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A computational model of food choice: Utility optimization through external cuing and heuristic search

By Lucie Yang

The field of economics tends to view decision-making through a lens of assumed rationality and utility maximization. Unfortunately, choices in reality tend to be more complicated than perfect conscious value assignment. One such type of decision-making is food choice, which incorporates not only many inherent values (health, taste, price, energy), but also exists in a world of many external influences (marketing, social pressure). The details of the space in which choices are made can be highly influential, disrupting the typical top-down attentional decision-making assumed with a homo economicus. This paper seeks to utilize a behavioral experiment, eye-tracking, and a novel computational model (the drift diffusion model) in an effort to explore how humans make food decisions. The drift diffusion model links the metrics, reaction time, gaze fixations, and eye movement path length and frequency to the probability of subsequently choosing each item. The model takes into account not only the intrinsic attractiveness of each item, but also the context surrounding them, creating group distributions as well as individual distributions for parameters of the decision process. This paper aims to look at various aspects of food decisions: how do personal internal states, visual salience, and external cues effect how one weights the multiple value characteristics of food.

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Advisor: Kent Kimbrough, Philip Sadowski | JEL Codes: D8, D80, D87 | Tagged: Decision-Making, Drift Diffusion Model, Food Consumption, Neuroeconomics

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