Measuring potential sub-unit efficiency to counter the aggregation bias in benchmarking
- 131 Downloads
The paper deals with benchmarking cases where highly aggregated decision making units are in the data set. It is shown that these units—consisting of sub-units which are not further known by the evaluator—are likely to receive an unjustifiable harsh evaluation, here referred to as aggregation bias. To counter this bias, we present an approach which allows to calculate the potential sub-unit efficiency of a decision making unit by taking into account the possible impact of its sub-units’ aggregation without having disaggregated sub-unit data. Based on data envelopment analysis, the approach is operationalized in several ways. Finally, we apply our method to the benchmarking model actually used by the Brazilian Electricity Regulator to measure the cost efficiency of the Brazilian distribution system operators. For this case, our results reveal that the potential effect of the aggregation bias on the operators’ efficiency scores is enormous.
KeywordsBenchmarking Data envelopment analysis DEA Aggregation bias Potential sub-unit efficiency Regulation
JEL ClassificationC14 C61 C67
The authors would like to thank the reviewers for their helpful comments. The first author gratefully acknowledges that this work was supported by the Deutsche Forschungsgemeinschaft (DFG) under Grant AH 90/5-1. The third author appreciates that this work was supported by the Fundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG) and the Companhia Energética de Minas Gerais (CEMIG) under Grant APQ-03165-11; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) under Grant 999999.000003/2015-08; Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) under Grant 444375/2015-5.
This work was supported by Deutsche Forschungsgemeinschaft (DFG) under Grant AH 90/5-1, Fundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG) and Companhia Energética de Minas Gerais (CEMIG) under Grant APQ-03165-11, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) under Grant 999999.000003/2015-08, Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) under Grant 444375/2015-5.
Compliance with ethical standards
Conflict of interest
Although one of the funds is supported by a company, there is no conflict of interest. The developed approach is universally applicable and of general interest for any benchmarking study.
- ANEEL (Agẽncia Nacional De Energia Elétrica) (2015) Metodologia de custos operacionais [operational costs methodology]. Technical note 66/2015. BrasiliaGoogle Scholar
- Bogetoft P, Lopes A (2015) Comments on the Brazilian benchmarking model for energy distribution regulation: fourth cycle of tariff review—technical note 407/2014. http://nespufmg.com.br/content/upload/p/d3d9446802a44259755d38e6d163e820.pdf. Accessed 16 Dec 2017
- Bogetoft P, Pruzan P (1991) Planning with multiple criteria. North-Holland, AmsterdamGoogle Scholar
- Farrell MJ (1957) The measurement of productive efficiency. J R Stat Soc 120:253–281Google Scholar
- Fox KJ (2012) Problems with (dis)aggregating productivity, and another productivity paradox. Ann Oper Res 37:249–259Google Scholar
- Hackman ST (2010) Production economics: integrating the microeconomic and engineering perspectives. Springer, BerlinGoogle Scholar
- Sung T-J, Lu Y-T, Ho S-S (2010) Time-based strategy and business performance under environmental uncertainty: an empirical study of design firms in Taiwan. Int J Des 4(3):29–42Google Scholar