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Empirical Analysis of Factors Affecting Financial Distress at Companies: An Emphasis on Data Mining Models | ||
| Iranian Economic Review | ||
| مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 23 بهمن 1402 | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22059/ier.2024.362655.1007769 | ||
| نویسندگان | ||
| Mohsen Lotfi؛ Seyed Hosein Seyedi* | ||
| Department of Industrial Engineering and Management, Shahrood University of Technology, Shahrood, Iran | ||
| چکیده | ||
| This study aimed to analyze the effects of macroeconomic factors (e.g., inflation, economic growth, currency exchange rate, and market competitiveness), managerial characteristics (e.g., ability, optimism, entrenchment, and myopia), and corporate governance (e.g., institutional shareholders, ownership concentration, number of shareholders, and managerial independence) on the financial distress risks of companies listed in the Tehran Stock Exchange. For this purpose, data mining models (e.g., Artificial neural networks and decision trees) were used along with the regression method to analyze a sample of 140 TSE-listed companies within the 2007–2020 period. The research results indicated that macroeconomic factors (i.e., external factors) and managerial characteristics (i.e., internal factors) were identified as the first and second most effective factors in the financial distress risk of companies, respectively. However, corporate governance variables were identified as the least effective factors. According to the results of ranking the effects of research variables on financial distress risk, the most effective variables were identified as market competitiveness, managerial myopia, and inflation. | ||
| کلیدواژه‌ها | ||
| Data Mining؛ Empirical Analysis؛ Financial Distress | ||
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آمار تعداد مشاهده مقاله: 28 |
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