Big data analytics for strategic decision-making across the battery value chain: a review of status, trends, and future directions

Hemmelder, André; Sehnal, Anne; Lux, Simon; Leker, Jens

Zusammenfassung

Batteries are crucial for decarbonising energy storage and mitigating climate change. As the battery industry expands, it faces increasing complexity due to accelerated innovation cycles, rising competition, and growing technological diversity, emphasising the need for cost-effective strategic decision-making across the battery value chain. This systematic review examines studies adopting big data analytics to guide strategic decision-making across the battery value chain, identifies key research trends and contributors, discusses geopolitical dimensions, policy implications, and cross-sectoral competitive perspectives, and highlights relevant research gaps. An AI-assisted search strategy was employed to identify relevant literature. Studies were systematically categorised and analysed using a newly developed conceptual analytical framework within four hierarchical design levels: battery applications, technologies, components, and materials. Research trends were examined using bibliometric data alongside framework parameters. 63 relevant publications were identified and analysed. The review reveals diverse methodological approaches across the battery value chain, with varying analytical sophistication from descriptive statistics to advanced machine learning techniques. Key contributors and geographical contexts were identified, showing concentration in specific regions and institutions. Research trends indicate growing integration of geopolitical considerations and cross-sectoral dynamics. This review provides the first comprehensive synthesis of big data analytics applications for strategic decision-making in the battery sector. Systematic mapping of research objects and analytical approaches reveals critical research gaps, offering orientation for emerging scholars and pointing to future research opportunities at the intersection of battery technology, data science, and strategy. The developed conceptual framework lays a foundation for academic inquiry and practical application in this rapidly evolving field.