Advertisement

Quantitative Models for Performance Evaluation and Benchmarking

Data Envelopment Analysis with Spreadsheets and DEA Excel Solver

  • Joe Zhu

Part of the International Series in Operations Research & Management Science book series (ISOR, volume 51)

Table of contents

  1. Front Matter
    Pages i-xxiii
  2. Joe Zhu
    Pages 1-45
  3. Joe Zhu
    Pages 47-59
  4. Joe Zhu
    Pages 61-90
  5. Joe Zhu
    Pages 91-104
  6. Joe Zhu
    Pages 105-111
  7. Joe Zhu
    Pages 131-156
  8. Joe Zhu
    Pages 157-179
  9. Joe Zhu
    Pages 181-195
  10. Joe Zhu
    Pages 197-215
  11. Joe Zhu
    Pages 217-261
  12. Joe Zhu
    Pages 263-283
  13. Back Matter
    Pages 285-301

About this book

Introduction

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.

Keywords

DEA (data envelopment analysis) Data Envelopment Analysis Data-Envelopment-Analysis benchmarking calculus data envelopment efficiency evaluation performance service

Authors and affiliations

  • Joe Zhu
    • 1
  1. 1.Worcester Polytechnic InstituteUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4757-4246-6
  • Copyright Information Springer-Verlag US 2003
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4757-4248-0
  • Online ISBN 978-1-4757-4246-6
  • Series Print ISSN 0884-8289
  • Buy this book on publisher's site