Advances In Dea Theory And Applications - With Extensions To Forecasting Models

A key resource and framework for assessing the performance of competing entities, including forecasting models

Advances in DEA Theory and Applications provides a much-needed framework for assessing the performance of competing entities with special emphasis on forecasting models. It helps readers to determine the most appropriate methodology in order to make the most accurate decisions for implementation. Written by a noted expert in the field, this text provides a review of the latest advances in DEA theory and applications to the field of forecasting.

Designed for use by anyone involved in research in the field of forecasting or in another application area where forecasting drives decision making, this text can be applied to a wide range of contexts, including education, health care, banking, armed forces, auditing, market research, retail outlets, organizational effectiveness, transportation, public housing, and manufacturing. This vital resource: 

• Explores the latest developments in DEA frameworks for the performance evaluation of entities such as public or private organizational branches or departments, economic sectors, technologies, and stocks
• Presents a novel area of application for DEA; namely, the performance evaluation of forecasting models
• Promotes the use of DEA to assess the performance of forecasting models in a wide area of applications
• Provides rich, detailed examples and case studies

Advances in DEA Theory and Applications includes information on a balanced benchmarking tool that is designed to help organizations examine their assumptions about their productivity and performance.

KAORU TONE is with the National Graduate Institute for Policy Studies, Japan. His contribution to DEA has a variety of attainments. He authored a classical book Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software under the co-authorship with Professor Cooper (University of Texas) and Professor Seiford (University of Michigan). He also published many papers on DEA in international journals. Kaoru Tone opened a new avenue for performance evaluation, called Slacks-based Measure (SBM) that is widely utilized over the world. His recent innovations include Network SBM, Dynamic SBM, Dynamic DEA with Network Structure, Congestion, Returns-to-growth in DEA, Ownership-specified Network DEA, Non-convex Frontier DEA, Past-Present-Future Inter-temporal DEA, Resampling DEA and SBM-Max.