Digital transformation is a crucial strategy for enterprises to navigate the digital economy, leading to a growing number of organizations actively engaging in this process. However, the high failure rates in digital transformation initiatives have pushed both academia and industry to identify effective approaches. Key challenges include a lack of relevant knowledge and capabilities as well as the need for coordinated resource utilization. Knowledge is vital for developing new business models, selecting appropriate digital technologies, and strategizing their use; knowledge transfer is a central component of this transformation. To address these challenges, this study reviews the literature on knowledge transfer, dynamic capabilities, and digital transformation and proposes a theoretical model that connects these elements. Empirical research through questionnaire surveys and structural equation modeling reveals that knowledge transfer significantly enhances digital transformation and positively impacts enterprises' ability to perceive, capture, and reconstruct knowledge. These abilities also serve as partial mediators between knowledge transfers and digital transformations. This study innovatively integrates knowledge transfer and digital transformation into a unified model, thereby contributing to the theoretical exploration of digital transformation pathways. Moreover, it enhances the understanding of dynamic capabilities in this context, providing valuable insights and practical implications for Chinese enterprises aiming to improve their digital transformation efforts through effective knowledge transfer and cultivation of dynamic capabilities.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11649124 | PMC |
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0311176 | PLOS |
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