Springer Digital Transformation and the World Economy: Critical Factors and Sector-Focused Mathematical Models (Studies on Entrepreneurship, Structural Change and Industrial Dynamics)

Nanotechnology, biotechnology, information technology, and cognitive sciences are contributing to the emergence of intelligent computers and robots with elements of artificial intelligence and intelligent machines. This book postulates that these developments are accelerating the technological substitution of jobs and the shift in labor demand towards high qualification levels, putting the jobs of lower-skilled labor at risk. The digital economy is poised to increase the demand for highly qualified specialists in STEM fields (scientific research, innovative technologies, engineering, and mathematics serving digital technologies). In addition, highly skilled robotics engineers, AI and machine learning specialists, and virtual and augmented reality architects will be required. This book, using sector-focused mathematical models, explores how the demand for specialized human capital will play a decisive role in increasing the efficiency and productivity of labor in the digital economy. Success is guaranteed to those entrepreneurs who manage to establish a successful process of interaction with intelligent machines, which will require a deep restructuring of the training system for the digital economy. From the Back Cover Nanotechnology, biotechnology, information technology, and cognitive sciences are contributing to the emergence of intelligent computers and robots with elements of artificial intelligence and intelligent machines. This book postulates that these developments are accelerating the technological substitution of jobs and the shift in labor demand towards high qualification levels, putting the jobs of lower-skilled labor at risk. The digital economy is poised to increase the demand for highly qualified specialists in STEM fields (scientific research, innovative technologies, engineering, and mathematics serving digital technologies). In addition, highly skilled robotics engineers, AI and machine learning specialists, and virtual and augmented reality architects will be required. This book, using sector-focused mathematical models, explores how the demand for specialized human capital will play a decisive role in increasing the efficiency and productivity of labor in the digital economy. Success is guaranteed to those entrepreneurs who manage to establish a successful process of interaction with intelligent machines, which will require a deep restructuring of the training system for the digital economy. About the Author Andrei Rudskoi is a well-known Russian scientist, a specialist in the field of materials science, digitization of modern industry, and economy. He holds a doctorate in technical sciences, and is professor and academician at the Russian Academy of Sciences. He is the current rector of Peter the Great St. Petersburg Polytechnic University (SPbPU, Russia). Askar Akaev is a well-known scientist in the field of nonlinear optics, dynamics of economic systems, and mathematical modeling of processes of economic dynamics. He is also known for his research in the field of digital transformation of economic systems and methods for assessing the level of economic inequality. He is the chief fellow at the Lomonosov Moscow State University (Russia). Tessaleno Campos Devezas is associate professor with habilitation at Atlântica – Instituto Universitário (Portugal). He is known for his contributions to the long waves theory in socioeconomic development, technological evolution, energy systems, world system analysis, and materials science. His main research interests embrace technological forecasting, futures studies, socioeconomic long waves, evolutionary economics, technological evolution, innovation theory and dynamics, complex adaptive systems, and advanced materials.