Focus And Scope

Statement

International Journal for Applied Information Management is 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. 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

2. 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