Nuclear fuel cycle–related R&amp;D classification for implementing the IAEA's additional protocol

Lee, Seungmin; Song, Wonjong; Yang, Jae‐Suk

doi:10.1016/j.pnucene.2021.103884

Cited by 1 publication

(1 citation statement)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…38 The country's government subsidy for energy R&D investment surpassed $843 million in 2021, which was more than a 23% increase from the budget in 2020. 39 With the country's rapidly growing energy R&D funding at both the firm- and government-level, the efficient and risk-diversifying funding allocations under uncertainty have become more important than ever before.…”

Section: Methodsmentioning

confidence: 99%

Creating portfolios of firm-specific energy R&D investment under market uncertainty

Lee

Park

Kim

et al. 2022

Energy & Environment

View full text Add to dashboard Cite

This research determines the optimal distribution of firm-specific energy research and development (R&D) investment that balances firms’ return and risk under market-induced uncertainty. We focus on creating optimal portfolios of target firms and their optimal energy R&D investments that maximize their return on investments (ROIs) for given levels of risk. We employ a stochastic optimization framework that maximizes firms’ ROIs for energy R&D investment, measured by the ratio of the number of patents issued for energy technologies to the amount of annual energy R&D expenditures, for 78 energy firms in South Korea between 2006 and 2017. The findings from our mean-standard deviation tradeoff frontiers are summarized as follows: 1) the tradeoff ratio increases as the weights shift from 100% on maximizing expected ROI toward 100% on minimizing its standard deviation regardless of market conditions and 2) the tradeoff ratio during the downturn is higher than during the upturn. These findings suggest that firms mitigate market-induced risk with a smaller sacrifice in the expected number of issued patents when the initial weight is primarily on maximizing expected ROIs and when the market is experiencing an upturn instead of a downturn. From the distribution patterns of prioritized firms for the two extreme risk preference points along the upturn and downturn tradeoff frontiers, we find that the target firms shift under different market conditions and risk assumptions. These priority shifts highlight the importance of decision-maker flexibility in structuring firms’ portfolios to support energy R&D, depending on the governments’ risk tolerances and market conditions.

show abstract

Section: Methodsmentioning

confidence: 99%