The basic information about the literature data used in this study is given in Table 1. The study period runs from 2003 to 2023 and involves a total of 429 publications from 135 journals, with an average half-life of publications of 4.04 years, 19,847 references are cited in these publications. In addition, the author’s keywords and keywords plus used to conduct topic exploration are identified 1136 and 732 respectively, through which the article analyzed the main research trends in this research area. In publications studying the impact of geopolitics on energy security, 1001 authors are involved in the process of knowledge creation, of which 73 authors conducte their research independently.
Publication trend
Thomas Kuhn in The nature of scientific revolutions proposed that the process of scientific development is a “primitive science” to “conventional science” transformation, as well as the transition from one “conventional science” to another “conventional science” process. It was divided into several stages: the scientific development of the pre-scientific, conventional science, scientific crises, scientific revolutions and the new conventional science. The formation of a discipline has undergone a theoretical accumulation of the formation of the paradigm to the paradigm of paradigm change, and then produce a new paradigm of the process of the entire process of scientific development under the impetus of scientific revolutions, the entire scientific development process of the continuous cycle of development (Kuhn, 1970). Price’s proposed literature growth curve is consistent with Thomas Kuhn’s theory of scientific development, he believed that the growth of the literature shows a logical growth trend of the “S” curve, but the growth of the literature is not endless and will eventually stop at a certain K (Price, 1963). The mathematical expression for the theoretical model of the literature growth by the logistic curve is shown below:
$$F\left(t\right)=\frac{k}{1+{{a{\rm {e}}}}^{-{kbt}}},\,k,a,b > 0$$
(1)
where \(F\left(t\right)\) is the literature accumulation for the year, \(t\) is the time, \(k\) is the literature accumulation when the time tends to infinity, and is the maximum value of the literature accumulation, and \(a,{b}\) are the conditional parameters.
To examine trends and forecast future developments in the growth of publications related to geopolitics and energy security, and to test whether the growth of the literature in this area conforms to a logistic growth curve, we fit a logistic to the annual cumulative publications. The trend in annual cumulative publication growth was first fitted using Excel, and it was found that the cumulative literature was optimally fitted according to the exponential, which got \({R}^{2}=0.9873\). Subsequently, according to the curve trend to take k = 90,000, to determine \(a=1.9\) when the most consistent with the cumulative curve, at this time to get \(b=0.2576\), and ultimately got the logistic growth curve as shown in Fig. 3, the cumulative annual growth in the number of publications in the field of research in line with \(y=1.9{{\rm {e}}}^{0.2576t}\). Comparison with the logistic growth curve reveals that the growth of literature in the field is currently in the pre-growth phase of the logistic curve and may reach the horizontal phase of the logistic curve after the next few decades. In the pre-growth phase, the annual number of publications increases significantly in 2022–2023, from 65 to 135, probably due to the impact of the Russia–Ukraine conflict in 2022, which has redirected people’s attention to the study of geopolitics and energy security.
This figure illustrates the growth trend of literature in the study area, with the horizontal axis representing time and the vertical axis indicating the cumulative number of publications. The smaller part of the graph depicts the detailed trend of annual and cumulative numbers of articles published.
Geographical spatial distribution
Spatial analysis of geographic distribution can reveal collaborative networks related to the geographic distribution of publications. Therefore, Scimago and VOSviewer were combined to map the geographic collaborative network of national issuance volumes. A geo-visualization network of the distribution of publications and the collaboration between countries is shown in Fig. 4a and b. The area of the circles in the graph indicates how many publications there are, with larger circles representing more publications, and the connecting lines between the nodes of the different circles indicating the collaboration between countries. In terms of the geographical distribution of publications, countries in Asia, Europe, Australia, and the Americas make the greatest contribution to this field. Among Asian countries, China coveres 168 publications and have the highest number of publications in this field, followed by the United Kingdom (60), the United States of America (43), Germany (26), and Turkey (24). Most of the countries in Europe are involved in research outputs in this area, in addition to countries in the Middle East, which may be attributed to the increased interest in research related to oil security in the region due to resource abundance.
a Global geographic distribution of publications and collaboration networks. b Localized zoomed-in view of the collaboration network. c Chord map of the intensity of country collaboration. This figure illustrates a geographic network of collaboration in the field of geopolitics and energy security. Nodes indicate countries, with size indicating the number of country postings. Connecting lines indicate collaborations between countries. a indicates the global collaboration network of countries, b indicates the detailed collaboration networks in Europe, northern Africa, and western Asia, and c indicates the country collaboration chord map.
Nevertheless, an exclusive emphasis on the number of national publications to assess a country’s scientific output is inadequate. The quantity of publications in a country merely reflects its quantitative capacity, without incorporating the quality of these publications into the evaluation. Therefore, considering the availability of data, we counted the total number of citations of the countries through VOSviewer, ranked the two indicators, the number of publications of the countries and the total number of citations by entropy-weighted TOPSIS, and evaluated them using SPSSAU (project. T S, 2024), which evaluates the 67 countries that participated in the publications. The entropy-weighted TOPSIS initially identifies the positive and negative ideal solution values (A+ and A−) for the evaluation indexes. Thereafter, the distance values D+ and D− are calculated for each evaluation object concerning the positive and negative ideal solutions, respectively. Finally, the proximity of each evaluation object to the optimal solution (C) is determined, and the C is ranked. The final ranking of the top 10 countries is presented in Table 2.
As illustrated in the accompanying table, the composition of the top ten countries differes when considering both the quantity and quality of publications. China retains its position at the top of the list, with 168 publications garnering 3608 citations from scientists across the globe. The reasons may be explained in the following ways. Firstly, as the world’s largest energy consumer, China’s rapid economic growth has led to an ever-increasing demand for energy, which has driven a significant number of studies and publications on energy security and geopolitics. Secondly, the Chinese government attached great importance to energy security and geopolitics and has formulated a series of policies and strategies, as well as provided strong support and funding to promote research and development in related fields. Furthermore, China is a highly active participant in international collaboration and academic exchanges. With the advancement of the Belt and Road Initiative, China’s influence in the global energy market is increasing, which has led to a significant increase in the international attention and citation value of its research results. The second-ranked country is the United Kingdom, which has a total of 60 publications with a total of 2139 citations, and the third-ranked country is Pakistan, which has 22 publications with a total of 1407 citations.
In the national collaboration on publications, the study of geopolitics on energy security involves a total of 67 countries around the world, of which 59 countries have collaborative relationships. From the chord diagram of international research collaboration, the depth of the color of the connecting lines between countries indicates the intensity of their collaboration. In Fig. 4c, the color of the connecting line between China and the United Kingdom, the United States, Romania, Saudi Arabia, Turkey, Spain, and Vietnam is red, which indicates that the intensity of collaboration between China and these countries is higher than that between other countries and that China has more partners and higher collaboration credits in this field of research. In addition, it is found that the geographic distribution of articles in studies of geopolitics and energy security shows a clear energy-oriented country or geopolitical risk-oriented country, unlike previous academic research, the main geographic distribution of publications in this subject area is concentrated in energy-rich or geopolitically risk-intensive areas, gradually moving away from the geographic distribution trend where the level of economic development leads to the distribution of scientific research.
Contribution of institution
In terms of meso-institutional collaboration, a total of 686 institutions around the world are involved in the research, forming a large network of institutional collaboration. The number of publications and the collaboration between them is shown in Fig. 5. As can be seen from Fig. 5, Qingdao University (China) has an outstanding research performance in this field, with 23 publications and a total of 782 citations. Meanwhile, Qingdao University has formed collaborative relationships with 33 domestic and foreign organizations, and the intensity of collaboration is 53. These institutions include the Lebanese American University, the Central University of Punjab, and the University of Southampton. The organizations within China are Qilu University of Technology, Southwest Jiaotong University, and Anhui University of Finance and Economics. The study of geopolitical impacts on energy security has resulted in 27 collaborative groups, which have worked together on a wide range of research topics.
This figure depicts a collaborative network of institutions. Nodes represent institutions, and lines between nodes indicate collaborative relationships between institutions. Nodes of the same color indicate similar research content.
Contribution of authorCore author distribution
Lotka’s Law describes the distribution of the frequency of scientific productivity: in a given field of study, the number of authors writing \(n\) papers are approximately \(\frac{1}{{n}^{2}}\) of the number of authors writing 1 paper. The proportion of all authors writing 1 paper to the total number of authors is approximately 60% (Lotka, 1926; Tsai, 2015). To test whether Lotka’s Law applies to this field of study, we analyzed it using Lotka’s Law and verified the reliability of the law using nonparametric hypothesis testing. The K–S test is a useful nonparametric hypothesis testing method that is primarily used to test whether a set of samples comes from a certain probability distribution. We followed the following steps to test.
-
(1)
Firstly, the data used for the calculations were prepared according to Table 3, which shows the number of authors with \(x\) publications, the total number of publications, the cumulative number of publications and the cumulative number of authors, as well as the cumulative percentage.
Table 3 Calculation of author productivity. -
(2)
Secondly, the data in Table 4 were used to calculate the exponent of Lotka’s Law, which was calculated from the least squares formula:
$$n=\frac{N\sum {XY}-\sum X\sum Y}{N\sum {X}^{2}-{(\sum X)}^{2}}=-2.6636$$
(2)
Thus, the absolute value of the exponent \(n\) is between 1.2 and 3.8, in accordance with Lotka’s Law.
-
(3)
Subsequently, \(c\) and critical value were calculated by the following equation:
$$c=\frac{1}{{\sum }_{1}^{p-1}\frac{1}{{x}^{n}}+\frac{1}{(n-1){p}^{n-1}}+\frac{1}{{2p}^{n}}+\frac{n}{{24(p-1)}^{n+1}}}$$
(3)
$${{\rm {critical}}\; {\rm {value}}}=\frac{1.63}{\sqrt{\sum Y}}$$
(4)
Calculated to get c = 0.7907, \({{\rm {critical}}\; {\rm {value}}}=0.3781\).
-
(4)
Finally, a nonparametric hypothesis test K–S test in Table 5 was conducted to test the reliability of Lotka’s Law.
$$D={{\rm {Max}}}{\rm{|}}{F}_{{\rm {O}}}\left(x\right)-{S}_{n}\left(x\right){\rm{|}}=0.0839$$
(5)
Therefore, the absolute value \({D}_{\max }=0.0839\, was calculated by the above steps, and hence it can be concluded that Lotka’s Law is valid in this subject area.
Co-author network
From the above analysis, it is clear that the author-output pattern of geopolitical impact on energy security is consistent with Lotka’s Law, to further explore patterns of author collaboration in this area, we used VOSviewer to map the network of author collaborations.
As shown in Fig. 6, there are 13 author collaborations in academic publications that examine the impact of geopolitics on energy security. One of the outstanding contributing authors in the field is Su Chi-Wei, who has contributed 14 scholarly publications and forms a collaborative cluster with 40 other authors. This is followed by Khan, Khalid (11 publications) with collaborative links with 32 authors, Umair, Muhammad (10 publications) with academic collaborations with 28 authors, and Qin, Meng, and Ma, Feng who have the same number of publications, both contributing 7 articles to the academic community. But Ma, Feng has more collaborations with other researchers, collaborating with 23 researchers, while Qin, Meng has collaborations with 21 authors. As shown in (a) of Fig. 6, among the top 5 authors in terms of number of publications, three authors are from China. In addition, from the time plot of the authors’ publication volume and collaborative networks, the node colors are dark to light indicating that the authors published their research papers from far to near. The collaborative cluster of authors led by Ma, Feng has a long-standing interest in this research area, with their research focusing on the market impact of uncertainty in geopolitical risk and volatility in crude oil prices. Su chi-wei, Khan, Khalid, Umair, Muhammad, and Qin, Meng are late researching this area. Their team published papers between 2021 and 2023 that examined the interactions between renewable energy, the energy transition, oil prices, and geopolitical risks. These contributions have helped to advance the field. It can also be seen in Fig. 6 that in the fringe group of the author collaboration network, the fringe authors tend to be publishers of recent publications and have not yet formed larger collaborative clusters and these fringe authors may be transformed into center authors in future studies.
a Collaboration network of the top 5 authors in terms of number of publications. b Author collaborative evolutionary networks. This figure depicts the authors’ collaborative network and its temporal evolution. Nodes represent authors, and connecting lines between nodes indicate collaborative relationships between them. Nodes of the same color indicate similar research content.
Contribution of journals
The geopolitical impact on energy security cuts across multiple disciplinary areas and has been analyzed from multiple publications, with the contribution of journals to the field assessed through the number of articles published in them. Information on the types of journals that ranks among the top 10 by the number of articles published in the field is shown in Table 6. Resources Policy has the highest focus on the topic of geopolitical influences on energy security, publishing 66 articles, and as can be seen from Fig. 7, Resource Policy shows a sharp increase in the number of articles published after 2022, possibly due to the increased global energy risks resulting from the Russia-Ukraine conflict, which has become a popular topic of choice for the journal. This is followed by Energy Policy (33 articles), Energy Economics (27 articles), Energy Research & Social Science (17 articles), and Energy (16 articles). Among the top 5 journals, journals in the field of energy and resources receive more attention than other fields. In addition, the co-citation network of journals (Fig. 8) shows the common citation relationships between publications published in different journals, with the thickness of the connecting line indicating the strength of the citation. Resources Policy and Energy Economics are the journals with the highest strength of connectivity, and articles in these two journals have the highest number of citations, suggesting that the content of articles published in Resources Policy and Energy Economics are highly similar in terms of research direction.
This figure illustrates the annual publication trend for the top 10 journals in terms of the number of articles published. The horizontal axis represents the year while the vertical axis depicts the number of articles published by the journal.
This figure depicts the journal citation network, where nodes represent journals, and connecting lines indicate citation relationships between papers published in the journals.
To further clarify the distribution of core journals in this subject area of geopolitical impact on energy security, the Bradford distribution of core journals was mapped using the Rstudio. Bradford’s Law describes the uneven distribution of scientific articles across journals due to differences in closeness between specialized disciplines (Bradford, 1934). Journals can be classified into three categories based on the number of articles published. The ratio of the number of journals in each group is \(1:a:{a}^{2}\) (Yang et al., 2016), which indicates that a large number of specialized papers are first concentrated in a few core journals, with some papers appearing in other journals related to the specialty. Bradford’s Law has been widely used to study different subject trends. Based on the information provided in the data in Table 7, the journals are categorized into three regions, each of which carries approximately the same number of articles. As can be seen in Fig. 9, the core journals in this subject area are mainly Resources Policy, Energy Policy, Energy Economics, Energy Research & Social Science. Journals in the core zone account for 2.96% of all journals and publish 33.33% of the articles in the field. Journals in the relevant journals account for 14.07% of the total number of journals and publish 33.8% of the articles in the field, while journals in the discrete journals account for 82.96% of the total number of journals and publish 32.87% of the articles in the field as shown in Table 8. The four journals, Resources Policy, Energy Policy, Energy Economics, and Energy Research & Social Science, are more concerned with geopolitics and energy security. Researchers engaged in this field may therefore consider these journals as a source of knowledge.
This figure illustrates the distribution of core journals within the field of study. The horizontal axis represents the journal category, the vertical axis represents the number of journal publications, and the shaded area represents the range of core journals.
Contribution of core literature
We used VOSviewer to map the literature coupling network of geopolitical impact studies on energy security to explore the most influential academic literature in the field, as shown in Fig. 10, where the node size indicates the total number of citations to the article and the connecting lines indicate the coupling relationships. Concurrently, the academic literature that has been cited the most is highlighted, and the detailed information of the top 10 most cited articles is listed in Table 9, including the title of the article, the first author, the country of affiliation, publication year, the total number of citations, the journal of publication, and the DOI of the literature. As illustrated in it, the literature with the greatest number of citations is Lynne Chester’s article Conceptualizing Energy Security and Making Explicit Its Polysemic Nature, published in Energy Policy in 2010. This article has been cited a total of 310 times since its initial publication, and it is widely recognized within the industry as a highly cited document in this subject area. This article presented an early research explanation of the conceptualization of energy security. It addressed the multifaceted connotations of energy security, the market paradigm, and its multidimensional nature from a theoretical perspective that informed subsequent studies (Chester, 2010). The second most frequently cited article is Renewable Energy and Geopolitics: A Review by Roman Vakulchuk, published in 2020. This review article presented a comprehensive analysis of the geopolitical literature related to renewable energy. The study revealed that many publications on renewable energy and geopolitics employed limited research methodologies, failed to delineate geopolitical periods, and lacked in-depth discussions. Furthermore, the analysis indicated that most relevant articles focused on oil-producing countries, while ignoring coal-dependent countries (Vakulchuk et al., 2020). Moreover, it is notable that almost half of the top 10 cited literature originates from China, which serves to corroborate China’s research production level in this area.
This figure represents the literature coupling network, the nodes represent the literature, the node size represents the number of citations, the node connecting lines represent the coupling relationship of the literature, and the node color represents the time distribution.
Thematic distributionThematic keywords
Keywords can provide information about the core content of the article (Wang et al., 2024b). The frequency of keyword occurrences over time can reflect research trends in the field of study. We used Rstudio programming techniques to draw keyword heat maps and cumulative keyword heat maps in the research area of geopolitical impact on energy security. As shown in Fig. 11, which demonstrates the top 20 high-frequency keywords in the study of geopolitical impact on energy security. From the keyword heat map and the cumulative keyword heat map, it can be seen that “Natural gas” and “Oil” are the first to appear in the heat map, and both of them have a significant heat in 2006, and the heat lastes for a long time. It shows that the geopolitical impact on energy security is first and foremost reflected in the impact on natural gas and oil and that geopolitics has a significant long-term impact on hydrocarbons. In addition to “natural gas” and “oil” having significant heat in the keyword heat map, other keywords that appear earlier and have significant heat include “Russia” and “China”. In addition, in terms of sudden heat, “Climate change” receives huge attention in 2016. “Energy policy”, “Energy”, “Uncertainty”, “Natural gas” and “Oil” have a sudden increase in heat in 2021. The following is an in-depth analysis of the featured keywords.
This figure depicts the distribution of keyword frequency and cumulative keyword frequency. The horizontal axis represents the year, the vertical axis represents the keyword category, and the color represents the heat value of the keyword.
Natural gas and oil
The co-occurrence mapping of natural gas and oil linked to other keywords is shown in Fig. 12. “Natural gas” co-occurs with several keywords such as “energy security”, “consumption”, “market”, “crude oil”, “oil”, “policy”, “risk”, “China”, “Russia”, “EU”, and so on. “Oil” co-occurs with several keywords such as “energy policy”, “renewable energy”, “market”, “natural gas”, “vulnerability”, “return”, “price”, “cooperation”, “consumption”, “China” and “Russia”. Natural gas and oil are important energy components and occupy a prominent place in the global energy landscape. Natural gas is a vital source of electricity generation, and natural gas-fired power plants can provide backup and grid stability for intermittent renewable energy sources such as solar and wind power (Baldick, 2014; Mac Kinnon et al., 2018), their ability to increase or decrease rapidly complements the variability of renewable energy production. Natural gas is highly efficient, flexible, and low-emission compared to other fossil fuels, and natural gas produces fewer carbon emissions and less pollution when burned (Safari et al., 2019). At the same time, natural gas is an important source of energy to support industrial production and social life. Oil is a key feedstock for the petrochemical industry (Keim, 2010). It provides raw materials for the production of a wide range of products, including plastics, synthetic rubber, solvents, fertilizers, and chemicals, and is an important driver of global trade and economic activity. The geopolitical impact on energy security is the first thing that prompts global scientists to discuss natural gas and oil, given their wide-ranging and important international status, for geopolitical factors play a crucial role in determining the global distribution of natural gas reserves and oil. Countries with rich hydrocarbon reserves often have important strategic advantages that influence regional political alliances, trade relations (Gu and Wang, 2015). And geopolitical tensions could disrupt oil and gas supplies and affect global oil and gas markets. Armed conflict and political instability in natural gas regions increase the risk of gas supply disruptions and hinder the construction of projects such as gas pipelines.
This figure shows the co-occurrence network for the keywords “natural gas” and “oil”, where different nodes represent different keywords and the lines between the keywords represent co-occurrence relationships.
Russia and China
The connection between Russia and China in the keyword co-occurrence diagram is shown in Fig. 13. Russia has co-occurring relationships with the keywords “energy security”, “gas”, “oil”, “cooperation”, “Ukraine”, “Europe”, “renewable energy”, “China”, “policy”. In the co-occurrence mapping of the keyword China, there are co-occurrence relationships for several keywords such as “economic growth”, “energy security”, “energy transition”, “oil price”, “cooperation”, “return”, “demand”, and “consumption”. Russia has the world’s largest natural gas reserves and is one of the largest producers of crude oil, as well as being the world’s largest producer and exporter of natural gas (Karacan et al., 2021). In view of the geographical advantages, a number of European countries have formed close energy cooperation with Russia, and the rich energy reserves have become an important tool for Russia’s strategic negotiations and energy diplomacy (Bilgin, 2009). Russia is located in a geopolitical risk zone, with armed conflict with Ukraine in 2022 having a huge impact on Russian and global energy markets (Rokicki et al., 2023). Several European countries have restricted Russian energy imports, leading to an energy supply crisis in Europe (Kuzemko et al., 2022). China is the world’s largest energy consumer, and the diversification of China’s energy mix has made it more concerned about global energy security conditions (Boute, 2019). This is because China’s energy demand is fueled by rapid economic growth and accelerated industrialization. Whereas China is heavily dependent on energy imports, the impact of regional conflicts and political tensions on global energy supplies could also affect China’s energy import trade. China actively engages in energy cooperation with countries in Central Asia (Zhou et al., 2020) and Africa (Bradshaw, 2009), putting forward the “Belt and Road” initiative, and significant investment in global energy infrastructure was done to increase China’s influence in major energy-producing regions, ensure access to key resources and enhance the country’s energy security (Duan and Duan, 2023).
This figure shows the co-occurrence network for the keywords “Russia” and “China”, where different nodes represent different keywords and the lines between the keywords represent co-occurrence relationships.
Climate change
As shown in Fig. 14, climate change is closely related to the keywords “environment”, “energy security”, “energy transition”, “carbon emissions”, “renewable energy”, and “cooperation”. Climate change has been an important global issue, and its involvement in the discussion of geopolitical influences on energy security is notable. On the one hand, geopolitical factors have led to changes in global energy consumption patterns, and the deterioration of inter-State relations could re-exacerbate dependence on fossil fuels such as coal, oil, and gas. The “Escalation effects” of geopolitical risks reduce renewable energy consumption and lead to higher carbon emissions (Anser et al., 2021). Geopolitical decisions related to the development of energy infrastructure may affect the integration of renewable energy into national or regional energy systems, slowing down clean energy deployment plans and increasing global greenhouse gas emissions. On the other hand, favorable geopolitical policies and international cooperation can drive investment in clean energy technologies and increase opportunities for international R&D cooperation. In conclusion, the implications for climate change under the geopolitical discussion of energy security are complex.
This figure shows the co-occurrence network for the keywords “Climate change”, where different nodes represent different keywords and the lines between the keywords represent co-occurrence relationships.
Energy policy and uncertainty
As shown in Fig. 15, energy policy is closely related to the keywords “renewable energy”, “price”, “oil”, “climate change”, and “country”. In the keyword co-occurrence mapping of “uncertainty”, the terms “market,” “price,” “return,” and “economic growth” appear more frequently. Energy policy and uncertainty are key themes influencing the discussion of geopolitical implications for energy security. Government intervention is an important response to energy security issues, and governments around the world develop energy policies as a strategic framework to address the complex interplay of domestic and international factors that seek to enhance energy security and reduce uncertainty in the energy sector (Youngs, 2009). The formulation of energy policy is influenced by factors such as national energy structure and energy consumption (Li et al. 2024). Uncertainty about geopolitical risks also affects national energy policies, and it is important for national policymakers to combine measures to address geopolitical risks with the maintenance of national energy security and to reduce the vulnerability of global energy prices, energy trade, and energy supply to geopolitical risks. Uncertainty in the geopolitical landscape poses a challenge to energy policymakers. Sudden geopolitical events, changes in international relations, or changes in the dynamics of energy markets can threaten energy security, and the development of effective energy policies has become an important tool for addressing geopolitical threats to energy security.
This figure shows the co-occurrence network for the keywords “Energy policy” and “Uncertainty”, where different nodes represent different keywords and the lines between the keywords represent co-occurrence relationships.
Thematic evolution path
This section mapped the timeline of keyword co-occurrence from the perspective of the temporal evolution of keyword co-occurrence. As shown in Fig. 16, the transition from cold to warm indicates the time from far to near, and the average occurrence time of keywords can be identified by the time color band in the graph. The research phases can be categorized into three distinct phases according to the average year in which the keywords appeared. The average year of emergence of the first stage is 2018–2020, with a focus on the energy sector, which means objects that geopolitics may threaten. The main objects of energy security risks that can be extracted from typical words are “natural gas”, “oil”, “power”, “hydropower”, “nuclear power”, “fossil fuels”, “energy trade”, and they form the core of the global energy infrastructure. The identified energy security risks are multifaceted, encompassing not only traditional concerns related to fossil fuels but also reaching into the complex dynamics of the “energy trade”. The interconnected nature of energy resources and their global distribution necessitate a thorough review of trade relationships to assess potential vulnerabilities in energy supply chains. In the geopolitical area, certain countries play a pivotal role, directly affecting or being affected by developments in the energy sector, “China”, “Russia”, “EU”, “United States”, “India”, “Germany”, “Japan”, “Turkey”, “Central Asia”, “Middle East”, “Ukraine”, “Pakistan”, “Poland” are in the spotlight at this stage. Each of these countries faces a unique set of challenges and opportunities in terms of energy security. As mentioned previously, China is a rapidly growing consumer and producer of energy, influencing the global energy market (Odgaard and Delman, 2014). Russia is rich in energy reserves and plays an important role in regional and global energy dynamics. The EU, as a collective entity, plays a central role in the development of energy policies and in promoting cooperation among its member States. India’s economy is booming and it seeks to ensure a stable and continuous supply of energy to support its growth trajectory (Kumar and Majid, 2020). Germany, Japan, and Turkey represent industrialized countries with special energy needs and dependencies (Cherp et al., 2017; Kilickaplan et al., 2017). A comprehensive look at countries and regions provides a comprehensive understanding of the interconnected network of energy security issues, including supplier and consumer countries in the global energy landscape. As the research continues, it aims to unravel the intricate relationships, dependencies, and potential hotspots that will shape the future of global energy security.
This figure depicts the temporal evolution of keyword co-occurrences, with colors ranging from cool to warm to indicate time from far to near.
The average year of occurrence of the second stage is 2020–2022, which is a light warm color on the clustered time plot. During this period, the keywords “geopolitical risk”, “renewable energy”, “energy transition”, “crude oil”, “price”, “crude oil price”, “uncertainty”, “return”, “demand”, “policy uncertainty”, “growth”, “oil price shocks”, “volatility”, “price volatility”, “markets”, “gold price”, “stock market” are found to be more frequent. Popular keywords provide a comprehensive overview of key themes and concerns in the energy industry and related markets. The emergence of the term “geopolitical risk” as a focal point indicates an acute awareness of the impact of geopolitical events on energy markets and the wider global economy, as well as a heightened sensitivity to geopolitical tensions, conflicts, and geopolitical strategies that could disrupt energy supplies and markets. “Renewable energy” and “energy transition” continue to feature prominently, highlighting the growing emphasis on sustainable and clean energy. This period has been characterized by growing interest and discussion around the global shift to renewable energy, reflecting a concerted effort to address environmental concerns and reduce dependence on traditional fossil fuels. The constant references to “crude oil”, “price” and “crude oil price”, together with terms such as “oil price shocks”, “volatility”, “price fluctuations”, “market”, “gold price” and “stock market”, highlight the energy industry’s continued interest in and scrutiny of the intricate relationship between geopolitical risks and global energy markets. Conflicts, political tensions, or disruptions in the oil supply chain in the world’s major oil-producing regions could lead to unpredictable and dramatic fluctuations in oil prices. Such sharp fluctuations create uncertainty for both producers and consumers, affecting investment decisions and market dynamics (Mei et al., 2020). In conclusion, this stage of research focuses on the fluctuations of geopolitics in the energy economy market and the financial market, and it is gradually recognized that geopolitics produces dramatic fluctuations in the energy economy market, while the sensitivity of the crude oil price, oil price to geopolitical risks promotes the exploration of measures to resist the geopolitical risks.
The average year of occurrence of the third stage is 2022–2023, which appears in red on the clustered time plot. “GDP”, “financial development”, “natural resources”, “green finance”, “determinants”, “empirical analysis”, “utility testing”, “regression analysis”, “impulse response analysis”, “time series”, “wavelet correlation”, and other keywords frequently appear. It is worth noting that the interconnection between the financial system and the energy market has received extensive attention from researchers and scholars in the context of the geopolitical impact on energy security, as indicated by keywords such as “GDP”, “financial development” and “green finance”. The keywords “determinants,” “empirical analysis,” “utility testing,” “regression analysis,” “impulse response analysis,” “time series,” and “wavelet correlation” collectively indicate a methodological shift toward rigorous quantitative analysis at this stage. Researchers seem to have employed advanced statistical tools and econometric techniques to explore the determinants and effects of various factors on energy-related phenomena. The methodological shift suggests that the field is moving toward evidence-based policymaking and a desire to build a solid empirical foundation. The diversity of keywords in this phase implies a multidimensional exploration, integrating economic, financial, and environmental factors, in addition to multiple keywords on research methodology suggesting that research is moving towards more advanced analytical tools and empirical frameworks.
Thematic clustering
Keyword clustering analysis is able to explain the main hotspots in the research field, which was mapped by VOSviewer and Scimago. As shown in Fig. 17, hotspot clusters are distributed in a two-dimensional rectangular coordinate system, and different colors indicate different clusters. The distribution of colors and the legend in Fig. 17 show that the main hotspots in this research area are distributed in six clusters. We obtained cluster labels from the keywords contained in the clusters and discussed with experts to determine the keyword labels that best summarize the nature of the clusters and labeled them in Fig. 17. The size of a clustering cluster is determined by the number of keywords contained in the cluster. The cluster with the largest number of keywords is the green cluster, which focuses on keywords such as “fossil energy”, “clean energy”, “renewable energy” and “energy transition”, it is therefore reasonable to name the green cluster “energy transition”. And then the purple cluster, which is identified through keyword analysis as being closely related to the natural environment, and is therefore identified as being labeled “natural environment”. Similarly, based on the keyword categories, the blue cluster is labeled “energy policy”, and the red and pink clusters, which cover a sparse number of keywords and tend to be similar in nature to the orange clusters, are combined and labeled “energy market”. It is worth noting that the horizontal and vertical axes in the 2D cartesian coordinate system have no obvious data meaning, but merely indicate the relative positions of the keywords and their clusters in the 2D space. Subsequently, our study further explored for the identified keyword clusters.
This figure illustrates keyword clustering, wherein nodes represent keywords and different nodes are colored to indicate distinct clusters. The horizontal and vertical axes represent the relative positions of the nodes.
Green cluster: energy transition
Energy transition refers to a change in the way energy is utilized, a reduction in the share of fossil energy in the energy mix, and a transition from traditional fossil energy consumption to clean energy consumption (Rasoulinezhad et al., 2020). Geopolitical risk works both ways for energy transition, with major changes in international energy markets under the Russia–Ukraine conflict. European countries, opposed to Russia’s military conflict over Ukraine and determined to reduce energy trade with Russia, have resumed coal- and oil-fired power generation amid gas shortages (Wang et al., 2023), higher geopolitical risk also increases the cost of renewable energy deployment (Shirazi et al., 2023), slows down the energy transition and inhibits the transition to renewable energy. Meanwhile, “high-risk” countries at geopolitical centers may face obstacles in seeking foreign investment, inhibiting the development of renewable energy infrastructure (Fischhendler et al., 2021). On an optimistic note, studies have demonstrated the positive contribution of geopolitical risk to the development of renewable energy, with high geopolitical risk spurring countries to consume more renewable energy (Sweidan, 2021), which could be an important tool to facilitate the clean energy transition (Liu et al., 2023). The complex relationship between geopolitical risk and renewable energy has been subjected to multiple argumentative studies, and thus energy transition is one of the important research directions for researchers and scholars in various countries in the context of geopolitical risk affecting energy security.
Purple cluster: natural environment
The three themes of geopolitical risk, energy security, and climate change have become popular topics for researchers and scholars around the world. Geopolitical tensions not only bring political and economic uncertainty but also harm the natural environment (Acheampong et al., 2023). The direct impact of geopolitical risk on the environment is manifested in the control of and access to valuable natural resources, such as oil, gas, minerals, and water, competition for which can lead to overexploitation, environmental degradation, and ecosystem destruction (Li et al., 2023). International conflicts and armed struggles also have a greater impact on the surrounding environment, and conflicts can lead to increased air pollution and destruction of green facilities in the region, and the production and manufacture of military equipment can increase atmospheric carbon dioxide (Ullah et al., 2020). Furthermore, geopolitical risks act on the natural environment by affecting the consumption structure of the energy sector. The previous analysis showed that the process of energy transition was negatively affected by geopolitical risks, the decline in the consumption of renewable energy sources, and the reduction of clean energy infrastructure were not conducive to the suppression of carbon emissions. In addition, unfriendly relations between countries can hamper global cooperation in addressing climate change and environmental issues, and prolonged hostilities can impede the conclusion of bilateral or multivariate agreements, which in turn affects sustainable development (Zhao et al., 2021).
Red, pink, and orange cluster: energy market
Geopolitical risks have historically played an important role in influencing global energy prices. One study summarized three channels through which geopolitical risk affected energy prices: the threat of conflict acting on energy conversion resulting in lower oil prices, the impact on energy prices of rising negative investor sentiment due to the threat of conflict, and the role of geopolitical uncertainty on energy supply and demand (Li et al., 2020). Additionally, geopolitical tensions and conflicts in major oil- and gas-producing regions could disrupt the production and transportation of energy resources. For example, conflicts in the Middle East involving major oil-producing countries such as Iraq or Saudi Arabia had the potential to result in supply disruptions and subsequent increases in oil prices (Cunado et al., 2019; Su et al., 2019). Then, geopolitical events have affected national foreign trade policies, leading to the imposition of sanctions or embargoes on certain countries, restricting their ability to export or import energy resources, and reducing the global supply of oil and natural gas, resulting in higher prices. Thus, the complex relationship between geopolitical risks and global energy markets has led to a strong interest in this direction among researchers and scholars in various countries.
Blue cluster: energy policy
As Governments grapple with the dual challenge of meeting growing energy demand and addressing climate issues, the energy policy landscape has changed significantly and is often influenced by geopolitical risks. Energy policy is an integrated strategic framework for managing the production, consumption, and sustainability of a country’s energy resources and plays an important role in economic development, national security, and environmental stability (Chen, 2011). The multidimensional objectives of energy policy underscore its centrality to national interests: ensuring reliable and affordable energy supplies, promoting economic growth, reducing environmental impacts, and enhancing energy security (Doukas et al., 2008). Energy policy is undergoing transformative changes in the contemporary geopolitical landscape, driven by an intricate interplay of technological advances, environmental imperatives, and geopolitical risks (Wang et al., 2024). The geopolitical landscape brings a layer of complexity to energy policy, as countries must navigate an intricate web of alliances, rivalries, and resource dependencies. Geopolitical risk manifests itself in the energy sector in a variety of ways, including disruptions in the global energy supply chain due to conflicts in major oil-producing regions, and trade disputes affecting energy trade (Golan et al., 2020; Zhang et al., 2023b). In the face of these risks, there is a need for a nuanced energy policy that requires a comprehensive understanding of how global geopolitical dynamics can affect energy markets and, in turn, a country’s energy security. Therefore, as the world faces continued geopolitical uncertainty, energy policy will continue to evolve, reflecting the need to balance energy security, economic development, and environmental sustainability in an increasingly interconnected and dynamic global environment.