Ranking the Financial Inefficiency Factors of Companies with the Combined Approach of Data Envelopment Analysis and Neural Network

Mazandaran Negar Foroghi (), Karimi Balal () and Shahverdiani Shadi ()
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Mazandaran Negar Foroghi: Department of Finance Management, Adiban Institute of Higher Education, Garmsar, Iran
Karimi Balal: Department of Mathematic, West Tehran Branch, Islamic Azad University, Tehran, Iran
Shahverdiani Shadi: Department of Business Administration-Finance, Shahr-e-Qods Branch, Islamic Azad University, Tehran, Iran

Studia Universitatis „Vasile Goldis” Arad – Economics Series, 2025, vol. 35, issue 2, 65-85

Abstract: The purpose of this article is to identify and rank the factors of financial inefficiency of companies. For this, a combined approach and two techniques of Data Envelopment Analysis (DEA) and Artificial Neural Network (ANN) are used. The work is done in two stages. In the first stage, we use the data envelopment analysis model and evaluate the efficiency of the companies. In the second stage, the efficiency score obtained for the companies is used and neural network methods are used to determine the factors of financial inefficiency in the companies admitted to the stock exchange. The results of the research show that the proposed approach identifies and prioritizes the factors of financial inefficiency of companies listed on the Tehran Stock Exchange.

Keywords: financial inefficiency factors; ranking; data envelopment analysis; neural network (search for similar items in EconPapers)
JEL-codes: C6 G20 M2 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:suvges:v:35:y:2025:i:2:p:65-85:n:1003

DOI: 10.2478/sues-2025-0008

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