Thesis advisor: Hideo Konishi / Online auctions have many different formats. Each of these affect the ways in which users bid strategically. One example of this is the end-time format. Some sites, like eBay, use a hard close, under which there is a strict end-time and the highest bidder at that time wins. Others, like Amazon, have an extended end-time format. It has been shown that these differences do, in fact, appear to change how bidders behave. This paper uses data obtained from Yahoo! Auctions, where both formats are used, to examine the impact these differences have on the final price of an auction. / Thesis (BA) — Boston College, 2005. / Submitted to: Boston College. College of Arts and Sciences. / Discipline: Economics Honors Program.

This thesis investigated trust over the Internet to seek a better understanding of trust and ways to increase trust in online transactions. The focus of this investigation was consumer-to-consumer transactions at online auctions where key actors were virtually anonymous to each other. The perceptions of a broad range of online auction community members support this thesis. Normative and grounded theoretical perspectives of trust and factors that affected trust were considered, compared and contrasted as part of this research. Concept mapping and the Theory of Planned Behaviour (TPB) were used to underpin the grounded theoretical perspective of trust developed as part of this thesis. Online auction cases were selected and analysed to check the grounded theoretical perspective of trust developed. This thesis provided a better understanding of trust, provided new insights into trust and distrust, added to the body of theory for trust and identified ways to increase trust in online transactions. This thesis provided better understandings of: trust; moral obligations; network decision structures; power; fairness; and perceived behavioural controls at online auctions. A grounded theoretical model of trust based in TPB was developed that was specific to online auctions. This model of trust developed appeared to provide clearer and richer insights into online auction trust. The model of trust developed identified factors and constructs that affected trust rather than the magnitude of any affects. The model developed and findings of this thesis can be applied to new or specific online auction sites to help practitioners build better online environments to encourage more people to transact rather than just browse online. The grounded theoretical perspective of trust and findings of this thesis may be relevant to other online consumer-to-consumer transactional environments.

My dissertation discusses a mechanism that thwarts sniping and improves efficiency in ascending Internet auctions with fixed ending times, specifically eBay. The first research chapter proposes a design of the bidding mechanism and the second chapter tests the effectiveness of the mechanism in a controlled environment. In addition, it presents an innovative theoretical representation of the eBay bidding environment. The first chapter investigates theoretically whether sellers can improve their profits in eBay-like auctions via the implementation of bidder credits. The analysis predicts that providing a credit, similar to a coupon or discount, for early bidding can thwart sniping and increase seller profit. The paper formulates and analyzes a multi-stage auction model with independently and identically distributed private values, where bidders place proxy bids. I show that sniping can emerge as a Bayesian-Nash equilibrium strategy so long as late bids run the risk of not being successfully received by the auctioneer; extending the prior work of Ockenfels and Roth. This equilibrium is inefficient and yields the worst outcome for sellers. The proposed credit mechanism awards a single early bidder a reduction, equal to the value of the credit, in the final price if he wins the auction. The optimal credit satisfies two necessary conditions; first, it increases seller ex-ante profit and second, it incentivizes bidders to deviate from the sniping equilibrium. Relative to the surplus generated by the sniping equilibrium, implementing the credit increases seller surplus and improves welfare. The second chapter experimentally investigates the effectiveness of the credit mechanism. In particular, it compares bidding strategies, seller profit, and overall efficiency in auction environments similar to eBay with and without credit incentives. I observe a significant decline in the frequency of sniping when subjects have the opportunity to receive the credit. The credit also improves auction efficiency primary because subjects overbid in auctions with the credit regardless of which subject has the credit. A within-subjects design allows me to directly compare differences across treatments conditional on the subjects being snipers. Auctions with snipers yield significantly lower profits to sellers because non-sniping rivals are bidding less aggressively when competing against a sniper.

This thesis provides a discussion on some analytical and empirical models of online auctions. The objective is to provide an alternative framework for analyzing online auctions, and to characterize the distribution of intermediate prices. Chapter 1 provides a mathematical formulation of the eBay auction format and background to the data used in the empirical analysis. Chapter 2 analyzes policies for optimally disposing inventory using online auctions. It is assumed a seller has a fixed number of items to sell using a sequence of, possibly overlapping, single-item auctions. The decision the seller must make is when to start each auction. The decision involves a trade-off between a holding cost for each period an item remains unsold, and a cannibalization effect among competing auctions. Consequently the seller must trade-off the expected marginal gain for the ongoing auctions with the expected marginal cost of the unreleased items by further deferring their release. The problem is formulated as a discrete time Markov Decision Problem. Conditions are derived to ensure that the optimal release policy is a control limit policy in the current price of the ongoing auctions. Chapter 2 focuses on the two item case which has sufficient complexity to raise challenging questions. An underlying assumption in Chapter 2 is that the auction dynamics can be captured by a set of transition probabilities. Chapter 3 shows with two fixed bidding strategies how the transition probabilities can be derived for a given auction format and bidder arrival process. The two specific bidding strategies analyzed are when bidders bid: 1) a minimal increment, and 2) their true valuation. Chapters 4 and 5 provides empirical analyzes of 4,000 eBay auctions conducted by Dell. Chapter 4 provides a statistical model where over discrete time periods, prices of online auctions follow a zero-inflated gamma distribution. Chapter 5 provides an analysis of the 44,000 bids placed in the auctions, based on bids following a gamma distribution. Both models presented in Chapters 4 and 5 are based on conditional probabilities given the price and elapsed time of an auction, and certain parameters of the competing auctions. Chapter 6 concludes the thesis with a discussion of the main results and possible extensions.

This thesis provides a discussion on some analytical and empirical models of online auctions. The objective is to provide an alternative framework for analyzing online auctions, and to characterize the distribution of intermediate prices. Chapter 1 provides a mathematical formulation of the eBay auction format and background to the data used in the empirical analysis. Chapter 2 analyzes policies for optimally disposing inventory using online auctions. It is assumed a seller has a fixed number of items to sell using a sequence of, possibly overlapping, single-item auctions. The decision the seller must make is when to start each auction. The decision involves a trade-off between a holding cost for each period an item remains unsold, and a cannibalization effect among competing auctions. Consequently the seller must trade-off the expected marginal gain for the ongoing auctions with the expected marginal cost of the unreleased items by further deferring their release. The problem is formulated as a discrete time Markov Decision Problem. Conditions are derived to ensure that the optimal release policy is a control limit policy in the current price of the ongoing auctions. Chapter 2 focuses on the two item case which has sufficient complexity to raise challenging questions. An underlying assumption in Chapter 2 is that the auction dynamics can be captured by a set of transition probabilities. Chapter 3 shows with two fixed bidding strategies how the transition probabilities can be derived for a given auction format and bidder arrival process. The two specific bidding strategies analyzed are when bidders bid: 1) a minimal increment, and 2) their true valuation. Chapters 4 and 5 provides empirical analyzes of 4,000 eBay auctions conducted by Dell. Chapter 4 provides a statistical model where over discrete time periods, prices of online auctions follow a zero-inflated gamma distribution. Chapter 5 provides an analysis of the 44,000 bids placed in the auctions, based on bids following a gamma distribution. Both models presented in Chapters 4 and 5 are based on conditional probabilities given the price and elapsed time of an auction, and certain parameters of the competing auctions. Chapter 6 concludes the thesis with a discussion of the main results and possible extensions.

Consumer-to-consumer (C2C) online auctions represent an important new marketplace from which consumers can access the goods they require, an alternative marketplace to bricks-and-mortar and online retail stores. Sellers are often ordinary consumers and the items on sale are often second-hand household items, although, modern C2C auction sites also accommodate small businesses selling unused products. Consumer behaviour in online C2C auctions is unlike consumer behaviour in bricks-and-mortar or online retail stores. While considerable research has been conducted into the dynamics of bidding in online C2C auctions little research has addressed the motives for consumers’ ongoing participation in this marketplace. The concept of consumer involvement may explain the amount of time and money consumers are spending in online C2C auctions and the frequency of their visits to auction sites. In the context of this thesis, involvement is defined as the long-term and enduring relevance, connection and relatedness of online auctions to a consumer’s life. The aim of this research is to explore the ways in which the consumer involvement construct offers an explanation for variation in buyers’ ongoing use of online auctions. The thesis also seeks to discover which consumer motives contribute to buyers’ enduring involvement with online auctions. TradeMe is New Zealand’s most popular online C2C auction site. In a country of just four million people, the TradeMe auction site has more than 2 million members and accounts for more than 50 per cent of Internet traffic originating from New Zealand websites. This study of buyers who use the TradeMe auction site, offers the opportunity to study online auction consumers in this unique context. Based on an extensive literature review, eighteen propositions were developed regarding buyer motives for enduring involvement with online C2C auctions. In-depth, semi-structured interviews were conducted with twenty TradeMe users, to test these propositions and to identify any further motives for enduring involvement with auctions that had not been revealed in the literature review. Interviews were audio-recorded and transcribed in full. NVivo8 qualitative data analysis software was used to code the interview transcripts. Thematic analysis reveals six themes representing buyer motives for enduring involvement with online auctions. The significant contribution of this thesis is to identify involvement as a useful construct for explaining consumer behaviour in online auctions. In addition to utilitarian and hedonic motives for involvement with online auctions, the interviews reveal that the buyers have a number of social and personal motives for involvement with online auctions. Analysis of the qualitative dataset also reveals a set of marketer activities which encourage ongoing use of the auction site, and a number of factors (anti-motives) which discourage use of the auction site. The research reveals the existence of an off-line community of auction users who value the social contact they experience with one another outside the auction site. Ongoing buyer-seller relationships are also shown to develop outside the auction site, prompted by an initial auction transaction. TradeMe users often express loyalty to the TradeMe website because they are proud of its New Zealand origins, feel secure in using a local auction website, believe they are supporting small New Zealand businesses by buying from TradeMe, and believe they are practicing sustainable consumption behaviour by purchasing second-hand goods. Future research should develop a multi-item, quantitative measure of buyers’ enduring involvement with online auctions and test the validity of this measure with further empirical data.

This thesis investigated trust over the Internet to seek a better understanding of trust and ways to increase trust in online transactions. The focus of this investigation was consumer-to-consumer transactions at online auctions where key actors were virtually anonymous to each other. The perceptions of a broad range of online auction community members support this thesis. Normative and grounded theoretical perspectives of trust and factors that affected trust were considered, compared and contrasted as part of this research. Concept mapping and the Theory of Planned Behaviour (TPB) were used to underpin the grounded theoretical perspective of trust developed as part of this thesis. Online auction cases were selected and analysed to check the grounded theoretical perspective of trust developed. This thesis provided a better understanding of trust, provided new insights into trust and distrust, added to the body of theory for trust and identified ways to increase trust in online transactions. This thesis provided better understandings of: trust; moral obligations; network decision structures; power; fairness; and perceived behavioural controls at online auctions. A grounded theoretical model of trust based in TPB was developed that was specific to online auctions. This model of trust developed appeared to provide clearer and richer insights into online auction trust. The model of trust developed identified factors and constructs that affected trust rather than the magnitude of any affects. The model developed and findings of this thesis can be applied to new or specific online auction sites to help practitioners build better online environments to encourage more people to transact rather than just browse online. The grounded theoretical perspective of trust and findings of this thesis may be relevant to other online consumer-to-consumer transactional environments.

Consumer-to-consumer (C2C) online auctions represent an important new marketplace from which consumers can access the goods they require, an alternative marketplace to bricks-and-mortar and online retail stores. Sellers are often ordinary consumers and the items on sale are often second-hand household items, although, modern C2C auction sites also accommodate small businesses selling unused products. Consumer behaviour in online C2C auctions is unlike consumer behaviour in bricks-and-mortar or online retail stores. While considerable research has been conducted into the dynamics of bidding in online C2C auctions little research has addressed the motives for consumers’ ongoing participation in this marketplace. The concept of consumer involvement may explain the amount of time and money consumers are spending in online C2C auctions and the frequency of their visits to auction sites. In the context of this thesis, involvement is defined as the long-term and enduring relevance, connection and relatedness of online auctions to a consumer’s life. The aim of this research is to explore the ways in which the consumer involvement construct offers an explanation for variation in buyers’ ongoing use of online auctions. The thesis also seeks to discover which consumer motives contribute to buyers’ enduring involvement with online auctions. TradeMe is New Zealand’s most popular online C2C auction site. In a country of just four million people, the TradeMe auction site has more than 2 million members and accounts for more than 50 per cent of Internet traffic originating from New Zealand websites. This study of buyers who use the TradeMe auction site, offers the opportunity to study online auction consumers in this unique context. Based on an extensive literature review, eighteen propositions were developed regarding buyer motives for enduring involvement with online C2C auctions. In-depth, semi-structured interviews were conducted with twenty TradeMe users, to test these propositions and to identify any further motives for enduring involvement with auctions that had not been revealed in the literature review. Interviews were audio-recorded and transcribed in full. NVivo8 qualitative data analysis software was used to code the interview transcripts. Thematic analysis reveals six themes representing buyer motives for enduring involvement with online auctions. The significant contribution of this thesis is to identify involvement as a useful construct for explaining consumer behaviour in online auctions. In addition to utilitarian and hedonic motives for involvement with online auctions, the interviews reveal that the buyers have a number of social and personal motives for involvement with online auctions. Analysis of the qualitative dataset also reveals a set of marketer activities which encourage ongoing use of the auction site, and a number of factors (anti-motives) which discourage use of the auction site. The research reveals the existence of an off-line community of auction users who value the social contact they experience with one another outside the auction site. Ongoing buyer-seller relationships are also shown to develop outside the auction site, prompted by an initial auction transaction. TradeMe users often express loyalty to the TradeMe website because they are proud of its New Zealand origins, feel secure in using a local auction website, believe they are supporting small New Zealand businesses by buying from TradeMe, and believe they are practicing sustainable consumption behaviour by purchasing second-hand goods. Future research should develop a multi-item, quantitative measure of buyers’ enduring involvement with online auctions and test the validity of this measure with further empirical data.

In this dissertation, we model and provide insights to some of the main challenges the world of online marketing currently faces. In the first chapter, we study the role of information asymmetry introduced by the presence of experts in online marketplaces and how it affects the strategic decisions of different parties in these markets. In the second chapter, we study the attribution problem in online advertising and examine optimal ways for advertisers to allocate their marketing budget across channels. In the third chapter, we explore the effects of modern ad blockers on users and online platforms. In the first chapter, we examine the effect of the presence of expert buyers on other buyers, the platform, and the sellers in online markets. We model buyer expertise as the ability to accurately predict the quality, or condition, of an item, modeled as its common value. We show that nonexperts may bid more aggressively, even above their expected valuation, to compensate for their lack of information. As a consequence, we obtain two interesting implications. First, auctions with a “hard close” may generate higher revenue than those with a “soft close”. Second, contrary to the linkage principle, an auction platform may obtain a higher revenue by hiding the item’s common-value information from the buyers. We also consider markets where both auctions and posted prices are available and show that the presence of experts allows the sellers of high quality items to signal their quality by choosing to sell via auctions. In the second chapter, we study the problem of attributing credit for customer acquisition to different components of a digital marketing campaign using an analytical model. We investigate attribution contracts through which an advertiser tries to incentivize two publishers that affect customer acquisition. We situate such contracts in a two-stage marketing funnel, where the publishers should coordinate their efforts to drive conversions. First, we analyze the popular class of multi-touch contracts where the principal splits the attribution among publishers using fixed weights depending on their position. Our first result shows the following counterintuitive property of optimal multi-touch contracts: higher credit is given to the portion of the funnel where the existing baseline conversion rate is higher. Next, we show that social welfare maximizing contracts can sometimes have even higher conversion rate than optimal multi-touch contracts, highlighting a prisoners’ dilemma effect in the equilibrium for the multi-touch contract. While multi-touch attribution is not globally optimal, there are linear contracts that “coordinate the funnel” to achieve optimal revenue. However, such optimal-revenue contracts require knowledge of the baseline conversion rates by the principal. When this information is not available, we propose a new class of ‘reinforcement’ contracts and show that for a large range of model parameters these contracts yield better revenue than multi-touch. In the third chapter, we study the effects of ad blockers in online advertising. While online advertising is the lifeline of many internet content platforms, the usage of ad blockers has surged in recent years presenting a challenge to platforms dependent on ad revenue. In this chapter, using a simple analytical model with two competing platforms, we show that the presence of ad blockers can actually benefit platforms. In particular, there are conditions under which the optimal equilibrium strategy for the platforms is to allow the use of ad blockers (rather than using an adblock wall, or charging a fee for viewing ad-free content). The key insight is that allowing ad blockers serves to differentiate platform users based on their disutility to viewing ads. This allows platforms to increase their ad intensity on those that do not use the ad blockers and achieve higher returns than in a world without ad blockers. We show robustness of these results when we allow a larger combination of platform strategies, as well as by explaining how ad whitelisting schemes offered by modern ad blockers can add value. Our study provides general guidelines for what strategy a platform should follow based on the heterogeneity in the ad sensitivity of their user base.

This thesis provides a discussion on some analytical and empirical models of online auctions. The objective is to provide an alternative framework for analyzing online auctions, and to characterize the distribution of intermediate prices. Chapter 1 provides a mathematical formulation of the eBay auction format and background to the data used in the empirical analysis. Chapter 2 analyzes policies for optimally disposing inventory using online auctions. It is assumed a seller has a fixed number of items to sell using a sequence of, possibly overlapping, single-item auctions. The decision the seller must make is when to start each auction. The decision involves a trade-off between a holding cost for each period an item remains unsold, and a cannibalization effect among competing auctions. Consequently the seller must trade-off the expected marginal gain for the ongoing auctions with the expected marginal cost of the unreleased items by further deferring their release. The problem is formulated as a discrete time Markov Decision Problem. Conditions are derived to ensure that the optimal release policy is a control limit policy in the current price of the ongoing auctions. Chapter 2 focuses on the two item case which has sufficient complexity to raise challenging questions. An underlying assumption in Chapter 2 is that the auction dynamics can be captured by a set of transition probabilities. Chapter 3 shows with two fixed bidding strategies how the transition probabilities can be derived for a given auction format and bidder arrival process. The two specific bidding strategies analyzed are when bidders bid: 1) a minimal increment, and 2) their true valuation. Chapters 4 and 5 provides empirical analyzes of 4,000 eBay auctions conducted by Dell. Chapter 4 provides a statistical model where over discrete time periods, prices of online auctions follow a zero-inflated gamma distribution. Chapter 5 provides an analysis of the 44,000 bids placed in the auctions, based on bids following a gamma distribution. Both models presented in Chapters 4 and 5 are based on conditional probabilities given the price and elapsed time of an auction, and certain parameters of the competing auctions. Chapter 6 concludes the thesis with a discussion of the main results and possible extensions. / Business, Sauder School of / Graduate