Data Envelopment Analysis: An intuitive introduction to relative efficiency analysis
English | 13 Jan. 2026 | ASIN: B0GGGLHNFN | Pages not found | Epub | 426.98 KB
Efficiency is one of the most widely used - and most misunderstood - concepts in performance analysis. Most methods reduce efficiency to a single indicator, a ranking, or an average. Data Envelopment Analysis (DEA) takes a fundamentally different approach. This book offers a clear, intuitive, and conceptually rigorous introduction to DEA , designed for readers who want to understand efficiency - not just calculate it. Written by a researcher with extensive academic and applied experience in DEA, this book transforms a complex quantitative method into an accessible framework for reasoning about performance, comparison, and improvement. Rather than focusing on formulas or software, the book builds understanding step by step: What efficiency really means in real-world settings Why simple indicators and rankings often fail How relative efficiency differs from absolute performance What the efficient frontier represents - and what it does not Why flexibility in weights is essential for fairness How scale, orientation, benchmarks, and slacks shape interpretation When DEA should be used - and when it should not Throughout the book, efficiency is treated not as a judgment, but as a learning opportunity . DEA is presented as a tool for: benchmarking rather than ranking learning rather than labeling improvement rather than punishment The result is a book that bridges the gap between theory and practice, making DEA accessible to: undergraduate and graduate students researchers entering efficiency analysis professionals working with performance evaluation, benchmarking, or policy analysis If you have ever run a DEA model without fully trusting the results - or avoided the method because it seemed too technical - this book was written for you. Efficiency is not about being the best. It is about being the best possible, given the circumstances.
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