<p>Central to the explosive growth of the Internet has been the desire</p><p>of dispersed buyers and sellers to interact readily and in a manner</p><p>hitherto impossible. Underpinning these interactions, auction</p><p>pricing mechanisms have enabled Internet transactions in novel ways.</p><p>Despite this massive growth and new medium, empirical work in</p><p>marketing and economics on auction use in Internet contexts remains</p><p>relatively nascent. Accordingly, this dissertation investigates the</p><p>role of online auctions; it is composed of three essays.</p><p>The first essay, ``Online Auction Demand,'' investigates seller and</p><p>buyer interactions via online auction websites, such as eBay. Such</p><p>auction sites are among the earliest prominent transaction sites on</p><p>the Internet (eBay started in 1995, the same year Internet Explorer</p><p>was released) and helped pave the way for e-commerce. Hence, online</p><p>auction demand is the first topic considered in my dissertation. The</p><p>second essay, ``A Dynamic Model of Sponsored Search Advertising,''</p><p>investigates sponsored search advertising auctions, a novel approach</p><p>that allocates premium advertising space to advertisers at popular</p><p>websites, such as search engines. Because sponsored search</p><p>advertising targets buyers in active purchase states, such</p><p>advertising venues have grown very rapidly in recent years and have</p><p>become a highly topical research domain. These two essays form the</p><p>foundation of the empirical research in this dissertation. The third</p><p>essay, ``Sponsored Search Auctions: Research Opportunities in</p><p>Marketing,'' outlines areas of future inquiry that I intend to</p><p>pursue in my research.</p><p>Of note, the problems underpinning the two empirical essays exhibits</p><p>a common form, that of a two-sided network wherein two parties</p><p>interact on a common platform (Rochet and Tirole, 2006). Although</p><p>theoretical research on two-sided markets is abundant, this</p><p>dissertation focuses on their use in e-commerce and adopts an</p><p>empirical orientation. I assume an empirical orientation because I</p><p>seek to guide firm behavior with concrete policy recommendations and</p><p>offer new insights into the actual behavior of the agents who</p><p>interact in these contexts. Although the two empirical essays share</p><p>this common feature, they also exhibit notable differences,</p><p>including the nature of the auction mechanism itself, the</p><p>interactions between the agents, and the dynamic frame of the</p><p>problem, thus making the problems distinct. The following abstracts</p><p>for these two essays as well as the chapter that describes my future</p><p>research serve to summarize these contributions, commonalities and</p><p>differences.</p><p>Online Auction Demand</p><p>With $40B in annual gross merchandise volume, electronic auctions</p><p>comprise a substantial and growing sector of the retail economy. For</p><p>example, eBay alone generated a gross merchandise volume of $14.4B</p><p>during the fourth quarter of 2006. Concurrent with this growth has</p><p>been an attendant increase in empirical research on Internet</p><p>auctions. However, this literature focuses primarily on the bidder;</p><p>I extend this research to consider both seller and bidder behavior</p><p>in an integrated system within a two-sided network of the two</p><p>parties. This extension of the existing literature enables an</p><p>exploration of the implications of the auction house's marketing on</p><p>its revenues as well as the nature of bidder and seller interactions</p><p>on this platform. In the first essay, I use a unique data set of</p><p>Celtic coins online auctions. These data were obtained from an</p><p>anonymous firm and include complete bidding and listing histories.</p><p>In contrast, most existing research relies only on the observed</p><p>website bids. The complete bidding and listing histories provided by</p><p>the data afford additional information that illuminates the insights</p><p>into bidder and seller behavior such as bidder valuations and seller</p><p>costs.</p><p>Using these data from the ancient coins category, I estimate a</p><p>structural model that integrates both bidder and seller behavior.</p><p>Bidders choose coins and sellers list them to maximize their</p><p>respective profits. I then develop a Markov Chain Monte Carlo (MCMC)</p><p>estimation approach that enables me, via data augmentation, to infer</p><p>unobserved bidder and seller characteristics and to account for</p><p>heterogeneity in these characteristics. My findings indicate that:</p><p>i) bidder valuations are affected by item characteristics (e.g., the</p><p>attributes of the coin), seller (e.g. reputation), and auction</p><p>characteristics (e.g., the characteristics of the listing); ii)</p><p>bidder costs are affected by bidding behavior, such as the recency</p><p>of the last purchase and the number of concurrent auctions; and iii)</p><p>seller costs are affected by item characteristics and the number of</p><p>concurrent listings from the seller (because acquisition costs</p><p>evidence increasing marginal values).</p><p>Of special interest, the model enables me to compute fee</p><p>elasticities, even though no variation in historical fees exists in</p><p>these data. I compute fee elasticities by inferring the role of</p><p>seller costs in their historical listing decision and then imputing</p><p>how an increase in these costs (which arises from more fees) would</p><p>affect the seller's subsequent listing behavior. I find that these</p><p>implied commission elasticities exceed per-item fee elasticities</p><p>because commissions target high value sellers, and hence, commission</p><p>reductions enhance their listing likelihood. By targeting commission</p><p>reductions to high value sellers, auction house revenues can be</p><p>increased by 3.9%. Computing customer value, I find that attrition</p><p>of the largest seller would decrease fees paid to the auction house</p><p>by $97. Given that the seller paid $127 in fees, competition</p><p>offsets only 24% of the fees paid by the seller. In contrast,</p><p>competition largely in the form of other bidders offsets 81% of the</p><p>$26 loss from buyer attrition. In both events, the auction house</p><p>would overvalue its customers by neglecting the effects of</p><p>competition.</p><p>A Dynamic Model of Sponsored Search Advertising</p><p>Sponsored search advertising is ascendant. Jupiter Research reports</p><p>that expenditures rose 28% in 2007 to $8.9B and will continue to</p><p>rise at a 26% Compound Annual Growth Rate (CAGR), approaching half</p><p>the level of television advertising and making sponsored search</p><p>advertising one of the major advertising trends affecting the</p><p>marketing landscape. Although empirical studies of sponsored search</p><p>advertising are ascending, little research exists that explores how</p><p>the interactions of various agents (searchers,</p><p>advertisers, and the search engine) in keyword</p><p>markets affect searcher and advertiser behavior, welfare and search</p><p>engine profits. As in the first essay, sponsored search constitutes</p><p>a two-sided network. In this case, bidders (advertisers) and</p><p>searchers interact on a common platform, the search engine. The</p><p>bidder seeks to maximize profits, and the searcher seeks to maximize</p><p>utility.</p><p>The structural model I propose serves as a foundation to explore</p><p>these outcomes and, to my knowledge, is the first structural model</p><p>for keyword search. Not only does the model integrate the behavior</p><p>of advertisers and searchers, it also accounts for advertisers</p><p>competition in a dynamic setting. Prior theoretical research has</p><p>assumed a static orientation to the problem whereas prior empirical</p><p>research, although dynamic, has focused solely on estimating the</p><p>dynamic sales response to a single firm's keyword advertising</p><p>expenditures.</p><p>To estimate the proposed model, I have developed a two-step Bayesian</p><p>estimator for dynamic games. This approach does not rely on</p><p>asymptotics and also facilitates a more flexible model</p><p>specification.</p><p>I fit this model to a proprietary data set provided by an anonymous</p><p>search engine. These data include a complete history of consumer</p><p>search behavior from the site's web log files and a complete history</p><p>of advertiser bidding behavior across all advertisers. In addition,</p><p>the data include search engine information, such as keyword pricing</p><p>and website design.</p><p>With respect to advertisers, I find evidence of dynamic</p><p>bidding behavior. Advertiser valuation for clicks on their sponsored</p><p>links averages about $0.27. Given the typical $22 retail price of</p><p>the software products advertised on the considered search engine,</p><p>this figure implies a conversion rate (sales per click) of about</p><p>1.2%, well within common estimates of 1-2% (gamedaily.com). With</p><p>respect to consumers, I find that frequent clickers place a</p><p>greater emphasis on the position of the sponsored advertising link.</p><p>I further find that 10% of consumers perform 90% of the clicks.</p><p>I then conduct several policy simulations to illustrate the effects</p><p>of change in search engine policy. First, I find that the</p><p>search engine obtains revenue gains of nearly 1.4% by sharing</p><p>individual level information with advertisers and enabling them to</p><p>vary their bids by consumer segment. This strategy also improves</p><p>advertiser profits by 11% and consumer welfare by 2.9%. Second, I</p><p>find that a switch from a first to second price auction results in</p><p>truth telling (advertiser bids rise to advertiser valuations), which</p><p>is consistent with economic theory. However, the second price</p><p>auction has little impact on search engine profits. Third, consumer</p><p>search tools lead to a platform revenue increase of 3.7% and an</p><p>increase of consumer welfare of 5.6%. However, these tools, by</p><p>reducing advertising exposure, lower advertiser profits by 4.1%.</p><p>Sponsored Search Auctions: Research Opportunities in Marketing</p><p>In the final chapter, I systematically review the literature on</p><p>keyword search and propose several promising research directions.</p><p>The chapter is organized according to each agent in the search</p><p>process, i.e., searchers, advertisers and the search engine, and</p><p>reviews the key research issues for each. For each group, I outline</p><p>the decision process involved in keyword search. For searchers, this</p><p>process involves what to search, where to search, which results to</p><p>click, and when to exit the search. For advertisers, this process</p><p>involves where to bid, which word or words to bid on, how much to</p><p>bid, and how searchers and auction mechanisms moderate these</p><p>behaviors. The search engine faces choices on mechanism design,</p><p>website design, and how much information to share with its</p><p>advertisers and searchers. These choices have implications for</p><p>customer lifetime value and the nature of competition among</p><p>advertisers. Overall, I provide a number of potential areas of</p><p>future research that arise from the decision processes of these</p><p>various agents.</p><p>Foremost among these potential areas of future research are i) the</p><p>role of alternative consumer search strategies for information</p><p>acquisition and clicking behavior, ii) the effect of advertiser</p><p>placement alternatives on long-term profits, and iii) the measure of</p><p>customer lifetime value for search engines. Regarding the first</p><p>area, a consumer's search strategy (i.e., sequential search and</p><p>non-sequential search) affects which sponsored links are more likely</p><p>to be clicked. The search pattern of a consumer is likely to be</p><p>affected by the nature of the product (experience product vs. search</p><p>product), the design of the website, the dynamic orientation of the</p><p>consumer (e.g., myopic or forward-looking), and so on. This search</p><p>pattern will, in turn, affect advertisers payments, online traffic,</p><p>sales, as well as the search engine's revenue. With respect to the</p><p>second area, advertisers must ascertain the economic value of</p><p>advertising, conditioned on the slot in which it appears, before</p><p>making decisions such as which keywords to bid on and how much to</p><p>bid. This area of possible research suggests opportunities to</p><p>examine how advertising click-through and the number of impressions</p><p>differentially affect the value of appearing in a particular</p><p>sponsored slot on a webpage, and how this value is moderated by an</p><p>appearance in a non-sponsored slot (i.e., a slot in the organic</p><p>search results section). With respect to the third area of future</p><p>research, customer value is central to the profitability and</p><p>long-term growth of a search engine and affects how the firm should</p><p>allocate resources for customer acquisition and retention.</p><p>Organization</p><p>This dissertation is organized as follows. After this brief</p><p>introduction, the essay, ``Online Auction Demand,'' serves as a</p><p>basis that introduces some concepts of auctions as two-sided</p><p>markets. Next, the second essay, ``A Dynamic Model of Sponsored</p><p>Search Advertising,'' extends the first essay by considering a</p><p>richer context of bidder competition and consumer choice behavior.</p><p>Finally, the concluding chapter, which outlines my future research</p><p>interests, considers potential extensions that pertain especially to</p><p>sponsored search advertising.</p> / Dissertation

This dissertation performs economic analysis of search advertising from a comprehensive picture of the competition facing advertisers---by incorporating the price competition to endogenously investigate advertisers' bidding incentive, and taking into account consumers' online search and the unique information structure associated with the search advertising format. It consists of three essays based on game-theoretic modeling. The first essay studies the oligopolistic price competition among advertisers placed in different advertising positions, considering distinctive features of consumers’ online search behaviors. We find an interesting local-competition pattern in which direct price competition occurs only between advertisers adjacent to each other. The second essay integrates the price competition into the bidding competition and investigates the endogenous bidding incentives of advertisers with different competitive strengths. Surprisingly, we find that an advertising position with a better exposure may not always be profitable for the advertisers with competitive advantage, even if it is cost free. We also show that the bidding outcome might not align with the relative competitive strength. The third essay further considers the effects of organic listing as a competing information source on the sponsored bidding competition and the outcome performances in search advertising. It provides answers to questions such as whether and why advertisers with sufficient exposure from the organic list may still be willing to bid for top sponsored positions, and how the existence of organic listing affects search engine’s revenue, consumer surplus, and social welfare. / text

States that sponsor terrorism pose one of the greatest policy and security challenges of the 21st century. Over the past decade, the United States and coalition allies have invested over a trillion dollars in the wars in Afghanistan and Iraq, both waged, in part, to end their support for terrorism. Iran's support for Hezbollah and Hamas makes negotiations over its nuclear program tremendously difficult and the prospect of an Iranian nuclear umbrella, under which these groups could operate, especially concerning. Likewise, Qaddafi's overthrow and the siege on Assad's regime in Syria have both been justified in the context of their historic support for terrorists, as well as the more recent normative concern for the repression of their people. This paper moves beyond a simple explanation of state sponsorship as covert war or way to persuade target states to concede policy objectives. Rather, it models state sponsored terrorism as a leader survival strategy that leaders choose when facing simultaneous internal and external threats. By investing a portion of the state's military power outside the control of the military and into terrorist groups and the security services that arm and train them, the leader is able to signal competency to other elites in his coalition and insulate himself from existing threats of coup d'état from the military while avoiding defeat in external conflict. Using a newly constructed dataset on state sponsorship that uses the leader-year (1968-2001) as the unit of analysis (N=5139), this study finds that many existing explanations for state sponsorship do not withstand empirical testing and that the combined level of high external threat and elevated threat of coup d'état are key determinants of a leader's decision to sponsor terrorist groups. This work has tremendous implications for US security policy as current practices, such as regime-targeted sanctions, may have the unintended effect of increasing the level of threat that the leader experiences and thus the likelihood of state sponsorship. These insights highlight a major reason why military strikes and economic sanctions are less successful than regime change for ending state sponsorship. Furthermore, it suggests that carefully reducing the external and internal levels of threat the leader faces may be the most effective method to end state sponsorship of terrorism. / text

Transportation analysts have monitored with interest the emergence of trip chaining, or multi-purpose trip making, which is becoming a common method of travel for many households. As of 2001, 61% of all working age adults trip chained. From a policy perspective, this warrants attention as these 61% of adults who trip chain generate 68% of average daily vehicle miles traveled (VMT). In addition, most trip chaining is accomplished by automobile and generally alone or with other family members. Trip chaining research has focused predominantly on travel by workers and findings suggest that one reason for its increase is that workers are scheduling non-work activities into their work commute, largely to support household needs (primarily childcare but also for shopping and personal business). Since the 1990s, significant federal funding has supported programs to improve air quality through reduced emissions. These include employer-based programs that seek to reduce VMT through ride sharing and the use of transit, along with incentives for doing so. The success of these programs is based on the flexibility of the commuter to change his/her work mode. As indicated above, however, trip chaining is typically associated with decreased flexibility and almost in direct conflict with programs that encourage alternative commute modes. This research identifies household, demographic, work, and activity setting factors that influence trip chaining in order to understand the related policy implications for employer-based programs that seek to reduce VMT through encouraging alternative commute modes. Using the 2001 National Household Travel Survey, a market segmentation identified trip chaining influencers. These were primarily the presence of children under the age of 16, worker status, more than one household adult, a high vehicle-to-worker ratio, and educational attainment above the high school level. The findings indicate that while between 30 and 42% of workers commute in the traditional manner, employer-based programs can achieve greater returns if increased focus is placed on improving employer amenities. In addition, further VMT reduction can be achieved through new programs that target the household instead of the employer, as evidenced by the TravelSmart program in Australia and SmartTrips program in Portland, OR. / text

This thesis examines the testimonies of victims related to the use of torture during the Pinochet dictatorship. It contends that the existence of a broad testimonial archive on torture, significantly produced by the victims themselves, points to a collective 'speech' by which victims have attempted to splinter the silence of the dictatorial state and, in the aftermath of the repression, to contest the 'official history' of the transitional state. The testimonies of torture victims, it will be argued, signify a specific mode of action, a 'doing' of memory, whereby the experience of torture is re-membered in an effort to bring accountability for the crimes committed and this, from the first days of the dictatorship up to today. This speech of victims moreover is seen to constitute the unifying link between the testimonies of torture victims that have emerged during the dictatorship itself and those that continue to emerge today.

Venture capital finances high-risk, high-return projects. In addition to financing, venture capitalists provide advice and expertise in management, commercialization, and development that enhance the value, success, and marketability of projects. Venture capitalists also have skills in selecting projects with potentially high returns. The first chapter investigates the contracting relationship between venture capitalists and entrepreneurs in a setting where the venture capitalist and entrepreneur contribute intangible assets (advice and effort) to a project that are non-contractible and non-verifiable. In general, in the private market equilibrium, advice provided by the venture capitalist and the number of projects funded are lower than the social optimum. Government tax and investment policies may alleviate these market failures. The impact of a capital gains tax, a tax on entrepreneur’s revenue, an investment subsidy to venture capitalists, and government run project enhancing programs are evaluated. Finally, we analyze the effects of a government venture capital firm competing with private venture capital. The second chapter focuses on competition in venture capital markets. We model a three-stage game of fund raising, investment in innovative projects and input of advice and effort, where fund raising is used as an entry deterrence mechanism. We examine the impacts of taxes and subsidies on venture capital market structure. We find that a tax on venture capitalist revenue and a tax on entrepreneur revenue increase the likelihood of entry deterrence and reduce the number of projects funded in equilibrium. A subsidy on investment reduces the likelihood of entry deterrence and increases the number of projects funded. The third chapter examines the venture capitalist's choice of investment in project selection skills and investment in managerial advice. We model, separately, a private venture capitalist and a labour-sponsored venture capitalist (LSVCC) with different objectives. A LSVCC is a special type of venture capitalist fund that is sponsored by a labour union. The private venture capitalist maximizes its expected profits, while the LSVCC maximizes a weighted function of expected profits and returns to labour. Consistent with empirical evidence, the quality of projects, determined by project selection skills and managerial advice, is higher for the private venture capitalist.

Interpreting user actions to better understand their needs provides an important tool for improving information access services. In the context of organic Web search, considerable effort has been made to model user behavior and infer query intent, with the goal of improving the overall user experience. Much less work has been done in the area of sponsored search, i.e., with respect to the advertisement links (ads) displayed on search result pages by many commercial search engines. This thesis develops and evaluates new models and methods required to interpret user browsing and click behavior and understand query intent in this very different context. The concern of the initial part of the thesis is on extending the query categories for commercial search and on inferring query intent, with a focus on two major tasks: i) enriching queries with contextual information obtained from search result pages returned for these queries, and ii) developing relatively simple methods for the reliable labeling of training data via crowdsourcing. A central idea of this thesis work is to study the impact of contextual factors (including query intent, ad placement, and page structure) on user behavior. Later, this information is incorporated into probabilistic models to evaluate the quality of advertisement links within the context that they are displayed in their history of appearance. In order to account for these factors, a number of query and location biases are proposed and formulated into a group of browsing and click models. To explore user intent and behavior and to evaluate the performance of the proposed models and methods, logs of query and click information provided for research purposes are used. Overall, query intent is found to have substantial impact on predictions of user click behavior in sponsored search. Predictions are further improved by considering ads in the context of the other ads displayed on a result page. The parameters of the browsing and click models are learned using an expectation maximization technique applied to click signals recorded in the logs. The initial motivation of the user to browse the ad list and their browsing persistence are found to be related to query intent and browsing/click behavior. Accommodating these biases along with the location bias in user models appear as effective contextual signals, improving the performance of the existing models.

Thesis (Ph. D.)--University of Hawaii at Manoa, 2005. / Includes bibliographical references. / Also available by subscription via World Wide Web / vii, 188 leaves, bound ill. (some col.) 29 cm

Thesis (Ph. D.)--University of Texas at Austin, 2008. / Vita. Includes bibliographical references.

Thesis (Ph. D.)--University of Hawaii at Manoa, 2005. / Includes bibliographical references.