Advances in information technology have created radically new business models, most notably the integration of advertising with keyword-based targeting, or "keyword advertising." Keyword advertising has two main variations: advertising based on keywords employed by users in search engines, often known as "sponsored links," and advertising based on keywords embedded in the content users view, often known as "contextual advertising." Keyword advertising providers such as Google and Yahoo! use auctions to allocate advertising slots. This dissertation examines the design of keyword auctions. It consists of three essays. The first essay "Ex-Ante Information and the Design of Keyword Auctions" focuses on how to incorporate available information into auction design. In our keyword auction model, advertisers bid their willingness-to-pay per click on their advertisements, and the advertising provider can weigh advertisers' bids differently and require different minimum bids based on advertisers' click-generating potential. We study the impact and design of such weighting schemes and minimum-bids policies. We find that weighting scheme determines how advertisers with different click-generating potential match in equilibrium. Minimum bids exclude low-valuation advertisers and at the same time may distort the equilibrium matching. The efficient design of keyword auctions requires weighting advertisers' bids by their expected click-through-rates, and requires the same minimum weighted bids. The revenue-maximizing weighting scheme may or may not favor advertisers with low click-generating potential. The revenue-maximizing minimum-bid policy differs from those prescribed in the standard auction design literature. Keyword auctions that employ the revenue-maximizing weighting scheme and differentiated minimum bid policy can generate higher revenue than standard fixed-payment auctions. The dynamics of bidders' performance is examined in the second essay, "Keyword Auctions, Unit-price Contracts, and the Role of Commitment." We extend earlier static models by allowing bidders with lower performance levels to improve their performance at a certain cost. We examine the impact of the weighting scheme on overall bidder performance, the auction efficiency, and the auctioneer's revenue, and derive the revenue-maximizing and efficient policy accordingly. Moreover, the possible upgrade in bidders' performance levels gives the auctioneer an incentive to modify the auction rules over time, as is confirmed by the practice of Yahoo! And Google. We thus compare the auctioneer's revenue-maximizing policies when she is fully committed to the auction rule and when not, and show that she should give less preferential treatment to low-performance advertisers when she is fully committed. In the third essay, "How to Slice the Pie? Optimal Share Structure Design in Keyword Auctions," we study the design of share structures in keyword auctions. Auctions for keyword advertising resources can be viewed as share auctions in which the highest bidder gets the largest share, the second highest bidder gets the second largest share, and so on. A share structure problem arises in such a setting regarding how much resources to set aside for the highest bidder, for the second highest bidder, etc. We address this problem under a general specification and derive implications on how the optimal share structure should change with bidders' price elasticity of demand for exposure, their valuation distribution, total resources, and minimum bids. / text

published_or_final_version / Business / Master / Master of Philosophy

Zhang, Nianbing. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (leaves 113-118). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Overview --- p.1 / Chapter 1.2 --- Motivation --- p.2 / Chapter 1.3 --- The Research Scope and Main Results --- p.4 / Chapter 1.3.1 --- The Mechanism --- p.4 / Chapter 1.3.2 --- Statement of Problem --- p.8 / Chapter 1.3.3 --- Main Results --- p.11 / Chapter 1.4 --- Structure of Research --- p.13 / Chapter 2 --- Survey of the Literature --- p.15 / Chapter 2.1 --- Overview --- p.15 / Chapter 2.2 --- E-business --- p.16 / Chapter 2.3 --- Auction --- p.18 / Chapter 2.3.1 --- Introduction --- p.18 / Chapter 2.3.2 --- Auction Theory --- p.20 / Chapter 2.3.3 --- Online Auctions --- p.21 / Chapter 2.4 --- Combination of Auction and Other Transaction Methods --- p.24 / Chapter 2.4.1 --- Auction with Posted Price --- p.24 / Chapter 2.4.2 --- Auction with Negotiation Process --- p.26 / Chapter 2.4.3 --- Auction with Noncompetitive Contract --- p.28 / Chapter 3 --- Single Unit Noncompetitive Contract --- p.29 / Chapter 3.1 --- The Model --- p.29 / Chapter 3.2 --- Strategy of Suppliers in the Auction --- p.31 / Chapter 3.3 --- Strategy of Selected Suppliers --- p.33 / Chapter 3.3.1 --- Selected Supplier of No-Information Case --- p.33 / Chapter 3.3.2 --- Supplier in Information Case --- p.40 / Chapter 3.4 --- Buyer´ةs Consideration --- p.44 / Chapter 3.4.1 --- Buyer's Cost in No-Information Case --- p.44 / Chapter 3.4.2 --- Buyer's Cost in Information Case --- p.45 / Chapter 3.4.3 --- Comparison of Costs in the Two Information Scenarios --- p.47 / Chapter 4 --- Buyer´ةs Strategy: Lower Cost and More Flexibility for Suppliers --- p.49 / Chapter 4.1 --- Is the Noncompetitive Contract Necessary --- p.50 / Chapter 4.1.1 --- No-Information Case --- p.50 / Chapter 4.1.2 --- Information Case --- p.52 / Chapter 4.2 --- Flexibility of Re-Entrance to Auction --- p.53 / Chapter 4.2.1 --- No-Information Case --- p.54 / Chapter 4.2.2 --- Information Case --- p.58 / Chapter 4.3 --- Flexibility of Making Decision After the Auction --- p.65 / Chapter 4.3.1 --- No-Information Case --- p.66 / Chapter 4.3.2 --- Information Case --- p.69 / Chapter 5 --- Multiple Noncompetitive Contracts --- p.73 / Chapter 5.1 --- No-Information Case --- p.74 / Chapter 5.1.1 --- Suppliers's Strategy --- p.74 / Chapter 5.1.2 --- Buyer´ةs Consideration --- p.76 / Chapter 5.2 --- Information Case --- p.78 / Chapter 5.2.1 --- Supplier's Strategy --- p.78 / Chapter 5.2.2 --- Computation of Buyer's Cost --- p.81 / Chapter 5.2.3 --- Comparison with the Case of One Noncompetitive Contract --- p.85 / Chapter 5.2.4 --- The Effect of Supplier´ةs Information --- p.89 / Chapter 5.3 --- General Number of Noncompetitive Contract --- p.91 / Chapter 5.3.1 --- No-Information Case --- p.91 / Chapter 5.3.2 --- Information Case --- p.94 / Chapter 6 --- Alternative Forms of Contracts --- p.96 / Chapter 6.1 --- SBIB Model --- p.97 / Chapter 6.2 --- SNIB Model --- p.98 / Chapter 6.2.1 --- Supplier's Strategy --- p.98 / Chapter 6.2.2 --- Buyer´ةs Cost in No-Information Case --- p.100 / Chapter 6.2.3 --- Buyer's Cost in Information Case --- p.103 / Chapter 6.2.4 --- Multiple Units Offered --- p.105 / Chapter 7 --- Conclusion --- p.110

This thesis looks at three aspects related to the design of E-commerce systems, online auctions and distributed grid computing systems. We show how formal verification techniques from computer science can be applied to ensure correctness of system design and implementation at the code level. Through e-ticket sales example, we demonstrate that model checking can locate subtle but critical flaws that traditional control and auditing methods (e.g., penetration testing, analytical procedure) most likely miss. Auditors should understand formal verification methods, enforce engineering to use them to create designs with less of a chance of failure, and even practice formal verification themselves in order to offer credible control and assistance for critical e-systems. Next, we study why many online auctions offer fixed buy prices to understand why sellers and auctioneers voluntarily limit the surplus they can get from an auction. We show when either the seller of the dibbers are risk-averse, a properly chosen fixed permanent buy-price can increase the social surplus and does not decrease the expected utility of the sellers and bidders, and we characterize the unique equilibrium strategies of uniformly risk-averse buyers in a buy-price auction. In the final chapter we look at the design of a distributed grid-computing system. We show how code-instrumentation can be used to generate a witness of program execution, and show how this witness can be used to audit the work of self-interested grid agents. Using a trusted intermediary between grid providers and customers, the audit allows payment to be contingent on the successful audit results, and it creates a verified reputation history of grid providers. We show that enabling the free trade of reputations provides economic incentives to agents to perform the computations assigned, and it induces increasing effort levels as the agents' reputation increases. We show that in such a reputation market only high-type agents would have incentive to purchase a high reputation, and only low-type agents would use low reputations, thus a market works as a natural signaling mechanism about the agents' type. / text

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