03282cam a22004218i 4500 21875916 CSPC 20241209112414.0 210122s2021 nju b 001 0 eng c 2021002141 9781119782476 (hardback) MdU/DLC eng rda MdU CSPC pcc HD30.27 .B874 2021 658.40355028563 23 B964 Business forecasting : the emerging role of artificial intelligence and machine learning / edited by Michael Gilliland, Len Tashman, and Udo Sglavo. 2104 Hoboken, New Jersey : John Wiley & Sons, Inc., 2021. xvii, 414 pages ; 26 cm. text txt rdacontent unmediated n rdamedia volume nc rdacarrier Wiley and SAS business series Includes bibliographical references and index. Artificial intelligence and machine learning in forecasting -- Big data in forecasting -- Forecasting methods: modeling, selection, and monitoring -- Forecasting performance -- Forecasting process: communication, accountability, and S&OP -- Afterwords: essays on topics in business forecasting. "Forecasting is the process of making predictions of the future based on past and present data and most commonly by analysis of trends. A commonplace example might be estimation of some variable of interest at some specified future date. Prediction is a similar, but more general term This book provides ideas from the most important and influential authors in the field of forecasting on an array of topics that are highly relevant. It provides multiple perspectives on relevant issues like monitoring forecast performance, forecasting process, communication and accountability for the forecast, the use of big data in forecasting, and the role of AI/ML in enhancing traditional time series forecasting methods. Note: Content is mostly material previously published in "practitioner" journals (Foresight and Journal of Business Forecasting), with a few articles from the academic International Journal of Forecasting. Some articles report on academic research, or include case studies, but most are thoughtful discussion of important business forecasting topics, such as the role of the sales force in forecasting, or the value of judgmental overrides to a statistical forecast, or how to determine what forecast error is "avoidable." Articles were chosen for their importance, influence, informativeness, and for being provocative -- leading the reader to new considerations and ideas"-- Provided by publisher. Business forecasting. Artificial intelligence. Machine learning. Gilliland, Michael, editor. Tashman, Len, 1942- editor. Sglavo, Udo, 1968- editor. Online version: Business forecasting Hoboken, New Jersey : Wiley, 2021 9781119782599 (DLC) 2021002142 7 cbc orignew 1 ecip 20 y-gencatlg ddc BK 23 658.40355028563 B964 CIR 2021 0 0 0 ddc 0 0 CSPC CSPC CIR 2024-12-09 0 CIR 658.40355028563 B964 2021 028621 2024-12-09 11:23:17 1-1 2024-12-09 BK 28561 28561