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The limit of targeting in networks

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  • Li, Jian
  • Zhou, Junjie
  • Chen, Ying-Ju

Abstract

This paper studies the value of network-based targeting within a class of network games with strategic complements, where the designer can target a group of seed players as first movers. We define an effectiveness index, called the relative network synergy equivalent (RNSE), to quantify the effect of a network-based targeting intervention relative to across-the-board peer effect enhancement. We show that, regardless of the targeting policies and network structures, a universal and tight upper bound for this index is 2≈1.414. This upper bound is robust to considerations of revenue maximization, costly seeding, random seeding as the alternative benchmark, and multiple stages of moves. Compared with network-based targeting, peer effect enhancing policy has the advantage of being agnostic to the network structure. In the case of small synergy, we provide comparative statics of the RNSE index concerning the network structures: fixing the targeting policy, increasing network links within the seeded group or the unseeded group will decrease the index; meanwhile, adding links across these two groups will increase the index. Our analysis sheds light on policy choices between network-based targeting and peer effect enhancing policies.

Suggested Citation

  • Li, Jian & Zhou, Junjie & Chen, Ying-Ju, 2022. "The limit of targeting in networks," Journal of Economic Theory, Elsevier, vol. 201(C).
  • Handle: RePEc:eee:jetheo:v:201:y:2022:i:c:s0022053122000084
    DOI: 10.1016/j.jet.2022.105418
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    More about this item

    Keywords

    Network games; Targeting; Strategic complements; Synergy;
    All these keywords.

    JEL classification:

    • D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory
    • D29 - Microeconomics - - Production and Organizations - - - Other
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design

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