This comprehensive book explores the evolving landscape of decision-making processes for engineering and IT professionals in increasingly heterogeneous technological environments. It addresses critical gaps in current educational materials by examining how technological advancements, situational awareness challenges, human-machine intelligence integration, and virtual uncertainties impact modern decision-making frameworks. The book provides a complete journey map of decision-making that connects theoretical foundations with practical applications, offering readers a structured approach to navigate complex adaptive systems in our data-driven society.
Optimizing Decision-Making in Engineering: A Journey Mapping Perspective includes an in-depth exploration of cognitive and emotional engagements in decision-making, an analysis of how advanced design functionalities influence cognitive biases and heuristics, and an examination of decision-making under virtual conditions where physical touch is absent. It presents analytical tools such as decision trees, Bayesian networks, and multi-criteria decision-making models (AHP, TOPSIS), while incorporating emerging technologies like artificial intelligence, virtual/augmented reality, IoT, and big data analytics. Real-world scenarios, use cases, and strategic frameworks like the Cynefin framework and Roger’s model provide a practical context for theoretical concepts.
Designed for technology professionals, including CTOs, IT project managers, systems architects, UX directors, and engineering team leads, this resource equips product managers, business analysts, solution architects, and digital transformation consultants with enhanced decision-making capabilities for complex environments. This comprehensive guide delivers particular value for specialized roles such as AI ethics officers, human factors engineers, and digital experience strategists, providing frameworks applicable across autonomous systems, healthcare technology, immersive experiences, retail analytics, and advanced manufacturing operations.
Table of Contents:
1. Fundamental Principles in Decision-Making. 2. A Journey Map of Decision-Making in Engineering Practices. 3. Ethics and Socio-Cultural Values in Decision-Making. 4. Human Factors, Situation Awareness, Critical Thinking, and Value Co-Creation in Decision-Making. 5. Critical Obstacles: Cognitive Bias and Heuristics in Decision-Making. 6. Uncertainties for Human-Computer Interaction (Heterogenous Environment) in . 7. Decision-Making Tools for Professionals in Engineering Practices. 8. Theory and Model Applications: Bayesian and Markov Network. 9. Theory and Model Applications: Multi-Criteria Decision-Making. 10. Applications of Group Decision-Making – Delphi Method. 11. Leadership and Strategic Decision-Making – Cynefin Framework. 12. Innovative Decision-Making for Human and Machine Intelligence.
About the Author :
Zian Shah Kabir is a sessional lecturer and research analyst at University of Technology Sydney (UTS), Australia, and has 17 years of experience as an information systems specialist within the telecommunications industry. He earned a PhD in information systems engineering at the UTS, a master’s at the Korea Advanced Institute of Science and Technology (KAIST), and a bachelor’s at the Chittagong University of Engineering and Technology (CUET), and various postgraduate diplomas in Information Technology. Dr. Kabir previously worked as a Director at the Bangladesh Telecommunication Regulatory Commission, where he governed policy frameworks and formulated national standards for a resilient digital society. He has also contributed to the International Telecommunication Union as an international expert. Throughout his career, Dr. Zian has developed expertise in quality assurance, system design and implementation, UX research and design, qualitative and quantitative research methods, cognitive research, and large-scale information systems project implementation, while participating in numerous working groups for standardization and recommendations.
