This book is a curated collection of selected papers from the International Conference on Business Analytics in Practice (ICBAP 2025), which was held on August 24-27, 2025, at the University of Piraeus, Greece. It brings together cutting-edge research and practical insights on data analytics, machine learning, and artificial intelligence, highlighting their transformative impact on business processes and decision-making. Covering a range of topics from predictive modeling to AI-driven strategies, the book offers valuable perspectives for academics, practitioners, and students keen to explore the latest advancements and applications of data-driven technologies in business.

Features various aspects of business analytics for both academics and practitioners Offers state-of-the-art research and valuable insights into data analytics, machine learning, and AI Explores a broad spectrum of subjects, from predictive modeling to AI-driven strategies

Autorentext

Ali Emrouznejad **is Professor and Chair in Business Analytics at Surrey Business School, UK. He also serves as Director of the Centre for Business Analytics in Practice, where he leads research in performance measurement and management, efficiency and productivity analysis, as well as artificial intelligence and big data analytics. He is the editor of the Springer book series Business Analytics in Practice. He has published 25 books and more than 250 articles in leading international journals. He has been recognised by Stanford University as one of the world’s top 2% most influential scientists.

Sotiris Bersimis is a Professor of Industrial Statistics and Business Analytics at the Department of Business Administration of the University of Piraeus, Greece and an elected member of International Statistical Institute. From 2014 to 2023 he was an elected member of the board of directors of the National (Greek) Statistical Institute. His research interests are mostly related to the development and implementation of stochastic models for process monitoring, the theory of runs and patterns, and finally the development of statistical machine learning methodologies. He has published more than 85 papers in international scientific journals and/or international peer-reviewed volumes and/or conference proceedings while his work has been presented at more than 150 Greek and international conferences. He has more than 2600 citations according to Google Scholar (as of February 2026).

Dimitrios A. Georgakellos is a Professor in the Department of Business Administration at the University of Piraeus, Greece. He received his graduate degree in Mechanical Engineering and his doctoral degree in Business Administration. His academic interests focus on technology and innovation management, environmental management, business plan preparation and entrepreneurship. He has more than 150 scientific articles published in scientific journals and conference proceedings.

Inhalt

Chapter 1: Introduction and Summary.- Chapter 2: The Dynamics of Knowledge Growth in Business.- Chapter 3: Intelligence and Analytics: A Bibliometric Investigation.- Chapter 4: AI for Business Analytics in Logistics and Supply Chain Management: current streams and future trends of research.- Chapter 5: DEA Meets AI in the Context of M&A: A Three-Decade Evolution and Research Outlook.- Chapter 6: AI for medical waste management: a bibliometric analysis.- Chapter 7: Pharmaceutical Product Optimization Using Artificial Intelligence and Machine Learning: A Comprehensive Bibliometric Analysis.- Chapter 8: Evolution of Portfolio Selection Literature: A Bibliometric Study with Emphasis on AI, ML, and DEA Models.- Chapter 9: Systematic analysis of Data Envelopment Analysis (DEA) in Latin America 2000-2024.- Chapter 10: Real-Time Monitoring of Data Streams by Exploiting Machine Learning and Process Monitoring Techniques.- Chapter 11: How Does Generative AI Rewire Organizations? A Deep Dive into Its Role as a Strategic Actor.-
Chapter 12: AI-Augmented Business Analytics in Innovative Startups.