Next Article in Journal
A Study of Chinese University Students’ English Learning Motivation, Anxiety, Use of English and English Achievement
Previous Article in Journal
Driver Behavior Mechanisms and Conflict Risk Patterns in Tunnel-Interchange Connecting Sections: A Comprehensive Investigation Based on the Behavioral Adaptation Theory
Previous Article in Special Issue
Research on Carbon Cap Regulation, Retailer Altruistic Preferences, and Green Decision-Making of Manufacturing Enterprises
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Sustainability
Volume 16
Issue 19
10.3390/su16198703
sustainability-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

The Path Driving China’s Energy Structure Transformation from the Perspective of Policy Tools

by
Jintao Li
1,2,
Hui Sun
2,
Long Cheng
1,2,* and
Lei Chu
1,2,*
1
Centre for Quality of Life and Public Policy Research, Shandong University, Qingdao 266200, China
2
School of Politics and Public Administration, Shandong University, Qingdao 266200, China
*
Authors to whom correspondence should be addressed.
Sustainability 2024, 16(19), 8703; https://doi.org/10.3390/su16198703
Submission received: 11 September 2024 / Revised: 6 October 2024 / Accepted: 7 October 2024 / Published: 9 October 2024
(This article belongs to the Special Issue Advancing Carbon Reduction Technology Innovation: Pathways to Global Carbon Neutrality and Sustainable Development)
Browse Figure
Review Reports Versions Notes

Abstract

:
Combing through Chinese energy-related policy texts and exploring the development path of energy restructuring are significant steps towards a better understanding of the history of energy restructuring in the process of building a moderately prosperous society in all aspects. To explore the various paths driving the transformation of China’s energy structure, the energy policies promulgated at the national level from 2001 to 2020 in China were systematically compiled. Based on the policy tool perspective, a theoretical framework for influencing China’s energy structure transition was proposed in three dimensions: objectives, tools, and intensity. A total of 39 national energy policy texts were analyzed using a fuzzy set qualitative comparative analysis method. The results show that (1) the consistency levels of individual preconditions were all below 0.9, which does not constitute a necessary condition for the transformation of China’s energy structure; (2) the sufficiency analysis identified three paths of China’s energy structure transformation, which can be described as models driven by “multiple objectives + information”, “single objective + information”, and “single objective”; (3) energy restructuring is a goal-oriented process; the clarity and certainty of the efficient and green objectives of energy policies have a facilitating effect on energy restructuring, and the support of information technology provides an important guarantee for energy restructuring; (4) compared with European and American countries, it was found that China’s energy policy tools were characterized by an emphasis on macro-planning, insufficient connectivity, and marked tendencies in practice.

1. Introduction

Energy systems are open and complex systems simultaneously coupled with economic and environmental systems. The complexity of energy system transformation is determined by the wide range of energy applications and their basic support to the economy and society [1]. Energy restructuring is the result of the interaction and synergistic evolution of multiple influencing factors. Since 1980, China has been building a moderately prosperous society, a goal that was achieved by 2020. Currently, China is in a new stage, with the goal of building a modern socialist country. Over the past two decades, innovative development concepts have guided historic achievements in energy development, promoting the clean and low-carbon transformation of China’s energy structure and providing a favorable foundation for the start of the 14th Five-Year Plan. Recently, the new energy industry has been developing rapidly, especially under increasingly severe energy and environmental problems. Energy saving and efficiency improvement, optimization of the energy structure, and technological innovation have become important, visible objectives for China’s energy quality development [2]. Accordingly, scholars have paid increasing attention to how to formulate and improve energy policies and promote energy structure transformation so as to achieve low-carbon, clean, and high-quality development.
Research on energy structure transformation presents diverse and cross-cutting characteristics; as such, scholars have employed different research foci and methods. The attention of existing studies has been directed to the impact factors and assessment of the effect of energy saving and emission reduction in the transition of the energy system. Studies on energy policies have focused on summarizing the experiences and shortcomings of policies on energy structure transformation. In recent years, the development of a new energy industry has triggered considerable policy research on clean energy and renewable energy. The research perspective has gradually shifted from macro research to the coexistence of macro and micro perspectives, and the research methods have become increasingly diversified. However, existing research on the impact factors of energy transition is still dominated by econometrics, and an analysis of the synergistic driving effects among different factors is currently lacking. These studies focus on a single time point, and relatively little research has been conducted on the dynamics of the energy transition, while the dynamic and holistic analysis of China’s energy transition policy development has been completely neglected. Policy research should not only include the top-level design of policies or the evaluation of the existing policy system but also focus on the evolutionary process of policies via systematic analysis [3].
With this background in mind, based on existing research, the fuzzy set qualitative comparative analysis method was employed to examine the evolutionary path of China’s energy structure transformation. This study took 39 national-level energy policy documents issued in China from 2001 to 2020 as the research object. The aim of this study was to identify the conditions that lead to differences in the intensity of energy structure transformation at different development stages through the synergistic driving effect of factors. Particularly, this study aimed to provide an explanation of the pathways that accelerate successful energy structure transformation and references for the low-carbon and clean transformation of energy structure in the future.
Firstly, we provide some background information about energy structure transformation and our research objectives in Section 1. In Section 2, we review the literature around energy transition practices across countries. In Section 3 and Section 4, we present the theoretical foundation of this research study and our research design. In Section 5, we illustrate the findings, focusing on how the different elements act synergistically to drive the transformation of energy. Section 6 and Section 7 contain, respectively, the discussion and conclusions.

2. Pathways to Energy Transition Practices: A Literature Review

Solving the energy problem is an important goal of China’s modernization and development process. Since the 10th Five-Year Plan period, China’s economic development and ecological environment have been changing in response to the reform and opening up process. As an important lever to regulate energy structure [4], China’s energy policy has been continuously adjusted. The concept of “transformation of energy structure” was first introduced in 1980 in the book Energy Transition: Growth and Prosperity without Oil and Uranium [5], published by the German Academy of Sciences. This book argued that the transformation of the energy structure requires a shift in the dominant energy source in the development process. This process requires a transition from oil and nuclear energy to renewable energy sources. Since the beginning of the 21st century, the impact of energy on economy, society, and politics has gradually increased. Accordingly, several studies have been conducted on the energy transition. The green and low-carbon transformation of the energy system provides solid support for the development of modernization [6]. With the development of the energy industry, and especially with the promotion of the ecological civilization, scholars have enriched existing research on energy structure transformation.
With the worsening of the climate and ecological problems, national governments are striving to find ways to reduce carbon emissions which are appropriate to their own national conditions. In order to minimize the cost of emission reduction, a wide range of complex modeling tools have been created in various countries or regions in the development of renewable energy plans. For instance, the Global Change Analysis Model for the United States (GCAM-USA), a multisectoral human–land systems model created in the United States which integrates multiple dynamic models of energy, economic, and land-use systems, can explore climate change mitigation policies, including carbon taxes, carbon trading, regulations, and an accelerated deployment of energy technologies [7]. Other examples include Japan’s energy system model, AIM/Enduse, which is designed to minimize total energy costs within a given set of constraints [8], and the Price-induced Market Equilibrium System (PRIMES) model, developed by the European Union (EU), which is used to provide a quantitative assessment of EU energy and environmental policies [9].
Existing research has proved that the development of renewable energy and reducing carbon emissions is a successful approach to sustainable development in various countries around the world [10,11,12]. In order to perform an analysis of the energy structure transformation path, scholars in various countries have generally accepted decarbonization as the future direction of energy development. Gardumi [13] and Granado et al. [14] explored the clean and low-carbon development path of the EU energy system through models and case studies. In particular, Granado et al. argued that the level of cooperation and decentralization plays a decisive role during the transformation of the energy structure. Economic growth, trade, and energy consumption are closely linked to externality problems at the local and international levels. Existing scientific evidence also suggests that export product diversification (EDIV) contributes to lower energy and carbon intensity and higher energy efficiency, making it a viable strategy to mitigate carbon externalities in the process of economic transition, especially for developed countries [15]. In any case, green technological innovation is one of the most effective tools to reduce CO2 emissions. In practice, governmental organizations and businesses are increasingly investing large sums of money in research and development so as to reduce pollution while at the same time ensuring economic growth [16]. Public policy, especially the scientific planning and institutional design of new energy sources by the government, typically plays a central role in the process of energy conservation and emission reduction. Scholars generally agree that the rapid development of the new energy industry was due to vigorous support by the government through policy instruments. For example, the policy of New Energy Demonstration Cities (NEDCs), a green development strategy that integrates environmental protection and economic growth, is crucial to solving the development dilemma of resource-based cities [17]. The transformation of the energy structure is characterized by a long cycle, the complexity of the subjects, and a wide range of areas. Therefore, in order to combine the diversity of different policies, as well as to adapt to the continuous changes in policies, the sustainable development of the energy sector is facilitated by a combination of policies [18].
Based on the national situation of China and through comparison with different countries, Chinese scholars have stated that China’s energy transformation faces three major challenges, including the clean utilization of coal, a rising external dependence of oil and gas, and an uncertainty of new energy pillar industries [19]. For the future development of China’s energy system, it has been suggested that the ideal solution would be to use oil and natural gas as a temporary alternative to coal in the short term [20], followed by the steady promotion of renewable energy based on stable social development. In recent years, with the increasing severity of climate change and environmental pollution problems, the promotion of energy restructuring and the development of clean energy have become common choices worldwide. As the world’s largest energy consumer and carbon emitter, China faces tremendous pressure to save energy and reduce emissions. These problems are faced by actively formulating carbon emission reduction measures and by carrying out carbon emission reduction activities. The development of natural gas and renewable energy has become an important path for China’s low-carbon energy transition. In this context, numerous scholars have investigated the path of low-carbon energy transition around new and clean energy. Yi et al. [21] and Li et al. [22] reviewed the development status of hydrogen, solar, and wind power generation both in China and internationally. They proposed that hydrogen, solar photovoltaic, and wind power generation, as clean energy sources, play an important role in promoting energy change and transformation. Based on the results of a model and cross-country experience analysis, Ma et al. [23] observed that during the period from 2015 to 2025, fossil energy sources would still play a dominant role, while natural gas and nuclear energy can be appropriately developed and the proportion of renewable energy can be increased. Also, digitalization [24], financial investments (both domestic [25] and foreign [26]), and technology [27] can have a positive impact as specific energy transition tools.

3. Theoretical Background

Policies are instruments of government which rely on public power, aim to solve public problems, respond to social needs, allow to achieve government goals, and have a certain degree of authority and coercion [28]. The development of the energy sector needs policy guidance and support, and the level of issuance of national policy documents, tools, and measures has direct impacts on the development of the energy industry. For the energy sector, policy tools serve three main functions: guiding macro direction, leading technological development, and optimizing resource allocation [29]. It is worth noting that policy tools do not have a decisive role in the policy system and its operation. As initiatives to reach policy goals, they are adjusted to the objective environment, the attention of political subjects, and the difficulty of policy implementation [30]. It is therefore essential to position the application of policy tools within the overall policy system, policy network, decision-making system, and implementation process [31].
The positive impacts of policy objectives [32], policy tools [33], and policy intensity [34] on the energy transition have been identified in a few studies in the literature. Although considerable attention has been paid to the antecedents of the energy structure transition, studies to date have mainly focused on the impact effects of different types of policy tools on the energy structure transition, and the impact of different policy dimensions on energy transition has received little consideration. By referring to the existing literature and using a policy tool perspective [4], this study analyzed the necessary conditions and the combination of factors affecting the transformation of the energy structure within the theoretical framework of policy objectives, policy intensity, and policy tools, as detailed in Figure 1.
In fact, policy objectives represent the direction for action, policy intensity represents the motivation for action, and policy tools represent the pathway for action, and all three interact with each other. Policy objectives are the desired outcomes, and their concentration and clarity are one of the prerequisites for policy synergy [35]. Energy policy objectives are necessary to promote the low-carbon transformation of the energy structure. It has been shown that strategies to improve energy efficiency and increase the share of renewable energy in almost all European Union countries have had a statistically significant impact on CO2 emission reductions [36]. China’s energy policy objectives are numerous in nature and carry policy tasks such as energy supply security, economic growth, resource conservation, and environmental protection. The problems and major contradictions faced by society at different historical stages will change; therefore, different policy objectives may have strong or weak effects on the transformation of the energy structure in the process of energy policy formulation. In general, the clearer and more focused the green and low-carbon objectives of energy policy are, the more conducive they are to the achievement of energy structure transformation goals.
Under the decentralized system, principal–agent problems often emerged between the central and local governments. Under the long-lasting political goal of “centering on economic development”, many Chinese officials tended to prioritize GDP achievements [37]. Therefore, in the energy structure transition, the central government has proposed various energy objectives, yet the inefficient implementation of these policies remains a significant impediment. Policy intensity reflects the degree of importance the government attaches to it [38] and can be used to assess the impact of a policy. The authoritative, high-pressure, and sustained characteristics of policy intensity make it a powerful signal to promote the transformation of the energy structure [33].
A reasonable policy structure requires the organic combination of policy objectives and policy tools [38]. If the policy objectives are the antecedents of the choice of policy tools, then the policy tools are the basic pathways for the realization of policy objectives [39]. The degree of synergy between policy tools and policy objectives has a direct impact on the effectiveness of policy implementation [40]. According to the classification of policy tools proposed by Howlet [41], the policy tools that affect energy restructuring were classified into four categories: administrative control tools, economic incentive tools, information tools, and voluntary participation tools. Different types of policy tools have different functions, as well as their own strengths and weaknesses. The policy tools used for energy restructuring need to be selected according to the specific energy goals and targets.

4. Research Method and Data

4.1. Research Method

QCA was first proposed by Ragin in the 1980s for small and medium-sized samples. QCA uses Boolean algebra and set theory as basic operations and includes a combination of characteristics from both quantitative and qualitative research methods. It is normally used to explore the multiple concurrent causes that impact a particular problem through the necessary and sufficient relationships between the condition and outcome variables. QCA can be used to explore multiple paths that lead to the same outcome and can effectively deal with complex interactions among multiple antecedent conditions [42]. This capability offers significant advantages to address causal complexity questions of multiple concurrent causality, causal asymmetry, and multiple scenario equivalence [43], thus overcoming the one-way, linear constraint of traditional linear regressions.
In this study, fuzzy set QCA (fs-QCA) was chosen as the main research method for three reasons. Firstly, among the two types of operation methods commonly used in QCA, i.e., crisp set QCA (cs-QCA) and fs-QCA, fs-QCA was chosen because of the difficulty associated with determining the assignment of antecedent conditions by simply using a dichotomous variable of 0 or 1. Energy structure transformation is a long-term, transitional development process, and two or more results of energy structure adjustment may occur after the promulgation of energy policies. The fs-QCA method uses the grouping algorithm of fuzzy set affiliation to calibrate relevant variables; in this way, it is possible to more accurately represent the condition and result variables. Secondly, the sample size of this study was limited. QCA has a relative advantage for small and medium sample sizes, i.e., within a sample size of 10–80. Currently, the number of specific policies for energy, especially energy restructuring, in China is small, and it is not suitable for large-scale statistical analysis. Thirdly, the process of energy policy development involves political, economic, and ecological factors, and the various antecedent conditions that promote energy structure transformation are often interdependent and mutually influential. QCA offers a unique advantage in solving the “different paths” and multiple concurrent causal relationships, thereby meeting the needs of energy structure transformation research.

4.2. Sample Source and Selection

A total of 64 energy-related policies promulgated at the central level between 2001 and 2020 were collected from government websites using the keywords “energy”, “energy conservation”, and “environmental protection”. The governmental portals of the State Council, the National Energy Administration, the National Development and Reform Commission, and the Ministry of Ecology and Environment were used to select 39 policies that are closely related to energy. This selection was conducted according to the requirements of typicality and comprehensiveness of case selection; the final list used in this study is shown in Table 1.

4.3. Variable Selection and Assignment

4.3.1. Condition Variables

Policy objectives: in this study, energy security, energy conservation, and energy cleanliness were considered to be measurement indicators of energy policy objectives. Following Mi et al. [44], each policy objective was assigned a score from 1 to 4 to reflect their clarity. Specifically, clear and quantifiable policy objectives, pointing out clear numerical standards for total energy, energy consumption per unit of GDP, and clean energy development scale were assigned a score of 4. When the policy objectives were clear but without quantifiable criteria, the assigned score was 3. When the policies only provided general statements of policy vision and expectations, the assigned score was 2. Finally, when the main policy objectives did not change, the assigned score was 1.
Policy tools: referring to Howlett et al. [41] and Mi et al. [44], in this study, policy tools were divided into four categories: administrative control tools, economic incentive tools, information tools, and voluntary participation tools. These categories were assigned a score from 1 to 4, respectively, according to the degree of governmental intervention. The specific criteria are as follows:
(1)
For administrative control tools, when one of the conditions presented in Table 2 was satisfied, the assigned score was 4. When the relevant elements of Table 2 were proposed in the policy without detailed programs, the assigned score was 3. When the government loosely controlled the criteria for energy restructuring and the terms were only briefly mentioned in the 4-point evaluation criteria for administrative control-type policy tools, the assigned score was 2. When the application of administrative control tools was not mentioned, the assigned score was 1.
(2)
For economic incentive tools, when one of the conditions presented in Table 2 was satisfied, the assigned score was 4. When the relevant elements of Table 2 were proposed in the policy without relevant implementation methods or measures, the assigned score was 3. When the terms were only briefly mentioned in the 4-point evaluation criteria for economic incentive tools, the assigned score was 2. When the application of economic incentive tools was not mentioned, the assigned score was 1.
(3)
For information tools, when one of the conditions presented in Table 2 was satisfied, the assigned score was 4. When the relevant elements of Table 2 were proposed in the policy without relevant implementation methods or related catalogs, the assigned score was 3. When the terms were only briefly mentioned in the 4-point evaluation criteria for information tools, the assigned score was 2. When the application of information tools was not mentioned, the assigned score was 1.
(4)
For voluntary participation tools, when one of the conditions presented in Table 2 was satisfied, the assigned score was 4. When the relevant elements of Table 2 were proposed in the policy without relevant implementation methods, the assigned score was 3. When the terms were only briefly mentioned in the 4-point evaluation criteria for voluntary participation tools, the assigned score was 2. When the application of voluntary participation tools was not mentioned, the assigned score was 1.
Policy intensity: in this study, policy intensity was quantified referring to the classification criteria of Li et al. [4]. Each policy was assigned a score from 1 to 6, with 6 levels based on the main issuing body of the policy. Specifically, laws promulgated by the National People’s Congress and its Standing Committee were assigned a score of 6. Decisions or directives issued by the State Council were assigned a value of 5. Opinions, methods, programs, plans, standards, or regulations promulgated by the State Council were assigned a value of 4. Opinions, approaches, programs, guidelines, plans, or directories issued by various ministries were assigned a value of 3. Approvals, notices, or reports issued by the State Council were assigned a value of 2. Notices, announcements, letters, or outlines issued by various ministries were assigned a value of 1.

4.3.2. Result Variables

Energy structure transformations are socio-technical processes that include expectations of energy efficiency, affordability, reliability, reduced vulnerability to the impacts of the fossil fuel industry, and energy independence [45]. The connotation of the transformation of the energy structure includes two aspects. First, the conversion of the dominant energy source, that is, a change in the energy structure. Second, the transformation of the energy system, which includes the physical facilities related to energy production, reserves, and consumption, as well as the organizational network and social elements attached to the physical facilities [46]. Throughout the evolutionary history of energy policies, the process of energy restructuring can be described as a process of energy greening and decarbonization. The ultimate goal of energy restructuring is to “promote the widespread application of renewable energy and low-carbon technologies” [47]. Consequently, the energy mix transition is also referred to as low-carbon energy transition. Regarding the assessment of the degree of energy structure transformation, scholars have used a diverse range of approaches, including the share of clean energy consumption in total energy consumption [48], the share of coal consumption in total energy consumption [49], and the amount of solar photovoltaic (PV) power generation [50]. With reference to previous studies [51], the energy structure was assigned a score from 1 to 4. Specifically, when the conditions presented in Table 3 were satisfied concurrently, the assigned score was 4. When the relevant elements of Table 2 were proposed in the policy, except specific quantitative indicators, the assigned score was 3. When the vision and expectations for energy restructuring were expressed in macro terms only, the assigned score was 2. When the degree of energy structure transformation was not mentioned at all, the assigned score was 1.

4.4. Data Calibration

This study adopted the direct calibration method, and the three values of 0.95, 0.5, and 0.05 were chosen as three qualitative anchors to calibrate the original data. A fuzzy affiliation of 0.95 indicates that the data were “almost completely affiliated with the set”, and a fuzzy affiliation of 0.05 that they were “almost completely unaffiliated with the set”, with a value of 0.5 as the dividing point. According to previous studies [52] and the characteristics of the data used in this study, the following three qualitative anchors were set (as shown in Table 4): the almost complete affiliation point was 75% of the original data; the cut-off point was the average of the condition variables; and the almost incomplete affiliation point was 25% of the original data.

5. Results

The fs-QCA 3.0 software was used to calibrate the raw data, construct the truth table, and conduct arithmetic analyses on the influencing factors of energy structure transformation. Single variables, as well as the combination of conditional variables affecting energy structure transformation, were clarified.

5.1. Single-Variable Necessity Analysis

Table 5 shows that the consistency of each conditional variable was below 0.9, which cannot be considered a sufficient or necessary condition for the occurrence of the outcome. This result indicates that none of the seven single conditional variables selected in this study are a necessary condition for energy restructuring. Moreover, this shows that a single level of policy objectives, policy tools, or policy intensity in the past energy restructuring process is insufficient to explain the promotion of the occurrence of the outcome. In short, energy restructuring is not the result of a single-factor influence, but of multiple complex, concurrent causes and effects.

5.2. Condition Configuration Analysis

Sufficient conditions are a combination of conditions that impact the strength of energy restructuring. In the sufficiency analysis, the case threshold was set to 1, the original consistency threshold was set to 0.8, and the proportional reduction in inconsistency (PRI) consistency threshold was set to 0.7. After the standard analysis of the truth table, three types of solutions were obtained: the Complex Solution, the Parsimonious Solution, and the Intermediate Solution.
In QCA applications, both the Intermediate Solution and Parsimonious Solution are usually employed for path analysis. In this study, following previous research, the specific paths and quantities that affect the intensity of energy restructuring were determined through the Intermediate Solution. The core and edge conditions of the grouping were determined through the specific explanatory variables in both the Intermediate Solution and the Parsimonious Solution. As shown in Table 6, the overall consistency and coverage values were 0.99 and 0.55, respectively, indicating that all the combinations of policy variables have a strong explanatory power for the outcome variable of energy restructuring. The consistency levels of the seven single antecedent group states were all greater than 0.8, thereby satisfying the sufficient condition requirement for energy restructuring. The coverage of their overall solution was 0.55, indicating that the seven conditional group states can explain more than half of the causes of energy restructuring overall. This result further confirms that energy restructuring is characterized by multiple concurrencies.
An analysis of the conditional groupings can clarify the logic of the synergistic interactions among the factors that promote the structural transformation of energy. Furthermore, this type of analysis allows for the identification of an optimization path for the green and low-carbon development of the energy industry. This study collated the seven conditional groupings that affect energy structure transformation into three patterns, based on their differences in the distribution of core variables present in the seven groupings.

5.2.1. “Multiple Objectives + Information” Model

This model includes paths R1a, R1b, and R1c (see Table 6) in three different condition groupings. All the core variables emphasize the important role of energy conservation, clean energy policy objectives, and information policy tools for energy structure transformation. In path R1a, energy security objectives and voluntary participation tools play a complementary role as marginal conditions for energy restructuring. This result indicates that even in an environment with a more relaxed political pressure, energy restructuring will be promoted through the guidance of multiple objectives, in combination with the synergistic effects of information-based and voluntary participation policy instruments. In addition to administrative control tools, economic incentive tools, and voluntary participation tools as common marginal conditions, the energy security objective plays a supporting role in path R1b. Furthermore, policy intensity plays a supporting role in path R1c as a marginal condition. This result indicates that with relatively well-developed policy tools, both the policy objective and the policy intensity of energy security are mutually substitutable to promote energy restructuring. The “multiple objectives + information”-driven path emphasizes the synergistic role of multiple objectives and information policy tools (mainly including science and technology research and energy information transfer). Previous studies showed that “information policy tools are mainly focused on strengthening scientific and technological research and development and providing technical support” [38]. Therefore, the centrality of the role played by information policy tools highlights the importance of the rapid development of information technology to achieve the goal of green energy structure transformation.
Several cases are covered under the “multiple objectives + information”-driven model, and the Strategic Action Plan for Energy Development (2014–2020), issued in 2014, was chosen as an illustrative example. To promote the transition of energy production and consumption, this Action Plan focuses on open-source, cost-cutting emission reduction, the active transformation of the energy development model, and the adjustment and optimization of the energy structure. On the one hand, this Action Plan proposes four key implementation strategies, namely green and low-carbon strategies, the active contribution to improving energy efficiency, and the promotion of the achievement of the goal of green energy development. It also emphasizes efforts to optimize the energy structure and the development of clean and low-carbon energy as the main direction to adjust the energy structure. Moreover, it clearly proposed that by 2020, the proportion of non-fossil primary energy consumption should reach 15%, and the proportion of coal consumption should be controlled at 62% or lower. On the other hand, to ensure the achievement of energy objectives, the development concept according to which “science and technology determine the future of energy, science and technology create the future of energy” was put forward. This Action Plan also proposes accelerating clean coal development and utilization technologies and to promote and implement a series of demonstration projects and energy-saving actions. Finally, it clearly promotes green living via the strengthening of publicity and education and the popularization of energy-saving knowledge.

5.2.2. “Single Objective + Information” Model

Paths R2a, R2b, and R2c (Table 6) belong to the “single objective + information”-driven model. The three paths under this model allocate different degrees of importance to the various aspects of the three dimensions. Paths R2a and R2b emphasize the important role of energy conservation and information tools. Administrative control, economic incentives, and voluntary participation policy tools are marginal conditions of R2a, while policy intensity plays a supporting role in promoting energy structure transformation. This highlights the importance of policy attention from the government for energy green and low-carbon transformation. In R2b, energy security objectives, administrative control type, and economic incentive tools are marginal conditions, while voluntary participation tools and policy intensity conditions are missing. The use of voluntary participation tools explains the role of the autonomous participation of non-governmental subjects in the transformation of the energy structure. Moreover, path R2b shows that in the case of a relatively low awareness of energy conservation and emission reduction among enterprises and citizens, as well as of insufficient policy attention, the transformation of the energy structure can still be promoted with the synergy among policy objectives and various policy tools. This can be achieved by clarifying and quantifying the goals of energy security and energy conservation, while at the same time strengthening the guidance and publicity of relevant information and technology in the energy sector. Unlike the first two paths, path R2c stipulates energy cleanliness as a core condition in the policy objective dimension and energy security as a marginal condition. With the exception of information policy tools, all other policy tools and policy intensity are lacking. Based on the configuration of this condition, under a clear energy policy goal, even if the government’s attention is scattered or resources are not sufficiently secured, the clean and low-carbon development of energy can be promoted by sufficient information disclosure and advanced technical support. This result is further corroborated by the statement that “the integration of low-carbon technology innovation is the core support for achieving low-carbon energy transition” [53].
The typical case covered by the “single objective + information”-driven model was briefly illustrated by the 10th Five-Year Plan for Energy Conservation and Comprehensive Utilization of Resources (hereinafter referred to as “the Plan”), issued by the State Economic and Trade Commission in 2001. The Plan highlights the importance of resources conservation and advocates for energy efficiency and a comprehensive utilization of resources. The Plan promotes the achievement of a coordinated development of the economy, resources, and the environment. To accelerate the improvement of energy utilization, the Plan proposes energy-saving targets in total energy consumption and key energy-utilizing areas, such as iron and steel enterprises, thermal power plants, and the construction industry. To achieve the energy-saving target, policy guarantee measures are proposed from administrative control tools, economic incentive tools, information tools, and voluntary participation tools. First, the Plan proposes accelerating the development of the supporting regulations of the Energy Conservation Law, including the “Energy Efficiency Labeling Management Measures”. Furthermore, energy efficiency standards and certification labeling systems need to be implemented to regulate the energy conservation market. Second, the goals are to conduct research and develop tax and public finance support policies in the fields of energy conservation and resource utilization and to provide appropriate tax incentives or financial subsidies for energy efficiency improvement projects. The Plan highlights the role of information policy tools, such as the promotion of industry–academia–research alliances, the active cultivation and development of technology markets, and the proposal of priority development technologies (including conservation and alternative oil technologies). To promote the application of new technologies and techniques, the Plan proposes actively exploring the information dissemination mechanism under market economy conditions. In addition, advanced technology and management information for enterprises should be provided by producing and publishing energy-saving cases and strengthening information services and by continuously guiding them to implement energy-saving technology transformation. In addition, the Plan proposes increasing national publicity and education on energy conservation to enhance national awareness of resource conservation and environmental protection. During the 10th Five-Year Plan period, energy consumption increased by 14% of the Gross Domestic Product per CNY 10,000, and the consumption of electricity among end-use energy sources increased by 85.3% [54]. Through technology development, industrial structure adjustment, and expansion in the use of non-fossil energy sources, the share of primary electricity and other energy sources increased by 9.1% at the end of the 10th Five-Year Plan period, compared to the year 2000. Led by an information-based synergy among energy conservation objectives, as well as by four types of policy tools and by policy intensity, energy use has developed in the direction of efficiency and cleanliness. Thus, the process of development of energy conservation and energy structure optimization has been promoted.

5.2.3. “Single Objective” Model

R2 is the only path in the “single objective”-driven model (Table 6). The only core condition of this path is energy cleanliness, while the marginal conditions are energy security, economic incentive, and voluntary participation instruments. These differ from the configurations of the other six conditions, as they lack information policy instruments. In terms of core conditions, this path emphasizes the importance of clear and quantifiable energy cleanliness goals for energy restructuring. The lack of policy strength and coercive policies creates a relatively liberal social development environment, which is equally prone to promote energy restructuring through the synergies among energy security, energy cleanliness goals, and economic incentive tools, such as financial policies, social advocacy policies, and guidance policies.
A typical example of the “single objective”-driven model is the 13th Five-Year Plan for Renewable Energy Development (hereinafter referred to as “the 13th Five-Year Plan”), promulgated by the National Development and Reform Commission in 2016. To accelerate the replacement of fossil energy and promote the clean and low-carbon transformation of energy system in China, the 13th Five-Year Plan puts forward the basic principle of “insisting on target control”. The strategic target of 15% of primary energy consumption by 2020 from non-fossil energy sources is clearly defined, and explicit quantitative standards are imposed for the total renewable energy targets and renewable energy generation. At the same time, to promote the diversified development of various types of renewable energies, the 13th Five-Year Plan has established development and utilization indicators from water, wind, light, and biomass energy. In the context of China’s pressure-based system, various quantified renewable energy development targets are decomposed and gradually added into local assessment indicators. The goal is to stimulate local administrative leaders to form a consensus on the development and utilization of renewable energy and promote energy transition in the process of social and economic development. Therefore, in the absence of other mandatory policy tools, quantitative and clear energy transition targets were expected to provide a strong constraint and incentive for local governments through target assessment or political incentives. Thus, the clean, low-carbon, safe, and efficient use of energy is promoted, and the high-quality development of social modernization is accelerated. The 13th Five-Year Plan proposes establishing a new type of power operation mechanism and tariff formation mechanism, as well as to implement a green certificate system for renewable energy power. The goal-oriented renewable energy development has strengthened the role of market players. In addition to its decisive role in the allocation of resources in the market, planning also allows for the active innovation of macro-regulation methods and means, such as codifying the fully guaranteed acquisition management approach for renewable energy generation, and for the establishment of a new coal power frequency regulation and peak compensation mechanism. To promote the application of new energy, regions are encouraged to establish energy transition demonstration cities and rural energy transition demonstration counties. According to the 14th Five-Year Plan for Renewable Energy Development, by 2020, renewable energy generation should have reached 2.2 trillion kWh, and the installed renewable energy generation capacity should have reached 934 million kW [55]. During the 13th Five-Year Plan period, breakthrough achievements have been made in the level of utilization of renewable energy, technology, equipment, and industrial competitiveness, thereby laying a solid foundation for the green and low-carbon transformation of energy in the new path towards building a modern socialist country.
In fs-QCA, researchers adopt certain subjective choices in the selection and confirmation of cases, policy assignments, and qualitative anchor settings. Changes in these choices can, to a certain extent, affect the final path of the study. Based on this basic characteristic of qualitative comparative research, robustness tests were conducted by varying the consistency thresholds. The consistency thresholds were raised from 0.8 to 0.85 and 0.9, while other treatments remained unchanged. The obtained conditional groupings and corresponding parameters remained unchanged; therefore, the results presented in this study can be considered to be robust.

6. Discussion

Since the oil energy crisis, there has been a general focus on energy-related policy adjustments around the world. There are both differences and commonalities in the energy policies of various countries. For the EU, innovation is an important part of its energy policies. The new version of the Strategic Energy Technology Plan (SET-Plan) published by the European Commission clearly placed innovation at the center of the transition to a low-carbon energy system. It was recently found that financial tools such as green bonds could be a beneficial aid to the development of green energy [56]. The EU has set up the EUR 17.5 billion Just Transition Fund to support the transition of fossil fuel-dependent regions [57]. The EU’s target system on energy transition is detailed to the end-use sectors and quantitative transition schemes have been developed through energy system modeling combined with data monitoring and reports. In order to address the slowness and complexity of the approval process for projects, the European Commission specifically revised the Renewable Energy Directive [58]. For the United States (US), which is abundant in fossil resources, it advocates the synergistic development of fossil energy and new energy sources for the purpose of stability in the economic order. Moreover, the US implemented specific policies at both the holistic level and specialized areas. Similar to the EU, the US has focused on the utilization of economic tools in promoting its energy clean-up strategies. The US, for example, has encouraged the reflow of manufacturing through high industrial subsidies [59]. The US has been developing clean energy infrastructure through diverse initiatives such as government purchases, tax support, and technology diffusion in the Bipartisan Infrastructure Deal [60].
After the Copenhagen Conference in 2009, China has been actively participating in the process of green development in the world. China has now established a diversified target system that covers energy restructuring and total carbon emission peaking [61], becoming the second largest country in the application of renewable energy. Yet there are still many weaknesses in the practical application of energy policy in China. Firstly, China has issued a large number of energy policies in the macro-planning category, and neglected laws and ordinances, which may weaken the control and binding power of energy policies. In the past decade, China formulated a number of highly coercive policies centered on subdivided energy sectors and industries. However, compared with the systematic promotion mechanism of the US and the EU, China’s energy policies are fragmented and poorly interconnected [62]. Secondly, there has been a distinct preference for the use of China’s energy policy tools. From the point of application, when it comes to environmental protection, carbon emissions, etc., the government prefers to use mandatory policy tools, which are often linked to the performance evaluation of officials [63]. However, according to the results of fs-QCA, mandatory policy tools are generally ineffective in promoting energy transition. With reference to the characteristics of energy policies in EU and the US, China has not made sufficient use of economic incentive-based policy tools. The role of economic incentive-based policy tools in energy transition pathways is not as evident as argued in previous studies [64]. Given China’s vast geographical extension and complex national conditions, the effectiveness of various policy tools for energy structure transformation is expected to have temporal and spatial variation. Accordingly, China’s energy structure transformation should take the advantages and disadvantages of various types of policy tools into account and explore the optimal allocation of policy tools.
Energy transition policies vary widely from country to country, but some consensus has developed among countries over time. The diversification and cleanliness of energy sources have become the objectives of national energy policies [65]. For example, the EU is accelerating its search for more energy suppliers after the war in Ukraine and is actively promoting green hydrogen as an alternative fuel [66]. It is worth noting, however, that as coal still dominates China’s energy consumption market, and a mature clean energy development and supply system has not yet been established, the excessive pursuit of energy cleanliness may exacerbate energy poverty [67]. In addition, technology is an extremely powerful way for countries to achieve their energy policy goals. In the existing literature, technological innovations and applications have been recognized as a central element in the resolution of the conflict between modern global economic growth and environmental protection [68]. The low-carbon transition of the energy system is a complicated project. In the long term, all countries need to accelerate the invention, popularization, and use of new energy technologies in order to seize the initiative in the context of fierce international competition. Meanwhile, there is also a necessity to maintain long-term dialogue and cooperation on sustainability issues and energy security and reshape alliances at the national and regional levels [69], which can further contribute to stable, inclusive, and green development globally.

7. Conclusions

It is important to explore the path of energy structure transition to achieve sustainable economic growth. The main goal of this study was to seek the path of energy structure transition—how policy goals, policy tools, and policy intensity as the key elements of energy policies promote the realization of energy transition. Based on a policy tool perspective, in this study, an fs-QCA method was proposed and policy texts from 2001 to 2020 were taken as research objects. The results showed how the collaborative drive between different condition variables affects China’s energy structure transformation from a complex cause-and-effect relationship.
This study found that energy restructuring has multiple, concurrent causal relationships. These paths can be summarized into three types, according to differences in the core variables: the “multiple objectives + information”-driven model; the “single objective + information”-driven model; and “the single objective”-driven model. In our study, it can be seen that the policy objective of energy cleanliness is present in almost every pathway. It showed that energy structure transition relied on the degree of clarity of energy cleanliness goals. For the Chinese government, the strategic objectives of the energy structure transition were disaggregated, and the assessment results were used as an essential indicator for performance evaluation. The clearer the energy strategy goal, the more binding, and the greater the reduction in the operational space in the decomposition of energy planning goals, as well as the enhancement of the driving force of the downward implementation of the goal. The results of this study also showed that information policy tools played a key role in ensuring the energy transition. Information tools appeared as core variables in six of the seven conditional configuration paths, indicating the key position of information technology in energy restructuring.
This study investigated China’s energy policy at the national level. Through a histogram analysis of the energy structure transition, the evolutionary logic behind the energy structure adjustment was explained comprehensively and effectively. However, energy structure transition is a system that involves various fields such as economy, society, environment, etc. Because of the complexity of the problem and the limitations in the individual knowledge, this study has some deficiencies, which should be further addressed. This study mainly focused on the pathways of the energy structure transition and performed a qualitative analysis at the macro level, thus excluding regional and provincial energy policies, which may result in some details being overlooked. Owing to the characteristics of the fs-QCA methodology, our study lacked consideration of control variables. So apart from the three major factors we have proposed, there may be other political factors affecting the energy structure transition. Moreover, the pathway for energy structure transformation may vary according to a country’s environmental and economic situation. We may not yet be able to provide more useful insights from our results for countries that differ significantly from China’s average level of energy production and consumption. In terms of research methodology, qualitative comparative analysis involves the assignment of values to different indicators and data calibration, which include a number of subjective factors. Although robustness tests were performed to avoid biases in the results, the handling of the data inevitably affected the final results. Therefore, objective energy statistics should be supplemented in future studies. On the basis of more quantitative data, the path of energy structure transition at the micro level in China can be explored, so as to further expand the depth and breadth of this study.

Author Contributions

Conceptualization, H.S.; methodology, H.S. and L.C. (Long Cheng); software, H.S.; validation, J.L. and L.C. (Long Cheng); formal analysis, H.S.; investigation, H.S. and L.C. (Long Cheng); resources, J.L.; data curation, H.S.; writing—original draft preparation, H.S.; writing—review and editing, J.L. and L.C. (Long Cheng); visualization, J.L.; supervision, J.L.; project administration, L.C. (Lei Chu); funding acquisition, J.L. and L.C. (Long Cheng). All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Natural Science Foundation of China (Grant No. 42001192, 42201276) and the Key Projects of Philosophy and Social Sciences of the Ministry of Education of China (Grant No. 21JZD014).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author/s.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Lin, B.Q.; Zhan, Y.H.; Sun, C.W. Study on collaborative development of energy supply and demand for carbon neutrality. Gov. Res. 2022, 38, 24–34+125. [Google Scholar]
  2. Liu, X.L.; Cui, L.L.; Li, B.; Du, X.W. Study on the path of China’s high quality energy development under the carbon neutrality target. J. Beijing Univ. Technol. (Soc. Sci. Ed.) 2021, 23, 1–8. (In Chinese) [Google Scholar]
  3. Kong, Y.; Feng, C.; Yang, J. How does China manage its energy market? A perspective of policy evolution. Energy Policy 2020, 147, 111898. [Google Scholar] [CrossRef]
  4. Li, H.; Xu, M.X.; Zhang, Q. A review of China’s energy policy in the 40 years of reform and opening up: From structure to logic. China Popul. Resour. Environ. 2019, 29, 167–176. [Google Scholar]
  5. Gu, H.B.; Zhang, S. A measurable study of China’s energy transition and comparison with the United States and Germany. Acad. Res. 2017, 84–91. (In Chinese) [Google Scholar]
  6. Li Keqiang Chaired a Meeting of the National Energy Commission. 2021. Available online: http://www.gov.cn/xinwen/2021-10/11/content_5641907.htm (accessed on 20 December 2023).
  7. Iyer, G.; Ledna, C.; Clarke, L.E.; Edmonds, J.; McJeon, H.; Kyle, P.; Williams, J.H. Measuring progress from nationally determined contributions to mid-century strategies. Nat. Clim. Chang. 2017, 7, 871–874. [Google Scholar] [CrossRef]
  8. Oshiro, K.; Kainuma, M.; Masui, T. Implications of Japan’s 2030 target for long-term low emission pathways. Energy Policy 2017, 110, 581–587. [Google Scholar] [CrossRef]
  9. Capros, P.; Zazias, G.; Evangelopoulou, S.; Kannavou, M.; Fotiou, T.; Siskos, P.; De Vita, A.; Sakellaris, K. Energy-system modelling of the EU strategy towards climate-neutrality. Energy Policy 2019, 134, 110960. [Google Scholar] [CrossRef]
  10. Rahman, M.M.; Sultana, N.; Velayutham, E. Renewable energy, energy intensity and carbon reduction: Experience of large emerging economies. Renew. Energy 2022, 184, 252–265. [Google Scholar] [CrossRef]
  11. Tagliapietra, S.; Zachmann, G.; Edenhofer, O.; Glachant, J.-M.; Linares, P.; Loeschel, A. The European union energy transition: Key priorities for the next five years. Energy Policy 2019, 132, 950–954. [Google Scholar] [CrossRef]
  12. Li, R.; Wang, X.; Wang, Q. Does renewable energy reduce ecological footprint at the expense of economic growth? An empirical analysis of 120 countries. J. Clean. Prod. 2022, 346, 131207. [Google Scholar] [CrossRef]
  13. Gardumi, F.; Keppo, I.; Howells, M.; Pye, S.; Avgerinopoulos, G.; Lekavičius, V.; Galinis, A.; Martišauskas, L.; Fahl, U.; Korkmaz, P.; et al. Carrying out a multi-model integrated assessment of European energy transition pathways: Challenges and benefits. Energy 2022, 258, 124329. [Google Scholar] [CrossRef]
  14. Granado, P.C.; Resch, G.; Holz, F.; Welisch, M.; Geipel, J.; Hartner, M.; Forthuber, S.; Sensfuss, F.; Olmos, L.; Bernath, C.; et al. Energy transition pathways to a low-carbon Europe in 2050: The degree of cooperation and the level of decentralization. Econ. Energy Environ. Policy 2020, 9, 121–135. [Google Scholar]
  15. Bashir, M.A.; Sheng, B.; Doğan, B.; Sarwar, S.; Shahzad, U. Export product diversification and energy efficiency: Empirical evidence from OECD countries. Struct. Chang. Econ. Dyn. 2020, 55, 232–243. [Google Scholar] [CrossRef]
  16. Aghabalayev, F.; Ahmad, M. Does innovation in ocean energy generations-related technologies in G7 countries reduce carbon dioxide emissions? Role of international collaboration in green technology development and commercial and monetary policies. Environ. Sci. Pollut. Res. 2022, 30, 14545–14564. [Google Scholar] [CrossRef]
  17. Schiederig, T.; Tietze, F.; Herstatt, C. Green Innovation in technology and innovation management: An exploratory literature review. Soc. Sci. Electron. Publ. 2012, 42, 180–192. [Google Scholar] [CrossRef]
  18. Rogge, K.S.; Reichardt, K. Policy mixes for sustainability transitions: An extended concept and framework for analysis. Res. Policy 2016, 45, 1620–1635. [Google Scholar] [CrossRef]
  19. Zou, C.N.; Pan, S.Q.; Dang, L.S. The energy revolution and the mission of science and technology. J. Southwest Pet. Univ. (Nat. Sci. Ed.) 2019, 41, 1–12. [Google Scholar]
  20. Zhang, S.L.; Wang, N. Energy transition and future energy investment in China. Chin. Econ. Rep. 2018, 69–71. (In Chinese) [Google Scholar]
  21. Yi, W.J.; Liang, Q.; Pei, Q.B. Application and progress of hydrogen energy for clean and low-carbon transition of China’s energy system. Environ. Prot. 2018, 46, 30–34. [Google Scholar]
  22. Li, Y.H.; Kong, L. Development of solar and wind power generation technologies to accelerate China’s energy transition. Proc. Chin. Acad. Sci. 2019, 34, 426–433. [Google Scholar]
  23. Ma, L.M.; Shi, D.; Pei, Q.B. Low carbon energy transition in China (2015–2050): Renewable energy development and feasible pathways. China Popul. Resour. Environ. 2018, 28, 8–18. [Google Scholar]
  24. Fan, L.; Zhang, Y.Y.; Jin, M.L.; Ma, Q.; Zhao, J. Does new digital infrastructure promote the transformation of the energy structure? The perspective of China’s energy industry Chain. Energies 2022, 15, 8784. [Google Scholar] [CrossRef]
  25. Kurramovich, K.K.; Abro, A.A.; Vaseer, A.I.; Khan, S.U.; Ali, S.R.; Murshed, M. Roadmap for carbon neutrality: The mediating role of clean energy development-related investments. Environ. Sci. Pollut. Res. 2022, 29, 34055–34074. [Google Scholar] [CrossRef] [PubMed]
  26. Shahbaz, M.; Sinha, A.; Raghutla, C.; Vo, X.V. Decomposing scale and technique effects of financial development and foreign direct investment on renewable energy consumption. Energy 2022, 238, 121758. [Google Scholar] [CrossRef]
  27. Li, K.; Lin, B. How to promote energy efficiency through technological progress in China? Energy 2018, 143, 812–821. [Google Scholar] [CrossRef]
  28. Zhuo, Y.; Zheng, Y.F. New strokes for identifying and categorizing government tools. Chin. Public Adm. 2020, 102–107. (In Chinese) [Google Scholar] [CrossRef]
  29. Tang, B.J.; Chen, J.Y.; Wang, C.Z. Analysis of development differences in the energy sector from the perspective of policy instruments. J. Beijing Univ. Technol. (Soc. Sci. Ed.) 2022, 24, 21–27. [Google Scholar]
  30. Chen, Z.M. The study of governmental instruments and the improvement of governmental management style—On the rise, themes and significance of the study of governmental instruments as a new branch of public management studies. Chin. Public Adm. 2004, 43–48. (In Chinese) [Google Scholar]
  31. Huang, H.H. Emergence of policy instruments theory of and its development in China. J. Soc. Sci. 2010, 13–19+187. (In Chinese) [Google Scholar]
  32. Bertoldi, P.; Mosconi, R. Do energy efficiency policies save energy? A new approach based on energy policy indicators (in the EU Member States). Energy Policy 2020, 139, 111320. [Google Scholar] [CrossRef]
  33. Huang, Y.J.; Gan, J.W.; Liu, B.L.; Zhao, K. Environmental policy and green development in urban and rural construction: Beggar-thy-neighbor or win-win situation? J. Clean. Prod. 2024, 446, 141201. [Google Scholar] [CrossRef]
  34. Razzaq, A.; Sharif, A.; Ozturk, I.; Yang, X. Central inspections of environmental protection and transition for low-carbon Chinese cities: Policy intervention and mechanism analysis. Energy Econ. 2023, 124, 106859. [Google Scholar] [CrossRef]
  35. Wang, L.Z.; Zhang, Y.J. Research on policy synergy in China’s new energy vehicle industry—A three-dimensional framework based on structure, process and content. Chin. Public Adm. 2017, 101–107. (In Chinese) [Google Scholar]
  36. Nagaj, R.; Gajdzik, B.; Wolniak, R.; Grebski, W.W. The Impact of Deep Decarbonization Policy on the Level of Greenhouse Gas Emissions in the European Union. Energies 2024, 17, 1245. [Google Scholar] [CrossRef]
  37. Pan, J.Y.; Du, L.Z.; Wu, H.T.; Liu, X. Does environmental law enforcement supervision improve corporate carbon reduction performance? Evidence from environmental protection interview. Energy Econ. 2024, 132, 107441. [Google Scholar] [CrossRef]
  38. Li, L.Y.; Fan, F.M.; Liu, X.D. China’s rural energy policy in the perspective of policy instruments. Coal Econ. Res. 2021, 41, 41–47. [Google Scholar]
  39. Zhou, G.X.; Pei, P.P.; Tan, Y.X. Research on China’s “Goal-Tool” synergy of inclusive financial policies: A quantitative analysis based on the policy texts from 2016 to 2022. Financ. Theory Teach. 2024, 42, 9–20. [Google Scholar]
  40. Yang, K.R.; Ban, A.; Shi, K.; Shi, W.J. Compatibility of policy objectives and policy tools about China’s chip industry policy: An analysis based on text quantification. Sci. Technol. Prog. Policy 2024, 41, 85–95. [Google Scholar]
  41. Howlett, M.; Ramesh, M.; Perl, A. Studying Public Policy: Policy Cycles and Policy Subsystems; Oxford University Press: Oxford, MA, USA, 2009. [Google Scholar]
  42. Zhang, C.; Zheng, X.J.; Wang, F.B. The application of qualitative comparative analysis in the study of management constructs: A review and prospect. Foreign Econ. Manag. 2017, 39, 68–83. [Google Scholar]
  43. Du, Y.Z.; Jia, L.D. Group perspective and qualitative comparative analysis (QCA): A new path for management research. Manag. World 2017, 155–167. [Google Scholar] [CrossRef]
  44. Mi, L.L.; Yang, J. Evaluation of the effectiveness and effectiveness of energy conservation guidance policies for residential life in China—A quantitative analysis based on Chinese policy texts from 1996–2015. Resour. Sci. 2017, 39, 651–663. [Google Scholar]
  45. Cantarero, V.; Mercedes, M. Of renewable energy, energy democracy, and sustainable development: A road map to accelerate the energy transit ion in developing countries. Energy Res. Soc. Sci. 2020, 70, 101716. [Google Scholar] [CrossRef]
  46. Li, J.J.; Wang, N. China’s Energy Transition and Path Selection. Adm. Reform 2019, 65–73. (In Chinese) [Google Scholar] [CrossRef]
  47. Li, H.; Tu, J.H. Research on the grouping of energy low-carbon transition factors from a multi-level perspective—A qualitative comparative analysis of fuzzy sets based on 30 provincial areas in China. Technol. Econ. 2020, 39, 152–160. [Google Scholar]
  48. Zhu, H.; Zheng, J.; Zhao, Q.Y.; Kou, D.X. Economic growth, energy structure transformation and carbon dioxide emission—Empirical analysis based on panel data. Res. Econ. Manag. 2020, 41, 19–34. [Google Scholar]
  49. Shao, S.; Li, X.; Cao, J.H. Urbanization promotion and haze pollution governance in China. Econ. Res. J. 2019, 54, 148–165. [Google Scholar]
  50. Lee, Y.; Kim, B.; Hwang, H. Which institutional conditions lead to a successful local energy transition? Applying fuzzy-set qualitative comparative analysis to solar PV cases in South Korea. Energies 2020, 13, 3696. [Google Scholar] [CrossRef]
  51. Zheng, Y.; Zhao, S.J.; Bao, X.H. Quantitative research on China’s provincial renewable energy policies based on a four-dimensional analysis framework. Resour. Dev. Mark. 2024, 1–18. (In Chinese) [Google Scholar]
  52. Xie, X.Y.; Xue, Y. A survey on the innovation efficiency improvement path of new energy vehicle enterprises from the perspective of dual innovation—Based on fuzzy set qualitative comparative analysis (fs-QCA). Manag. Mod. 2021, 41, 45–48. [Google Scholar]
  53. Zeng, S.H.; Li, G.; Weng, Z.X.; Li, T.F. Research on China’s energy transition pathway towards carbon peaking and carbon neutrality targets. Environ. Prot. 2021, 49, 26–29. [Google Scholar]
  54. National Statistical Office. Statistical Yearbook of China; Chinese Statistics Press: Beijing, China, 2021. [Google Scholar]
  55. Notice on the Issuance of the 14th Five-Year Plan for the Development of Renewable Energy. 2022. Available online: https://www.ndrc.gov.cn/xwdt/tzgg/202206/t20220601_1326720.html (accessed on 20 December 2023).
  56. Jin, C.; Lv, Z.W.; Li, Z.R.; Sun, K. Green finance, renewable energy and carbon neutrality in OECD countries. Renew. Energy 2023, 211, 279–284. [Google Scholar]
  57. Zhang, Q.Z.; Wang, W.T.; Chen, W.Y. Energy and climate policies of the EU and UK and their implications. China Popul. Resour. Environ. 2023, 33, 81–91. [Google Scholar]
  58. REPower EU Affordable, Secure and Sustainable Energy for Europe. 2022. Available online: https://commission.europa.eu/strategy-and-policy/priorities-2019-2024/european-green-deal/repowereu-affordable-secure-and-sustainable-energy-europe_en#how-repowereu-is-funded (accessed on 26 September 2024).
  59. Xu, Y.R.U.S. Energy strategy and institutional changes of its energy governance. Chin. J. Am. Stud. 2024, 38, 66–91+6–7. [Google Scholar]
  60. Fact Sheet: The Bipartisan Infrastructure Deal. 2021. Available online: https://www.whitehouse.gov/briefing-room/statements-releases/2021/11/06/fact-sheet-the-bipartisan-infrastructure-deal/ (accessed on 26 September 2024).
  61. Tang, Y.N.; Yan, R.X.; Zhou, Y.L. Structural representation and optimization path of energy policy under carbon neutral vision. J. Tsinghua Univ. (Nat. Sci. Ed.) 2022, 63, 1–14. [Google Scholar]
  62. Li, L.C.; Liu, Q.; Chen, W.; Tang, Y.; Chen, J. Research and implications of the US clean energy strategy. Bull. Chin. Acad. Sci. 2024, 39, 1348–1364. [Google Scholar]
  63. Jiang, Q.S.; Tang, P.C. All roads lead to Rome? Carbon emissions, pollutant emissions and local officials’ political promotion in China. Energy Policy 2023, 181, 113700. [Google Scholar] [CrossRef]
  64. Sun, X.M.; Yan, S. The driving path for low-carbon transformation of resource-dependent cities under the TOE frame work: An fs-QCA research based on 108 resource-dependent cities in China. Sci. Technol. Prog. Policy 2023, 40, 72–81. [Google Scholar]
  65. Su, X.; Tan, J.L. Regional energy transition path and the role of government support and resource endowment in China. Renew. Sustain. Energy Rev. 2023, 174, 113150. [Google Scholar] [CrossRef]
  66. Sandri, S.; Hussein, H.; Alshyab, N.; Sagatowskib, J. The European Green Deal: Challenges and opportunities for the Southern Mediterranean. Mediterr. Politics 2023, 1–12. [Google Scholar] [CrossRef]
  67. Karpinska, L.; Smiech, S. Will energy transition in Poland increase the extent and depth of energy poverty? J. Clean. Prod. 2021, 328, 129480. [Google Scholar] [CrossRef]
  68. Gielen, D.; Boshell, F.; Saygin, D.; Bazilian, M.D.; Wagner, N.; Gorini, R. The role of renewable energy in the global energy transformation. Energy Strategy Rev. 2019, 24, 38–50. [Google Scholar] [CrossRef]
  69. Schuetze, B.; Hussein, H. The geopolitical economy of an undermined energy transition: The case of Jordan. Energy Policy 2023, 180, 113655. [Google Scholar] [CrossRef]
Sustainability 16 08703 g001
Figure 1. Theoretical framework.
Figure 1. Theoretical framework.
Sustainability 16 08703 g001
Table 1. List of the energy policy documents published from 2001 to 2020 analyzed in this study.
Table 1. List of the energy policy documents published from 2001 to 2020 analyzed in this study.
IDYearName of Policy DocumentPublishing Department
(Abbreviation)
12001The 10th Five-Year Plan for Energy Conservation and Comprehensive Utilization of ResourcesSETC, PRC
22001The 10th Five-Year Plan for National Ecological Environmental ProtectionEPA, NPC, SETC, MOF, PRC
32003China’s Outline of Action for Sustainable Development at the Beginning of the 21st CenturySC, PRC
42004Energy Efficiency Labeling Management ApproachNDRC, AQSIQ, PRC
52004Medium and Long-term Special Planning for Energy SavingNDRC, PRC
62005Establishment of National Energy Leadership Group (expired in 2015)General Office of the SC, PRC
72005Notice on Strengthening Environmental Protection in Hydropower ConstructionEPA, NDRC, PRC
82005Several Opinions on Promoting the Healthy Development of the Coal IndustrySC, PRC
92005Several Opinions on Accelerating the Development of Circular EconomySC, PRC
102005Notice on the Issuance of Interim Measures for the Management of Land Use and Environmental Protection of Wind Farm ProjectsNDRC, MOLR, EPA, PRC
112005On the Release and Implementation of the Interim Provisions to Promote Industrial RestructuringSC, PRC
122006Decision on Strengthening Energy ConservationSC, PRC
132007The 11th Five-Year Plan for Energy DevelopmentNDRC, PRC
142007Notice on the Issuance of a Comprehensive Work Program of Energy Conservation and Emission ReductionSC, PRC
152007The 11th Five-Year Plan for Renewable Energy DevelopmentNDRC, PRC
162007National Action Implementation Plan for Energy Saving and Emission ReductionNDRC, PD of the CPC Central Committee, PRC
172007Energy Conservation Law of the People’s Republic of ChinaThe 13th Session of the Standing Committee of the 10th National People’s Congress, PRC
182010Notice on Further Strengthening the Work of Eliminating Backward Production CapacitySC, PRC
192010Notice on the Promotion of Joint Prevention and Control of Air Pollution Work to Improve Regional Air Quality GuidanceEPA, NDRC, MOST, MOIIT, MOF, MOHURD, MOT, MOFCOM, NEA, PRC
202010Notice on the Clean-up of High Energy-consuming Enterprises with Preferential TariffNDRC, SERC, NEA, PRC
212011The 12th Five-Year Plan for Comprehensive Work Plan of Energy Conservation and Emission ReductionSC, PRC
222011The 12th Five-Year Plan for National Environmental ProtectionSC, PRC
232012Energy-saving and New Energy
Vehicle Industry
Development Plan (2012–2020)		SC, PRC
242012The 12th Five-Year Plan for Energy Saving and Emission ReductionSC, PRC
252013The 12th Five-Year Plan for Energy DevelopmentNDRC, NEA, PRC
262014The Plan for Energy-saving Emission Reduction and Low-carbon Development Action from 2014 to 2015General Office of the SC, PRC
272014The Strategic Action Plan for Energy Development (2014–2020)General Office of the SC, PRC
282015Guidance on the Promotion of Scientific Development of the Coal IndustryNEA, PRC
292016Notice on Promoting the Orderly Development of Coal Power in ChinaNDRC, NEA, PRC
302016The 13th Five-Year Plan for Ecological Environmental ProtectionSC, PRC
312016The 13th Five-Year Plan for Renewable Energy DevelopmentNDRC
322016The 13h Five-Year Plan Comprehensive Work Plan for Energy Conservation and Emission ReductionSC, PRC
332016The 13th Five-Year Plan for Energy DevelopmentNDRC, NEA, PRC
342016Energy Production and Consumption Revolution Strategy (2016–2030)NDRC, NEA, PRC
352017Guidance on Promoting the Development of Energy Storage Technology and IndustryNDRC, MOF, MOST, MIIT, NEA, PRC
362018Several Opinions on Promoting the Coordinated and Stable Development of Natural GasSC, PRC
372019Notice on the Establishment of Electricity Consumption Guarantee Mechanism of Renewable EnergyNDRC, NEA, PRC
382020Notice on Further Improvement of Coal Power Industry to Eliminate Backward Production CapacityNEA, PRC
392020Guidance on Energy Work in 2020NEA, PRC
Table 2. Scoring criteria of energy policy tools.
Table 2. Scoring criteria of energy policy tools.
Type of Policy ToolContent of the Assessment
Administrative
control tools		Establishment of mandatory access conditions, thresholds, and standards; establishment of relevant assessment, standards, as well as supervision and inspection methods of energy restructuring; establishment of a mandatory phase-out of high energy-consuming product directory; strict carrying out of environmental impact assessment on administrative approval projects; establishment of a mandatory management approach specifically to promote energy restructuring
Economic incentive toolsStrong support for financial budgets, subsidies, and incentives, and proposal of the amount of financial subsidies and incentives or support methods; vigorous promotion of energy restructuring in terms of price, cost, and metering; development of methods or programs to control energy production, energy consumption, and clean energy through the implementation of price and cost adjustments, as well as specific accounting methods or standards for related costs and prices
Information toolsVigorous guidance of market organizations or individuals to carry out energy conservation and utilization or technology development, the use of clean energy, and the development of specific implementation methods or programs; development of detailed guidance policy system and measures; development of detailed technology research, priorities, and programs; clear proposition to vigorously implement energy security, energy conservation, energy cleaning, and other related education and training; clear indication to establish a recommended catalog of products and energy adjustment-related guidance measures; clear implementation of technological innovation and other demonstration projects or pilots
Voluntary participation toolsDevelopment of specific measures to promote energy conservation and energy efficiency, such as the “Energy Campaign Week” and other specific promotional activities and methods; requirement for enterprises, governmental communities, and other units and individuals to implement the tool; development of the implementation plan to increase energy conservation and energy cleaning promotion, public participation in monitoring or evaluation of specific methods
Table 3. Scoring criteria for the transformation of the energy structure.
Table 3. Scoring criteria for the transformation of the energy structure.
Result
Variable		Content of the Assessment
Degree of energy structure transformationThe objectives of energy restructuring are clearly stated, the strength and direction of adjustments are proposed for each energy category, and specific quantitative indicators are proposed
Table 4. Qualitative anchor taking values for each variable.
Table 4. Qualitative anchor taking values for each variable.
Variable0.050.50.95
Energy security12.03
Energy conservation22.84
Energy cleanliness22.74
Administrative control tools33.54
Economic incentive tools22.43
Information tools1.52.54
Voluntary participation tools11.92.5
Policy intensity33.24
Degree of energy structure transformation12.34
Table 5. Results of the single-variable necessity analysis.
Table 5. Results of the single-variable necessity analysis.
Condition VariableHigh-Intensity Energy
Structure Transformation		~High-Intensity Energy Structure Transformation
ConsistencyCoverageConsistencyCoverage
Energy security0.6195230.6810980.3576540.457317
~Energy security0.5063780.4039820.7505960.696460
Energy conservation0.6816420.6771350.3872200.447383
~Energy conservation0.4437050.3836930.7205530.724700
Energy cleanliness0.6788690.7251190.3071060.381517
~Energy cleanliness0.4209650.3431290.7787320.738246
Administrative
control tools		0.6627840.5128760.6175490.555794
~Administrative
control tools		0.4259570.4891720.4587510.612739
Economic incentive tools0.7176930.6551900.3843590.408101
~Economic incentive tools0.3516360.3293510.6752500.735584
Information tools0.7221300.7618490.3328570.408426
~Information tools0.4392680.3614790.8059130.771338
Voluntary participation tools0.6716580.6621100.3943730.452160
~Voluntary participation tools0.4442600.3867700.7052930.714148
Policy intensity0.5119250.5445430.4372910.541003
~Policy intensity0.5684970.4648530.6318550.600907
Note: the “~” indicates the non-set of the corresponding variable.
Table 6. Combined constructions affecting the strength of the energy structure transition.
Table 6. Combined constructions affecting the strength of the energy structure transition.
VariableR1R2R3
R1aR1bR1cR2aR2bR2c
Energy security◎◎ Ⓧ◎◎◎
Energy conservation●●●●●ⓍⓍ
Energy cleanliness●●●ⓍⓍ●●
Administrative
control tools		Ⓧ◎◎◎◎ⓍⓍ
Economic incentive tools ◎◎◎◎Ⓧ◎
Information tools●●●●●●Ⓧ
Voluntary participation tools◎◎◎◎ⓍⓍ◎
Policy intensityⓍ ◎◎ⓍⓍⓍ
Consistency110.9591190.948617111
Raw
coverage		0.1724900.1525240.1691620.1331100.0892960.0998340.109262
Unique
coverage		0.0998340.0316140.0515810.0881860.0499170.0504720.043816
Consistency of the overall solution0.987065
Coverage of the overall solution0.550194
Note: ◎ and ● indicate that the condition appears; Ⓧ and Ⓧ indicate that the condition does not appear; ● and Ⓧ indicate that the element is a core condition; ◎ and Ⓧ indicate that the element is a marginal condition; and spaces indicate that the presence or absence of the element has no effect on the result.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Li, J.; Sun, H.; Cheng, L.; Chu, L. The Path Driving China’s Energy Structure Transformation from the Perspective of Policy Tools. Sustainability 2024, 16, 8703. https://doi.org/10.3390/su16198703

AMA Style

Li J, Sun H, Cheng L, Chu L. The Path Driving China’s Energy Structure Transformation from the Perspective of Policy Tools. Sustainability. 2024; 16(19):8703. https://doi.org/10.3390/su16198703

Chicago/Turabian Style

Li, Jintao, Hui Sun, Long Cheng, and Lei Chu. 2024. "The Path Driving China’s Energy Structure Transformation from the Perspective of Policy Tools" Sustainability 16, no. 19: 8703. https://doi.org/10.3390/su16198703

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop