Researchers demonstrate the potential of big data analytics for strategic decisions in the battery sector

New Study Reveals Potential of Big Data Analytics for Strategic Decision-Making in the Battery Industry / Researchers identify trends and research gaps / Systematic analysis uncovers growing importance of geopolitical factors

The battery industry faces enormous challenges: accelerated innovation cycles, intensified competition, and growing technological diversity require cost-effective strategic decision-making across the entire battery value chain. A research team from the Institute for Business Administration at the University of Münster has now conducted a comprehensive study examining how big data analytics can support strategic decision-making processes in the battery industry.

The scientists systematically analyzed 63 relevant publications and developed a novel conceptual framework encompassing four hierarchical design levels: battery applications, technologies, components, and materials. The study reveals remarkable diversity in methodological approaches – from descriptive statistics to advanced machine learning techniques.

This study provides the first comprehensive synthesis of big data analytics applications for strategic decision-making in the battery sector. The systematic mapping of research objects and analytical approaches reveals critical research gaps and points to future research opportunities at the intersection of battery technology, data science, and strategy.

Particularly striking is the growing integration of geopolitical considerations and cross-sectoral dynamics in research. The analysis shows a concentration of research activities in specific regions and institutions, providing important insights for the strategic positioning of various stakeholders.

The developed conceptual framework lays the foundation for both academic inquiry and practical applications in this rapidly evolving field. The researchers emphasize that their findings offer guidance for emerging scholars and highlight new research directions.

Link to original publication: https://doi.org/10.1016/j.esr.2025.101797