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Attention Capture

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  • Andrew Koh
  • Sivakorn Sanguanmoo

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.

Suggested Citation

  • Andrew Koh & Sivakorn Sanguanmoo, 2022. "Attention Capture," Papers 2209.05570, arXiv.org, revised Sep 2024.
    • Handle: RePEc:arx:papers:2209.05570
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    References listed on IDEAS

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    1. Dirk Bergemann & Stephen Morris, 2013. "Robust Predictions in Games With Incomplete Information," Econometrica, Econometric Society, vol. 81(4), pages 1251-1308, July.
    2. Jeffrey C. Ely & Martin Szydlowski, 2020. "Moving the Goalposts," Journal of Political Economy, University of Chicago Press, vol. 128(2), pages 468-506.
    3. Sims, Christopher A., 2003. "Implications of rational inattention," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 665-690, April.
    4. repec:cwl:cwldpp:1821rrr is not listed on IDEAS
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