Quantitative Conceptual Mapping of Knowledge Management and Digital Transformation Literature

Digital transformation and new technologies offer companies a unique opportunity to tap into new revenue streams while increasing value creation. Through targeted investments in digital and knowledge management, it is possible to develop new sources of income and expand their business. Digitizing knowledge, for example, makes it easier for a company's employees to access information. In addition, individuals can use technology to share and control the information they have access to. The development of innovations and the improvement of business models will benefit all stakeholders so that everyone can benefit from the digital revolution. In this framework, we conduct a bibliometric study of the digital transformation literature and identify the factors that influence the success of a digital transformation project. In this work, we have considered a query: "knowledge management", assets, and "digital transformation", where The scientific production considered covers scientific articles from 2005 to 2022. Methodologically speaking, we combine two different separate statistical analyses from the construction of the bibliometric database. First, we considered a multivariate analysis using multiple correspondence analysis; then, we used cluster analysis to identify the relevant groups of keywords in the literature. In this respect, the performed exploratory multiple correspondence analysis aims to visualize on a two-dimensional map the significant keywords from the articles which can be considered in this scientific literature. We uncover the most significant relationships between the most relevant terms from the subsequently published literature. We repeated the complete bibliometric analysis to evaluate the sensitivity of the results by using different terms than the previous study. More specifically, from the second bibliometric analysis, we analyze the robustness of the results obtained in the study performed by considering slightly different terms valid to discover relevant issues related to the use of similar keywords on the queries (digital "change" instead of digital "transformation" for instance). Throughout this research, it is possible to discover the different clusters of ideas associated with the basic conceptual groupings that characterized the literature. Therefore, it is necessary to perform a cluster analysis to understand the critical needs for digital transformation and the links between these needs and knowledge management and digitization. Overall, we emphasize the importance of intellectual capital in the digital transformation process, as higher intellectual capital leads to better use of resources.