Joe Zhu is Associated Professor of Operations, Department of Management at Worcester Polytechnic Institute, Worcester, MA. His research interests include issues of performance evaluation and benchmarking, supply chain design and efficiency, and Data Envelopment Analysis. He has published over 70 articles in journals such as Management Science, Operations Research, IIE Transactions, Annals of Operations Research, Journal of Operational Research Society, European Journal of Operational Research, Information Technology and Management Journal, Computer and Operations Research, OMEGA, Socio-Economic Planning Sciences, Journal of Productivity Analysis, INFOR, Journal of Alternative Investment and others. He is the author of Quantitative Models for Evaluating Business Operations: Data Envelopment Analysis with Spreadsheets (Kluwer Academic Publishers, 2003). He developed the DEAFrontier software which is a DEA add-in for Microsoft Excel. Professor Zhu has also co-authored two books on modeling performance measurement and evaluating hedge funds. He is a co-editor of the DEA handbook. He is an Associate Editor of OMEGA and The Asia-Pacific Journal of Operational Research. He is also a member of Computers & Operations Research Editorial Board. For more information on his research, please visit www.deafrontier.com.

List of Tables. List of Figures. Preface. 1. Basic DEA Models. 2. Measure-specific DEA Models. 3. Returns-to-Scale. 4. DEA with Preference. 5. Modeling Undesirable Measures. 6. Context-dependent Data Envelopment Analysis. 7. Benchmarking Models. 8. Models for Evaluating Value Chains. 9. Congestion. 10. Super Efficiency. 11. Sensitivity Analysis and Its Uses. 12. DEA Excel Solver. References. Author Index. Topic Index.

Managers are often under great pressure to improve the performance of their organizations. To improve performance, one needs to constantly evaluate operations or processes related to producing products, providing services, and marketing and selling products. Performance evaluation and benchmarking are a widely used method to identify and adopt best practices as a means to improve performance and increase productivity, and are particularly valuable when no objective or engineered standard is available to define efficient and effective performance. For this reason, benchmarking is often used in managing service operations, because service standards (benchmarks) are more difficult to define than manufacturing standards. Benchmarks can be established but they are somewhat limited as they work with single measurements one at a time. It is difficult to evaluate an organization's performance when there are multiple inputs and outputs to the system. The difficulties are further enhanced when the relationships between the inputs and the outputs are complex and involve unknown tradeoffs. It is critical to show benchmarks where multiple measurements exist. The current book introduces the methodology of data envelopment analysis (DEA) and its uses in performance evaluation and benchmarking under the context of mUltiple performance measures.