We address a number of operational challenges encountered in two emerging types of practices in the procurement of truckload transportation services: collaboration and auctions. The main objective in these two types of procurement strategies is identifying and exploiting synergies between the lanes of a carrier's network. In shipper collaboration, we take the perspective of a shipper who collaborates with other shippers to seek synergy between his lanes and other participants' lanes. On the other hand, in procurement auctions, although we take the carriers' perspective in our work, a shipper tries to discover the carrier (or carriers) whose network has the most synergy with his lanes. The first part of the thesis concerns the solution of optimization problems arising in collaborative transportation procurement networks where a group of shippers comes together and jointly negotiates with carriers for the procurement of transportation services. Through collaboration, shippers may be able to identify and submit sequences of continuous loaded movements to carriers, reducing the carriers' need for repositioning, and thus lowering the carriers' costs. A portion of the carriers' cost savings may be returned to the shippers in the form of lower prices. We discuss optimization technology that helps identify repeatable, dedicated truckload continuous move tours with little truck repositioning. Timing considerations are critical to practical viability and are a key focus of our efforts. We demonstrate the effectiveness of our algorithms on randomly generated instances as well as on instances derived from real-world data. The second part concerns the pricing of transportation services offered by the trucking companies (carriers). We look at the bid determination problem faced by carriers in transportation procurement auctions where a shipper requests quotes from multiple carriers and purchases the services of the lowest bidder. The specific problem being studied is the bid valuation problem in the case where the carrier must place bids on multiple lanes simultaneously. We model the problem as a stochastic optimization problem and propose a coordinate search algorithm for solving this problem. Then, we conduct a simulation study to demonstrate the positive impact of the approach on carrier profits.

A recent pursuit of the auction design literature has been the development of an auction mechanism which performs well in a multi-good setting, when the goods are not substitutes. This work began in earnest with the Federal Communications Commission spectrum license auctions in the early nineties and continues to this day. In a setting in which goods are not substitutes, the value of one good depends nonnegatively on the quantities of other goods that are won. This type of interdependent value structure has proven difficult to account for in auction design. However, the need for mechanisms that account for such a value structure hinges on the magnitude of the interdependence, whose computation is an empirical exercise. I identify a setting in which to perform this computation. I develop an empirical methodology that allows me to recover bidders' value functions in a multi-good auction setting. This methodology allows me to assess the magnitude of any interdependence in the goods? value structure. Since the auction setting that I analyze is a variation of the standard uniform price auction, which has been adapted for a multi-good setting, I am able to measure the benefit of having a direct revelation mechanism. This counterfactual study is performed by maximizing the value of the auction using the recovered bidder value functions. I find evidence that there is an interdependent value structure in the setting. The counterfactual auction finds that the standard uniform price auction, adapted to a multi-good setting, performs poorly in the presence of such a value structure. The setting for this analysis is an auction for financial transmission rights held in Texas in 2002. The auction involved twenty two firms and collected almost $70 million in revenue. This research is the first to empirically assess efficiency in this type of auction setting.

Electronic commerce is becoming more important day by day. Many transactions and business are done electronically and many people do not want paper work anymore. When a firm wants to buy raw materials or components, it announces its need to related websites or in the newspapers. Similar demands and announcements can be seen almost everywhere nowadays. In this way, it needs to perform fast and reliable auctions as much as possible. On the other hand, buyers not only consider cost but also consider a lot of different aspects like quality, warranty period, lead time etc when they want to purchase something. This situation leads to more complex problems in the purchasing process. As a consequence, some researchers started to consider auction mechanisms that support bids characterized by several attributes in addition to the price (quality of the product, quantity, terms of delivery, quality of the supplier etc.). These are referred to as multi-attribute combinatorial auctions. In this thesis, Combinatorial Auctions are analyzed. Single-attribute multi-unit, multi-attribute multi-unit combinatorial auction models are studied and an interactive method is applied for solving the multi-attribute multi-unit combinatorial auction problem.

Η παρούσα διπλωματική εργασία παρουσιάζει την ανάπτυξη ενός διαδικτυακού ιστότοπου (website) προς τη διενέργεια ηλεκτρονικών δημοπρασιών. Ως ηλεκτρονική δημοπρασία ορίζεται η δημοπρασία που διενεργείται με χρήση σύγχρονων διαδικτυακών και υπολογιστικών υπηρεσιών. Σε αυτή την εργασία υλοποιούμε έναν ιστότοπο που αναφέρεται σε χρήστες του ελλαδικού χώρου που θέλουν να πουλήσουν ή να αγοράσουν εξαρτήματα υλικού Η/Υ. Κύριο αντικείμενο της ανάπτυξης αποτέλεσε η δημιουργία ορθού κώδικα που θα διαχειρίζεται τη διαδικασία των προσφορών (bid) που πραγματοποιούν οι χρήστες και του αντίστοιχου κώδικα για τη δημιουργία δημοπρασιών εκ μέρους των χρηστών. Οι χρήστες μπορεί να είναι απλοί, οι οποίοι έχουν μόνο δικαίωμα περιήγησης στον ιστότοπο, χωρίς τη δυνατότητα δημιουργίας δημοπρασιών και εκτέλεσης προσφορών ή εγγεγραμμένοι, οι οποίοι μπορούν να εκμεταλλευθούν τις πλήρεις δυνατότητες του ιστότοπου. Η υλοποίηση του εγχειρήματος επιτεύχθηκε με τη χρήση ευρέως διαδεδομένων τεχνολογιών & γλωσσών προγραμματισμού διαδικτύου ανοιχτής προέλευσης (open source). Συγκεκριμένα έγινε χρήση της τεχνολογίας PHP έκδοσης 5 για τον προγραμματισμό της πλευράς του διακομιστή διαδικτύου (server side scripting) και των τεχνολογιών HTML έκδοση 5, Javascript (βιβλιοθήκη JQUERY έκδοση 1.11.1), AJAX για τον προγραμματισμό της πλευράς του χρήστη (client side scripting). Ταυτόχρονα έγινε χρήση του διαδικτυακού πλαισίου (web framework) bootstrap, το οποίο ενσωματώνει μία ειδική δομή σχεδιασμού & εικαστικού περιεχομένου περιλαμβάνοντας κλάσεις, εφαρμογές Javascript και τεχνικές της τεχνολογίας CSS για την εμφάνιση και τις λειτουργίες της διεπαφής του χρήστη. / This thesis presents the development of a website for conducting electronic auctions. Electronic auction is defined as an auction conducted using modern internet and computing services. In this work, we implement a website that refers to users from Greece who want to sell or buy Computer Hardware. The main object of the development was the core code that manages the process of bidding made by users and the corresponding code for creating auction by users. There may be normal users, having only browsing rights, without the capability of creating and executing auction deals or registered ones, who may experience the full capabilities of this website. The implementation of the project was achieved using widely available open source internet technologies and programming languages. We used PHP version 5 for the webserver’s side scripting and HTML version 5, Javascript (JQUERY library version 1.11.1), AJAX for the client’s side scripting . At the same time, we made use of bootstrap web framework, which incorporates a special structure design & visual content including classes, applications Javascript and CSS techniques technology for the appearance and functionality of user interface.

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.

Past empirical analysis show that in contrast to the theory predictions; prices tend to decline in some sequential auctions, a puzzle known as the declining price anomaly. Several theoretical explanations were proposed demonstrating the possibility of a declining price pattern under certain assumptions. In this paper, we demonstrate that when bidders have private values and multi-unit demand, expected selling price can be increasing, constant, decreasing or even non-monotonic. In our model, price pattern depends on the distributions from which bidder valuations are drawn (including the size of the bidders demand reduction), and the number of bidders.

Signals convey information to marketplace participants regarding the unobservable quality of a product. Whenever product quality if unobservable prior to purchase, there is the risk of adverse selection. Problems of hidden information also occur in the consumer marketplace when the consumer is unable to verify the quality of a good prior to purchase. The sending, receiving, and interpretation or signals are potential ways to overcome the problem of adverse selection. In general, there is a lack of empirical evidence for signaling hypothesis, particularly that which links signaling to business performance outcomes. This research proposes that reputation serves as a marketplace signal to convey unobservable information about products offered for sale. Signaling hypotheses are tested in a network context, examining the influence of signals throughout a network of buyers and sellers in a marketplace. There are many situations where a signal does not affect just one sender and one receiver; multiple constituencies may be aware of and react to a given signal. This study incorporates the actions of seller side principals, seller side agents, and buyer side agents when examining marketplace signals and provides a new perspective and better vantage point from which to test signaling theory. The research setting for this study is the world’s largest individual marketplace for Thoroughbred yearlings. Several sources of secondary data are employed. These openly available published sources of information were selected as representative of the information that would typically be available to marketplace principals and agents to use in planning interactions in this unique live auction marketplace. The findings from his study indicate that the reputation of seller side principals and agents affect the eventual business performance outcomes as measured by final price brought at auction for goods. Specifically, seller side principals and agents who have developed a reputation for producing or selling high-priced or high-performing goods will be rewarded in the marketplace with relatively higher prices for their goods. Buyer side agents who are more central in the marketplace will pay relatively higher prices for goods. Evidence suggests that more central seller side agents will receive relatively higher prices for their goods.

The contemporary fine art auction house is a space where aesthetics and commerce merge into a spectacular experience. Sotheby's, London is one example of an auction house turned entertainment space, which masks its blatant capitalist tendencies through the replication of validated cultural institutions. The auction house mimics museum and theatre space in order to create a legitimate social and cultural experience for its clients. Every aspect of the auction event is choreographed to generate demand for its art and an authentic experience for its patrons. Individuals with the approved educational and economical background have access to these constructed locations, and attend the auction performance to purchase social status in conjunction with the art. As a result of this, Sotheby's effectively transforms economic capital into class acceptance through its spectacular space and legitimized cultural events.

The field of algorithmic mechanism design is concerned with the design of computationally efficient algorithms for use when inputs are provided by rational agents, who may misreport their private values in order to strategically manipulate the algorithm for their own benefit. We revisit classic problems in this field by considering settings of incomplete information, where the players' private values are drawn from publicly-known distributions. Such Bayesian models of partial information are common in economics, but have been largely unexplored by the computer science community. In the first part of this thesis we show that, for a very broad class of single-parameter problems, any computationally efficient algorithm can be converted without loss into a mechanism that is truthful in the Bayesian sense of partial information. That is, we exhibit a transformation that generates mechanisms for which it is in each agent's best (expected) interest to refrain from strategic manipulation. The problem of constructing mechanisms for use by rational agents therefore reduces to the design of approximation algorithms without consideration of game-theoretic issues. We furthermore prove that no such general transformation is possible if we require mechanisms that are truthful in the stronger non-Bayesian sense of dominant strategies. In the second part of the thesis we study simple greedy methods for resolving complex auctions. We show that while such greedy algorithms are not truthful, they suffer very little loss in worst-case performance bounds when agents apply strategies at equilibrium, even in settings of partial information. Our analysis applies to various different equilibrium concepts, including Bayes-Nash equilibrium, regret-minimizing strategies, and asynchronous best-response dynamics. Thus, even though greedy auctions are not truthful, they may be appropriate for use as mechanisms under the goal of achieving high social efficiency at equilibrium. Moreover, we prove that no algorithm in a broad class of greedy-like methods can be used to create a deterministic truthful mechanism while retaining a non-trivial approximation to the optimal social welfare. Our overall conclusion is that while full-information models of agent rationality currently dominate the algorithmic mechanism design literature, a relaxation to settings of partial information is well-motivated and provides additional power in solving central problems in the field.