Identifying the Influential Factors in Increasing the Efficiency of Network Systems: A Mixed Binary Linear Programming

Reza Feizabadi () and Mehri Bagherian ()
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Reza Feizabadi: Hakim Sabzevari University
Mehri Bagherian: University of Guilan

SN Operations Research Forum, 2023, vol. 4, issue 4, 1-14

Abstract: Abstract Old models in data envelopment analysis (DEA) consider decision-making units (DMUs) as black boxes. Therefore, they do not have a proper efficiency to evaluate network systems. This shortcoming has led to the emergence of network models that take the performance of a system’s processes into account in calculating the performance, and some of which also assign a certain value of performance to the processes. However, no model has examined the effect of intermediate factors in a network system, while the study of these intermediate factors can greatly help to increase the efficiency of a system. In this paper, our aim is to present a mixed binary linear programming that identifies the intermediate factors that are relatively more effective in increasing the performance of a network system. At the end, the new model is implemented on a small network system in order to better describe the performance, as well as on a real-world network system.

Keywords: Data envelopment analysis (DEA); Network systems; Intermediate factors; Mixed binary linear programming (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s43069-023-00259-8

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