Problem definition: Airports and airlines have been challenged to improve decision-making by producing accurate forecasts in real time. We develop a two-phased predictive system that produces forecasts of transfer passenger flows at an airport. In the first phase, the system predicts the...

Improving airport collaborative decision making is at the heart of airport operations centers (APOCs), recently established in several major European airports. In this paper, we describe a project commissioned by Eurocontrol, the organization in charge of the safety and seamless flow of European...

An inherent characteristic of Ramp;D projects is technological uncertainty, which may result in project failure, and time and resources spent without any tangible return. In pharmaceutical projects, for instance, stringent scientific procedures have to be followed to ensure patient safety and...

We investigate project scheduling with stochastic activity durations to maximize the expected net present value. Individual activities also carry a risk of failure, which can cause the overall project to fail. To mitigate the risk that an activity's failure jeopardizes the entire project, more...

Research and development (R&D) collaborations, common in high-tech industries, are challenging to manage due to technical and market risks as well as incentive problems. We investigate how control rights, options, payment terms and timing allow the innovator to capture maximum value from its R&D...

Decision makers are often called on to make snap judgments using fast-and- frugal decision rules called cognitive heuristics. Although early research into cognitive heuristics emphasized their limitations, more recent research has focused on their high level of accuracy. In this paper we...

We study the problem of forecasting an entire demand distribution for a new product before and after its launch. Firms need accurate distributional forecasts of demand to make operational decisions about capacity, inventory and marketing expenditures. We introduce a unified, robust, and...

When several individuals are asked to forecast an uncertain quantity, they often face implicit or explicit incentives to be the most accurate. Despite the desire to elicit honest forecasts, such competition induces forecasters to report strategically and non-truthfully. The question we address...

Over the years, families of forecasting models, such as the exponential smoothing family and Autoregressive Integrated Moving Average, have expanded to contain multiple possible forms and forecasting profiles. In this paper, we question the need to consider such large families of models. We...