TY - GEN
T1 - A Dynamic Tradeoff Model of Intertemporal Choice
AU - Dai, Junyi
AU - Pleskac, Timothy J.
AU - Pachur, Thorsten
N1 - Publisher Copyright:
© CogSci 2017.
PY - 2017
Y1 - 2017
N2 - The delay discounting perspective, which assumes an alternative-wise processing of attribute information, has long dominated research on intertemporal choice. Recent studies, however, have suggested that intertemporal choice is based on attribute-wise comparison. This line of research culminated in the tradeoff model (Scholten & Read, 2010; Scholten, Read, & Sanborn, 2014), which can accommodate most established behavioral regularities in intertemporal choice. One drawback of the tradeoff model, however, is that it is static, providing no account of the dynamic process leading to a choice. Here we develop a dynamic tradeoff model that can qualitatively account for empirical findings in intertemporal choice regarding not only choices but also response times. The dynamic model also outperforms the original, static tradeoff model when quantitatively fitting choices from representative data sets, and even outperforms the best-performing dynamic model derived from Decision Field Theory in Dai and Busemeyer (2014) when fitting both choices and response times.
AB - The delay discounting perspective, which assumes an alternative-wise processing of attribute information, has long dominated research on intertemporal choice. Recent studies, however, have suggested that intertemporal choice is based on attribute-wise comparison. This line of research culminated in the tradeoff model (Scholten & Read, 2010; Scholten, Read, & Sanborn, 2014), which can accommodate most established behavioral regularities in intertemporal choice. One drawback of the tradeoff model, however, is that it is static, providing no account of the dynamic process leading to a choice. Here we develop a dynamic tradeoff model that can qualitatively account for empirical findings in intertemporal choice regarding not only choices but also response times. The dynamic model also outperforms the original, static tradeoff model when quantitatively fitting choices from representative data sets, and even outperforms the best-performing dynamic model derived from Decision Field Theory in Dai and Busemeyer (2014) when fitting both choices and response times.
KW - dynamic models, random utility, discrimination threshold
KW - intertemporal choice
KW - tradeoff model
UR - http://www.scopus.com/inward/record.url?scp=85139567154&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85139567154
T3 - CogSci 2017 - Proceedings of the 39th Annual Meeting of the Cognitive Science Society: Computational Foundations of Cognition
SP - 265
EP - 270
BT - CogSci 2017 - Proceedings of the 39th Annual Meeting of the Cognitive Science Society
PB - The Cognitive Science Society
T2 - 39th Annual Meeting of the Cognitive Science Society: Computational Foundations of Cognition, CogSci 2017
Y2 - 26 July 2017 through 29 July 2017
ER -