Purpose – There are several approaches trying to explain the diffusion of renewable energy technologies (RET). The most commonly used instruments are learning and experience curves, followed by further economic, policy‐ and barrier‐related analyses. In order to gain a more comprehensive understanding, additional influence factors on RET diffusion have to be studied. This paper aims to contribute to research on RET diffusion by adding the raw material price perspective. Design/methodology/approach – The authors develop a regression model to test the influence of raw material prices on RET diffusion, using investments in RET capacities as indicators of diffusion, and crude oil and natural gas prices as well as public R&D subsidies as main independent variables. The model is then applied to emerging RET (wind and solar power) for electricity generation in 18 OECD‐countries. Findings – In the case of wind power, the model shows an adequate fit and a highly significant impact of oil as well as gas prices on investments in RET capacity. In the case of solar power, the impact of raw material prices proves to be highly significant as well, but the weak model fit demands further adjustments of the parameters. Originality/value – Theoretical implications include the expansion of existing RET diffusion models to a raw material price component. From a practical point of view, the authors provide a starting basis for the systematic integration of raw material price developments into companies' planning and forecasting processes.
foresight – Emerald Publishing
Published: Nov 8, 2013
Keywords: Innovation; Forecasting; Energy management
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