Low-carbon technology development under multiple adoption risks

Jian-Xin Guo, Kaiwei Zhu, Xianchun Tan and Baihe Gu

Technological Forecasting and Social Change, 2021, vol. 172, issue C

Abstract: Reducing greenhouse gas emissions is now an important global issue. The promotion and application of low-carbon technologies is one important method of achieving greenhouse gas reduction. The core problem is identifying the types of technology to introduce, when and to what degree, while satisfying the related sustainable goals. This study proposes a frame of development path design for low-carbon technology. Contrary to existing methods, our innovation lies in the introduction of multiple uncertainties in the technology adoption process. We consider four main types of technical risks, and provide corresponding quantitative descriptions. Our framework describes a class of technology development path problems as dynamic programming problems with different random constraints. Using existing numerical simulation methods, we obtain solutions of the original problem at a certain level of confidence, and discuss important issues, such as the learned robust features, and the relevant sensitivity of the model in a given solution space. Related results confirm the effectiveness of our model. Notably, our analysis framework can be generalized to solve similar problems, especially, in the characterization of technical risks.

Keywords: Low-carbon technology; Multiple adoption risks; Stochastic optimization; Sample average approximation (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:172:y:2021:i:c:s0040162521004431

DOI: 10.1016/j.techfore.2021.121011

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