Attention Capture

TL;DR

This paper provides a comprehensive analysis of how information can be optimally designed to capture attention over time, considering dynamic decision processes and the value of information.

Contribution

It introduces a unified framework characterizing optimal attention capture, including the structure of stopping times and the role of dynamic information structures.

Findings

Optimal attention capture depends on relative time preferences.

Sequentially optimal information structures induce stochastic beliefs.

Intertemporal commitment is unnecessary for optimality.

Abstract

We develop a unified analysis of how information captures attention. A decision maker (DM) faces a dynamic information structure and decides when to stop paying attention. We characterize the convex$\unicode{x2013}$order frontier and extreme points of feasible stopping times, as well as dynamic information structures which implement them. This delivers the form of optimal attentional capture as a function of the designer and DM's relative time preferences. Intertemporal commitment is unnecessary: sequentially optimal information structures always exist by inducing stochastic interim beliefs. We further analyze optimal attention capture under non instrumental value of information. Our results speak directly to the attention economy.