Hostname: page-component-78c5997874-j824f Total loading time: 0 Render date: 2024-11-03T03:27:17.118Z Has data issue: false hasContentIssue false
  • English
  • Français

A Dynamic Dual Process Model of Intertemporal Choice

Published online by Cambridge University Press:  23 December 2019

Adele Diederich  and
Wenjia Joyce Zhao
Adele Diederich*
Affiliation:
Jacobs University (Germany)
Wenjia Joyce Zhao
Affiliation:
University of Pennsylvania (USA)
*
*Correspondence concerning this article should be addressed to Adele Diederich, Jacobs University. Department of Life Sciences & Chemistry. 28759 Bremen (Germany). E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Dual process theories of decision making describe choice as the result of an automatic System 1, which is quick to activate but behaves impulsively, and a deliberative System 2, which is slower to activate but makes decisions in a rational and controlled manner. However, most existent dual process theories are verbal descriptions and do not generate testable qualitative and quantitative predictions. In this paper, we describe a formalized dynamic dual process model framework of intertemporal choice that allows for precise, experimentally testable predictions regarding choice probability and response time distributions. The framework is based on two-stage stochastic process models to account for the two postulated systems and to capture the dynamics and uncertainty involved in decision making. Using quasi closed form solutions, we illustrate how different factors (timing of System 1, time constraint, and preferences in both systems), which are reflected in the model parameters, influence qualitative and quantitative model predictions. Furthermore, we show how an existing static-deterministic model on intertemporal choice can be implemented in the framework allowing for testable predictions. The proposed framework can bring novel insights into the processes underlying intertemporal choices.

Keywords

dual process modelsIntertemporal Choicesequential samplingtwo-stage stochastic process
Type
Research Article
Information
The Spanish Journal of Psychology , Volume 22 , 2019 , E54
Copyright
Copyright © Universidad Complutense de Madrid and Colegio Oficial de Psicólogos de Madrid 2019 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

This paper grew out of an invited talk given at the VII Advanced International Seminar – Mathematical Models of Decision Making Processes: State of the Art and Challenges held at the School of Psychology, Universidad Complutense de Madrid (Spain) in October 2018 (http://eventos.ucm.es/go/DecisionMakingModels). This paper was supported by Deutsche Forschungsgemeinschaft (Grant /Award Number: DI 506/15-1).

How to cite this article:

Diederich, A., & Zhao, W. J. (2019). A dynamic dual process Model of Intertemporal Choice. The Spanish Journal of Psychology, 22. e54. Doi:10.1017/sjp.2019.53

References

Alós-Ferrer, C. (2018). A dual-process diffusion model. Journal of Behavioral Decision Making, 31, 203–2018. https://doi.org/10.1002/bdm.1960CrossRefGoogle Scholar
Baron, J., & Gürcay, B. (2017). A meta-analysis of response-time tests of the sequential two-systems model of moral judgment. Memory & Cognition, 45, 566–575. https://doi.org/10.3758/s13421-016-0686-8CrossRefGoogle ScholarPubMed
Brown, S., & Heathcote, A. (2005). A ballistic model of choice response time. Psychological Review, 112, 117–128. https://doi.org/10.1037/0033-295X.112.1.117CrossRefGoogle ScholarPubMed
Burks, S. V., Carpenter, J. P., Goette, L., & Rustichini, A (2009). Cognitive skills affect economic preferences, strategic behavior, and job attachment. Proceedings of the National Academy of Sciences, 106(19), 7745–7750. https://doi.org/10.1073/pnas.0812360106CrossRefGoogle ScholarPubMed
Busemeyer, J. R., & Diederich, A. (2002). Survey of decision field theory. Mathematical Social Sciences, 43, 345–370. https://doi.org/10.1016/S0165-4896(02)00016-1CrossRefGoogle Scholar
Busemeyer, J. R., & Townsend, J. T. (1993). Decision field theory: A dynamic cognition approach to decisión making. Psychological Review, 100, 432–459.CrossRefGoogle Scholar
Dai, J., & Busemeyer, J. R. (2014). A probabilistic, dynamic, and attribute-wise model of intertemporal choice. Journal of Experimental Psychology: General, 143(4), 1489–1514. https://doi.org/10.1037/a0035976CrossRefGoogle ScholarPubMed
Diederich, A. (1997). Dynamic stochastic models for decision making with time constraints. Journal of Mathematical Psychology, 41(3), 260–274. https://doi.org/10.1006/jmps.1997.1167CrossRefGoogle ScholarPubMed
Diederich, A. (2008). A further test on sequential sampling models accounting for payoff effects on response bias in perceptual decision tasks. Perception and Psychophysics, 70(2), 229–256.CrossRefGoogle Scholar
Diederich, A. (2016). A multistage attention-switching model account for payoff effects on perceptual decision tasks with manipulated processing order. Decision, 3(2), 81–114. https://doi.org/10.1006/jmps.1997.1167CrossRefGoogle Scholar
Diederich, A., & Oswald, P. (2014). Sequential sampling model for multiattribute choice alternatives with random attention time and processing order. Frontiers in Human Neuroscience, 8, Article 697. https://doi.org/10.3389/fnhum.2014.00697CrossRefGoogle ScholarPubMed
Diederich, A., & Oswald, P. (2016). Multi-stage sequential sampling models with finite or infinite time horizon and variable boundaries. Journal of Mathematical Psychology, 74, 128–145.CrossRefGoogle Scholar
Diederich, A., & Trueblood, J. S. (2018). A dynamic dual process model of risky decision making. Psychological Review, 125(2), 270–292. https://doi.org/10.1037/rev0000087CrossRefGoogle ScholarPubMed
Dolan, R. J., & Dayan, P. (2013). Goals and habits in the brain. Neuron, 80(2), 312–325. https://doi.org/10.1016/j.neuron.2013.09.007CrossRefGoogle Scholar
Evans, J. S. B. T. (2006). The heuristic-analytic theory of reasoning: Extension and evaluation. Psychonomic Bulletin & Review, 13(3), 378–395. https://doi.org/10.3758/BF03193858CrossRefGoogle ScholarPubMed
Evans, J. S. B. T. (2008). Dual-processing accounts of reasoning, judgment, and social cognition. Annual Review of Psychology, 59, 255–278.CrossRefGoogle ScholarPubMed
Figner, B., Knoch, D., Johnson, E. J., Krosch, A. R., Lisanby, S. H., Fehr, E., & Weber, E. U. (2010). Lateral prefrontal cortex and self-control in intertemporal choice. Nature Neuroscience, 13(5), 538–539. https://doi.org/10.1038/nn.2516CrossRefGoogle ScholarPubMed
Fudenberg, D., & Levine, D. K. (2006). A dual-self model of impulse control. American Economic Review, 96, 1449–1476. https://doi.org/10.1257/aer.96.5.1449CrossRefGoogle ScholarPubMed
Gawronski, B., & Creighton, L. A. (2013). Dual process theories. In Carlston, D. (Series Ed.), Oxford Library of Psychology. The Oxford handbook of social cognition (pp. 282–312). New York, NY: Oxford University Press.Google Scholar
Hammond, K. R. (1996). Human judgment and social policy. New York, NY: Oxford University Press.Google Scholar
Hare, T. A., Camerer, C. F., & Rangel, A. (2009). Selfes modulation of the vmPFC valuation system. Science, 324(5927), 646–648.CrossRefGoogle Scholar
Kahneman, D. (2011). Thinking, fast and slow. New York, NY: Farrar, Straus and Giroux.Google Scholar
Kahneman, D., & Frederick, S. (2002). Representativeness revisited: Attribute substitution in intuitive judgment. In Gilovich, T., Griffin, D., & Kahneman, D. (Eds.), Heuristics and biases: The psychology of intuitive judgment (pp. 49–81). New York, NY: Cambridge University Press.CrossRefGoogle Scholar
Keren, G., & Schul, Y. (2009). Two is not always better than one: A critical evaluation of two-system theories. Perspectives on Psychological Science, 4(6), 533–550. https://doi.org/10.1111/j.1745-6924.2009.01164.xCrossRefGoogle Scholar
Krajbich, I., Bartling, B., Hare, T., & Fehr, E. (2015). Rethinking fast and slow based on a critique of reaction-time reverse inference. Nature Communications, 6, Article 7455. https://doi.org/10.1038/ncomms8455CrossRefGoogle ScholarPubMed
Lindner, F., & Rose, J. (2017). No need for more time: Intertemporal allocation decisions under time pressure. Journal of Economic Psychology, 60, 53–70. https://doi.org/10.1016/j.joep.2016.12.004CrossRefGoogle Scholar
Loewenstein, G., O’Donoghue, T., & Bhatia, S. (2015). Modeling the interplay between affect and deliberation. Decision, 2, 55–81. https://doi.org/10.1037/dec0000029CrossRefGoogle Scholar
McClure, S. M., Laibson, D. I., Loewenstein, G., & Cohen, J. D. (2004). Separate neural systems value immediate and delayed monetary rewards. Science, 306(5695), 503–507. https://doi.org/10.1126/science.1100907CrossRefGoogle ScholarPubMed
McClure, S. M., Ericson, K. M., Laibson, D. I., Loewenstein, G., & Cohen, J. D. (2007). Time discounting for primary rewards. The Journal of Neuroscience, 27(21), 5796–5804. https://doi.org/10.1523/JNEUROSCI.4246-06.2007CrossRefGoogle ScholarPubMed
Mukherjee, K. (2010). A dual system model of preferences under risk. Psychological Review, 117, 243–255. https://doi.org/10.1037/a0017884CrossRefGoogle ScholarPubMed
Osman, M. (2004). An evaluation of dual-process theories of reasoning. Psychonomic Bulletin & Review, 11, 988–1010. https://doi.org/10.3758/BF03196730CrossRefGoogle Scholar
Peters, J., & Büchel, C. (2011). The neural mechanisms of inter-temporal decision-making: Understanding variability. Trends in Cognitive Sciences, 15(5), 227–239. https://doi.org/10.1016/j.tics.2011.03.002CrossRefGoogle ScholarPubMed
Rangel, A., Camerer, C., & Montague, P. R. (2008). A framework for studying the neurobiology of value-based decision making. Nature Reviews Neuroscience, 9(7), 545–556. https://doi.org/10.1038/nrn2357CrossRefGoogle ScholarPubMed
Rodriguez, C. A., Turner, B. M., & McClure, S. M. (2014). Intertemporal choice as discounted value accumulation. PLOS ONE, 9(2), e90138. https://doi.org/10.1371/journal.pone.0090138CrossRefGoogle ScholarPubMed
Schneider, W., & Shiffrin, R. M. (1977). Controlled and automatic human information processing: I. Detection, search, and attention. Psychological Review, 84, 1–66. https://doi.org/10.1037/0033-295X.84.1.1CrossRefGoogle Scholar
Shamosh, N. A., DeYoung, C. G., Green, A. E., Reis, D. L., Johnson, M. R., Conway, A. R. A., … Gray, J. R. (2008). Individual differences in delay discounting: Relation to intelligence, working memory and anterior prefrontal cortex. Psychological Science, 19(9), 904–911. https://doi.org/10.1111/j.1467-9280.2008.02175.xCrossRefGoogle ScholarPubMed
Sloman, S. A. (1996). The empirical case for two systems of reasoning. Psychological Bulletin, 119, 3–22. https://doi.org/10.1037/0033-2909.119.1.3CrossRefGoogle Scholar
Stanovich, K., & West, R. (2000). Individual differences in reasoning: Implications for the rationality debate? Behavioral and Brain Sciences, 23(5), 645–665. https://doi.org/10.1017/S0140525X00003435CrossRefGoogle ScholarPubMed
Zhao, W. J., Diederich, A., Trueblood, J. S., & Bhatia, S. (2019). Automatic biases in intertemporal choice. Psychonomic Bulletin & Review, 26, 661–668.CrossRefGoogle ScholarPubMed