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Argues that there is no guarantee that it will be possible to maintain the present situation, with regard to energy, in an enlarged EU. Indeed, the enlargement has heightened concerns that the current approach may be undermined. Deplores the absence of a clear safety framework for EU nuclear installations and further details the problems, in full, in the article.

This chapter argues that the concept of metagovernance offers an alternative to multi-level governance (MLG) for understanding how policy is delivered through complex networks. Whereas MLG portrays the state as a diminished entity, metagovernance argues for a strong, capable state that can govern through the deployment of policy tools. The chapter identifies and evaluates how policy tools are selected to realise the strategic objectives of government.

A critical case methodology is employed. Nuclear power is held to be a most difficult test for the British government’s ability to metagovern. The empirical data was collected from in-depth qualitative interviews conducted between August 2008 and July 2013.

The chapter shows that the British government’s metagovernance efforts are informed by the risks that would-be developer face. The British government is shown to have some ability to practice metagovernance but the complexities of nuclear power and the existence of a MLG structure create risks that government cannot overcome. It is also observed that in nuclear power programmes, the risks of construction cost overruns and electricity price fluctuations have the greatest impact on the calculations of would-be developers.

The findings offer insight into the limits of government capacity in the face of networks and claims of continued state power. The chapter links together the literature on risk and the emergent literature on metagovernance. It is shown that institutional risks in the form of political opportunism are ever present and cannot be easily overcome.

Government are often called upon oversee difficult projects that are delivered by commercial actors. The findings indicate how governments might approach the task and point to a need for greater sensitivity to the nature of the project itself.

The empirical results show that to moderate risk, government has tended to adopt very technocratic policies that limit wider democratic consultation in favour of working directly with commercial actors.

The chapter presents a detailed analysis of government decision-making in a highly controversial area of public policy – nuclear power.

Nuclear power is a stable and reliable energy source that can improve energy structure while reducing carbon emissions, which is of great significance for environmental protection and combating climate change. As a unique industry, it is facing rare development opportunities in China and has broad market prospects. However, the characteristics of technical difficulty, loose organizational structure and uneven regional distribution limit the expansion of the nuclear power industry. This paper aims to a better understanding of the accumulation process for innovation capability from the perspective of network evolution and provides policy guidance for the market development of the nuclear power industry (NPI).

Methodologically, social network analysis is used to explore the co-evolution of multidimensional collaboration networks. First, the development and policy evolution of the NPI is introduced to divide the evolution periods. Then, the authors identify and analyze the core organizations, technologies and regions that promote nuclear power patent collaboration. Furthermore, three levels of collaboration networks based on organizations, technologies and regions are constructed to analyze the coevolution of patent networks in China’s NPI.

The results show that nuclear power enterprises always play the foremost role in the organizational collaboration network (OCN), and the dominance of foreign enterprises is replaced by Chinese state-owned enterprises in the third period. The technology hotspot has shifted from nuclear power plant construction to the control system. The regional collaboration network was initially formed in the coastal areas and gradually moved inland, with Guangdong and Beijing becoming the two cores of the network. The scale of three collaboration networks is still expanding but the speed has slowed down.

In response to the pain points of the NPI, this research focuses on multidimensional collaborative innovation, investigates the dynamic evolution process of collaborative innovation networks in China’s NPI and links policy evolution with network evolution creatively. The ultimate result not only helps nuclear power enterprises integrate innovative resources in complex environments but also promotes industrial upgrading and market development.

Asks whether nuclear power is viable as a clean source of energy and an independent energy source and whether it should be used to attain targeted reductions in fossil fuels or as a method of electricity generation. Also considers whether nuclear energy should be used in preference to energy from a third country. Discusses problems such as technological safety, nuclear waste, costs and the individual energy policies of Member States. Cites the main issue as public perception as the subject is regarded as dangerous and secretive. Outlines how the debate in Europe is being re‐evaluated and with the evolution of new science and technology, the positive contribution of nuclear energy to sustainable development is a factor to be weighed in the balance.

In recent years, continuous expansion of the scale of the new energy export industry in China caused a boycott of American and European countries. Export injury early warning research is an urgent task to develop the new energy industry in China. The purpose of this paper is to build an indicator system of exports injury early warning of the new energy industry in China and corresponding quantitative early warning models.

In consideration of the actual condition of the new energy industry in China, this paper establishes an indicator system according to four aspects: export price, export quantity, impact on domestic industry and impact on macro economy. Based on the actual data of new energy industry and its five sub-industries (solar, wind, nuclear power, smart grid and biomass) in China from 2003 to 2013, GM (1,1) model is used to predict early warning index values for 2014-2018. Then, the principal component analysis (PCA) is used to obtain the comprehensive early warning index values for 2003-2018. The 3-sigma principle is used to divide the early warning intervals according to the comprehensive early warning index values for 2003-2018 and their standard deviation. Finally, this paper determines alarm degrees for 2003-2018.

Overall export condition of the new energy industry in China is a process from cold to normal in 2003-2013, and the forecast result shows that it will be normal from 2014 to 2018. The export condition of the solar energy industry experienced a warming process, tended to be normal, and the forecast result shows that it will also be normal in 2014-2018. The biomass and other new energy industries and nuclear power industry show a similar development process. Export condition of the wind energy industry is relatively unstable, and it will be partially hot in 2014-2018, according to the forecast result. As for the smart grid industry, the overall export condition of it is normal, but it is also unstable, in few years it will be partially hot or partially cold. The forecast result shows that in 2014-2018, it will maintain the normal state. In general, there is a rapid progress in the export competitiveness of the new energy industry in China in the recent decade.

Export injury early warning research of the new energy industry can help new energy companies to take appropriate measures to reduce trade losses in advance. It can also help the relevant government departments to adjust industrial policies and optimize the new energy industry structure.

This paper constructs an index system that can measure the alarm degrees of the new energy industry. By combining the GM (1,1) model and the PCA method, the problem of warning condition detection under small sample data sets is solved.

It is predicted that the bitcoin system will enter many areas of our lives in the future. Although it has many benefits, the most criticized issue of this system is excessive energy consumption. Since an excessive amount of energy is used in this process, it is vital that the preferred energy is environmentally friendly. For example, mining bitcoin with fossil fuels is likely to release a significant amount of carbon gas into the atmosphere. This will cause serious environmental problems. Therefore, great attention should be paid to the type of energy that will be used in bitcoin mining. In this study, it was stated that it would be beneficial to prefer nuclear energy in bitcoin mining. As a result of the use of nuclear energy, no carbon gas is released into the atmosphere. This will help reduce environmental pollution to a significant extent. Another dimension of nuclear energy being preferred in bitcoin mining is that the energy produced is continuous. The main reason for this is that nuclear energy is not affected by climatic conditions and temperature differences. Thanks to the preference of nuclear energy in bitcoin mining, it will be possible to contribute to the uninterrupted progress of this process.