Abstract –
While the role of organizational learning in improving firm performance is well documented, there are still questions on what drives technological learning. This is evident in the electricity industry where the growth of renewable energy technologies has been pervasive. Vicarious learning contributes to the adoption of emerging technologies through successful inter-firm knowledge sharing and transfer. However, there is hesitation to adoption that characterizes vicarious learning especially in the context of intra-firm learning. This paper investigates the differences in knowledge acquisition within and across electricity firms in the U.S. The learning curve model is applied to a longitudinal study of 5573 plants belonging to 1542 U.S. electricity firms between 1998 and 2010. This study finds: (i) The capacity growth of the solar photovoltaic technology is positively associated with intra-firm knowledge acquisition; (ii) The effect of financial incentives on the adoption of solar and wind technologies is higher under inter-firm learning; (iii) The higher the stringency of policy mandates, the more varied is the progress on technological change across technologies; (iv) Knowledge sharing between firms are higher for wind technology than for solar technology. These findings combine to show disparities in the learning trends of technologies across and within firms’ boundaries.
Introduction
Within the past decade, billions of dollars have been invested in clean technologies. This has led to a clean energy revolution in the U.S. electricity sector. Yet, sustaining market competition and maintaining competitive advantage for U.S. electricity firms remain key issues. Knowledge acquisition and technological innovation are becoming effective tools for harnessing competition and designing firms’ profit maximization strategies. This article seeks to explore the mechanisms of knowledge acquisition, either between firms or within a firm, on the adoption of energy technologies among U.S. electricity firms. For that purpose, this study inspects the heterogeneity related to knowledge acquisition within and across electricity firms. Furthermore, questions of environmental regulations and firms’ desire to innovate and maximize profits are complex and intricate. Thus, to shed more light on the mechanisms underlying firm innovation, this paper borrows Vockell (2001)’s modeling framework from psychology and applies Yelle (1980)’s learning curve model. Combining these models allows us to explain the transfer of learning and how organizations learn from (i) the experience of others, and (ii) their own experience. However, this research differs from the existing literature on the transfer of knowledge in service organizations, such as Darr et al. (1995), by focusing on firms’ electricity generating technologies. It carries out a longitudinal study of 5573 plants belonging to 1542 U.S. electricity firms between 1998 and 2010 by generating seven models of the responses in cost per electricity produced.
This paper demonstrates that the acquisition of new knowledge through intra-firm learning by U.S. electricity firms is positively associated with the improvement of a new technology, solar photovoltaic in particular. This paper shows the fruitful relationship between financial incentives for clean technologies and innovation in clean technologies through inter-firm transfer of technology knowledge. The results show that the improvement of knowledge acquisition for wind technologies within electricity firms is stimulated by production tax credits. The analysis further shows that complying with policy instruments often produces diversity in terms of technological progress. The results further demonstrate how inter-firm knowledge acquisition is more prevalent for wind technology than for solar technology, resulting in a higher learning rate for wind technology. Policy mandates and financial incentives have a positive impact on technological innovation. In the light of these findings, and given the economical and environmental benefits of emissions reduction, policies designed to cost-effectively grow the adoption of renewable energy are necessary.
The rest of this article is organized as follows. In section 2, the theoretical framework is introduced and the rationale behind each hypothesis is elaborated on. In this section, the article also reviews the theory of organizational learning to further highlight the processes driving how the firm advances along the learning curve. In section 3, the article provides the econometric models with the implications of policy instruments on technological learning or adoption. In this section, the article also describes the research design, industry context, and sources of data. In section 4, the results are presented. Section 5 concludes.
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