A Bilevel DEA Model for Efficiency Evaluation and Target Setting with Stochastic Conditions

Andreas C. Georgiou (), Konstantinos Kaparis, Eleni-Maria Vretta, Kyriakos Bitsis and George Paltayian
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Andreas C. Georgiou: Quantitative Methods and Decision Analysis Lab, Department of Business Administration, University of Macedonia, GR-54636 Thessaloniki, Greece
Konstantinos Kaparis: Quantitative Methods and Decision Analysis Lab, Department of Business Administration, University of Macedonia, GR-54636 Thessaloniki, Greece
Eleni-Maria Vretta: Quantitative Methods and Decision Analysis Lab, Department of Business Administration, University of Macedonia, GR-54636 Thessaloniki, Greece
Kyriakos Bitsis: Quantitative Methods and Decision Analysis Lab, Department of Business Administration, University of Macedonia, GR-54636 Thessaloniki, Greece
George Paltayian: Quantitative Methods and Decision Analysis Lab, Department of Business Administration, University of Macedonia, GR-54636 Thessaloniki, Greece

Mathematics, 2024, vol. 12, issue 4, 1-21

Abstract: The effective allocation of limited resources and the establishment of targeted goals play a pivotal role in enhancing the overall efficiency of large enterprises and organizations. To achieve optimal organizational efficiency, managers seek dynamic strategies that adapt to the constraints of limited and uncertain historical data. This paper introduces an evaluation of organizational efficiency through a stochastic framework, employing a bilevel data envelopment analysis (DEA) approach. This decision-making process is centralized within a decision-making unit (DMU) overseeing subordinate decision-making units (subDMUs). Discrete scenarios, each associated with a realization probability, define the uncertain parameters in the bilevel DEA-based model. This stochastic approach allows for recourse actions upon scenario realization leading to an enhanced overall organizational strategy. Decision-makers acting within uncertain and dynamic environments can benefit from this research since it allows the investigation of efficiency assessment under alternative scenarios in the presence of volatility and risk. The potential impact of applying this methodology varies depending on the specific domain. Although, the context of this paper focuses on banking, in general, enhancing resource allocation and target setting under stochasticity, contributes to advancing sustainability across all its three dimensions (economic, environmental, social). As mentioned earlier, the practical application of our approach is demonstrated via a case study in the banking sector.

Keywords: DEA; bilevel optimization; stochastic conditions; resource allocation (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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