In the final phase, the result and deployment phase, the proposed models are put into action (Figure 8). The entire process is summarized in a report (which refers to all previous deliverables). The report should clearly interpret the results and compare the final results under different model specifications. Indeed, presenting different model specifications will allow the evaluated entities to present themselves as well as possible. If the entity is ranked low in different model specifications, it is more difficult to argue that its ranking arises from the model.
In their search for continuous improvements, the entities could try to assess their efficiency internally. Therefore, the researcher could decide to use an off-the-shelf DEA package (e.g., Emrouznejad and Thanassoulis, 2010 and Emrouznejad, 2005) or to develop a software package (with instructions for novice users). Combined with or independent from the software package, a document including some technical information should be delivered in order to be able to repeat the non-parametric analysis.
Finally, a well documented report containing some information on how to improve the efficiency should be delivered. Any suggestion for improvement has to arise from the non-parametric model. Thanks to the software package, entities will be able to experiment with changes in particular variables. The recommended report has to be written from the point of view of the decision makers. Any technicalities should be bundled in specific sections. The DEA results and interpretations have to be explained as clearly and simple as possible.
Return to COOPER Framework
In this section
by Ali Emrouznejad & Rajiv Banker

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William W Cooper

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FAQ
- What is Data Envelopment Analysis?
- BCC
- Categorical variable
- CCR (ratio) mode
- Composite unit
- Constant returns to scale
- Convex cone - Conical hull
- Convex hull
- Convexity constraint
- Cross efficiency matrix
- DEA algorithm
- DEA results are biased
- Decreasing returns to scale
- Discretionary factor
- Discriminatory power
- DMU (Decision making unit)
- Dual Model
- Dual weights - dual multipliers
- Efficiency score
- Efficiency/Productive efficiency
- Envelopment form
- Environmental factor
- Epsilon
- Exogeneously fixed factor
- Facet
- Homogeneity
- Increasing returns to scale
- Input
- Input-oriented
- Input/output mix
- Isotonicity
- Most productive scale size (MPSS)
- Multiplier form
- Non-naturally enveloped unit
- Nondiscretionary factor
- Ordinal variable
- Outlier
- Output
- Output-oriented
- Overall efficiency
- Pareto-efficiency/Pareto-Koopmans efficiency:
- Peer group
- Piecewise linearity
- Primal (CCR) model
- Production function
- Productivity
- Projected point
- Radial measure
- Ratio models
- Reference set
- Reference unit
- Scale efficiency
- Scale of operations
- Slacks
- Targets
- Technical efficiency
- Technology/Production technology
- Unit
- Unit isoquant/Isoquant
- Units invariance
- Variable
- Variable returns to scale
- Virtual input(output)
- Virtual multipliers
- Visualisation
- Weight Flexibility
- Weights
- Well-rounded performance
- Window analysis