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Incentive design for temptation avoidance
Individuals are often faced with temptations that can lead them astray from long-term goals. We're interested in developing interventions that steer individuals toward making good initial decisions and then maintaining those decisions over time. In the realm of financial decision making, a particularly successful approach is the prize-linked savings account: individuals are incentivized to make deposits by tying deposits to a periodic lottery that awards bonuses to the savers. Although these lotteries have been very effective in motivating savers across the globe, they are a one-size-fits-all solution. We investigate whether customized bonuses can be more effective. We formalize a delayed-gratification task as a Markov decision problem and characterize individuals as rational agents subject to temporal discounting, costs associated with effort, and moment-to-moment fluctuations in willpower. Our theory is able to explain key behavioral findings in intertemporal choice. We created an online delayed-gratification game in which the player scores points by choosing a queue to wait in and patiently advancing to the front. Data collected from the game is fit to the model, and the instantiated model is then used to optimize predicted player performance over a space of incentives. We demonstrate that customized incentive structures can improve goal-directed decision making.
Students
Shruthi Sukumar (Computer Science, Colorado)
Camden Elliott-Williams (Computer Science, Colorado)
Collaborators
Shabnam Hakimi (Neuroscience, Duke)
Adrian F. Ward (McCombs School of Business, U. Texas Austin)