Business Analytics and Applications, 2nd Edition

Dear Colleagues,

We are pleased to announce the Special Issue of “Business Analytics and Applications, 2nd Edition”, dedicated to exploring the integration of advanced analytical methods with their ethical and effective implementation in modern business environments.

Topics of interest include, but are not limited to, the following:

1. Next-Generation Methods And Architectures
   • Advanced statistical modeling, machine learning, and deep learning approaches for business analytics.
   • Applications of Generative AI in business analytics, including Retrieval-Augmented Generation (RAG) and knowledge-graph-enhanced decision support.
   • Low-Code/No-Code analytics platforms enabling faster deployment and democratization of analytical tools.
   • Multi-agent collaborative systems for complex problem-solving and workflow optimization
   • Cloud and hybrid architectures for advanced analytics.
2. Ethical AI, Governance And Trust
   • Fairness-aware modeling and bias mitigation in statistical, machine learning, and deep learning systems.
   • Explainable AI (XAI) techniques for interpretable business analytics models.
   • Cultural and political bias in generative AI systems and their implications for analytical outcomes.
   • Ethical reasoning frameworks for generative AI in business analytics.
   • Cognitive biases in analytical prompts and their effects on decision quality.
   • Data governance and protection across analytics pipelines.
   • Privacy-preserving and federated analytics for secure cross-organizational collaboration.
   • Vulnerability assessment and mitigation strategies in analytical systems.
3. Organizational Adoption And Impact
   • Human-AI collaboration in decision-making and hybrid intelligence systems.
   • Analytics capability maturity models and organizational assessment frameworks.
   • Automation-driven evolution of skill requirements in analytics teams.
   • Upskilling and continuous learning to strengthen analytical literacy and ethical competence.
   • Socio-psychological factors influencing business analytics integration.
   • Value creation mechanisms linking analytical investments to business outcomes.
   • AI-augmented knowledge work and its impact on creativity, productivity, and collaboration.

We welcome original research, case studies, and review articles that contribute to advancing the theory and practice of business analytics in these areas.

We look forward to your valuable contributions.

Prof. Dr. Tatiana Ermakova
Guest Editor

Manuscript Submission Information

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