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Academic Journal

International Journal of Adaptive Management and Business Intelligence

ISSN: 3143-7176 Building robust, ethical, and scalable organizations requires an integrated approach that recognizes the close interdependence between adaptive management strategies and data-driven business intelligence. As global markets and operational environments become increasingly volatile, it is essential to move beyond static models and embrace systems that prioritize reliability, transparency, and long-term strategic sustainability. IJAMBI focuses on methods that are resilient to market uncertainty and distributional shifts, specifically designing systems that allow businesses and institutions to adapt to evolving real-world conditions. Achieving meaningful progress in this field demands attention to foundational challenges such as data quality, predictive analytics, computational efficiency, and responsible deployment within corporate and governmental frameworks. The International Journal of Adaptive Management and Business Intelligence (IJAMBI) provides a dedicated scholarly platform to advance these objectives. With a multidisciplinary focus, the journal brings together perspectives from management science, artificial intelligence, business analytics, and organizational theory to deepen understanding of how intelligent systems can be designed and applied to enhance human decision-making. IJAMBI supports research that bridges the gap between theoretical frameworks and practical business applications, encouraging contributions that demonstrate both methodological rigor and real-world relevance. Through its editorial standards, the journal promotes reproducibility and ethical responsibility, recognizing the critical role that adaptive systems play in shaping resilient, competitive, and equitable futures.

ISSN2589-0042
Publishing modelOpen Access
Latest IssueJul 26, Vol. 1, Issue 2
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Journal Updates

Call for Papers – International Journal of Adaptive Management and Business Intelligence (IJAMBI)

The International Journal of Adaptive Management and Business Intelligence (IJAMBI) invites submissions for its inaugural issues from researchers, strategists, and practitioners working at the intersection of organizational agility and data-driven insights.

IJAMBI welcomes original research articles, comprehensive review papers, and practice-oriented case studies that present substantive contributions to management theory, analytical methodology, or real-world business implementation.

Scope of Submissions

We invite high-quality submissions, including, but not limited to:

  • Adaptive Management Frameworks: Innovative models for agile leadership, resilient organizational structures, and change management in volatile environments.

  • Business Intelligence & Analytics: Methodological advances in predictive modeling, prescriptive analytics, and data mining for strategic advantage.

  • Decision Support Systems: Design and evaluation of intelligent systems that enhance executive and operational decision-making.

  • Strategic Data Governance: Research on the ethical, legal, and social implications of AI and big data within corporate and public governance.

  • Applied Industry Studies: Case studies demonstrating the deployment and measurable impact of business intelligence solutions in practical settings.

  • Interdisciplinary Insights: Work that bridges management science with machine learning, economics, or behavioral science to solve complex organizational challenges.

  • Critical Reviews: Systematic syntheses that evaluate the current state of adaptive management or emerging trends in business intelligence technology.

Submission Standards

The journal encourages submissions that emphasize methodological clarity, strategic relevance, and reproducibility. Authors should clearly articulate how their work contributes to existing management knowledge or enhances practical organizational intelligence.

Contributions from both academic and industry contexts are highly encouraged, provided they meet scholarly standards and offer verifiable insights.

Submission Details

  • Status: Open for Submissions (Inaugural Issue)

  • Review Model: Double-blind peer review

  • Publication Model: Open Access