000			03282cam a22004218i 4500
001			21875916
003			CSPC
005			20241209112414.0
008			210122s2021 nju b 001 0 eng c
010			_a 2021002141
020			_a9781119782476 _q(hardback)
040			_aMdU/DLC _beng _erda _cMdU _dCSPC
042			_apcc
050	0	0	_aHD30.27 _b.B874 2021
082	0	0	_a658.40355028563 _223 _bB964
245	0	0	_aBusiness forecasting : _bthe emerging role of artificial intelligence and machine learning / _cedited by Michael Gilliland, Len Tashman, and Udo Sglavo.
263			_a2104
264		1	_aHoboken, New Jersey : _bJohn Wiley & Sons, Inc., _c2021.
300			_axvii, 414 pages ; _c26 cm.
336			_atext _btxt _2rdacontent
337			_aunmediated _bn _2rdamedia
338			_avolume _bnc _2rdacarrier
490			_aWiley and SAS business series
504			_aIncludes bibliographical references and index.
505	0		_aArtificial 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.
520			_a"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"-- _cProvided by publisher.
650		0	_aBusiness forecasting.
650		0	_aArtificial intelligence.
650		0	_aMachine learning.
700	1		_aGilliland, Michael, _eeditor.
700	1		_aTashman, Len, _d1942- _eeditor.
700	1		_aSglavo, Udo, _d1968- _eeditor.
776	0	8	_iOnline version: _tBusiness forecasting _dHoboken, New Jersey : Wiley, 2021 _z9781119782599 _w(DLC) 2021002142
906			_a7 _bcbc _corignew _d1 _eecip _f20 _gy-gencatlg
942			_2ddc _cBK _e23 _h658.40355028563 _iB964 _kCIR _m2021 _n0
999			_c28561 _d28561