The Linkage Between Digital Transformation and Organizational Culture: Novel Machine Learning Literature Review Based on Latent Dirichlet Allocation

Tobias Reisberger (), Philip Reisberger (), Lukáš Copuš (), Peter Madzík () and Lukáš Falát ()
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Tobias Reisberger: Comenius University Bratislava
Philip Reisberger: Comenius University Bratislava
Lukáš Copuš: Comenius University Bratislava
Peter Madzík: Comenius University Bratislava
Lukáš Falát: University of Žilina

Journal of the Knowledge Economy, 2025, vol. 16, issue 1, No 73, 2082-2118

Abstract: Abstract Organizational culture is a crucial component of innovation in company success, particularly in the setting of the information economy. The purpose of this research is to conduct a bibliometric analysis in order to identify dominant research topics, their potential shifts, and recent developments in the fields of organizational culture and digital transformation. It demonstrates a machine learning–supported method for identifying and segmenting the current state of this research field. The literature was identified from the Scopus database through a search query. The analyzed amount of papers (3065) was published in 1619 sources (journals, proceedings, books, etc.) with various research impacts. Identifying the dominant research topics resulted in eight topics: Social Media Connectivity; Digital Innovation Ecosystems; Socio-economic Sustainability; Digital Workforce Transformation; Digital Competence and Cultural Transformation; Knowledge, Culture, and Innovation; Data and Resource Management; and Digital Transformation Maturity. The results showed a shift in the research field on organizational culture related to digital transformation towards the subject area of business, management, and accounting, with increasing research interest and impact for the Digital Workforce Transformation as well as for the Knowledge, Culture, and Innovation topics.

Keywords: Organizational culture; Digital transformation; Industry 4.0; Machine learning; Latent Dirichlet allocation; Literature review (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s13132-024-02027-3

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