No / Reverse e-auctions are increasingly being used in business-to-business procurement and have been reported to yield significant price reductions for buyer firms. However, the adoption of online auction formats has raised many concerns among suppliers, often being criticized for damaging supplier-buyer relationships and for being antithetical to what is currently regarded as good supply chain management. Against this background this paper aims to examine the reverse auction phenomenon in the UK packaging sector. Data were collected from the direct experiences of one large food-packaging supplier, using case studies of reverse e-auctions, and from exploratory interviews with other suppliers in the sector. While buyers are reaping significant short-term price reductions, the benefits to suppliers are less obvious. In fact, little reference was detected to the often-quoted reductions in overall transaction costs for either buyers or suppliers. However, most respondents were not able to specify their transaction costs and associated risks and did not appear to have adequate costing systems to enable such quantification.

Du Xin. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2004. / Includes bibliographical references (leaves 67-68). / Abstracts in English and Chinese. / Abstract --- p.i-ii / Acknowledgement --- p.iii / Table of Contents --- p.iv-v / Chapter Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Background information and history of VRM auctions in Hong Kong --- p.2 / Chapter 1.2 --- VRM auctions in other countries --- p.6 / Chapter 1.3 --- Chinese numerology in brief --- p.8 / Chapter Chapter 2 --- "Data Set, literature review and models" --- p.11 / Chapter 2.1 --- Data Set --- p.11 / Chapter 2.2 --- Literature review --- p.13 / Chapter 2.3 --- Variables --- p.14 / Chapter 2.4 --- Model set-up --- p.18 / Chapter 2.4.1 --- Sub-sample estimation --- p.18 / Chapter 2.4.1.1 --- LENGTH as the segmentation criterion --- p.18 / Chapter 2.4.1.2 --- Price range as the segmentation criterion --- p.20 / Chapter 2.4.2 --- Taking logarithm to smooth the fluctuation --- p.22 / Chapter Chapter 3 --- Estimations of hedonic pricing models using the entire sample --- p.23 / Chapter 3.1 --- Estimation results for sub-samples using LENGTH as the segmentation criterion --- p.23 / Chapter 3.2 --- Estimation results for sub-samples using price range as the segmentation criterion --- p.29 / Chapter 3.2.1 --- Estimation of models for the first sub-sample --- p.30 / Chapter 3.2.2 --- Estimation of models for the second sub-sample --- p.33 / Chapter 3.2.3 --- Estimation of models for the third sub-sample --- p.36 / Chapter Chapter 4 --- Estimations of hedonic pricing models using the 99% sample --- p.42 / Chapter 4.1 --- Estimation results for sub-samples using LENGTH as the segmentation criterion --- p.42 / Chapter 4.2 --- Estimation results for sub-samples using price range as the segmentation criterion --- p.49 / Chapter 4.2.1 --- Estimation of models for the first sub-sample --- p.50 / Chapter 4.2.2 --- Estimation of models for the second sub-sample --- p.52 / Chapter 4.2.3 --- Estimation of models for the third sub-sample --- p.52 / Chapter Chapter 5 --- Estimations of hedonic pricing models for LNP --- p.60 / Chapter Chapter 6 --- Conclusion --- p.65 / References --- p.67 / Appendix A Normality test for LNP --- p.69

There is a growing interest in electronic auctions in the literature. Many researchers work on the single attribute version of the problem. Multi-attribute version of the problem is more realistic. However, this brings a substantial difficulty in solving the problem. In order to overcome the computational difficulties, we develop an Evolutionary Algorithm (EA) for the case of multi-attribute multi-item reverse auctions. We generate the whole Pareto front using the EA. We also develop heuristic procedures to find several good initial solutions and insert those in the initial population of the EA. We test the EA on a number of randomly generated problems and compare the results with the true Pareto optimal front obtained by solving a series of integer programs. We also develop an exact interactive approach that provides aid both to the buyer and the sellers for a multi-attribute single item multi round reverse auction. The buyer decides on the provisional winner at each round. Then the approach provides support in terms of all attributes to each seller to be competitive in the next round of the auction.

This thesis studies issues in auctions and contests. The seller of an object and the organizer of a contest have many instruments to improve the revenue of the auction or the efficiency of the contest. The three essays in this dissertation shed light on these issues. Chapter 2 investigates how a refund policy affects a buyer's strategic behavior by characterizing the equilibria of a second-price auction with a linear refund policy. I find that a generous refund policy induces buyers to bid aggressively. I also examine the optimal mechanism design problem when buyers only have private initial estimates of their valuations and may privately learn of shocks that affect their valuations later. When all buyers are \emph{ex-ante} symmetric, this optimal selling mechanism can be implemented by a first-price or second-price auction with a refund policy. Chapter 3 investigates how information revelation rules affect the existence and the efficiency of equilibria in two-round elimination contests. I establish that there exists no symmetric separating equilibrium under the full revelation rule and find that the non-existence result is very robust. I then characterize a partially efficient separating equilibrium under the partial revelation rule when players' valuations are uniformly distributed. I finally investigate the no revelation rule and find that it is both most efficient and optimal in maximizing the total efforts from the contestants. Within my framework, more information revelation leads to less efficient outcomes. Chapter 4 analyzes the signaling effect of bidding in a two-round elimination contest. Before the final round, bids in the preliminary round are revealed and act as signals of the contestants' private valuations. Compared to the benchmark model, in which private valuations are revealed automatically before the final round and thus no signaling of bids takes place, I find that strong contestants bluff and weak contestants sandbag. In a separating equilibrium, bids in the preliminary round fully reveal the contestants' private valuations. However, this signaling effect makes the equilibrium bidding strategy in the preliminary round steeper for high valuations and flatter for low valuations compared to the benchmark model. / Thesis (Ph.D, Economics) -- Queen's University, 2010-04-20 21:34:12.295

MBA Professional Report / Aproved for public release; distribution is unlimited. / In light of the limited recognition of electronic reverse auctions (e-RA) in the acquisition field, the purpose of this research paper is to further the use of e-RAs throughout the federal government and the Department of Defense (D0D). By exploring a multitude of auction types and designs that have been or are currently being used in the private sector, these practices set a basis for researching the auction types being used in the public sector. This paper further explores the regulations guiding the use of e-RAs and investigates the federal government's application of reverse auctions through studies, reports, and interviews with users of e-RAs. Details as to what attributes are prevalent in these e-RAs, what features are best suited for e-RAs, and what benefits have been derived from the use of e-RAs in the federal government are also included. Finally, the researchers found that e-RAs have increased transparency, cost savings, and efficiencies in the acquisition process. Although reverse auctions are being used effectively, the researchers found that there are still opportunities for improvement including incorporating a fully functional best-value tool into e-RA technology and developing more thorough federal guidance on e-RAs as an alternative pricing method.

In this thesis, we do an algorithmic study of optimization problems in budgeted auctions, and some well known covering problems in the multi-agent setting. We give new results for the design of approximation algorithms, online algorithms and hardness of approximation for these problems. Along the way we give new insights for many other related problems. Budgeted Auction. We study the following allocation problem which arises in budgeted auctions (such as advertisement auctions run by Google, Microsoft, Yahoo! etc.) : Given a set of m indivisible items and n agents; agent i is willing to pay b[subscript ij] for item j and has an overall budget of B[subscript i] (i.e. the maximum total amount he is willing to pay). The goal is to allocate items to the agents so as to maximize the total revenue obtained. We study the computation complexity of the above allocation problem, and give improved results for the approximation and the hardness of approximation. We also study the above allocation problem in an online setting. Online version of the problem has motivation in the sponsored search auctions which are run by search engines. Lastly, we propose a new bidding language for the budgeted auctions: decreasing bid curves with budget constraints. We make a case for why this language is better both for the sellers and for the buyers. Multi-agent Covering Problems. To motivate this class of problems, consider the network design problem of constructing a spanning tree of a graph, assuming there are many agents willing to construct different parts of the tree. The cost of each agent for constructing a particular set of edges could be a complex function. For instance, some agents might provide discounts depending on how many edges they construct. The algorithmic question that one would be interested in is: Can we find a spanning tree of minimum cost in polynomial time in these complex settings? Note that such an algorithm will have to find a spanning tree, and partition its edges among the agents. Above are the type of questions that we are trying to answer for various combinatorial problems. We look at the case when the agents' cost functions are submodular. These functions form a rich class and capture the natural properties of economies of scale or the law of diminishing returns.We study the following fundamental problems in this setting- Vertex Cover, Spanning Tree, Perfect Matching, Reverse Auctions. We look at both the single agent and the multi-agent case, and study the approximability of each of these problems.

Conselho Nacional de Desenvolvimento CientÃfico e TecnolÃgico / In this work, letâs apply auction theory to solve a parsimonious procurement model in a situation where there is a contracting firm by the Government. Itâs a natural extension of the bidimensional auction model proposed by Yeon-Koo Che (1993) to model actions of the Department of Defense (DoD) in United States. The extension will be made based in a secret reservation price model proposed by Laffont et at. (1994) to unidimensional case. At end, we will make a short numerical analysis of the model proposed in this work. / Neste trabalho, vamos aplicar a teoria dos leilÃes para resolver um modelo parcimonioso de uma licitaÃÃo pÃblica em uma situaÃÃo em que hà a contrataÃÃo de uma firma pelo Governo. Trata-se de uma extensÃo natural do modelo de leilÃo bidimensional proposto por Yeon-Koo Che (1993) para modelar leilÃes do Departamento de Defesa dos Estados Unidos. A extensÃo serà feita baseada em um modelo de preÃo reserva secreto proposto por Laffont et al. (1994) para o caso unidimensional. Por fim, faremos uma breve anÃlise numÃrica do modelo desenvolvido neste trabalho.

[pt] Este trabalho se concentra no desenvolvimento de mecanismos de leilões reveladores aleatorizados que buscam maximizar simultaneamente a receita e a eficiência econômica, ou função social, de leilões de demanda unitária. Em um leilão de demanda unitária, um conjunto de k bens é leiloado para um conjunto de n consumidores, com a restrição de que nenhum consumidor pode comprar mais de um bem. É apresentado um arcabouço para o desenvolvimento de mecanismos reveladores aleatorizados de complexidade polinomial derivados do mecanismo de Vickrey-Clarke- Groves, ou VCG. Ao invés de utilizar preços de reserva, estas variantes do VCG utilizam como parâmetro o número de bens que devem ser efetivamente vendidos. Os mecanismos se diferenciam entre si pela maneira como é feito o cálculo do número de bens que devem ser vendidos e permitem um balanço interessante entre receita e eficiência econômica, ao mesmo tempo que melhoram os resultados teóricos alcançados para o problema de Leilões de Demanda Unitária. / [en] This work focuses on the development of randomized truthful mechanisms that seek to maximize both the revenue and the economic efficiency, or social welfare, of unit-demand auctions. In a unit-demand auction a set of k items is auctioned to a set of n consumers and no consumer can purchase more than one item. A framework is presented for devising polynomial-time randomized truthful mechanisms that are based on a new variant of the Vickrey-Clarke-Groves (VCG) mechanism. Instead of using reserve prices, this variant of VCG uses the number of objects that we wish to sell as a parameter. The mechanisms obtained differ er from each other in the way they select the number of items to be sold and allow an interesting trade-off between revenue and economic effciency, while improving upon the stateof- the-art results for the Unit-Demand Auction problem (09).

The interaction of theoretical computer science with game theory and economics has resulted in the emergence of two very interesting research directions. First, it has provided a new model for algorithm design, which is to optimize in the presence of strategic behavior. Second, it has prompted us to consider the computational aspects of various solution concepts from game theory, economics and auction design which have traditionally been considered mainly in a non-constructive manner. In this thesis we present progress along both these directions. We first consider optimization problems that arise in the design of combinatorial auctions. We provide an online algorithm in the important case of budget-bounded utilities. This model is motivated by the recent development of the business of online auctions of search engine advertisements. Our algorithm achieves a factor of $1-1/e$, via a new linear programming based technique to determine optimal tradeoffs between bids and budgets. We also provide lower bounds in terms of hardness of approximation in more general submodular settings, via a PCP-based reduction. Second, we consider truth-revelation in auctions, and provide an equivalence theorem between two notions of strategy-proofness in randomized auctions of digital goods. Last, we consider the problem of computing an approximate Nash equilibrium in multi-player general-sum games, for which we provide the first subexponential time algorithm.

published_or_final_version / Business / Master / Master of Philosophy