Bibliometric Analyses in Data-Driven Decision-Making

1. Auflage 2025
ISBN: 978-1-394-30252-9
Verlag: Wiley

Buch, Englisch, 720 Seiten

Bibliometric Analyses in Data-Driven Decision-Making is a comprehensive guide that will provide insights into the growth, impact, and trends within bibliometric tools and methodologies. The handbook will adopt a pragmatic approach, balancing theoretical concepts with practical applications of data-driven decision-making models through the perspectives of bibliometric analyses. It's a cohesive guide to navigate the complexities of bibliometric analysis. This book will accommodate a specific audience interested in utilizing bibliometric analysis to understand and navigate the dynamic landscape of the increasingly vital field of data-driven decision-making and its applications in a range of areas.

The book is organized into six different sections. Each chapter will include real-world examples, case studies, and step-by-step guides for applying bibliometric analysis. Section one begins with an overview of bibliometric analysis and methodologies, laying the foundation for the detailed discussion that follows. Subsequent sections explore bibliometric analysis in logistics and supply chain management, healthcare, and medicine, and its integration with multi-criteria decision-making. The book also addresses advances in artificial intelligence (AI) and machine learning and concludes with a focus on technology, sustainability, and innovation. Each section provides a thorough analysis of the literature and emerging trends within these fields.

Autoren/Hrsg.

Chatterjee, Prasenjit

Saha, Abhijit

Kadry, Seifedine

Demir, Gulay

Fachgebiete

• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Datenanalyse, Datenverarbeitung
• Interdisziplinäres Bibliothekswesen, Informationswissenschaften Bibliothekswesen, Informationswissenschaften, Archivwesen
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Mathematik | Informatik Mathematik Stochastik Mathematische Statistik

Über Autor(innen)

Prasenjit Chatterjee, Ph.D., is a postdoctoral fellow at the Department of Applied Data Science, Noroff University College, Kristiansand, Norway, and also a professor of Mechanical Engineering and Dean (Research and Consultancy) at MCKR Institute of Engineering, West Bengal, India. He has authored and edited over 43 books on intelligent decision-making, fuzzy computing, supply chain management, etc. Dr. Chatterjee is one of the developers of two multiple-criteria decision-making methods called Measurement of Alternatives and Ranking according to Compromise Solutions (MARCOS) and Ranking Alternatives through Functional Mapping of Criterion Sub-Intervals into a Single Interval (RAFSI).

Abhijit Saha, Ph.D., is an assistant professor (research) in the Department of Computer Technologies at SRM Institute of Science and Technology, Tamil Nadu, India. His research interests encompass fuzzy set theory, soft set theory, aggregation operators, optimization, and decision-making. He has published nearly 50 research articles in esteemed international journals.

Seifedine Kadry, Ph.D., is a professor at the Department of Computer Science and Mathematics, Lebanese American University, Beirut, Lebanon, and the Department of Applied Data Science, Noroff University, College, Kristiansand, Norway. His research focuses on data science, education technology, system prognostics, smart learning, etc. He has published over 100 peer-reviewed papers and authored several books. He has also served as an editor-in-chief of the research journals of mathematics and statistics and the ARPN Journal of Systems and Software.

Gulay Demir, Ph.D., works at Sivas Cumhuriyet University Vocational School of Health Services, Sivas, Turkey. Her research interests focus on fuzzy logic, multi-criteria analysis, mathematical statistics, statistical analysis, etc. She has more than 75 works, especially her works that are taught as graduate textbooks in different universities.