Optimal marketing strategies over social networks
Proceedings of the 17th international conference on World Wide Web
Optimal iterative pricing over social networks
WINE'10 Proceedings of the 6th international conference on Internet and network economics
Influential nodes in a diffusion model for social networks
ICALP'05 Proceedings of the 32nd international conference on Automata, Languages and Programming
Optimal iterative pricing over social networks
WINE'10 Proceedings of the 6th international conference on Internet and network economics
Optimal auctions with positive network externalities
Proceedings of the 12th ACM conference on Electronic commerce
Optimal online pricing with network externalities
Information Processing Letters
On allocations with negative externalities
WINE'11 Proceedings of the 7th international conference on Internet and Network Economics
WINE'12 Proceedings of the 8th international conference on Internet and Network Economics
Equilibrium pricing with positive externalities
Theoretical Computer Science
Optimal Auctions with Positive Network Externalities
ACM Transactions on Economics and Computation - Special Issue on Algorithmic Game Theory
Pricing public goods for private sale
Proceedings of the fourteenth ACM conference on Electronic commerce
Competitive auctions for markets with positive externalities
ICALP'13 Proceedings of the 40th international conference on Automata, Languages, and Programming - Volume Part II
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We study the problem of selling an item to strategic buyers in the presence of positive historical externalities, where the value of a product increases as more people buy and use it. This increase in the value of the product is the result of resolving bugs or security holes after more usage. We consider a continuum of buyers that are partitioned into types where each type has a valuation function based on the actions of other buyers. Given a fixed sequence of prices, or price trajectory, buyers choose a day on which to purchase the product, i.e., they have to decide whether to purchase the product early in the game or later after more people already own it. We model this strategic setting as a game, study existence and uniqueness of the equilibria, and design an FPTAS to compute an approximately revenue-maximizing pricing trajectory for the seller in two special cases: the symmetric settings in which there is just a single buyer type, and the linear settings that are characterized by an initial type-independent bias and a linear type-dependent influenceability coefficient.