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Engagement Maximization

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  • Benjamin H'ebert
  • Weijie Zhong

Abstract

We study a Bayesian agent receiving signals over time and then acting. The agent chooses when to stop and act, and prefers to act earlier all else equal. The signals are determined by a principal, who maximizes engagement (the total attention paid by the agent). We show that engagement maximization minimizes the agent's welfare, induces excessive information acquisition (relative to an agent-optimal benchmark), and leads to extreme beliefs. The principal optimally sends only "suspensive signals" that lead the agent to become "less certain than the prior" and "decisive signals" that lead the agent to stop immediately.

Suggested Citation

  • Benjamin H'ebert & Weijie Zhong, 2022. "Engagement Maximization," Papers 2207.00685, arXiv.org, revised Sep 2024.
    • Handle: RePEc:arx:papers:2207.00685
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    References listed on IDEAS

    as
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    More about this item

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D86 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Economics of Contract Law

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