This paper introduces a contest model in which each player decides when to stop a privately observed Brownian motion with drift and incurs costs depending on his stopping time. The player who stops his process at the highest value wins a prize. Applications of the model include procurement...

This paper presents a strategic model of risk-taking behavior in contests. Formally, we analyze an n-player winner-take-all contest in which each player decides when to stop a privately observed Brownian Motion with drift. A player whose process reaches zero has to stop. The player with the...

During the recent COVID-19 pandemic, traditional (offline) chess tournaments were prohibited and instead held online. We exploit this as a unique setting to assess the impact of moving offline tasks online on the cognitive performance of individuals. We use the Artificial Intelligence embodied...