Buch, Englisch, 328 Seiten, Format (B × H): 152 mm x 229 mm
Approaches for Handling Ratio Data
Buch, Englisch, 328 Seiten, Format (B × H): 152 mm x 229 mm
ISBN: 978-0-443-36488-4
Verlag: Elsevier Science
Advanced Topics in Inverse Data Envelopment Analysis: Approaches for Handling Ratio Data explores and tackles the most significant challenges encountered by researchers and practitioners in decision analysis and performance evaluation. This book delves into the sophisticated realm of Ratio Data Envelopment Analysis (DEA-R), offering a thorough examination of advanced methodologies, practical examples, and insights into managing complex problems involving both non-negative and negative data. Filling crucial gaps in existing literature, this comprehensive resource focuses on the emerging field of Inverse DEA-R, equipping readers with the necessary tools and knowledge to address a wide range of challenging data types. This book serves as an essential guide for making informed and efficient decisions, guiding researchers and graduate students in computer science, applied mathematics, industrial engineering, and finance, navigating the complexities of decision analysis in today's data-driven world.
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
- Wirtschaftswissenschaften Betriebswirtschaft Betriebswirtschaft: Theorie & Allgemeines
- Mathematik | Informatik EDV | Informatik Business Application Unternehmenssoftware
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken Automatische Datenerfassung, Datenanalyse
Weitere Infos & Material
1. Managerial concepts and practical motivations
2. Introduction to Data Envelopment Analysis
3. DEA Models in the Presence of Negative Data
4. DEA Models for Ratio Data (DEA-R Models)
5. Introduction to Inverse DEA Models
6. Modelling using Inverse DEA
7. Inverse DEA-R Models for Engineering
8. Inverse DEA-R Models for Input and Output Estimation in the Presence of Negative Data
9. Inverse DEA-R Models for Mergers and Acquisitions
10. Inverse DEA-R Models for Mergers and Acquisitions in the Presence of Negative Data