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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