Aims and Scope

AVE Trends in Intelligent Management Letters (ATIML) is a quarterly worldwide journal that publishes original, high-quality articles on intelligent systems in accounting, economics, finance, marketing, and management.  Big data, business intelligence, social media, and other developing technologies are also covered by the journal. ATIML promotes new technology development and integration into actual applications.  Therefore, implementation concerns are as important as development issues. ATIML targets academics in intelligent systems, emerging technologies, and business, as well as advanced practitioners who want to improve their productivity, efficiency, and economy.  The journal uses intelligent systems and application reviewers, a unique characteristic.  Reviewers must assess originality and influence on accounting, finance, and management research, teaching, and practice. ATIML publishes papers on novel intelligent systems technologies with application potential, the application of established technologies in areas of accounting, finance, or management previously dominated by unintelligent systems approaches, re-examinations of intelligent system performance that improve understanding of either the technique or the application area, and implementation and performance papers.  Case studies using new and intelligent technologies are also sought.  Finally, surveys that are useful to academics, teachers, and practitioners are sought.

Topics covered include:

• AI-Driven Decision Making in Financial Management
• Social Media Analytics for Consumer Behavior Insights
• Supply Chain Optimization Through Data-Driven Strategies
• Augmented Analytics for Business Process Optimization
• Big Data Analytics for Predictive Marketing Strategies
• Cloud-Based Business Intelligence Solutions for Enterprises
• Corporate Governance and Financial Transparency
• Explainable AI for Ethical Decision-Making in Finance
• Predictive Modeling for Stock Market Analysis
• Role of CRM Systems in Customer Retention Strategies
• Sentiment Analysis for Market Trend Predictions
• Financial Risk Management Strategies in Banking
• Impact of Business Intelligence on Decision-Making
• Machine Learning Models for Risk Assessment in Banking
• Economic Impact of Digital Transactions on Traditional Banking
• Effectiveness of Internal Auditing in Fraud Prevention