Overview
- Presents recent research on Digital Transformation
- Integrates research from different fields of activity outlining a timely picture
- Presents technologies, tools, and studies
Part of the book series: Intelligent Systems Reference Library (ISRL, volume 253)
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Table of contents (12 chapters)
Keywords
About this book
This book presents a multidisciplinary approach to digital transformation process of organizational transformation, offering support throughout the implementation process to all those interested. The digital transformation (DT) is a priority for many companies in the context of technological evolution. The use of appropriate tools, methodologies, methods, approaches, and techniques for DT, depending on the organizational characteristics, can contribute to a complete approach to organizational processes and to their efficiency. Digital transformation involves the adoption and use of new digital technologies to develop new products and services, modify existing ones and develop new business models to increase efficiency, productivity, and competitiveness. Starting from marketing to culture and education to health, automotive, engineering, mobility and human resources and others, it is addressed to professionals, practitioners, researchers, students, and other interested parties.
Editors and Affiliations
About the editors
Bibliographic Information
Book Title: Digital Transformation
Book Subtitle: Technology, Tools, and Studies
Editors: Lucian-Ionel Cioca, Larisa Ivascu, Florin Gheorghe Filip, Banciu Doina
Series Title: Intelligent Systems Reference Library
DOI: https://doi.org/10.1007/978-3-031-55952-5
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2024
Hardcover ISBN: 978-3-031-55951-8Published: 27 April 2024
Softcover ISBN: 978-3-031-55954-9Due: 28 May 2024
eBook ISBN: 978-3-031-55952-5Published: 26 April 2024
Series ISSN: 1868-4394
Series E-ISSN: 1868-4408
Edition Number: 1
Number of Pages: XI, 262
Number of Illustrations: 4 b/w illustrations, 73 illustrations in colour
Topics: Data Engineering, Computational Intelligence, Big Data