This book contains the second volume of proceedings of the ECAI 2024 Workshop on Intelligent Management Information Systems (IMIS 2024). IMIS 2024 was part of the 27th European Conference on Artificial Intelligence ECAI 2024, held in Santiago de Compostela from October 19, 2024, to October 24, 2024.The book discusses emerging challenges related to implementing artificial intelligence in management information systems. The main focus is put on knowledge management and machine learning methods in information systems, artificial intelligence for decision support systems, intelligent customer management methods, hybrid artificial intelligence, and multiple criteria decision analysis methods and advanced computational methods for support business processes and decision-making.The book is divided into three major parts covering the main issues related to the topic. The first part presents issues related to the knowledge management in intelligent information systems. The second part is devoted to application of machine learning in management information systems. The third part presents problems related to multiple criteria decision analysis and computational methods.The book has an interdisciplinary character; therefore, it is intended for a broad scope of readers, including researchers, students, managers, and employees of business organizations, software developers, IT, and management specialists.

This book contains the second volume of proceedings of the ECAI 2024 Workshop on Intelligent Management Information Systems (IMIS 2024). IMIS 2024 was part of the 27th European Conference on Artificial Intelligence ECAI 2024, held in Santiago de Compostela from October 19, 2024, to October 24, 2024.The book discusses emerging challenges related to implementing artificial intelligence in management information systems. The main focus is put on knowledge management and machine learning methods in information systems, artificial intelligence for decision support systems, intelligent customer management methods, hybrid artificial intelligence, and multiple criteria decision analysis methods and advanced computational methods for support business processes and decision-making.The book is divided into three major parts covering the main issues related to the topic. The first part presents issues related to the knowledge management in intelligent information systems. The second part is devoted to application of machine learning in management information systems. The third part presents problems related to multiple criteria decision analysis and computational methods.The book has an interdisciplinary character; therefore, it is intended for a broad scope of readers, including researchers, students, managers, and employees of business organizations, software developers, IT, and management specialists.

This book contains the second volume of proceedings of the ECAI 2024 Workshop on Intelligent Management Information Systems (IMIS 2024). IMIS 2024 was part of the 27th European Conference on Artificial Intelligence ECAI 2024, held in Santiago de Compostela from October 19, 2024, to October 24, 2024.The book discusses emerging challenges related to implementing artificial intelligence in management information systems. The main focus is put on knowledge management and machine learning methods in information systems, artificial intelligence for decision support systems, intelligent customer management methods, hybrid artificial intelligence, and multiple criteria decision analysis methods and advanced computational methods for support business processes and decision-making.The book is divided into three major parts covering the main issues related to the topic. The first part presents issues related to the knowledge management in intelligent information systems. The second part is devoted to application of machine learning in management information systems. The third part presents problems related to multiple criteria decision analysis and computational methods.The book has an interdisciplinary character; therefore, it is intended for a broad scope of readers, including researchers, students, managers, and employees of business organizations, software developers, IT, and management specialists.