Online bidding is gradually becoming a popular shopping behavior among modern consumers. The combination of traditional auctions and Web technology has drawn substantial research interest. Bidder behavior in online auctions, including online bidding strategies, has been a focus of scholars. Previous studies have discovered and described different bidding strategies in online auctions. However, there is a dearth of research that examines the determinants of bidding strategies using theoretical frameworks and multiple data types. Hence, online bidding behavior requires further investigation. / This study aims to fill the research gap by systematically exploring the factors that influence bidding strategies. It summarizes previous literature on bidding strategies and proposes an integrated model derived from behavioral decision theories, motivational theories, and literature on online auctions. The proposed determinants of bidding strategies and their effects are validated empirically using both subjective and objective data. Results confirm the validity of the proposed integrated model. Three bidding strategies-ratchet bidding, agent bidding, and snipe bidding-are identified in online single-unit auctions. These strategies are influenced by determinants such as starting price, bid increment, perceived utility, network effect, bidding agent effectiveness, bidding experience, risk preference, time availability, and utilitarian motivation. / Cui, Xiling. / Advisers: Xiande Zhao; Siu King Vincent Lai. / Source: Dissertation Abstracts International, Volume: 73-03, Section: A, page: . / Thesis (Ph.D.)--Chinese University of Hong Kong, 2010. / Includes bibliographical references (leaves 131-140). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [201-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. Ann Arbor, MI : ProQuest dissertations and theses, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese; appenidx B in Chinese.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, 2003. / Includes bibliographical references (leaves 95-97). / At Internet auction sites like eBay, similar goods are often sold in a sequence of auctions. Buyers can therefore benefit from forward-looking bidding strategies that take into account the available information about future auctions. This dissertation develops a model of such bidding, provides both experimental and econometric evidence of the model's relevance to behavior, and explores the impact of forward-looking bidding on the seller's optimal selling strategy as well as on the overall market equilibrium. Extending prior sequential-auction theories, the proposed model assumes that bidders know their private valuations of objects auctioned in the near future. Rational bidders "bargain-hunt" in that they bid less than they would otherwise, and early bids decrease with the private values of later objects. The model's predictions are tested in two laboratory experiments, both involving a sequence of two auctions. Both experiments show that first-auction bids decrease with the private values of the future object, but the second experiment suggests that the average decrease is smaller than predicted by the theory. An econometric analysis of eBay data finds that buyers seem to look ahead, and on average adjust their bids down as a function of their private preferences for the objects sold in the near future. They also bid less when the same item they are bidding on is available within the next few auctions. To explore the supply-side of a sequential auction marketplace, the dissertation analyzes a model of a long-lived monopolist facing overlapping generations of forward-looking buyers. When the seller learns about the current auction-market demand from past prices, bargain-hunting poses not only the obvious cost of a lower average revenue, but it also provides a benefit to the seller by making prices more informative. / (cont.) In equilibrium, the seller limits the extent of bargain-hunting by threatening to withhold future supply, but the threat is only credible when the profitability of the auction-market is close to the seller's outside option. Therefore, bargain-hunting can coexist with strategic selling, but is shown to be a self-regulating phenomenon that diminishes when the existence of the auction-market is threatened by an outside spot-market. / by Robert Zeithammer. / Ph.D.

Thesis (Ph. D.)--University of Texas at Austin, 2002. / Vita. Includes bibliographical references. Available also from UMI Company.

Thesis (Ph. D.)--University of Washington, 2007. / Vita. Includes bibliographical references (p. 104-107).

Thesis (Ph. D.)--University of Texas at Austin, 2000. / Vita. Includes bibliographical references (leaves 109-112). Available also in a digital version from Dissertation Abstracts.

Thesis (M.S.)--University of Florida, 2001. / Title from title page of source document. Document formatted into pages; contains x, 115 p.; also contains graphics. Includes vita. Includes bibliographical references.

Thesis (MPhil)--AUT University, 2009. / Includes bibliographical references. Also held in print (x, 221 leaves : ill. ; 30 cm.) in the Archive at the City Campus (T 381.1770993 ABD)

M.Sc. / This dissertation investigates how auctioneer agents can maximise the revenue of an auction. Auctions are an effective solution to agent negotiation because of their simplicity. They are therefore the most widely used approach to agent negotiation. A review of auction theory proves that auction revenue is influenced by factors such as the auction format and the auction parameters. The optimal auction format and parameters are dependent on the bidders and the auction environment. A study of internet auctions confirms the findings of auction theory regarding the importance of the format as well as the parameters in an auction. There has been significant research on the strategies bidding agents can adopt in order to maximise their utility. There is little research, however, on the strategies auctioneer agents can adopt to maximise auction revenue. In this study, a survey is done of the related auctioneer agents in research that maximise auction revenue. The shortcomings of these are identified. The aim of this research is to develop an adaptive auctioneer agent that can maximise the revenue of an auction. The proposed solution is the revenue maximising adaptive auctioneer (RMAA) agent. The RMAA agent consists of three components: the auction manager, the auction format selector (AFS) and the auction parameter selector (APS). The AFS employs a customised zeroth-level classifier system to select the auction format based on the auction environment. The APS employs reinforcement learning combined with a local hill climbing algorithm to learn what the most profitable values are for auction parameters, such as the reserve price and the bid increment. The auction manager automates the auction and coordinates the AFS and APS. It implements the four traditional auction formats, namely the English auction, the Dutch auction, the Vickrey auction and the first-price sealed-bid auction. Experiments conducted to evaluate the effectiveness of the RMAA agent prove that this agent can consistently generate more revenue than a non-adaptive auctioneer agent. The contribution of this research is an auctioneer agent that adapts both the auction format and the auction parameters according to the environment in order to maximise the auction revenue.

by Chi-Wai Lee. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2002. / Includes bibliographical references (leaves 112-117). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgement --- p.iii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Background and Motivations --- p.1 / Chapter 1.2 --- Problem Definition --- p.5 / Chapter 1.3 --- Contributions --- p.5 / Chapter 1.4 --- Thesis Organization --- p.7 / Chapter 2 --- Literature Review --- p.8 / Chapter 2.1 --- Electronic Commerce --- p.8 / Chapter 2.2 --- Agents for Electronic Commerce --- p.9 / Chapter 2.3 --- Online Auctions --- p.11 / Chapter 2.3.1 --- Business Models --- p.12 / Chapter 2.3.2 --- Auction Formats --- p.13 / Chapter 2.3.3 --- Time Duration of Auctions --- p.14 / Chapter 2.3.4 --- Minimum Bids and Reserve Prices --- p.15 / Chapter 2.3.5 --- Auction Properties and Bidder Behaviours --- p.15 / Chapter 2.3.6 --- "Comparison of English, Dutch and Double auction" --- p.16 / Chapter 2.4 --- Agents Developing Tools and Tool-kits --- p.17 / Chapter 2.5 --- Limitations of Agent Tool-kits --- p.18 / Chapter 2.6 --- Markov Processes for Stochastic Modeling --- p.20 / Chapter 2.6.1 --- Continuous Time Markov Chain --- p.21 / Chapter 2.6.2 --- Poisson Arrival Model --- p.22 / Chapter 2.6.3 --- Example: discrete time Markov chain with stationary probabilities --- p.22 / Chapter 3 --- Markov Chain Model --- p.25 / Chapter 3.1 --- Markov Chain for English Auction --- p.25 / Chapter 3.1.1 --- Variables --- p.27 / Chapter 3.1.2 --- Auction Assumptions --- p.27 / Chapter 3.1.3 --- Bidder Assumptions --- p.29 / Chapter 3.1.4 --- Propositions of the Markov Model --- p.31 / Chapter 3.1.5 --- Tractability --- p.35 / Chapter 3.2 --- Markov Chain for Dutch Auction --- p.38 / Chapter 3.2.1 --- Variables --- p.39 / Chapter 3.2.2 --- Model Assumptions --- p.39 / Chapter 3.2.3 --- Propositions of the Markov Model --- p.42 / Chapter 3.2.4 --- Tractability --- p.43 / Chapter 3.3 --- Progression of the Price Vector for English and Dutch Auction --- p.43 / Chapter 3.4 --- Markov Chain for Double auction --- p.45 / Chapter 3.4.1 --- Variables --- p.47 / Chapter 3.4.2 --- Model Assumptions --- p.47 / Chapter 3.4.3 --- Propositions of the Markov Model --- p.49 / Chapter 3.4.4 --- Tractability --- p.53 / Chapter 3.5 --- Progression of the Price Vector for Double Auction --- p.53 / Chapter 3.6 --- Summary --- p.54 / Chapter 4 --- System Design --- p.57 / Chapter 4.1 --- System Features --- p.58 / Chapter 4.2 --- System Architecture --- p.59 / Chapter 4.2.1 --- System Workflow --- p.60 / Chapter 4.2.2 --- Communication Layer --- p.61 / Chapter 4.2.3 --- Agent Logic Layer --- p.62 / Chapter 4.2.4 --- Database Abstraction Layer --- p.62 / Chapter 4.3 --- Roles of the Agents --- p.62 / Chapter 4.4 --- Implementation Details --- p.65 / Chapter 4.4.1 --- Choosing a Scripting Language --- p.65 / Chapter 4.4.2 --- Choosing a Database --- p.68 / Chapter 4.4.3 --- Server-Side Java with Jakarta-tomcat --- p.69 / Chapter 4.4.4 --- Agent API --- p.70 / Chapter 4.4.5 --- Class java.agent.Agent --- p.72 / Chapter 4.5 --- Summary --- p.73 / Chapter 5 --- Experimental Results --- p.75 / Chapter 5.1 --- Simulation Environment --- p.75 / Chapter 5.2 --- Experiment One: A small English auction --- p.76 / Chapter 5.3 --- Experiment Two: A large English auction --- p.80 / Chapter 5.4 --- Experiment Three: A small Dutch auction --- p.82 / Chapter 5.5 --- Experiment Four: A large Dutch auction --- p.83 / Chapter 5.6 --- Experiment Five: Partial knowledge on other BAs --- p.84 / Chapter 5.7 --- Experiment Six: Partial knowledge on closing time --- p.86 / Chapter 5.8 --- Experiment Seven: A small Double auction --- p.87 / Chapter 5.9 --- Comparisons and Discussions --- p.89 / Chapter 5.10 --- Summary --- p.90 / Chapter 6 --- Conclusion --- p.91 / Chapter A --- Markov Chain for English Auction --- p.93 / Chapter A.1 --- Graphs of F and F* Functions --- p.93 / Chapter A.2 --- Solution of a Small Example --- p.96 / Chapter A.2.1 --- Computation of Transition Probabilities --- p.97 / Chapter A.2.2 --- Progression of the Price Vector --- p.97 / Chapter B --- Markov Chain for Double Auction --- p.101 / Chapter B.1 --- Graphs of Fb(vbi) and Fs(vsi) Functions --- p.101 / Chapter B.2 --- Solution of a Small Example --- p.102 / Chapter B.2.1 --- Computation of Transition Probabilities --- p.102 / Chapter C --- Implementation Details --- p.105 / Chapter C.1 --- Tables Design in MySQL --- p.105 / Chapter C.2 --- Sample Apache Configuration File --- p.109 / Bibliography --- p.112

Thesis (M.S.)--University of Florida, 2001. / Title from first page of PDF file. Document formatted into pages; contains x, 61 p.; also contains graphics. Vita. Includes bibliographical references (p. 58-60).