MODELING THE IMPACT OF INDUSTRY 4.0 TECHNOLOGIES ON THE INNOVATIVE DEVELOPMENT OF INDUSTRIAL ENTERPRISES

The article is devoted to modeling the relationship between investments in the latest Industry 4.0 technologies and the productivity of industrial enterprises. The relevance of the topic is driven by the need to better understand the mechanisms that determine the impact of innovation on economic performance, as well as the need to develop effective policies to stimulate innovation. The modeling is based on data from 150 large industrial companies in the EU. For our analysis, we use a modified econometric CDM model that estimates the relationship between R&D expenditures and productivity. The methodology of applying the structural CDM model allows us to take into account key methodological aspects, in particular, problems with sample and time (simultaneity) bias. This model includes three stages of estimation of a structural econometric model: decisionmaking on R&D investments, knowledge production process, and economic efficiency assessment. At the first stage of modeling, it was found that the growth of industrial enterprises' productivity and their transformation are most influenced by Industry 4.0 technologies. The consequences of the introduction of new technologies on the financial, operational, innovative and technological development of enterprises are determined. The second stage of the study analyzes the relationship between investments in Industry 4.0 technologies, patterns of innovative behavior and productivity of industrial companies using a modified CDM model. The application of this model helps to assess the impact of R&D investments on the intensity of innovation and, ultimately, on labor productivity. The results of the study confirm that innovatively active enterprises have a higher chance of increasing labor productivity, and the impact of innovation activity varies by age. Based on the results of the study, five stylized facts (empirical regularities) were formed that highlight the key factors that influence innovation activity: the positive impact of the size and age of the enterprise, the importance of the competitive environment, the importance of employee qualifications and professional development, the role of investment in information technology, and the significant impact of innovation on labor productivity growth. The practical value of the study lies in the provision of sound empirical data that can be used to formulate innovation policy, in particular in creating conditions for access to financial resources, supporting professional development and stimulating the introduction of the latest Industry 4.0 technologies.