The international and commercialised recognition of the Olympic Games can bring upon prestigious benefits to a country's Olympic Games legacy. Due to this, candidate cities have capitalised on this opportunity to leverage their bids to successfully secure hosting rights. Consequently, this has commodified the bidding process, which has intensified the competition and the declining number of bids over recent years. Thus, jeopardising the legitimacy of the Olympic Games bids to its true values of Olympism. Hence, utilising a semi-systematic literature review, this thesis aims to investigate the extent and in what ways the Olympic Games bids have embodied the values of Olympism. Specifically exploring within three case-study examples; the Beijing 2008; the London 2012; and the Rio De Janeiro 2016 Summer Olympic Games. Adopting a thematic analysis and theoretical framework, findings have noted four overarching themes that influence the leveraging of bids; Economical, Political, Globalisation and the Public (Social). Further, and to a vague extent, the selected Olympic Games bids embodied the values of Olympism as secondary and appear to be a by-product of a prominent agenda that reflects the ebb and flow of politics and economics of the respective host-city. Interestingly, by examining the Olympism philosophy and legacy this may not be an issue due to its abstract construction and lack of precision, which has enabled great flexibility. As a resolution, this thesis calls for the values to be measurable and the implementation of evaluative committees that span beyond the Olympic Games to ensure Olympism values and its legacy is embodied successfully.

This dissertation consists of two essays on the topic of bidding in multi-unit common value auction. Essay one examines the role of capacity constraint on the auction results and bidding behavior. We consider a general case where bidders are unconstrained, and a second setting where bidders are capacity constrained. We document downward sloping demand curves for individual bidders. Bidders shade their bids by submitting quantity-price pairs and spreading their bids. The winner's curse is strong in the unconstrained treatment, but we find no evidence of the winner's curse when bidding constraints are imposed. Unconstrained bidders shade bids significantly more and their quantity-weighted prices are much lower than those in the constrained treatment. Interacting with the information structure, the capacity constraint has a significant impact on the auction results including the market clearing price, market efficiency, and the degree of market concentration. We provide evidence that efficient price discovery in multi-unit auctions with diverse information is possible, but careful attention to auction design will make this outcome more likely. Essay two examines how the introduction of a noncompetitive bidding option affects outcomes in a multi-unit uniform-price auction. The experimental design incorporates many of the characteristics of the markets that pertain to the issuance of new equity securities. Important features of the bidding environment include endogenous bidder entry, costly information acquisition, bidders that differ by capacity constraint, and substantial uncertainty with respect to the intrinsic value. We use a standard uniform-price auction as our baseline setting where only competitive bids are accepted. Our results show that introducing the noncompetitive bidding option improves auction performance by increasing revenue and reducing price error. Underpricing is found in both treatments, but is less severe in the presence of the noncompetitive bidding option. The incorporation of this option significantly increases both the small bidder participation rate and allocation, and reduces the incentive for small bidders to free ride by submitting extremely high bids. Under both treatments, information acquisition increases large bidders' profits but proves unprofitable for small bidders, and pricing accuracy is increasing in the rate of information acquisition.

The increasing availability of richer, high-dimensional, home sales data-sets, as well as spatially geocoded data, allows for the use of new econometric and computational methods to explore novel research questions. This dissertation consists of three separate research papers which aim to leverage this trend to answer empirical inferential questions, propose new computational approaches in environmental valuation, and address future challenges. The first research chapter estimates the effect on home values of 10 large-scale urban stream restoration projects situated near the project sites. The study area is the Johnson Creek Watershed in Portland, Oregon. The research design incorporates four matching model approaches that vary based on the temporal bands' width, a narrow and a wider band, and two spatial zoning buffers, a smaller and larger that account for the affected homes' distances. Estimated effects tend to be positive for six projects when the restoration projects' distance is smaller, and the temporal bands are narrow, while two restoration projects have positive effects on home values across all four modeling approaches. The second research chapter focuses on the underlying statistical and computational properties of matching methods for causal treatment effects. The prevailing notion in the literature is that there is a tradeoff between bias and variance linked to the number of matched control observations for each treatment unit. In addition, in the era of Big Data, there is a paucity of research addressing the tradeoffs between inferential accuracy and computational time across different matching methods. Is it worth employing computationally costly matching methods if the gains in bias reduction and efficiency are negligible? We revisit the notion of bias-variance tradeoff and address the subject of computational time considerations. We conduct a simulation study and evaluate 160 models and 320 estimands. The results suggest that the conventional notion of a bias-variance tradeoff, with bias increasing and variance decreasing with the number of matched controls, does not hold under the bias-corrected matching estimator (BCME), developed by Abadie and Imbens (2011). Specifically, for the BCME, the trend of bias decreases as the number of matches per treated unit increases. Moreover, when the pre-matching balance's quality is already good, choosing only one match results in a significantly larger bias under all methods and estimators. In addition, the genetic search matching algorithm, GenMatch, is superior compared to the baseline Greedy Method by achieving a better balance between the observed covariate distributions of the treated and matched control groups. On the down side, GenMatch is 408 times slower compared to a greedy matching method. However, when we employ the BCME on matched data, there is a negligible difference in bias reduction between the two matching methods. Traditionally, environmental valuation methods using residential property transactions follow two approaches, hedonic price functions and Random Utility sorting models. An alternative approach is the Iterated Bidding Algorithm (IBA), introduced by Kuminoff and Jarrah (2010). This third chapter aims to improve the IBA approach to property and environmental valuation compared to its early applications. We implement this approach in an artificially simulated residential housing market, maintaining full control over the data generating mechanism. We implement the Mesh Adaptive Direct Search Algorithm (MADS) and introduce a convergence criterion that leverages the knowledge of individuals' actual pairing to homes. We proceed to estimate the preference parameters of the distribution of an underlying artificially simulated housing market. We estimate with significantly higher precision than the original baseline Nelder-Mead optimization that relied only on a price discrepancy convergence criterion, as implemented during the IBAs earlier applications. / Doctor of Philosophy / The increasing availability of richer, high-dimensional, home sales data sets enables us to employ new methods to explore novel research questions involving housing markets. This dissertation consists of three separate research papers which leverage this trend. The first research paper estimates the effects on home values of 10 large-scale urban stream restoration projects in Portland, Oregon. These homes are located near the project sites. The results show that the distance of the homes from the project sites and the duration of the construction cause different effects on home values. However, two restorations have positive effects regardless of the distance and the duration period. The second research study is focused on the issue of causality. The study demonstrates that a traditional notion concerning causality known as the ``bias-variance tradeoff" is not always valid. In addition, the research shows that sophisticated but time-consuming algorithms have negligible effects in improving the accuracy of estimating the causal effects when we account for the required computational time. The third research study improves an environmental evaluation method that relies on residential property transactions. The methodology leverages the features of more informative residential data sets in conjunction with a more efficient optimization method, leading to significant improvements. The study concludes that due to these improvements, this alternative method can be employed to elicit the true preferences of homeowners over housing and locational characteristics by avoiding the shortcomings of existing techniques.

<div>The practice of project bundling, which involves combining multiple projects into a single multi-project contract, is in increased use at infrastructure agencies. Researchers have shown that this practice potentially reduces project cost but could cause undesirable consequences such as reduced market competition. For this reason, bundling policy needs to be guided by a determination of whether specific projects should be bundled, the bundling strategy in terms of bundle size, bundling combinations, geographical locations, and project scheduling, and the resulting outcome of each strategy in the terms of contract performance (overall cost and time duration, and cost and time overrun). Practitioners seeking answers to these questions continue to be stymied by the lack of quantified relationships between bundling alternatives and the resulting contract performance.</div><div>This dissertation addresses these questions by analyzing empirical data including the costs and durations of highway contracts and projects over a ten-year period. Using a variety of modeling approaches, the dissertation developed models to quantify the effects of bundling-related factors on the key contract performance measures (CPMs). The bundling related factors are contract size, bundle size, project combinations, project similarity and spatial proximity between bundled projects, and the CPMs are project cost and time performance, market competition, and the risks of cost overrun and project delay. Through the modeling process, the dissertation measured the effects of project similarity, economies of scale, economies of bundling, and economies of competition on bundling, and developed a novel technique to measure similarities between projects. Using the developed models, the dissertation then established an optimization framework to identify cost-effective bundling strategies. A greedy approach that minimizes the overall cost in a polynomial time was proposed to obtain heuristic solutions. The outcomes of this dissertation are twofold: first, it provides highway agencies with a quick, convenient and robust tool to design long-term cost-effective bundling strategies for any given pool of candidate projects; secondly, it provides guidelines and directions for future bundling policy formulation or evaluation. </div>

One goal of every business is to save money, and building strategies that work to minimize spending and maximize profit is key to the success of a company. Cidewalk is a mobile advertisement company that wished to implement an optimal bidding strategy to help reduce the company's cost and in turn maximize their profits. To accomplish this goal we collected market data which was then analyzed to identify the distribution of second best bids, which is the price Cidewalk pays for an advertisement space by bidding in a Vickrey auction. The optimal bidding model was then implemented through a simulation together with Bayesian updating methods to ensure the model would be responsive to changes in the market. The model's performance was evaluated through the simulation and it was discovered that throughout one day the implemented model yielded 17% savings when compared to Cidewalk's current bidding model.

One goal of every business is to save money, and building strategies that work to minimize spending and maximize profit is key to the success of a company. Cidewalk is a mobile advertisement company that wished to implement an optimal bidding strategy to help reduce the company's cost and in turn maximize their profits. To accomplish this goal we collected market data which was then analyzed to identify the distribution of second best bids, which is the price Cidewalk pays for an advertisement space by bidding in a Vickrey auction. The optimal bidding model was then implemented through a simulation together with Bayesian updating methods to ensure the model would be responsive to changes in the market. The model's performance was evaluated through the simulation and it was discovered that throughout one day the implemented model yielded 17% savings when compared to Cidewalk's current bidding model.

[pt] O WiMAX é um padrão de tecnológico de broadband wireless que tem o potencial de oferecer infra-estrutura para conectividade de última milha para clientes corporativos e residências, abrangendo grandes distâncias e oferecendo uma alternativa ao DSL e cabo. Este novo padrão wireless é percebido pelas empresas de telecomunicações como uma oportunidade de ganhar penetração em localidades onde ainda não são oferecidas soluções de banda larga. Como qualquer padrão wireless, o WiMAX necessita de faixas de espectros de freqüência para operar, e como as faixas de freqüências são bens públicos e escassos, as mesmas são licitadas pelo órgão regulador garantindo exclusividade no seu uso. Este trabalho avalia quanto uma empresa pode ofertar numa licitação de blocos de freqüência na faixa de 3,5GHz que serão utilizados para operar um rede WiMAX tanto pelo método tradicional do FCD quanto pela teoria das opções reais. No mercado de telecomunicações, este tipo de projeto apresenta grandes incertezas e também significativas flexibilidades gerenciais, o que indica que a teoria de opções reais pode ser mais adequada para este tipo de análise. Os resultados obtidos conferem isso e as opções do projeto aumentaram seu valor em 149%, permitindo à empresa elevar o valor máximo a ser ofertado na licitação em até 58% do valor original obtido pelo FCD, aumentando as chances de vencer a licitação e investir em um projeto rentável. / [en] WiMAX is a broadband wireless technology developed as an alternative to DSL and cable, to offer infrastructure last mile connectivity for business and residential clients, covering great distance. This new wireless standard is considered in telecommunication marketing as an opportunity to offer broadband in areas where this service does not exist. As any wireless standard, WiMAX requires spectrum allocations to operate, and as frequency bands are scarce public assets, they are bid out by the regulatory agency to assure exclusivity. In this dissertation we value the bid for some frequency bands of the 3,5GHz WiMAX frequency spectrum, under both Discounted Cash Flow methods (DCF) and Real Option Valuation. In the telecommunications market, this type of project presents great uncertainty and flexibility, which implies that real option valuation is the best alternative for this analysis. The results shows that the options embedded in the project increase its value by up to 149% when compared to the DCF approach. This allows the firm to increase the value of its bid by up to 58%, increasing its chances of wining a profitable project.

Em diversos mercados de energia onde há competição, a formação de preços de energia elétrica no mercado de curto prazo decorre do equilíbrio da oferta e da demanda, onde geradores e grandes consumidores informam, em periodicidade horária ou inferior, as quantidades de energia e preços associados aos quais estão dispostos a produzir e consumir, respectivamente. No Brasil, no entanto, a demanda utilizada no modelo de formação de preço de energia elétrica no curto prazo (PLD) é considerada inelástica em relação ao preço. Por mais que se possam constatar sinais de resposta da demanda frente à volatilidade do PLD, ou ao custo com uso da rede de transmissão e distribuição no período de ponta, não há mecanismo estabelecido para que os consumidores ofertem as quantidades de energia e preços aos quais estão dispostos a reduzir seu consumo. O presente trabalho tem o objetivo de apresentar proposta de alteração no processo de formação de preço no curto prazo de modo a permitir a Oferta da Redução do Consumo (ORC) pelos consumidores industriais. A proposta parte da representação do parque termelétrico atual, que serve de base para o valor da oferta de redução do consumo, as adaptações para introdução da curva de operação para fins de consideração da redução de consumo, bem como metodologia para aferição do montante de energia efetivamente reduzido. Além disso, de modo a apresentar o potencial benefício sistêmico com a introdução da proposta, são apresentadas simulações com a cadeia de modelos de formação de preço atual tendo como base a indústria de alumínio no Brasil. Os cenários de ORC da indústria levam em consideração parâmetros econômicos que asseguram a atratividade do negócio em consonância com o benefício sistêmico de redução do custo de operação. Apresenta-se ainda simulação da operação do ano de 2015 com estimativa do potencial de ORC no Ambiente de Contratação Livre (ACL) onde se constatou reduções de até 25% no Custo Marginal de Operação (CMO) e 16% de redução despacho termelétrico. / In several competitive power markets, short term power price is the result of the balance of supply and demand represented by bid and ask prices and energy quantities. In Brazil, short term power price (PLD) calculated by Newave/Decomp price models consider price-inflexible demand, even though traces of demand response to short term power prices and demand tariffs can be identified. The purpose of this Thesis is the proposal of changes in process of power pricing allowing large energy consumers bid their price to curtail their consumption in substitution of thermal power dispatch. Topics included in proposal are: cost of installed thermal power plants in power system, industrial demand curtail and restart features, and demand response effectiveness appraisal tools. Current power price models were employed on simulations to evaluate system\'s benefits with demand response. From an industrial perspective, accounting measures were basis to convert loss of production in demand-side bidding price in order to keep business profitability. Estimate of demand side bidding potential market in Brazilian free market with simulation of system impact in 2015 with results that reached 25% of Marginal Cost reduction and 16% of Thermal Dispatch reduction.

O setor público brasileiro passa por momentos de desenvolvimento em sua forma de gestão, objetivando maior aproximação com as técnicas de gestão do setor privado, que utilizam métodos e conceitos mais eficientes. Esta pesquisa utilizou o conceito do Custo Total de Propriedade - CTP (Total Cost of Ownership, traduzido do inglês) como forma de aprimorar o processo de aquisições de bens duráveis, no caso, veículos, que atualmente é pautado na Lei de Licitações (Lei 8.666 de 1993), que possui o menor preço como critério de decisão de compra. Baseado no CTP, o preço de aquisição é apenas uma variável de custo a ser analisado durante o processo de compra, devendo também haver análise dos custos pós-aquisição e de descarte, fatores que não estão formalizados no processo de aquisição atual e tampouco existem no momento do pregão. Esse conceito traz a definição de compra mais vantajosa, como aquela que possui o menor CTP e não apenas o menor preço de aquisição; portanto, objetiva-se investigar quais aspectos seriam impactados com a aplicação prática do conceito de CTP no fluxo de aquisição de um bem durável em um órgão público. Com isso, a questão a ser respondida é: quais aspectos seriam impactados com a aplicação prática do conceito do Custo Total de Propriedade no fluxo de aquisição de um bem durável em um órgão público. Esta pesquisa se enquadra como qualitativa, com aplicação de questionário semiestruturado aos atores responsáveis pelo processo licitatório da Prefeitura de Franco da Rocha - SP, para: (i) formalizar o atual fluxo de aquisições de veículos; (ii) entender sua percepção sobre aplicação do CTP no processo; e ainda (iii) captar as possíveis variáveis de custo a serem mensuradas na realidade daquela municipalidade. Para fins de validação de informações, foram coletados dados com análise documental de editais de licitações de compras de veículos de 2013 a 2016, sendo necessárias também para composição do exercício de mensuração do CTP. Foram utilizadas as variáveis extraídas das respostas dos entrevistados e sugeriu-se a utilização de novas variáveis para que o cálculo se tornasse mais amplo. Com relação aos resultados, foi possível observar que os aspectos impactados com a aplicação do CTP no processo de aquisição foram: (i) melhora da descrição técnica do bem na etapa inicial realizada pelo solicitante do bem, permeando itens que viabilizem o CTP e que possam influenciar positivamente a qualidade dos bens; e (ii) acurácia na projeção de custos pós-aquisição para atendimento da Lei de Responsabilidade Fiscal - LRF. Espera-se que haja desenvolvimento das técnicas de gestão de compras em órgãos públicos com uso eficiente dos recursos públicos no que diz respeito aos custos com aquisições, além de demonstrar de forma didática o cálculo e algumas variáveis de custos que podem ser padronizadas no processo de aquisições. / The Brazilian public sector is going through a period of development on its management form, aiming greater approximation with the private sector management techniques, which use more efficient methods and concepts. This research used the concept of TCO - Total Cost of Ownership to improve the process of durable goods acquisition, in this case, vehicles, nowadays grounded by the Brazilian Bidding Law (Law 8.666 of 1993), which has the lowest price as criteria for purchase decision. Based on the TCO, the acquisition price is just a cost variable to be analyzed during the purchase process. There should also be a post-acquisition and disposal cost analysis, factors not formalized in the current acquisition process and neither existing in the trading session. This concept brings the definition of the most advantageous purchase, such as the one that has the lowest TCO and not only the lowest acquisition price; therefore, it aims to investigate which aspects would be impacted by the practical application of the TCO concept in a durable good acquisition flow in a public body. Thus, the question to be answered is which aspects would be impacted by the practical application of the Total Cost of Ownership concept in a durable good acquisition flow in a public body. This research can be classified as qualitative, with the application of a semi-structured questionnaire on the people responsible for the bidding process in the Municipality of Franco da Rocha - SP, to (i) formalize the current flow of vehicles acquisition; (ii) understand their perception of the TCO in the process; and (iii) find possible cost variables to be measured in the reality of that municipality. For purposes of information validation, there were collected data with documentary analysis of the bidding documents for vehicles purchases from 2013 to 2016, also being necessary for the composition of the TCO measurement exercise. Extracted variables from the respondents\' answers were used and it was suggested the application of new variables for the calculation to be broader. Regarding the results, it was possible to observe that the aspects impacted by the TCO application were: (i) improvement of the technical description of the good in the initial stage carried out by the good requestor, permeating items that make the TCO viable and can positively influence the quality of goods; and (ii) accuracy in the projection of post-acquisition costs for compliance with the Fiscal Responsibility Law - LRF. It is expected that there will be a development of the management purchase techniques in public bodies with efficient use of public resources regarding costs acquisitions, as well as demonstrating, in a didactic way, the calculation and some cost variables that can be standardized in the acquisition process.

On the one hand, the demand response management and dynamical pricing supported by the smart grid had started to lead to fundamentally different energy consumption behaviours; On the other hand, energy supply has gone through a dramatic new pattern due to the emergence and development of renewable energy resources. Facing these changes, this thesis investigates one of the resulting challenges, which is how to integrate the wholesale market and the retail market into one framework in order to achieve optimal balancing between demand and supply. Firstly, based on the existing mechanisms of the wholesale and retail electricity markets, a simulation tool is proposed and developed. This enables the ISO to find the best balance between supply and demand, by taking into account the different objectives of the generators, retailers and customers. Secondly, a new market mechanism based on the interval demand is proposed in order to address the challenges of the unpredictable demand due to the demand response management programs. Under the proposed new market mechanism, the corresponding approaches are investigated in order to support the retailers to find their profit-optimal pricing strategies, the generators to develop their best bidding strategies, and the ISO to identify the market clearing price function in order to best balance supply and demand. In particular: 1) For the ISO, our designed mechanism could effectively handle unpredictable demand under the dynamic retail pricing. It also enables the realisation of the goals of dynamic pricing by utilising smart meters; 2) In the retail market, we extend the smart pricing model in the current research in order to enable the retailers to find the most-profitable pricing scheme under the proposed new mechanism with the demand-based piecewise cost (i.e., market clearing price) function; 3) For the wholesale market, we developed a pricing forecasting model in order to forecast a market clearing price. Based on this model, we analysed the optimal bidding strategies for a generator under an interval demand from the ISO. Simulation results are provided in order to verify the effectiveness of the proposed approaches.