Establishing the laws of preferential choice behavior
Mathematical and computational decision models are powerful tools for studying choice behavior, and hundreds of distinct decision models have been proposed over the long interdisciplinary history of decision making research. The existence of so many models has led to theoretical fragmentation and re...
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| Autores principales: | , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Society for Judgment and Decision Making
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/d8fb77dad0964670aea7eb8609903cc4 |
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| Sumario: | Mathematical and
computational decision models are powerful tools for studying choice behavior,
and hundreds of distinct decision models have been proposed over the long
interdisciplinary history of decision making research. The existence of so many
models has led to theoretical fragmentation and redundancy, obscuring key
insights into choice behavior, and preventing consensus about the essential
properties of preferential choice. We provide a synthesis of formal models of
risky, multiattribute, and intertemporal choice, three important domains in
decision making. We identify recurring insights discovered by scholars of
different generations and different disciplines across these three domains, and
use these insights to classify over 150 existing models as involving various
combinations of eight key mathematical and computational properties. These
properties capture the main avenues of theoretical development in decision
making research and can be used to understand the similarities and differences
between decision models, aiding both theoretical analyses and empirical tests. |
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