The evolution of technologies is driven by science that is often viewed as a self-organizing system having over time various scientific change associated with the development of economies and societies (Sun et al., 2013). Scholars maintain that the evolution of technologies is driven by the interaction between inter-related technological systems and scientific fields that generate co-evolutionary pathways of scientific and technological change (Jovanovic et al., 2021). Cloud computing technology has many characteristics of general-purpose technologies (GPTs) because it has the potential to sustain industrial, economic and social change (Bresnahan, 2010; Sahal, 1981). The technological aspects of GPT are basic to analyze and explain the evolution of cloud computing technology, and some brief background is useful to understand and clarify this vital concept for technology analysis here. GPTs are enabling technologies that support clusters of new products and processes (Helpman, 1998, p.3; Coccia, 2020). Lipsey et al. (1998, p.43) define a GPT as: “a technology that initially has much scope for improvement and eventually comes to be widely used, to have many users and to have many Hicksian and technological complementarities”. GPTs are characterized by: “pervasiveness, inherent potential for technical improvements and ‘innovational complementarities’, giving rise to increasing returns-to-scale, such as steam engine, electric motor, and semiconductors” (Bresnahan and Trajtenberg, 1995, p.83). Jovanovic and Rousseau (2005, p.1185) show the distinguishing characteristics of a GPT:
1 Pervasiveness: GPT should propagate to many sectors
2 Improvement: GPT should reduce costs of its adopters
3 Innovation spawning: GPT should produce new products and processes (cf. also, Bresnahan and Trajtenberg, 1995).
Lipsey et al. (1998, p.38ff) describe other similar characteristics of GPTs, such as: the scope for improvement, wide variety, and range of uses and strong complementarities with existing or new technologies (cf., Coccia, 2020). Another feature of GPTs is a long-run period between their initial research in science, the emergence as invention and therefore final introduction in new products/processes having a societal impact (Lipsey et al., 1998, 2005). Rosegger (1980, p.198) showed that the estimated time interval between invention and major innovation can be about 50 years: e.g., for electric motor is about 58 years, electric arc lights 50 years, telegraph about 44 years, synthetic resins 52 years, etc. GPTs support new architecture of various families of products/processes. In fact, GPTs can affect with different technological trajectories almost every branch of the economy (Freeman and Soete, 1987, pp.56–57; Bresnahan and Trajtenberg, 1995, p.8; Hall and Rosenberg, 2010). Coccia (2005, pp.123–124) claims, referring to revolutionary innovations, such as GPTs that:
The means of human communication are radically changed and a new means of communication, which heavily affects all the economic subjects and objects, is born, forcing all those who use it to change their habits. A new technoeconomic paradigm is born… The propulsive capacity for development offered by seventh-degree innovation is so high that it hauls the entire economy. Thanks to the new methods of communication, there is also greater territorial, social, and human integration. Another characteristic of seventh-degree innovations is the ease of their spread. The mobility of people, goods, capital, and information increases, and the time taken to travel and communicate is reduced.
Overall, then, GPTs are complex technologies that support product/process innovations in several sectors for a corporate, industrial, economic, and social change (Coccia, 2020). The characteristics of GPTs can help the explanation of scientific and technological development of cloud computing research and technology. Especially, the technology analysis of new trajectories of cloud computing technology is essential to predict new applications in markets for technological, economic and social change (Nelson, 2008, p.489). The cloud computing technology as a complex technology can generate "certain meta-evolutionary processes involving a combination of two or more symbiotic technologies" (Sahal, 1985, p.70). Sahal (1985, p.79, original emphasis) also maintains that technological evolution is due generic innovation avenues that: “the emergence of a new innovation avenue through fusion of two or more avenues or through fission of an existing avenue can give rise to sudden changes in the mode and tempo of technical progress”. The goal of investigating here technological trajectories of cloud computing technology and research is important to clarify the long-run evolution of this technology based on the behavior and evolution of different inter-related technologies. Hence, the detection of new directions of research fields and technology in cloud computing can provide main characteristics to understand future evolutionary paths in science and society (Deshmukh and Mulay, 2021). In this context, the study here analyzes publications that are a main unit of scientific and technology analysis of cloud computing technology to show how technological trajectories evolve over time (Boyack et al., 2009). As matter of fact, quantitative approaches based on bibliometric data of journals are useful techniques to capture information earlier in the cycle of technology development, whereas patents, in contrast, trail behind (Cozzens et al., 2010; Ding et al., 2000). In this research stream, the study here, based on a theoretical background of GPTs and using statistical analyses on publications and patens, has the purpose of detecting technological technologies in cloud computing directed to path-breaking applications in future markets. The idea here is to analyze the evolution of cloud computing by examining new technological trajectories that are basic in science, technology, and society to explain the evolution of this technology and support strategic management of policymakers for R&D investments towards research fields and technologies having a high potential of growth and positive societal impact. Next section presents the methods of this scientific investigation.