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Dr Hassan Rostamzadeh, Dr Ali Reza Fakharzadeh,
Volume 17, Issue 1 (5-2026)
Abstract
Existing merger approaches in data envelopment analysis integrate decision-making units in a single stage, but in practice, merging units may not be possible or affordable at once. We propose a finite multi-stage framework for the gradual merger of decision-making units that incorporates practical constraints. The model determines input and output contributions of the merged units at each stage and constructs a strictly increasing efficiency sequence that converges to a Pareto-efficient state. Each new unit is optimized using both input and output orientation while preserving a uniform return to scale type across stages. The framework is validated through a multi-stage merger application on a subset of Iranian banks.
F. Ahmadi, S. Kordrostami, M. Mirzaei Chalakei, L. Khoshandam,
Volume 17, Issue 1 (5-2026)
Abstract
Measuring capacity utilization is an important aspect among processes in order to determine overcapacity or undercapacity. Furthermore, in many situations, the convexity and homogeneity properties are not satisfied. Accordingly, in this paper, meta-frontier free disposal hull (FDH) frameworks are proposed to estimate output-oriented and input-oriented capacity utilization (CU) rates of firms under nonconvexity property and heterogeneity of technology. Also, the introduced technique is applied to assess capacity utilization of some Iranian hospitals. The findings show the presented approach is beneficial to measure capacity utilization rates of systems in the presence of nonconvexity and heterogeneity.
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