A Behavioral Characterization of the Drift Diffusion Model and Its Multialternative Extension for Choice Under Time Pressure

Carlo Baldassi (), Simone Cerreia-Vioglio, Fabio Maccheroni (), Massimo Marinacci and Marco Pirazzini ()
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Carlo Baldassi: Department of Decision Sciences, Bocconi University, 20136 Milan, Italy; Bocconi Institute for Data Science and Analytics (BIDSA), Bocconi University, Milan, Italy 20136; Artificial Intelligence Lab (ARTLAB), Bocconi University, Milan, Italy 20136;
Fabio Maccheroni: Department of Decision Sciences, Bocconi University, 20136 Milan, Italy; Artificial Intelligence Lab (ARTLAB), Bocconi University, Milan, Italy 20136; Innocenzo Gasparini Institute for Economic Research (IGIER), Bocconi University, Milan, Italy 20136
Marco Pirazzini: Department of Decision Sciences, Bocconi University, 20136 Milan, Italy; Artificial Intelligence Lab (ARTLAB), Bocconi University, Milan, Italy 20136;

Management Science, 2020, vol. 66, issue 11, 5075-5093

Abstract: In this paper, we provide an axiomatic foundation for the value-based version of the drift diffusion model (DDM) of Ratcliff, a successful model that describes two-alternative speeded decisions between consumer goods. Our axioms present a test for model misspecification and connect the externally observable properties of choice with an important neurophysiologic account of how choice is internally implemented. We then extend our axiomatic analysis to multialternative choice under time pressure. In a nutshell, we show that binary DDM comparisons of the alternatives, paired with Markovian exploration of the consideration set, approximately lead to softmaximization.

Keywords: drift diffusion model; softmax; neuroscience; marketing; consideration sets (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (12)

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