The role of knowledge diffusion and incremental innovations in the emergence of path-dependent processes underlying socio-technical transitions are focal to the ideas of technological paradigms and technological trajectories (Dosi, 1982). Dosi defines a technological paradigm as a pattern of seeking solutions for technological problems, and proposes that the usual path of knowledge development is very selective in terms of the technical frameworks are taken by innovative firms. This leads to the fact that from all possible directions technological development, only a small portion is realized. In this sense, the term paradigm is often used to describe the first general selection made from all possible research directions in a path dependent and cumulative process (Verspagen, 2007).
Thus, a technological paradigm dominating the path of techno-economic developments for a long time is set out of a small number of innovative ideas and technological solutions. Along with the paradigm, incremental innovations create variations, although the main direction is limited by the main path or paradigm. In other words, there is some space for choices along with the main path, and these choices are governed by specific circumstances in which the technology develops (Dosi, 1982). These variations are called trajectories of technology, innovation or knowledge diffusion, based on the maturity of the system or the focus of observation. As a result, the concept of variety is crucial for describing the trajectories as the sets of branching and merging technologies (Frenken et al., 1999).
While looking at the inner dynamics of the main path and different trajectories, the main interest is not the commercial applications, but to map the technological interconnectedness (Perez, 2009). In fact, the notion of trajectories considers
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technological innovations as sequential and interrelated events (Liu et al., 2008), and suggests within the network of interconnected ideas and innovations, a few main streams or main paths of knowledge exists that summarize the major developments in the field. In this respect, the main path of the network corresponds to the primary flow of ideas.
This main flow of ideas has a degree of selectivity over the main path, in the sense what emerges as the primary stream of ideas is focused on a limited portion of technology space, and other technological solutions and innovations, although might be searched and tested, do not have a substantial contribution to the main stream (Verspagen, 2007). One way to operationalize this idea is to investigate whether the main activities or streams of knowledge are converging to a limited set of innovations in a path-dependent process or wandering in a non-convergent way. Furthermore, the selectivity of the main path can be studied by analyzing the extent the new activities or innovative firms grasp to the main trajectory of knowledge or start forming new trajectories.
Apart from selectivity, the second important concept in analyzing the main path is cumulativeness, which leads to path dependency of the activities and trajectories. However, due to uncertainties of innovative activities, as well as coevolution with economic and social factors, one can expect to see some direction change in trajectories and variations in the main path. It leads to occasional splitting of the main path, along with convergence or fusion of separate trajectories. This mix of persistence and exploration of new directions is a critical factor in generating and exploiting innovations. It is also an important factor for analyzing the early years of development of a new technological system, where the path-dependency is not very high and there is the possibility of changing or redirecting the main path of knowledge development.
Path-dependency of incremental innovation processes in a complex socio-technical system implies that small differences between different alternatives or the trajectories of development of the innovation system can lead to completely different solutions in the future states of the system. Therefore, understanding these possible trajectories is important for the formulation and implementation of possible scenarios to maintain the level of competition in the innovation ecosystem as well as preventing the rapid
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convergence to suboptimal solutions, a problem called ‘early lock-in’ (Faber and Frenken, 2009).
This is the aim of this paper to formalize the notions of selectivity, cumulativeness and path-dependency in a method to investigate the main streams of knowledge in an emerging technological system. This study proposes to use the network of research projects for main path and trajectory analysis. The particular case of smart grid development is studied and Research and Development (R&D) projects are used to map the link between innovations in this field.
The rest of this paper is structured as follows. In §4.3, the proposed methodology and data used in this paper are explained. First, a hybrid model of random and preferential attachment networks is presented to verify the existence of a main path (§4.3.1), followed by a social network analysis of the network of projects for finding the main path of knowledge development and the knowledge diffusion trajectories (§4.3.2). Then, the context of this research is presented (§4.3.3); where the database used is briefly presented. §4.4 presents the results and explains the main projects in each trajectory. §4.5 discusses some possible explanations of the emerging trajectories and implications for policy makers. §4.6 concludes.