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...
Guardado en:
| Autores principales: | , , |
|---|---|
| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Society for Judgment and Decision Making
2021
|
| Materias: | |
| Acceso en línea: | https://doaj.org/article/d8fb77dad0964670aea7eb8609903cc4 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| id |
oai:doaj.org-article:d8fb77dad0964670aea7eb8609903cc4 |
|---|---|
| record_format |
dspace |
| spelling |
oai:doaj.org-article:d8fb77dad0964670aea7eb8609903cc42021-11-29T22:45:18ZEstablishing the laws of preferential choice behavior1930-2975https://doaj.org/article/d8fb77dad0964670aea7eb8609903cc42021-11-01T00:00:00Zhttp://journal.sjdm.org/21/210112/jdm210112.pdfhttps://doaj.org/toc/1930-2975Mathematical 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.Sudeep BhatiaGraham LoomesDaniel ReadSociety for Judgment and Decision Makingarticledecision making mathematical and computational modeling risky choice multiattribute choice intertemporal choicenakeywordsSocial SciencesHPsychologyBF1-990ENJudgment and Decision Making, Vol 16, Iss 6, Pp 1324-1369 (2021) |
| institution |
DOAJ |
| collection |
DOAJ |
| language |
EN |
| topic |
decision making mathematical and computational modeling risky choice multiattribute choice intertemporal choicenakeywords Social Sciences H Psychology BF1-990 |
| spellingShingle |
decision making mathematical and computational modeling risky choice multiattribute choice intertemporal choicenakeywords Social Sciences H Psychology BF1-990 Sudeep Bhatia Graham Loomes Daniel Read Establishing the laws of preferential choice behavior |
| description |
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. |
| format |
article |
| author |
Sudeep Bhatia Graham Loomes Daniel Read |
| author_facet |
Sudeep Bhatia Graham Loomes Daniel Read |
| author_sort |
Sudeep Bhatia |
| title |
Establishing the
laws of preferential choice behavior |
| title_short |
Establishing the
laws of preferential choice behavior |
| title_full |
Establishing the
laws of preferential choice behavior |
| title_fullStr |
Establishing the
laws of preferential choice behavior |
| title_full_unstemmed |
Establishing the
laws of preferential choice behavior |
| title_sort |
establishing the
laws of preferential choice behavior |
| publisher |
Society for Judgment and Decision Making |
| publishDate |
2021 |
| url |
https://doaj.org/article/d8fb77dad0964670aea7eb8609903cc4 |
| work_keys_str_mv |
AT sudeepbhatia establishingthelawsofpreferentialchoicebehavior AT grahamloomes establishingthelawsofpreferentialchoicebehavior AT danielread establishingthelawsofpreferentialchoicebehavior |
| _version_ |
1718406892575784960 |