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 (M.B.A.) - Carleton University,2001. / Includes bibliographical references (p.92-96). Also available in electronic format on the Internet.

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Retaining business value in a legacy commercial enterprise resource planning system today often entails more than just maintaining the software to preserve existing functionality. This type of system tends to represent a significant capital investment that may not be easily scrapped, replaced, or re-engineered without considerable expense. A legacy system may need to be frequently extended to impart new behavior as stakeholder business goals and technical requirements evolve. Legacy ERP systems are growing in prevalence and are both expensive to maintain and risky to evolve. Humans are the driving factor behind the expense, from the engineering costs associated with evolving these types of systems to the labor costs required to operate the result. Autonomic computing is one approach that addresses these challenges by imparting self-adaptive behavior into the evolved system. The contribution of this dissertation aims to add to the body of knowledge in software engineering some insight and best practices for development approaches that are normally hidden from academia by the competitive nature of the retail industry. We present a formal architectural pattern that describes an asynchronous, low-complexity, and autonomic approach. We validate the pattern with two real-world commercial case studies and a reengineering simulation to demonstrate that the pattern is repeatable and agnostic with respect to the operating system, programming language, and communication protocols. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2015. / FAU Electronic Theses and Dissertations Collection

Indiana University-Purdue University Indianapolis (IUPUI) / indefinitely