Stochastic Benchmarking: Theory and Applications: 317 (International Series in Operations Research & Management Science) - Tapa dura

Acerca del autor

Alireza Amirteimoori is a professor in the Applied Mathematics and Operations Research Group at Islamic Azad University, Iran. His research interests lie in the broad area of performance management with special emphasis on quantitative methods for performance measurement, and especially those based on the broad set of methods known as data envelopment analysis (DEA).

Biresh K. Sahoo is a professor of economics at Xavier Institute of Management, XIM University, Bhubaneswar, India, and an associate editor of Omega: The International Journal of Management Science. He specializes in applied production frontier analysis, and his research interests are in the areas of efficiency and productivity performance of firms and the economics of benchmarking.

Vincent Charles is an experienced researcher in the field of artificial intelligence and management science, currently with the School of Management, University of Bradford, UK.He has more than two decades of teaching, research, and consultancy experience, having been a full professor and director of research for more than a decade. He has published over 130 research outputs and is the recipient of many international academic honors and awards.

De la contraportada

This book introduces readers to benchmarking techniques in the stochastic environment, primarily stochastic data envelopment analysis (DEA), and provides stochastic models in DEA for the possibility of variations in inputs and outputs. It focuses on the application of theories and interpretations of the mathematical programs, which are combined with economic and organizational thinking. The book's main purpose is to shed light on the advantages of the different methods in deterministic and stochastic environments and thoroughly prepare readers to properly use these methods in various cases. Simple examples, along with graphical illustrations and real-world applications in industry, are provided for a better understanding. The models introduced here can be easily used in both theoretical and real-world evaluations.