Introduction and Comparison of Data Envelopment Analysis Software Packages

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Alireza Alinezhad¹
Seyyed Hamed Mirtaleb
Javad Khalili

¹Associate Professor, Department of Industrial Engineering, Islamic Azad University, Qazvin, Iran

Series: Mathematics Research Developments
BISAC: MAT000000

This book presents and compares 11 software packages of Data Envelopment Analysis (DEA). Performance measurement is done by various methods, one of which is DEA. Due to the ability of DEA models to meet practical requirements, extensive research can be conducted in the fields of mathematics, management, economics, and engineering. Therefore, during recent decades, the use of this method has been considered with significant growth among researchers. DEA evaluates the performance of Decision Making Units (DMUs) by using linear programming. Since linear programming should be solved for each DMU, performance measurement for a large number of DMUs is difficult and time-consuming. For this purpose, various software packages have been designed and developed to address these problems. Each of these software’s is designed for different purposes and has different features and applications. The main objectives of this book are to introduce, express the advantages and disadvantages of each of these software packages, as well as their comparisons.

 

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PREFACE
ABOUT THE AUTHORS
Chapter 1. Review of Data Envelopment Analysis Models
1.1. Introduction
1.2. Methods of Efficiency Measurement
1.2.1. Parametric Methods
1.2.2. Non-Parametric Methods
1.3. Data Envelopment Analysis (DEA)
1.4. Production Possibility Set (PPS)
1.5. Production Technology
1.6. DEA Models
1.6.1. CCR Model
1.6.2. BCC Model
1.6.3. Free Disposal Hull (FDH) Model
1.6.4. Radial Model
1.6.5. Directional Distance Function (DDF) Model
1.6.6. Additive Model
1.6.7. Non-Controllable Variable (NCN) Model
1.6.8. Undesirable Inputs/Outputs Model
1.6.9. Generalized DEA Model
1.6.10. Window Analysis Model
1.6.11. Malmquist Index
1.6.12. Slacks-Based Measure (SBM) Model
1.6.13. Assurance Region (AR) Model
1.6.14. Bounded Variable (BND) Model
1.6.15. Categorical Variable (CAT) Model
1.6.16. Bilateral Comparison Model
1.6.17. Enhanced Russell Measure (ERM) Model
1.6.18. Congestion Model
1.6.19. Cost and New Cost Efficiency Models
1.6.20. Revenue and New Revenue Efficiency Models
1.6.21. Profit and New Profit Efficiency Models
1.6.22. Ratio Efficiency model
1.6.23. Scale Elasticity Model
1.6.24. Epsilon-Based Measure (EBM) Model
1.6.25. Weak Disposability Model
1.6.26. Metafrontier Model
1.6.27. Dynamic DEA Model
1.6.28. Network DEA Model
1.6.29. Context Dependent Model
1.6.30. Bootstrapping Model
1.7. Conclusion
Chapter 2. DEA Excel Software
2.1. Introduction
2.2. Software Presentation
2.2.1. Settings
2.2.2. BCC and CCR Models
2.2.3. Additive Model
2.2.4. NCN Model
2.2.5. Undesirable Input/Output Model
2.3. Running the DEA Excel Software
2.4. Conclusion
Chapter 3. DEA Frontier Software
3.1. Introduction
3.2. Software Presentation
3.2.1. Envelopment Model
3.2.2. Multiplier Model
3.2.3. SBM Model
3.2.4. Measure-Specific Model
3.3. Running the DEA Frontier Software
3.4. Conclusion
Chapter 4. DEA Solver Software
4.1. Introduction
4.2. Software Presentation
4.2.1. Models
4.2.2. Data File Preparation
4.2.2.1. CCR, BCC, IRS, DRS, GRS, SBM, FDH, EBM, Scale Elasticity,
and Congestion Models
4.2.2.2. AR Model
4.2.2.3. AR Global Model
4.2.2.4. Super-Efficiency Model
4.2.2.5. NCN and NDSC Models
4.2.2.6. BND Model
4.2.2.7. Bilateral, System and CAT Models
4.2.2.8. Cost Efficiency and New Cost Efficiency Models
4.2.2.9. Revenue Efficiency and New Revenue Efficiency Models
4.2.2.10. Profit Efficiency and New Profit Efficiency Models
4.2.2.11. Malmquist-Radial and Malmquist, Window Analysis Models
4.2.2.12. Scale Elasticity Model
4.2.2.13. Congestion Model
4.2.2.14. Undesirable Outputs Model
4.2.2.15. Weighted SBM Model
4.2.2.16. Hybrid Model
4.2.2.17. Network DEA (Network SBM) Model
4.2.2.18. Dynamic DEA (Dynamic SBM) Model
4.2.2.19. Dynamic and Network SBM (DNSBM) Model
4.2.2.20. Non-Convex Model
4.2.2.21. Resampling Model
4.2.2.22. DDF Model
4.2.3. Types of Results for Worksheets
4.2.3.1. Score
4.2.3.2. Projection
4.2.3.3. Weight
4.2.3.4. Weighted Data
4.2.2.5. Summary
4.2.3.6. Slack
4.2.3.7. Graph 1
4.2.3.8. Graph 2
4.2.3.9. RTS
4.2.3.10. Malmquist k
4.2.3.11. Scale Elasticity
4.2.3.12. Congestion
4.2.3.13. Resample Summary
4.2.3.14. Window k
4.2.3.15. Decomposition
4.2.3.16. SASvsCRSvsVRS
4.3. Running the DEA Solver Software
4.4. Conclusion
Chapter 5. DEAP Software
5.1. Introduction
5.2. Software Presentation
5.2.1. Executable File (DEAP.EXE)
5.2.2. Data File (EG-dta.txt)
5.2.3. Instruction File (EG-ins.txt)
5.2.4. Results File (EG-out.txt)
5.3. Running the DEAP Software
5.4. Conclusion
Chapter 6. EMS Software
6.1. Introduction
6.2. Software Presentation
6.2.1. Data File
6.2.2. Final Results
6.3. Running the EMS Software
6.4. Conclusion
Chapter 7. Frontier Analyst Software
7.1. Introduction
7.2. Software Presentation
7.2.1. Toolbar
7.2.1.1. Home
7.2.1.2. Source Data
7.2.1.3. Analysis
7.2.1.4. Result
7.2.1.5. Graph
7.2.1.6. Report
7.2.1.7. Translation
7.2.2. Data entry
7.2.2.1. Transfer Data from Excel
7.2.2.2. Transfer Data from the Clipboard
7.2.2.3. Link to External Database
7.2.2.4. Use SPSS Software Information
7.2.2.5. Import Data from the Text File
7.2.2.6. Enter Data Manually
7.2.2.7. Import Data via Web Files
7.3. Running the Frontier Analyst Software
7.4. Conclusion
Chapter 8. Pioneer Software
8.1. Introduction
8.2. Software Presentation
8.2.1. Software Models
8.2.2. Data Entry
8.2.3. Final Results
8.3. Running the Pioneer Software
8.4. Conclusion
Chapter 9. MaxDEA Software
9.1. Introduction
9.2. Software Presentation
9.2.1. Toolbar
9.2.1.1. Prepare Data
9.2.1.2. Run Model
9.2.1.2.1. Envelopment Models
9.2.1.2.1.1. Measuring Efficiency Based on Distance
9.2.1.2.1.2. Efficiency Measurement Based on Orientation
9.2.1.2.1.3. Efficiency Measurement Based on the RTS
9.2.1.2.1.4. Efficiency Measurement Based on Frontier
9.2.1.2.1.5. Advanced Models 1
9.2.1.2.1.6. Advanced Models 2
9.2.1.2.1.7. Results for Envelopment Models
9.2.1.2.1.8. Options
9.2.1.2.2. Multiplier Models
9.2.1.2.2.1. Measuring Efficiency Based on Distance
9.2.1.2.2.2. Efficiency Measurement Based on Orientation
9.2.1.2.2.3. Efficiency Measurement Based on the RTS
9.2.1.2.2.4. Advanced Models 1 and 2
9.2.1.2.2.5. Bootstrapping Model
9.2.1.2.2.6. Results
9.2.1.2.2.7. Options
9.2.1.3. Final Results
9.2.1.4. Frontier Graphs
9.2.1.5. Help
9.2.1.6. Software Language Setting
9.2.1.7. Editing
9.2.1.8. Filtering and Sorting
9.3. Running the MaxDEA Software
9.4. Conclusion
Chapter 10. MDeap Software
10.1. Introduction
10.2. Software Presentation
10.2.1. Toolbar
10.2.1.1. File
10.2.1.2. Edit
10.2.1.3. Unit
10.2.1.4. Variable
10.2.1.5. Model
10.2.1.6. View
10.2.1.7. Help
10.3. Running the MDeap Software
10.4. Conclusion
Chapter 11. PIM Software
11.1. Introduction
11.2. Software Presentation
11.2.1. Toolbar
11.2.1.1. File
11.2.1.2. View
11.2.1.3. Data
11.2.1.4. Run
11.2.1.5. Models
11.2.1.5.1. Model Selection
11.2.1.5.2. Final Results
11.2.1.6. Help
11.2.1.7. Project Explorer
11.2.2. Data Entry
11.3. Running the PIM Software
11.4. Conclusion
Chapter 12. DEAOS Web-Based Software
12.1. Introduction
12.2. Software Presentation
12.2.1. The Main Tools
12.2.2. Data Entry
12.2.3. Problem Solving
12.2.4. Final Results
12.3. Running the DEAOS Software
12.4. Conclusion
Chapter 13. Software Packages Comparison
13.1. Introduction
13.2. Software Packages Comparison
13.3. Conclusion
REFERENCES
INDEX

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