Malmquist Productivity Index under Network Structure and Negative Data: An Application to Banking Industry
محورهای موضوعی : Decision Analysis
Seyed Ehsan Shojaie
1
(Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran)
Seyed Jafar Sadjadi
2
(School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran)
رضا توکلی مقدم
3
(Tehran University)
کلید واژه: Network Data Envelopment Analysis, Malmquist Productivity Index, Negative Data, Production Possibility Set, Two-Stage Structure, Banking Industry,
چکیده مقاله :
In this paper, we present a comprehensive approach for evaluating efficiency in complex networks by integrating network data envelopment analysis (NDEA) with the Malmquist productivity index. The proposed method addresses the inherent challenge of accommodating negative data within the network efficiency evaluation framework, which is a common occurrence in real-world network operations. Through the introduction of a two-stage structure, the model not only effectively manages the presence of negative values, but also provides a robust and insightful assessment of network efficiency. A case study from banking sector is employed to demonstrate the efficacy of the proposed approach, showcasing its capacity to offer valuable and actionable insights for decision-making in complex network environments. The results highlight the practical applicability and importance of the extended approach in addressing the complexities associated with evaluating efficiency in diverse network settings.
In this paper, we present a comprehensive approach for evaluating efficiency in complex networks by integrating network data envelopment analysis (NDEA) with the Malmquist productivity index. The proposed method addresses the inherent challenge of accommodating negative data within the network efficiency evaluation framework, which is a common occurrence in real-world network operations. Through the introduction of a two-stage structure, the model not only effectively manages the presence of negative values, but also provides a robust and insightful assessment of network efficiency. A case study from banking sector is employed to demonstrate the efficacy of the proposed approach, showcasing its capacity to offer valuable and actionable insights for decision-making in complex network environments. The results highlight the practical applicability and importance of the extended approach in addressing the complexities associated with evaluating efficiency in diverse network settings.
