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- Factors that impact digital transformation : an analysis using machine learning and literature reviewPublication . Melo, Francisco Betti Teixeira e; Ribeiro, Rita Moura Bastos de AlmeidaDigital transformation (DT) has become a critical topic for both academic research and organizational strategy, as it reshapes how businesses operate, compete, and create value. It represents a profound shift that impacts structures, processes, and decision-making across all sectors. This study aims to identify and validate the key factors that influence digital transformation processes within organizations. To achieve this, a dual-method approach was adopted: a traditional literature review and the application of Latent Dirichlet Allocation (LDA) to a corpus of 6,669 abstracts extracted from the Scopus database. The literature review identified eight principal factors impacting DT, while the LDA model generated 30 topics, of which 11 were interpreted as corresponding to DT impact factors. The comparison revealed substantial alignment between literature-based and data-driven factors, reinforcing their relevance. Additionally, the LDA model uncovered four emergent factors not captured in the initial literature analysis, reflecting evolving dimensions of DT. This study contributes both methodologically and practically: it demonstrates that hybrid approaches combining literature and unsupervised topic modeling can validate and expand knowledge on DT factors, while also revealing emerging concerns. For business leaders, executives, and strategic decision-makers, the findings provide concrete guidance on which factors should be prioritized when planning or executing digital transformation efforts. For researchers, this work opens new possibilities for combining interpretative and data-driven methods to better understand the complexity and evolution of digital transformation.