DEA-based performance measurement with a centralized view on DMUs

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Standard Data Envelopment Analysis (DEA) has widely been used to evaluate the efficiency of Decision Making Units (DMUs) on the assumption that each DMU operates independently. Under the scenario of a centralized management, however, an umbrella organization strives for improving the overall performance of its DMUs. Our research addresses this scenario by modifying DEA-based benchmarking systems according to a controlling-type structure by which the central management’s preferences can be taken into account. While DFG project (sign removed) (10/2015–09/2018) served to develop approaches to incorporate crucial controlling parameters into DEA with a centralized view of measurement, the purpose of project (sign removed)(10/2018–09/2020) is to design systems of incentives for DMUs partitioned into distinct groups and for organizations with different degrees of decentralization.Our respective findings have opened up one more research avenue that refers to the incorporation of environmental variables into the centralized view of measurement. A well-designed approach to account for such variables not only can enhance our conceptual frameworks being developed but also gives rise to innovative models. They are in the focus of our final research objective: Accounting for environmental variables – Design of a system of incentives with a centralized view of measurement.Taking the heterogeneity of the DMUs’ environments into account is of particular importance when frontier-based benchmarking approaches are used to run incentive systems for improving performance: While such a system obliges poor-performing units to save costs, e.g., good-performing units may receive rewards to perform better. Naturally, the units may strive to claim that they are not fully responsible for their performance that would to some degree depend on factors (i.e. environmental variables) beyond their control.Against this background, we aim at designing a new system of incentives that takes environmental variables into account. Its usefulness will be shown with regard to the electricity transmission sector in Brazil. The respective regulatory agency faces severe problems regarding the development of an appropriate incentive system by which this sector should be regulated. Based on this example, our first goal is to show how such regulatory systems can be modeled from both the perspective of principal-agent theory in general and frontier-based incentive regulation in particular. To account for environmental factors, the Brazilian regulator applies the so-called second-stage procedure: The DEA efficiency scores computed in a first stage are regressed on a set of environmental variables in a second stage. However, the regulator’s procedure suffers from a number of serious shortcomings, cause by, e.g., the small sample size. Hence, the second goal of our research is to convincingly incorporate environmental variables into the performance analysis.