Standort: ---
Exemplare:
---
| |  Online-Ressource |
|---|
| Verfasst von: | Nair, Devadrita [VerfasserIn]  |
|---|
| | Saenz, Maria Jesus [VerfasserIn] |
|---|
| Titel: | Pair people and AI for better product demand forecasting |
|---|
| Titelzusatz: | a new framework helps leaders orchestrate human and AI agents to accurately forecast product demand |
|---|
| Verf.angabe: | Devadrita Nair, Maria Jesus Saenz |
|---|
| Ausgabe: | [First edition]. |
|---|
| Verlagsort: | [Cambridge, Massachusetts] |
|---|
| Verlag: | MIT Sloan Management Review |
|---|
| Jahr: | 2024 |
|---|
| Umfang: | 1 online resource (7 pages) |
|---|
| Illustrationen: | illustrations |
|---|
| Fussnoten: | Reprint #65315. - Includes bibliographical references |
|---|
| Abstract: | Today’s fad-driven retail environment is volatile, making it challenging for companies to accurately predict product demand. The authors provide a framework that considers both product life cycle and demand volatility that can help organizations fine-tune their product demand forecasting, with human and AI agents working in concert. |
|---|
| URL: | Aggregator: https://learning.oreilly.com/library/view/-/53863MIT65315/?ar |
|---|
| Datenträger: | Online-Ressource |
|---|
| Sprache: | eng |
|---|
| Sach-SW: | Intelligence artificielle ; Applications industrielles |
|---|
| | Commerce de détail |
|---|
| | Marketing |
|---|
| | marketing |
|---|
| K10plus-PPN: | 1885007124 |
|---|
| |
|
|---|
| | |
|---|
| Lokale URL UB: |  Zum Volltext |
|---|
| |
|
|---|
| | Bibliothek der Medizinischen Fakultät Mannheim der Universität Heidelberg |
|---|
| |  Bestellen/Vormerken für Benutzer des Klinikums Mannheim
Eigene Kennung erforderlich |
| Bibliothek/Idn: | UW / m450721484X |
|---|
| Lokale URL Inst.: | Zum Volltext |
|---|
Pair people and AI for better product demand forecasting / Nair, Devadrita [VerfasserIn]; 2024 (Online-Ressource)
69197355
