Bayesian Ensembles of Exponentially Smoothed Life-Cycle Forecasts
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 interpretable approach to producing these pre- and post-launch distributional forecasts. Our approach is inspired by Bayesian model averaging. Each candidate model in our ensemble is a life-cycle model fitted to the completed life cycle of a comparable product.
Faculty Members Earn Distinction at 2022 INFORMS Annual Meeting
Smith Chair of Management Science Michael Fu, was presented with the George E. Kimball Medal for recognition of distinguished service to the Institute for Operations Research and the Management Sciences (INFORMS), the operations research profession and that of management sciences.
How To Shorten Long Airport Lines
Airport congestion and bottlenecks are a hassle for travelers and the airline industry. But new research from Maryland Smith is helping improve decision making within airport operations by producing accurate traveler forecasts in real-time.
Maryland Smith Announces Eight New Faculty Members
As courses convene for the new academic year, Maryland Smith is welcoming eight new scholars to its faculty. Tejwansh (Tej) Anand is joining the decision, operations and information technologies department as a clinical professor. Anand earned a PhD from Columbia University.
Maryland Smith Announces Five New Faculty Members
There will be a few new professors in the corridors of Van Munching Hall and in Maryland Smith’s online courses this academic year. Five new professors will join the faculty at the University of Maryland’s Robert H. Smith School of Business. Here’s a little bit about them.