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Artificial Intelligence in Supply Chain Management (Volumen 6) (Tienda española)
Between Aspiration and Reality
Calvin Klein (Autor)Previo
Lectura de prueba, PDF (240 KB)
Indice, PDF (86 KB)
| ISBN-13 (Impresion) | 9783736978812 |
| ISBN-13 (E-Book) | 9783736968813 |
| Idioma | Inglés |
| Numero de paginas | 98 |
| Laminacion de la cubierta | mate |
| Edicion | 1. |
| Serie | Künstliche Intelligenz & Digitalisierung |
| Volumen | 6 |
| Lugar de publicacion | Göttingen |
| Fecha de publicacion | 06.10.2023 |
| Clasificacion simple | Libro de divulgacion |
| Area |
Economía
|
| Palabras claves | Artificial Intelligence, Artificial General Intelligence, Artificial Neural Networks, Customer Relationship Management, Deep Learning, Enterprise Resource Planning, Fuzzy Systems, Internet of Things, Institute of Supply Chain Management at the University of St. Gallen, Key Performance Indicator, Multi-Agent Systems, Machine Learning, Natural Language Processing, Return on Invest, Supply Chain Management,Supply Chain Risk Management, Transportation Management Software, Künstliche Intelligenz, Künstliche allgemeine Intelligenz, Künstliche Neuronale Netze, Kundenbeziehungsmanagement, Tiefes Lernen, Unternehmensressourcenplanung, Unscharfe Systeme, Internet der Dinge, Institut für Supply Chain Management an der Universität St. Gallen, Multi-Agenten-Systeme, Maschinelles Lernen, Natürliche Sprachverarbeitung, Kapitalrendite, Management der Lieferkette, Risikomanagement in der Lieferkette, Transportmanagement-Software |
Descripcion
As Artificial Intelligence (AI) continues to revolutionize industries worldwide, its omnipresence becomes increasingly evident in Supply Chain Management (SCM).
This Consortium Study, conducted by the Institute of Supply Chain Management (ISCMHSG) at the University of St.Gallen and its promotional association, examines the integration of AI in SCM and aims to address the gap between expectations and reality.
The study provides a knowledge foundation to assist supply chain managers in developingrealistic expectations of this technology. Considering the rapid advancement of AI technologies and their potential impact on SCM, this study explores the current state of
AI in SCM and analyzes the disparity between expectations and reality. Through a comprehensive market analysis of AI solutions offered in SCM, opportunities for improvement are identified.
The study focuses on aligning expectations and reality by fostering a better understanding of the capabilities of AI in SCM.
Additionally, the study investigates obstacles to successful AI integration, including data quality, integration challenges, and unrealistic expectations of potential benefits.
Through the collaborative efforts of the participating organizations, this Consortium Study offers a collective understanding of the current state of AI in SCM. It serves as a
valuable resource for industry professionals, and academia facilitating the successful integration of AI and driving operational excellence in SCM.
