Home  Journals  Economic Analysis: Theory and Practice  5(536) - 2023 May

Practical applications of Network Data Envelopment Analysis

Received: 30 March 2023

Received in revised form: 10 April 2023

Accepted: 18 April 2023

Available online: 30 May 2023

Subject Heading: BUSINESS PERFORMANCE

JEL Classification: C61, C67, O4

Pages: 800–828

https://doi.org/10.24891/ea.22.5.800

Subject. The article considers a methodology for assessing the comparative effectiveness of the activity of homogeneous economic agents, i.e. Data Envelopment Analysis.
Objectives. The focus is on systematization and classification of modern practical applications of network Data Envelopment Analysis, identification of types of additional information that can be extracted from solving problems of network DEA for the strategic management of companies/organizations.
Methods. The study rests on systematic literature review.
Results. At present, multi-stage DEA models are most actively used to model and evaluate the performance of banks, supply chains consisting of a “supplier-manufacturer-distributor” link, innovative and high-tech companies (or territories), and companies whose activities are regulated by strict environmental standards. Least of all, multi-stage DEA models are so far used to model consumer behavior as a sequential process consisting of many stages, which is explained by the underdevelopment of approaches to measuring consumer behavior factors.
Conclusions. The main difference between the types of multi-stage network models is the absence or presence of common inputs for several stages, which are divided in a certain proportion between the stages (subsystems). This factor significantly affects the type of optimization model and approaches to its solution. The presence of common inputs gives rise to the need to solve an additional optimization problem for the distribution of resources between subsystems.

Keywords: Network Data Envelopment Analysis, staged modeling, partial efficiency, system efficiency, network structure

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