Return to COOPER Framework


This paper provides a framework to deal with large data samples which are difficult to oversee. When different stakeholders have different objectives, when different data sources could differ in quality, when model techniques could result in different outcomes, a uniform approach to assess performance is advised. A standardized model will make non-parametric assessments more reliable, more repeatable, and less costly.
We proposed a framework which consists of 6 interrelated phases: (1) Concepts and objectives, (2) On structuring data, (3) Operational models, (4) Performance comparison model, (5) Evaluation, and (6) Results and deployment. Abbreviated, we obtain the ‘COOPER-framework’. The framework provides both support and a step-by-step plan for the novice researcher, as well as a check-list for the experienced researcher. It is a tool which can be further adapted and modified along the specific needs of the researcher.
This paper also provides some interesting and promising lines for further research. Firstly, the Cooper-framework could benefit from the interaction with empirical applications. Indeed, a similar framework should never be finished and always be open for new developments. Potential applications of the framework consist of educational questions (e.g., the OECD Pisa dataset), business performance (e.g., World Economic Forum), consumer confidence, and the analysis of large statistical databases (e.g., on company performances). The practitioner applying the framework to a particular application may tailor the framework to his/her specific needs. Secondly, although extending the idea of the framework from the outlined DEA model to alternative methodologies (FDH, SFA and parametric models) is rather straightforward, not every phase and checklist item is applicable. We consider it as further research to create a similar framework for other methodologies. Finally, the framework will definitely benefit from new developments in the academic literature. As computing power grows and methodological advances are made, the phases will further evolve.


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