Intelligent Management

AI, Data-Driven Decision Making, and Business Optimisation

Karolina Beyer|Kesra Nermend|Małgorzata Łatuszyńska|Mateusz Piwowarski|Simon Grima
Emerald
Emerald

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Hardback
9781837425051
30 March 2027
£90.00
Available to order on 28 February 2027
eBook (PDF)
9781837425044
09 March 2027
£90.00
Available to order on 07 February 2027
eBook (ePub)
9781837425068
09 March 2027
£90.00
Available to order on 07 February 2027

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  • Description
  • Contents
  • About

Intelligent Management discusses the core principles of intelligent management, including AI-enabled decision-making, ethics in AI management, the impact of big data, and applications in various business areas such as crisis management, sustainability, and supply chain optimisation.

Key chapters explore human-machine collaboration, ethical considerations in AI adoption, and leadership evolution in the era of intelligent management. Intelligent Management fill a critical gap in the literature by providing a structured approach to integrating intelligent technologies into management practices. By addressing real-world challenges and applications, they serves as a valuable resource for academics, practitioners, and students in management, technology, and business analytics.

Emerald Studies in Neuro-Decision Making for Risk Analysis explores multidisciplinary subjects in depth, offering a thorough grasp of decision-making across many situations by combining ideas from economics, psychology, and neuroscience in the field of Behavioural Economics and Decision Science.

Part I. Governance, Legal Frameworks and Risk in AI-Enabled Management

  • Chapter 1. Legal Rules for the Use of AI in Public Services Management; Kinga Flaga-Gieruszyńska, Neringa Gaubienė, Kristina Pranevičienė, and Piotr Krzystek
  • Chapter 2. Legal Risk and Behavioural Governance in AI-Driven Decision-Making: Toward Intelligent and Ethical Management; Aleksandra Klich, Bartosz Brożyński, Yuliya Khvatsik, and Marcin Białecki
  • Part II. Neuroscience-Based Decision Making: Methods, Tools and Applications
  • Chapter 3. Designing Intelligent Management with Neuroscience through the Factor Analysis of Structural Dimensions; Marta Starostka-Patyk, Joanna Tylkowska-Drożdż, Marcin Zawada, Helena Kościelniak, and Joanna Panek
  • Chapter 4. The Relationship Between Biological Parameters and Emotional Coping in Students, and the Effectiveness of Academic Education: The Diagnostic Potential of Neurofeedback; Bartłomiej Piwowarski, Małgorzata Nermend, Alma Shehu Lokaj, Zdzisław Kroplewski, and Mehmet Salih Batirhan
  • Chapter 5. Eye-Tracking as a Neurocognitive Tool for Design and Optimisation of Driver-Training Materials for Future Drivers; Patryk Wlekły, Małgorzata Nermend, Marcin Gryczka, Mariusz Borawski, and Halit Shabani
  • Part III. Organizational Intelligence: Leadership, Digital Transformation and AI Integration
  • Chapter 6. The Role of Leadership in Optimising Decision-Making Processes Using Artificial Intelligence: Empirical Research on a Sample of Management Staff; Agnieszka Rzepka, Ewa Mazur-Wierzbicka, Magdalena Czerwińska, Jacek Witkowski, and Dariusz Czerwiński
  • Chapter 7. Digital Transformation and Business Process Improvement in Veterinary Clinics: AI-Driven Decision-Making and Risk Analysis; Karolina Beyer, Iwona Chomiak-Orsa, Zbigniew Pietrzykowski, Dominik Rozkrut, and Mehmet Salih Batirhan
  • Chapter 8. AI-Enabled Decision Architectures in Media Consumption: Intelligent Management, Risk, and Business Optimization among Generation Z in Poland; Edyta Rudawska and Luca Giraldi
  • Part IV. Advanced Analytical Methods and AI Technologies for Business Optimization
  • Chapter 9. Rough Set Theory in Making Decisions on Cloud Computing Implementation; Damian Dziembek, Karol Kuczera, Anna Dunay, Csaba Bálint Illés, and Kacper Kuczera
  • Chapter 10. Tackling Literature Overload: Multi-Embedding Consensus for Effective SLR Decision-Making; Paweł Karol Frankowski, Joanna Wiśniewska, and Sebastian Matysik
  • Chapter 11. Large-Scale AIS Database for Advanced AI-Driven Decision-Making Systems in the Maritime Shipping Sector; Ernest Czermański, Aneta Oniszczuk-Jastrząbek, Janusz Przewocki, Jakub Neumann, Tomasz Borzyszkowski, Elżbieta Szaruga, and Michał Pluciński
  • Chapter 12. Artificial Intelligence in Plastic Surgery: Applications, Outcomes and Future Implications; Wojciech Drożdż, Krystian Redżeb, and Jan Petriczko

Karolina Beyer is an Assistant Professor and Deputy Director for Education at the Institute of Management, University of Szczecin, and Vice-President of the Center for Research and Development for the University of Szczecin, Poland.

Kesra Nermend is a Professor at the University of Szczecin along with the Head of the Department of Decision Support Methods and Cognitive Neuroscience, the Director of the Institute of Management, University of Szczecin, the Director of the Center for Transfer and Technology at the University of Szczecin, and the President of the Center for Research and Development for the University of Szczecin, Poland.

Małgorzata Łatuszyńska is Associate Professor at the University of Szczecin, Poland, dr. habil. of economic science in the scope of economics (specialisation economical informatics).

Mateusz Piwowarski is an Assistant Professor and Supervisor of the Cognitive Neuroscience Laboratory at the Institute of Management US, and Vice-President of the Center for Research and Development for the University of Szczecin, Poland.

Simon Grima is the Dean of the Faculty of Economics, Management and Accountancy at the University of Malta, Professor and Head of the Department of Insurance and Risk Management. Simon is also a Professor at the University of Latvia, Faculty of Economics and Social Sciences, a visiting Professor at Haxhi Zeka University, Kosovo.