Dynamic cognitive models of intertemporal choice.

Area of Science:

• Cognitive Psychology
• Decision Science
• Behavioral Economics

Background:

• Traditional intertemporal choice models are static and deterministic, assuming alternative-wise processing.
• Recent research emphasizes dynamic, probabilistic intertemporal choice with attribute-wise processing.
• Current dynamic models primarily use evidence accumulation frameworks.

Purpose of the Study:

• To develop and compare novel dynamic models for intertemporal choice.
• To extend the random utility framework to include response dynamics.
• To evaluate models using both choice and response time data.

Main Methods:

• Developed two novel dynamic models: one lexicographic and noncompensatory, another based on random utility and discrimination thresholds.
• Compared these models with an existing decision field theory model.
• Fit models to empirical choice and response time data simultaneously.

Main Results:

• All three models accommodated key behavioral regularities in intertemporal choice.
• Models based on random utility and discrimination thresholds showed superior performance when fitting choice and response time data.
• Significant individual differences in choice dynamics were observed.

Conclusions:

• The random utility framework can be successfully extended to model response dynamics in intertemporal choice.
• This approach offers a viable alternative to the evidence accumulation framework for decision-making dynamics.
• Simultaneous analysis of choice and response time data enhances model selection accuracy.