I/B/E/S removes 6% of one-quarter-ahead earnings forecasts from the calculation of the consensus forecast. This study examines managers' role in these removals. We show optimistic forecasts are removed more often than pessimistic forecasts, after controlling for removal policies that I/B/E/S...

In this paper we suggest a new efficient technique for solving integer knapsack problems. Our algorithms can be seen as application of Fast Fourier Transform to generating functions of integer polytopes. Using this approach, it is possible to count the number of boolean solutions of a single...

We provide a technique for constructing optimal multiattribute screening contracts in a general setting with one-dimensional types based on necessary optimality conditions. Our approach allows for type-dependent participation constraints and arbitrary risk profiles. As an example we discuss...

Consensus estimates, formed by taking an average of analyst forecasts, play an important role in capital markets (e.g., provide investors with a proxy for earnings expectations). We show I/B/E/S, a prominent information intermediary, removes 6% of one-quarter-ahead earnings forecasts before...

We model a market, such as an online software market, in which an intermediary connects sellers and buyers by displaying sellers' products. With two vertically-differentiated products, an intermediary can place either: (1) one product, not necessarily the better one, on the first page, and the...

We investigate the incentives for capacity investments in a simple strategic dynamic model with random demand growth. We construct non-collusive Markovian equilibria where the firms' decisions depend on the current capacity stock only. The firms maintain small reserve margins and high market...

We discuss a few supply chain design concepts and optimization models that have been applied in the energy sector. It is not our intention to provide a comprehensive review of the vast literature. Our goal is to provide the reader with pointers to some interesting and challenging problems,...

Purpose: This research aims to develop a dynamic and self-regulated application that considers demand forecasts, based on linear regression as a basic algorithm for machine learning. Methodology: This research uses aggregate planning and machine learning along with inventory policies through the...

We extend the dynamic Cournot model of Ludkovski and Sircar (2012) by considering stochastic demand. We analyze a duopoly between an exhaustible producer and a "green" competitor. Both producers dynamically make decisions regarding their production rates; in addition the exhaustible producer...