Studies in technological innovation systems (TIS) have made significant progress in explaining the dynamics of industry formation for emerging technologies, recognizing that learning is an interactive process. Recent literature suggests that knowledge development and diffusion among different sectors can play a role in the establishment of a TIS. However, we lack an understanding of how the characteristics of different sectors involved in a TIS influence inter-sectoral learning, i.e. purposive learning-by-interacting between different sectors involved in a TIS. To address this gap, we examine how patterns of inter-sectoral learning vary across three TISs – solar photovoltaic systems, wind turbines, and lithium-ion batteries. Using concepts from the literature on sectoral systems of innovation, we show that the characteristics of the different sectors involved in the TIS influence patterns of inter-sectoral learning. Thus, we provide a systematic way of explaining differences in the importance of learning-by-interacting between different technologies observed in the empirical literature, helping policymakers anticipate potential failures in inter-sectoral learning, and we suggest measures to address them. We also demonstrate the value of explicitly analyzing the sectoral configuration in future TIS analyses, and hence contribute to more closely integrating the literatures on TIS and sectoral systems of innovation.

Introduction

Technological innovation has often been identified as a necessary part of any solution to address societal grand challenges such as climate change, water resource management, healthcare, and food security, while maintaining economic growth (Foray et al., 2012; Kuhlmann and Rip, 2018). Thus, several scholars have argued for a “mission-oriented” approach to supporting innovation in specific technologies in a targeted manner (Mazzucato and Perez, 2015; Wesseling and Edquist, 2018). In practice, several countries have set ambitious targets for deployment of clean energy technologies combined with industrial and innovation policies, with varying degrees of success (Anadón, 2012; Lewis and Wiser, 2007; Nemet, 2009; Peters et al., 2012; Taylor, 2008). To explain this variation, studies in technological innovation systems (TISs) have made significant progress in explaining the dynamics of industry formation for emerging technologies. At its core, the literature on innovation systems recognizes that “learning is predominantly an interactive, and therefore, a socially embedded process” (Lundvall, 2010, p. 1), taking place in networks of actors that interact under a particular institutional infrastructure (Binz et al., 2014; Gallagher et al., 2012; Lewis, 2007; Lundvall, 1985).1 Because of the systemic nature of innovation, the addressal of system failures2 plays an important role in strengthening key functions of innovation systems (Bergek et al., 2008; Weber and Rohracher, 2012; Negro et al., 2012).