Part I: Principles of Business Forecasting: A First Course in Forecasting
Principles of Business Forecasting 2ed can be purchased as a complete textbook OR separately in three individual sections. The sections are only available as ebooks.
Keith Ord is Professor Emeritus in the Operations and Information Management group at the McDonough School of Business at Georgetown University.
He completed his graduate work at the University of London, and held faculty positions at the Universities of Bristol and Warwick before moving to The Pennsylvania State University in 1980, and then to Georgetown University in 1999.
Keith’s research interests include time series and forecasting, spatial modeling and the statistical modeling of business processes. He is a co-author of the 2008 research monograph, Forecasting with Exponential Smoothing: The State-Space Approach,and also co-authored Kendall’s Advanced Theory of Statistics.
He has served as an editor of the International Journal of Forecasting. Keith is a Fellow of the American Statistical Association, the International Institute of Forecasters, and the Royal Statistical Society.
Robert Fildes is Distinguished Professor in the Management School, Lancaster University, Director of the Centre for Marketing Analytics and Forecasting.
He graduated from Oxford and the University of California, and went on to write one of the early forecasting texts. In 1981, with Spyros Makridakis and Scott Armstrong, he founded the International Institute of Forecasters, which has organized conferences for nearly 40 years and, more recently, workshops on all aspects of forecasting.
Robert was co-founder in 1985 of the International Journal of Forecasting, the premier academic forecasting journal.
His current research interests are concerned with the comparative evaluation of different forecasting methods, particularly applied to retailing and the implementation of improved forecasting procedures and systems: in a nutshell, getting improvements into practice.
Nikolaos Kourentzes is a Professor in the Skövde Artificial Intelligence Lab at the University of Skövde and in the Department of Management Science at Lancaster University Management School.
His background began in Strategic Management, but he quickly changed his interests to Management Science, earning a Ph.D. from Lancaster University in forecasting with neural networks.
Nikos’ primary research focus is modeling uncertainty in a business forecasting context, whether that concerns model specification and selection, or ways to make forecasts more reliable and robust. His research addresses forecasting issues of aggregation and hierarchies, model combination, promotional modeling, and supply chain collaboration.
He has published multiple forecasting-related open-source packages for R, in his attempt to bring current forecasting research to practice. Nikos is on the editorial board of the International Journal of Forecasting.