A note of revenue maximization and efficiency in multi-object auctions

Combining the result of Palfrey (1983) about the role of bundling and the revenue equivalence theorem, this note shows that there is a conflict between revenue maximization and efficiency in multi-object auctions even with symmetric bidders

The European UTMS/IMT2000 license auctions

We survey the recent European UMTS license auctions and compare their outcomes with the predictions of a simple model that emphasizes future market structure as a main determinant of valuations for licenses. Since the main goal of most spectrum allocation procedures is economic efficiency, and since consumers (who are affected by the ensuing market structure) do not participate at the auction stage, good designs must alleviate the asymmetry among incumbents and potential entrants by actively encouraging entry

The limits of ex post implementation

The sensitivity of Bayesian implementation to agents' beliefs about others suggests the use of more robust notions of implementation such as ex-post implementation, which requires that each agent' s strategy be optimal for every possible realization of the types of other agents. We show that the only deterministic social choice functions that are ex-post implementable in generic mechanism design frameworks with multi-dimensional signals, interdependent valuations and transferable utilities, are constant functions. In other words, deterministic ex-post implementation requires that the same alternative must be chosen irrespective of agents' signals. The proof shows that ex-post implementability of a non-trivial deterministic social choice function implies that certain rates of information substitution coincide for all agents. This condition amounts to a system of differential equations that are not satis�ed by generic valuation functions

Texture spectrum coupled with entropy and homogeneity image features for myocardium muscle characterization

People in middle/later age often suffer from heart muscle damage due to coronary artery disease associated to myocardial infarction. In young people, the genetic forms of cardiomyopathies (heart muscle disease) are the utmost protuberant cause of myocardial disease. Accurate early detected information regarding the myocardial tissue structure is a key answer for tracking the progress of several myocardial diseases. The present work proposes a new method for myocardium muscle texture classification based on entropy, homogeneity and on the texture unit-based texture spectrum approaches. Entropy and homogeneity are generated in moving windows of size 3x3 and 5x5 to enhance the texture features and to create the premise of differentiation of the myocardium structures. Texture is then statistically analyzed using the texture spectrum approach. Texture classification is achieved based on a fuzzy c–means descriptive classifier. The noise sensitivity of the fuzzy c–means classifier is overcome by using the image features. The proposed method is tested on a dataset of 80 echocardiographic ultrasound images in both short-axis and long-axis in apical two chamber view representations, for normal and infarct pathologies. The results established that the entropy-based features provided superior clustering results compared to homogeneity

Innovation and Crowdsourcing Contests

In an innovation contest, an organizer seeks solutions to an innovation-related problem from a group of independent agents. Agents, who can be heterogeneous in their ability levels, exert efforts to improve their solutions, and their solution qualities are uncertain due to the innovation and evaluation processes. In this chapter, we present a general model framework that captures main features of a contest, and encompasses several existing models in the literature. Using this framework, we analyze two important decisions of the organizer: a set of awards that will be distributed to agents and whether to restrict entry to a contest or to run an open contest. We provide a taxonomy of contest literature, and discuss past and current research on innovation contests as well as a set of exciting future research directions

Optimal Resource Allocation over Networks via Lottery-Based Mechanisms

We show that, in a resource allocation problem, the ex ante aggregate utility of players with cumulative-prospect-theoretic preferences can be increased over deterministic allocations by implementing lotteries. We formulate an optimization problem, called the system problem, to find the optimal lottery allocation. The system problem exhibits a two-layer structure comprised of a permutation profile and optimal allocations given the permutation profile. For any fixed permutation profile, we provide a market-based mechanism to find the optimal allocations and prove the existence of equilibrium prices. We show that the system problem has a duality gap, in general, and that the primal problem is NP-hard. We then consider a relaxation of the system problem and derive some qualitative features of the optimal lottery structure