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.
1. Chapter two. Introduction to data envelopment analysis - p. 33 2. Chapter three. Data envelopment analysis models in the presence of negative data - p. 77 3. Chapter four. Data envelopment analysis models for ratio data - p. 103 4. Chapter five. Introduction to inverse data envelopment analysis models - p. 145 5. Chapter six. Modelling mergers and acquisitions using inverse data envelopment analysis - p. 173 6. Chapter seven. Inverse ratio-based data envelopment analysis models for input and output estimation - p. 193 7. Chapter eight. Inverse ratio-based data envelopment analysis models for input and output estimation in the presence of negative data - p. 215 8. Chapter nine. Inverse data envelopment analysis for ratio data models for mergers and acquisitions - p. 243 9. Chapter ten. Inverse ratio-based data envelopment analysis models for mergers and acquisitions in the presence of negative data - p. 279 10. Index - p. 305
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.
1. Chapter two. Introduction to data envelopment analysis - p. 33 2. Chapter three. Data envelopment analysis models in the presence of negative data - p. 77 3. Chapter four. Data envelopment analysis models for ratio data - p. 103 4. Chapter five. Introduction to inverse data envelopment analysis models - p. 145 5. Chapter six. Modelling mergers and acquisitions using inverse data envelopment analysis - p. 173 6. Chapter seven. Inverse ratio-based data envelopment analysis models for input and output estimation - p. 193 7. Chapter eight. Inverse ratio-based data envelopment analysis models for input and output estimation in the presence of negative data - p. 215 8. Chapter nine. Inverse data envelopment analysis for ratio data models for mergers and acquisitions - p. 243 9. Chapter ten. Inverse ratio-based data envelopment analysis models for mergers and acquisitions in the presence of negative data - p. 279 10. Index - p. 305
