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Search Engines: Alexandre de Corniere

Search Engines: Alexandre de Corniere. Simon P. Anderson University of Virginia Discussion. Discussion outline. Very clean, elegantly done, clear Several extensions – ready to ship Overview Random serving up of surfers? (obfuscation) Minor comments Future directions. Model backdrop.

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Search Engines: Alexandre de Corniere

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  1. Search Engines: Alexandre de Corniere Simon P. Anderson University of Virginia Discussion

  2. Discussion outline • Very clean, elegantly done, clear • Several extensions – ready to ship • Overview • Random serving up of surfers? (obfuscation) • Minor comments • Future directions

  3. Model backdrop • Circle for products and consumers (continua) • Optimal consumer search as a stopping rule • Hence no point in advertiser paying a if won’t stop leads to (restricted) optimality result: search costs minimized (one search) • Defines the advertiser width per consumer • Then find the (monopoly – all stop) product price (no discrimination) over the disparate consumers • Search engine serves up advertisers at random • But, (when) is uniform distribution optimal?

  4. Tensions in engine (platform) pricing • Classic two-sided market balance: revenue per viewer times number of viewers • Here though there is only one click per viewer (only one advertiser pays) • Still deliver up eyeballs by rendering attractive the expected package • Need here to temper Diamond Paradox by including some less desirable matches • Still monopoly pricing (not price competition), but affecting demand elasticity

  5. Google’s secret sauce • What should be served up? • Not just the ideal match! Then price is reservation value of highest valuation consumer. Zero surplus, so no-one clicks. • Instead of uniform, what probability distribution is optimal for engine? • More density on ends? Reduces price, but worse matches • Bruestle (UVA): serving up the “wrong” eyeballs • So, find the algorithm! (not too hard?) • Reminiscent of threshold match (AR, AER ‘06) – tell enough, but not too much

  6. Minor points • A3 should be (1-F) log-concave • Caplin and Nalebuff (1989); Anderson, de Palma, Nesterov (1985)

  7. Random serving assumption • Would the engine profit from a different algorithm? • Serve up the best? (what would happen? – Diamond paradox?) • Maybe not … • Bruestle (UVA: “serving up the wrong eye-balls”) Similar ingredients; but serving up some “wrong” surfers How it works: full-fledged 2-sided market logic: get more surfers on-board (to deliver to discipline prices)

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