Data Envelopment Analysis. Weights Optimization Primal – Dual Relations.

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Presentation transcript:

Data Envelopment Analysis

Weights Optimization

Primal – Dual Relations

Minimize Inputs Interpretation

Graphic Illustration

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

Maximize Outputs

Conclusions From Optimality Pareto Efficient Technical Output Efficiency

Return to Scale

Modeling Return to Scale

Numeric Example

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

DEA Software

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.

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.