Optimizing Decision-Making in Engineering (Hardcover)
Language: English
Published by Taylor & Francis Ltd, London, 2026
- Hardcover
- New

Seller: CitiRetail, Stevenage, United KingdomCitiRetail
AbeBooks seller since June 29, 2022
Condition: New
US$ 181.67
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Hardcover. 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, humanmachine 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 Rogers 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. This book explores the decision-making processes for engineering and IT professionals in increasingly heterogeneous technological environments. It provides a map of decision-making that connects theoretical foundations with practical applications, offering readers a structured approach to navigate complex adaptive systems. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…
Seller Inventory # 9781041163909
- Title
- Optimizing Decision-Making in Engineering (Hardcover)
- Author
- Zian Shah Kabir
- Publisher
- Taylor & Francis Ltd, London
- Publication year
- 2026
- Condition
- new
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 1041163908
- ISBN 13
- 9781041163909
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.
"Synopsis" may belong to another edition of this title.
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.
"About the title" may belong to another edition of this title.
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