Archives
Vol. 1 No. 1 (2026)
The International Journal of Adaptive Management and Business Intelligence (IJAMBI) showcases research addressing emerging challenges and opportunities in management, finance, enterprise systems, and intelligent technologies. The articles examine financial system evaluation during periods of uncertainty, data-driven algorithmic trading enhanced by market sentiment analysis, SAP S/4HANA-enabled finance transformation, continuous auditing and fraud detection, and cognitive computing approaches for autonomous financial decision-making. Together, these studies demonstrate the growing role of advanced analytics, enterprise platforms, and artificial intelligence in improving organizational performance, governance, risk management, and strategic business intelligence.
Vol. 1 No. 3 (2026)
This issue presents a diverse collection of research advancing knowledge discovery, intelligent systems, and digital transformation across education, business, and enterprise technology. The featured studies explore learning analytics in virtual education, visual analytics for business workflows, organizational intelligence maturity, agile project integration, decentralized wireless infrastructure management, and university-based entrepreneurship. Further contributions examine generative AI for financial workflow automation, universal journal architecture in next-generation ERP, innovation in digital commerce, and deep neural attribution for stage-aware marketing. Together, these studies offer valuable insights into emerging technologies, strategic decision-making, and data-driven innovation.
Vol. 1 No. 2 (2026)
This issue brings together a diverse collection of high-quality research spanning geospatial analytics, educational technology, financial systems, enterprise resource planning, supply chain resilience, business intelligence, and artificial intelligence. The featured articles present innovative frameworks, critical reviews, empirical investigations, and advanced analytical approaches that address contemporary challenges across academia and industry. By combining methodological rigour with practical relevance, these contributions offer valuable insights into data-driven decision-making, digital transformation, financial forecasting, and organisational resilience. Collectively, they highlight the expanding role of intelligent technologies and interdisciplinary research in shaping sustainable, efficient, and future-ready systems.