نوع مقاله : پژوهشی
عنوان مقاله English
نویسندگان English
This study analyzes the evolution and scientific structure of artificial intelligence (AI) applications in strategic investment decision-making, focusing on machine learning, deep learning, and portfolio optimization. Employing a structured review and bibliometric analysis, we examined 1,428 research and review articles from the Web of Science Core Collection (1991–June 2026) using Bibliometrix, Biblioshiny, and VOSviewer.
Findings reveal a 16.07% annual growth rate, with over 70% of the literature published between 2022 and 2026. China leads in both production and citations, followed by the United States. Expert Systems with Applications is identified as the most influential source. Conceptually, the field centers on machine learning, portfolio optimization, reinforcement learning, stock selection, and risk management, while its intellectual foundations rest on portfolio theory, financial econometrics, and computational intelligence.
For strategic management accounting, these results emphasize the critical need for prospective information design, model governance, performance measurement, risk control, and the documentation of management judgment. Ultimately, this research provides a comprehensive multidisciplinary synthesis, offering a strategic agenda for future decision-making and academic inquiry in AI-driven investment.
کلیدواژهها English
فصلنامه حسابداری مدیریت راهبردی