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A Game-theoretic Analysis of Catalog Optimization JOEL OREN, UNIVERSITY OF TORONTO. JOINT WORK WITH: NINA NARODYTSKA, AND CRAIG BOUTILIER 1
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Motivating Story: Competitive Adjustment of Offerings A large retail chain opens a new store. Multiple competitors. Multiple potential customers: Typically doesn’t buy too many items – say, just one item. Buy their most preferred item, given what is offered in total – over all stores. Exogenous (fixed) prices. How should they choose what to offer, so as to maximize their profits? A form of assortment optimization. 2
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Catalog 1 3 Vendor 1 Vendor 2 $10 $5 $15 $4 $8 Catalog 1 $10 $15 $8 $10 Catalog: a set (assortment) of offered items. Best-response: Optimizing one’s catalog may be tricky – What are the convergence properties of these dynamics? 1.Do pure Nash eq. (PNE) exist? 2.What is the Price of Anarchy/Stability, (PoA/PoS)? 1 50 1 X 100
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The Formal Model 4
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Selecting the Best Response – the Full Information Setting Theorem: Computing a best response is Max-SNP hard. Implication: there is a constant, such that approximating the maximal profit beyond this constant is NP-hard. 5
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A Special Case: Single-Peaked Truncated Preference 6
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Partial Information Setting 7 Catalog 1 Vendor 1 Vendor 2 $10 $5 $15 $4 $8 Catalog 1 $10 $1 5 $8
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Partial Information Setting 8 Catalog 1 Vendor 1 Vendor 2 $10 $5 $15 $4 $8 Catalog 1 $10 $15 $8
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Equilibria and Stability of the Game 9 Full information Partial information - IC Mutual sets All vendors’ sets are disjoint
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Full Information, Disjoint Sets 10
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Partial Information, Disjoint Sets 11
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Full Information, Mutual Sets 12
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Partial Information, Mutual Sets 13
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Conclusions and Future Directions Best response: Max-SNP hard in general, easier under some assumptions. Question: can we design an approximation algorithm for the full-info. case? Game theoretic analysis: PoA/PoS under complete VS partial information, disjoint VS mutual sets. Question: can we show that there is always a PNE under a general Mallows dist.? Additional directions: Other classes of preferences. Study the game when prices are set endogenously. 14
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