Comparative analysis of the R&amp;D investment performance of Korean local governments

Lee, Hyoung Seok; Seo, Hyungjun

doi:10.1016/j.techfore.2020.120073

Cited by 32 publications

(27 citation statements)

References 35 publications

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“…Several literatures such as Lin and Wesseh, 6 Lee et al 7 and Bockman et al 8 analyzed the investment value of renewable generation sources under uncertainties of electricity price or subsidy program. Lin and Wesseh 6 used a real option pricing approach to evaluate the investment value of solar power technology under uncertainty of fossil fuel prices when feed-in tariff (FIT) policy is imposed in China.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Lee et al 7 evaluated the investment value of R&D for wind power technology and the optimal investment timing using a binomial tree approach. This paper assumed that a decision maker can make a choice to either abandon, deployment or continue the R&D, and the empirical result showed that considerable investment value exists in continuing wind power R&D in Korea.…”

Section: Literature Reviewmentioning

confidence: 99%

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Price and subsidy under uncertainty: Real-option approach to optimal investment decisions on energy storage with solar PV

Jeon

2021

Energy & Environment

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Renewable generation sources still have not achieved economic validity in many countries including Korea, and require subsidies to support the transition to a low-carbon economy. An initial Feed-In Tariff (FIT) was adopted to support the deployment of renewable energy in Korea until 2011 and then was switched to the Renewable Portfolio Standard (RPS) to implement more market-oriented mechanisms. However, high volatilities in electricity prices and subsidies under the RPS scheme have weakened investment incentives. In this study we estimate how the multiple price volatilities under the RPS scheme affect the optimal investment decisions of energy storage projects, whose importance is increasing rapidly because they can mitigate the variability and uncertainty of solar and wind generation in the power system. We applied mathematical analysis based on real-option methods to estimate the optimal trigger price for investment in energy-storage projects with and without multiple price volatilities. We found that the optimal trigger price of subsidy called the Renewable Energy Certificate (REC) under multiple price volatilities is 10.5% higher than that under no price volatilities. If the volatility of the REC price gets doubled, the project requires a 26.6% higher optimal investment price to justify the investment against the increased risk. In the end, we propose an auction scheme that has the advantage of both RPS and FIT in order to minimize the financial burden of the subsidy program by eliminating subsidy volatility and find the minimum willingness-to-accept price for investors.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Price and subsidy under uncertainty: Real-option approach to optimal investment decisions on energy storage with solar PV

Jeon

2021

Energy & Environment

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“…Therefore, by giving a careful consideration, this study attempts to construct a ternary SVAR (2) model for the real estate bubble, corporate liquidity, and corporate R&D investment. The specific structure is presented in formula (5).…”

Section: Plos Onementioning

confidence: 99%

“…The endogenous growth theory shows that R&D investment and innovation capabilities help improve economic efficiency and increase China's potential economic growth rate [5]. Therefore, during the economic transition period, China needs to pay more attention to the R&D investment by enterprises.…”

Section: Introductionmentioning

confidence: 99%

Does real estate bubble affect corporate innovation? Evidence from China

Wang

Lee

et al. 2021

PLoS ONE

Self Cite

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With the rapid increase of downward pressure on China’s economy, the stability of the property market, as an important part of the economic transformation process, also has a far-reaching impact on enterprises’ R&D investment. We select the data of Chinese large and medium-sized industrial enterprises from 1998 to 2015 as our research sample and propose a new combination measurement model based on closeness degree to measure the real estate bubble level in China accurately. The structural vector autoregressive (SVAR) theory is utilized to empirically test the dynamic relationship between the real estate bubble, corporate liquidity, and R&D investment. The results indicate that the real estate bubble level in China is increasing, and a certain risk of deviating from the safety interval in the future exists; The rapid expansion of the real estate bubble has a continuing negative impact on corporate R&D investment, that is, its "credit mitigation effect" is much smaller than the "capital relocation effect," and industrial enterprises will fall into the so-called "low-tech lock-in" state. In other words, to a certain extent, the development of this kind of real estate bubble will not be conducive to the transformation and upgradation of enterprises and long-term economic growth.

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“…Recently, researchers favor using the DEA to estimate a functional relationship between multiple research inputs and outputs rather than sum weighted quantitative indicators directly. Lee et al [15] evaluated Korea's R&D investment performance at the local government level using slack-based model data envelopment analysis (SBM-DEA). Qin et al [24] measured regional R&D efficiency and its spillover effects in China using DEA as a performance analysis tool.…”

Section: Introductionmentioning

confidence: 99%

Using context-dependent DEA to analyze the efficiency of highly funded scientists in China

Xiang

Liang

Guo

et al. 2021

Complex Intell. Syst.

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Funding inputs and research outputs have always been two central issues in the science of science. In recent decades, research funding plays an increasingly important role in scientific research. Thus, it is progressively significant for management authorities to measure the research efficiency of highly funded scientists, which can be helpful for them to make effective policies. However, few researchers use quantitative analysis to study these issues. To promote the research in this field, we begin with collecting a dataset. This dataset contains research funding and other information from 345 highly funded scientists in Mainland China. Next, we use the dataset to measure the efficiency of highly funded scientists based on the data envelopment analysis. In this way, highly funded scientists are placed into several levels according to their research inputs and outputs. We also give their attractiveness and progress scores compared to other grades. The learning path for less efficient scientists is also provided. We find that highly funded scientists have relatively high efficiency in three kinds of projects, such as the Major Research Plan. Besides, the career length and career start year are demonstrated to have a limited impact on the highly funded scientists. These patterns are beneficial for the development of the scientific community and management authorities to make policies.

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Comparative analysis of the R&D investment performance of Korean local governments

Cited by 32 publications

References 35 publications

Price and subsidy under uncertainty: Real-option approach to optimal investment decisions on energy storage with solar PV

Price and subsidy under uncertainty: Real-option approach to optimal investment decisions on energy storage with solar PV

Does real estate bubble affect corporate innovation? Evidence from China

Using context-dependent DEA to analyze the efficiency of highly funded scientists in China

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