Discrete Strategies in Keyword Auctions and Their Inefficiency for Locally Aware Bidders

We study formally discrete bidding strategies for the game induced by the Generalized Second Price keyword auction mechanism. Such strategies have seen experimental evaluation in the recent literature as parts of iterative best response procedures, which have been shown not to converge. We give a detailed definition of iterative best response under these strategies and, under appropriate discretization of the players' strategy spaces we find that the discretized configurations space {\em contains} socially optimal pure Nash equilibria. We cast the strategies under a new light, by studying their performance for bidders that act based on local information; we prove bounds for the worst-case ratio of the social welfare of locally stable configurations, relative to the socially optimum welfare

A Free Exchange e-Marketplace for Digital Services

The digital era is witnessing a remarkable evolution of digital services. While the prospects are countless, the e-marketplaces of digital services are encountering inherent game-theoretic and computational challenges that restrict the rational choices of bidders. Our work examines the limited bidding scope and the inefficiencies of present exchange e-marketplaces. To meet challenges, a free exchange e-marketplace is proposed that follows the free market economy. The free exchange model includes a new bidding language and a double auction mechanism. The rule-based bidding language enables the flexible expression of preferences and strategic conduct. The bidding message holds the attribute-valuations and bidding rules of the selected services. The free exchange deliberates on attributes and logical bidding rules for automatic deduction and formation of elicited services and bids that result in a more rapid self-managed multiple exchange trades. The double auction uses forward and reverse generalized second price auctions for the symmetric matching of multiple digital services of identical attributes and different quality levels. The proposed double auction uses tractable heuristics that secure exchange profitability, improve truthful bidding and deliver stable social efficiency. While the strongest properties of symmetric exchanges are unfeasible game-theoretically, the free exchange converges rapidly to the social efficiency, Nash truthful stability, and weak budget balance by multiple quality-levels cross-matching, constant learning and informs at repetitive thick trades. The empirical findings validate the soundness and viability of the free exchange

To Score or Not to Score? Estimates of a Sponsored Search Auction Model

We estimate a structural model of a sponsored search auction model. To accomodate the "position paradox", we relax the assumption of decreasing click volumes with position ranks, which is often assumed in the literature. Using data from "Website X", one of the largest online market places in China, we find that merchants of different qualities adopt different bidding strategies: high quality merchants bid more aggressively for informative keywords, while low quality merchants are more likely to be sorted to the top positions for value keywords. Counterfactual evaluations show that the price trend becomes steeper after moving to a score-weighted generalized second price auction, with much higher prices obtained for the top position but lower prices for the other positions. Overall, there is only a very modest change in total revenue from introducing popularity scoring, despite the intent in bid scoring to reward popular merchants with price discounts

Multi-Keyword Multi-Click Option Contracts for Sponsored Search Advertising

In sponsored search, advertising slots are usually sold by a search engine to an advertiser through an auction mechanism in which advertisers bid on keywords. In theory, an auction mechanism encourages the advertisers to truthfully bid for keywords. However, keyword auctions have a number of problems including: (i) volatility in revenue, (ii) uncertainty in the bidding and charged prices for advertisers’ keywords, and (iii) weak brand loyalty between the advertiser and the search engine. To address these issues, we study the possibility of creating a special option contract that alleviates these problems. In our proposal, an advertiser purchases an option in advance from a search engine by paying an upfront fee, known as the option price. The advertiser then has the right, but no obligation, to then purchase specific keywords for a fixed costper-click (CPC) for a specified number of clicks in a specified period of time. Hence, the advertiser has increased certainty in sponsored search while the search engine could raise the customers’ loyalty. The proposed option contract can be used in conjunction with traditional keyword auctions. As such, the option price and corresponding fixed CPC price must be set such that there is no arbitrage opportunity. In this paper, we discuss an option pricing model tailored to sponsored search that deals with spot CPCs of targeted keywords in a generalized second price (GSP) auction. We show that the pricing model for keywords is closely related to a special exotic option in finance that contains multiple underlying assets (multi-keywords) and is also multi-exercisable (multi-clicks). Experimental results on real advertising data verify our pricing model and demonstrate that advertising options can benefit both advertisers and search engines

A Systematic Review on Search Engine Advertising

The innovation of Search Engine Advertising (SEA) was first introduced in 1998. It soon became a very popular tool among practitioners for promoting their websites on the Web and turned into a billion dollar revenue source for search engines. In parallel with its rapid growth in use, SEA attracted the attention of academic researchers resulting in a large number of publications on the topic of SEA. However, no comprehensive review of this accumulated body of knowledge is currently available. This shortcoming has motivated us to conduct a systematic review of SEA literature. Herewith, we searched for and collected 101 papers on the topic of SEA, published in 72 journals from different disciplines and analyzed them to answer the research questions for this study. We have identified the historical development of SEA literature, predominant journals in the publication of SEA research, active reference disciplines as well as the main researchers in the field of SEA. Moreover, we have classified SEA literature into four categories and 10 research topics. We also uncovered a number of gaps in SEA literature and provided future research direction accordingly. Available at: https://aisel.aisnet.org/pajais/vol7/iss3/2

Automated Markets and Trading Agents

Computer automation has the potential, just starting to be realized, of transforming the design and operation of markets, and the behaviors of agents trading in them. We discuss the possibilities for automating markets, presenting a broad conceptual framework covering resource allocation as well as enabling marketplace services such as search and transaction execution. One of the most intriguing opportunities is provided by markets implementing computationally sophisticated negotiation mechanisms, for example combinatorial auctions. An important theme that emerges from the literature is the centrality of design decisions about matching the domain of goods over which a mechanism operates to the domain over which agents have preferences. When the match is imperfect (as is almost inevitable), the market game induced by the mechanism is analytically intractable, and the literature provides an incomplete characterization of rational bidding policies. A review of the literature suggests that much of our existing knowledge comes from computational simulations, including controlled studies of abstract market designs (e.g., simultaneous ascending auctions), and research tournaments comparing agent strategies in a variety of market scenarios. An empirical game-theoretic methodology combines the advantages of simulation, agent-based modeling, and statistical and game-theoretic analysis.http://deepblue.lib.umich.edu/bitstream/2027.42/49510/1/ace_galleys.pd