Data Envelopment Analysis (DEA) is a mathematical programming model that calculates the relative efficiency of homogenous Decision Making Units (DMUs). The conventional DEA models used to calculate the efficiency require the exact amount of inputs and outputs; in real business situations, however, it is often impossible to determine the exact numeral value of some inputs and outputs. At the same time the Common Set of Weights (CSW) overcomes the weakness of DEA models for assessment under same conditions. On the other hands, it is important to considering the balance in evaluation and calculation of indicators. This study develops a new model to calculate the CSW in fuzzy environments, considering the balanced environment using the Balanced Scorecard (BSC). Our proposed model is linear for fairly and equitably evaluating the DMUs on the same scale, also enables us to deal with fuzzy environment and greatly reduces the computational complexities for enormous volumes of data in many real applications and treat difficulties in fuzzy DEA models. From a managerial point of view, this paper aims to provide an integrated framework to form a better strategic decision-making process about organization performance, which ultimately leads to the competitive advantages and success of the organization in the long run. Finally, in the field of performance management, the proposed model was applied to evaluate the performances of ten manufacturing enterprises in to confirm the validity and applicability of the proposed approach.
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Zarei Mahmoudabadi, M., Emrouznejad, A. Balanced performance assessment under uncertainty: an integrated CSW-DEA and balanced scorecard (BSC). Ann Oper Res (2022). https://doi.org/10.1007/s10479-022-04637-z
- Decision analytics
- Data envelopment analysis (DEA)
- Fuzzy DEA
- Common set of weights (CSW)
- Balanced scorecard (BSC)