Entry with two correlated signals : the case of industrial espionage and its positive competitive effects

Recent advances in information and communication technologies have increased the incentives for firms to acquire information about rivals. These advances may have major implications for market entry because they make it easier for potential entrants to gather valuable information about, for example, an incumbent's cost structure. However, little theoretical research has actually analyzed this question. This paper advances the literature by extending a one-sided asymmetric information version of Milgrom and Roberts' (1982) limit pricing model. Here, the entrant is allowed access to an intelligence system (IS) of a certain precision that generates a noisy signal on the incumbent's cost structure. The entrant thus decides whether to enter the market based on two signals: the price charged by the incumbent and the signal sent by the IS. Crucially, for intermediate values of IS precision, the set of pooling equilibria with ex-ante profitable market entry is non-empty. Moreover, the probability of ex-ante non-profitable entry is strictly positive. In classical limit pricing models, an entrant never enters in a pooling equilibrium, so this result suggests that the use of an IS may potentially increase competition

Information in Mechanism Design

We survey the recent literature on the role of information for mechanism design. We specifically consider the role of endogeneity of and robustness to private information in mechanism design. We view information acquisition of and robustness to private information as two distinct but related aspects of information management important in many design settings. We review the existing literature and point out directions for additional future work.Mechanism Design, Information Acquisition, Ex Post Equilibrium, Robust Mechanism Design, Interdependent Values, Information Management

Theoretical Models of Industrial Espionage

Dada la importancia del espionaje industrial en la realidad económica, el objetivo de la presente tesis es analizar teóricamente el comportamiento de las empresas a la hora de obtener información de sus competidores, para poder comprenderlo mejor y ver cuáles pueden ser sus consecuencias, ya que, aunque el espionaje industrial es una práctica muy extendida, pocos trabajos teóricos han tratado de analizarlo. Más concretamente, nuestro objetivo es analizar teóricamente el impacto del espionaje industrial sobre el comportamiento estratégico de las empresas en un contexto de disuasión de la entrada usando las herramientas propias de la Teoría de Juegos. En los modelos de la presente tesis se considera la existencia de un monopolio (M) en un mercado y un entrante potencial (E) al mismo. Para tratar de impedir que E entre al mercado, M considera invertir en la expansión de su capacidad (Capítulos 2 y 3) o invertir en I+D para reducir su coste de producción (Capítulo 4). En el primer caso, E no observa las decisiones de inversión de M, y en el segundo E no sabe si la inversión para reducir costes fue exitosa. Por ello E utiliza un Sistema de Inteligencia (SI), que puede tener un coste o ser de libre acceso, para tratar de detectar la acción de M en el primer caso, y el resultado de la inversión en el segundo, y tiene en cuenta esta información que le proporciona el SI para decidir si entra o no al mercado.El SI puede enviar dos señales con ruido sobre la decisión de M en el primer caso, y sobre el resultado de la inversión en el segundo. En esta tesis se supone que la precisión del SI puede ser tanto exógena (Capítulos 2 y 4) como endógena (Capítulo 3). El primer caso sería aquel en que la empresa que espía dispone de un SI antes de encontrar a un nuevo rival (por ejemplo, una empresa que puede implantar un Caballo de Troya en el sistema informático de sus rivales). El segundo sería el de una empresa que contrata a directivos y trabajadores de otra para que le proporcionen información de la misma. Por último comentar que este tipo de SI no es un jugador que actúa estratégicamente

Essays on Self-Referential Games

This dissertation studies self-referential games in which agents can learn (perfectly and imperfectly) about an opponents\u27 intentions from a private signal. In the first chapter, my main focus is on the interaction of two sources of information about opponents\u27 play: direct observation of an opponent\u27s code of conduct and indirect observation of the same opponent\u27s play in a repeated setting. Using both sources of information I prove a folk theorem for repeated self-referential games with private monitoring. In the second chapter, I investigate the impact of self-referentiality on bad reputation games in which the long-run player must choose specific actions to make short-run players participate in the game. Since these particular actions could be interpreted as evidence of perverse behavior, the long-run agent attempts to separate himself from other types and this results in efficiency losses. When players identify intentions perfectly, I show that inefficiencies and reputational concerns due to a bad reputation disappear. In the case of imperfect observation, I find that self-referentiality and stochastic renewal of the long-run player together overcome inefficiencies because of bad reputation. In the third chapter, I address the timing of signals in self-referential games. These models typically suppose that intentions are divined in a pre-play phase; however, in many applications this may not be the case. For games with perfect information when players observe signals in advance, I show that any subgame perfect equilibria of an infinite-horizon game coincides with a Nash equilibrium of the self-referential finite-horizon approximation of the original game. Then, I focus on two specific classes of games. First, in finitely repeated games with discounting I show that a version of the folk theorem holds regardless of the time at which signals are observed. Second, I examine exit games in which players can terminate the game at any stage. In contrast to repeated games, I find that the equilibrium outcome of the self-referential exit game is unique if signals arrive after the first stage, whereas a folk theorem results only if they occur before the first stage. Finally, I explore asynchronous monitoring of intentions where players may not receive signals simultaneously. With asynchronicity, a folk theorem continues to apply for repeated games; however, for exit games there is a unique equilibrium outcome independent of signal timing, or indeed, independent of having a signal

R&D Outsourcing Contract with Information Leakage

This paper studies an R&D outsourcing contract between a firm and a contractor, considereing the possibility that in the interim stage, the contractor might sell the innovation to the rival firm. Our result points out that due to the competition in the interim stage, the reward needed to prevent leakage will be pushed up to the extent that a profitable leakage free contract does not exist. This result will also apply to cases considering revenue-sharing schemes and a disclosure punishment for commercial theft. Then, we demonstrate that in a competitive mechanism where the R&D firm hires two contractors together with a relative performance scheme, the disclosure punishment might help and there exists a perfect Bayesian Nash equilibrium where the probability of information leakage is lower and the equilibrium reward is also cheaper than hiring one contractor.R&D outsourcing, Contract, Information leakage, Collusion, Multiple agents