04158nam a22005775i 4500 978-981-97-6972-8 DE-He213 20251030113251.0 cr nn 008mamaa 241029s2024 si | s |||| 0|eng d 9789819769728 978-981-97-6972-8 10.1007/978-981-97-6972-8 doi T57.6-.97 KJT bicssc KJMD bicssc BUS049000 bisacsh KJT thema KJMD thema Analytical Decision Making and Data Envelopment Analysis [electronic resource] : Advances and Challenges / edited by S.A Edalatpanah, Farhad Hosseinzadeh Lotfi, Kristiaan Kerstens, Peter Wanke. 1st ed. 2024. Singapore : Springer Nature Singapore : Imprint: Springer, 2024. XI, 489 p. 99 illus., 77 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Infosys Science Foundation Series in Mathematical Sciences, 2364-4044 Chapter 1 Merging Data Envelopment Analysis and Atructural Risk Minimization: Some Examples of Use of Multi-Output Machine Learning Techniques on Real-World Data -- Chapter 2 A New Network Data Envelopment Analysis Model for Efficacy Evaluation of Decision-Making Units -- Chapter 3 Possibilistic Network DEA Approach for Performance Evaluation of Two-Stage Decision-Making Units under Uncertainty. This book explores the intersection of data envelopment analysis (DEA) and various analytical decision-making methodologies. Featuring contributions from experts in the field from across the world, each chapter delves into different aspects of DEA and its applications in real-world scenarios. The book covers a wide range of topics, including integrating DEA with machine learning techniques, performance evaluation in diverse sectors like banking and civil engineering, and using DEA in managerial decision-making. It also examines data mining during the Covid-19 pandemic and the application of blockchain and IoT in supply chain management. The book offers a deep dive into the evolution of nonparametric frontier methods and the development of new optimization algorithms, addressing the complexities of modern analytical decision-making tools. A few chapters delve into futuristic topics like fuzzy sets and their extensions in decision-making and exploring e-learning platforms for education. This book is an invaluable resource for researchers, practitioners and students interested in the latest DEA advancements and practical applications in various fields. Its multidisciplinary approach makes it a useful addition to the libraries of those seeking to understand the complexities and potentials of modern analytical decision-making tools. Operations research. 57943 Computational complexity. Operations Research and Decision Theory. 67143 Computational Complexity. Edalatpanah, S.A. editor. edt http://id.loc.gov/vocabulary/relators/edt 86804 Hosseinzadeh Lotfi, Farhad. editor. edt http://id.loc.gov/vocabulary/relators/edt 68758 Kerstens, Kristiaan. editor. edt http://id.loc.gov/vocabulary/relators/edt 86805 Wanke, Peter. editor. edt http://id.loc.gov/vocabulary/relators/edt 86806 SpringerLink (Online service) Springer Nature eBook Printed edition: 9789819769711 Printed edition: 9789819769735 Printed edition: 9789819769742 Infosys Science Foundation Series in Mathematical Sciences, 2364-4044 69688 https://doi.org/10.1007/978-981-97-6972-8 ZDB-2-SMA ZDB-2-SXMS 64595 64595