Computing with strategic agents

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005.Includes bibliographical references (p. 179-189).This dissertation studies mechanism design for various combinatorial problems in the presence of strategic agents. A mechanism is an algorithm for allocating a resource among a group of participants, each of which has a privately-known value for any particular allocation. A mechanism is truthful if it is in each participant's best interest to reveal his private information truthfully regardless of the strategies of the other participants. First, we explore a competitive auction framework for truthful mechanism design in the setting of multi-unit auctions, or auctions which sell multiple identical copies of a good. In this framework, the goal is to design a truthful auction whose revenue approximates that of an omniscient auction for any set of bids. We focus on two natural settings - the limited demand setting where bidders desire at most a fixed number of copies and the limited budget setting where bidders can spend at most a fixed amount of money. In the limit demand setting, all prior auctions employed the use of randomization in the computation of the allocation and prices.(cont.) Randomization in truthful mechanism design is undesirable because, in arguing the truthfulness of the mechanism, we employ an underlying assumption that the bidders trust the random coin flips of the auctioneer. Despite conjectures to the contrary, we are able to design a technique to derandomize any multi-unit auction in the limited demand case without losing much of the revenue guarantees. We then consider the limited budget case and provide the first competitive auction for this setting, although our auction is randomized. Next, we consider abandoning truthfulness in order to improve the revenue properties of procurement auctions, or auctions that are used to hire a team of agents to complete a task. We study first-price procurement auctions and their variants and argue that in certain settings the payment is never significantly more than, and sometimes much less than, truthful mechanisms. Then we consider the setting of cost-sharing auctions. In a cost-sharing auction, agents bid to receive some service, such as connectivity to the Internet. A subset of agents is then selected for service and charged prices to approximately recover the cost of servicing them.(cont.) We ask what can be achieved by cost -sharing auctions satisfying a strengthening of truthfulness called group-strategyproofness. Group-strategyproofness requires that even coalitions of agents do not have an incentive to report bids other than their true values in the absence of side-payments. For a particular class of such mechanisms, we develop a novel technique based on the probabilistic method for proving bounds on their revenue and use this technique to derive tight or nearly-tight bounds for several combinatorial optimization games. Our results are quite pessimistic, suggesting that for many problems group-strategyproofness is incompatible with revenue goals. Finally, we study centralized two-sided markets, or markets that form a matching between participants based on preference lists. We consider mechanisms that output matching which are stable with respect to the submitted preferences. A matching is stable if no two participants can jointly benefit by breaking away from the assigned matching to form a pair.(cont.) For such mechanisms, we are able to prove that in a certain probabilistic setting each participant's best strategy is truthfulness with high probability (assuming other participants are truthful as well) even though in such markets in general there are provably no truthful mechanisms.by Nicole Immorlica.Ph.D

Four Essays in Economic Theory

This thesis comprises four essays that belong to different strands of the theoretical economic literature. Chapter 1 and Chapter 2 study two-sided one-to-one matching markets with quasi-linear utility and multi-dimensional heterogeneity. Chapter 1 investigates the efficiency properties of two-sided investments and in particular the sources and limitations of potential investment coordination failures in large two-sided economies with competitive post-investment market. Chapter 2 scrutinizes a novel two-sided matching model with a finite number of agents and two-sided private information about exogenously given attributes. Chapter 3 is a note on the optimal size of fixed-prize research tournaments that seeks to fill two important gaps in an influential paper by Fullerton and McAfee (1999), and Chapter 4 studies the impact of incomplete information on the problem of maximizing revenue in a dynamic version of the knapsack problem, which is a classical combinatorial resource allocation problem with numerous economic applications

The Roles of Corporate IT Infastructure and their Impact on IS Effectiveness

In the strategic alignment model of Henderson and Venkatraman (1993) [1] IT infrastructure has an important but only implicitly defined role. According to evolving literature, IT infrastructure serves many different purposes in large companies. We outline the main missions (roles) of the corporate-wide IT infrastructure and its contribution to IS effectiveness and study the relationship of IT infrastructure with alignment processes and strategic integration. Our empirical tests with data from almost one hundred large companies resulted in three IT infrastructure roles, which reflect the IS communality, strategic, and flexibility dimensions of the corporate-wide IT infrastructure. The roles were not symmetrically related to the IS effectiveness and alignment perspectives. IT infrastructure roles had a significant interplay with strategic integration in improving IS effectiveness. However, the interplay of IT infrastructure roles with alignment perspectives had only marginal effects. Implications of the results for research and practice are discussed

Integrating Long-Term and Short-Term Contracting in Beef Supply Chains

Published version made available with the permission of INFORMS</p

Solving Multi-objective Integer Programs using Convex Preference Cones

Esta encuesta tiene dos objetivos: en primer lugar, identificar a los individuos que fueron víctimas de algún tipo de delito y la manera en que ocurrió el mismo. En segundo lugar, medir la eficacia de las distintas autoridades competentes una vez que los individuos denunciaron el delito que sufrieron. Adicionalmente la ENVEI busca indagar las percepciones que los ciudadanos tienen sobre las instituciones de justicia y el estado de derecho en Méxic

Essays on Dynamic Mechanism Design

We consider the allocation of one or several units of a good in a dynamic environment. The time horizon is finite and in each period, a random number of potential buyers arrives. In Chapter 1, we study revenue maximization in an environment where buyers are privately informed about their valuations and their deadlines. Depending on the type distribution, the incentive compatibility constraint for the deadline may or may not be binding in the optimal mechanism. We identify a static and a dynamic pricing effect that drive incentive compatibility and violations thereof. Both effects are related to distinct properties of the type distribution and sufficient conditions are given under which each effect leads to a binding or slack incentive constraint for the deadline. An optimal mechanism for the binding case is derived for the special case of one object, two periods and two buyers. It can be implemented by a fixed price in period one and an asymmetric auction in period two. In order to prevent buyer one from buying in the first period when his deadline is two, the seller sets a reserve price that is lower than in the classic (Myerson, 1981) optimal auction and gives him a (non-linear) bonus. The bonus leads to robust bunching at the top of the type-space. Chapter 2 contains a characterization of asymmetric reduced form auctions. In chapter 3, we consider a more general dynamic environment in which buyers' valuations may depend on the time of allocation in an arbitrary way. We show that the static Vickrey auction can be generalized to the dynamic framework. This yields a simple payment rule for the implementation of the efficient allocation rule of a single object. To define the dynamic Vickrey auction, we show that the multi-dimensional type-space can be reduced to essentially one dimension. This allows to define the winner's payment as the lowest valuation in the reduced type-space, that suffices to win. Finally we define an ascending clock-auction with an equilibrium-outcome that coincides with the outcome of the dynamic Vickrey auction