WJSTSD · Vol 21, Nos 1/2/3 · 2026Research

Financial Leverage and Dividends as Determinants of Earnings Management: Evidence from Amman Stock Exchange and Implications for AI and Sustainability

Samah Mohmmad Noor Zeab Al-Khalili
Master of Accounting, Faculty of Business, Applied Science Private University
Mohammed Idris
Associate Professor of Accounting, Accounting Department
Faculty of Business, Applied Science Private University
Sodfa Eltaher
Department of Business Administration
Faculty of Commerce for Girls, Al-Azhar University
Received: 24 November 2025Revised: 16 December 2025Accepted: 22 December 2025Published: 20 March 2026
Purpose

The aim of the study is to explore the effect of financial leverage on the relationship between cash dividends and earnings management in service companies listed on the Amman Stock Exchange (ASE).

Design/Methodology/Approach

The researchers used a quantitative methodology to achieve the study objectives. The study duration is five years, from 2020 to 2024.

Findings

The study demonstrates that different earnings management mechanisms behave differently, supporting the argument that firms selectively choose channels with the lowest detection risk.

Original/Value of the Paper

This paper contributes to the discussion by considering the sustainability of dividends, leverage, and earnings management through the lens of artificial intelligence (AI).

Research Limitations/Implications

The study considers only service firms listed on the ASE from 2020 to 2024.

Practical Implications

The research reveals that it is important for regulators and firms to adopt AI-based financial governance systems that may lead to improved data quality, ethical soundness, and sustainability-induced transparency.

Keywords
Earnings ManagementFinancial LeverageArtificial IntelligenceIntegrationSustainability
Citation

Al-Khalili, S. M. N. Z., Idris, M. Eltaher, S. (2026): Financial Leverage and Dividends as Determinants of Earnings Management: Evidence from Amman Stock Exchange and Implications for AI and Sustainability. World Journal of Science, Technology and Sustainable Development (WJSTSD), Vol. 21, Nos. 1/2/3, pp. 145-161. WASD: London, United Kingdom.