Predicting the performance of companies under pressure based on CEO strength indicators using artificial neural network

Aliabadi, Majid; Sarraf, Fatemeh; Darabi, Roya

doi:10.22075/ijnaa.2023.29675.4225

Predicting the performance of companies under pressure based on CEO strength indicators using artificial neural network

Articles in Press

Document Type : Research Paper

Authors

Majid Aliabadi

Fatemeh Sarraf

Roya Darabi

Department of Accounting, South Tehran Branch, Islamic Azad University, Tehran, Iran

10.22075/ijnaa.2023.29675.4225

Abstract

This article identifies the relationship between the CEO's power indicators and the company's performance under-pressure in the companies listed on the Tehran Stock Exchange and adopts an Artificial Neural Network (ANN) to predict their performance. Accordingly, this paper examined the companies listed on the Tehran Stock Exchange for 10 years from 2011-2021. The regression test by SPSS 20 and 7 Eviews was used to analyze data from 135 companies. The results indicate that the efficiency and honesty of the management affect the performance of the company in the companies under pressure; however, the results did not confirm the effect of the ownership of the board members and the percentage of non-commissioned members of the board of directors on the performance of the company in the under-pressure companies.

Keywords

CEO Power Indicators

Under-pressure Company

Product Market Competition

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