Search

Patent pricing is the core issue in patent industrialisation. This paper uses game theory to study the effects of auction behaviours when the members of the patent portfolio are auctioned either together or separately. A comparison of patent product yields the results (1) the outputs of a patented product are lower in a packaged auction than in a separate auction, and the outputs of the two auction modes decrease as the correlation between patent members increases; (2) the profits of package portfolios are higher under packaged auctions than under separate auctions, and an enterprise's profit is negatively related to the correlation between the patent members; (3) when a patent portfolio is subjected to separate auction, the product outputs under Stackelberg equilibrium in a game are higher than that under static equilibrium, and the product outputs in the Stackelberg equilibrium decrease with the correlation between patent members; and (4) when the members of a patent portfolio are auctioned separately, the profits in the Stackelberg equilibrium and static equilibrium are related to the correlation between patent portfolio members; the profits in the Stackelberg equilibrium will first decrease and then increase as the correlation between patent portfolio members increases. [ABSTRACT FROM AUTHOR]

We study combinatorial auctions with bidders that exhibit an endowment effect. In most of the previous work on cognitive biases in algorithmic game theory the focus was on analyzing the implications and mitigating their negative consequences. In contrast, in this paper we show how in some cases cognitive biases can be harnessed to obtain better outcomes. Specifically, we study Walrasian equilibria in combinatorial markets. It is well known that Walrasian equilibria exist only in limited settings, e.g., when all valuations are gross substitutes, but fail to exist in more general settings, e.g., when the valuations are submodular. Our main result shows that when the valuations are submodular, even a mild degree of endowment effect is sufficient to guarantee the existence of Walrasian equilibria. [ABSTRACT FROM AUTHOR]

Budgets play a significant role in ad markets that implement sequential auctions such as those hosted by internet companies. In "Multiplicative Pacing Equilibria in Auction Markets," the authors look at pacing in an ad marketplace using the lens of game theory. The goal is understanding how bids must be shaded to maximize advertiser welfare, at equilibrium. Motivated by the real-world auction mechanism, they construct a game where advertisers in the auctions choose a multiplicative factor not larger than 1 to possibly reduce their bids and best respond to the other advertisers. The article studies the theoretical properties of the game such as existence and uniqueness of equilibria, offers an exact algorithm to compute them, connects the game to well-known abstractions such as Fisher markets, and performs a computational study with real-world-inspired instances. The main insights are that the solutions to the studied game can be used to improve the outcomes achieved by a closer-to-reality dynamic pacing algorithm and that buyers do not have an incentive to misreport bids or budgets when there are enough participants in the auction. Budgets play a significant role in real-world sequential auction markets such as those implemented by internet companies. To maximize the value provided to auction participants, spending is smoothed across auctions so budgets are used for the best opportunities. Motivated by a mechanism used in practice by several companies, this paper considers a smoothing procedure that relies on pacing multipliers: on behalf of each buyer, the auction market applies a factor between 0 and 1 that uniformly scales the bids across all auctions. Reinterpreting this process as a game between buyers, we introduce the notion of pacing equilibrium, and prove that they are always guaranteed to exist. We demonstrate through examples that a market can have multiple pacing equilibria with large variations in several natural objectives. We show that pacing equilibria refine another popular solution concept, competitive equilibria, and show further connections between the two solution concepts. Although we show that computing either a social-welfare-maximizing or a revenue-maximizing pacing equilibrium is NP-hard, we present a mixed-integer program (MIP) that can be used to find equilibria optimizing several relevant objectives. We use the MIP to provide evidence that: (1) equilibrium multiplicity occurs very rarely across several families of random instances, (2) static MIP solutions can be used to improve the outcomes achieved by a dynamic pacing algorithm with instances based on a real-world auction market, and (3) for the instances we study, buyers do not have an incentive to misreport bids or budgets provided there are enough participants in the market. [ABSTRACT FROM AUTHOR]