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Optimal Design of Revenue‐Maximizing Position Auctions with Consumer Search

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  • Ying‐Ju Chen

Abstract

We examine the impact of consumer search from the perspective of revenue‐maximizing optimal auction design. In this two‐sided market, advertisers are endowed with privately known qualities, and consumers incur heterogeneous search costs when clicking on advertisements displayed by the search engine. Our general approach eliminates ad hoc restrictions and therefore allows us to uncover the salient economic trade‐offs. We adopt the optimal mechanism design approach to examine this two‐sided private information problem. The optimal mechanism design approach gives rise to the truly revenue‐maximizing scheme, and yields managerial implications that are substantially different from the literature. We show that from the revenue maximization perspective, the search engine necessarily displays the advertisers in the descending order of their qualities. The search engine shall insert unnecessary hassles to induce the revenue‐maximizing search behaviors. Thus, each consumer stops searching pre‐maturely compared to the socially optimal search behavior. In addition, the search engine shall implement probabilistic forced termination upon consumers’ clicking on advertisements, and this probability is higher for advertisers with poorer qualities. When each advertiser has a two‐dimensional type on consumer learning and matching, even if consumers’ search costs become negligible, the allocative inefficiency does not vanish. Moreover, no strategic obfuscation is imposed. When allowing for non‐independent qualities, we show that product variety does not constitute a rationale for advertisers’ favoritism.

Suggested Citation

  • Ying‐Ju Chen, 2021. "Optimal Design of Revenue‐Maximizing Position Auctions with Consumer Search," Production and Operations Management, Production and Operations Management Society, vol. 30(9), pages 3297-3316, September.
  • Handle: RePEc:bla:popmgt:v:30:y:2021:i:9:p:3297-3316
    DOI: 10.1111/poms.13437
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    References listed on IDEAS

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    1. Susan Athey & Glenn Ellison, 2011. "Position Auctions with Consumer Search," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 126(3), pages 1213-1270.
    2. Leon Yang Chu & Hamid Nazerzadeh & Heng Zhang, 2020. "Position Ranking and Auctions for Online Marketplaces," Management Science, INFORMS, vol. 66(8), pages 3617-3634, August.
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    Cited by:

    1. Qingwei Jin & Mengyan Zhu & Yi Yang & Lin Liu, 2022. "Consumer search with anticipated regret," Production and Operations Management, Production and Operations Management Society, vol. 31(8), pages 3337-3351, August.

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