Focus And Scope

Statement

International Journal for Applied Information Management is a multidisciplinary, an open-access, internationally single-blind peer-reviewed journal which is not limited to a specific aspect of science and information but is instead devoted to a wide range of subfields in information management topics. While it encourages a broad spectrum of contribution in information management. Articles of interdisciplinary nature are particularly welcome..

Publishing Schedule

IJAIM has been publishing four issues per year (quarterly) since 2021. The exact schedule of publication for each issue is as the following:

  1. April
  2. July
  3. September
  4. December

Aim

The principal concern of the “International Journal for Applied Information Management” (IJAIM) is to review and document significant developments in the fields of science and information management that have the potential to shape future directions. IJAIM is an internationally recognized, peer-reviewed scholarly journal dedicated to promoting the advancement of knowledge across scientific, technological, legal, socio-economic, and policy dimensions of information management. IJAIM serves as a platform for the dissemination of high-quality research articles, which can be utilized for further research, educational purposes, and practical applications by students, researchers, academics, and industry professionals. The journal addresses the increasing demand for experts, engineers, technocrats, and policymakers who can effectively apply best management practices derived from various interdisciplinary fields to create a sustainable future.

Scope

The journal scopes include (but not limited to) the following topics:

1. Information Management & Governance

  • Digital information lifecycle management

  • Data governance and stewardship models

  • Metadata frameworks and knowledge graphs

  • Ethical and legal aspects of information systems (e.g., GDPR, CCPA)

  • Information systems for smart cities and e-government

2. Data Science & Analytics

  • Data integration and wrangling in heterogeneous environments

  • Scalable data pipelines and real-time analytics

  • Feature engineering and dimensionality reduction

  • Predictive and prescriptive analytics

  • Evaluation frameworks for data-driven decision-making

3. Artificial Intelligence & Machine Learning Applications

  • Machine learning and deep learning models in applied domains

  • Explainable AI (XAI) for high-stakes decisions

  • Natural Language Processing (NLP) for public services and policy modeling

  • AI for anomaly detection in IoT and cyber-physical systems

  • Computer vision for operational automation

4. Applied Enterprise and Sectoral Solutions

  • Data mesh and decentralized analytics in enterprises

  • AI-driven transformation in healthcare, agriculture, and logistics

  • Real-time edge AI systems for supply chain and environmental monitoring

  • AI-powered dashboards for public transparency and citizen engagement

  • Cross-border and post-merger data harmonization strategies

5. Ethical, Responsible, and Sustainable AI

  • Bias detection and fairness in AI models

  • Auditable AI systems and algorithmic transparency

  • Societal impact of automated decision systems

  • Sustainability and energy-efficiency in AI deployment

  • Participatory modeling and citizen-in-the-loop AI