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.
Prasenjit Chatterjee, PhD is a post-doctoral fellow in the Department of Applied Data Science, Noroff University College, and a professor of mechanical engineering and Dean of Research and Consultancy at the MCKV Institute of Engineering, India. He has published over 135 research papers in various international journals and conferences, authored and edited more than 43 books on intelligent decision-making, fuzzy computing, supply chain management, optimization techniques, risk management, and sustainability modelling.
Abhijit Saha, PhD is an assistant professor in the Department of Computing Technologies at SRM Institute of Science and Technology, Tamil Nadu, India with over ten years of teaching and research experience. He has published over 50 research articles in international journals and serves on the editorial boards of three international journals. His research interests encompass fuzzy set theory, soft set theory, aggregation operators, optimization, and decision-making.
Seifedine Kadry, PhD is a professor in the Department of Computer Science and Mathematics at the Lebanese American University and the Department of Applied Data Science at Noroff University College. He has published over 100 peer-reviewed papers and authored several books. His research interests include data science, system prognostics, stochastic systems, smart learning, social network analysis, and e-systems.
Gülay Demir, PhD is affiliated with Sivas Cumhuriyet University Vocational School of Health Services. She has over 75 publications, primarily in graduate-level textbooks. Her research interests include fuzzy logic, multi-criteria analysis, mathematical statistics, statistical analysis, data analysis, non-parametric statistics, statistical calculation, and parametric statistics.
