DOE OSTI2019
An enduring puzzle in the US solar industry is that despite substantial reductions in the cost of photovoltaic hardware, soft costs (defined here as all costs not directly driven by hardware) have not done the same (US DOE, 2012). In fact, soft costs now account for the majority of the cost of total cost of installed solar systems, despite decades of efforts by firms and policy-makers to reduce these costs. In this study, we address two questions: a) what drives soft costs within the US solar industry, and b) how do firms gain the knowledge required to address these costs? We address this question through an explorative inductive multiple-case study (e.g., Eisenhardt, 1989; Appleyard, 1996). Our sample consists of 15 actors from across various roles within the industry, including residential and commercial installers (8), distribution intermediaries (3), and business software vendors (4). We conducted extensive interviews with executives at each firm (76 interviews in total), and supplemented this information with archival resources such as press releases, news coverage, analyst reports, and internet articles. This data was synthesized into a comprehensive case for each actor, detailing the activities conducted within each firm, the drivers of soft costs within that firm, and knowledge flows (e.g., new technologies, best practices, etc) within and across firms. We then compared across these cases to identify common patterns in cost and knowledge dynamics. Our study contributes a nuanced perspective on the drivers of soft costs within the solar industry as well as the patterns and mechanisms of knowledge flows within the industry. We find for example that the majority of the soft costs occur at the interface between firms (e.g., utilities, suppliers). We also observe substantive variation in costs across different types of actors and even within firm types (e.g., small vs. large installers). We also provide insight into how firms acquire knowledge and when they are able to apply it in order to reduce these costs. Our data reveal heterogeneity in a) the types of knowledge, and b) the pathways of knowledge flow between the actors in the industry. For example, we observe that distributors and suppliers play a key role in the dissemination of new technologies as well as general management knowledge for smaller firms. In contrast, informal personal networks and internal experimentation appear to be more important for larger firms. We also reveal critical distinctions across markets – e.g., differences in organizational culture that facilitate learning and experimentation more readily in residential vs. commercial markets. Overall, these results contribute preliminary insights into the knowledge dynamics of the solar industry, the persistence of soft costs over time, heterogeneity across firm types and regions, and the effective design of policy to support the solar industry.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗