A diverse and international author and reviewer network
Real-World Impact
Research that advances theory and practice
Int. J. Adapt. Manag. Bus. Intell.
A global platform for research at the intersection of intelligent systems and data science.
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.
Publisher: Who Supports This Journal?
The International Journal of Adaptive Management and Business Intelligence (IJAMBI) is published and supported by Femington, an independent academic publishing organization committed to advancing open, ethical, and high-quality scholarly communication. The journal is maintained using the Open Journal Systems (OJS) platform, an open-source publishing infrastructure widely adopted by academic institutions and journals worldwide.
By leveraging OJS, Femington ensures that IJAMBI operates on transparent, community-driven, and sustainable publishing principles. This enables efficient manuscript management, rigorous peer review, and long-term digital preservation, reinforcing the journal’s commitment to accessibility and academic integrity.
IJAMBI aims to make academic research available:
Online
Immediately upon publication
Free from most copyright or licensing restrictions
Accepted Types of Articles
IJAMBI considers the following categories of scholarly contributions:
Original Research / Research Articles:
Substantial and novel contributions presenting original theoretical developments in management, methodological innovations in business intelligence, or empirical analyses of adaptive systems. (6,000–8,000 words).
Review Articles:
Critical synthesis of existing research. This includes Critical Reviews of management literature, Systematic Reviews of business analytics trends, or Meta-Analyses of organizational performance data. (6,000–8,000 words).
Case Studies:
In-depth examinations of real-world implementations of adaptive management or BI solutions in corporate, governmental, or non-profit settings. (3,000–4,000 words).
Research Notes:
Concise manuscripts presenting preliminary findings, novel datasets, or emerging methodological ideas in business intelligence that warrant rapid communication. (2,000–3,000 words).
Editorials:
Commissioned pieces addressing topical issues or strategic directions relevant to adaptive management.
Aims and Scope
The rapid advancement of business intelligence and the increasing volatility of global markets have transformed organizational decision-making. These changes introduce critical challenges related to scalability, strategic robustness, and the ethical responsibility of automated and human-led systems.
The International Journal of Adaptive Management and Business Intelligence (IJAMBI) seeks to address these challenges by publishing research that advances the theoretical foundations and applied practices of intelligent management systems. The journal aims to foster innovation while encouraging critical reflection on the reliability and accountability of data-driven governance.
Principal areas covered include, but are not limited to:
Adaptive Management:
Agile leadership, change management, and resilient organizational architectures.
Business Intelligence & Analytics:
Predictive and prescriptive analytics, data mining for market insights, and real-time dashboarding.
Strategic Decision Support:
Recommender systems for executive decision-making and automated workflow optimization.
Data Governance & Ethics:
Privacy, transparency, and ethical AI in corporate environments.
Big Data in Management:
Scalable analytics and knowledge discovery in large-scale enterprises.
Interdisciplinary Applications:
BI in healthcare management, digital transformation in the public sector, and sustainable business models.
Benefits to Authors
All articles published in IJAMBI are fully open access. Key benefits include:
Flexible publication fees to ensure global inclusivity
Rigorous double-blind peer-review process
3143-7176ISSN
3 daysSubmission to first decision (median)
Continuous PublishingFrequency
CC BY 4.0License
Editorial Masthead
The International Journal of Adaptive Management and Business Intelligence (IJAMBI) is guided by an international editorial team comprising leading scholars and professionals in management science, business analytics, artificial intelligence, and strategic decision-making. Members of the editorial board contribute their expertise to uphold the journal’s academic integrity, editorial independence, and high standards of rigorous peer review.
Editorial decisions at IJAMBI are made independently and without bias. The journal applies consistent and transparent criteria across all submissions, ensuring fairness and scholarly quality, whether the research is focused on theoretical management frameworks or applied business intelligence technologies. Our team works closely with reviewers to maintain an ethical, efficient, and constructive review process that adds value to the author's work.
In recognition of the vital service provided by our academic community, Femington formally acknowledges editorial and reviewer contributions through journal communications, annual reports, and public statements. This reflects IJAMBI’s commitment to fostering a collaborative environment for academic service and professional engagement.
Meet Our Editorial Team
Balaji Natarajan is a Program Management Leader with over 24 years of experience in engineering, product development, and global project delivery across the mobility and industrial sectors. A PMP-certified professional, he has led multidisciplinary teams and managed complex engineering programs in both India and the United States. His expertise includes new product development, manufacturing engineering, product lifecycle management, and engineering change management.
Throughout his career at L&T Technology Services, Balaji has directed cross-functional engineering initiatives, overseen global product development programs, and driven cost optimization, quality improvement, and production scale-up for international clients. His interests include adaptive project management, smart manufacturing, product innovation, and business transformation through engineering excellence.
Balaji Natarajan is a Program Management Leader with over 24 years of experience in engineering, product development, and global project delivery across the mobility and industrial sectors. A PMP-certified professional, he has led multidisciplinary teams and managed complex engineering programs in both India and the United States. His expertise includes new product development, manufacturing engineering, product lifecycle management, and engineering change management.
Throughout his career at L&T Technology Services, Balaji has directed cross-functional engineering initiatives, overseen global product development programs, and driven cost optimization, quality improvement, and production scale-up for international clients. His interests include adaptive project management, smart manufacturing, product innovation, and business transformation through engineering excellence.
Krutika Shah is a Lead .NET Developer and Technical Project Leader with over nine years of experience delivering enterprise software solutions, cloud platforms, and digital transformation initiatives across healthcare and business technology domains. Her expertise includes software architecture, project management, Agile delivery, cloud technologies, and enterprise information systems.
Holding an MBA in Project Management, she combines technical leadership with strong organizational and strategic expertise. Her professional interests include enterprise systems, business process optimization, digital transformation, and technology-driven decision support, contributing to the advancement of adaptive management and business intelligence.
Krutika Shah is a Lead .NET Developer and Technical Project Leader with over nine years of experience delivering enterprise software solutions, cloud platforms, and digital transformation initiatives across healthcare and business technology domains. Her expertise includes software architecture, project management, Agile delivery, cloud technologies, and enterprise information systems.
Holding an MBA in Project Management, she combines technical leadership with strong organizational and strategic expertise. Her professional interests include enterprise systems, business process optimization, digital transformation, and technology-driven decision support, contributing to the advancement of adaptive management and business intelligence.
Yagnesh Ahir is a management and research-focused professional with extensive experience in research analysis, data review, compliance reporting, and organizational operations. He holds a Bachelor of Science in Business Administration with a major in Management and has professional experience with organizations including Refinitiv (Thomson Reuters) and The Red Flag Group.
His work has involved conducting structured research, analyzing data, preparing reports, performing information screening, and supporting teams in delivering accurate analytical outcomes. He has also trained and mentored new team members while supporting client-facing operations. His combination of management education, analytical expertise, and professional experience contributes to effective editorial evaluation and scholarly development.
Yagnesh Ahir is a management and research-focused professional with extensive experience in research analysis, data review, compliance reporting, and organizational operations. He holds a Bachelor of Science in Business Administration with a major in Management and has professional experience with organizations including Refinitiv (Thomson Reuters) and The Red Flag Group.
His work has involved conducting structured research, analyzing data, preparing reports, performing information screening, and supporting teams in delivering accurate analytical outcomes. He has also trained and mentored new team members while supporting client-facing operations. His combination of management education, analytical expertise, and professional experience contributes to effective editorial evaluation and scholarly development.
Ganga Raju Vemula is a Civil and Water Engineering Specialist with over 15 years of experience in large-scale water infrastructure, hydraulic systems, and flood management. His expertise spans the full project lifecycle, covering detailed structural design, multidisciplinary coordination, construction management, and regulatory compliance.
Holding a PMP certification and an MSc in Construction Management with First Class Honours from Nottingham Trent University, he integrates technical engineering with strategic project leadership. His work focuses on fluid dynamics, pipeline optimization, and structural health monitoring, advancing resilient civil infrastructure and sustainable water resource management.
Ganga Raju Vemula is a Civil and Water Engineering Specialist with over 15 years of experience in large-scale water infrastructure, hydraulic systems, and flood management. His expertise spans the full project lifecycle, covering detailed structural design, multidisciplinary coordination, construction management, and regulatory compliance.
Holding a PMP certification and an MSc in Construction Management with First Class Honours from Nottingham Trent University, he integrates technical engineering with strategic project leadership. His work focuses on fluid dynamics, pipeline optimization, and structural health monitoring, advancing resilient civil infrastructure and sustainable water resource management.
As organizations increasingly use machine learning in business process management, the need for transparent predictive models becomes critical. Predictive process monitoring (PPM) techniques deliver accurate forecasts of process outcomes
This paper discusses how business analytics capabilities can lead to innovation in digital commerce firms by turning data into actionable insights for strategic and operational decisions. By relying on secondary evidence published in articles, the findings analyze the use of descriptive, predictive, and
This paper explores the application of learning analytics in online educational environments to derive actionable insights from student-teacher interactions and digital learning activities. The proposed approach systematically utilizes techniques of data warehousing and data mining to collect, organize, process and analyze educational data generated by virtual learning
Bhargavi Ugandhar
September 2026 · Vol. 1 · Issue 3
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