
==== Front
Heliyon
Heliyon
Heliyon
2405-8440
Elsevier

S2405-8440(24)13003-4
10.1016/j.heliyon.2024.e36972
e36972
Research Article
Impact of geopolitical risk on green international technology spillovers: FDI and import channels
Cheng Pengfei chengpengfei@jbnu.ac.kr
a
Li Kanyong b
Choi Baekryul c
Guo Xiao c
Wang Mengzhen 20230022@huat.edu.cn
d⁎
a Department of Financial Management, Hubei University of Automotive Technology, Shiyan City, Hubei Province, China
b School of Economics and Management, Shandong Jiaotong University, China
c Department of International Trade, Jeonbuk National University, Jeonju-si, Jeollabuk-do, Republic of Korea
d Department of Economic and Trade, Hubei University of Automotive Technology, Shiyan City, Hubei Province, China
⁎ Corresponding author. 20230022@huat.edu.cn
27 8 2024
15 9 2024
27 8 2024
10 17 e3697227 4 2024
11 8 2024
26 8 2024
© 2024 The Authors. Published by Elsevier Ltd.
2024

https://creativecommons.org/licenses/by-nc/4.0/ This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
This study investigates the impact of geopolitical risk (GPR) on green international technology spillovers through foreign direct investment (FDI) and import channels. The research aims to understand how GPR influences the transfer of green technologies, which are crucial for sustainable development, particularly in developing countries. Utilizing data from 30 Chinese provinces from 2003 to 2019, our findings indicate that increased GPR significantly hinders green technology spillovers through both FDI and imports. Additionally, the research demonstrates that advancements in local green technology levels (GTL), marketization (Mark), and intellectual property rights protection (IPRP) can mitigate the adverse effects of GPR. These results underscore the critical importance of political stability and robust internal mechanisms in promoting international technological exchanges. This study contributes to the literature on the intersection of political risks and technological advancement and provides actionable insights for policymakers to enhance resilience against geopolitical uncertainties, thereby fostering sustainable economic development.

Keywords

Geopolitical risk
Green international technology spillovers
Green technological progress
Moderating effect
China
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pmc1 Introduction

Advancements in green technology are pivotal in reducing environmental pollution and promoting sustainable development, as they involve innovations that lower energy consumption, reduce pollution, and enhance resource efficiency [1,2]. For developing countries, which often lack sufficient R&D funding and knowledge accumulation, the international spillover of technology through foreign direct investment (FDI) and import trade (IM) channels is an essential source of technological progress [3]. Therefore, understanding how geopolitical risks (GPR) impact these spillovers is critical in the context of globalization and environmental sustainability.

GPR refer to uncertainties and risks arising from political decisions, conflicts, instability, or political changes. These risks may stem from changes in national policies, tensions in international relations, conflicts, and sanctions [4]. Consequently, GPR inevitably impacts FDI and international trade, subsequently affecting the international spillover of green technology. Specifically, GPR manifests through its impact on national sovereignty and security, such as ethnic conflicts, religious disputes, economic dependencies, and political turmoil. It also includes military interventions, armed threats, major power interventions, terrorism, and other threats to national military security [5].

Despite the recognized role of FDI and IM in facilitating technology spillover, the impact of external factors such as GPR remains underexplored. Existing literature has predominantly focused on the economic impacts of GPR, with limited attention to its effects on green technology spillovers. Geopolitical risks, encompassing political instability, international conflicts, and policy changes, can deter foreign investment and disrupt international trade, thereby affecting technology transfer [6]. Thus, this study addresses this gap by exploring how GPR influences green technology spillovers through FDI and IM.

China serves as an ideal case study for several reasons. As the world's second-largest economy and an emerging market, China has experienced rapid growth in FDI and international trade since joining the World Trade Organization. This growth has significantly contributed to its economic development and technological progress [7]. However, China's environmental protection and technological innovation capabilities remain relatively weak, with a reliance on imports for key technologies and high-tech intermediate products [8]. Moreover, China plays a crucial role in the global production chain, making it highly susceptible to geopolitical risks that can affect technology spillovers [9]. Therefore, studying China provides valuable insights into the impact of GPR on green technology spillovers in a rapidly developing and geopolitically complex environment.

This study seeks to answer the following questions: (1) What is the impact of GPR on green technology spillovers through FDI and IM channels? (2) What are the moderating effects of local green technology levels (GTL), marketization (Mark), and intellectual property rights protection (IPRP) on this relationship? By investigating these questions, this study aims to provide a nuanced understanding of the mechanisms through which GPR impacts green technology spillovers and how internal factors can mitigate these effects.

The main contributions of this research are providing robust empirical evidence on the negative impact of GPR on green technology spillovers, thereby contributing to the broader literature on the intersection of political risks and technological advancement. Furthermore, it demonstrates the mitigating effects of green technology levels, marketization, and intellectual property rights protection, offering actionable insights for policymakers to enhance resilience against geopolitical uncertainties. Additionally, it highlights the complementary relationship between FDI and import channels in facilitating technology spillover, underscoring the need for integrated policy approaches that leverage multiple channels for technology transfer. By conducting an in-depth regional analysis, the study illustrates the varying impacts of GPR across different areas, providing a detailed understanding of regional disparities and helping tailor specific strategies for different contexts. These findings offer valuable insights for policymakers and stakeholders in developing strategies to enhance green technology spillovers despite geopolitical uncertainties, thereby promoting sustainable economic development.

The structure of this paper is organized as follows: Section 2 reviews the relevant literature. Section 3 develops the research hypotheses. Section 4 describes the data and methodology used in this study. Section 5 presents the empirical results and provides a comprehensive discussion. Finally, Section 6 examines the policy implications derived from the findings and offers suggestions for future research.

2 Literature review and research gap

Green technology spillovers are vital for promoting sustainable development and mitigating environmental pollution. Extensive research has investigated the mechanisms and impacts of international technology spillovers through channels such as FDI and IM, which provide developing countries with access to advanced technologies, fostering innovation and economic growth [10]. Existing studies have underscored the importance of FDI in technology transfer, showing its contribution to economic growth via technology diffusion and the role of multinational corporations in transferring advanced technologies to host countries [11,12]. The environmental implications of FDI have also been explored. Some research indicates that FDI can lead to increased pollution due to less stringent environmental regulations in host countries [13,14]. Conversely, other studies highlight the potential for FDI to facilitate the transfer of cleaner technologies and practices (Potterie, 2001 [100]). Pata et al. [15] supported the Environmental Kuznets Curve (EKC) hypothesis, suggesting that FDI initially exacerbates environmental degradation but ultimately leads to improvements as income levels rise.

Import trade is another critical avenue for technology spillovers, bringing advanced production equipment, efficient energy, and environmental technologies, thus enhancing local enterprises' technological level and environmental performance. However, the environmental impacts of import trade can be mixed. While it can lead to increased pollution in developing countries with lax regulations, it can also improve local environmental quality by importing advanced technologies [16]. Research highlights the importance of governance quality in maximizing the environmental benefits of import trade [17].

Despite substantial research on FDI, IM, and their roles in technology transfer, there is a notable gap in understanding how GPR specifically impacts green technology spillovers. Existing studies have primarily focused on the general economic effects of GPR, such as impacts on economic growth, investment, and trade [18,19]. GPR, encompassing political instability, conflicts, and policy changes, can deter foreign investment and disrupt international trade, significantly affecting the channels through which technology spillovers occur [20]. However, the mechanisms through which GPR affects the transfer of green technologies have not been thoroughly investigated.

Given the importance of environmental sustainability, it is essential to understand how geopolitical factors influence the international spillover of green technologies. Green technologies are critical for addressing global environmental challenges, and any hindrance in their transfer can have significant implications. This study aims to fill this gap by examining the impact of GPR on green technology spillovers through FDI and IM channels. It also explores the moderating effects of local green technology levels, marketization, and intellectual property rights protection on this relationship. By providing empirical evidence on the impact of GPR on green technology spillovers, this study contributes to the broader literature on political risks and technological advancement. The findings will help policymakers and stakeholders develop strategies to promote green growth and sustainable development amidst geopolitical challenges.

3 Theoretical basis and hypothesis development

3.1 GPR and international green technology spillover

FDI is recognized as a significant channel for technology spillover, particularly for the development of green technology in recipient countries [21]. Through direct investment, multinational corporations introduce advanced green technologies, management practices, and innovative concepts, thereby enhancing the environmental efficiency and sustainable development of host countries. This technology spillover is facilitated not only through direct technology transfer but also via personnel training, learning effects, and collaboration with local businesses [22,23]. Similarly, import channels serve as an important conduit for international green technology spillover. By importing advanced environmental equipment, clean energy technologies, and high-efficiency materials, nations can swiftly elevate the technological level and environmental performance of their local industries [24]. Such spillovers contribute to environmental protection, energy efficiency enhancement, and sustainable development in host countries [25]. Concurrently, the impact of geopolitical risks (GPR) on FDI and IM is increasingly garnering scholarly attention. GPR encompasses events likely to cause social unrest, such as wars, terrorism, political disputes, and natural disasters. Recent literature has increasingly shifted to explore the adverse impacts of GPR on economic growth and other microeconomic and macroeconomic variables [26]. Most studies have found that an increase in GPR in host countries inhibits the growth of FDI and IM [27]. Next, we will specifically analyze the impact of GPR on green technology spillover through both FDI and IM channels.

3.1.1 GPR and FDIsp

In the context of green technology spillover through FDI channels, the role of GPR is multifaceted, impacting investment decisions, corporate strategies, and the technology acceptance capabilities of host countries. A detailed analysis and explanation of these aspects are as follows:

Firstly, GPR significantly affects the investment decisions of multinational corporations. When considering FDI, businesses conduct comprehensive risk assessments, including political stability, policy coherence, and international relations. High GPR usually implies political turbulence, policy uncertainty, or international conflicts, which increase uncertainty and potential investment costs. Consequently, faced with high GPR, companies might opt to reduce investment amounts, delay investment decisions, or seek other lower-risk investment destinations [28,29].

Secondly, GPR influences not only the quantity of FDI but also corporations' strategic choices and methods of technology transfer. In high-risk environments, companies might adopt more conservative technology transfer strategies, such as limiting the scope of technology transfer, selecting technologies less prone to replication, or implementing stricter intellectual property protection measures. While these actions can protect corporate interests, they might reduce the opportunities for host countries to acquire and absorb advanced green technologies, thus impacting the effectiveness and speed of green technology spillover [[30], [31], [32]].

Thirdly, GPR can impact the technology acceptance capabilities of host countries. High risks might lead to political and economic instability in host countries, affecting their ability to attract and utilize foreign technology. For example, political turmoil could result in economic fluctuations and increased market uncertainty, thereby impacting businesses' production, sales, and technology absorption activities. Furthermore, policy incoherence might increase operational costs and legal risks, reducing businesses' willingness to adopt new technologies and innovate [33,34].

In conclusion, GPR can significantly impact the spillover of green technology through FDI channels by influencing foreign corporations' investment decisions and strategic choices, reducing the scale and speed of technology transfer, and impacting technology acceptance capabilities. Therefore, understanding and mitigating the adverse effects of GPR is essential for fostering the effective transfer and adoption of green technologies in host countries.

3.1.2 GPR and IMsp

When analyzing the impact of GPR on the spillover of green technology through import channels, several nuanced perspectives emerge:

Firstly, GPR is often linked to political instability, tense diplomatic relations, or frequent policy changes. These factors can lead to increased uncertainty in trade policies, such as changes in tariffs, renegotiations, or cancellations of trade agreements. For nations reliant on the international market for importing green technologies, such uncertainty could cause hesitation among businesses, leading to delayed or canceled import plans and consequently impacting the acquisition and application of green technology [35,36].

Secondly, elevated GPR may cause instability in supply chains, particularly in the field of green technology, where specific materials and high-tech products are often needed. Geopolitical conflicts could result in supply chain disruptions or force companies to seek alternative suppliers, leading to increased costs and time delays, thus affecting the efficiency and effectiveness of green technology spillover [37,38].

Thirdly, GPR contributes to the instability of financial markets and increases investment risks. Investors might seek safer investment channels in high-risk environments, reducing or withdrawing investments in higher-risk markets. Such shifts in capital flows could affect exchange and interest rates, thereby influencing the cost of imports, particularly for capital-intensive and high-tech green technologies [39].

Additionally, GPR can alter the conditions for market access and the competitive environment between host and supply countries. For instance, political tensions may lead to import restrictions or anti-dumping measures against products from certain countries, limiting market access and competitiveness for green technology products. Furthermore, political risks could impact international cooperation projects and technological exchanges, reducing opportunities for technology spillover [40,41].

Therefore, GPR can significantly impact the spillover of green technology through import channels by influencing trade policies, supply chain stability, investment and financial markets, market access, and the competitive environment. In summary, we propose the following hypothesis:H1 GPR will inhibit the spillover of green technology through both FDI and import channels.

3.2 Moderating effects of GTL, marketization, and IPRP

Despite the potential negative impact of GPR on green technology spillover through FDI channels, host countries can mitigate these effects through certain internal factors. Therefore, we include green technology levels (GTL), marketization (Mark), and intellectual property rights protection (IPRP) in our analytical framework to further analyze their moderating effects on GPR.

3.2.1 Moderating effect of GTL

The role of GTL is indispensable when exploring the impact of GPR on international green technology spillover. Firstly, advancements in green technology enhance the technological autonomy of the host country. Improved technological autonomy means that in the face of external political risks, the host country can more flexibly adjust its technology development strategy and industrial layout, reducing dependency on external technology [42]. This is particularly important for countries pursuing technological innovation and economic development in a geopolitically tense environment.

Secondly, advancements in green technology enhance the host country's competitiveness in the international market. Advanced green technologies can help produce more efficient and environmentally friendly products, meeting the global market demand for sustainable development products. Increased international competitiveness helps attract foreign direct investment and increase exports, thereby alleviating the economic pressures brought about by GPR [43,44].

Thirdly, the host country's advanced GTLs attract international investment and cooperation, especially in high-tech fields. When a country possesses advanced green technology capabilities, it is more likely to attract FDI and international cooperation projects, including green technology investments. These not only aid in local technological and economic development but also strengthen international cooperation, reducing the potential impact of GPR [45,46].

Lastly, GTLs contribute to environmental quality improvement and social stability enhancement. Improving the environment and social stability can reduce social discontent and unrest caused by GPR while enhancing the government's ability to handle external pressures [47,48].

In summary, host country GTLs provide important tools for effectively addressing GPR by enhancing technological autonomy, increasing international competitiveness, attracting foreign investment and international cooperation, and promoting social stability and environmental improvement. Therefore, we propose the following hypothesis:H2 GTL can alleviate the negative impact of GPR.

3.2.2 Moderating effect of mark

Incorporating existing research and relevant theories, marketization (Mark) is posited to modulate the impact of GPR in several ways. The Mark level refers to the market's dominant role in resource allocation, reflecting the extent of market operations in an economy. Studies indicate that the Mark level of the host country is a key factor influencing international technology spillover [49]. Additionally, research shows that countries with a higher degree of marketization can maintain more stable technological innovation and economic growth in the face of geopolitical conflicts [50].

Furthermore, in environments with higher Mark, businesses and individuals are more willing to invest in long-term green technology research and development, even if these investments might face short-term uncertainties due to GPR [51]. Specifically, economies with a higher level of Mark usually have more effective resource allocation [52]. In these economies, the market, rather than the government, predominantly dictates resource distribution, especially in the field of green technology. Consequently, resources are more likely to be invested in the most promising areas, fostering technological innovation and spillover, even amidst geopolitical uncertainty [53].

Moreover, intense market competition in a marketized environment compels firms to continuously innovate to maintain their competitiveness [54]. This competitive pressure stimulates the development of green technology, encouraging firms to persist in technological innovation even under high GPR. Additionally, countries with higher Mark levels typically possess stronger legal and business environments, including effective protection of intellectual property rights. This provides the necessary safeguards for innovation and the international transfer of green technologies, maintaining a certain level of technological innovation and exchange even in politically turbulent times [55].

Overall, the level of marketization is a key factor in mitigating the adverse impact of GPR on the spillover of green technology. It provides a solid foundation for the development of green technology by promoting effective resource allocation, stimulating market competition and innovation, enhancing investor confidence, and establishing robust legal and commercial environments. Based on this, we propose the following hypothesis:H3 Mark can alleviate the negative impact of GPR.

3.2.3 Moderating effect of IPRP

Enhanced intellectual property rights protection (IPRP) implies stricter legal and policy measures to protect patents, copyrights, and trademarks, thereby incentivizing innovation and safeguarding the interests of technology developers [56]. Additionally, IPRP is beneficial in mitigating the adverse impacts of regional GPR [57,58]. Drawing from existing research, IPRP may alleviate the adverse impacts of GPR in several ways.

Firstly, IPRP provides incentives for innovation, which is particularly crucial in the field of green technology. Knowing their inventions are legally protected, innovators are more motivated to invest in research and development. This incentive is particularly important in the face of GPR, as it maintains the enthusiasm of technology developers even in highly uncertain environments [59].

Secondly, a higher level of IPRP encourages collaboration between international enterprises and research institutions in green technology. This protection reduces the risk of technology theft or misuse, thereby promoting the international transfer and spillover of technology and offering some security against GPR [60]. Furthermore, such protection also aids in attracting international investments, especially in high-tech and green technology sectors [61].

Additionally, IPRP enhances market access and competitiveness, which is considered one of the essential conditions for international trade and investment [62]. Countries providing ample IPRP are more likely to attract FDI, including in green technology. Such investments not only enhance a country's competitiveness but also provide local enterprises with opportunities to learn and assimilate advanced international technologies [63].

In summary, enhancing IPRP is vital to reducing the adverse impact of GPR. It facilitates innovation, promotes technology spillover and international cooperation, and strengthens market access and competitiveness, providing a solid foundation for the development of green technology. Thus, we propose the following hypothesis:H4 IPRP can alleviate the negative impact of GPR.

4 Methodology specification and variable description

4.1 Variable description and data source

4.1.1 Dependent variable

The world's advanced green technologies are predominantly concentrated in developed countries, which typically have strong environmental protection awareness. Given China's main partners in import trade and FDI, we selected G7 countries as the source countries for China's green technology spillover. This study measures the green technology spillover effect of FDI and imports (IM) using the methodologies of Lichtenberg and De La Potterie [64] and Cheng et al. [65]. The calculation formulas are shown in Equations (1), (2). Data on China's FDI and import trade are sourced from the China Statistical Yearbook (2004–2020). The number of green patents from G7 countries is obtained from the OECD Stata database.

The following formula (equation (1)) calculates the FDI-generated green international technology spillover (FDIspit):(1) FDIspit=FDIitFDIt∑j=1n(FDIjtGDPjt×ESjt)

where FDIspit represents the green international technology spillover absorbed through FDI in province i in year t. The term FDIjtGDPjt represents the share of investment in GDP in China from country j in year t, and FDIitFDIt represents the share of actual utilization of foreign investment in province i in the country in year t.

The green international technology spillover from IM (IMspit) is calculated as follows (equation (2)):(2) IMspit=IMitIMt∑j=1n(EXjtGDPjt×ESjt)

where IMspit represents the green international technology spillover through imports in province i in year t. The term ESjt is the number of green patents in country j in year t, EXjtGDPjt is the share of export value of goods to China from country j in year t in its GDP; IMitIMt is the share of the import value of goods in province i in the country in year t.

4.1.2 Core explanatory variable

Data on GPR is sourced from the EPU Database, which has been extensively used in recent studies. The GPR index constructed by Caldara and Iacoviello [66] analyzes key terms related to GPR in news reports, comprehensively considering factors such as war, terrorism, and geopolitical tensions. This index provides a holistic reflection of the overall level of GPR. A higher index value indicates greater GPR. Fig. 1 illustrates the trend of China's GPR index. Starting in 2016, the GPR index experienced a significant increase, primarily due to the South China Sea disputes and the deployment of the THAAD missile defense system in South Korea by the United States, which heightened regional tensions and strained Sino-Korean relations. The index reached new heights in 2018 with the onset of the China-U.S. trade war, which involved conflicts over tariffs, technology, and supply chains, significantly escalating tensions between the two nations. The sharp fluctuations in China's GPR provide a basis for our research.Fig. 1 China's GPR trend chart.

Fig. 1

4.1.3 Moderating variables

(1) Green technology level (GTL): The number of green patent applications directly reflects green technology innovation [67]. Therefore, we use the logarithm of the number of green patent applications in each province in China as a proxy indicator for green technology level. The data is obtained from the Chinese Research Data Services (https://www.cnrds.com/).

(2) Marketization (Mark): The marketization index is a comprehensive indicator reflecting the relationship between the government and the market in a specific region, the development of the non-state economy, the maturity of the product market, the development of factor markets, and the maturity of market intermediaries and the legal system environment. Data is sourced from the China Market Index Database (https://cmi.ssap.com.cn/).

(3) Intellectual property rights protection (IPRP): IPRP provides institutional safeguards for the dissemination of knowledge and technology. The GP index, reported by Ginarte and Park [68] and updated by Park [69], is one of the most commonly used measures for assessing IPRP. However, this index does not include the provincial data of China needed for our study. Therefore, we use the IPRP data of Chinese provinces provided by the Intellectual Property Development Research Center of the National Intellectual Property Administration (https://www.cnipa-ipdrc.org.cn/) as a proxy indicator for IPRP. Since this data starts from 2007, our IPRP data covers the period 2007–2019.

4.1.4 Control variables

Our model incorporates provincial economic growth, regional innovation capability, urbanization, and industrialization as control variables based on existing research [70,71]. The indicator for regional innovation capability is derived from the “China Regional Innovation Capability Report,” while other data is sourced from EPS China Data (http://olap.epsnet.com.cn/).

This study utilizes data from 30 provinces (excluding Tibet, Hong Kong, Macau, and Taiwan) in China over the period from 2003 to 2019. The selection of this time frame is motivated by several factors. Firstly, 2003 marked the beginning of significant economic and technological changes in China following its accession to the World Trade Organization (WTO) in 2001. This period captures the subsequent rapid growth in foreign direct investment (FDI) and international trade, which are crucial for analyzing green technology spillovers. Secondly, extending the data period to 2019 allows for a comprehensive analysis without the confounding effects of the COVID-19 pandemic, which began in late 2019. The pandemic significantly disrupted global economic activities and technology flows, introducing extraordinary factors that could obscure the typical patterns and relationships we aim to study. Lastly, data availability plays a crucial role in defining this period. Reliable and consistent data on geopolitical risks, green technology levels, marketization, intellectual property rights protection, and other control variables are readily available up to 2019. Extending the period beyond 2019 would introduce gaps and inconsistencies in the dataset, potentially affecting the robustness and reliability of our findings. By focusing on the 2003–2019 period, we ensure that our analysis is based on stable and comparable data, providing clear insights into the impact of geopolitical risk on green technology spillovers through FDI and import channels during a period of significant economic development in China.

All variables (except for ratio variables) are log-transformed to mitigate heteroscedasticity issues. Basic statistical information on each variable is shown in Table 1. Table 1 shows that the standard errors for FDIsp and IMsp are 0.73 and 0.76, respectively, indicating significant variations in FDI and IM technology spillover across different provinces in China. Additionally, the maximum, minimum, and standard errors of GPR are −0.09, −1.05, and 0.3, respectively, showing substantial fluctuations in GPR during the sample period, which provides a basis for our analysis. Other variables are also consistent with existing research and reflect the actual situation in various provinces in China.Table 1 Basic statistics.

Table 1Variable		N	Mean	S.D.	Min	Max	
FDI-generated green international technology spillover	LnFDIsp	510	−3.180	0.730	−6.380	−1.590	
IM-generated green international technology spillover	LnIMsp	510	−4.530	0.760	−6.710	−2.330	
Geopolitical risk	LnGPR	510	−0.730	0.300	−1.050	−0.0900	
Green technology level	LnGTL	510	2.750	0.790	0	4.510	
Marketization	LnMark	510	1.950	0.280	0.910	2.440	
Intellectual property rights protection	LnIPRP	390	−0.510	0.220	−0.900	−0.0600	
Economic growth	LnEG	510	3.890	0.450	2.560	4.800	
Innovation capability	LnIC	510	1.520	0.140	1.070	1.860	
Urbanization	Urb	510	0.530	0.150	0.260	0.900	
Industrialization	Ind	510	1.160	0.630	0.530	5.230	

4.2 Model construction

The construction of the estimated model is based on the theoretical foundation and empirical evidence from existing literature, focusing on the impact of GPR on green international technology spillovers through FDI and IM channels.

4.2.1 Baseline model

The baseline model aims to capture the direct impact of GPR on green technology spillovers via FDI and IM channels. Geopolitical risk encompasses political instability, international conflicts, and policy changes, which can hinder foreign investment and international trade, thereby affecting technology transfer. Existing studies indicate that high GPR typically leads to a reduction in foreign investment and global trade, thus inhibiting the international spillover of green technology. For instance, Jensen [72] and Busse and Hefeker [73] highlighted that high GPR increases investment uncertainty, leading to reduced foreign investment. Additionally, Antras [74] and Caldara and Iacoviello [66] demonstrated that rising GPR increases trade costs, reduces international trade, and affects technology transfer. FDI and IM are critical channels for technology spillovers; FDI brings advanced green technologies and management practices through multinational corporations, enhancing the host country's environmental efficiency and sustainable development. Similarly, import channels introduce advanced environmental equipment and efficient materials, improving local industries' technological level and environmental performance.

According to the knowledge spillover theory, FDI facilitates the transfer of advanced technologies and practices from multinational corporations to local firms, thereby promoting local innovation and technological upgrading [75]. On the other hand, import trade enables the acquisition of advanced foreign technologies embedded in imported goods and services, enhancing the technological capabilities of the importing country [76]. Based on these theoretical insights, we formulate the following baseline models (equations (3), (4))):(3) LnFDIspit=α0+α1LnGPRt+βXit+εit

(4) LnIMspit=γ0+γ1LnGPRt++βXit+εit

4.2.2 Moderating effect model

Using a moderating effect model is essential in understanding how various factors can influence the relationship between primary variables. The rationale for employing this model lies in its ability to provide a nuanced understanding of how internal factors can mitigate or exacerbate the effects of external risks on green technology transfer and innovation. Based on research H2, H3, H4, we further test the moderating effects of GTL, Mark, and IPRP on GPR by introducing interaction terms into the model, and obtaining the following model (equations (5), (6))):(5) LnFDIspit=α0+α1LnGPRt+α2LnGPRt×Mit+βXit+εit

(6) LnIMspit=γ0+γ1LnGPRt+γ2LnGPRt×Mit+βXit+εit

where LnFDIspit is the green technology spillover of FDI, LnIMspit is the green technology spillover of import, LnGPRt is the geopolitical risk, Mit includes GTL, Mark, and IPRP, Xit is the set of control variables, and εit is the error term.

These models not only examine the direct impact of GPR on green technology spillovers through FDI and IM channels but also analyze how internal factors can mitigate these effects, providing a comprehensive analytical framework.

4.3 Preliminary test

Before proceeding with the regression analysis, we conducted preliminary tests on the data, specifically examining slope homogeneity and unit root tests, to ensure the robustness of model selection and regression results. Firstly, the results of the slope homogeneity test, presented in Table 2, indicate that the null hypothesis of homogeneous slopes is rejected for both Models (3) and (4). This finding implies that our baseline models exhibit issues of slope heterogeneity. Secondly, we performed the LLC panel unit root test [77]. The results, shown in Table 3, suggest that all variables reject the null hypothesis of the presence of a unit root, indicating that the variables are stationary. Given the slope heterogeneity in our models, it is necessary to seek an appropriate econometric method to achieve unbiased, consistent, and effective results. To address the issue of slope heterogeneity, we incorporate fixed effects models, which allow for individual-specific slopes in the baseline model. Additionally, we employ heteroskedasticity-robust standard errors in the regression to further enhance the robustness of the regression results. By ensuring the robustness of our model selection and regression analysis through these preliminary tests, we establish a solid foundation for the subsequent empirical analysis.Table 2 Slope homogeneity test.

Table 2Slope Homogeneity Test	
Model (3)	Model (4)	
12.714***	14.913***	
(0.000)	(0.000)	
Note: P-values in parentheses; *, **, and *** represent the significance level at 10 %, 5 %, and 1 %, respectively.

Table 3 Panel unit root test.

Table 3LLC Panel Unit Root Test	
LnFDIsp	LnIMsp	LnGPR	LnGTL	LnMark	LnIPRP	LnEG	LnIC	Urb	Ind	
−3.88***	−4.22***	−6.31***	−6.18***	−3.46***	−3.46***	−4.45***	−9.48***	−5.28***	−3.32***	
(0.000)	(0.000)	(0.000)	(0.000)	(0.000)	(0.000)	(0.000)	(0.000)	(0.000)	(0.000)	
Note: P-values in parentheses; *, **, and *** represent the significance level at 10 %, 5 %, and 1 %, respectively.

5 Findings and discussion

5.1 Baseline results

Columns 1 and 2 of Table 4 include only GPR as an independent variable, while Columns 3 and 4 incorporate all control variables. The results of the Hausman test indicate the necessity of using a fixed effects model for our analysis. Additionally, the maximum variance inflation factor (VIF) value for the baseline regression models is 2.90, suggesting that there is no severe multicollinearity in our regression. The results in Columns 3 and 4 of Table 4 show that the coefficients for GPR are −3.713 and −3.436, respectively, and are significant at the 1 % level. This implies that a 1 % increase in GPR reduces green technology spillover from FDI and IM by 3.713 % and 3.436 %, respectively. Therefore, increased GPR significantly inhibits green technology spillover from FDI and IM, validating Hypothesis 1.Table 4 Baseline results.

Table 4	(1)	(2)	(3)	(4)	
FDIsp	IMsp	FDIsp	IMsp	
LnGPR	−1.070***	−1.530***	−3.713**	−3.436**	
(0.207)	(0.114)	(1.516)	(1.062)	
LnEG			1.043	0.877	
		(0.884)	(0.663)	
LnIC			0.754*	0.493**	
		(0.371)	(0.172)	
Urb			1.362	0.794	
		(1.278)	(0.748)	
Ind			0.236	0.0889	
		(0.218)	(0.0776)	
Constant	−3.520***	−4.887***	−10.69**	−10.25**	
(0.081)	(0.044)	(4.093)	(3.059)	
VIF			2.90	2.90	
Hausman teat			330.1***	166.7***	
		[0.000]	[0.000]	
Cross-section fixed	Yes	Yes	Yes	Yes	
Period fixed	Yes	Yes	Yes	Yes	
N	510	510	510	510	
Adj. R2	0.461	0.776	0.506	0.807	
Note: Standard errors in parentheses; P-values in square brackets; *, **, and *** represent the significance level at 10 %, 5 %, and 1 %, respectively.

This inhibition may be attributed to several factors: In the face of high GPR, businesses may reduce or delay investments in countries with political instability, policy changes, or legal environment uncertainties. Given that FDI is an important channel for green technology spillover, such reductions directly impact the host country's opportunity to acquire advanced green technologies. Moreover, existing research indicates that regions with higher GPR often attract less high-tech investment, particularly in green technology [78,79]. Regarding import trade, GPR also leads to a reduction in international green technology spillover. High risks may cause increased trade barriers, rising trade costs, and supply chain instability, thereby reducing the international flow of green technology products and services. This not only limits the host country's ability to acquire advanced international technology through imports but also affects its competitiveness in the global green market [[80], [81], [82]]. In summary, the results indicate that increased GPR significantly inhibits the spillover of green technology through both FDI and import channels. This is due to reduced investments and increased trade barriers, which limit the host country's access to advanced green technologies and its competitiveness in the global market.

The R-square value in column 3 of Table 4 is 0.506. This relatively moderate R-square value may be due to several factors. Firstly, the complexity and multifaceted nature of GPR and their impacts on green technology spillovers mean that not all influential variables are captured in the model. Additionally, the unique regional characteristics and varying levels of technological adoption across different provinces in China contribute to the unexplained variance. While the R-square value provides a measure of the model's explanatory power, it is essential to consider it in conjunction with other model diagnostics and robustness checks to ensure the validity and reliability of the findings. Therefore, this paper conducted a series of robustness tests and heterogeneity analyses to enhance the study's credibility.

5.2 Robustness tests

We employed the following methods for robustness checks:(1) Following Gozgor et al. [83], we conducted a robustness check by lagging the GPR data by one period. The results are shown in Columns 1 and 2 of Table 5.Table 5 Robustness test results.

Table 5	(1)	(2)	(3)	(4)	
FDIsp	IMsp	FDIsp	IMsp	
L. LnGPR	−3.039**	−2.746**			
(1.331)	(0.882)			
LnGPRH			−4.791**	−4.434**	
		(1.956)	(1.370)	
LnEG	1.020	1.089	1.043	0.877	
(0.957)	(0.698)	(0.884)	(0.663)	
LnIC	0.734**	0.585**	0.754*	0.493**	
(0.326)	(0.176)	(0.371)	(0.172)	
Urb	1.351	0.319	1.362	0.794	
(1.287)	(0.813)	(1.278)	(0.748)	
Ind	0.235	0.0719	0.236	0.0889	
(0.219)	(0.0840)	(0.218)	(0.0776)	
Constant	−10.28**	−10.69**	−11.82**	−11.30**	
(4.235)	(3.056)	(4.543)	(3.378)	
Cross-section fixed	Yes	Yes	Yes	Yes	
Period fixed	Yes	Yes	Yes	Yes	
N	480	480	510	510	
Adj. R2	0.495	0.756	0.506	0.807	
Note: Standard errors in parentheses; *, **, and *** represent the significance level at 10 %, 5 %, and 1 %, respectively.

(2) In addition to the GPR data we used, the EPU Database also provides GPR Historical (GPRH) data. We replaced the original GPR data with GPRH data for a robustness check. The results are shown in Columns 3 and 4 of Table 5.

(3) We analyzed the issue using the 2SLS method to alleviate endogeneity concerns. Following Jia et al. [84], we used the change in the number of diplomatic visits by high-level Chinese officials (Dvisit) as an instrumental variable for GPR. Data on the changes in the number of diplomatic visits by high-level Chinese officials were sourced from the “China Foreign Affairs Yearbook.” We divided the annual number of visits by 100 to obtain the Dvisit data. The results are shown in Columns 1 and 2 of Table 6.Table 6 Endogeneity test.

Table 6	(1)	(2)	(3)	(4)	
FDIsp	IMsp	FDIsp	IMsp	
L. FDIsp			0.206***		
		(0.059)		
L. IMsp				0.397**	
			(0.201)	
LnGPR	−3.360**	−3.138***	−0.948***	−0.707**	
(1.312)	(0.904)	(0.142)	(0.263)	
LnEG	1.043	0.877	0.974***	0.732**	
(0.884)	(0.663)	(0.135)	(0.308)	
LnIC	0.754**	0.493**	0.300	0.550**	
(0.371)	(0.172)	(0.202)	(0.205)	
Urb	1.362	0.794	0.956**	1.037**	
(1.278)	(0.748)	(0.398)	(0.402)	
Ind	0.236	0.0889	0.019	0.120**	
(0.218)	(0.0776)	(0.048)	(0.054)	
Constant	−10.48**	−10.07***	−7.931***	−7.643**	
(3.972)	(2.965)	(0.640)	(2.620)	
AR (1)			0.075	0.071	
AR (2)			0.799	0.702	
Hansen			0.207	0.121	
N	510	510	480	480	
Note: Standard errors in parentheses; *, **, and *** represent the significance level at 10 %, 5 %, and 1 %, respectively.

(4) The field of green technology is rapidly evolving, with new technologies and innovations emerging continuously. Thus, the sources, nature, and applications of green technology change over time, and the patterns and effects of technology spillover may also shift. To account for these dynamic changes, we added the lagged term of the dependent variable as an explanatory variable to our baseline model and re-estimated it using the System GMM method to enhance the robustness of our research results. The results are shown in Columns 3 and 4 of Table 6.

The results in Table 5 indicate that the coefficients of GPR are significantly negative both when GPR is lagged by one period and when GPR data is replaced, consistent with the baseline regression results. Furthermore, the coefficients of GPR remain significantly negative in Columns 1–4 of Table 6. Additionally, in the regression results of Columns 3–4 of Table 6, AR(1) < 0.1, AR(2) > 0.1, and the Hansen J test values are 0.207 and 0.121, respectively, indicating the effectiveness of our System GMM regression. Therefore, our model does not suffer from serious endogeneity issues, and the results are relatively robust.

5.3 Moderating effect analysis

Table 7 reports the empirical analysis results of the moderating effects. Except for the insignificant impact of the interaction term of IPRP on IMsp, the coefficients of the interaction terms of GTL, Mark, and IPRP are all significantly positive. This suggests that improvements in local GTL, Mark, and IPRP mitigate the negative effects of GPR on green technology spillover, thereby validating H2, H3, H4. There are several possible reasons for these findings:(1) Advanced green technologies can attract international corporate investments, especially from companies seeking sustainable development and environmentally friendly technologies. Even in the presence of GPR, technological leadership can be a key factor in attracting external resources [85].

(2) A marketized environment promotes international business and technological cooperation. Even under tense political relations, a robust market can maintain and attract international investments and technological collaborations [86,87].

(3) Strengthened intellectual property rights protection enhances investors' confidence in the local market, particularly in technology-intensive fields. This confidence fosters FDI and technological cooperation, facilitating the introduction and spillover of green technologies [88].

Table 7 Moderating effect results.

Table 7	(1)	(2)	(3)	(4)	(5)	(6)	
FDIsp	FDIsp	FDIsp	IMsp	IMsp	IMsp	
LnGPR	−4.388**	−4.356**	−2.490**	−4.025**	−4.031**	−1.604**	
(1.706)	(1.700)	(1.069)	(1.158)	(1.170)	(0.538)	
LnGPR × LnGTL	0.310**			0.124*			
(0.126)			(0.061)			
LnGPR × LnMark		0.703**			0.334**		
	(0.266)			(0.152)		
LnGPR × LnIPRP			0.902*			0.165	
		(0.457)			(0.225)	
LnGTL	−0.176			0.035			
(0.242)			(0.094)			
LnMark		0.281			0.314**		
	(0.239)			(0.135)		
LnIPRP			0.132			0.032	
		(0.298)			(0.185)	
Constant	27.00	24.09	39.89	18.88	15.20	36.83*	
(21.05)	(20.85)	(31.55)	(16.86)	(17.25)	(19.12)	
Control variables	Yes	Yes	Yes	Yes	Yes	Yes	
Cross-section fixed	Yes	Yes	Yes	Yes	Yes	Yes	
Period fixed	Yes	Yes	Yes	Yes	Yes	Yes	
N	510	510	390	510	510	390	
Adj. R2	0.518	0.513	0.490	0.802	0.808	0.536	
Note: Standard errors in parentheses; *, **, and *** represent the significance level at 10 %, 5 %, and 1 %, respectively.

In summary, improvements in GTL, the Mark level, and IPRP alleviate the adverse impact of GPR on green technology spillover through their respective mechanisms. These factors work together not only to enhance the local capacity for technology absorption and application but also to strengthen resilience and attractiveness in the face of external political uncertainties. Therefore, they are important strategies for mitigating the impact of GPR and promoting the international spillover of green technology.

5.4 Heterogeneity analysis

Table 8 reports the results of the heterogeneity analysis. Columns 1–2 present the regression results for the eastern region, Columns 3–4 for the central region, and Columns 5–6 for the western region. The results indicate that in the eastern region, green technology spillovers through both FDI and IM channels are significantly negatively impacted by GPR. In the central region, GPR has a significant negative effect on IMsp. In the western region, GPR significantly negatively affects FDIsp. Several possible reasons explain these findings:(1) Eastern China generally has higher economic openness and closer international connections. When GPR rises, international investors and trading partners may reduce investment and technology transfer due to increased risks, significantly affecting green technology spillovers. Additionally, the eastern region has many industrial agglomerations and high-tech industries, which are highly competitive and dependent on foreign high-tech. Therefore, the increase in GPR may lead to increased barriers to international cooperation, affecting the introduction and innovation of green technologies [89].

(2) Although the central region is gradually opening up and developing, its degree of internationalization and technology absorption capacity may be relatively low compared to the eastern region. In this case, the rise in GPR may primarily reduce the spillover of green technology by affecting the import channel. Compared with FDI, imports may be the more important medium for introducing technology. Additionally, as the Chinese government promotes industrial transfer and balanced regional development policies, the central region may rely more on policy support to attract technology and capital. This dependence may make green technology spillovers from import channels more susceptible to rising GPR [90].

(3) The infrastructure and industrial base in the western region are not as developed as in the eastern and central regions, making FDI in the region more sensitive to GPR, as foreign investors may have higher requirements for the stability and risks of the investment environment. Furthermore, the western region may have more difficulty attracting and sustaining FDI due to its geographical location and relatively weak policy environment, especially as GPR rises. Lower levels of marketization and IPRP may also exacerbate this effect [91].

Table 8 Heterogeneity regression results.

Table 8	(1)	(2)	(3)	(4)	(5)	(6)	
FDIsp	IMsp	FDIsp	IMsp	FDIsp	IMsp	
LnGPR	−4.608**	−2.562**	−2.072	−4.746**	−6.673*	−4.017	
(1.968)	(0.713)	(1.873)	(1.113)	(3.336)	(2.755)	
LnEG	1.771	0.218	0.326	1.351	1.280	1.866	
(1.429)	(0.382)	(0.911)	(0.763)	(1.352)	(2.052)	
LnIC	0.206	0.397	−0.387	−0.088	0.874	0.675*	
(0.367)	(0.283)	(0.347)	(0.344)	(0.541)	(0.370)	
Urb	−0.060	0.261	3.973**	2.696**	5.323*	−0.894	
(1.547)	(0.773)	(1.444)	(0.548)	(2.873)	(2.392)	
Ind	0.206**	0.102	−0.188	0.201	0.790	0.071	
(0.085)	(0.069)	(0.363)	(0.284)	(0.605)	(0.245)	
Constant	−12.10*	−6.419**	−6.158	−12.96**	−15.54*	−13.69	
(6.353)	(2.124)	(4.517)	(3.112)	(7.350)	(7.904)	
Cross-section fixed	Yes	Yes	Yes	Yes	Yes	Yes	
Period fixed	Yes	Yes	Yes	Yes	Yes	Yes	
N	187	187	119	119	204	204	
Adj. R2	0.784	0.945	0.394	0.841	0.517	0.662	
Note: Standard errors in parentheses; *, **, and *** represent the significance level at 10 %, 5 %, and 1 %, respectively.

5.5 Further analysis

Since the 1980s, the academic community has used empirical analysis to delve deeper into the interrelationship between FDI and international trade. Bhagwati et al. [92] examined the dynamics between trade and FDI from a political-economic perspective, noting that interactions among different interest groups could lead to either substitutive or complementary effects between FDI and international trade. Subsequently, scholars like Pfaffermayr [93] and Jun & Singh (1996) [99] applied the Granger causality model to test the relationship between international trade and FDI in major global investment recipient countries. The results showed that in most countries, there is indeed a causal link between international trade and FDI. Building on these findings, this study further analyzes the potential for substitutive or complementary effects between green technology spillover through FDI and IM channels.

The results in Table 9 indicate a complementary effect between FDIsp and IMsp. This can be understood from several perspectives. First, FDI typically brings direct knowledge and technology transfer, including management skills, production processes, and green innovation technologies. At the same time, imports provide advanced machinery, equipment, raw materials, and potentially embedded technology and knowledge. Therefore, these two channels together offer host countries a richer and more diverse range of knowledge and technological resources, fostering local enterprise learning and technology absorption [94,95]. Second, FDI often involves the production and R&D activities of multinational corporations in the host country, which can promote the development of local supply and industry chains [96,97]. Technology spillover through imports provides these supply chains with high-quality inputs and advanced technologies. Consequently, the interaction of these two elements jointly drives the technological upgrading and green development of the entire industry chain. Third, the entry of FDI can stimulate market competition, forcing local enterprises to enhance efficiency and technological levels. Simultaneously, technology and knowledge obtained through imports can help local businesses respond more quickly to such competitive pressures, achieving technological upgrading and innovation [98]. Thus, the mutual reinforcement of these factors collectively enhances the host country's overall market efficiency and technological innovation capacity.Table 9 Further analysis results.

Table 9	(1)	(2)	
IMsp	FDIsp	
FDIsp	0.114**		
(0.0481)		
IMsp		0.365*	
	(0.201)	
LnEG	0.758	0.723	
(0.696)	(0.950)	
LnIC	0.407**	0.574*	
(0.191)	(0.322)	
Urb	0.638	1.072	
(0.670)	(1.104)	
Ind	0.0619	0.203	
(0.0730)	(0.194)	
Constant	−7.216**	−5.467	
(2.619)	(3.427)	
Cross-section fixed	Yes	Yes	
Period fixed	Yes	Yes	
N	510	510	
Adj. R2	0.815	0.526	
Note: Standard errors in parentheses; *, **, and *** represent the significance level at 10 %, 5 %, and 1 %, respectively.

6 Conclusions and implications

6.1 Conclusions

This study investigates the impact of GPR on the spillover of green technology through FDI and IM channels using data from 30 Chinese provinces from 2003 to 2019. The findings indicate that GPR significantly inhibits green technology spillover via both FDI and IM channels. This underscores the critical importance of political stability in fostering international technological exchanges and suggests that policymakers need to consider the geopolitical environment's potential impact on economic and technological development. Moreover, the study reveals that advancements in local green technology, marketization, and intellectual property rights protection can mitigate the adverse effects of GPR. By enhancing technological capabilities, improving market mechanisms, and strengthening legal protections, regions can partially shield themselves against external political risks, thus maintaining the stability and efficiency of technology spillovers. Additionally, the research highlights regional variations in the impact of GPR on green technology spillover, which may be due to differences in economic development levels, industrial structures, openness, and policy environments across regions. This insight suggests that policymakers should tailor their strategies to regional characteristics to develop more precise and effective measures.

6.2 Implications and suggestions

Based on our findings, we propose the following recommendations. Firstly, advancements in green technology are a crucial pathway to sustainable development, and both governments and businesses should give ample importance to the significant role of GPR in international green technology spillover. Therefore, strengthening the management and early warning of GPR is essential. Secondly, enhancing green technology innovation capabilities, optimizing market environments, and strengthening intellectual property protection are vital strategies to mitigate GPR, foster technology spillover, and achieve green development. Additionally, the complementary nature of FDI and import technology spillover should be fully recognized, comprehensively utilizing different channels to promote technological progress and green development. Lastly, given the regional variance in the impact of GPR, policy formulation should consider regional characteristics, crafting more precise and effective measures.

6.3 Limitations and future recommendations

This study has several limitations that need to be acknowledged. Firstly, the research focuses solely on China, which may limit the generalizability of the findings to other countries or regions. Additionally, methodologically, while the econometric models used are robust, they have limitations in capturing complex causal relationships and potential endogeneity issues. Furthermore, the study does not differentiate between various sectors, which might experience different impacts from GPR.

Future research should include a broader range of countries to test the generalizability of the findings. Additionally, employing advanced econometric techniques could better address potential endogeneity issues and uncover more complex relationships. Finally, conducting sector-specific studies will allow for a more detailed understanding of how different industries are impacted by geopolitical risks, helping in designing targeted policies and strategies.

Data availability statement

Data will be made available on request.

Institutional review board statement

Not applicable.

Informed consent statement

Not applicable.

Funding

This study was supported by Key Laboratory of Automotive Power Train and Electronics (10.13039/501100004499 Hubei University of Automotive Technology ), (No. ZDK12023B02 ).

CRediT authorship contribution statement

Pengfei Cheng: Writing – original draft. Kanyong Li: Formal analysis, Conceptualization. Baekryul Choi: Methodology, Funding acquisition. Xiao Guo: Data curation. Mengzhen Wang: Writing – review & editing, Supervision.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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