This study examines how Business Intelligence (BI) is conceptualised, adopted, and implemented within Small and Medium-sized Enterprises (SMEs), a context where digital transformation is essential yet insufficiently explored. Although BI is widely recognised as a strategic driver of informed decision-making and competitiveness, existing research remains fragmented and often sector-specific. Using a hybrid methodology that combines bibliometric analysis with a qualitative systematic literature review from 2015 to 2024, the study traces a shift from early semantic and dashboard-driven models to cloud-based, predictive solutions. It also identifies key limitations and proposes future research on empirical validation, adaptable governance, and innovation-resource trade-offs.

Business Intelligence for SMEs: a hybrid review of models, barriers, and future directions

Tafuro, Alessandra;Colamartino, Chiara;Toma, Pierluigi
2026-01-01

Abstract

This study examines how Business Intelligence (BI) is conceptualised, adopted, and implemented within Small and Medium-sized Enterprises (SMEs), a context where digital transformation is essential yet insufficiently explored. Although BI is widely recognised as a strategic driver of informed decision-making and competitiveness, existing research remains fragmented and often sector-specific. Using a hybrid methodology that combines bibliometric analysis with a qualitative systematic literature review from 2015 to 2024, the study traces a shift from early semantic and dashboard-driven models to cloud-based, predictive solutions. It also identifies key limitations and proposes future research on empirical validation, adaptable governance, and innovation-resource trade-offs.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11587/567786
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