Performance evaluation through DEA benchmarking adjusted to goals

By José L. Ruiz, Inmaculada Sirvent. Omega, 2018

67 citations recorded by the source corpus.

Abstract Data Envelopment Analysis (DEA) is extended to the evaluation of performance of organizations within the framework of the implementation of plans for improvements that set management goals. Managers usually set goals without having any evidence that they will be achievable at the moment of conducting performance evaluation or, on the contrary, they may set little too unambitious goals. Using DEA for the benchmarking ensures an evaluation in terms of targets that both are attainable and represent best practices. In addition, the approach we propose adjusts the DEA benchmarking to the goals in order to consider the policy of improvements that was pursued with the setting of such goals. From the methodological point of view, the models that minimize the distance to the DEA strong efficient frontier are extended to incorporate goal information. Specifically, the models developed seek DEA targets that are as close as possible to both actual performances and management goals. To illustrate, we examine an example that is concerned with the evaluation of performance of public Spanish universities.

Subfields: Economics and Econometrics, Management Information Systems, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/d8cb73e93f28558351a1eed80a1ecdb7e6847e41

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Citations in the corpus

Feature Selection in Data Envelopment Analysis: A Mathematical Optimization approach (2020, methodology): “Within benchmarking, Data Envelopment Analysis (DEA) is one of the most widely used tools, [4, 7, 8, 11, 14, 15].”