Advanced Data Analytics, Machine Learning and AI in Business

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.

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.