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Towards a brain-to-society systems model of individual choice

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An Erratum to this article was published on 07 November 2008

Abstract

Canonical models of rational choice fail to account for many forms of motivated adaptive behaviors, specifically in domains such as food selections. To describe behavior in such emotion- and reward-laden scenarios, researchers have proposed dual-process models that posit competition between a slower, analytic faculty and a fast, impulsive, emotional faculty. In this paper, we examine the assumptions and limitations of these approaches to modeling motivated choice. We argue that models of this form, though intuitively attractive, are biologically implausible. We describe an approach to motivated choice based on sequential sampling process models that can form a solid theoretical bridge between what is known about brain function and environmental influences upon choice. We further suggest that the complex and dynamic relationships between biology, behavior, and environment affecting choice at the individual level must inform aggregate models of consumer choice. Models using agent-based complex systems may further provide a principled way to relate individual and aggregate consumer choices to the aggregate choices made by businesses and social institutions. We coin the term “brain-to-society systems” choice model for this broad integrative approach.

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References

  • Ashby, F. G., & Townsend, J. T. (1986). Varieties of perceptual independence. Psychological Review, 93, 154–179. doi:10.1037/0033-295X.93.2.154.

    Article  Google Scholar 

  • Axtell, R. L., et al. (2002). Population growth and collapse in a multiagent model of the Kayenta Anasazi in Long House Valley. Proceedings of the National Academy of Sciences of the United States of America, 99(3), 7275–7279. doi:10.1073/pnas.092080799.

    Article  Google Scholar 

  • Bechara, A., & Damasio, A. (2004). The somatic marker hypothesis: A neural theory for economic decisions. Games and Economic Behavior, 1, 1–37 (Special issue on Neuroscience and Economics).

    Google Scholar 

  • Bernheim, B. D., & Rangel, A. (2004). Addiction and cue-triggered decision processes. The American Economic Review, 94(5), 1558–159. doi:10.1257/0002828043052222.

    Article  Google Scholar 

  • Berthoud, H.-R. (2002). Multiple neural systems controlling food intake and body weight. Neuroscience and Biobehavioral Reviews, 26, 393–428. doi:10.1016/S0149-7634(02)00014-3.

    Article  Google Scholar 

  • Böckenholt, U. (2007). Thurstonian-based analysis: past, present and future utilities. Psychometrika, 10, 1336–1350.

    Google Scholar 

  • Broberger, C. (2005). Brain regulation of food intake and appetite: Molecules and networks. Journal of Internal Medicine, 258, 301–327. doi:10.1111/j.1365-2796.2005.01553.x.

    Article  Google Scholar 

  • Busemeyer, J. R., & Diederich, A. (2002). Survey of decision field theory. Mathematical Social Sciences, 43, 345–370. doi:10.1016/S0165-4896(02)00016-1.

    Article  Google Scholar 

  • Busemeyer, J. R., & Townsend, J. T. (1993). Decision field theory: A dynamic-cognitive approach to decision making in an uncertain environment. Psychological Review, 100, 432–459. doi:10.1037/0033-295X.100.3.432.

    Article  Google Scholar 

  • Cacioppo, J. T., Bernston, G. G., Sheridan, J. F., & McClintock, M. K. (2000). Multilevel integrative analysis of human behavior: Social neuroscience and the complementing nature of social and biological approaches. Psychological Bulletin, 126(6), 829–843. doi:10.1037/0033-2909.126.6.829.

    Article  Google Scholar 

  • Chen, S., & Chaiken, S. (1999). The heuristic–systematic model in its broader context. In S. Chaiken, & Y. Trope (Eds.), Dual-process theories in social psychology (pp. 73–96). New York: Guildford.

    Google Scholar 

  • Chintagunta, P., Erdem, T., Rossi, P. E., & Wedel, M. (2006). Structural modeling in marketing: Review and assessment. Marketing Science, 25, 604–616. doi:10.1287/mksc.1050.0161.

    Article  Google Scholar 

  • Desmeules, R., Bechara, A., & Dubé, L. (2008). Subjective valuation and asymmetrical motivational systems: Implications of scope insensitivity for decision making. Journal of Behavioral Decision Making, 21, 211–224.

    Article  Google Scholar 

  • DeSarbo, W. S., Di Benedetto, C. A., Jedidi, K., & Song, M. (2006). Identifying sources of heterogeneity for empirically deriving strategic types: A constrained finite-mixture structural equation methodology. Management Science, 52, 909–924. doi:10.1287/mnsc.1060.0529.

    Article  Google Scholar 

  • Diederich, A. (1997). Dynamic stochastic models for decision making under time constraints. Journal of Mathematical Psychology, 41, 260–274. doi:10.1006/jmps.1997.1167.

    Article  Google Scholar 

  • Dubé, L., Le Bel, J., & Lu, J. (2005). Affect asymmetry and comfort food consumption. Physiology & Behavior, 86(4), 559–567. doi:10.1016/j.physbeh.2005.08.023.

    Article  Google Scholar 

  • Epstein, J. (2002). Modeling civil violence: An agent-based computational approach. Proceedings of the National Academy of Sciences of the United States of America, 99, 7243–7250. doi:10.1073/pnas.092080199.

    Article  Google Scholar 

  • Erden, T., Srinivasan, W., Amaldoss, P., Bajari, H., Che, T., et al. (2005). Theory driven choice models. Marketing Letters, 16, 225–237. doi:10.1007/s11002-005-5887-z.

    Article  Google Scholar 

  • Förster, J. (2002). How body feedback influences consumers’ evaluation of products. Journal of Consumer Psychology, 14, 416–426. doi:10.1207/s15327663jcp1404_10.

    Article  Google Scholar 

  • Fudenberg, D., & Levine, D. K. (1999). Conditional universal consistency. Games and Economic Behavior, 29, 104–130. doi:10.1006/game.1998.0705.

    Article  Google Scholar 

  • Faruk, G., & Pesendorfer, W. (2001). Temptation and Self-Control. Econometrica, 69, 1403–1435.

    Google Scholar 

  • Hammond, R. A., & Epstein, J. M.(2007). “Exploring price independent mechanisms in the obesity epidemic”. Center on Social and Economic Dynamics Working Paper, p. 48.

  • Herman, C. P., Roth, D. A., & Polivy, J. (2003). Added effects of the presence of others on food intake: A normative interpretation. Psychological Bulletin, 129(6), 873–886. doi:10.1037/0033-2909.129.6.873.

    Article  Google Scholar 

  • Huettel, S. A., Song, A. W., & McCarthy, G. (2005). Decisions under uncertainty: Probabilistic context influences activity of prefrontal and parietal cortices. The Journal of Neuroscience, 25, 3304–3311. doi:10.1523/JNEUROSCI.5070-04.2005.

    Article  Google Scholar 

  • Huk, A. C., & Shadlen, M. N. (2005). Neural activity in macaque parietal cortex reflects temporal integration of visual motion signals during perceptual decision making. The Journal of Neuroscience, 25(45), 10420–10436. doi:10.1523/JNEUROSCI.4684-04.2005.

    Article  Google Scholar 

  • Johnson, J. G., & Busemeyer, J. R. (2005). A dynamic computational model of preference reversal phenomena. Psychological Review, 112, 841–861. doi:10.1037/0033-295X.112.4.841.

    Article  Google Scholar 

  • Kalivas, P. W., & Volkow, N. D. (2005). The neural basis of addiction: A pathology of motivation and choice. American Journal of Psychiatry, 162, 8, 1403.

    Article  Google Scholar 

  • Killgore, W. D. S., Young, A. D., Femia, L. A., Bogorodzki, P., Rogowska, J., & Yurgelun-Todd, D. A. (2003). Cortical and limbic activation during viewing of high- versus low-calorie foods. NeuroImage, 19(4), 1381–1394. doi:10.1016/S1053-8119(03)00191-5.

    Article  Google Scholar 

  • Klucharev, V., Hytonen, K., Rijpkema, M., Smidts, A., and Fernandexz, G. (2008). An error of being different? Brain mechanisms of social norms. Working Paper, F. C. Donders Center for Cognitive Neuroimaging, Radbout University Nijmegen.

  • Knutson, B., Rick, S., Wimmer, G. E., Prelec, D., & Lowenstein, G. (2007). Neural predictors of purchases. Neuron, 53, 147–156. doi:10.1016/j.neuron.2006.11.010.

    Article  Google Scholar 

  • Laibson, D. (2001). A cue-theory of consumption. The Quarterly Journal of Economics, 116, 81–119. doi:10.1162/003355301556356.

    Article  Google Scholar 

  • Loewenstein, G., & O’Donoghue, T. (2004). Animal spirit: Affective and deliberative processes in economic behavior. Worker Paper, Carnegie Mellon University.

  • McClure, S. M., Li, J., Tomlin, D., Cypert, K. S., Montague, L. M., & Montague, P. R. (2004). Neural correlates of behavioral preference for culturally familiar drinks. Neuron, 44(2), 379–387. doi:10.1016/j.neuron.2004.09.019.

    Article  Google Scholar 

  • Mischel, W., Ebbesen, E. B., & Zeiss, A. R. (1972). Cognitive and attentional mechanisms in delay of gratification. Journal of Personality and Social Psychology Bulletin, 21, 204–218.

    Article  Google Scholar 

  • O’Doherty, J., et al. (2001). Abstract reward and punishment representations in the human orbitofrontal cortex. Nature Neuroscience, 4, 95–102. doi:10.1038/82959.

    Article  Google Scholar 

  • O’Donoghue, T., & Rabin, M. (1999). Doing it now or later. The American Economic Review, 89, 103–124.

    Google Scholar 

  • Otter, T., Rieskamp, J., Brazell, J. D., Hutchinson, W., Ruan, S., et al. (2008). Psychological processes underlying violations of Luce’s choice axiom. Marketing Letters (this issue).

  • Padoa-Schioppa, C., & Assad, J. A. (2006). Neurons in the orbitofrontal cortex encode economic value. Nature, 441, 223–226. doi:10.1038/nature04676.

    Article  Google Scholar 

  • Petty, R. E., & Cacciopo, J. T. (1986). The elaboration likelihood model of persuasion. In L. berkowitz (Ed.), Advances in experimental social psychology, vol 19 (pp. 123–205). New York: Academic.

    Chapter  Google Scholar 

  • Plassmann, H., O’Doherty, J., Shiv, B., & Rangel, A. (2008). Marketing actions can modulate neural representations of experienced processes. Proceedings of the National Academy of Sciences of the United States of America, 105(3), 1050–1054. doi:10.1073/pnas.0706929105.

    Article  Google Scholar 

  • Platt, M. L., & Glimcher, P. W. (1999). Neural correlates of decision variables in parietal cortex. Nature, 400, 233–238. doi:10.1038/22268.

    Article  Google Scholar 

  • Read, D., & van Leeuwen, B. (1998). Predicting hunger: The effect of appetite and delay on choice. Organizational Behavior and Human Decision Processes, 76, 189–205. doi:10.1006/obhd.1998.2803.

    Article  Google Scholar 

  • Rorie, A. E., & Newsome, W. T. (2005). A general mechanism for decision making in the human brain. Trends in Cognitive Sciences, 9(2), 41–43. doi:10.1016/j.tics.2004.12.007.

    Article  Google Scholar 

  • Schultz, W. (1998). Predictive reward signal of dopamine neurons. Journal of Neurophysiology, 80, 1–27.

    Google Scholar 

  • Small, D. M., Gotman, M. J., & Dagher, A. (2003). Feeding induced dopamine release in dorsal striatum correlates with meal pleasantness rating in healthy human volunteer. NeuroImage, 19, 1709–1715. doi:10.1016/S1053-8119(03)00253-2.

    Article  Google Scholar 

  • Sen, A. (1993). Internal consistency of choice. Econometrica, 61(3), 495–521. doi:10.2307/2951715.

    Article  Google Scholar 

  • Sengupta, J., & Zhou, R. (2007). Understanding impulsive eaters’ choice behaviors: The motivational influences of regulatory focus. JMR, Journal of Marketing Research, 44, 297–308. doi:10.1509/jmkr.44.2.297.

    Article  Google Scholar 

  • Shiv, B., Bechara, A., Levin, I., Alba, J. W., Bettman, J. R., et al. (2005). Decision neuroscience. Marketing Letters, 16, 375–386. doi:10.1007/s11002-005-5899-8.

    Article  Google Scholar 

  • Shiv, B., & Fedorikhin, A. (1999). Heart and mind in conflict: The interplay of affect and cognition in consumer decision making. The Journal of Consumer Research, 26(December), 278–292. doi:10.1086/209563.

    Article  Google Scholar 

  • Spitzer, M., Fischbacher, U., Herrberger, B., Gron, G., & Fehr, E. (2007). The neural signature of social norm compliance. Neuron, 48, 175–187.

    Google Scholar 

  • Strack, F., Werth, L., & Deutsch, R. (2006). Reflective and impulsive determinants of consumer behaviour. Journal of Consumer Psychology, 16(3), 205–216. doi:10.1207/s15327663jcp1603_2.

    Article  Google Scholar 

  • Sugrue, L. P., Corrado, G. S., & Newsome, W. T. (2005). Choosing the greater of two goods: Neural currencies for valuation and decision making. Nature Neuroscience, 6, 363–375.

    Article  Google Scholar 

  • Volkow, N. D., & O’ Brien, C. P. (2007). Issues for DSM-V: Should obesity be included as a brain disorder? The American Journal of Psychiatry, 164(5), 708–710.

    Article  Google Scholar 

  • Wise, R. A. (2004). Dopamine, learning and motivation. Nature Reviews. Neuroscience, 5, 483–494. doi:10.1038/nrn1406.

    Article  Google Scholar 

  • Wansink, B. (2006). Mindless eating: Why we eat more than we think. New York: Bantam.

    Google Scholar 

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Correspondence to Laurette Dubé.

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Authors include participants to the Brain-to-Society Systems of choice session at the Choice Symposium and members of the research team.

Contents of this publication do not necessarily reflect the views or policies of the National Institutes of Health.

An erratum to this article can be found at http://dx.doi.org/10.1007/s11002-008-9067-9

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Dubé, L., Bechara, A., Böckenholt, U. et al. Towards a brain-to-society systems model of individual choice. Mark Lett 19, 323–336 (2008). https://doi.org/10.1007/s11002-008-9057-y

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