them. Such decision‐making is cognitively demanding, often triggering alternative decision rules. We develop a new model where individuals aggregate multi‐attribute information into meta‐attributes. Applying our model to a choice experiment (CE) dataset, accounting for attribute aggregation (AA) improves model fit. The probability of adopting AA is greater for: homogenous attribute information; participants who had shorter response time and failed the dominance test; and for later located choices. Accounting for AA has implications for welfare estimates. Our results underline the importance of accounting for information processing rules when modelling multi‐attribute choices.
ISSN:1057-9230
1099-1050
DOI:10.1002/hec.4245