1. Data Envelopment Analysis

2. Weights Optimization

3. Primal – Dual Relations

4. Minimize Inputs Interpretation

5. Graphic Illustration

6. Conclusions From Optimality Pareto Efficient Technical Input Efficiency Efficient Goal and Efficient Peers

7. Maximize Outputs

8. Conclusions From Optimality Pareto Efficient Technical Output Efficiency

9. Return to Scale

10. Modeling Return to Scale

11. Numeric Example

15. M 3 is inefficient M 2 and M 4 are efficient peers

16. DEA Software

17. Summary, Pros and Cons Avoids arbitrary selection of weights. Uses the theory of mathematical programming. Need to solve n programs. Assumes deterministic measurements. Requires a sufficient number of units.

18. Summary, Pros and Cons Requires units to use the same exact variables. Insufficient conclusions for decision making. Use of discrete or even categorical values. Unchangeable values.