Data envelopment analysis in performance measurement: a critical analysis of the literature

Abstract

(2016). Data envelopment analysis in performance measurement: a critical analysis of the literature. Problems and Perspectives in Management,. doi:10.21511/ppm.14(3-3) This study examines the benefits of data envelopment analysis (DEA) in evaluating the performance of decision making units (DMUs). DEA is a mathematical programming tool applied in performance measurement. The problem identified is establishing business support units as value adding business units. A case is made for applying DEA when evaluating the performance of such business support units. To this end, a literature review of the results of applications of DEA to the evaluation of information technology and purchasing supply chain management functions was conducted. The findings indicate the benefits of DEA are that the method identifies efficient performers in a given population and, therefore, allows for benchmarking against the 'best in class' performer. This as opposed to more commonly used parametric methods, such as regression analysis, which result in a comparator that represents the average performance for a given population, therefore, allowing only for measurement against the average. In addition, the findings indicate that in respect of business support units, the DEA methodology allows for the incorporation of intermediate outcomes, which facilitates the measurement of the contribution of these units to overall company performance. Although the DEA methodology has been widely applied, it is still not as well known or generally applied as the more common approaches. The recommendations made in this paper will be beneficial in bringing DEA to the attention of decision-makers. The recommendations will also raise awareness of the potential benefits to be realised when applying the method in developing performance measurement frameworks for business support units.

Supply chain sustainability performance measurement of small and medium sized enterprises using structural equation modeling

“…A large number of research associated with applications of DEA on performance measurement and firm benchmarking exists (e.g., Chen and Zhu 2004;Chiu et al 2011;Easton et al 2002;Halkos and Salamouris 2004;Saranga and Moser 2010;Soheilirad et al 2017;Wang et al 1997). We refer the interested reader to Shewell and Migiro (2016) for a review on the applications of DEA in performance measurement. DEA, which is a non-parametric linear programming approach, evaluates the performance of a set of entities called decision making units (DMUs) by using the observed inputs and outputs of each DMU to calculate its efficiency in relation to all other DMUs in the population.…”

“…Thus, DEA calculations result in a relative efficiency score for each DMU. Based on this framework, DEA has been extensively used for evaluating the performance of many different types of business units and activities (Shewell and Migiro 2016). Advantages of DEA in performance evaluation rely on the fact that DEA does not rely on prior assumptions such as required for regression analysis and it does not rely on any assumptions of a functional form relating inputs to outputs.…”

Data envelopment analysis for measuring performance in a competitive market

“…There are limitations to using DEA. Shewell and Migiro (2016) wrote that the number of input and output variables related to the size of the population analyzed (number of DMUs) can limit the effectiveness of analysis. A further possible restriction of the DEA application is that there may be other performance indicators that can impact the performance of DMUs that are not includ-ed in the examination.…”

Benchmarking of bank performance using the life cycle concept and the DEA approach

“…Thus, Emrouznejad and Thanassoulis (2010) offered a dynamic index of productivity of 17 industrialized countries based on the DEA method; Khodabakhshi and Aryavash (2014) use it to measure the productivity of forest districts. Shewell and Migiro (2016) highlighted the advantages of the DEA method for assessing the effectiveness of business units and presented the results of a literature review regarding its use for assessing information technologies and the system of management of supply chains. This method is also used to determine the production efficiency of automobile transport in the regional context (Grigoriev, 2010), to evaluate the efficiency of crop production (Dolgikh, 2015).…”