This book is a practical and theoretical guide that demonstrates how to leverage investment data in numerical models despite uncertainty and ambiguity. The author presents innovative methods that incorporate fuzzy set theory to overcome the imprecision of expert opinions and appraisals. Through real industry case studies and comparative analyses, the book provides a comprehensive understanding of how these novel approaches can be implemented to measure robustness.
This book is a must-read for managers involved in investment decision making, for economists, lecturers, as well as M.Sc. and Ph.D. students studying investment decision-making.
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Cengiz Kahraman graduated from Kuleli Military High School in 1983. He received his B.Sc. degree in 1988, M.Sc. degree in 1990, and Ph.D. degree in 1996 from Industrial Engineering of Istanbul Technical University. Prof. Kahraman is now a full professor at Istanbul Technical University. His research areas are engineering economics, quality control and management, statistical decision-making, multi-criteria decision-making, and fuzzy decision-making. He published about 350 journal papers and about 250 conference papers. He became the guest editor of many international journals and the editor of many international books from Springer and Atlantis Press. He is the member of editorial boards of 20 international journals. He organized various conferences such as FLINS, RACR, FSSCMIE, and INFUS. He was the vice dean of ITU Management Faculty between 2004 and 2007 and the head of ITU Industrial Engineering Department between 2010 and 2013.
Dr. Elif Haktanır received the degrees of M.S. (2018) and Ph.D. (2022) in industrial engineering from the Istanbul Technical University in Turkey. She is currently an assistant professor at Bahcesehir University (Istanbul). She is one of the organization committee members of international conference on intelligent and fuzzy systems. Her main research interests include fuzzy logic, multi-criteria decision-making, and engineering economics. She is the editor of the book Intelligent Systems in Digital Transformation (Springer). She has reviewed several articles in Journal of Intelligent & Fuzzy Systems, Complex & Intelligent Systems, and some other journals.
This book is a practical and theoretical guide that demonstrates how to leverage investment data in numerical models despite uncertainty and ambiguity. The author presents innovative methods that incorporate fuzzy set theory to overcome the imprecision of expert opinions and appraisals. Through real industry case studies and comparative analyses, the book provides a comprehensive understanding of how these novel approaches can be implemented to measure robustness.
This book is a must-read for managers involved in investment decision making, for economists, lecturers, as well as M.Sc. and Ph.D. students studying investment decision-making.
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