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.

Orientador: Fernando Antonio Campos Gomide / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-07T11:13:01Z (GMT). No. of bitstreams: 1 Gonzaga_CynthiaSamaradeMedeiros_M.pdf: 6002445 bytes, checksum: ea520ecbc837e9454f7c845b857e88b9 (MD5) Previous issue date: 2006 / Resumo: Agentes computacionais têm um papel importante no comércio eletrônico, pois permitem um melhor aproveitamento de negociações e aumentam o grau de automação do mercado eletrônico. Agentes podem interagir entre si para atingir seus objetivos. Leilões fornecem mecanismos simples de interação e negociação entre agentes e, com o advento da Internet, estão se tomando um veículo eficaz para a realização de negociações eletrônicas intermediadas por agentes. Destaca-se nesse contexto o desenvolvimento de agentes para atuar em leilões eletrônicos simultâneos heterogêneos com bens inter-relacionados. Participar de múltiplos leilões simultaneamente traz a vantagem de permitir, por exemplo, que um agente possa monitorar preços de vários leilões e realizar o negócio naquele que se mostrar mais lucrativo. Além disso, muitas vezes a compra de bens individuais pode não fazer sentido. É o caso, por exemplo, de passagens aéreas e diárias de hotel em agências de viagem; a compra de um bem só se justifica diante da presença do outro. Com o intuito de promover e encorajar pesquisas na área de agentes atuando em leilões eletrônicos simultâneos heterogêneos com bens interrelacionados criou-se uma competição, o Trading Agent Competition-Classic (TAC-Classic). O TACClassic simula uma agência de viagem onde os agentes (participantes da competição) têm o objetivo de propor pacotes de viagem. Os bens são negociados em leilões simultâneos heterogêneos. Esta dissertação versa sobre o agente e-Agent, um dos finalistas do TAC-Classic 2005. O e-Agent utiliza técnicas de inteligência computacional em seus algoritmos de tomada de decisão. A determinação dos bens a serem comprados é realizada através de um modelo de programação linear inteira. A determinação dos valores dos lances a serem realizados é baseada em um método de previsão que determina a tendência dos valores em uma série temporal, um sistema baseado em regras fuzzy do tipo Takagi-Sugeno otimizado via um algo ritmo genético e procedimentos heurísticos. A arquitetura, as estratégias de decisão e a participação do e-Agent na competição são detalhadas e discutidas nesta dissertação / Abstract: Software agents play an important role in the electronic commerce because they allow negotiation and increase the degree of automation. To reach theil< goals, agents interact to communicate, negotiate and decide. Auctions provide a means for interaction and decision of agents especially within the Internet environment. In this context, development of agents to act in electronic simultaneous heterogeneous auctions with inter-related goods is a major issue. It is convenient for an agent to monitor multiple auctions because it increases chances and opportunities to do better deals. For example, it can compare multiple auctions prices in real time and make a bid for the cheapest one. Moreover, often it may not be meaningful to buy individual goods. This is, for example, the case of airline ticket and hotel reservation in many traveI agencies; here to buy of one good may only is justified with the presence other. To promote and encourage high quality research in the area of agents acting in electronic simultaneous heterogeneous auctions with inter-related goods, a market game, namely the Trading Agent Competition-Classic (TAC-Classic), was created. The TAC-Classic simulates a traveI agency scenario where .agents (entrants to the competition) have the goal of assembling traveI packages for their customers. The goods are traded in simultaneous heterogeneous auctions. This dissertation introduces e-Agent agent, a finalist in TAC-Classic 2005. The e-Agent uses decision-making mechanisms based on computational intelligence techniques and integer linear programming to determine the goods to be purchased. Before deciding on bid values, the agent uses a Takagi-Sugeno prediction model optimized by a genetic algorithm and heuristic procedures to compute tendencies of time series. The dissertation details the e-Agent architecture, its decision-making strategies, and reports on its performance during TAC-Classic 2005 / Mestrado / Engenharia de Computação / Mestre em Engenharia Elétrica

Os leilões na Internet têm ganhado muita popularidade, tornando-se uma das mais bem sucedidas formas de comércio eletrônico na atualidade. Apresento um modelo teórico para descrever um leilão ascendente, semelhante ao que ocorre na eBay, e verifico suas previsões comportamentais através de dois experimentos. Os resultados mostraram um distanciamento grande entre as previsões teóricas e o que foi observado na prática, no que se refere às estratégias utilizadas, mas acredito que isso se deva à falta de experiência dos participantes dos experimentos. Desenvolvo, então, programas que automatizam a coleta de dados de leilões de selos na eBay e analiso as variáveis que influenciam preços, número de compradores e lances iniciais (preços mínimos). Não houve surpresas em tal análise, no sentido de observar-se resultados contra-intuitivos, mas destaco a reputação dos vendedores como fator relevante para a determinação de preços finais e número de compradores participantes. Além disso, também destaco a ocorrência da submissão tardia de lances, fenômeno recorrente nos leilões na Internet. Proponho, por fim, um método simples que busca determinar o tipo de modelo de leilão, se de valor comum ou de valor privado, e aplico o método nos dados obtidos dos leilões de selos. O resultado foi o de que os leilões analisados estão enquadrados no modelo de valor comum. / Online auctions are one of the most popular and successful types of electronic commerce nowadays. I present a theoretical framework to address the kind of ascending auction implemented at eBay, and I check its predictions through two experiments. The results of the experiments did not confirm the theory, but I believe this is due to the bidders’ lack of previous experience. I also present an algorithm that automatically gathers data from auctions of stamps at eBay. These data is then used on an exploratory analysis that tries to shed some light on the determinants of final prices, minimum bids and the number of bidders. There were no surprises in this analysis, but I would highlight the measurable effect that seller’s reputation has on final prices and the number of bidders. Furthermore, it was possible to observe the occurrence of late bidding. At last, I propose a simple method that determines to which paradigm the on-line auction of stamps at eBay belongs: private value or common value. The result was that the auction of stamps at eBay belongs to the common value paradigm.

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

The aim of this thesis is to give a comprehensive overview about the internet auctions from several different perspectives, but mainly form the law-related perspective. The relation of the internet auctions to other branches of law is examined -- especially to the consumer protection or the questions of counterfeit goods. Part of this thesis is devoted to pay-per-bid auctions and their place in legal regulations in Czech Republic. The German regulations are also introduced a compared to the Czech ones. In the end there is an introduction to some interests from the auction world.

The predictive power of pre-sale estimates in comparison with hedonic model of hammer price is tested within Czech painters' dataset in Czech and foreign auctions. It appears that pre-sale estimates do not account for all available information from public database which influence hammer price. The determinants of differences are examined on Czech and foreign auctions separately (OLS with instrumental variable) and in addition bought-in works are included into examination of foreign dataset by Heckit model. The same author appears to be the most viable difference in both datasets (after bought-in works inclusion in foreign data). Techniques and supports with higher hammer prices tend to have higher rate of difference between hammer and estimate prices. The influence of the oldest auction houses to higher hammer prices than estimates was confirmed. In Czech environment this influence of some auction house was not registered.

No description available.

Information availability plays a fundamental role in decision-making for business operations. The present dissertation aims to develop frameworks and algorithms in order to guide a decision-maker in environments with limited information. In particular, in the first part, we study the fundamental problem of designing optimal auctions while relaxing the widely used assumption of common prior. We are able to characterize (near-)optimal mechanisms and associated performance. In the second part of the dissertation, we focus on data-driven pricing in the low sample regime. More precisely, we study the fundamental problem of a seller pricing a product based on historical information consisting of one sample of the willingness-to-pay distribution. By drawing connection with the statistical theory of reliability, we propose a novel approach, using dynamic programming, to characterize near-optimal data-driven pricing algorithms and their performance. In the last part of the dissertation, we delve into the detailed practical operations of the online display advertising marketplace from an information structure perspective. In particular, we analyze the tactical role of intermediaries within this marketplace and their impact on the value chain. In turn, we make the case that under some market conditions, there is a potential for Pareto improvement by adjusting the role of these intermediaries.

No description available.

Industrial online-reverse-auctions have become a common procurement strategy used by many firms to reduce the cost of purchased goods and services. The advantages of online-reverse-auctions include significant price reductions, increased purchasing and selling efficiencies, and access to new supply and purchasing markets. Despite these benefits, practitioners and academics alike have raised concerns with respect to the impact of online-reverse-auctions on the buyer-supplier relationship. Previous research suggests that the parameters and characteristics of an online-reverse-auction can influence the perceptions of online-reverse-auction participants. This dissertation investigates this phenomenon by examining how the design of an online-reverse-auction influences the supplier's perception of the buyer-supplier relationship. Specifically, this research considers the effects of online-reverse-auction design in terms of the independent variables of auction control, auction bid visibility, and auction award rules and the dependent variables of supplier commitment to the buyer and supplier trust in the buyer. Using a 2 x 2 x 2 quasi-experimental design and the statistical technique of MANCOVA, this study tests hypotheses related to how different online-reverse-auction design characteristics influence supplier commitment to the buyer and supplier trust in the buyer. The results of the study suggest that the type of online-reverse-auctions buyers utilize can have an impact on supplier perceptions of the buyer supplier relationship. Overall, the result suggest that supplier trust is influenced by the type of auction design buyers utilize, however, supplier commitment is not. Auctions utilizing third party auction providers, partial bid visibility, and post auction negotiations tended to result in higher levels of trust on the part of suppliers. This study makes a contribution to the literature in the following areas. First, this study is one of only a handful of empirical studies examining the effects of online-reverse-auction designs on the buyer-supplier relationship. While a considerable debate exists within the literature concerning the pros and cons of online-reverse-auctions, little empirical work exists. This study makes a contribution by providing insight with respect to how online-reverse-auction designs influence supplier perceptions of the buyer-supplier relationships. Secondly, this analysis considers the buyer-supplier relationship in terms of commitment and trust. Previous studies have largely neglected these constructs despite their prominence in the buyer-supplier relationship literature. Finally, given that the use of online-reverse-auctions seems well entrenched in the purchasing strategies of many buying organizations; this study provides guidance for the design of online-reverse-auctions such that buyers can potentially reduce the negative aspects of the process.