Assessing Adoption Archetypes of Advanced Technologies in Industrial Clusters

The effective adoption of advanced Industry 4.0 (I4.0) technologies is a crucial research area. While some authors propose readiness or maturity models to analyze the level of adoption of I4.0 technologies, others examine their impact on company performance. However, there is a dearth of studies offering evidence on the implementation patterns of I4.0 technologies in general, and the adoption of advanced technologies related to artificial neural networks, deep learning, and computational intelligence, in particular, within various manufacturing clusters. This gap has prompted working hypotheses to investigate the current implementation and adoption patterns, as well as the degree of adoption or stage of maturity of these technologies in industrial clusters. This paper proposes a qualitative-quantitative study to determine the degree of adoption of advanced I4.0 technologies. It aims to develop an analysis that describes the archetypes characterizing the implementation patterns of I4.0 technologies and the adoption of advanced technologies related to machine learning applications in Argentinian clusters.