The Dynamics of Knowledge Growth in Business Intelligence and Analytics: A Bibliometric Investigation
Date Issued
2025-08
Author(s)
Nartnik, Tina
Jaklic, Jurij
Savic, Gordana
Abstract
Business Intelligence and Analytics (BI&A) has emerged over the last thirty years
as a vital domain for driving organizational performance, digital transformation,
and competitive advantage. As the field continues to expand rapidly, especially
with the rise of AI-augmented analytics, understanding the structure and direction
of existing research becomes critical. Without a clear map of intellectual progress
and thematic shifts, both academic and practical efforts risk becoming disconnected
and misaligned.
This study provides a systematic bibliometric investigation of the evolution of
knowledge within Business Intelligence and Analytics. The motivation behind this
analysis is to bring clarity to a complex and growing body of literature and to
identify strategic pathways that can inform future research, innovation, and
practice. By uncovering the foundations, trends, and turning points in the field, we
support a more informed and impactful development of analytics strategies across
sectors.
We examine a dataset of 2,361 peer-reviewed articles indexed in Scopus,
applying a combination of citation network analysis, bibliographic coupling, co
authorship exploration, and keyword co-occurrence mapping. Following the PRISMA guidelines and employing advanced text mining, we extract key thematic
clusters and trace the emergence of influential research streams.
The results reveal a strong progression from early technical focus to more
integrated, strategic, and domain-specific applications. This transition highlights
the importance of cross-disciplinary collaboration and the alignment of analytics
with real-world business needs. By capturing the dynamic evolution of BI and
Analytics, this study offers a robust foundation for scholars, industry leaders, and
policymakers to align academic inquiry with technological advancement and
organizational priorities.
as a vital domain for driving organizational performance, digital transformation,
and competitive advantage. As the field continues to expand rapidly, especially
with the rise of AI-augmented analytics, understanding the structure and direction
of existing research becomes critical. Without a clear map of intellectual progress
and thematic shifts, both academic and practical efforts risk becoming disconnected
and misaligned.
This study provides a systematic bibliometric investigation of the evolution of
knowledge within Business Intelligence and Analytics. The motivation behind this
analysis is to bring clarity to a complex and growing body of literature and to
identify strategic pathways that can inform future research, innovation, and
practice. By uncovering the foundations, trends, and turning points in the field, we
support a more informed and impactful development of analytics strategies across
sectors.
We examine a dataset of 2,361 peer-reviewed articles indexed in Scopus,
applying a combination of citation network analysis, bibliographic coupling, co
authorship exploration, and keyword co-occurrence mapping. Following the PRISMA guidelines and employing advanced text mining, we extract key thematic
clusters and trace the emergence of influential research streams.
The results reveal a strong progression from early technical focus to more
integrated, strategic, and domain-specific applications. This transition highlights
the importance of cross-disciplinary collaboration and the alignment of analytics
with real-world business needs. By capturing the dynamic evolution of BI and
Analytics, this study offers a robust foundation for scholars, industry leaders, and
policymakers to align academic inquiry with technological advancement and
organizational priorities.
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